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Shen K, McGarry BE, Gandhi AD. Association Between Staff Turnover and Care Quality in Nursing Homes-Reply. JAMA Intern Med 2024; 184:335. [PMID: 38285601 DOI: 10.1001/jamainternmed.2023.7717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Affiliation(s)
- Karen Shen
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Brian E McGarry
- Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, New York
| | - Ashvin D Gandhi
- Anderson School of Management, University of California, Los Angeles
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Abstract
Importance Turnover in health care staff may disrupt patient care and create operational and organizational challenges, and nursing home staff turnover rates are particularly high. Empirical evidence on the association between turnover and quality of care is limited and has typically relied on low-quality measures of turnover, small and selected samples of facilities, and comparisons across facilities that are highly susceptible to residual confounding. Objective To quantify the association between nursing home staff turnover and quality of care using within-facility variation over time in reliable turnover measures available for virtually all US nursing homes. Design, Setting, and Participants In this cross-sectional study, data from the Centers for Medicare & Medicaid Services on health inspection citations and quality measures at US nursing homes were combined with turnover measures constructed from daily staffing payroll data for quarter 2 of 2017 (April 1 to June 30) to quarter 4 of 2019 (October 1 to December 31), covering 1.06 billion shifts for 7.48 million employment relationships at 15 869 facilities. A 2-way fixed-effects design was used to estimate the association between staff turnover (direct care nursing staff and administrators) and quality-of-care outcomes based on how the same facility performed differently in times of low and high turnover. Data analysis was performed from September 2022 to August 2023. Exposures Facility turnover, defined as the share of hours worked in a period by staff hired within the last 90 days. Main Outcomes and Measures Number, type, scope, and severity of health inspection citations, overall health inspection scores, and Nursing Home Compare quality measures. Results The study sample included 1.45 million facility-weeks between April 1, 2017, and December 31, 2019, corresponding to 13 826 unique facilities. During an average facility-week, 15.0% of nursing staff and 11.6% of administrators were new hires due to recent turnover. After both administrator turnover and the overall staffing level were controlled for, an additional 10 percentage points in nursing staff turnover in the 2 weeks before a health inspection was associated with an additional 0.241 (95% CI, 0.084-0.399) citations in that inspection, compared with a mean of 5.98 citations. An additional 10 percentage points in nursing staff turnover was associated with a mean decrease of 0.035 (95% CI, 0.023-0.047) SDs in assessment-based quality measures and 0.020 (95% CI, 0.001-0.038) SDs in claims-based quality measures, with the strongest associations found for measures related to patient functioning. Conclusions and Relevance Within-facility variation in staff turnover was associated with decreased quality of care. These findings suggest that efforts to monitor and reduce staff turnover may be able to improve patient outcomes.
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Affiliation(s)
- Karen Shen
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Brian E. McGarry
- Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, New York
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McGarry BE, Gandhi AD, Barnett ML. Covid-19 Surveillance Testing in Nursing Homes. Reply. N Engl J Med 2023; 388:2207-2208. [PMID: 37285544 DOI: 10.1056/nejmc2304781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
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Abstract
BACKGROUND Despite widespread adoption of surveillance testing for coronavirus disease 2019 (Covid-19) among staff members in skilled nursing facilities, evidence is limited regarding its relationship with outcomes among facility residents. METHODS Using data obtained from 2020 to 2022, we performed a retrospective cohort study of testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among staff members in 13,424 skilled nursing facilities during three pandemic periods: before vaccine approval, before the B.1.1.529 (omicron) variant wave, and during the omicron wave. We assessed staff testing volumes during weeks without Covid-19 cases relative to other skilled nursing facilities in the same county, along with Covid-19 cases and deaths among residents during potential outbreaks (defined as the occurrence of a case after 2 weeks with no cases). We reported adjusted differences in outcomes between high-testing facilities (90th percentile of test volume) and low-testing facilities (10th percentile). The two primary outcomes were the weekly cumulative number of Covid-19 cases and related deaths among residents during potential outbreaks. RESULTS During the overall study period, 519.7 cases of Covid-19 per 100 potential outbreaks were reported among residents of high-testing facilities as compared with 591.2 cases among residents of low-testing facilities (adjusted difference, -71.5; 95% confidence interval [CI], -91.3 to -51.6). During the same period, 42.7 deaths per 100 potential outbreaks occurred in high-testing facilities as compared with 49.8 deaths in low-testing facilities (adjusted difference, -7.1; 95% CI, -11.0 to -3.2). Before vaccine availability, high- and low-testing facilities had 759.9 cases and 1060.2 cases, respectively, per 100 potential outbreaks (adjusted difference, -300.3; 95% CI, -377.1 to -223.5), along with 125.2 and 166.8 deaths (adjusted difference, -41.6; 95% CI, -57.8 to -25.5). Before the omicron wave, the numbers of cases and deaths were similar in high- and low-testing facilities; during the omicron wave, high-testing facilities had fewer cases among residents, but deaths were similar in the two groups. CONCLUSIONS Greater surveillance testing of staff members at skilled nursing facilities was associated with clinically meaningful reductions in Covid-19 cases and deaths among residents, particularly before vaccine availability.
