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The American Journal of Managed Care December 2018
Feasibility of Expanded Emergency Department Screening for Behavioral Health Problems
Mamata Kene, MD, MPH; Christopher Miller Rosales, MS; Sabrina Wood, MS; Adina S. Rauchwerger, MPH; David R. Vinson, MD; and Stacy A. Sterling, DrPH, MSW
From the Editorial Board: Jonas de Souza, MD, MBA
Jonas de Souza, MD, MBA
Risk Adjusting Medicare Advantage Star Ratings for Socioeconomic Status
Margaret E. O’Kane, MHA, President, National Committee for Quality Assurance
Reducing Disparities Requires Multiple Strategies
Melony E. Sorbero, PhD, MS, MPH; Susan M. Paddock, PhD; and Cheryl L. Damberg, PhD
Cost Variation and Savings Opportunities in the Oncology Care Model
James Baumgardner, PhD; Ahva Shahabi, PhD; Christopher Zacker, RPh, PhD; and Darius Lakdawalla, PhD
Patient Attribution: Why the Method Matters
Rozalina G. McCoy, MD, MS; Kari S. Bunkers, MD; Priya Ramar, MPH; Sarah K. Meier, PhD; Lorelle L. Benetti, BA; Robert E. Nesse, MD; and James M. Naessens, ScD, MPH
Patient Experience During a Large Primary Care Practice Transformation Initiative
Kaylyn E. Swankoski, MA; Deborah N. Peikes, PhD, MPA; Nikkilyn Morrison, MPPA; John J. Holland, BS; Nancy Duda, PhD; Nancy A. Clusen, MS; Timothy J. Day, MSPH; and Randall S. Brown, PhD
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Relationships Between Provider-Led Health Plans and Quality, Utilization, and Satisfaction
Natasha Parekh, MD, MS; Inmaculada Hernandez, PharmD, PhD; Thomas R. Radomski, MD, MS; and William H. Shrank, MD, MSHS
Adalimumab Persistence for Inflammatory Bowel Disease in Veteran and Insured Cohorts
Shail M. Govani, MD, MSc; Rachel Lipson, MSc; Mohamed Noureldin, MBBS, MSc; Wyndy Wiitala, PhD; Peter D.R. Higgins, MD, PhD, MSc; Sameer D. Saini, MD, MSc; Jacqueline A. Pugh, MD; Dawn I. Velligan, PhD; Ryan W. Stidham, MD, MSc; and Akbar K. Waljee, MD, MSc
The Value of Novel Immuno-Oncology Treatments
John A. Romley, PhD; Andrew Delgado, PharmD; Jinjoo Shim, MS; and Katharine Batt, MD
Medicare Advantage Control of Postacute Costs: Perspectives From Stakeholders
Emily A. Gadbois, PhD; Denise A. Tyler, PhD; Renee R. Shield, PhD; John P. McHugh, PhD; Ulrika Winblad, PhD; Amal Trivedi, MD; and Vincent Mor, PhD
Provider-Owned Insurers in the Individual Market
David H. Howard, PhD; Brad Herring, PhD; John Graves, PhD; and Erin Trish, PhD
Mixed Messages to Consumers From Medicare: Hospital Compare Grades Versus Value-Based Payment Penalty
Jennifer Meddings, MD, MSc; Shawna N. Smith, PhD; Timothy P. Hofer, MD, MSc; Mary A.M. Rogers, PhD, MS; Laura Petersen, MHSA; and Laurence F. McMahon Jr, MD, MPH

Relationships Between Provider-Led Health Plans and Quality, Utilization, and Satisfaction

Natasha Parekh, MD, MS; Inmaculada Hernandez, PharmD, PhD; Thomas R. Radomski, MD, MS; and William H. Shrank, MD, MSHS
The results of the study demonstrate the potential of provider-led health plans to deliver high-quality care and patient satisfaction. The relationships between these plans and outcomes differed by plan size, nonprofit status, and region.
ABSTRACT

Objectives: To compare healthcare quality, utilization, and patient satisfaction between provider-led health plans (PLHPs) and non-PLHPs.

Study Design: Observational study of 2016 Medicare Advantage (MA) plans.

Methods: We included 3 quality outcomes (MA Star Rating System, Healthcare Effectiveness Data and Information Set [HEDIS] effectiveness aggregate score, and HEDIS access aggregate score), 4 utilization outcomes (HEDIS average procedure rates, discharge rates, inpatient days, and readmission probability), and 1 patient satisfaction outcome (National Committee for Quality Assurance consumer satisfaction rating). We performed regression analysis to compare the 8 selected outcomes between PLHPs and non-PLHPs, controlling for key covariates, including region, profit status, patient risk, and patient-related and provider-related demographics.

Results: Our sample included 64 contracts offered by 31 PLHPs (representing 3,197,284 enrollees) and 311 contracts offered by 55 non-PLHPs (representing 13,881,210 enrollees). Compared with non-PLHPs, in our primary multivariable model, PLHPs were associated with higher star ratings (β = 0.41; 95% CI, 0.15-0.67), effectiveness scores (β = 3.11; 95% CI, 1.43-4.80), and patient satisfaction (β = 0.57; 95% CI, 0.30-0.84), and lower procedure rates (β = –0.47; 95% CI, –0.79 to –0.16). There were no significant differences in access, discharges, inpatient days, and readmission probability. The association between PLHPs and outcomes differed by plan size, nonprofit status, and region.

Conclusions: Receipt of care within a PLHP was associated with improved quality, effectiveness, and patient satisfaction, as well as lower procedure rates. As providers bear increasing financial risk under alternative payment models, there is momentum to integrate healthcare provision and payment through PLHPs. Our results demonstrate the potential of such organizations to deliver high-quality care, although opportunities remain to optimize utilization.

