Mona K Pedersen1,2, Gunnar L Nielsen3,4, Lisbeth Uhrenfeldt5,6, Søren Lundbye-Christensen4,7. 1. Department of Internal Medicine, Aalborg University Hospital, Mølleparkvej 4, 9000, Aalborg, Denmark. mokyp@rn.dk. 2. Clinical Nursing Research Unit, Aalborg University Hospital, Aalborg, Denmark. mokyp@rn.dk. 3. Department of Internal Medicine, Aalborg University Hospital, Mølleparkvej 4, 9000, Aalborg, Denmark. 4. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark. 5. Clinical Nursing Research, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. 6. Faculty of Nursing and Health Sciences, Nord University, Bodø, Norway. 7. Unit of Clinical Biostatistics, Aalborg University Hospital, Aalborg, Denmark.
Abstract
BACKGROUND: Hospital readmission is considered an adverse health outcome in older people, adding additional pressure on clinical resources within health care services. Despite numerous studies on risk factors for readmissions, studies find different strengths of respective determinants and there is a need to explore and identify patterns of risk factors in larger cohorts. OBJECTIVE: Exploring and identifying patterns of risk factors for acute, all-cause 30-day readmission in a Danish cohort of patients aged 65+. DESIGN: Register-based cohort study using individual-level linkable information on demographics, social determinants, clinical conditions, health care utilization, and provider determinants obtained from primary and secondary health care. PARTICIPANTS: Historic cohort of 1,267,752 admissions in 479,854 patients, aged 65+, discharged from Danish public hospitals from January 2007 to September 2010. MAIN MEASURES: We included patient-level variables and admission-level variables. Outcome was acute, all-cause 30-day readmission. Data was analyzed by univariable and multivariable logistic regression. Strength of associations was analyzed using Wald test statistics. Receiver operating characteristic (ROC) analysis was used for quantification of predictive ability. For validation, we used split-sample design. KEY RESULTS: Acute admission and number of days since previous hospital discharge were factors strongly associated with readmission. Patients at risk of future readmission suffered from comorbidity, consumed more drugs, and were frequent users of in- and outpatient health care services in the year prior to the index admission. Factors related to index admission were only weakly associated with readmission. The predictive ability was 0.709 (0.707-0.711) for acute readmission. CONCLUSIONS: In a general population of older people, we found that pre-hospital factors rather than hospital factors account for increased risk of readmission and are dominant contributors to predict acute all-cause 30-day readmission. Therefore, risk for excess readmission should be shared across sectors and focus the care trajectory over time rather than distinct care episodes.
BACKGROUND: Hospital readmission is considered an adverse health outcome in older people, adding additional pressure on clinical resources within health care services. Despite numerous studies on risk factors for readmissions, studies find different strengths of respective determinants and there is a need to explore and identify patterns of risk factors in larger cohorts. OBJECTIVE: Exploring and identifying patterns of risk factors for acute, all-cause 30-day readmission in a Danish cohort of patients aged 65+. DESIGN: Register-based cohort study using individual-level linkable information on demographics, social determinants, clinical conditions, health care utilization, and provider determinants obtained from primary and secondary health care. PARTICIPANTS: Historic cohort of 1,267,752 admissions in 479,854 patients, aged 65+, discharged from Danish public hospitals from January 2007 to September 2010. MAIN MEASURES: We included patient-level variables and admission-level variables. Outcome was acute, all-cause 30-day readmission. Data was analyzed by univariable and multivariable logistic regression. Strength of associations was analyzed using Wald test statistics. Receiver operating characteristic (ROC) analysis was used for quantification of predictive ability. For validation, we used split-sample design. KEY RESULTS: Acute admission and number of days since previous hospital discharge were factors strongly associated with readmission. Patients at risk of future readmission suffered from comorbidity, consumed more drugs, and were frequent users of in- and outpatient health care services in the year prior to the index admission. Factors related to index admission were only weakly associated with readmission. The predictive ability was 0.709 (0.707-0.711) for acute readmission. CONCLUSIONS: In a general population of older people, we found that pre-hospital factors rather than hospital factors account for increased risk of readmission and are dominant contributors to predict acute all-cause 30-day readmission. Therefore, risk for excess readmission should be shared across sectors and focus the care trajectory over time rather than distinct care episodes.
Entities:
Keywords:
database; health services research; readmission; risk assessment
Authors: Morten Schmidt; Sigrun Alba Johannesdottir Schmidt; Jakob Lynge Sandegaard; Vera Ehrenstein; Lars Pedersen; Henrik Toft Sørensen Journal: Clin Epidemiol Date: 2015-11-17 Impact factor: 4.790