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Payer Effects of Personalized Preventive Care for Patients With Diabetes
Brant Morefield, PhD; Lisa Tomai, MS; Vladislav Slanchev, PhD; and Andrea Klemes, DO
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Payer Effects of Personalized Preventive Care for Patients With Diabetes

Brant Morefield, PhD; Lisa Tomai, MS; Vladislav Slanchev, PhD; and Andrea Klemes, DO
We examine the effects of MD–Value in Prevention (MDVIP) enrollment on Medicare expenditures and utilization among fee-for-service beneficiaries with diabetes over a 5-year period.
ABSTRACT

Objectives:
To examine the effects of MD–Value in Prevention (MDVIP) enrollment on Medicare expenditures and utilization among fee-for-service (FFS) beneficiaries with diabetes over a 5-year period.

Study Design: We obtained participating physician and beneficiary enrollment lists from MDVIP and Medicare FFS claims data through the Virtual Research Data Center to compare changes in outcomes, before and after enrollment dates, with those of nonenrolled beneficiaries receiving primary care in the same local market.

Methods: We employed propensity score matching to identify comparison beneficiaries similar in observed characteristics and preenrollment trends. Individual fixed effects were used to control for time-consistent differences between treatment and comparison populations.

Results: We found that enrollment is statistically associated with reductions in outpatient expenditures, Medicare expenditures in year 5, emergency department (ED) utilization, and unplanned inpatient admissions, accompanied by significant increases in evaluation and management visits and expenditures. Total Medicare expenditures over the 5-year period, as well as all inpatient admissions, were not statistically different between the MDVIP and comparison groups.

Conclusions: Our finding of reduced unplanned inpatient admissions and ED utilization supports the previous findings regarding MDVIP enrollees. We did not find significant changes in overall third-party expenditures, although savings were estimated in year 5, the last year of observation, and may occur later. Our approach, however, strengthens controls for baseline characteristics of the population and uses a comparison population drawn from the same markets who do not experience the loss of their primary care physician at the time of enrollment.

Am J Manag Care. 2020;26(3):e70-e75. https://doi.org/10.37765/ajmc.2020.42638
Takeaway Points

We used claims data to examine how healthcare utilization and third-party Medicare expenditures change after individuals with diabetes enroll in the MD–Value in Prevention (MDVIP) model.
  • Changes from before to after enrollment were compared with changes among selected similar individuals in the same healthcare market.
  • After MDVIP enrollment, outpatient expenditures, emergency department utilization, and unplanned admissions were lower than expected.
  • After enrollment, individuals received more evaluation and management visits and, relatedly, had higher Part B expenditures than expected.
  • We did not find significant changes in overall third-party expenditures, although savings were estimated in year 5, the last year of observation, and may occur later.
Numerous primary care physicians and patients voluntarily participate in personalized primary care arrangements, sometimes referred to as concierge medicine or retainer medicine. MD–Value in Prevention (MDVIP) is a large, geographically diverse example of such a model. MDVIP members pay an annual fee (average of $1800 in 2020) and, in return, receive a personalized wellness plan, including screenings and diagnostic tests, diet and exercise planning, and other services, such as same-day appointments and a physician who is reachable 24/7.1 To provide such care, MDVIP-affiliated physicians agree to serve a panel of 600 or fewer patients1 compared with a national average panel size of 2300 patients for internal medicine and family practice physicians.2 We examined patients enrolled in MDVIP and matched comparisons to investigate whether the MDVIP model affects healthcare utilization and third-party payer expenditures for a population with a diagnosis of diabetes.

Prior research suggests that enrollment in MDVIP reduces utilization of inpatient or emergency department (ED) services. Musich et al analyzed medical utilization of MDVIP members in comparison with a sample of Medicare Advantage beneficiaries who did not join the model and showed that participation in MDVIP led to savings in medical expenditures for 2 years after joining, resulting from reduced hospitalizations and ED visits.3 Similar reductions in healthcare utilization related to MDVIP membership were found by Klemes et al4 and Musich et al,5 who used patient-level data from 5 states within the Intellimed data set and a sample of patients with a UnitedHealthcare employer-sponsored health plan, respectively. Our study continues this evidence base by examining the role of the MDVIP model on third-party Medicare fee-for-service (FFS) expenditures and healthcare utilization for the older Medicare FFS population. Further, we chose to focus on a population with diabetes, a common and costly chronic condition, because patients with chronic conditions may experience differential effects of personalized primary care arrangements from those presented in prior research.

As physician and patient participation is voluntary and involves enrollment fees for patients, we expect that MDVIP physicians and patients may differ from others who are part of the Medicare FFS population. A review of the work of Klemes et al4 by the American College of Physicians raised questions regarding identification of an MDVIP effect without further adjustment for baseline health and socioeconomic factors.6 We addressed such factors in this study by matching comparison beneficiaries on observed characteristics, including baseline health, and controlling for time-consistent unobserved characteristics using fixed effects.

METHODS

We obtained lists of MDVIP-participating physicians and MDVIP-enrolled beneficiaries 65 years or older, as well as their associated program enrollment dates, from MDVIP, and 2000-2015 Medicare claims (parts A and B) and Master Beneficiary Summary File Chronic Conditions segment data from the Virtual Research Data Center. The Chronic Conditions segment applies algorithms to identify the incidence of chronic conditions based on diagnosis and service codes in beneficiaries’ claims histories. We used these chronic condition flags to identify beneficiaries meeting the diabetic criteria at the time of MDVIP enrollment or potential enrollment.

Study Populations

We first identified all Medicare FFS beneficiaries receiving at least 1 Part B service from an MDVIP-affiliated physician in a 15-month period ending when the physician joined MDVIP, including both beneficiaries who did and did not join the MDVIP model. Among beneficiaries receiving care from future MDVIP-affiliated physicians, we cross-referenced sex, date of birth, and zip code in Medicare records with MDVIP enrollment files. Using this approach, we uniquely identified 90% of FFS beneficiaries listed by MDVIP.

We also identified unaffiliated primary care physicians operating in the same primary care service area (PCSA) and the population of patients receiving care from these non-MDVIP physicians in the 15 months prior to when the MDVIP physicians joined. As such, we selected a population of potential comparison beneficiaries who received primary care in the same market at the same time as beneficiaries who enroll in MDVIP, where markets are defined as PCSAs.7

Because more than 90% of beneficiaries enrolled in MDVIP within 30 days of their providers’ enrollment, and 95% within 90 days, we used the providers’ enrollment dates as the start of MDVIP for the enrolled population. For beneficiaries seeing non-MDVIP providers, the intervention start date was defined as the enrollment date of the linked local MDVIP provider.

From the providers’ enrollment dates, we extracted beneficiaries’ Medicare FFS claims 3 years prior to and up to 5 years post enrollment. We only included years in which the beneficiary was enrolled in Medicare Part A and Part B and not enrolled in Medicare managed care.


 
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