Donna M Zulman1,2, Liberty Greene1,2, Cindie Slightam1, Sara J Singer2, Matthew L Maciejewski3,4, Mary K Goldstein5,6, Megan E Vanneman7,8,9, Jean Yoon10,11, Ranak B Trivedi1,12, Todd Wagner10,13, Steven M Asch1,2, Derek Boothroyd1,14. 1. Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California, USA. 2. Department of Medicine, Stanford University School of Medicine, Stanford, California, USA. 3. Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, North Carolina, USA. 4. Department of Population Health Sciences, Duke University, Durham, North Carolina, USA. 5. Office of Geriatrics and Extended Care, Veterans Health Administration, Washington, DC, USA. 6. Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California, USA. 7. Informatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA. 8. Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA. 9. Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA. 10. Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, USA. 11. Department of General Internal Medicine, UCSF School of Medicine, San Francisco, California, USA. 12. Division of Public Mental Health and Population Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA. 13. Department of Surgery, Stanford University School of Medicine, Palo Alto, California, USA. 14. Quantitative Sciences Unit, Stanford University School of Medicine, Palo Alto, California, USA.
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 health care 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: The mean (SD) 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.
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 health care 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: The mean (SD) 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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Authors: Donna M Zulman; Liberty Greene; Cindie Slightam; Sara J Singer; Matthew L Maciejewski; Mary K Goldstein; Megan E Vanneman; Jean Yoon; Ranak B Trivedi; Todd Wagner; Steven M Asch; Derek Boothroyd Journal: Health Serv Res Date: 2022-03-11 Impact factor: 3.734
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Authors: Donna M Zulman; Liberty Greene; Cindie Slightam; Sara J Singer; Matthew L Maciejewski; Mary K Goldstein; Megan E Vanneman; Jean Yoon; Ranak B Trivedi; Todd Wagner; Steven M Asch; Derek Boothroyd Journal: Health Serv Res Date: 2022-03-11 Impact factor: 3.734