Despite enormous expenditures and innovations in treatment, the United States health care system does not consistently deliver effective treatment to individuals with serious mental illnesses. Health care reform promises to make insurance benefits newly available to many, eliminate inequitable treatment limits and financial requirements, and promote integrated primary and behavioral health care. Quality measures can help achieve the full promise of these reforms by providing feedback to payors and providers and enabling greater transparency and accountability.
The purpose of this project was to identify, specify, and test at least three measures that address pharmacological treatment, psychosocial treatment, and physical health needs for individuals with schizophrenia that can be calculated solely from Medicaid claims data. The psychosocial treatment measure was dropped because procedure codes used in claims data are ambiguous, lacking sufficient detail to reflect the actual service provided and these codes are not used consistently in different states and programs. Ten measures were pilot tested using MAX data. They address the following concepts: use of antipsychotic medications, antipsychotic medication possession ratio, diabetes screening, diabetes monitoring cardiovascular health screening, cardiovascular health monitoring cervical cancer screening, emergency department utilization for mental health conditions, and follow-up after mental health hospitalization within seven days and within 30 days. [149 PDF pages]
"Acronyms
ACT | assertive community treatment |
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APA | American Psychiatric Association |
ASPE | Office of the Assistant Secretary for Planning and Evaluation |
BHO | behavioral healthcare organization |
BMI | body mass index |
CMS | Centers for Medicare and Medicaid Services |
DHHS | New Hampshire Department of Health and Human Services |
ED | emergency department |
EHR | electronic health record |
FFS | fee-for-service |
FUH | follow-up after hospitalization |
HCPCS | Healthcare Common Procedure Coding System |
HbA1c | Hemoglobin A1c |
HMO | health maintenance organization |
ICSI | Institute for Clinical Systems Improvement |
IQR | interquartile range |
LAI | long-acting injectable |
MAX | Medicaid Analytic eXtract |
MBHO | managed behavioral healthcare organization |
MMDLN | Medicaid Medical Directors Learning Network |
NACBHDD | National Association of County Behavioral Health and Developmental Disability Directors |
NAMI | National Alliance on Mental Illness |
NCQA | National Committee for Quality Assurance |
NICE | National Institute for Health and Clinical Excellence |
NQF | National Quality Forum |
PCP | primary care provider |
PDC | proportion of days covered |
PORT | Patient Outcomes Research Team |
RCT | randomized controlled trial |
SMI | serious mental illness |
SPMI | serious and persistent mental illness |
TAG | Technical Advisory Group |
WFBH | Wake Forest Baptist Health |
Executive Summary
In August 2010, the U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation (ASPE) contracted with Mathematica Policy Research and its subcontractor--the National Committee for Quality Assurance--to develop evidence-based quality measures to assess the quality of care provided to Medicaid enrollees diagnosed with schizophrenia. The goal of the project was to create a set of claims-based ambulatory care measures that meet National Quality Forum (NQF) criteria for importance, scientific acceptability, usability, and feasibility and would thus be suitable for submission to the NQF for endorsement consideration.
The project began with a review of existing literature and other evidence describing evidence-based practices for people with schizophrenia. Assisted by expert consultants, this effort emphasized the findings of the Schizophrenia Patient Outcomes Research Team and allowed the team to create concepts for new measures that assess the quality of medication management, underuse of evidence-based psychosocial treatments, and access to primary care and preventive health services. Once the measure concepts were vetted by a Technical Advisory Group (TAG), we developed draft specifications and sought comment from measure stakeholders, including representatives from managed behavioral healthcare organizations (MBHOs), Medicaid medical directors, and state mental health directors to assess their perspectives on the importance, scientific acceptability, usability, and feasibility of the proposed measures. After these key stakeholders gave their input, measure specifications were posted for public comment, and they were pilot-tested using Medicaid Analytic eXtract (MAX) data from 2007 and 2008 to further assess their feasibility, reliability, and validity. Throughout the project, the project team received valuable advice and guidance from ASPE, members of the TAG, and our project consultants.
The project team sought to develop measures in three domains, pharmacology, psychosocial care, and physical health, as well as cross-cutting measures that span several of these domains. Based on the review of the literature and feedback from the TAG and ASPE, we developed detailed specifications for an initial set of 17 measure concepts before settling on a final set of ten to be submitted to NQF for endorsement.
Focus groups with state Medicaid and mental health leaders, as well as with MBHO staff, yielded remarkably consistent results. Key points included: (1) claims data are unreliable for identifying some behavioral health services, particularly evidence-based psychosocial treatments; (2) variation in financing of services for people with serious mental illness (SMI) limits the ability to consistently measure the quality of care across Medicaid programs; and (3) some candidate measures address problems that are not unique to patients with schizophrenia--measures could be broadened to include patients with bipolar disorder, schizophrenia, and severe forms of depression. The feedback from public comment was positive, with 87 percent of the comments either supporting the measures or supporting them with modifications.
Overall, 9.7 percent of Medicaid recipients in our 22-state 2007 MAX dataset had schizophrenia and 12.8 percent had SMI (bipolar disorder and/or schizophrenia). The objective of pilot-testing was to determine the scientific acceptability of each measure to the extent practicable through the use of Medicaid claims data. Five of the ten proposed measures demonstrated significant variability in state-level performance, indicating general utility of the measures. Seven of the ten proposed measures demonstrated evidence of either construct or convergent validity. Construct validity was assessed by examining the association between measure performance and outcomes (schizophrenia-related (1) hospitalization, and (2) emergency department [ED] visits). We reported the percentage of people who were either hospitalized or visited the ED for schizophrenia, comparing the worst and best-performing quartiles of state performance for each measure. Seven measures demonstrated evidence of construct validity, indicated by the association between (higher) measure performance and (lower) rates of adverse events. Convergent validity was determined through enrollee-level measure correlations. Three of the ten measures demonstrated evidence of convergent validity. Nine of the ten measures demonstrated evidence of reliability, assessed between measures calculated during calendar year 2007 and 2008, either through test-retest correlations or relative performance stability over this time period.
Although some of these results are encouraging, important limitations of our findings warrant consideration. First, use of Medicaid claims data as a source to implement and test schizophrenia quality measures limited the number of evidence-based practices that could be implemented as measures. This limitation prevented our ability to develop psychosocial measures. In addition, several topics could not be developed because the evidence base, tools, and methods for tracking these measures are immature. We also found that variation in the financing of services for people with SMI limited our ability to generalize measurement of the care provided by Medicaid programs. For example, the provision of services through state mental health systems, the coverage of mental health services through Medicare for dual-eligible beneficiaries, the prohibition of same-day billing of medical and behavioral health services, and interstate variation in Medicaid and disability standards all underscore the limitations of claims data to measure quality for enrollees with schizophrenia. Finally, the distinction between enrollees with schizophrenia and other SMI conditions is, in many cases, artificial. The project team, ASPE, and measure stakeholders all expressed the belief that conceptually, many issues related to schizophrenia also apply broadly to people with any SMI. Further work is needed to consider whether measures similar to the ones developed and tested under this contract would be relevant for people with bipolar disorder and other SMI.
I. Overview of the Project
Despite enormous expenditures and remarkable breakthroughs in medical treatment, the United States behavioral health care system does not consistently deliver safe and effective treatment to those with serious and persistent mental illness (SPMI), many of whom go untreated or inadequately treated. Now, as the nation stands at the doorstep of fundamental reforms that offer insurance benefits for those without them, remove inequitable treatment limits and financial barriers to mental health treatments, and promote integrated primary and behavioral health care, we have an enormous opportunity to close the gap between the availability of effective treatments and providing them in a manner that promotes recovery. By enhancing transparency, new quality measures that promote feedback to providers and enable value-based purchasing represent an essential tool to achieve the full promise of these reforms.
In August 2010, the U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation (ASPE) contracted with Mathematica Policy Research and its subcontractor--the National Committee for Quality Assurance (NCQA)--to develop evidence-based quality measures to assess the quality of care provided to Medicaid enrollees diagnosed with schizophrenia. The goal of the project was to create a set of claims-based ambulatory care measures that meet National Quality Forum (NQF) criteria for importance, scientific acceptability, usability, and feasibility and would thus be suitable for submission to the NQF for endorsement consideration.
The project began with a review of existing literature and other evidence describing evidence-based practices for people with schizophrenia. Assisted by expert consultants, this effort emphasized the findings of the Schizophrenia Patient Outcomes Research Team (PORT) and allowed the team to create concepts for new measures that assess the quality of medication management, underuse of evidence-based psychosocial treatments, and access to primary care and preventive health services. Once the measure concepts were vetted by a Technical Advisory Group (TAG), we developed draft specifications and sought comment from measure stakeholders, including representatives from managed behavioral healthcare organizations (MBHOs), Medicaid medical directors, and state mental health directors to assess their perspectives on the importance, scientific acceptability, usability, and feasibility of the proposed measures. After these key stakeholders gave their input, measure specifications were posted for public comment, and they were pilot-tested using Medicaid Analytic eXtract (MAX) data from 2007 and 2008 to further assess their feasibility, reliability, and validity. Throughout the project, the project team received valuable advice and guidance from ASPE, members of the TAG, and our project consultants.
This report presents a chronology of the process, key findings, and lessons learned during our project to develop claims-based measures of services provided to Medicaid enrollees with schizophrenia that meet key NQF criteria. Chapter II reviews that process and describes how several findings in our data collection changed the course of measure development. Chapter III summarizes key findings from our field and pilot-testing efforts, and Chapter IV discusses lessons learned that we hope will improve the process of measure development and the quality of the resulting measures. The appendices contain all key documents produced throughout the project, including material presented at each TAG meeting, pilot-testing results, and the candidate measure summary information.
II. the Development of Schizophrenia Quality Measures: a Chronology
In developing new quality measures to assess the quality and appropriateness of care for Medicaid enrollees with schizophrenia, Mathematica and NCQA carried out the following tasks under guidance from ASPE:
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Identified appropriate measure topics and concepts through an environmental scan and a review of the literature.
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Defined and developed measure specifications.
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Convened meetings of the project TAG.
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Field-tested measures with key stakeholders.
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Posted the measures for public comment.
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Pilot-tested measures and evaluated the reliability and validity of measures using Medicaid claims data.
1. Environmental Scan: Identify Appropriate Measure Topics and Concepts
The process for identifying the measure concepts included a review of the clinical literature prepared by ASPE, an environmental scan of treatment measure guidelines and existing measures by NCQA, and consultation with experts. We focused on measure concepts in three treatment domains specified by ASPE: pharmacotherapy, psychosocial treatment, and physical health. Drs. Julie Kreyenbuhl and Lisa Dixon, leaders of the Schizophrenia PORT at the University of Maryland School of Medicine, served as content experts and consultants to the project. Their role was to identify potential errors of interpretation, emphasis, inclusion, or omission prior to developing a report that summarized the scientific literature, clinical guidelines, and existing measures that are focused on the population of interest.
The environmental scan identified systematic reviews (e.g., the Schizophrenia PORT reviews), measure specifications, and treatment guidelines and standards developed by professional societies and measurement organizations that relate to care for people with schizophrenia (Buchanan et al. 2010; Dixon et al. 2010). ASPE also conducted a supplemental review of the clinical literature restricted to human adult clinical trials, and in the case of pharmacologic agents, those that have advanced beyond preliminary safety and efficacy testing (Sherry 2010). Because the PORT recommendations include only studies published through March 2008, the ASPE literature review identified more recent studies. In addition, we consulted with a multistakeholder TAG. To identify existing measures assessing care for people with schizophrenia, we searched measure databases from the NQF, the National Quality Measures Clearinghouse, the National Registry of Evidence-Based Programs and Practices through the Substance Abuse and Mental Health Services Administration, and the Center for Quality Assessment and Improvement in Mental Health. Measures were organized by the measure steward, name, description, numerator, denominator, data source, and measurement domain (that is, physical health, pharmacotherapy, and psychosocial interventions). The final measure concepts are presented in Chapter III.
2. Define and Develop Initial Measure Specifications
Based on the review of the literature and feedback from the TAG and ASPE, we developed detailed specifications for an initial set of 17 measure concepts before settling on a final set of ten to be submitted to NQF for endorsement. Initial measure specifications included codes likely to be found on claims and that define populations eligible to be in the denominator, codes that adequately defined the nature of the processes or outcomes to be assessed (the numerator), and the appropriate time frames for assessment. We used the input of the TAG and our understanding of the MAX data to guide drafting measure specifications. Appendix A lists the original 17 measure concepts.
3. Convene Meetings of the Project Technical Advisory Group
To guide the measure development process and provide the perspectives of all stakeholders, we convened three meetings of a multistakeholder TAG. This group included 16 members representing expertise in clinical care, research, state and federal policy, consumers, managed behavioral health care, and quality measurement. The TAG met three times by teleconference through the course of the project. During the first teleconference, we asked TAG members to review proposed measure concepts, identify potential gaps in these concepts, assess measure development priorities, and recommend measures to be specified and tested. Measure specifications and the testing plan for the selected concepts were then reviewed during the second TAG meeting. The third meeting consisted of reviewing the preliminary results of the field and pilot-testing. In addition, the TAG evaluated and provided further feedback on the specifications and recommended measures for NQF submission. Appendix B lists the TAG members and includes material presented at each TAG meeting.
4. Field-Test Measure Specifications with Key Stakeholders
To inform our understanding of feasibility and usability, we conducted focus groups with: (1) State Medicaid Medical Directors; (2) representatives from MBHOs; and (3) State Mental Health Commissioners and Medical Directors (or their designees). The goal was to obtain feedback on attributes that are reviewed by NQF during the endorsement process, including the importance, usability, and feasibility of the measures. We asked focus group participants about their understanding of the measure specifications; the feasibility of implementing quality data for the measures through a claims-based system, including anticipated operational challenges in collecting and reporting the data; the relevance and importance of the measures to their program or organization; their interest in collecting information and receiving feedback on the measures; and any suggestions for refining the measures.
