Richard W. Grant, MD, MPH; Jeffrey M. Ashburner, MPH; Clemens S. Hong, MD, MPH; Yuchiao Chang, PhD; Michael J. Barry, MD; Steve J. Atlas, MD, MPH
Acknowledgment: The authors thank Lulu Y. Liu, MS, from the General Medicine Division, for her assistance with preparing the manuscript; Jennifer M. Luttrell from the Laboratory of Computer Science, for creating the online patient review tool; and the primary care providers of the Primary Care Operations Improvement Advisory Board, Massachusetts General Hospital, for clinical insights and valuable feedback during the project.
Grant Support: By the Systems Improvement Grant Program of Partners Community Healthcare, Inc.
Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-0862.
Reproducible Research Statement:Study protocol and statistical code: Available from Dr. Atlas (e-mail, firstname.lastname@example.org). Data set: Not available.
Requests for Single Reprints: Richard W. Grant, MD, MPH, Kaiser Permanente, Division of Research, 2101 Webster Street, 20th Floor, Oakland, CA 94612; e-mail, Richard.W.Grant@KP.org.
Current Author Addresses: Dr. Grant: Kaiser Permanente, Division of Research, 2101 Webster Street, 20th Floor, Oakland, CA 94612.
Mr. Ashburner and Drs. Hong, Chang, Barry, and Atlas: General Medicine Division, Massachusetts General Hospital, 50 Staniford Street, 9th Floor, Boston, MA 02114.
Author Contributions: Conception and design: R.W. Grant, M.J. Barry, S.J. Atlas.
Analysis and interpretation of the data: R.W. Grant, J.M. Ashburner, C.S. Hong, Y. Chang, S.J. Atlas.
Drafting of the article: R.W. Grant, J.M. Ashburner.
Critical revision of the article for important intellectual content: J.M. Ashburner, C.S. Hong, M.J. Barry, S.J. Atlas.
Final approval of the article: R.W. Grant, J.M. Ashburner, C.S. Hong, M.J. Barry, S.J. Atlas.
Provision of study materials or patients: R.W. Grant, J.M. Ashburner.
Statistical expertise: Y. Chang.
Obtaining of funding: R.W. Grant.
Administrative, technical, or logistic support: J.M. Ashburner, M.J. Barry.
Collection and assembly of data: R.W. Grant, J.M. Ashburner, S.J. Atlas.
Patients with complex health needs are increasingly the focus of health system redesign.
To characterize complex patients, as defined by their primary care physicians (PCPs), and to compare this definition with other commonly used algorithms.
1 hospital-based practice, 4 community health centers, and 7 private practices in a primary care network in the United States.
40 physicians who reviewed a random sample of 120 of their own patients.
After excluding patients for whom they were not directly responsible, PCPs indicated which of their patients they considered complex. These patients were characterized, independent predictors of complexity were identified, and PCP-defined complexity was compared with 3 comorbidity-based methods (Charlson score, Higashi score, and a proprietary Centers for Medicare & Medicaid Services algorithm).
Physicians identified 1126 of their 4302 eligible patients (26.2%) as complex and assigned a mean of 2.2 domains of complexity per patient (median, 2.0 [interquartile range, 1 to 3]). Mental health and substance use were identified as major issues in younger complex patients, whereas medical decision making and care coordination predominated in older patients (P < 0.001 for trends by decade). Major independent predictors of PCP-defined complexity (P < 0.001) included age (probability of complexity increased from 14.8% to 19.8% with age increasing from 55 to 65 years), poorly controlled diabetes (from 12.7% to 47.6% if hemoglobin A1c level ≥9%), use of antipsychotics (from 12.7% to 31.8%), alcohol-related diagnoses (from 12.9% to 27.4%), and inadequate insurance (from 12.5% to 19.2%). Classification agreement for complex patients ranged from 26.2% to 56.0% when PCP assignment was compared with each of the other methods.
Results may not be generalizable to other primary care settings.
Primary care physicians identified approximately one quarter of their patients as complex. Medical, social, and behavioral factors all contributed to PCP-defined complexity. Physician-defined complexity had only modest agreement with 3 comorbidity-based algorithms.
Partners Community Healthcare, Inc.
Grant RW, Ashburner JM, Hong CS, Chang Y, Barry MJ, Atlas SJ. Defining Patient Complexity From the Primary Care Physician's Perspective: A Cohort Study. Ann Intern Med. ;155:797–804. doi: 10.7326/0003-4819-155-12-201112200-00001
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Published: Ann Intern Med. 2011;155(12):797-804.
Cardiology, Coronary Risk Factors, Diabetes, Endocrine and Metabolism, Healthcare Delivery and Policy.
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