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The American Journal of Managed Care May 2018
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Changes in Specialty Care Use and Leakage in Medicare Accountable Care Organizations

Michael L. Barnett, MD, MS, and J. Michael McWilliams, MD, PhD
Reducing specialty leakage is promoted as crucial for accountable care organizations (ACOs). This study finds that Medicare ACOs had modest reductions in specialty use and minimal changes in leakage.
Statistical Analysis

We conducted 2 sets of analyses, one a set of descriptive analyses among ACO-attributed beneficiaries and the other a set of quasi-experimental analyses that also included beneficiaries attributed to non-ACO providers as a control group. The purpose of the descriptive analyses was to characterize trends in leakage, contract penetration, and stability of attribution from 2010 to 2014 among ACO-attributed beneficiaries. These analyses lacked a control group because we could only identify collections of practices forming ACOs for ACOs, as claims data do not include indicators of organization above the level of a TIN, which may refer to an individual physician, a practice site, a multisite practice, or a large provider group or health system. For analyses of leakage, we focused on the most specialty-oriented ACOs (those with proportions of specialists in the top quartile among ACOs) to characterize levels and trends among ACOs with the greatest opportunity for limiting leakage. In the extreme, ACOs composed entirely of PCPs leak 100% of specialty care. Therefore, examining trends in leakage for such ACOs would be uninformative. We conducted complementary analyses of trends in use of specialist visits inside versus outside ACOs to describe the source of any changes in leakage.

For contract penetration, we stratified ACOs by quartile of specialty orientation to describe how levels and trends varied across the full spectrum of specialty mix. To determine if changes in care patterns might be due to changes in population of beneficiaries attributed to ACOs, we examined the characteristics of ACO-attributed patients over time.

In our second set of analyses, we used linear regression and a difference-in-differences (DID) approach to estimate changes in use of specialist office visits from the precontract to postcontract period that differed from concurrent changes in the control group of beneficiaries attributed to non-ACO practices. The regression models adjusted for all patient characteristics and fixed effects for each hospital referral region (HRR) by year combination to compare ACO-attributed beneficiaries with beneficiaries in the control group living in the same area, and to adjust for concurrent regional changes in use of specialist visits occurring in the control group. Models also included fixed effects for each ACO to adjust for precontract differences between ACOs and the control group and for any changes in the distribution of ACO-attributed beneficiaries across ACOs over the study period. Thus, this analysis compared utilization in the postcontract period for ACO-attributed patients with utilization that would be expected in the absence of ACO contracts, using local changes in a similar population to establish that counterfactual scenario.

We estimated effects separately for each entry cohort of ACOs, allowing each cohort to have a different precontract period (2010-2011 for the 2012 entry cohort, 2010-2012 for the 2013 cohort, and 2010-2013 for the 2014 cohort). Because ACOs with the fewest specialists have the strongest financial incentives to reduce use of specialty care by their attributed beneficiaries, we estimated effects of MSSP participation separately for ACOs in the lowest quartile of specialty orientation (the most primary care–oriented) versus all other ACOs by adding interaction terms to DID models. 

We used robust variance estimators to account for clustering of beneficiaries within ACOs (for the ACO group) or HRRs (for the control group). In sensitivity analyses, we fit generalized linear models with a log link and proportional to mean variance function, as well as 2-part models separately modeling any specialty use among all beneficiaries and the number of specialist visits conditional on some use.

To assess for potential selection bias in our DID analyses, we compared trends in use of specialist visits between the ACO and control groups during the precontract period to check if trends were already diverging or converging. We also tested whether patients’ sociodemographic and clinical characteristics differentially changed from the precontract to postcontract period in the ACO group relative to the control group.

RESULTS

Patterns of Outpatient Care Among ACOs

The characteristics of patients attributed to ACOs were stable over the study period, with minimal changes in each MSSP cohort from before to after the start of ACO contracts (Table 1).35 The 25 most common primary diagnoses for new specialist visits in all MSSP cohorts in 2014 prominently featured musculoskeletal problems (limb, joint, and back pain), common skin conditions (nail dermatophytosis, seborrheic keratosis), and diagnoses often managed primarily by PCPs (hypertension, diabetes) (eAppendix Table 1 [eAppendix available at ajmc.com]).

Contract penetration varied widely by ACO specialty orientation but changed minimally over time (Figure 1). In the 2012 MSSP entry cohort of ACOs, for example, contract penetration ranged from 47% in 2014 for the most specialty-oriented quartile of ACOs to 85% for the least specialty-oriented quartile. Thus, for ACOs composed entirely or almost entirely of PCPs, MSSP contracts covered a high proportion of Medicare revenue for outpatient care.

From 2010 to 2014, leakage decreased slightly in 2 MSSP cohorts, from 70% to 68% in the 2012 entrants and from 64% to 61% in the 2013 entrants (Figure 2). These changes were driven primarily by rising use of specialist visits within ACOs without concurrent decreases in use of specialist visits outside of ACOs, such that total use of specialist visits rose slightly for ACO-attributed patients over the study period (Figure 2).

For new specialist visits, trends in leakage were similar, except that modest reductions in leakage occurred in all 3 MSSP cohorts (Figure 3). The largest decline in leakage of new specialist visits occurred in the 2013 cohort, from 66% in 2010 to 62% in 2014. As with total specialist visits, reductions in leakage of new specialist visits were largely driven by increased use inside of ACOs.

For both overall specialist visit use and new specialist visit use, the modest reductions in leakage began prior to entry into the MSSP, without clear acceleration after entry (Figure 2). Rates of leakage were higher for ACOs with lower proportions of specialists, but trends were generally similar (eAppendix Figures 1-4).

Stability of beneficiary attribution to ACOs changed minimally across all 3 MSSP cohorts (eAppendix Table 2). For example, in the 2012 cohort of ACOs, the average proportion of beneficiaries who were assigned to the same ACO as in the previous year was 77.2% in 2010 and 75.3% in 2014.

Association Between MSSP Participation and Changes in Use of Specialist Visits

Tests of key assumptions supported inferences from DID analyses. For each MSSP cohort, the characteristics of attributed patients changed minimally relative to the control group (eAppendix Tables 3-5). In the precontract period, rates of specialist visit use were generally similar among the MSSP ACO cohorts and the control group, with some small statistically significant differences, and precontract annual trends in specialist visit use differed minimally among the ACO and control groups (eAppendix Table 6).

For the most primary care–oriented quartile of ACOs in the 2012 entry cohort (<13% specialists), MSSP participation was associated with a significant reduction in overall annual use of specialist visits (differential change: –0.10 visits/beneficiary or –2.1% of the precontract mean of 4.77 visits/beneficiary; P = .002) and a more prominent differential reduction in annual use of new specialist visits (–0.037 visits/beneficiary or –5.0% of the precontract mean of 0.746 visits/beneficiary; P <.001) (Table 2). These reductions grew over time from 2013 to 2014 (eAppendix Table 7). In contrast, differential changes in use of specialist visits were small and not statistically significant in the 2012 cohort for other ACOs with more specialists.

In the 2014 cohort, MSSP participation was similarly associated with a differential reduction in use of new specialty visits for primary care–oriented ACOs (–0.023 visits/beneficiary or –3.1% of the precontract mean; P <.001) but not for other, more specialty-oriented ACOs (Table 2). In the 2013 cohort, MSSP participation was associated with modest differential decreases in use of new specialist visits and all specialist visits for primary care–oriented ACOs and with modest differential increases in use for other ACOs, but these differential changes were not statistically significant. Estimates from generalized linear models with a log link and 2-part models were consistent with our main results.



 
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