Focus group testing with the State Medicaid Medical Directors occurred in conjunction with the Medicaid Medical Directors Learning Network meeting in Washington, DC, and 28 states were represented. Representatives of MBHOs were recruited from industry lists; individuals representing commercial and Medicaid plans in six states (Florida, Oklahoma, Pennsylvania, Illinois, Missouri, and Iowa) participated. We later added a focus group of state mental health commissioners and medical directors in response to suggestions from ASPE; officials from five states (California, Michigan, Missouri, Georgia, and Florida) participated. A memo summarizing our conversations with the focus groups is in Appendix C.
5. Post Measure Specifications for Public Comment
For this task, NCQA developed and managed a dedicated web page to receive public comments. Candidate measures (excluding the HIV screening and psychosocial treatment measures) were posted September 15, 2011, through October 15, 2011, and included draft technical specifications, instructions, and supporting information for the public-comment period. We collated the public comments and reviewed them to identify themes and areas of concern. We then prepared a document summarizing the comments and action taken (Appendix D). Twenty-two organizations, including academic institutions, health plans, pharmaceutical companies, universities, and other health care associations, submitted a total of 67 comments.
6. Pilot-Test Measures to Assess Usability, Validity, and Reliability
To assess the usability and scientific acceptability of the measures, we examined the distribution, content and convergent validity, and test-retest reliability of the candidate measures using MAX data from 2007 and 2008. Use of MAX data permits real-world assessment of measure usability for state Medicaid officials. At the same time, operationalization of quality measures in Medicaid claims data provides an opportunity to retrospectively assess measure validity by correlating measure performance with outcomes such as schizophrenia-related hospitalization and emergency department (ED) use. The MAX data are standardized eligibility and claims files for each state that include person-level on every beneficiary enrolled in Medicaid during the calendar year. The MAX files are created from claims data that each state submits to the Centers for Medicare and Medicaid Services (CMS).
Defining the Population
Diagnosis of schizophrenia was inferred by either a single primary inpatient diagnosis or two outpatient primary diagnoses of schizophrenia.1, 2 In response to comments from Medicaid medical directors, we modified and tested some measures to include persons with serious mental illness (SMI) defined by a single primary inpatient diagnosis or two outpatient primary diagnoses of either schizophrenia or bipolar disorder.
In addition, we required that enrollees have 10 months of Medicaid eligibility, non-dual status, and qualification for Medicaid on the basis of a disability, which resulted in 1,019,123 Medicaid recipients who met our inclusion criteria.3
Overall, 9.7 percent of Medicaid recipients in our dataset had schizophrenia and 12.8 percent had SMI (bipolar disorder and/or schizophrenia) in 2007. Both of these populations were demographically diverse (Appendix Table E.2). About one in five enrollees with schizophrenia were diagnosed with diabetes (17 percent).
Pilot-Test Methodology: Usability, Validity, and Reliability
Pilot-testing the measures using MAX data took several forms. First, we evaluated measure importance (gaps in quality) and scientific acceptability (meaningful differences in performance) by assessing the distributional properties of each measure. This was accomplished by tabulating the minimum, maximum, median, mean, and interquartile range (IQR) for each measure at the state level. The IQR is demarcated by the values at the 25th and 75th percentiles of a distribution. Generally speaking, measures with a broader IQR are preferable to measures with a narrowly distributed IQR or those with an IQR at the very low or very high end of the distribution. For example, a measure with a narrow IQR may not be sufficiently sensitive to detect differences in quality. Measures with an IQR of at least 10 percentage points were considered to have the strongest evidence of usability for quality measurement purposes.
Validity and reliability are important characteristics of measure scientific acceptability. Construct validity was evaluated by examining enrollee outcomes with results displayed by quartile of state-level performance for each measure. We compared rates of schizophrenia-related hospitalization and ED utilization, for beneficiaries in the highest and lowest performing quartile for each quality measure. The difference between the outcomes among enrollees in the best and worst quartiles of state performance for each measure was tested using a one-way analysis of variance; an F-test significance level of p<0.01 was used to determine statistically different outcomes. For a given measure, construct validity was inferred when rates for adverse events among enrollees in high performing states were significantly better (i.e., lower) than the rates of adverse events among enrollees in low performing states.
Convergent validity was examined through between-measure correlation coefficients. For example, we hypothesized that adherence to antipsychotics, as measured by a high rate of antipsychotic medication possession ratio, would be negatively associated with measures of mental health ED use and positively correlated with the measures of 30-day outpatient follow-up after a mental health related discharge. We identify measures with a Pearson correlation of at least 0.15 with two or more measures.
We assessed measure reliability using state-level test-retest correlations with data from 2007 and 2008 MAX data.4 We identify measures with a year-to-year correlation of >0.30. We also examined the stability of relative performance quartiles between 2007 and 2008, with the expectation that at the state level, performance measures should not exhibit any discernible pattern of performance instability over time. In other words, measure stability would be demonstrated if a state was in the top quartile of performance for a given measure in 2007, the same state should demonstrate similar relative performance in 2008. Results from the pilot and field-testing efforts are summarized in the next section.
III. Summary of Key Findings
The purpose of this measure development project was to identify, specify, and test at least three measures that address pharmacological treatment, psychosocial treatment, and physical health needs for patients with schizophrenia that can be calculated solely from Medicaid claims data. Ten measures met our rigorous criteria for measure development, including evidence review, consultation with the TAG, focus groups with key stakeholders, public comment, and pilot-testing using the MAX data.
Tables III.1-III.4 list the measure concepts that we considered based on the environmental scan and initial input from the TAG; these concepts addressed the domains requested by ASPE (pharmacology, psychosocial treatment, and physical health) as well as a set of cross-cutting issues identified through the scan. We did not further pursue some of these topics because we did not believe that they could be assessed in claims; these measure concepts were not presented to the TAG (see Appendix B).
Based on TAG recommendations, 13 measures were specified. Two (use of any psychosocial treatment and HIV screening) were dropped before testing in the MAX files. The psychosocial treatment measure was dropped because procedure codes used in claims data are ambiguous and thus do not provide sufficient detail to reflect the actual service provided, and because these codes are not used consistently in different states and programs. The HIV screening measure was dropped because of the lack of strong evidence suggesting a gap in care for people with schizophrenia. Based on the input received from the public comment period, we dropped the measure of general ED utilization due to provider attribution concerns, which resulted in ten measures that were later pilot-tested in the MAX data.
1. Measure Concepts Considered, Specified, and Tested, and Submitted for Endorsement
The project team sought to develop measures in three domains, pharmacology, psychosocial care, and physical health, as well as cross-cutting measures that span several of these domains. Tables III.1-III.4 list the proposed measure concepts, the measures that were specified and tested in focus groups, the measures that were tested in the MAX data, and the measures submitted for NQF endorsement. The final ten measures submitted to NQF for endorsement consideration are listed in the last column. Appendix F consists of the proposed measures' numerator, denominator, and exclusions.
TABLE III.1. Pharmacological Concepts Considered, Specified, Tested, and Submitted | |||
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Proposed Measure Concepts | Measures Specified & Tested in Focus Groups | Measures Tested in MAX Files | Measures Submitted for NQF Endorsement |
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Use of clozapine in treatment-resistant patients was dropped due to difficulty with identifying treatment-resistant patients from claims data and concerns about small denominator size. The polypharmacy treatment measure concept was dropped because there is insufficient evidence to define a polypharmacy threshold (e.g., two versus three antipsychotics) and lack of evidence regarding the impact of polypharmacy on quality of care. The TAG also was uncertain whether to broaden the concept to encompass other psychiatric medications (e.g., antidepressants).
TABLE III.2. Psychosocial Concepts Considered, Specified, Tested, and Submitted | |||
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Proposed Measure Concepts | Measures Specified & Tested in Focus Groups | Measures Tested in MAX Files | Measures Submitted for NQF Endorsement |
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| (None) | (None) |
Use of ACT post-hospitalization, case management, family therapy, supported employment, cognitive behavioral therapy, and social education were dropped as a result of the inconsistent availability of these services across state Medicaid programs and, where those services are available, unreliable coding and uncertain fidelity to the evidence-based models. Use of any psychosocial treatment was specified and tested in focus groups, but was dropped because of the fidelity and reliability concerns. Availability of and the presence or duration of a waitlist for psychosocial treatment are structural measures not suited to claims data measurement.
TABLE III.3. Physical Health Concepts Considered, Specified, Tested, and Submitted | |||
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Proposed Measure Concepts | Measures Specified & Tested in Focus Groups | Measures Tested in MAX Files | Measures Submitted for NQF Endorsement |
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Weight assessment and counseling among patients on antipsychotics was deemed identifiable only from chart data, which were out of scope for this project. Concerns about reliable documentation of tobacco and substance use screening and counseling in claims data resulted in removing these concepts from further consideration. HIV screening was dropped because of the lack of strong evidence suggesting a gap in care for people with schizophrenia.
TABLE III.4. Cross-Cutting Concepts Considered, Specified, Tested, and Submitted | |||
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Proposed Measure Concepts | Measures Specified & Tested in Focus Groups | Measures Tested in MAX Files | Measures Submitted for NQF Endorsement |
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The use of combination antipsychotic medication and psychosocial treatment measure concept was dropped due to the inability to capture psychosocial treatments reliably through claims data.
2. Field-Testing
The focus groups with state Medicaid and mental health leaders, as well as with MBHO staff, yielded remarkably consistent results. Key points included:
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Claims data are unreliable for identifying some behavioral health services, particularly evidence-based psychosocial treatments.
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Variation in financing of services for people with SMI limits the ability to consistently measure the quality of care across Medicaid programs. For example, while some states reimburse for a bundled set of services collectively known as assertive community treatment (ACT), other states reimburse individual services that resemble services included in the ACT model. In other states, some of these services are provided outside of the Medicaid program, such as through the state mental health authority.
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Some candidate measures address problems that are not unique to patients with schizophrenia; measures could be broadened to include patients with bipolar disorder, schizophrenia, and severe forms of depression (SPMI).
While focus group participants generally viewed the proposed measure concepts as important and relevant topics, they noted some gaps. In particular, Medicaid officials raised concerns about the lack of candidate measures addressing perceived problems of overuse of care for people with schizophrenia (for example, polypharmacy or hospital readmissions).
The panels offered specific advice on technical specifications and testing. In particular, they recommended that the measures apply to patients not included in MAX files, specifically TANF enrollees and people with dual Medicare beneficiaries, who receive treatment through Medicaid programs.
3. Public Comment
The feedback from public comment was positive, with 87 percent of the comments either supporting the measures or supporting them with modifications (Appendix D). The majority of the comments touched on issues that had been discussed by the project team and the TAG during the measure development process, such as expanding the denominator in the physical health screening measures to include anyone with SMI, including measures evaluating psychosocial care, and lowering the age of eligibility for the measures.
Some comments raised concerns about the accountability for measures; for example, several commenters expressed concern that offering cervical cancer screening was out of scope for psychiatrists and psychologists. The project team believes this is a misunderstanding on the part of providers. The state, not the provider, is the unit of accountability for these measures. Further, given the push toward integrated care, states may be held accountable for the coordination of care between medical and mental health settings. This may include encouraging mental health professionals, including psychiatrists, to inquire about these services and potentially refer for such services. This is no different from the expectation that psychiatrists address the metabolic condition of patients in their care. Therefore, we propose retaining screening measures.
We received technical comments concerning coding of medication lists, including HbA1c tests as part of the diabetes screening measure, and methods to determine use of injectable antipsychotic medications. The project team carefully considered these concerns when finalizing measure specifications.
The measure that received the least support from public comment was Emergency Department Utilization for People with Schizophrenia. Feedback centered on the measure being non-action-oriented because it included non-mental health admissions. Comments also focused on the measure possibly encouraging overuse of emergency servces. Based on this feedback, the broad measure of Emergency Department Utilization was not submitted for NQF endorsement.
4. Pilot-Testing
The objective of pilot-testing was to determine the scientific acceptability of the measures based on NQF criteria. Table III.5, summarizes the evidence found for each measure through our pilot-testing activities using our 22-state MAX dataset (2007) and our 16-state MAX dataset (2008). Cells containing an 'X' indicate that a measure met predetermined criteria, summarized in Chapter II, which we used to assess differences in performance across states, validity, or reliability. An empty cell indicates that a measure did not meet the criterion in the corresponding column; however, as we discuss in the paragraphs that follow, this does not indicate a measure is without merit or should not be considered useful. In general, as we described below in further detail, caution is warranted in interpreting our pilot-testing findings, as testing results using Medicaid claims should not be used as the sole criteria for judging the merit of the measures.
TABLE III.5. Summary of Pilot-Testing Results: Evidence of Measure Usability, Validity, and Reliability | |||||
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Measure | Detection of Meaningful Differences | Validity | Reliability | ||
IQR Dispersiona | Construct Validityb | Convergent Validityc | Test-Retest Correlationd | Performance Stabilitye | |
Use of Antipsychotic Medication | X | ||||
Antipsychotic Possession Ratio (>80%) | X | ||||
Diabetes Screening (SMI)f | X | X | X | X | X |
Diabetes Monitoring | X | X | X | X | X |
Cardiovascular Health Screening (SMI)f | X | X | |||
Cardiovascular Health Monitoring | X | X | X | X | |
Cervical Cancer Screening | X | X | |||
ED Utilization for Mental Health Conditions | N/A | X | |||
Follow-up after Mental Health Hospital Discharge (7-day) | X | X | X | ||
Follow-up after Mental Health Hospital Discharge (30-day) | X | X | X | X | |
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Five of the ten proposed measures demonstrated significant variability in state-level performance. A key indicator of a quality measure's utility is its ability to capture a wide range of performance. Appendix Table E.13 lists each measure and its distribution across the 22-state dataset. Table III.5 identifies the four measures with an IQR of at least 10 percentage points and those where the lower and upper bounds of the IQR did not encompass the tails of performance (either low or high), indicating measures with the greatest utility for quality measurement purposes.
