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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
Currently Reading
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
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
Primary Care Burnout and Populist Discontent
James O. Breen, MD
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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

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
Reliable identification of the physician–patient relationship is necessary for accurate evaluation. Standardization of evidence-based attribution methods is essential to improve the value of healthcare.
RESULTS

Patient Characteristics Across Attribution Methods

In 2011, 146,469 patients were paneled to a PCP. Another 4494 patients who were not paneled to a PCP in 2011 were attributed by at least 1 method. Between 61,813 (42%) and 106,152 (72%) of paneled patients were attributed to any PCP by the 5 attribution methods, although not necessarily to the paneled PCP (Figure 1). Overall, the ACO method attributed the highest number of patients to MCR providers (n = 108,589) and had the highest proportion of attributed-matched patients (60.6%). In contrast, the HP method attributed the fewest (n = 63,837) patients and also had the lowest proportion of attributed-matched patients (51.5%). In general, the 3 methods that allowed 2 years of data to be used for attribution (ie, ACO, private payer, MNCM) attributed more patients.

All methods had more attributed-matched than attributed-unmatched patients (Figure 1). The ratio of attributed-matched to attributed-unmatched patients ranged from 1.1 for the HP method to 2.0 for the private payer method; a higher ratio is indicative of more accurate PCP matching. The proportion of paneled patients who were not attributed despite having billed services during the measurement period varied from less than 28% using the ACO method to almost 58% using the HP method.

Patients attributed by the 5 methods differed on key demographic, payer, and clinical characteristics. Overall, attributed patients were older, had higher prevalence of chronic disease, and had higher ACG weights than paneled patients (attributed or not) (Table 2). The ACO method, which attributed the largest proportion of patients overall, had younger patients with the lowest mean ACG weight; it attributed nearly all paneled patients with the chronic conditions examined. In contrast, the HP method, which attributed the fewest patients overall, yielded a cohort with older patients and attributed a higher proportion of patients with chronic diseases.

Healthcare Utilization and Total Cost of Care

Healthcare utilization and total standardized costs of care varied for attributed patients across all methods (Table 3). Methods attributing fewer patients had higher total costs of care during the year of attribution. Mean costs were highest for patients attributed by the HP method and lowest for patients attributed by the ACO method. Differences in mean cost between methods were driven by the type of patients attributed. As shown in Figure 2, the ACO method captured a higher proportion of primary care patients in each cost category, but it also attributed a much larger portion of patients who had no healthcare costs in 2011.

Generally, attributed patients had higher healthcare utilization than unattributed patients (Table 3). Mean OP, IP, and ED utilization were lowest when measured with the ACO method. Patients attributed by the public payer and HP methods had the highest IP and ED use in both 2011 and 2012. Total costs of care in 2011 were also highest among patients attributed by the public payer method, whereas patients attributed by HP had highest mean costs in 2012. The ACO and public payer methods attributed almost all patients with 2011 costs exceeding $100,000.

Quality Measures

Both the number of patients included in the assessment (measure denominator) and the percentage of compliance with the 4 chronic disease quality measures differed by attribution method (Table 3). Nonetheless, quality measure compliance rates were comparable across attribution methods.


 
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