Gender as risk factor for 30 days post-discharge hospital utilisation: a secondary data analysis

Shaula Woz, Suzanne Mitchell, Caroline Hesko, Michael Paasche-Orlow, Jeffrey Greenwald, V K Chetty, Julie O'Donnell, Brian Jack, Shaula Woz, Suzanne Mitchell, Caroline Hesko, Michael Paasche-Orlow, Jeffrey Greenwald, V K Chetty, Julie O'Donnell, Brian Jack

Abstract

Objective: In the 30 days after hospital discharge, hospital utilisation is common and costly. This study evaluated the association between gender and hospital utilisation within 30 days of discharge.

Design: Secondary data analysis using Poisson regression stratified by gender.

Participants: 737 English-speaking hospitalised adults from general medical service in urban, academic safety-net medical centre who participated in the Project Re-Engineered clinical trial (clinicaltrials.gov identifier: NCT00252057).

Main outcome measure: The primary end point was hospital utilisation, defined as total emergency department visits and hospital readmissions within 30 days after index discharge.

Results: Female subjects had a rate of 29 events for every 100 people and male subjects had a rate of 47 events for every 100 people (incident rate ratio (IRR) 1.62, 95% CI 1.28 to 2.06). Among men, risk factors included hospital utilisation in the 6 months prior to the index hospitalisation (IRR 3.55, 95% CI 2.38 to 5.29), being unmarried (IRR 1.72, 95% CI 1.12 to 2.64), having a positive depression screen (IRR 1.53, 95% CI 1.09 to 2.13) and no primary care physician (PCP) visit within 30 days (IRR 1.64, 95% CI 1.08 to 2.50). Among women, the only risk factor was hospital utilisation in the 6 months prior to the index hospitalisation (IRR 3.08, 95% CI 1.86 to 5.10).

Conclusions: In our data, male subjects had a higher rate of hospital utilisation within 30 days of discharge than female subjects. For men-but not for women-risk factors were being retired, unmarried, having depressive symptoms and having no PCP visit within 30 days. Interventions addressing these factors might lower hospital utilisation rates observed among men.

Conflict of interest statement

Competing interests: None.

Figures

Figure 1
Figure 1
Kaplan–Meier curve: time to multiple hospitalisation events by gender.

References

    1. Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare Fee-for-service program. N Engl J Med 2009;360:1418–28
    1. Patient Protection and Affordable Care Act, Pub. L. No. 111–148, 124 Stat. 119 (2010).
    1. Oddone EZ, Weinberger M, Horner M, et al. Classifying general medicine readmissions. Are they preventable? Veterans affairs cooperative studies in health services group on primary care and hospital readmissions. J Gen Intern Med 1996;11:597–607
    1. Ashton CM, Wray NP. A conceptual framework for the study of early readmission as an indicator of quality of care. Soc Sci Med 1996;43:1533–41
    1. Jack BW, Chetty VK, Anthony D, et al. A Reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med 2009;150:178–87
    1. Billings J, Dixon J, Mijanovich T, et al. Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients. BMJ 2006;333:327.
    1. Bottle A, Aylin P, Majeed A. Identifying patients at high risk of emergency hospital admissions: a logistic regression analysis. J R Soc Med 2006;99:406–14
    1. Weissman JS, Stern RS, Epstein AM. The impact of patient socioeconomic status and other social factors on readmission: a prospective study in four Massachusetts hospitals. Inquiry 1994;31:163–72
    1. Krumholz HM, Parent EM, Tu N, et al. Readmission after hospitalization for congestive heart Failure among medicare beneficiaries. Arch Intern Med 1997;157:99–104
    1. Cherpitel CJ. Emergency room and primary care services utilization and associated alcohol and drug use in the United States general population. Alcohol Alcohol 1999;34:581–9
    1. Mitchell SE, Paasche-Orlow MK, Forsythe SR, et al. Post-discharge hospital utilization among adult medical inpatients with depressive symptoms. J Hosp Med 2010;5:378–84
    1. Kartha A, Anthony D, Manasseh CS, et al. Depression is a risk factor for rehospitalization in medical inpatients. Prim Care Companion J Clin Psychiatry 2007;9:256–62
    1. Mackenzie CS, Gekoski WL, Knox VJ. Age, gender, and the underutilization of mental health services: the influence of help-seeking attitudes. Aging Ment Health 2006;10:574–82
    1. Davis TC, Long SW, Jackson RH, et al. Rapid estimate of adult literacy in medicine: a shortened screening instrument. Fam Med 1993;25:391–5
    1. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83
    1. Molloy GJ, Perkins-Porras L, Strike PC, et al. Social networks and partner stress as predictors of adherence to medication, rehabilitation attendance, and quality of life following acute coronary syndrome. Health Psychol 2008;27:52–8
    1. Courtenay WH. Constructions of masculinity and their influence on men's well-being: a theory of gender and health. Soc Sci Med 2000;50:1385–401
    1. Weinberger M, Oddone EZ, Henderson WG. Does increased access to primary care Reduce hospital readmissions? N Engl J Med 1996;334:1441–7
    1. World Health Organization Gender and Mental Health. 2002. (accessed Jun 2011).
    1. Kuehn BM. Men face barriers to mental health care. JAMA 2006;296:2303–4
    1. Davis AM, Sawyer DR, Vinci LM. The potential of group visits in diabetes care. Clin Diabetes 2008;26:58–62

Source: PubMed

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