The measure "Use of Antipsychotic Medication" had the most restricted performance range (an IQR of 3 percentage points). For example, a state performing at the lower end of the IQR (that is, the 25th percentile), reported 92 percent of recipients received an antipsychotic, while a state at the top end of the IQR (the 75th percentile) reported 95 percent of recipients received an antipsychotic. Therefore, we believe that this measure has limited value from a quality improvement perspective, since the performance range is restricted and is already near the top, thus limiting the potential for improvement. However, because antipsychotic use is a fundamental issue for this population and the measure was widely endorsed by our consultants (the TAG and stakeholder groups), "use of antipsychotic medication" has considerable utility as a monitoring measure.
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Seven of the ten proposed measures demonstrated evidence of validity. We assessed validity using two approaches. To assess construct validity we examined the association between measure performance and outcomes (schizophrenia-related hospitalization and ED visits). We compared the percentage of people who hospitalized or visited the ED for schizophrenia, comparing the worst and best-performing quartiles of state performance for each measure. For example, we found enrollees in states with the highest rates of antipsychotic use had significantly lower rates of hospitalization for schizophrenia compared with enrollees in states with the lowest rates of antipsychotic use (Appendix Table E.14). Seven measures demonstrated evidence of construct validity.
Convergent validity was determined through examination of recipient-level measure correlations (Appendix Table E.15). We considered measures with a correlation coefficient of 0.15 or greater with at least two other measures to demonstrate evidence of convergent validity. Three of the ten measures met this criterion.
Although some of these results are encouraging, some important limitations of these measures warrant consideration. Our measures of schizophrenia-related hospitalization and schizophrenia-related ED visits assess adverse outcomes at one extreme of care and thus do not reflect the full spectrum of care. Further, measures that assess preventive care processes were not anticipated to have a significant effect on schizophrenia-related hospitalization or ED use, therefore this relationship warrants further investigation to understand this finding.
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Nine of the ten measures demonstrated evidence of reliability. Reliability was assessed through correlation of state-level 2007 and 2008 performance. Seven of the ten measures demonstrated 2007-2008 correlation of 0.30 or higher at the state level (Appendix Table E.16). In addition, we compared each state's performance quartile in 2007 with its performance quartile in 2008 to understand the stability of each measure. We defined stability as no more than a one-quartile performance difference between 2007 and 2008; six measures met this criterion (Table III.5). Only "Use of Antipsychotic Medications" failed to show a strong state-level year-to-year correlation (r=0.25) and showed a large performance difference (a three-quartile change) between 2007 and 2008, although this difference was observed in a single, small state.
In summary, we began with a list of 23 measure concepts to assess the care provided to Medicaid enrollees with schizophrenia, and arrived at a final list of ten measures for submission to NQF. These measures fall into three domains, pharmacological, physical health measures and cross-cutting measures. Current evidence and limitations of claims data prevented us from developing robust measures of psychosocial treatments. Appendix F details the numerator, denominator and exclusions for each of the ten proposed measures.
IV. Lessons Learned
While we successfully developed and tested ten quality measures, development of several additional measures was not feasible given the constraints of Medicaid claims data and Medicaid payment policies. The following discussion of our experience and lessons learned is designed to be instructive for future efforts in the development of quality measures for people with SPMI.
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Use of Medicaid claims data as a source to implement and test schizophrenia quality measures presented several noteworthy limitations. Because of the limitations of the claims data, several evidence-based practices could not be implemented as measures. These limitations were particularly conspicuous when attempting to operationalize evidence-based guidelines for psychosocial treatments such as those recommended in the Schizophrenia PORT. In analyses using MAX data, we found psychosocial treatments are either inconsistently coded in claims data or not available at all. For example, claims for smoking cessation programs were not observed in the MAX data; therefore, this measure was not developed because it could not be assessed in claims data. Consequently, no psychosocial measures emerged from our measure development process, despite the strength of evidence for these practices. Specific evidence-based recommendations that could not be accurately identified in the claims data, and thus were not field or pilot-tested, included:
- Supported employment;
- Family psychoeducation;
- Assertive community-based treatment;
- Cognitive behavioral therapy;
- Social skills training.
Claims-only assessment presents other challenges for measure development. Because mental health problems are difficult to diagnose, claims often contain incorrect information that present challenges to accurate case finding. We attempted to minimize this problem by requiring either an inpatient claim with a primary diagnosis of schizophrenia or two outpatient claims on different days with a primary diagnosis of schizophrenia, adapting definitions used by others (Busch, Frank & Lehman 2004). However, we acknowledge that claims are not an ideal source to identify this population and may provide an undercount of the target population as diagnosis fields are not required for payment of services. Although current guidelines specify follow-up with a mental health provider following hospitalization, performance on our candidate measure is assessed by follow-up with any provider because mental health providers cannot be identified in Medicaid claims.
Finally, use of MAX data to test the measures limits the external validity of our results. Our MAX analytic study population was purposely limited to Medicaid recipients with claims data so that we could reliably identify patients with schizophrenia and the services they received. As a result, our study population included primarily disabled, non-dual-eligible enrollees in FFS plans. However, this group represents only a minority of the universe of people with SMI who receive mental health treatment through Medicaid programs. In particular, because drugs treatments are reimbursed by Medicare Part D for dually-eligible enrollees we are unable to include them, thus eliminating about 40 percent of all disabled Medicaid recipients from performance assessment.
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Several topics were of interest to ASPE, the development team, and stakeholders, but the evidence base, tools, and methods for tracking these measures are immature. For example, evaluating receipt of evidence-based psychosocial services may require measures that address the structures of care (e.g., availability of trained providers, supervision). State officials in particular were interested in measures addressing potential overuse of pharmacological treatments, which is challenging to document in the absence of tools for risk adjustment and symptom measurement. In addition, the evidence to support overuse measures is inconsistent. Patient-reported outcomes were also of interest to stakeholders, but they cannot be ascertained using claims data.
There was considerable interest in focus groups and TAG on addressing the physical health needs of people with schizophrenia; however, there was not always evidence to provide a rationale for a particular focus on such people for a given test. Some highly important preventive services, in particular tobacco cessation counseling and assistance, are not feasible in claims data. While there was evidence of low rates of cervical cancer screening among women with schizophrenia, there was no such evidence of a gap in care for HIV screening. Continuity of Medicaid enrollment was proposed to assess whether people with schizophrenia have consistent access to services; however, some lapses in coverage may be related to desirable outcomes (such as employment), and it would not be possible to determine the reason for loss of coverage. As the evidence base grows and use of electronic medical records and other electronic data repositories (for example, registries) also grows, so too will the ability to implement evidence-based measures.
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Quality measurement for Medicaid recipients with schizophrenia presents implementation issues. During the development process, and in particular during the field-testing process, we became aware of several issues related to measure implementation. Key implementation issues included measure attribution, variations in care financing, and the need for long look-back periods for several measures. For example, although the TAG and several stakeholders endorsed the inclusion of a general measure tracking ED use, some providers voiced concerns about attribution for this measure. Specifically, during the field-testing process, mental health providers felt they should not be held accountable for ED visits for accidents or other non-mental health reasons. Consequently, we dropped the measure of general ED use from our pilot-testing. However, attribution of care processes and outcomes will likely prove controversial, though implementation of the proposed measures at the state (rather than the provider level) will help to minimize concerns over attribution.
We found that variation in the financing of services for people with SMI limited our ability to measure the care provided by Medicaid programs. For example, the provision of services through state mental health systems, the coverage of mental health services through Medicare for dual-eligible beneficiaries, the prohibition of same-day billing of medical and behavioral health services, and interstate variation in Medicaid and disability standards all underscore the limitations of claims data to measure quality for enrollees with schizophrenia.
Finally, we found that reliance on Medicaid claims to produce rates of health screening can require a large volume of data to address issues of "look-back" for selected conditions. For example, some health conditions have a screening recommendation of every five years. Therefore, to compute a health screening measure for these conditions, information systems require the capacity to look back over a five-year claims history, which for some states could be a daunting task.
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The distinction between enrollees with schizophrenia and other SMI conditions is, in many cases, artificial. The project team, ASPE, and measure stakeholders all expressed the belief that conceptually, many issues related to schizophrenia also apply broadly to people with any SMI. It was outside the scope of this project to conduct the full evidence review and testing necessary for this work. Further work is needed to consider whether measures similar to the ones developed and tested under this contract would be relevant for people with bipolar disorder and other SMI.
References
Buchanan, Robert W. et al. (2010). "The 2009 schizophrenia PORT psychopharmacological treatment recommendations and summary statements." Schizophrenia Bulletin, 36(1): 71-93.
Busch, Alisa B., Richard Frank and Anthony Lehman. "The effect of a managed behavioral health carve-out on quality of care for Medicaid patients diagnosed as having schizophrenia." Archives of General Psychiatry, 61: 442-448.
Dixon, Lisa B., Faith Dickerson, Alan S. Bellack, et al. (2010). "The 2009 PORT psychosocial treatment recommendations and summary statements." Schizophrenia Bulletin, 36(1): 48-70.
Sherry, Tisamarie (2010). "Guidelines for the Treatment of Schizophrenia: A Review of the Literature." Unpublished draft report.
Notes
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An ICD-9 code of 295.xx was used to flag schizophrenia.
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Outpatient diagnoses were observed on different days.
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We used MAX data from the following states in 2007: Alabama, Alaska, California, Connecticut, Georgia, Idaho, Illinois, Indiana, Iowa, Louisiana, Maryland, Missouri, Mississippi, New Hampshire, North Carolina, North Dakota, Nevada, Oklahoma, South Dakota, Washington DC, West Virginia, and Wyoming. These states were noted to have complete enrollment, fee-for-service (FFS) claims and encounter records. Although the sample was primarily enrolled in FFS plans, some states with complete encounter data were included in our analytic sample.
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2008 data were available for a subset (N=16) of the 2007 states: Alabama, Alaska, Connecticut, Georgia, Idaho, Indiana, Iowa, Louisiana, Maryland, Mississippi, New Hampshire, North Carolina, Oklahoma, South Dakota, West Virginia, and Wyoming.
To obtain a printed copy of this report, send the full report title and your mailing information to:
U.S. Department of Health and Human Services
Office of Disability, Aging and Long-Term Care Policy
Room 424E, H.H. Humphrey Building
200 Independence Avenue, S.W.
Washington, D.C. 20201
FAX: 202-401-7733
Email: webmaster.DALTCP@hhs.gov
RETURN TO:
Office of Disability, Aging and Long-Term Care Policy (DALTCP) Home [http://aspe.hhs.gov/office_specific/daltcp.cfm]
Assistant Secretary for Planning and Evaluation (ASPE) Home [http://aspe.hhs.gov]
U.S. Department of Health and Human Services (HHS) Home [http://www.hhs.gov]
Appendices
Appendix A. Measure Concepts for Patients with Schizophrenia
Appendix B. TAG Membership and Slide Decks
Name | Affiliation | Area of Expertise |
---|---|---|
Alisa Busch, MD, MS | Harvard Medical School McLean Hospital | Clinical/psychiatry |
Enola Proctor, PhD, MSW | Washington University | Clinical/social work |
David Shern, PhD | Mental Health America | Consumer |
Dan For, MD, MPH | Johns Hopkins University | Measurement |
Wilma Thownshend, MSW | SAMHSA | Consumer |
Lorrie Rickman-Jones, PhD | Illinois Department of Human Services | State mental health policy |
Eric Hamilton | ValueOptions | Managed behavioral health |
Alexander Young, MD, MSHS | University of California, Los Angeles | Measurement |
Peter Delaney, PhD, LCSWC | SAMHSA | Federal mental health policy |
Ben Druss, MD | Emory University | Clinical/psychiatry |
Maureen Corcoran | VORYS Health Care Advisors | State and federal mental health policy |
Mike Fitzpatrick | NAMI | Consumer |
Bob Heinssen, PhD | NIMH | Federal mental health policy |
Anita Yuskauskas, PhDa | CMS | Federal mental health policy/ Medicaid |
Peggy Clark, MSW, MPAb | CMS | Federal mental health policy/ Medicaid |
Phil Wang, MD, DrPHb | NIMH | Federal mental health policy |
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Appendix C. Memo Summarizing Focus Group Input
MATHEMATICA Policy Research
600 Maryland Ave., SW, Suite 550
Washington, DC 20024-9220
Telephone (202) 484-9220
Fax (202) 863-1763
http://www.mathematica-mpr.com
MEMORANDUM
TO: Lisa Patton, Ph.D., Office of the Assistant Secretary for Planning and Evaluation
Hakan Aykan, Ph.D., Office of the Assistant Secretary for Planning and Evaluation
FROM: Thomas W. Croghan, M.D., Mathematica Policy Research, Inc.
