Thirty-Day Unplanned Readmissions Following Hospitalisation for Atrial Fibrillation in Australia and New Zealand

Long-term outcomes after hospitalization for atrial fibrillation or flutter

BACKGROUND AND AIMS

Atrial fibrillation (AF) and flutter are common causes of hospitalizations but contemporary long-term outcomes following these episodes are uncertain. This study assessed outcomes up to 10 years after an acute AF or flutter hospitalization.

METHODS

Patients hospitalized acutely with a primary diagnosis of AF or flutter from 2008-17 from all public and most private hospitals in Australia and New Zealand were included. Kaplan-Meier methods and flexible parametric survival modelling were used to estimate survival and loss in life expectancy, respectively. Competing risk model accounting for death was used when estimating incidence of non-fatal outcomes.

RESULTS

A total of 260 492 adults (mean age 70.5 ± 14.4 years, 49.6% female) were followed up for 1 068 009 person-years (PY), during which 69 167 died (incidence rate 6.5/100 PY) with 91.2% survival at 1 year, 72.7% at 5 years, and 55.2% at 10 years. Estimated loss in life expectancy was 2.6 years, or 16.8% of expected life expectancy. Re-hospitalizations for heart failure (2.9/100 PY), stroke (1.7/100 PY), and myocardial infarction (1.1/100 PY) were common with respective cumulative incidences of 16.8%, 11.0%, and 7.1% by 10 years. Re-hospitalization for AF or flutter occurred in 21.3% by 1 year, 35.3% by 5 years, and 41.2% by 10 years (11.6/100 PY). The cumulative incidence of patients undergoing catheter ablation of AF was 6.5% at 10 years (1.2/100 PY).

CONCLUSIONS

Patients hospitalized for AF or flutter had high death rates with an average 2.6-year loss in life expectancy. Moreover, re-hospitalizations for AF or flutter and related outcomes such as heart failure and stroke were common with catheter ablation used infrequently for treatment, which warrant further actions.

Avoiding double counting: the effect of bundling hospital events in administrative datasets for the interpretation of rural-urban differences in Aotearoa New Zealand

BACKGROUND AND OBJECTIVES

All publicly funded hospital discharges in Aotearoa New Zealand are recorded in the National Minimum Dataset (NMDS). Movement of patients between hospitals (and occasionally within the same hospital) results in separate records (discharge events) within the NMDS and if these consecutive health records are not accounted for hospitalization (encounters) rates might be overestimated. The aim of this study was to determine the impact of four different methods to bundle multiple discharge events in the NMDS into encounters on the relative comparison of rural and urban Ambulatory Sensitive Hospitalization (ASH) rates.

METHODS

NMDS discharge events with an admission date between July 1, 2015, and December 31, 2019, were bundled into encounters using either using a) no method, b) an "admission flag", c) a "discharge flag", or d) a date-based method. ASH incidence rate ratios (IRRs), the mean total length of stay and the percentage of interhospital transfers were estimated for each bundling method. These outcomes were compared across 4 categories of the Geographic Classification for Health.

RESULTS

Compared with no bundling, using the date-based method resulted in an 8.3% reduction (150 less hospitalizations per 100,000 person years) in the estimated incidence rate for ASH in the most rural (R2-3) regions. There was no difference in the interpretation of the rural-urban IRR for any bundling methodology. Length of stay was longer for all bundling methods used. For patients that live in the most rural regions, using a date-based method identified up to twice as many interhospital transfers (5.7% vs 12.4%) compared to using admission flags.

CONCLUSION

Consecutive events within hospital discharge datasets should be bundled into encounters to estimate incidence. This reduces the overestimation of incidence rates and the undercounting of interhospital transfers and total length of stay.

Long-Term Pattern and Associated Costs of Re-hospitalisations in Patients After Index Atrial Fibrillation Admission in Western Australia, 2011-2017

AIMS

This study aimed to determine total and cardiovascular-specific re-hospitalisation patterns and associated costs within 2 years of index atrial fibrillation (AF) admission in Western Australia (WA).

METHOD

Patients aged 25-94 years, surviving an index (first-in-period) AF hospitalisation (principal diagnosis) from 2011 to 2015 were identified from WA-linked administrative data and followed for 2 years. Person-level hospitalisation costs ($ Australian dollar) were computed using the Australian Refined Diagnosis Related Groups and presented as median with first and third quartile costs.

RESULTS

The cohort comprised 17,080 patients, 59.0% men, mean age 69.6±13.3 (standard deviation) years, and 59.0% had a CHA2DS2-VA (one point for congestive heart failure, hypertension, diabetes mellitus, vascular disease or age 65-74 years; two points for prior stroke/transient ischaemic attack or age ≥75 years) score of 2 or more. Within 2 years, 13,776 patients (80.6%) were readmitted with median of 2 (1-4) readmissions. Among total all-cause readmissions (n=54,240), 40.1% were emergent and 36.6% were cardiovascular-related, led by AF (19.5%), coronary events (5.8%), and heart failure (4.2%). The median index AF admission cost was $3,264 ($2,899-$7,649) while cardiovascular readmission costs were higher, particularly stroke ($10,732 [$4,179-23,390]), AF ablation ($7,884 [$5,283-$8,878]), and heart failure ($6,759 [$6,081-$13,146]). Average readmission costs over 2 years per person increased by $4,746 (95% confidence interval [CI] $4,459-$5,033) per unit increase in baseline CHA2DS2-VA score. The average 2-year hospitalisation costs per patient, including index admission, was $27,820 (95% CI $27,308-$28,333) and total WA costs were $475.2 million between 2011 and 2017.

CONCLUSIONS

Patients after index AF hospitalisation have a high risk of cardiovascular and other readmissions with considerable healthcare cost implications. Readmission costs increased progressively with baseline CHA2DS2-VA score. Better integrated management of AF and coexistent comorbidities is likely key to reducing readmissions and associated costs.