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Background: This study aimed to investigate the prevalence of hospital readmission for chronic obstructive pulmonary disease (COPD) at 30, 90 and 365 days, and to determine demographic and socioeconomic risk factors for 30-day and 90-day readmission and time to COPD-related readmission within 365 days in Tasmania. Methods: Patients =40 years admitted for COPD between 2011 and 2015 were identified using administrative data from all major public hospitals in Tasmania, Australia. Factors associated with readmission and time to readmission were identified using logistic and Cox regression, respectively. Results: The rates of COPD-related readmission were 6.7% within 30 days, 12.2% within 90 days and 23.7% within 365 days. Being male (odds ratio [OR]: 1.49, CI: 1.06-2.09), Indigenous (OR: 2.47, CI: 1.31-4.66) and living in the lower socioeconomic North-West region of Tasmania (OR: 1.80, CI: 1.20-2.69) were risk factors for 30-day readmission. Increased COPD-related (OR: 1.48, CI: 1.22-1.80; OR: 1.52, CI: 1.29-1.78) and non-COPD-related (OR: 1.12, CI: 1.03-1.23; OR: 1.11, CI: 1.03-1.21) emergency department (ED) visits in the preceding six months were risk factors for both 30-day and 90-day readmissions. Being Indigenous (hazard ratio [HR]: 1.61, CI: 1.10-2.37) and previous COPD-related ED visits (HR: 1.30, CI: 1.21-1.39) decreased, while a higher Charlson Comorbidity Index (CCI) (OR: 0.91, CI: 0.83-0.99) increased the time to readmission within 365 days. Conclusion: Being male, Indigenous, living in the North-West region and previous ED visits were associated with increased risk of COPD readmission in Tasmania. Interventions to improve access to primary healthcare for these groups may reduce COPD-related readmissions. [ABSTRACT FROM AUTHOR]

Background: Adverse drug events are a leading cause of hospitalization among older people. Up to half of all medication-related hospitalizations are potentially preventable. The objective of this study was to investigate and compare the association between medication regimen complexity and number of medications with unplanned hospitalizations over a 3-year period.Methods: Data were analyzed for 3,348 participants aged 60 years or older in Sweden. Regimen complexity was assessed using the 65-item Medication Regimen Complexity Index (MRCI) and number of medications was assessed as a continuous variable. Cox proportional hazard models were used to compute unadjusted and adjusted hazard ratios with 95% confidence intervals (CIs) for associations between regimen complexity and number of medications with unplanned hospitalizations over a 3-year period. Receiver operating characteristics curves with corresponding areas under the curve were calculated for regimen complexity and number of medications in relation to unplanned hospitalizations. The population attributable fraction of unplanned hospitalizations was calculated for MRCI and number of medications.Results: In total, 1,125 participants (33.6%) had one or more unplanned hospitalizations. Regimen complexity (hazard ratio 1.22; 95% CI 1.14-1.34) and number of medications (hazard ratio 1.07; 95% CI 1.04-1.09) were both associated with unplanned hospitalizations and had similar sensitivity and specificity (area under the curve 0.641 for regimen complexity and area under the curve 0.644 for number of medications). The population attributable fraction was 14.08% (95% CI 9.62-18.33) for MRCI and 17.61% (95% CI 12.59-22.35) for number of medications.Conclusions: There was no evidence that using a complex tool to assess regimen complexity was better at predicting unplanned hospitalization than number of medications. [ABSTRACT FROM AUTHOR]