Sarah Hudson Scholle, Dr.P.H., National Committee for Quality Assurance
DATE: 6/13/2011
SUBJECT: Testing of Measures for Medicaid Beneficiaries with Schizophrenia
Appendix D. Summary of Public Comment
TABLE D.1. Public Comment Summary | ||||
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Organization Name | Feedback Type | Comments | Comments Modified | Disposition |
Schizophrenia Measure Set -- Overall | ||||
Accountable Behavioral Health Alliance | Support with modification. | In Central Oregon our Oregon Health Plan/SPMI population dies at the average age of 45. Preliminary reasoning includes poor overall physical health, lack of medical care follow-up and side effects from the long-term use of antipsychotic medications. Standards must be set with this high risk population to ensure that both physical and mental health are actively tracked to receive adequate services to improve overall health and life expectancy. I also fear how indigent individuals are fairing. More attention should be focused on the holistic view of this at risk population subgroup with better follow-up and improved access. | Consider approaching these measures in a more holistic way due to the fact that the SMI population in general a high risk group. | NCQA will share this thought with Mathematica. |
University of California, Irvine | Support. | Long-Acting Depot preparations are going to revolutionize outcomes and decrease recidivism. The reason they are not being used today in great numbers is the very poor reimbursement. One small study showed that if every schizophrenic in this country was on a long-acting injectable (LAI), within 6 months half of our psychiatry hospitals would no longer be needed. The cost savings would be close to $11 Billion dollars per year. So the way to get greater use is to increase the reimbursement for the practitioner who administers the injection. I see this as the biggest cost saving and patient improvement program in the history of our treatment of schizophrenia. Please contact me for this concept. | Consider focusing on a long-term solution, which would be focusing on LAIs. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
Seven Counties Services | Support with modification. | Good set of measures. I am sure that it will get shorter, but I want to include 2 additional measures: one for smoking assessment and one for exercise assessment. The smoking assessment is critical. Along with bad antipsychotic management it is one of the 2 major killers for people with schizophrenia. Let's start assessing and offering evidence-based interventions. | Consider adding measures for smoking assessment and exercise assessment. | Smoking assessment and exercise assessment are not readily available in claims and therefore cannot be included. |
National Association of County Behavioral Health and Developmental Disability Directors (NACBHDD) | Support with modification. | Why are you beginning at age 25 when adult Medicaid begins at age 22 and early onset schizophrenia can begin as early as 17? Issue is that you need be create a clear line between adolescence and adulthood. | Concerned that the age specifications in the measures are not representative of Medicaid or early onset schizophrenia. | TAG recommended 25 to ensure stability of diagnosis. |
New Hampshire Department of Health and Human Services (DHHS) | Support with modification. | The list of antipsychotics needs to be updated. | Concerned that the list of antipsychotics are not updated. | NCQA and Mathematica will review the list of antipsychotics. |
Kaiser Health Plan | Support with modification. | Kaiser Permanente is supportive of a creation of a measure set for people with schizophrenia focusing on the pharmacological and physical health needs of this population. The group recognizes that people with schizophrenia often receive sub-optimal care in the areas which these candidate measures seek to address. We are glad to have been a part of this discussion and look forward to working to improve the quality of care that our members with schizophrenia receive. There is a concern however, that given that most of the Kaiser Permanente members who are Medicaid recipients, have split coverage. In most regions, the behavioral health coverage is carved out and provided at the community mental health clinic level while their physical health coverage is provided with the Kaiser Permanente system. This might make coordinating this care difficult and data collection nearly impossible. Comments on Inclusion Criteria: There is consensus that the diagnoses proposed are adequate for identification of people with schizophrenia and that the number of visits in differing venues was reasonable. There was a concern raised however, about how diagnoses made in an ED would count. Diagnoses made in the ED are often erroneous and depending on how these are included, may increase the denominator. If ED diagnoses would require 2 visits on separate dates with the diagnoses, this could address the issue. |
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Gulf Coast Health Center | Support with modification. | Over 30 years of respected research supports the use of a biopsychosocial model for effective and efficient treatment of schizophrenia, as well as schizoaffective and bipolar disorders including psychosis. You limit measures of treatment quality/effectiveness to medical encounters, specifically readmission to an inpatient facility. The designation "health care" should replace the term medical, to more accurately measure treatment which really works. Additionally, by your standard, "treatment" is successful if the person is not readmitted for inpatient services. So all the psychotic persons wandering our streets, sleeping on our park benches and clogging up our county jails received successful treatment, by your limited measure(s). Diseases like diabetes, primary hypertension, alcohol and other drug dependence, schizophrenia, bipolar disorder--and several other disorders--need to be treated as chronic conditions by a varied mix of care providers, not limited to medical practitioners. And quality measures of successful treatment must include quality of life components, the bare basics being clothing, housing, and employment. Your current measure of "success" has caused a mushroom-like proliferation of intensive outpatient and partial hospitalization programs, with 20% of the price tag for this "treatment" (for persons without both Medicare AND Medicaid coverage) falling directly on the shoulders of the patients you are purportedly treating in a successful manner. Your quality measure for schizophrenia treatment is woefully inadequate. | Concern that the proposed measures do not go nearly far enough. | The concerns raised do not account for the difficulty of collecting data for performance measures. NCQA will share these thoughts with Mathematica. |
University of Pittsburgh | Support with modification. | It is quite clear that these measures fit a model of care that predates the emerging recovery approach. I have no particular issues with them except there inadequacy to care quality care--all these things could be done without a recovery framework. I understand that you considered other measures but found the data sources too weak to support their use. Obviously we need to develop and Implement other measures--and soon. Candidate measures I would suggest is if there is any evidence that the person receiving services was supported in the opportunity to outline their own goals for care or had any role in shared decision making about the care and its goals. I hope your report suggests this. In the mean time--I would suggest that you consider as a measure how often individuals are admitted involuntarily, put into seclusion/ restraints or given forced medications. This data is collected, so should be available. Clearly all efforts to decrease coercion in the context of care are elements of improved care. The campaign to radically reduce seclusion and restraint proves the merit of collecting this data as a quality indicator. | Consider including a measure about individuals being admitted involuntarily, put into seclusion/restraints or given forced medications. | NCQA will share this thought with Mathematica. |
University of Pittsburgh | Support with modification. | One final measurable recovery oriented quality measure would be if they were ever encountered by a peer support specialist during their care, and if so, to what extent. This should show in billing data and in electronic health records (EHRs). Also data that could be available is to track how many persons with schizophrenia get on disability if they have no source of income, how long it takes and how many ever come off. Harder to get but an incredibly important element of care. Thanks. I would be very happy to discuss Any of these ideas if that would be useful. |
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National Council for Community Behavioral Healthcare | Support. | We applaud NCQAs work on these measures. The measures are practical, timely and necessary. | Support. | Support. |
American Psychological Association | Support with modification. | I am writing on behalf of the American Psychological Association the largest organization of psychologists worldwide with over 154,000 members. The Association supports NCQA's efforts to measure important aspects of both physical and mental health care for Medicaid beneficiaries with schizophrenia. The proposed measures can be used to further the important goals of improving access to care and quality of care for this vulnerable population. However, we disagree with the decision not to include measures of psychosocial care and recommend that you develop a measure(s) for this important aspect of schizophrenia treatment. There is substantial evidence of the benefits of psychosocial care. For example, a 2011 study by Grant et al. found that low-functioning patients with schizophrenia who were treated with cognitive therapy showed statistically significant and clinically meaningful improvements in functioning and reductions in symptom severity (http://archpsyc.ama-assn.org/cgi/content/full/archgenpsychiatry.2011.129). An excellent source of relevant data in this area is the Schizophrenia PORT project. PORT recently released a comprehensive summary of current evidence-based psychosocial interventions for patients with schizophrenia along with specific treatment recommendations (http://schizophreniabulletin.oxfordjournals.org/content/36/1/48.full.pdf+html). In addition, the "Resolution on APA Endorsement of the Concept of Recovery for People with Serious Mental Illness" provides citations to several important studies that demonstrate the value of psychological interventions (http://www.apa.org/practice/leadership/smi/recovery-resolution.pdf). The Association resolution highlights the need to make potentially beneficial services accessible. In addition, the "Resolution on APA Endorsement of the Concept of Recovery for People with Serious Mental Illness" provides citations to several important studies that demonstrate the value of psychological interventions (http://www.apa.org/practice/leadership/smi/recovery-resolution.pdf). The Association resolution highlights the need to make potentially beneficial services accessible, particularly for minorities and people of lower socioeconomic status such as Medicaid beneficiaries. | Concerned that psychosocial measures are not included. | These measures were in the original list of potential measures, but plans do not currently have the ability to gather all the data using claims. NCQA will share these thoughts with Mathematica. |
OptumHealth Behavioral Solutions | Support with modification. | Thank you for focusing on this very important diagnostic category for our Medicaid population. As we mention in our comments, our most significant concern is that the reliability of the results may be compromised based on potentially low denominators. We hope that the development of these datasets will encourage states to review common datasets and have standard, consistent expectations. Overall, these metrics are a very good start. We encourage NCQA to find ways to look at treatment outcome measures in future metrics. There may be ways to look at "treat to remission" and relapse prevention measures using normed instruments. OptumHealth Behavioral Solutions would value the opportunity to work with you to develop future measures. | Consider looking at outcomes in future measure development. | Will consider for future projects. |
American Psychiatric Association (APA) | Support with modification | The CPT code 90862 (Pharmacological Management) is often used for clinical encounters with psychiatrists, and should be added to the specifications of these measures (e.g., in establishing the diagnosis) as appropriate. The specifications of these measures should clearly indicate that these are system-level measures. Should these measures be expanded for institution or clinician level analysis in the future, additional specification would be required. Some measures, such as the measure on follow-up after hospitalization (FUH), involves many factors and may not be appropriate for measurement and accountability at the clinician level of analysis. We understand the rationale for excluding psychosocial interventions from this measure set, and encourage that additional interventions be considered for inclusion as the tools for performance measurement advance. | Consider adding the CPT code 90862 (Pharmacological Management) in the measure specifications. | NCQA and Mathematica will evaluate this code and its applicability to the measure set. |
National Alliance on Mental Illness (NAMI) | Support. | NAMI would like to express strong support for the Quality Measures for Medicaid Beneficiaries with Schizophrenia developed by the NCQA. As the nation's largest organization representing people living with SMI and their families, NAMI applauds NCQA for this important effort to move forward with this groundbreaking effort to more effectively assess treatment and outcomes in the Medicaid program. NAMI is especially supportive of the breadth of these proposed measures and the inclusion of key indicators for psychiatric treatment such as treatment adherence, ED utilization and post-acute care follow-up services. However, even more important are the diverse measures for medical comorbidities experienced by Medicaid beneficiaries living with schizophrenia including cardiovascular, diabetes and cervical cancer screening and monitoring. Implementation of the measures will be critical for the field of publicly funded mental health services. For decades, data, outcome measures and accountability in publicly funded mental health services has lagged far behind other major health care disciplines. In many states, existing data have been non-existent for available services, service needs and positive outcomes. Further, what data has existed is rarely standardized across states or public sector health plans, making comparisons and the identification of useful avenues for improvement extremely difficult. This is especially the case with the Medicaid program where accountability is spread across CMS (a federal agency whose role is limited to retroactively matching state spending), state Medicaid programs and state mental health agencies that oversee local providers. For years, federal officials, state mental health agencies and community providers have haggled over leadership definitions, and strategies for addressing the data collection and outcome measure | Support. | Support. |
Cardiovascular Health and Diabetes Monitoring | ||||
BJC HealthCare | Support with modification. | Specify that Hemoglobin A1c (HbA1c) be used, not glucose. The American Diabetes Association now recommends HbA1c for screening and for monitoring. It is more reliable and readily testable as it can be done any time of the day with any amount of food or drink consumed. HbA1c is the standard for monitoring diabetes. It is much easier to have a system to test for it for both screening and monitoring rather than fasting glucose for screening and HbA1c for monitoring. | Consider only using HbA1c testing for screening and monitoring to stay consistent with the American Diabetes Association's recommendation. | Review guidelines and evidence for cardiovascular and diabetes screening and monitoring. |