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Affiliation(s)
- Brian E McGarry
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
| | - Ashvin D Gandhi
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
| | - Michael L Barnett
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
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McGarry BE, Gandhi AD, Syme M, Berry SD, White EM, Grabowski DC. Association of State COVID-19 Vaccine Mandates With Staff Vaccination Coverage and Staffing Shortages in US Nursing Homes. JAMA Health Forum 2022; 3:e222363. [PMID: 35983581 PMCID: PMC9338409 DOI: 10.1001/jamahealthforum.2022.2363] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 06/08/2022] [Indexed: 11/14/2022] Open
Abstract
Question Are state COVID-19 vaccine mandates for US nursing home employees associated with staff vaccination coverage and reported staff shortages? Findings This cohort study of nursing homes in 38 states found that states with a vaccine mandate experienced an increase in staff vaccination coverage compared with facilities in states with no mandate and no worsening of reported staffing shortages following the mandates. Meaning These findings suggest that given the waning vaccine-induced immunity and low booster dose coverage among nursing home staff in many parts of the US, state mandates for booster doses may be warranted to improve and sustain vaccination coverage in nursing homes. Importance Several states implemented COVID-19 vaccine mandates for nursing home employees, which may have improved vaccine coverage but may have had the unintended consequence of staff departures. Objective To assess whether state vaccine mandates for US nursing home employees are associated with staff vaccination rates and reported staff shortages. Design, Setting, and Participants This cohort study performed event study analyses using National Healthcare Safety Network data from June 6, 2021, through November 14, 2021. Changes in weekly staff vaccination rates and reported staffing shortages were evaluated for nursing homes in states with mandates after the mandate announcement compared with changes in facilities in nonmandate states. An interaction between the mandates and county political leaning was considered. Data analysis was performed from February to March 2022. Exposures Weeks after announcement of a state’s COVID-19 vaccine mandate. Main Outcomes and Measures Weekly percentage of all health care staff at a nursing home who received at least 1 COVID-19 vaccine dose, and a weekly indicator of whether a nursing home reported a staffing shortage. Results Among 38 study-eligible states, 26 had no COVID-19 vaccine mandate for nursing home employees, 4 had a mandate with a test-out option, and 8 had a mandate with no test-out option. Ten weeks or more after mandate announcement, nursing homes in states with a mandate and no test-out option experienced a 6.9 percentage point (pp) increase in staff vaccination coverage (95% CI, −0.1 to 13.9); nursing homes in mandate states with a test-out option experienced a 3.1 pp increase (95% CI, 0.5 to 5.7) compared with facilities in nonmandate states. No significant increases were detected in the frequency of reported staffing shortages after a mandate announcement in mandate states with or without test-out options. Increases in vaccination rates in states with mandates were larger in Republican-leaning counties (14.3 pp if no test-out option; 4.3 pp with option), and there was no evidence of increased staffing shortages. Conclusions and Relevance The findings of this cohort study suggest that state-level vaccine mandates were associated with increased staff vaccination coverage without increases in reported staffing shortages. Vaccination increases were largest when mandates had no test-out option and were also larger in Republican-leaning counties, which had lower mean baseline vaccination rates. These findings support the use of state mandates for booster doses for nursing home employees because they may improve vaccine coverage, even in areas with greater vaccine hesitancy.
