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Zulman DM, Greene L, Slightam C, Singer SJ, Maciejewski ML, Goldstein MK, Vanneman ME, Yoon J, Trivedi RB, Wagner T, Asch SM, Boothroyd D. Outpatient care fragmentation in Veterans Affairs patients at high-risk for hospitalization. Health Serv Res 2022; 57:764-774. [PMID: 35178702 PMCID: PMC9264453 DOI: 10.1111/1475-6773.13956] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 01/28/2022] [Accepted: 02/01/2022] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE To examine outpatient care fragmentation and its association with future hospitalization among patients at high risk for hospitalization. DATA SOURCES Veterans Affairs (VA) and Medicare data. STUDY DESIGN We conducted a longitudinal study, using logistic regression to examine how outpatient care fragmentation in FY14 (as measured by number of unique providers, Breslau's Usual Provider of Care (UPC), Bice-Boxerman's Continuity of Care Index (COCI), and Modified Modified Continuity Index (MMCI)) was associated with all-cause hospitalizations and hospitalizations related to ambulatory care sensitive conditions (ACSC) in FY15. We also examined how fragmentation varied by patient's age, gender, race, ethnicity, marital status, rural status, history of homelessness, number of chronic conditions, Medicare utilization, and mental healthcare utilization. DATA EXTRACTION METHODS We extracted data for 130,704 VA patients ≥65 years old with a hospitalization risk ≥90th percentile and ≥ four outpatient visits in the baseline year. PRINCIPAL FINDINGS Mean (standard deviation) of FY14 outpatient visits was 13.2 (8.6). Fragmented care (more providers, less care with a usual provider, more dispersed care based on COCI) was more common among patients with more chronic conditions and those receiving mental health care. In adjusted models, most fragmentation measures were not associated with all-cause hospitalization, and patients with low levels of fragmentation (more concentrated care based on UPC, COCI, and MMCI) had a higher likelihood of an ACSC-related hospitalization (AOR, 95% CI = 1.21 (1.09-1.35), 1.27 (1.14-1.42), and 1.28 (1.18-1.40), respectively). CONCLUSIONS Contrary to expectations, outpatient care fragmentation was not associated with elevated all-cause hospitalization rates among VA patients in the top 10th percentile for risk of admission; in fact, fragmented care was linked to lower rates of hospitalization for ACSCs. In integrated settings such as the VA, multiple providers and dispersed care might offer access to timely or specialized care that offsets risks of fragmentation, particularly for conditions that are sensitive to ambulatory care.
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Affiliation(s)
- Donna M Zulman
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States.,Department of Medicine, Stanford University School of Medicine, Stanford, California, United States
| | - Liberty Greene
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States.,Department of Medicine, Stanford University School of Medicine, Stanford, California, United States
| | - Cindie Slightam
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States
| | - Sara J Singer
- Department of Medicine, Stanford University School of Medicine, Stanford, California, United States
| | - Matthew L Maciejewski
- Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, North Carolina, United States.,Department of Population Health Sciences, Duke University, Durham, North Carolina, United States
| | - Mary K Goldstein
- Office of Geriatrics and Extended Care, Veterans Health Administration.,Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, United States
| | - Megan E Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, United States.,Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States.,Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, United States
| | - Jean Yoon
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States.,Department of General Internal Medicine, UCSF School of Medicine, San Francisco, California, United States
| | - Ranak B Trivedi
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States.,Division of Public Mental Health and Population Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, United States
| | - Todd Wagner
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States.,Department of Surgery, Stanford University School of Medicine, Palo Alto, California, United States
| | - Steven M Asch
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States.,Department of Medicine, Stanford University School of Medicine, Stanford, California, United States
| | - Derek Boothroyd
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, United States.,Quantitative Sciences Unit, Stanford University School of Medicine, Palo Alto, California, United States
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Abstract
OBJECTIVE To identify novel properties of health care fragmentation measures, drawing on insights from mathematically equivalent measures of genetic diversity. STUDY DESIGN We describe mathematical relationships between two measures: (a) Breslau's Usual Provider of Care (UPC), the proportion of care with the most frequently visited provider, analogous to the "frequency of the most frequent allele" at a genetic locus; and (b) Bice-Boxerman's Continuity of Care Index (COCI), a measure of care dispersion across multiple providers, analogous to "Nei's estimator of homozygosity" in genetics. PRINCIPAL FINDINGS Just as the frequency of the most frequent allele places a tight constraint on homozygosity, the proportion of care with the most frequently visited provider (UPC) places lower and upper bounds on dispersion of care (COCI), and vice versa. This property presents the possibility of a normalized COCI given UPC (NCGU) measure, which reflects a bounded range of care dispersion dependent on the number of visits with the most frequently visited provider. Mathematical aspects of UPC and COCI also suggest thresholds for the minimal number of patient visits to use when studying fragmentation. CONCLUSIONS Applying knowledge from population genetics elucidated relationships between care fragmentation measures and produced novel insights for care fragmentation studies.
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Affiliation(s)
- Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, California
| | - Donna M Zulman
- Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California.,Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California
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