Kaiser Health Plan | Support. | Support. | Support. | Support. |
OptumHealth Behavioral Solutions | Support with modification. |
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APA | Support. | We suggest including physical findings such as weight and BMI as monitoring requirements when this type of data can be more easily captured for performance measurement purposes (e.g., broader use of EHRs). | Consider adding weight and BMI monitoring to the physical health measures for schizophrenia when there is broader use of EHRs. | Will consider for future projects. |
NAMI | Support. |
| Support. | Support. |
Cardiovascular Health and Diabetes Screening | ||||
BJC HealthCare | Support with modification. | Specify that HbA1c be used, not glucose. Glucose is a much less reliable screen due to the need for it to be fasting. The American Diabetes Association now recommends HbA1c for screening. It is more reliable and readily testable as it can be done any time of the day with any amount of food or drink consumed. HbA1c is the standard for monitoring diabetes. It is much easier to have a system to test for it for both screening and monitoring rather than fasting glucose for screening and HbA1c for monitoring. | Consider only using HbA1c testing for screening and monitoring to stay consistent with the American Diabetes Association's recommendation. | Review guidelines and evidence for cardiovascular and diabetes screening and monitoring. |
Kaiser Health Plan | Support with modification. | Relevance: We are concerned that both screening recommendations are too frequent. Would like to suggest that the frequency of screenings be reconciled against recommendations from the American Diabetes Association. American Usefulness: We agree that the measure would be useful in improving quality of care. Collection: This data could be collected. | Concern that screenings are too frequent and will not allow actionability. | Measures are specified for people with schizophrenia, therefore a high frequency of screenings should not be an issue. |
Bristol-Myers Squibb Company | Support with modification. | It is important that a lab test is done before or at the time of a new prescription to ensure appropriate decision making. We would suggest an additional measure such as the percentage of members with schizophrenia and who were prescribed any antipsychotic medication during the measurement year who received a diabetes/cardiovascular health screening prior to or at the time of their initial prescription. | Consider adding a rate that looks at the percentage of people that received a diabetes and cardiovascular screening prior to or at the time of their initial antipsychotic prescription. | Will consider for future projects. |
OptumHealth Behavioral Solutions | Support with modification. |
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APA | Support. | We suggest including physical findings such as weight and BMI as screening requirements when this type of data can be more easily captured for performance measurement purposes (e.g., broader use of EHRs). | Consider adding weight and BMI monitoring to the physical health measures for schizophrenia when there is broader use of EHRs. | Will consider for future projects. |
NAMI | Support. |
| Support. | Support. |
Cervical Cancer Screening for Women with Schizophrenia | ||||
Wake Forest University School of Medicine | Support with modification. | This metric should not be a review criterion for the performance of a treating psychiatrist for a person with schizophrenia. it does not fit with the boundaries of the psychiatrists competence. | Concern that the measure asks psychiatrists to perform a cervical cancer screening, because the screening does not fall within the boundaries of a psychiatrist's expertise. | Clarify that the measure does not ask a psychiatrist to perform cervical cancer screening. The measure asks the entity being measured to identify patients with a schizophrenia diagnosis that had a cervical cancer screening. |
Wake Forest Baptist Health (WFBH) | Do NOT Support. | I believe this is the responsibility of the PCP. | Concern that the measure asks psychiatrists to perform a cervical cancer screening, because the screening does not fall within the boundaries of a psychiatrist's expertise. | Clarify that the measure does not ask a psychiatrist to perform cervical cancer screening, but asks the entity being measured to identify patients with a schizophrenia diagnosis that had a cervical cancer screening. |
WFBH | Do NOT Support. | Do NOT Support. | Do NOT Support. | Do NOT Support. |
Wake Health | Support with modification. | How can a psychiatrist manage cervical cancer screening? | Concern that the measure asks psychiatrists to perform a cervical cancer screening, because the screening does not fall within the boundaries of a psychiatrist's expertise. | Clarify that the measure does not ask a psychiatrist to perform cervical cancer screening. The measure asks the entity being measured to identify patients with a schizophrenia diagnosis that had a cervical cancer screening. |
University of Nevada School of Medicine | Do NOT Support. | A treating psychiatrist cannot control whether a female patient goes to a gynecologist to have Cervical Cancer Screening and cannot do exam himself. He can only refer, so this should not be a quality measure. | Concern that the measure asks psychiatrists to perform a cervical cancer screening, because the screening does not fall within the boundaries of a psychiatrist's expertise. | Clarify that the measure does not ask a psychiatrist to perform cervical cancer screening. The measure asks the entity being measured to identify patients with a schizophrenia diagnosis that had a cervical cancer screening. |
Kaiser Health Plan | Do NOT Support. | Relevance: We feel this may be redundant to existing measures. Although an appreciation that this issue is often overlooked in women with schizophrenia, We have some concerns about the alignment of this with evidence. Usefulness: We have concerns about how this measure would interface with the existing HEDIS measures for cervical cancer screening. Would these patients be in both denominators? Collection: This data could be collected via claims. |
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OptumHealth Behavioral Solutions | Support with modification. |
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APA | Support. | We support this measure, but suggest that the measure include justification and a description of the gap in care within the specifications. There are many general medical screenings that could have been included in this measure set (e.g., colonoscopy), so the rationale as to why this screening was singled out would be useful. | Consider including the measure justification and a description of how this measure addressed the gap in care within the specifications. | The specifications are not designed to include the measure rationale. NCQA and Mathematica will consider publishing the measure workups with the specifications. |
NAMI | Support. |
| Concern that cervical cancer screening is a mental health risk for women with a history of sexual trauma or who have paranoia symptoms. If the measure did not exclude members with this history, then it will be incumbent on Medicaid plans to provide better education about the screening prior to the procedure. | Discuss with Mathematica how to account for members with a history of sexual trauma and members with paranoia symptoms. |
Emergency Department Utilization | ||||
Kaiser Health Plan | Do NOT Support. | Relevance: We have a concern regarding the inclusion criteria; would this include any ED visit or only those for an acute exacerbation of their schizophrenia symptoms? Usefulness: We do not feel that this measure would not be as useful as the other candidate measures. Collection: The data could be collected. |
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OptumHealth Behavioral Solutions | Do NOT Support. | The ED visits used to identify inclusion in the numerator are not tied to a specific problem or diagnostic code. This measure, therefore, does not reflect the effectiveness of care. Medicaid enrollees with a diagnosis of schizophrenia are at increased risk of living in poverty, having comorbid medical illnesses and not having adequate support or supervision. Assigning a rate to ED utilization may encourage health plans to address an issue that is not an established medical or treatment issue. The unintended consequences of this focus may be squandered resources and even potential restrictions on access to emergency services. | Concern that this measure does not have enough focus and will encourage health plans to provide unnecessary treatment that will only increase resource use. | For this measure, a lower rate represents better performance. NCQA will clarify that in the specification. NCQA and Mathematica will discuss the level of focus needed in the measure. |
APA | Do NOT Support. | We do not feel we can support this measure without justification and a description of the gap in care included within its specifications. ED admissions unrelated to the diagnosis of schizophrenia should not be counted in the numerator. | Concern that this measure does not have enough focus. | Will review ED measure definition. |
NAMI | Support. |
| Support. | Support. |
Follow-Up After Hospitalization for Schizophrenia | ||||
BJC HealthCare | Support with modification. | Specify 7 "calendar" days and 30 "calendar days". Organizations easily move these standards to their business days. The data collected and standard sought should be "a week after discharge" and "a month after discharge" (i.e., calendar days). | Clarify that the days are calendar days and not business days. | HEDIS measure specifications do not specify calendar days versus business days. All HEDIS measures use calendar days. |
NACBHDD | Support with modification. | Separate acute inpatient care for a mental health reason from other acute inpatient episodes. Otherwise, findings will be ambiguous. | Consider separating the measure by the type of acute inpatient event. | The measure only looks at acute inpatient episodes for members that had a schizophrenia diagnosis upon discharge. |
Kaiser Health Plan | Support with modification. | Kaiser Permanente has several comments. Relevance of measure: We agree that this measure is quite relevant. Much of our care is provided via telephone visits, which currently do not count toward meeting this measure. Could telephone visits be included in this measure? Usefulness: We agree that the measure would be useful in improving quality of care. However, we have concerns on how this proposed measure would interface with the existing HEDIS measures for follow-up after psychiatric hospitalization. Would these patients be in both denominators? Collection: This data would be difficult to collect for members who have carved out behavioral health coverage. |
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American Psychological Association | Support. | We support the inclusion of a measure of follow-up care by a mental health practitioner after hospitalizations for schizophrenia, as it will help to avoid unnecessary hospital readmissions and promote continuity of care. | Support. | Support. |
OptumHealth Behavioral Solutions | Support with modification. |
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APA | Support with modification. | The definition of "mental health practitioner" was referenced but not made available for review in the public comment materials. | Clarify the definition for mental health practitioner. | Include definitions in final specifications. |
NAMI | Support. |
| Support. | Support. |
Use and Continuity of Antipsychotic Medications | ||||
New Hampshire DHHS | Support with modification. | Please modify age--I do not understand why people under 25 years were omitted. Young people with schizophrenia are an extremely high need population and antipsychotic treatment is extremely important for their care. | Consider modifying the age limits to include younger people. | TAG recommended 25 to ensure stability of diagnosis. |
Kaiser Health Plan | Support with modification. | Kaiser Permanente agrees this measure is relevant and useful in improving the quality of care for this population. We have a concern that information about prescriptions filled in owned and contracted pharmacies could not be collected. | Concern that some prescription data will not be captured. | NCQA will share this thought with Mathematica. |
National Council for Community Behavioral Healthcare | Support with modification. | Would suggest that you include all antipsychotic medications to the list regardless of delivery mechanism, inclusive of long-acting injection medications. | Consider being more comprehensive with the antipsychotic medication list by including long action and injectable medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
Johnson & Johnson Health Care Systems | Support with modification. | The candidate measure "Use & Continuity of Antipsychotic medications" utilizes the "proportion of days covered" (PDC) calculation to derive the measure, which we understand would exclude LAI medications. The resulting measurement would not incorporate an important treatment choice that physicians often choose for patients that have difficulty staying on their medication. We believe this would compromise the actual measure objective, namely improved adherence. It is important to note that the utilization of LAIs, which can provide medication "on board" for patients up to one month, has increased over the last few years. That trend is expected to continue as newer LAIs enter the marketplace. Johnson & Johnson Health Care Systems, Inc. | Consider including LAI medications in the measures. This would require changes to the specifications for Use and Continuity of Antipsychotic medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
Mercer University College of Pharmacy and Health Sciences | Support with modification. | Please consider the inclusion of long-acting injections such as Haldol Decanoate, Invega Sustenna, Prolixin Decanoate and Risperidal Consta. These agents play a vital role on patient adherence. Our society has an unusual position regarding these agents, however, we must realize that patient adherence is a major issue in this population and this type of formulation provides an added option for patient treatment. | Consider including LAI medications in the measures. This would require changes to the specifications for Use and Continuity of Antipsychotic medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
Valley Mental Heath | Support with modification. | LAIs are integral in treating this illness and a big part of future medication development. You are missing the boat by not incorporating LAI medicines in your measures | Consider including LAI medications in the measures. This would require changes to the specifications for Use and Continuity of Antipsychotic medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
OptumHealth Behavioral Solutions | Support with modification. |
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Mercy Behavioral Health | Support with modification. | I was concerned that Injectable. Therapy was not considered as a cornerstone to the Continuity piece. This is the most effective way to ensure continuity both in the community and during the transition from hospital to community. I definitely believe that to make recommendations without including all options is misinforming. I am a large user and proponent of long-acting therapies for keeping people healthy and safe in the community. | Consider including LAI medications in the measures. This would require changes to the specifications for Use and Continuity of Antipsychotic medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