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Affiliation(s)
- Brian E. McGarry
- Division of Geriatrics and Aging, Department of Medicine, University of Rochester Medical Center, Rochester, New York
| | - Ashvin D. Gandhi
- Anderson School of Management, University of California Los Angeles
| | - Maggie Syme
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts
| | - Sarah D. Berry
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts
- Beth Israel Deaconess Medical Center, Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Elizabeth M. White
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
| | - David C. Grabowski
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
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Shen K, McGarry BE, Grabowski DC, Gruber J, Gandhi AD. Staffing Patterns in US Nursing Homes During COVID-19 Outbreaks. JAMA Health Forum 2022; 3:e222151. [PMID: 35977215 PMCID: PMC9308062 DOI: 10.1001/jamahealthforum.2022.2151] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/25/2022] [Indexed: 11/14/2022] Open
Abstract
Importance Staff absences and departures at nursing homes may put residents at risk and present operational challenges. Objective To quantify changes in nursing home facility staffing during and after a severe COVID-19 outbreak. Design Setting and Participants In this cohort study, daily staffing payroll data were used to construct weekly measures of facility staffing, absences, departures, and use of overtime and contract staff among US nursing homes experiencing a severe COVID-19 outbreak that started between June 14, 2020, and January 1, 2021. Facility outbreaks were identified using COVID-19 case data. An event-study design with facility and week fixed effects was used to investigate the association of severe outbreaks with staffing measures. Exposures Weeks since the beginning of a severe COVID-19 outbreak (4 weeks prior to 16 weeks after). Main Outcomes and Measures Total weekly staffing hours, staff counts, staff absences, departures, new hires, overtime and contract staff hours measured for all nursing staff and separately by staff type (registered nurses, licensed practical nurses, certified nursing assistants), facility self-reported staff shortages, and resident deaths. Results Of the included 2967 nursing homes experiencing severe COVID-19 outbreaks, severe outbreaks were associated with a statistically significant drop in nursing staffing levels owing to elevated absences and departures. Four weeks after an outbreak's start, around when average new cases peaked, staffing hours were 2.6% (95% CI, 2.1%-3.2%) of the mean below preoutbreak levels, despite facilities taking substantial measures to bolster staffing through increased hiring and the use of contract staff and overtime. Because these measures were mostly temporary, staffing declined further in later weeks; 16 weeks after an outbreak's start, staffing hours were 5.5% (95% CI, 4.5%-6.5%) of the mean below preoutbreak levels. Staffing declines were greatest among certified nursing assistants, primarily owing to smaller increases in new hires of this staff type compared with licensed practical nurses and registered nurses. Conclusions and Relevance In this cohort study of nursing homes experiencing severe COVID-19 outbreaks, facilities experienced considerable staffing challenges during and after outbreaks. These results suggest the need for policy action to ensure facilities' abilities to maintain adequate staffing levels during and after infectious disease outbreaks.
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Affiliation(s)
- Karen Shen
- Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Brian E McGarry
- Division of Geriatrics & Aging, Department of Medicine, University of Rochester Medical Center, Rochester, New York
| | - David C Grabowski
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Jonathan Gruber
- Department of Economics, Massachusetts Institute of Technology, Cambridge
| | - Ashvin D Gandhi
- UCLA Anderson School of Management, University of California, Los Angeles
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Affiliation(s)
| | | | | | - Ashvin D Gandhi
- Anderson School of Management of the University of California, Los Angeles, Los Angeles, CA
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McGarry BE, Shen K, Barnett ML, Grabowski DC, Gandhi AD. Association of Nursing Home Characteristics With Staff and Resident COVID-19 Vaccination Coverage. JAMA Intern Med 2021; 181:1670-1672. [PMID: 34529009 PMCID: PMC8446903 DOI: 10.1001/jamainternmed.2021.5890] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 08/23/2021] [Indexed: 11/14/2022]
Affiliation(s)
- Brian E. McGarry
- Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, New York
| | - Karen Shen
- Department of Economics, Harvard University, Boston, Massachusetts
| | - Michael L. Barnett
- Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - David C. Grabowski
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Ashvin D. Gandhi
- Anderson School of Management, University of California, Los Angeles
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Abstract
Staff in skilled nursing facilities (SNFs) are essential health care workers, yet they can also be a source of COVID-19 transmission. We used detailed staffing data to examine the relationship between a novel measure of staff size (that is, the number of unique employees working daily), conventional measures of staffing quality, and COVID-19 outcomes among SNFs in the United States without confirmed COVID-19 cases by June 2020. By the end of September 2020, sample SNFs in the lowest quartile of staff size had 6.2 resident cases and 0.9 deaths per 100 beds, compared with 11.9 resident cases and 2.1 deaths per 100 beds among facilities in the highest quartile. Staff size, including staff members not involved in resident care, was strongly associated with SNFs' COVID-19 outcomes, even after facility size was accounted for. Conventional staffing quality measures, including direct care staff-to-resident ratios and skill mix, were not significant predictors of COVID-19 cases or deaths. Reducing the number of unique staff members without decreasing direct care hours, such as by relying on full-time rather than part-time staff, could help prevent outbreaks.
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Affiliation(s)
- Brian E McGarry
- Brian E. McGarry is an assistant professor in the Department of Medicine, University of Rochester, in Rochester, New York
| | - Ashvin D Gandhi
- Ashvin D. Gandhi is an assistant professor at the University of California Los Angeles Anderson School of Management, in Los Angeles, California
| | - David C Grabowski
- David C. Grabowski is a professor of health care policy at Harvard Medical School, in Boston, Massachusetts
| | - Michael Lawrence Barnett
- Michael Lawrence Barnett is an assistant professor of health policy and management, Harvard T. H. Chan School of Public Health, in Boston, Massachusetts, and an assistant professor of medicine at Harvard Medical School
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