Understanding the High Prevalence of Low-Prevalence Chronic Disease Combinations: Databases and Methods for Research. Utah Department of Health Dataset


Utah All Payer Claims Database


Office of Health Care Statistics Utah Health Data Committee. The Utah All Payer Claims Database (APCD). 2013. http://health.utah.gov/hda/apd/

Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities.
Sponsorship: Office of Health Care Statistics; Utah Health Data Committee; Utah Department of Health
Description: The Utah All Payer Claims Database (APCD) became the fifth operating APCD in the nation on September 13th, 2009 with the receipt of the very first data submissions. Participating plans submit enrollment, medical, and pharmacy files starting from 1/1/2007 until they are current. As of 2010, there are 11 plans in full production; that is, they have submitted all required historic data and are reporting new data on determined schedule
Database: (Scope, Size, Setting, Population, Age Range) State of Utah; all-payer claims data.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Claims and administrative enrollment files. All payer claims database.
Database Source/Origin: Medicaid Claims, CHIP, PPO’s and HMO’s in Colorado, Medicare claims are pending inclusion due to cost/infrastructure.
Date or Frequency of Data Collection:

Inpatient Hospital Discharge Data (1992–2010)

Ambulatory Surgery Data (1996–2009)

Emergency Department Data (1996–2010)

Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: Health insurance carriers are required to submit health insurance files.
Sampling Strategy: All patients receiving and paying for healthcare services in the State of Utah.
Unit of Analysis: Patient
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis)

Principal Diagnosis

Secondary Diagnosis

Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9 or ICD-10
Number of Diagnoses Captured: Up to nine diagnoses are captured for each patient.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Total Charges, Facility Charges, and Professional Charges
Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type of Procedure, Number of Admission/Type of Admission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.)

Length of Stay


Type of Procure


Measures of Healthcare Access: Yes, but specific measures not reported.
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Age, Gender, Marital Status, and Race/Ethnicity.
Clinical Information: (BMI, Medical Conditions [high blood pressure], Smoker Status, History of Various Conditions, Preventative Health Measures , Activities of Daily Living, Instrumental Activities of Daily Living) Yes, extensive clinical data from EHRs.
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) Place of Residence
Site of Service Information: Zip Code, Residential County
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions)

Discharge Status

Patient Severity Subclass Values

Patient Risk of Mortality Values

Strengths, Limitations & Feasibility
Data Strengths: Large patient sample size; represents all types of payment sources.
Data Limitations: Only representative of the State of Utah; still in development and missing claims data for some periods of time.
Data Access Restrictions: Some files are publically available. However, more advanced files for health care cost, quality and access need to be purchased after IRB and HDC consent is achieved.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) Patient and Physician Identifiers. Data is very easy to link; there are a number of personal identifiers.
Related Grouping Systems: All ICD-related grouping systems.


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