Cerebral Palsy of New Jersey | Support with modification. | As a behavioral health executive with 35 years of experience managing inner city, comprehensive community mental health centers, I think it is excellent to see "use and continuity of antipsychotic medication" identified as a quality measure. Medication non-adherence puts patients at extreme risk for adverse outcomes and adds millions of dollars to the cost of health care in regards to rapid readmissions. I believe, however, it is crucial that long-acting injections be added to the measure. LAIs offer a superior way of monitoring adherence, offer a superior method of delivering the medication and offer a much less stressful adherence plan for consumers who are easily overwhelmed by trying to adhere to multiple doses of daily oral antipsychotics. I strongly urge the NCQA to include long-acting in this measure. | Consider including LAI medications in the measures. This would require changes to the specifications for Use and Continuity of Antipsychotic medications. | The measure is intended to include injectables as part of the definition of antipsychotic medication. Will verify that list includes them. |
APA | Support with modification. | The following medications appear to be absent from the table: iloperidone; lurasidone; and asenapine. The following medications are included in the table but are no longer available in the United States: trifluoperazine; mesoridazine; and molindone. When electronic prescribing is more prevalent in the future, we suggest consider differentiating between prescriptions that were not written versus prescriptions which were written but not filled by the patient. Quality improvement approaches will differ depending on which is the cause of lack of medication use or continuity. | Consider adding iloperidone; lurasidone; and asenapine to the medication measure. The following medications are included in the table but are no longer available in the United States: trifluoperazine; mesoridazine; and molindone. | NCQA and Mathematica will review the list of antipsychotics. |
NAMI | Support. |
| Support. | Support. |
Inclusion of Bipolar Disorder in the Denominator | ||||
BJC HealthCare | Do NOT Support. | No. People with Bipolar Disorder are treated with a number of medications in addition to the antipsychotics. Those other medications can contribute to weight gain, and thus affect risk factors for heart disease, weight and diabetes. Therefore including bipolar in the denominator confounds the data unless all those medications which have weight gain as a side effect are included (i.e., several of the anti-depressants and mood stabilizers; e.g., trazadone, lithium, etc.) | Concern that including bipolar disorder will confound the data due to medication differences. | NCQA will pass share this thought with Mathematica. |
NACBHDD | Support with modification. | Run 2 separate analyses for schizophrenia and bipolar. Otherwise results will be ambiguous. | Concern that the results of the data will be ambiguous. | NCQA will share this thought with Mathematica. |
University of Nevada School of Medicine | Do NOT Support. | Bipolar disorder does not always require treatment with an antipsychotic (e.g., when patient is on Depakote or Lithium and the bipolar disorder is in remission). Sometimes it is contraindicated. Thus bipolar disorder should not be included in the numerator or denominator. | Concern that including bipolar disorder will confound the data due to medication differences. | NCQA will share this thought with Mathematica. |
Kaiser Health Plan | Support with modification. | Please consider making this based upon the use of medications known to increase risk of diabetes and dyslipidemia, rather than limit this to those with a specific diagnosis and medication. | Consider changing the measure focus away from a specific diagnosis to a focus on medications known to increase the risk of diabetes and dyslipidemia. | The measures are intended to focus on people with schizophrenia. |
National Council for Community Behavioral Healthcare | Support. | Support. | Support. | Support. |
American Psychological Association | Support. | We support the proposed expansion of measure denominators to include Medicaid beneficiaries with bipolar disorder in order to increase screening and monitoring of cardiovascular health and diabetes. | Support. | Support. |
Bristol-Myers Squibb Company | Support. | I would like to indicate support for the expansion of the denominator beyond schizophrenia to include patients with bipolar disorder for the following reasons: Patients with bipolar disorder typically suffer from a high burden of comorbid medical problems, including metabolic issues. Bipolar patients are often overweight and likely to meet criteria for "metabolic syndrome", placing them at increased risk of developing cardiovascular disease, stroke and Type 2 diabetes. Moreover, several medications used to treat bipolar disorder pose hazards for increasing body weight and worsening metabolic parameters. Given that obesity and illness of the endocrine/metabolic system have been correlated with poorer outcomes, the appropriate monitoring of metabolic health remains critical for this patient group. | Consider adding bipolar disorder to the measure denominators, because patients with this diagnosis suffer from comorbid medical problems. | NCQA will share this thought with Mathematica. |
OptumHealth Behavioral Solutions | Support. | Support. | Support. | Support. |
APA | Support. | We support the expansion of the cardiovascular screening and monitoring measures to the diagnosis of bipolar disorder, and suggest that these measures be considered for expansion to all patients treated with atypical antipsychotic medications, regardless of diagnosis, given the increased risk of cardiovascular illness. | Consider expanding the cardiovascular measures to anyone treated with atypical antipsychotic medications, regardless of diagnosis. | Discuss recommendation with Mathematica. |
NAMI | Support. | NAMI strongly endorses extension of these measures to bipolar disorder in the denominator. As with schizophrenia, bipolar disorder is a complex mental disorder with multiple phases and a diverse pathology of symptoms--mania, extreme mood swings, depression, anxiety, mixed state and, in some instances, psychotic features. Treatment for bipolar disorder is often complex and can involve prescribing of multiple compounds. As with schizophrenia, treatment adherence is often challenging for many individuals living with bipolar disorder. In fact, a number of the existing atypical antipsychotic compounds listed in the draft adherence measure are approved by the Food and Drug Administration for treatment of bipolar disorder (e.g., mood stabilizing agents). Likewise, persons with bipolar disorder experience many of the complex medical comorbidities (including cardiovascular disease, diabetes and cervical cancer) of individuals living with schizophrenia. In addition, they have nearly identical needs with respect to follow-up care after a hospital admission. Finally, they also utilize EDs for a diverse array of needs that often associated with failure to access treatment. For these reasons, NAMI urges that NCQA extend all 6 measures for schizophrenia to bipolar disorder. | Support. | NCQA will share these thoughts with Mathematica. |
Appendix E. Pilot-testing Results
TABLE E.1. Enrollee Information and Selected SMI Conditions by State | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
State | Total FFS | FFS Disabled | FFS Disabled & Non- Dually Eligible | Meet All Inclusion Criteriaa | Schizophreniab | Bipolar Disorderc | Schizophrenia or Bipolar Disorderd | Schizophrenia and Bipolar Disordere | ||||
N | N | N | N | N | Percent | N | Percent | N | Percent | N | Percent | |
AL | 903,809 | 210,887 | 111,630 | 52,351 | 4,071 | 7.8 | 1,201 | 2.3 | 5,067 | 9.7 | 205 | 0.4 |
AK | 126,203 | 15,747 | 8,510 | 2,670 | 270 | 10.1 | 114 | 4.3 | 379 | 14.2 | 5 | 0.2 |
CA | 10,654,123 | 1,128,827 | 628,773 | 348,599 | 36,571 | 10.5 | 12,404 | 3.6 | 45,920 | 13.2 | 3,055 | 0.9 |
CT | 465,746 | 68,349 | 30,397 | 19,875 | 2,699 | 13.6 | 1,215 | 6.1 | 3,629 | 18.3 | 285 | 1.4 |
DC | 77,172 | 34,998 | 23,741 | 12,700 | 1,716 | 13.5 | 703 | 5.5 | 2,239 | 17.6 | 180 | 1.4 |
GA | 1,104,108 | 282,632 | 151,295 | 66,548 | 6,177 | 9.3 | 1,870 | 2.8 | 7,617 | 11.4 | 430 | 0.6 |
ID | 229,423 | 36,382 | 20,555 | 7,613 | 781 | 10.3 | 648 | 8.5 | 1,329 | 17.5 | 100 | 1.3 |
IL | 2,380,314 | 344,733 | 171,810 | 103,202 | 12,781 | 12.4 | 5,580 | 5.4 | 15,956 | 15.5 | 2,405 | 2.3 |
IN | 970,830 | 148,624 | 72,925 | 38,034 | 3,198 | 8.4 | 1,793 | 4.7 | 4,778 | 12.6 | 213 | 0.6 |
IA | 479,755 | 71,302 | 33,342 | 14,413 | 1,376 | 9.5 | 675 | 4.7 | 1,907 | 13.2 | 144 | 1.0 |
LA | 1,155,231 | 197,309 | 124,592 | 58,473 | 4,314 | 7.4 | 1,180 | 2.0 | 5,258 | 9.0 | 236 | 0.4 |
MD | 835,727 | 138,739 | 84,577 | 41,442 | 4,340 | 10.5 | 2,718 | 6.6 | 6,495 | 15.7 | 563 | 1.4 |
MO | 721,719 | 187,957 | 99,510 | 55,677 | 4,775 | 8.6 | 3,910 | 7.0 | 8,021 | 14.4 | 664 | 1.2 |
MS | 745,543 | 171,082 | 93,910 | 41,175 | 3,377 | 8.2 | 803 | 2.0 | 4,039 | 9.8 | 141 | 0.3 |
NH | 144,366 | 22,315 | 8,848 | 4,682 | 374 | 8.0 | 228 | 4.9 | 581 | 12.4 | 21 | 0.4 |
NC | 1,655,892 | 283,473 | 153,256 | 66,404 | 5,670 | 8.5 | 2,777 | 4.2 | 7,932 | 11.9 | 515 | 0.8 |
ND | 73,449 | 10,883 | 4,594 | 2,041 | 219 | 10.7 | 59 | 2.9 | 268 | 13.1 | 10 | 0.5 |
NV | 197,548 | 39,964 | 23,054 | 8,567 | 749 | 8.7 | 348 | 4.1 | 1,039 | 12.1 | 58 | 0.7 |
OK | 783,335 | 103,287 | 55,442 | 27,102 | 2,600 | 9.6 | 1,330 | 4.9 | 3,720 | 13.7 | 210 | 0.8 |
SD | 131,924 | 19,026 | 8,709 | 3,591 | 279 | 7.8 | 73 | 2.0 | 346 | 9.6 | 6 | 0.2 |
WV | 289,435 | 113,811 | 72,220 | 41,844 | 1,933 | 4.6 | 2,090 | 5.0 | 3,806 | 9.1 | 217 | 0.5 |
WY | 77,782 | 9,869 | 5,179 | 2,120 | 142 | 6.7 | 72 | 3.4 | 203 | 9.6 | 11 | 0.5 |
Total | 24,203,434 | 3,640,196 | 1,986,869 | 1,019,123 | 98,412 | 9.7 | 41,791 | 4.1 | 130,529 | 12.8 | 9,674 | 0.9 |
SOURCE: Mathematica analysis of 2007 MAX data.
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TABLE E.2. Enrollee Demographics | |||||
---|---|---|---|---|---|
Characteristic | Meet All Inclusion Critera | Schizophreniab | Schizophrenia or Bipolar Disorderc | ||
N | N | Percent | N | Percent | |
Gender | |||||
Male | 425,462 | 49,949 | 11.7 | 58,946 | 13.9 |
Female | 593,632 | 48,462 | 8.2 | 71,581 | 12.1 |
Age | |||||
25 - 30 | 96,156 | 10,454 | 10.9 | 14,054 | 14.6 |
31 - 40 | 170,421 | 19,770 | 11.6 | 27,620 | 16.2 |
41 - 50 | 298,627 | 35,211 | 11.8 | 46,957 | 15.7 |
51 - 60 | 351,638 | 27,890 | 7.9 | 35,567 | 10.1 |
61 - 64 | 102,281 | 5,087 | 5.0 | 6,331 | 6.2 |
Unknown | |||||
Race/Ethnicity | |||||
African American | 332,190 | 38,067 | 11.5 | 44,169 | 13.3 |
Caucasian | 473,576 | 41,105 | 8.7 | 62,834 | 13.3 |
Hispanic | 83,492 | 7,001 | 8.4 | 8,825 | 10.6 |
Other | 61,492 | 5,513 | 9.0 | 6,329 | 10.3 |
Unknown | 68,373 | 6,726 | 9.8 | 8,372 | 12.2 |
Comorbid Diagnoses | |||||
Cardiovascular diseased | 84,624 | 4,700 | 5.6 | 6,405 | 7.6 |
Diabetese | 178,962 | 17,027 | 9.5 | 21,845 | 12.2 |
Managed Care Status | |||||
Enrolled in HMO | 126,495 | 11,273 | 8.9 | 16,080 | 12.7 |
Enrolled in BHO | 14,352 | 1,372 | 9.6 | 1,900 | 13.2 |
Enrolled in other MC | 78,159 | 6,605 | 8.5 | 8,710 | 11.1 |
Total | 1,019,123 | 98,412 | 9.7 | 130,529 | 12.8 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
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TABLE E.3a. Use of Antipsychotic Medication by Enrollee Characteristic | |||
---|---|---|---|
Characteristic | Schizophreniaa | Use of Antipsychotic Medication | |
N | N | Percent | |
Gender | |||
Male | 48,642 | 45,704 | 94.0 |
Female | 47,787 | 44,458 | 93.0 |
Age | |||
25 - 30 | 10,170 | 9,639 | 94.8 |
31 - 40 | 19,312 | 18,212 | 94.3 |
41 - 50 | 34,513 | 32,345 | 93.7 |
51 - 60 | 27,410 | 25,326 | 92.4 |
61 - 64 | 5,025 | 4,641 | 92.4 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 37,041 | 34,324 | 92.7 |
Caucasian | 40,491 | 38,003 | 93.9 |
Hispanic | 6,898 | 6,541 | 94.8 |
Other | 5,412 | 5,137 | 94.9 |
Unknown | 6,588 | 6,158 | 93.5 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 4,683 | 4,246 | 90.7 |
Diabetesc | 16,968 | 15,942 | 94.0 |
Managed Care Status | |||
Enrolled in HMO | 11,018 | 10,125 | 91.9 |
Enrolled in BHO | 1,358 | 1,287 | 94.8 |
Enrolled in other MC | 6,529 | 6,108 | 93.6 |
Total | 96,430 | 90,163 | 93.5 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
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TABLE E.3b. Use of Antipsychotic Medication by State | |||
---|---|---|---|
State | Schizophreniaa | Use of Antipsychotic Medication | |
N | N | Percent | |
AL | 3,997 | 3,788 | 94.8 |
AK | 261 | 242 | 92.7 |
CA | 35,895 | 33,664 | 93.8 |
CT | 2,672 | 2,566 | 96.0 |
DC | 1,588 | 1,426 | 89.8 |
GA | 5,997 | 5,618 | 93.7 |
ID | 772 | 714 | 92.5 |
IL | 12,527 | 11,570 | 92.4 |
IN | 3,146 | 2,985 | 94.9 |
IA | 1,359 | 1,288 | 94.8 |
LA | 4,217 | 4,004 | 94.9 |
MD | 4,232 | 3,973 | 93.9 |
MO | 4,693 | 4,442 | 94.7 |
MS | 3,310 | 2,959 | 89.4 |
NH | 368 | 353 | 95.9 |
NC | 5,561 | 5,172 | 93.0 |
ND | 215 | 198 | 92.1 |
NV | 737 | 702 | 95.3 |
OK | 2,580 | 2,359 | 91.4 |
SD | 249 | 229 | 92.0 |
WV | 1,915 | 1,784 | 93.2 |
WY | 139 | 127 | 91.4 |
Total | 96,430 | 90,163 | 93.5 |
SOURCE: 2007 MAX data.
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TABLE E.4a. Antipsychotic Medication Possession Ratio by Enrollee Characteristic (All States) | |
---|---|
Characteristic | Antipsychotic Possession Ratio >80% |
Percent | |
Gender | |
Male | 64.9 |
Female | 63.7 |
Age | |
25 - 30 | 59.0 |
31 - 40 | 60.8 |
41 - 50 | 62.8 |
51 - 60 | 69.0 |
61 - 64 | 74.2 |
Unknown | 0.0 |
Race/Ethnicity | |
African American | 53.0 |
Caucasian | 72.6 |
Hispanic | 64.8 |
Other | 71.1 |
Unknown | 69.3 |
Comorbid Diagnoses | |
Cardiovascular diseasea | 62.7 |
Diabetesb | 71.0 |
Managed Care Status | |
Enrolled in HMO | 62.1 |
Enrolled in BHO | 74.7 |
Enrolled in other MC | 60.5 |
Total | 64.3 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care. Antipsychotic Possession Ratio = # Days supplied/# Days in treatment period.
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TABLE E.4b. Antipsychotic Medication Possession Ratio by State | |
---|---|
State | Antipsychotic Medication Possession Ratio >80% |
Percent | |
AL | 59.3 |
AK | 66.5 |
CA | 67.5 |
CT | 72.1 |
DC | 48.3 |
GA | 55.3 |
ID | 78.6 |
IL | 64.2 |
IN | 68.5 |
IA | 74.7 |
LA | 54.7 |
MD | 62.8 |
MO | 66.5 |
MS | 48.9 |
NH | 80.0 |
NC | 64.6 |
ND | 84.6 |
NV | 62.6 |
OK | 62.8 |
SD | 70.9 |
WV | 65.5 |
WY | 65.9 |
Total | 64.3 |
SOURCE: 2007 MAX data. Antipsychotic Possession Ratio = # Days supplied/# Days in treatment period. |
TABLE E.5a. Diabetes Screening Among Enrollees with Schizophrenia or Bipolar Disordera by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | Diabetes Screen | |
N | N | Percent | |
Gender | |||
Male | 40,443 | 4,118 | 10.2 |
Female | 43,749 | 4,760 | 10.9 |
Age | |||
25 - 30 | 10,087 | 1,096 | 10.9 |
31 - 40 | 18,686 | 2,083 | 11.1 |
41 - 50 | 30,206 | 3,104 | 10.3 |
51 - 60 | 21,492 | 2,199 | 10.2 |
61 - 64 | 3,721 | 396 | 10.6 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 27,027 | 2,469 | 9.1 |
Caucasian | 41,324 | 4,574 | 11.1 |
Hispanic | 5,758 | 728 | 12.6 |
Other | 4,463 | 477 | 10.7 |
Unknown | 5,620 | 630 | 11.2 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 3,079 | 384 | 12.5 |
Diabetesc | N/A | N/A | N/A |
Managed Care Status | |||
Enrolled in HMO | 10,393 | 1,191 | 11.5 |
Enrolled in BHO | 1,250 | 255 | 20.4 |
Enrolled in other MC | 5,539 | 695 | 12.5 |
Total | 84,192 | 8,878 | 10.5 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
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TABLE E.5b. Diabetes Screening Among Enrollees with Schizophrenia or Bipolar Disordera by State | |||
---|---|---|---|
State | Denominator | Diabetes Screen | |
N | N | Percent | |
AL | 3,253 | 420 | 12.9 |
AK | 245 | 21 | 8.6 |
CA | 31,796 | 3,758 | 11.8 |
CT | 2,442 | 689 | 28.2 |
DC | 1,284 | 52 | 4.0 |
GA | 4,683 | 148 | 3.2 |
ID | 824 | 69 | 8.4 |
IL | 9,515 | 562 | 5.9 |
IN | 3,031 | 543 | 17.9 |
IA | 1,251 | 255 | 20.4 |
LA | 3,499 | 382 | 10.9 |
MD | 4,094 | 93 | 2.3 |
MO | 5,030 | 427 | 8.5 |
MS | 2,392 | 232 | 9.7 |
NH | 377 | 83 | 22.0 |
NC | 4,735 | 452 | 9.5 |
ND | 171 | 35 | 20.5 |
NV | 756 | 67 | 8.9 |
OK | 2,318 | 278 | 12.0 |
SD | 217 | 53 | 24.4 |
WV | 2,148 | 253 | 11.8 |
WY | 131 | 6 | 4.6 |
Total | 84,192 | 8,878 | 10.5 |
SOURCE: 2007 MAX data.
