Recommendations for Monitoring Access to Care among Medicaid Beneficiaries at the State-level. Recommended Indicators of Access for Medicaid Beneficiaries

02/01/2013

Understanding the need for HHS to assess access for the Medicaid population in the near term, NORC developed several indicators that can be used immediately while progress continues toward longer-term recommendations for indicators. Based on the findings from the environmental scan and TEP discussions, NORC selected measures identified by the TEP as high-priority indicators of access for Medicaid enrollees which can be operationalized using current data sets in all states, or at least a majority of states.

Even accounting for the limitations described in the findings section, a set of indicators can be constructed for all three facets of access: for consumer perceptions using BRFSS and NHIS, for provider reports using the NAMCS-EMR,[17] and for realized access using MSIS. These measures can be used immediately to establish baseline levels of access for the Medicaid population at the state-level. These indicators are included in Exhibit 1 and additional detail on constructing the measures is available in Appendix D.

Exhibit 1. Recommended Indicators by Data Source

Consumer Perceptions: BRFSS

 

Major Limitation: Before 2013 there is no Medicaid specific measure and beyond 2013 it is unknown if there will be a specific measure of Medicaid coverage. Income is only measured categorically. Does not include data on children under 18.

Consumer Perceptions: NHIS

 

Major Limitation: State estimates only available for 32 largest states and a smaller number of states are likely to have an adequate effective sample size for the Medicaid enrolled population. Access to state data is limited to NCHS RDC.

Provider Reports: NAMCS-EMR

 

Major Limitation: Access to state-level identifiers limited to NCHS RDC.

 

Realized Access:
MSIS

Major Limitation: Limited understanding of state-level variation and ability to make cross-state comparisons. Largely limited to Medicaid Fee For Service.

% of low-income adults with access to a usual source of care

 

% of Medicaid population with a usual source of care

% physicians accepting new patients (by primary care providers and specialists)

% eligible FFS beneficiaries with at least one service

% of low-income adults who forewent receiving care because it was unaffordable

Type of usual source of care

% physicians accepting new Medicaid patients (by primary care providers and specialists)

% eligible FFS beneficiaries with at least one ambulatory care visit

% of low-income adults without a preventive care visit in the last 2 years

% with Medicaid coverage that delayed medical care due to cost

% of physician patient population with Medicaid/CHIP (by primary care providers and specialists)

% eligible FFS beneficiaries with at least one specialty care (aggregate) visit

 

Interval since last doctor visit

% physician revenue from Medicaid (by primary care providers and specialists)

% eligible FFS beneficiaries with at least one specialty care (specific) visit

 

% who experienced trouble finding a general doctor or provider

% physicians accepting new Medicaid patients in practices with mid-level providers (e.g., NP, PA) (by primary care providers and specialists)

Number of participating providers (using NPI)

 

% with Medicaid coverage who were not accepted as new patients

 

Number and range of FFS beneficiaries served per provider

 

% with Medicaid coverage who visited doctors' offices that did not accept their form of health insurance

 

 

 

% with Medicaid coverage who delayed getting medical care because they could not get an appointment soon enough

 

 

 

These indicators can be stratified to examine access to care issues for different types of Medicaid beneficiaries. It should be acknowledged that stratifying the sample by demographic or other variables will exacerbate the sample size issues. However, the Exhibit 2 includes recommendations for potential stratifying variables when the state sample size permits.

Exhibit 2. Potential Stratifying Variables by Data Source

Data Source

Stratifying Variables

BRFSS

Race, ethnicity, age, gender, categorical household income, insurance coverage, state, MSA

NHIS

Race, ethnicity, age, gender, family income relative to poverty, Medicaid enrollment, type of insurance coverage, state, urban/rural residence

NAMCS & NAMCS-EMR

Physician Characteristics: State, race, ethnicity, age, gender, physician type (MD, DO), specialty group, employment

Practice Characteristics: Office setting, practice ownership, practice size, solo, MSA

MSIS

Race, ethnicity, age, sex, basis of eligibility category, TANF, dual-eligible

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