Am J Manag Care. 2018;24(12):628-632
Takeaway Points
  • In this cross-sectional study of 2016 Medicare Advantage plans, provider-led health plans (PLHPs) were associated with higher quality, effectiveness, and patient satisfaction and decreased procedure rates compared with non-PLHPs.
  • The association between PLHPs and outcomes differed by plan size, nonprofit status, and region.
  • There were no significant differences between PLHPs and non-PLHPs in access, number of inpatient discharges, duration of stay, and readmission probability.
  • As alternative payment models grow in popularity and momentum builds for providers to start their own health plans, our results demonstrate the potential of PLHPs to deliver higher-quality care and patient satisfaction, although opportunities remain to optimize utilization.
As healthcare providers accept increasing financial risk in alternative payment models, more provider organizations are expected to operate their own health insurance plans, known as provider-led health plans (PLHPs). Over the past 2 decades, PLHPs have become increasingly popular in the United States, with more than 100 plans covering more than 15 million individuals.1,2 Often referred to as vertical integration, the integration of healthcare providers and payers offers potential advantages to the patient, provider, and system. By inherently aligning payer–provider incentives and managing healthcare across a continuum of services, PLHPs may be particularly advantageous in population health management and, therefore, may have superior outcomes with lower premiums compared with non-PLHPs.1-8

Our knowledge of the impact of PLHPs on outcomes remains limited and inconsistent.1-14 For instance, critics of PLHPs argue that they are not consistently associated with higher-quality healthcare and can lead to increased costs due to greater market power and administrative costs.10-14 Furthermore, it remains unknown how PLHP characteristics, including size, region, and nonprofit status, may affect outcomes. For example, nonprofit plans may perform better than for-profit plans,15 and larger plans may perform better than smaller plans through increased experience.

The objectives of this study were therefore to (1) determine the association between PLHP status and healthcare quality, utilization, and patient satisfaction and (2) determine whether these associations differed by plan size, nonprofit status, and region.

METHODS

We conducted an observational study of Medicare Advantage (MA) contracts using December 2016 MA enrollment data from CMS. We focused on MA due to its large population and available outcome data that allow for standardized comparisons.16 We identified all MA contracts offered in 2016 with more than 20,000 enrollees to increase generalizability. For each contract, we obtained information on 3 quality outcomes, 4 utilization outcomes, and 1 patient satisfaction outcome. The quality outcomes were the 2017 MA Star Rating System (5-star maximum); 2016 Healthcare Effectiveness Data and Information Set (HEDIS) effectiveness aggregate score, defined as the average of 55 HEDIS Effectiveness of Care measures (100% maximum); and 2016 HEDIS access aggregate score, defined as the average of 2 HEDIS Access of Care measures (100% maximum). The utilization outcomes were 2016 HEDIS measures and included procedure rates, defined as average procedure rates per 1000 members for 13 selected procedures; discharge rates, defined as risk-adjusted discharges per 1000 members; inpatient days, defined as inpatient days per 1000 member-months; and risk-adjusted readmission probability. The patient satisfaction outcome was the 2016-2017 National Committee for Quality Assurance consumer satisfaction ratings, which are based on 2016-2017 Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys (5-point maximum) (see eAppendix Table 1 for outcome details [eAppendix available at ajmc.com]).

We categorized each MA contract as belonging to a PLHP or non-PLHP based on a publicly available list from the Robert Wood Johnson Foundation,10 which we enhanced to include additional PLHPs based on lists from McKinsey and Avalere (eAppendix Table 2).1,2,10,17 When there was uncertainty about PLHP status, we conducted an internet search to verify. We obtained region and profit status from the December 2016 MA enrollment list and patient risk from 2015 CMS plan payment data.18,19

To compare how outcomes differed between PLHP and non-PLHP contracts, we constructed multivariable linear regression models using generalized estimating equations with exchangeable correlation matrices to account for correlation between contracts within health plans. For example, Aetna’s health plan offered 25 MA contracts in our data set. The model controlled for accessible covariates identified as meaningful from existing literature,1,6,15 including MA region, contract profit status, average MA patient risk score, and the following covariates, all of which were derived from Area Health Resources Files20 and weighted for county contract enrollment: percent urban residence, percent black/African American, mean per capita income, college education among population 25 years or older, percent poverty among population 65 years or older, population 65 years or older per 1000 population, hospital beds per 1000 population, and active physicians per 1000 population. Each contract was analytically weighted by enrollee number.

We conducted subgroup analyses to evaluate how the association between PLHP contracts and outcomes differed by PLHP size, profit status (for-profit vs nonprofit), and MA region. To assess outcome differences by size, we compared outcomes of the 6 PLHPs with at least 100,000 enrollees (Kaiser Permanente, UPMC, Healthfirst, Spectrum, Innovacare, and Tufts) with those of the remaining PLHPs. To assess PLHP effects stratified by region, we mapped our model results for each MA region, differentiating areas where PLHPs performed significantly better than non-PLHPs, worse than non-PLHPs, or where there was no difference. Subgroup analyses were based on the multivariable model above, except for regional analyses. Regional analyses only adjusted for profit status and patient risk score because the inclusion of additional covariates prevented the model from producing estimates for many regions. Finally, to explore whether our findings were driven by Kaiser Permanente, a notably high-quality plan, we ran our base-case models after excluding Kaiser Permanente contracts.

Analyses were performed using Stata 14 (StataCorp LP; College Station, Texas) and SAS 9.4 (SAS Institute Inc; Cary, North Carolina). Further information on data sources, variable definitions, and missing data is available in eAppendix Table 1 and eAppendix Table 3.


 
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