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TABLE E.6a. Cardiovascular Health Screening Among Enrollees with Schizophrenia or Bipolar Disordera by Enrollee Characteristics | |||
---|---|---|---|
Characteristic | Denominator | Cardiovascular Screen | |
N | N | Percent | |
Gender | |||
Male | 45,195 | 19,384 | 42.9 |
Female | 52,338 | 23,423 | 44.8 |
Age | |||
25 - 30 | 10,773 | 3,870 | 35.9 |
31 - 40 | 20,926 | 8,507 | 40.7 |
41 - 50 | 35,219 | 15,599 | 44.3 |
51 - 60 | 26,032 | 12,553 | 48.2 |
61 - 64 | 4,584 | 2,279 | 49.7 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 32,001 | 11,752 | 36.7 |
Caucasian | 46,781 | 21,525 | 46.0 |
Hispanic | 7,043 | 3,657 | 51.9 |
Other | 5,256 | 2,732 | 52.0 |
Unknown | 6,453 | 3,142 | 48.7 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | N/A | N/A | N/A |
Diabetesc | 16,421 | 10,173 | 62.0 |
Managed Care Status | |||
Enrolled in HMO | 11,715 | 3,829 | 32.7 |
Enrolled in BHO | 1,501 | 654 | 43.6 |
Enrolled in other MC | 6,520 | 2,937 | 45.0 |
Total | 97,534 | 42,808 | 43.9 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
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TABLE E.6b. Cardiovascular Health Screening Among Enrollees with Schizophrenia or Bipolar Disordera by State | |||
---|---|---|---|
State | Denominator | Cardiovascular Screen | |
N | N | Percent | |
AL | 3,911 | 1,840 | 47.0 |
AK | 281 | 104 | 37.0 |
CA | 35,706 | 19,593 | 54.9 |
CT | 2,985 | 1,262 | 42.3 |
DC | 1,488 | 716 | 48.1 |
GA | 5,568 | 547 | 9.8 |
ID | 994 | 502 | 50.5 |
IL | 11,363 | 2,959 | 26.0 |
IN | 3,557 | 1,775 | 49.9 |
IA | 1,502 | 654 | 43.5 |
LA | 3,958 | 2,002 | 50.6 |
MD | 4,659 | 323 | 6.9 |
MO | 5,770 | 2,613 | 45.3 |
MS | 2,880 | 1,222 | 42.4 |
NH | 450 | 285 | 63.3 |
NC | 5,898 | 3,313 | 56.2 |
ND | 210 | 131 | 62.4 |
NV | 826 | 375 | 45.4 |
OK | 2,651 | 1,115 | 42.1 |
SD | 252 | 118 | 46.8 |
WV | 2,476 | 1,311 | 52.9 |
WY | 149 | 48 | 32.2 |
Total | 97,534 | 42,808 | 43.9 |
SOURCE: 2007 MAX data.
|
TABLE E.7a. Diabetes Monitoring Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | Diabetes Test | |
N | N | Percent | |
Gender | |||
Male | 6,919 | 3,557 | 51.4 |
Female | 10,107 | 5,330 | 52.7 |
Age | |||
25 - 30 | 676 | 347 | 51.3 |
31 - 40 | 2,298 | 1,226 | 53.4 |
41 - 50 | 6,135 | 3,195 | 52.1 |
51 - 60 | 6,509 | 3,398 | 52.2 |
61 - 64 | 1,409 | 722 | 51.2 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 7,125 | 3,203 | 45.0 |
Caucasian | 6,492 | 3,659 | 56.4 |
Hispanic | 1,403 | 801 | 57.1 |
Other | 904 | 592 | 65.5 |
Unknown | 1,103 | 633 | 57.4 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 1,755 | 882 | 50.3 |
Diabetesc | 17,027 | 8,888 | 52.2 |
Managed Care Status | |||
Enrolled in HMO | 1,486 | 638 | 42.9 |
Enrolled in BHO | 263 | 174 | 66.2 |
Enrolled in other MC | 1,231 | 732 | 59.5 |
Total | 17,027 | 8,888 | 52.2 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.7b. Diabetes Monitoring Among Enrollees with Schizophreniaa by State | |||
---|---|---|---|
State | Denominator | Diabetes Test | |
N | N | Percent | |
AL | 812 | 474 | 58.4 |
AK | 43 | 11 | 25.6 |
CA | 5,075 | 3,376 | 66.5 |
CT | 566 | 305 | 53.9 |
DC | 281 | 175 | 62.3 |
GA | 1,118 | 186 | 16.6 |
ID | 153 | 103 | 67.3 |
IL | 2,958 | 604 | 20.4 |
IN | 607 | 407 | 67.1 |
IA | 263 | 174 | 66.2 |
LA | 651 | 441 | 67.7 |
MD | 669 | 61 | 9.1 |
MO | 810 | 460 | 56.8 |
MS | 640 | 396 | 61.9 |
NH | 76 | 62 | 81.6 |
NC | 1,294 | 955 | 73.8 |
ND | 39 | 31 | 79.5 |
NV | 92 | 68 | 73.9 |
OK | 432 | 262 | 60.6 |
SD | 45 | 25 | 55.6 |
WV | 384 | 301 | 78.4 |
WY | 19 | 11 | 57.9 |
Total | 17,027 | 8,888 | 52.2 |
SOURCE: 2007 MAX data.
|
TABLE E.8a. Cardiovascular Health Monitoring Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | Cardiovascular Test | |
N | N | Percent | |
Gender | |||
Male | 2,218 | 1,250 | 56.4 |
Female | 2,482 | 1,378 | 55.5 |
Age | |||
25 - 30 | 81 | 45 | 55.6 |
31 - 40 | 333 | 189 | 56.8 |
41 - 50 | 1,529 | 852 | 55.7 |
51 - 60 | 2,185 | 1,234 | 56.5 |
61 - 64 | 572 | 308 | 53.8 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 2,027 | 999 | 49.3 |
Caucasian | 2,028 | 1,223 | 60.3 |
Hispanic | 232 | 160 | 69.0 |
Other | 136 | 91 | 66.9 |
Unknown | 277 | 155 | 56.0 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 4,700 | 2,628 | 55.9 |
Diabetesc | 1,755 | 1,074 | 61.2 |
Managed Care Status | |||
Enrolled in HMO | 317 | 121 | 38.2 |
Enrolled in BHO | 49 | 29 | 59.2 |
Enrolled in other MC | 307 | 180 | 58.6 |
Total | 4,700 | 2,628 | 55.9 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.8b. Cardiovascular Health Monitoring Among Enrollees with Schizophreniaa by States | |||
---|---|---|---|
State | Denominator | Cardiovascular Test | |
N | N | Percent | |
AL | 178 | 99 | 55.6 |
AK | 12 | 4 | 33.3 |
CA | 1,436 | 1,059 | 73.7 |
CT | 105 | 60 | 57.1 |
DC | 76 | 36 | 47.4 |
GA | 260 | 44 | 16.9 |
ID | 19 | 14 | 73.7 |
IL | 1,147 | 462 | 40.3 |
IN | 156 | 105 | 67.3 |
IA | 49 | 29 | 59.2 |
LA | 222 | 146 | 65.8 |
MD | 179 | 21 | 11.7 |
MO | 233 | 136 | 58.4 |
MS | 107 | 66 | 61.7 |
NH | 9 | 4 | 44.4 |
NC | 229 | 158 | 69.0 |
ND | 5 | 3 | 60.0 |
NV | 24 | 16 | 66.7 |
OK | 130 | 82 | 63.1 |
SD | 7 | 6 | 85.7 |
WV | 112 | 77 | 68.8 |
WY | 5 | 1 | 20.0 |
Total | 4,700 | 2,628 | 55.9 |
SOURCE: 2007 MAX data.
|
TABLE E.9a. Cervical Cancer Screening Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | Cervical Cancer Screen | |
N | N | Percent | |
Gender | |||
Male | 0 | 0 | 0.0 |
Female | 47,800 | 10,913 | 22.8 |
Age | |||
25 - 30 | 3,347 | 1,061 | 31.7 |
31 - 40 | 8,549 | 2,348 | 27.5 |
41 - 50 | 17,433 | 4,194 | 24.1 |
51 - 60 | 15,313 | 2,856 | 18.7 |
61 - 64 | 3,158 | 454 | 14.4 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 18,419 | 4,182 | 22.7 |
Caucasian | 20,105 | 4,723 | 23.5 |
Hispanic | 3,143 | 727 | 23.1 |
Other | 2,753 | 552 | 20.1 |
Unknown | 3,380 | 729 | 21.6 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 2,437 | 479 | 19.7 |
Diabetesc | 9,953 | 2,429 | 24.4 |
Managed Care Status | |||
Enrolled in HMO | 5,753 | 1,051 | 18.3 |
Enrolled in BHO | 757 | 249 | 32.9 |
Enrolled in other MC | 3,619 | 799 | 22.1 |
Total | 47,800 | 10,913 | 22.8 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.9b. Cervical Cancer Screening Among Enrollees with Schizophreniaa by States | |||
---|---|---|---|
State | Denominator | Cervical Cancer Screen | |
N | N | Percent | |
AL | 2,271 | 507 | 22.3 |
AK | 132 | 28 | 21.2 |
CA | 16,773 | 3,623 | 21.6 |
CT | 1,388 | 329 | 23.7 |
DC | 848 | 210 | 24.8 |
GA | 3,411 | 797 | 23.4 |
ID | 419 | 120 | 28.6 |
IL | 5,519 | 1,223 | 22.2 |
IN | 1,604 | 409 | 25.5 |
IA | 759 | 250 | 32.9 |
LA | 2,269 | 536 | 23.6 |
MD | 1,987 | 157 | 7.9 |
MO | 2,247 | 666 | 29.6 |
MS | 1,821 | 423 | 23.2 |
NH | 208 | 60 | 28.8 |
NC | 3,018 | 839 | 27.8 |
ND | 115 | 40 | 34.8 |
NV | 387 | 83 | 21.4 |
OK | 1,381 | 299 | 21.7 |
SD | 131 | 32 | 24.4 |
WV | 1,028 | 264 | 25.7 |
WY | 84 | 18 | 21.4 |
Total | 47,800 | 10,913 | 22.8 |
SOURCE: 2007 MAX data.
|
TABLE E.10a. ED Utilization for Mental Health Conditions Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | ED for Mental Health Conditionsb | |
N | N | Percent | |
Gender | |||
Male | 49,949 | 13,696 | 27.4 |
Female | 48,462 | 14,805 | 30.5 |
Age | |||
25 - 30 | 10,454 | 3,747 | 35.8 |
31 - 40 | 19,770 | 6,513 | 32.9 |
41 - 50 | 35,211 | 10,279 | 29.2 |
51 - 60 | 27,890 | 6,751 | 24.2 |
61 - 64 | 5,087 | 1,211 | 23.8 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 38,067 | 12,145 | 31.9 |
Caucasian | 41,105 | 11,978 | 29.1 |
Hispanic | 7,001 | 1,906 | 27.2 |
Other | 5,513 | 902 | 16.4 |
Unknown | 6,726 | 1,570 | 23.3 |
Comorbid Diagnoses | |||
Cardiovascular diseasec | 4,700 | 2,170 | 46.2 |
Diabetesd | 17,027 | 5,343 | 31.4 |
Managed Care Status | |||
Enrolled in HMO | 11,273 | 2,879 | 25.5 |
Enrolled in BHO | 1,372 | 409 | 29.8 |
Enrolled in other MC | 6,605 | 1,995 | 30.2 |
Total | 98,412 | 28,501 | 29.0 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.10b. ED Utilization for Mental Health Conditions Among Enrollees with Schizophreniaa by State | |||
---|---|---|---|
State | Denominator | SMI ED Useb | |
N | N | Percent | |
AL | 4,071 | 1,221 | 30.0 |
AK | 270 | 97 | 35.9 |
CA | 36,571 | 8,168 | 22.3 |
CT | 2,699 | 993 | 36.8 |
DC | 1,716 | 564 | 32.9 |
GA | 6,177 | 2,003 | 32.4 |
ID | 781 | 208 | 26.6 |
IL | 12,781 | 4,631 | 36.2 |
IN | 3,198 | 830 | 26.0 |
IA | 1,376 | 409 | 29.7 |
LA | 4,314 | 1,485 | 34.4 |
MD | 4,340 | 1,487 | 34.3 |
MO | 4,775 | 1,607 | 33.7 |
MS | 3,377 | 897 | 26.6 |
NH | 374 | 125 | 33.4 |
NC | 5,670 | 1,981 | 34.9 |
ND | 219 | 53 | 24.2 |
NV | 749 | 201 | 26.8 |
OK | 2,600 | 785 | 30.2 |
SD | 279 | 76 | 27.2 |
WV | 1,933 | 630 | 32.6 |
WY | 142 | 50 | 35.2 |
Total | 98,412 | 28,501 | 29.0 |
SOURCE: 2007 MAX data.
