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The American Journal of Managed Care December 2018
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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
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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.
METHODS

Patients and Setting

This is a cross-sectional study of patients who received primary care at MCR or were paneled to an MCR PCP between January 1, 2011, and December 31, 2011 (N = 150,963). MCR is an integrated healthcare delivery system based in Rochester, Minnesota, that serves local (47.7%), regional (21.3%), national (29.6%), and international (1.4%) patients. All primary care patients (people residing in the local catchment area, as well as MCR employees and dependents) are assigned (paneled) to a PCP in order to provide continuity of care and optimize population health management. Patients are paneled to any available PCP and are typically paneled prior to being seen. Empanelment is not contingent on past or future encounters with the paneled PCP. Patients are administratively removed from a panel if they are inactive in the MCR system for 3.5 years. Approximately 10% of patients on primary care panels at MCR changed panel status from 2010 to 2011.

Patients are seen in 1 of 6 primary care clinics: 3 urban, 2 suburban, and 1 rural. MCR PCPs include physicians in family medicine (n = 29), internal medicine (n = 201), and pediatrics (n = 70); residents in these 3 specialties (n = 223); and family medicine–trained advanced practice providers (APPs), including nurse practitioners (n = 44) and physician assistants (n = 29). Graduate medical education residency programs last 3 years and begin and end on approximately July 1; therefore, one-third of patients on trainee panels are expected to change PCP midyear.

We also identified patients who were not paneled to an MCR PCP but were nonetheless assigned to an MCR PCP by 1 or more methods during the 2011 calendar year. Most of these patients received either acute or urgent care. Two general internal medicine groups and 1 pediatrics group serve patients living outside the local area in a consultative practice. They do not provide continuity of care and therefore are not considered PCPs.

The study was deemed exempt from institutional review board review because it involved analysis of pre-existing data.

Attribution Methods

We examined 5 patient attribution methods with methodological variability. They are summarized in Table 118,20,21 and, in greater detail, the eAppendix Table (eAppendix available at ajmc.com). The methods were the (1) Dartmouth (“ACO”) method20 used by CMS for Medicare accountable care organization (ACO) attribution and Medicare Shared Savings Program, (2) public health plan (“public payer”) method used for performance-based contracts by a health plan providing Medicaid coverage in the Midwestern United States (specifications obtained from MCR Contracting Department), (3) private health plan (“private payer”) method used for provider profiling by a large commercial health plan (specifications obtained from MCR Contracting Department), (4) HealthPartners (HP) method21 submitted to the National Quality Forum as an example attribution method for total cost of care calculations, and (5) Minnesota Community Measurement (MNCM) method18 used for mandatory public reporting in Minnesota.

All methods attribute patients at the provider level, except MNCM, which attributes them at the clinic level. In this study, MNCM was applied at the provider level to facilitate direct comparison. Also, APPs are classified as PCPs by all methods except the public payer method, which considers the APP practice setting to determine PCP status. At MCR, APPs practice in a wide range of settings and were therefore classified based on their clinical practice site.

Independent Variables

Administrative data from between January 1, 2010, and December 31, 2011, were used to document diagnoses (International Classification of Diseases, Ninth Revision [ICD-9] codes), procedures (Current Procedural Technology and ICD-9 codes), number and type of visits, financial information, service locations, provider identifiers, and patient characteristics as of December 31, 2011. The operational definition of chronic conditions was based on Naessens et al,22 which supplements the chronic conditions identified by Hwang et al23 in Agency for Healthcare Research and Quality Clinical Classifications Software.24 Comorbidity burden was quantified using the total count of chronic diseases recorded during 2010-2011 and the Reference Unscaled Adjusted Clinical Group (ACG) Weight25 based on 2011 billing diagnoses. The Reference Unscaled ACG Weight is an estimate of concurrent resource use associated with a given ACG based on a reference database and expressed as a relative value.25 Attribution was based on data from 2010 to 2011, with the specific time frame dependent on the method.

For each attribution method, patients were categorized as (1) attributed by that method to the paneled MCR PCP (attributed-matched), (2) attributed to an MCR PCP who is different from the paneled MCR PCP (attributed-unmatched), (3) attributed to an MCR PCP but not paneled to any PCP at MCR (attributed-unpaneled), or (4) paneled to a PCP at MCR but not attributed to any MCR PCP using that attribution method (paneled-unattributed).

Outcome Measures

We compared the (1) extent and concordance of attribution; (2) percentage of patients meeting criteria for receiving high-quality diabetes, vascular, asthma, and depression care; (3) annual standardized cost of care26; and (4) number of inpatient (IP), emergency department (ED), and outpatient (OP) visits in 2011. Nonvisit and e-health services were excluded.

Statistical Analysis

Descriptive statistics were calculated for each attribution method. The proportion of patients attributed by each method was calculated for paneled and nonpaneled patients. Utilization, clinical outcome, and cost statistics were calculated based on all patients attributed by that method within each cohort. Analyses were performed using SAS version 9.4 (SAS Institute; Cary, North Carolina).


 
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