Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data

Abstract

BackgroundHospitalisation for heart failure is common and post-discharge outcomes, including readmission and mortality, are often poor and are poorly understood. The purpose of this study was to examine patient- and hospital-level variation in the risk of 30-day unplanned readmission and mortality following discharge from hospital with a diagnosis of heart failure.MethodsProspective cohort study using data from the Sax Institute’s 45 and Up Study, linking baseline survey (Jan 2006-April 2009) to hospital and mortality data (to Dec 2011). Primary outcomes in those admitted to hospital with heart failure included unplanned readmission, mortality and combined unplanned readmission/mortality, within 30 days of discharge. Multilevel models quantified the variation in outcomes between hospitals and examined associations with patient- and hospital-level characteristics.ResultsThere were 5074 participants with a heart failure admission discharged from 251 hospitals; 1052 (21%) had unplanned readmissions, 186 (3.7%) died, and 1146 (23%) had either/both outcomes within 30 days of discharge. Crude outcomes varied across hospitals, but between-hospital variation explained little of the total variation in outcomes (intraclass correlation coefficients (ICC) after inclusion of patient factors: 30-day unplanned readmission ICC = 0.0125 (p = 0.24); death ICC = 0.0000 (p > 0.99); unplanned readmission/death ICC = 0.0266 (p = 0.07)). Patient characteristics associated with a higher risk of unplanned readmission included: being male (male vs female, adjusted odds ratio (aOR) = 1.18, 95% CI: 1.00–1.37); prior hospitalisation for cardiovascular disease (aOR = 1.44, 1.08–1.91) and for anemia (aOR = 1.36, 1.14–1.63); comorbidities at admission (severe vs none: aOR = 1.26, 1.03–1.54); lower body-mass-index (obese vs normal weight: aOR = 0.77, 0.63–0.94); and lower social interaction scores. Similarly, risk of 30-day mortality was associated with patient- rather than hospital-level factors, in particular age (≥85y vs 45–< 75y: aOR = 3.23, 1.93–5.41) and comorbidity (severe vs none: aOR = 2.68, 1.82–3.94).ConclusionsThe issue of high readmission and mortality rates in people with heart failure appear to be system-wide, with the variation in these outcomes essentially attributable to variation between patients rather than hospitals. The findings suggest that there are limitations in using these outcomes as hospital performance measures in this patient population and support the need for patient-centred strategies to optimise heart failure management and outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2152-0) contains supplementary material, which is available to authorized users.

Survival After an Acute Heart Failure Admission. Twelve-Month Outcomes From the NSW HF Snapshot Study

“…We recruited a real-world cohort of patients, and the prospective design enabled the collection of data beyond those normally contained in administrative datasets including an objective assessment of frailty. The 30-day readmission and 12-month mortality rates in the NSW HF Snapshot are similar to rates reported both in Australia [2][3][4] and internationally [6,7]. No adjudication was undertaken on the cause of readmission or death.…”

“…The best available Australian data on acute HF admissions and outcomes come from the Acute Decompensated Heart Failure Registry International-Asia Pacific (ADHERE-AP) [1] which is now more than 10 years old and through the integration of administrative datasets [2][3][4]. These studies are limited by only including a small number of Australian centres of excellence in the case of ADHERE-AP or by being a retrospective analysis of administrative datasets.…”

Association between continuity of provider-adjusted regularity of general practitioner contact and unplanned diabetes-related hospitalisation: a data linkage study in New South Wales, Australia, using the 45 and Up Study cohort

“…MBS and PBS data were linked by the Sax Institute using a unique identifier provided by the DHS. Quality assurance data on the data linkage show false-positive and false-negative rates of <0.5 and <0.1%, respectively 23…”

Effect Modification of Multimorbidity on the Association Between Regularity of General Practitioner Contacts and Potentially Avoidable Hospitalisations

“…Quality assurance of the data linkage method showed false-positive and false-negative rates of < 0.5 and < 0.1%, respectively. 20,21 Institutional ethics committee approval was obtained from Curtin University Human Research Ethics Committee (RD- and the NSW Population and Health Services Research Ethics Committee (HREC/17/CIPHS/ 37). Consent was given by all participants in the 45 and Up Study for their information to be used in approved studies, and for follow-up and data linkage.…”