|
TABLE E.11a. 7-Day Follow-Up After Mental Health Discharge Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | 7-Day Follow-Up | |
N | N | Percent | |
Gender | |||
Male | 19,467 | 4,842 | 24.9 |
Female | 19,755 | 5,731 | 29.0 |
Age | |||
25 - 30 | 5,064 | 1,338 | 26.4 |
31 - 40 | 9,589 | 2,459 | 25.6 |
41 - 50 | 14,916 | 3,998 | 26.8 |
51 - 60 | 8,414 | 2,402 | 28.5 |
61 - 64 | 1,239 | 376 | 30.3 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 18,259 | 4,740 | 26.0 |
Caucasian | 15,042 | 4,724 | 31.4 |
Hispanic | 2,765 | 466 | 16.9 |
Other | 1,114 | 208 | 18.7 |
Unknown | 2,042 | 435 | 21.3 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 4,098 | 1,161 | 28.3 |
Diabetesc | 7,710 | 2,464 | 32.0 |
Managed Care Status | |||
Enrolled in HMO | 4,541 | 939 | 20.7 |
Enrolled in BHO | 725 | 272 | 37.5 |
Enrolled in other MC | 2,337 | 996 | 42.6 |
Total | 39,222 | 10,573 | 27.0 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.11b. 7-Day Follow-Up After Mental Health Discharge Among Enrollees with Schizophreniaa by State | |||
---|---|---|---|
State | Denominator | 7-Day Follow-Up | |
N | N | Percent | |
AL | 1,484 | 650 | 43.8 |
AK | 32 | 10 | 31.3 |
CA | 10,953 | 908 | 8.3 |
CT | 1,229 | 354 | 28.8 |
DC | 1,303 | 551 | 42.3 |
GA | 2,386 | 843 | 35.3 |
ID | 72 | 20 | 27.8 |
IL | 8,366 | 2,212 | 26.4 |
IN | 1,253 | 656 | 52.4 |
IA | 725 | 272 | 37.5 |
LA | 441 | 102 | 23.1 |
MD | 2,864 | 849 | 29.6 |
MO | 2,453 | 832 | 33.9 |
MS | 1,420 | 334 | 23.5 |
NH | 121 | 80 | 66.1 |
NC | 2,181 | 1,123 | 51.5 |
ND | 79 | 20 | 25.3 |
NV | 124 | 47 | 37.9 |
OK | 862 | 349 | 40.5 |
SD | 106 | 35 | 33.0 |
WV | 735 | 309 | 42.0 |
WY | 33 | 17 | 51.5 |
Total | 39,222 | 10,573 | 27.0 |
SOURCE: 2007 MAX data.
|
TABLE E.12a. 30-Day Follow-Up After Mental Health Discharge Among Enrollees with Schizophreniaa by Enrollee Characteristics (All States) | |||
---|---|---|---|
Characteristic | Denominator | 30-Day Follow-Up | |
N | N | Percent | |
Gender | |||
Male | 14,622 | 7,340 | 50.2 |
Female | 15,930 | 9,277 | 58.2 |
Age | |||
25 - 30 | 3,949 | 2,047 | 51.8 |
31 - 40 | 7,284 | 3,771 | 51.8 |
41 - 50 | 11,470 | 6,213 | 54.2 |
51 - 60 | 6,795 | 3,948 | 58.1 |
61 - 64 | 1,054 | 638 | 60.5 |
Unknown | 0 | 0 | 0.0 |
Race/Ethnicity | |||
African American | 13,734 | 7,230 | 52.6 |
Caucasian | 12,114 | 7,371 | 60.8 |
Hispanic | 2,135 | 883 | 41.4 |
Other | 924 | 387 | 41.9 |
Unknown | 1,645 | 746 | 45.3 |
Comorbid Diagnoses | |||
Cardiovascular diseaseb | 2,804 | 1,728 | 61.6 |
Diabetesc | 5,852 | 3,807 | 65.1 |
Managed Care Status | |||
Enrolled in HMO | 3,582 | 1,634 | 45.6 |
Enrolled in BHO | 597 | 470 | 78.7 |
Enrolled in other MC | 2,033 | 1,472 | 72.4 |
Total | 30,552 | 16,617 | 54.4 |
SOURCE: 2007 MAX data. HMO = health maintenance organization; BHO = behavioral healthcare organization; MC = managed care.
|
TABLE E.12b. 30-Day Follow-Up After Mental Health Discharge Among Enrollees with Schizophreniaa by State | |||
---|---|---|---|
State | Denominator | 30-Day Follow-Up | |
N | N | Percent | |
AL | 1,329 | 950 | 71.5 |
AK | 27 | 21 | 77.8 |
CA | 8,498 | 2,172 | 25.6 |
CT | 1,008 | 602 | 59.7 |
DC | 941 | 613 | 65.1 |
GA | 2,008 | 1,349 | 67.2 |
ID | 66 | 48 | 72.7 |
IL | 5,601 | 3,119 | 55.7 |
IN | 1,091 | 897 | 82.2 |
IA | 597 | 470 | 78.7 |
LA | 412 | 247 | 60.0 |
MD | 2,195 | 1,348 | 61.4 |
MO | 1,938 | 1,226 | 63.3 |
MS | 1,257 | 770 | 61.3 |
NH | 96 | 85 | 88.5 |
NC | 1,881 | 1,471 | 78.2 |
ND | 69 | 55 | 79.7 |
NV | 107 | 81 | 75.7 |
OK | 713 | 530 | 74.3 |
SD | 83 | 57 | 68.7 |
WV | 605 | 480 | 79.3 |
WY | 30 | 26 | 86.7 |
Total | 30,552 | 16,617 | 54.4 |
SOURCE: 2007 MAX data.
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TABLE E.13. Distributions of Measures at the State Level (N=22) | ||||||
---|---|---|---|---|---|---|
Measure | Minimum | 25th Percentile | Median | Mean | 75th Percentile | Maximum |
Schizophrenia | ||||||
Use of Antipsychotic Medications | 89.4 | 92.1 | 93.4 | 93.3 | 94.8 | 96.0 |
Antipsychotic Medication Possession Ratio | 48.3 | 62.6 | 65.7 | 65.7 | 70.9 | 84.6 |
Diabetes Monitoring | 9.1 | 55.6 | 62.1 | 57.3 | 67.7 | 81.6 |
Cardiovascular Health Monitoring | 11.7 | 44.4 | 59.6 | 54.5 | 67.3 | 85.7 |
Cervical Cancer Screening | 7.9 | 21.7 | 23.7 | 24.4 | 27.8 | 34.8 |
ED Utilization For Mental Health Conditions | 22.3 | 26.8 | 32.5 | 31.0 | 34.4 | 36.8 |
Follow-up After Mental Health Discharge (7-day) | 8.3 | 27.8 | 34.6 | 36.0 | 42.3 | 66.1 |
Follow-up After Mental Health Discharge (30-day) | 25.6 | 61.4 | 72.1 | 69.7 | 78.7 | 88.5 |
Schizophrenia or Bipolar Disorder | ||||||
Diabetes Screening | 2.3 | 8.4 | 10.3 | 12.1 | 17.9 | 28.2 |
Cardiovascular Health Screening | 6.9 | 42.1 | 46.1 | 43.4 | 50.6 | 63.3 |
SOURCE: 2007 MAX data. |
TABLE E.14. Utilization by Measure Performance Quartile | ||||
---|---|---|---|---|
Measure | Enrollees Hospitalized for Schzophrenia (Percentage) | Enrollees Hospitalized for Schzophrenia (Percentage) | ||
States in Bottom 25% | States in Top 25% | States in Bottom 25% | States in Top 25% | |
Schizophrenia | ||||
Use of antipsychotic medications | 18.5 | 10.5 | 21.2 | 22.3 |
Antipsychotic possession ratio | 14.0 | 15.5 | 23.4 | 23.3 |
Diabetes monitoring | 23.7 | 14.3 | 26.7 | 24.2 |
Cardiovascular health monitoring | 24.2 | 17.1 | 26.6 | 16.1 |
Cervical cancer screen | 17.9 | 18.4 | 15.8 | 21.2 |
Mental health follow-up (7 day) | 19.4 | 16.3 | 18.1 | 23.0 |
Mental health follow-up (30 day) | 19.3 | 16.0 | 18.6 | 19.1 |
Schizophrenia or Bipolar Disorder | ||||
Diabetes screening | 24.3 | 18.1 | 26.6 | 24.5 |
Cardiovascular health screening | 24.2 | 17.4 | 26.6 | 16.2 |
SOURCE: 2007 MAX data. NOTES: Lower rates of hospitalization and ED use hypothesized for enrollees in the top 25% for each measure. Hospitalization percentages significantly different at p<0.01 except Cervical Cancer Screen. ED percentages significantly different at p<0.01 except Use of Antipsychotic Medications, Antipsychotic Possession Ratio, and Mental Health Follow-up (30-day). |
TABLE E.15. Enrollee Level Correlation Matrix (2007) | |||||||||
---|---|---|---|---|---|---|---|---|---|
Antipsychotic Use | Antipsychotic Possession Ratio | Diabetes Screening | Diabetes Monitoring | Cardiovascular Screening | Cardiovascular Monitoring | Cervical Cancer Screen | ED Utilization (MH) | Follow-Up (7-Day) | |
Antipsychotic Use | |||||||||
Antipsychotic Possession Ratio | 0.000 | ||||||||
Diabetes Screening | 0.000 | 0.063 | |||||||
Diabetes Monitoring | 0.013 | 0.073 | 0.000 | ||||||
Cardiovascular Screening | 0.000 | 0.116 | 0.276 | 0.908 | |||||
Cardiovascular Monitoring | 0.039 | 0.073 | 0.198 | 0.888 | 0.000 | ||||
Cervical Cancer Screen | -0.008 | 0.028 | 0.050 | 0.082 | 0.112 | 0.104 | |||
ED Utilization (MH) | 0.031 | -0.138 | 0.013 | -0.038 | -0.026 | -0.033 | -0.013 | ||
MH Follow-up (7-day) | 0.092 | 0.103 | 0.014 | 0.081 | 0.068 | 0.095 | 0.051 | 0.060 | |
MH Follow-up (30-day) | 0.105 | 0.153 | 0.007 | 0.092 | 0.063 | 0.069 | 0.081 | 0.019 | 0.495 |
SOURCE: 2007 MAX data. |
TABLE E.16. State Measure Correlations, 2007-2008 (N=16) | |
---|---|
2007-2008 Correlation | |
Use of Antipsychotic Medications | 0.252 |
Antipsychotic Medication Possession Ratio | 0.550 |
Diabetes Screening | 0.330 |
Diabetes Monitoring | 0.453 |
Cardiovascular Health Screening | 0.426 |
Cardiovascular Health Monitoring | 0.403 |
Cervical Cancer Screen | 0.314 |
ED Utilization for Mental Health Conditions | 0.416 |
Follow-up after Mental Health Discharge (7-day) | 0.173 |
Follow-up: after Mental Health Discharge (30-day) | 0.202 |
SOURCE: 2007 and 2008 MAX data. |
Appendix F. Schizophrenia Quality Measures: Numerator, Denominator and Exclusion Criteria
TABLE F.1. Measure Criteria: Numerators, Denominators and Exclusions | |||
---|---|---|---|
Measure Title | Numerator | Denominator | Exclusions |
Use of Antipsychotic Medications | Individuals with schizophrenia prescribed any antipsychotic medication during the year. | Adults age 25-64 with a diagnosis of schizophrenia during the measurement year. | None. |
Antipsychotic Medication Possession Ratio | Individuals who achieved a PDCa of at least 80% for their antipsychotic medications during the measurement year. | Adults age 25-64 with a diagnosis of schizophrenia with a claim for any antipsychotic medication during the measurement year. | Individuals with fewer than 90 days in observation period. |
Diabetes Screening | Individuals with a CPT code for glucose screening: 82947, 82950, 82951, or ICD9 DX code V77.1. | Adults age 25-64 with a diagnosis of schizophrenia or bipolar disorder during the measurement year who received at least 2 months of an antipsychotic medication. | Individuals with diabetesb. |
Diabetes Monitoring | Individuals with a CPT code for HbA1c testing: 83036, 83037, 3044F, 3045F, 3046F, and any CPT code for LDL-C screening: 80061, 83700, 83701, 83704, 83721, 3048F, 3049F, 3050F. | Adults age 25-64 with a diagnosis of schizophrenia and diabetesb during the measurement year. | None. |
Cardiovascular Health Screening | Individuals with a CPT code for LDL-C screening: 80061, 83700, 83701, 83704, 83721, 3048F, 3049F, 3050F. | Adults age 25-64 with a diagnosis of schizophrenia or bipolar disorder during the measurement year who received at least 2 months of an antipsychotic medication. | Individuals who had diagnoses or CPT, HCPCS codes indicating CABG, PCI, CHF, IVD or MI during the measurement year. |
Cardiovascular Health Monitoring | Individuals with a CPT code for LDL-C testing: 80061, 83700, 83701, 83704, 83721, 3048F, 3049F, 3050F. | Adults age 25-64 with a diagnosis of schizophrenia and any codes indicating CABG, CHF, PCI, IVD or MI during the measurement year. | None. |
Cervical Cancer Screening | Individuals with a CPT code for cervical cancer screen. | Female adults age 25-64 with a diagnosis of schizophrenia. | Hysterectomy. |
ED Utilization for Mental Health Conditions | ED visit with a visit related diagnosis of 290, 293, 295-302, 306-316. | Adults age 25-64 with a diagnosis of schizophrenia during the measurement year. | None. |
Follow-up after Mental Health Discharge (7 days) | Any CPT, HCPCs or POS codes to identify follow-up visit within 7 days of discharge date. CPT=90804-90815, 98960-98962, 99078, 99201-99205, 99211-99215, 99217-99220, 99241-99245, 99341-99345, 99347-99350, 99383-99387, 99393-99397, 99401-99404, 99411, 99412, 99510. [90801, 90802, 90816-90819, 90821-90824, 90826-90829, 90845, 90847, 90849, 90853, 90857, 90862, 90870, 90875, 90876 (required POS=03, 05, 07, 09, 11, 12, 13, 14, 15, 20, 22, 24, 33, 49, 50, 52, 53, 71, 72)] [99221-99223, 99231-99233, 99238, 99239, 99251-99255 (require POS=52, 53)] HCPS=G0155, G0176, G0177, G0409-G0411, H0002, H0004, H0031, H0034-H0037, H0039, H0040, H2000, H2001, H2010-H2020, M0064, S0201, S9480, S9484, S9485. | Inpatient mental health discharges (ICD-9 diagnosis=290, 293, 295-302, 306-316) among adults age 25-64 with a diagnosis of schizophrenia. | None. |
Follow-up after Mental Health Discharge (30 days) | Any CPT, HCPCs or POS codes to identify follow-up visit within 30 days of discharge date. (See 7-day measure for listing of codes to identify outpatient follow-up visit). | Inpatient mental health discharges (ICD-9 diagnosis=290, 293, 295-302, 306-316) among adults age 25-64 with a diagnosis of schizophrenia. | None. |
NOTE: Schizophrenia identified by any inpatient primary diagnosis ICD-9 code of 295 or 2 primary outpatient ICD-9 codes of 295 observed on different days.
|