Evaluating the Quality and Value of U.S. Ambulatory Care Delivered Among Medicaid Expansion States and Non-Expansion States, 2012-2015
Evaluating the Quality and Value of U.S. Ambulatory Care Delivered Among Medicaid Expansion States and Non-Expansion States, 2012-2015
Quasi-experimental pre-post analysis of the rate of high-value and low-value care services between states that expanded Medicaid and states that did not expand Medicaid January 1, 2014, for adult ambulatory visits, using visit-level survey data from the National Ambulatory Medical Care Survey January 1, 2012 - December 31, 2015.
Data Source: Visit level data obtained from the National Ambulatory Medical Care Survey (NAMCS) between January 1, 2012-December 31, 2015.
Identification of Observations (Visits) for Primary Analysis: Adult visits in states that did expand Medicaid January 1, 2014 (experimental group) and states that did not expand Medicaid January 1, 2014 (control group). Eight Medicaid expansion states (experimental group): Arizona, California, Illinois, Massachusetts, New Jersey, Ohio, Washington Five states that did not expand Medicaid (control group): Florida, Georgia, North Carolina, Texas, Virginia. Visits will be included only if they could receive a low value service (visits for back pain, headache, general medical exam, URI) or high value service (visits with patients who have CAD, DM, CVD, Depression, CHF, Osteoporosis and no exclusion to receive the indicated high value service) when evaluating low value service counts and high value service counts respectively as opposed to all adult visits regardless of the opportunity to receive a high value or low value care service (e.g. visit for hand pain and none of the high or low value areas above.)
Identification of Observations (Visits) for Secondary Analyses: Medicaid patient subpopulation will be defined as those visits for primary analysis that are coded with Medicaid as a pay type for the visit. "New" Medicaid patient subpopulation will be defined as those visits for primary analysis that are coded with Medicaid as a pay type, have not seen before, to a provider who is accepting new patients and accepts Medicaid for new patients.
Create Indicator Variables for Primary and Secondary Outcome Analyses: Develop a set of low value and high value services with distinct inclusion and exclusion criteria for each service. Create indicator variable for each high value and low value service. Low value care measures (Imaging for Low Back Pain, Opioid for Low Back Pain, Opioid for Headache, Imaging for Headache, Antibiotic for Upper Respiratory Infection, General Medical Examination with ECG ordered, General Medical Examination with Urinalysis ordered.) High value care measures (Antiplatelet for CAD, Beta Blocker for CAD, Statin for CAD, Anticoagulation for Atrial Fibrillation, Statin for DM, Antiplatelet CVD, Treatment for Depression, Beta Blocker for CHF, ACE/ARB/ARNI for CHF, Treatment for Osteoporosis)
Analysis: Evaluate for pre-intervention (Medicaid Expansion) parallel trends (This has already been established). Then perform pre-post difference-in-differences analyses of primary and secondary outcomes between the experimental group (states that expanded Medicaid) and control group (states that did not expand Medicaid). Regression analysis will be performed to adjust for respondent age, sex, race/ethnicity, number of chronic illnesses, and clinic rural/urban location. Stratified models based on payer type will allow for analyses of the Medicaid population. Perform sensitivity analyses of primary and secondary outcomes.
Inclusion Criteria:
Exclusion Criteria: