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Headline
Factors predicting mortality and readmission following admission with heart failure or chronic obstructive pulmonary disease were identified at both patient and hospital levels.
Abstract
Background:
Heart failure (HF) and chronic obstructive pulmonary disease (COPD) lead to unplanned hospital activity, but our understanding of what drives this is incomplete.
Objectives:
To model patient, primary care and hospital factors associated with readmission and mortality for patients with HF and COPD, to assess the statistical performance of post-discharge emergency department (ED) attendance compared with readmission metrics and to compare all the results for the two conditions.
Design:
Observational study.
Setting:
English NHS.
Participants:
All patients admitted to acute non-specialist hospitals as an emergency for HF or COPD.
Interventions:
None.
Main outcome measures:
One-year mortality and 30-day emergency readmission following the patient’s first unplanned admission (‘index admission’) for HF or COPD.
Data sources:
Patient-level data from Hospital Episodes Statistics were combined with publicly available practice- and hospital-level data on performance, patient and staff experience and rehabilitation programme website information.
Results:
One-year mortality rates were 39.6% for HF and 24.1% for COPD and 30-day readmission rates were 19.8% for HF and 16.5% for COPD. Most patients were elderly with multiple comorbidities. Patient factors predicting mortality included older age, male sex, white ethnicity, prior missed outpatient appointments, (long) index length of hospital stay (LOS) and several comorbidities. Older age, missed appointments, (short) LOS and comorbidities also predicted readmission. Of the practice and hospital factors we considered, only more doctors per 10 beds [odds ratio (OR) 0.95 per doctor; p < 0.001] was significant for both cohorts for mortality, with staff recommending to friends and family (OR 0.80 per unit increase; p < 0.001) and number of general practitioners (GPs) per 1000 patients (OR 0.89 per extra GP; p = 0.004) important for COPD. For readmission, only hospital size [OR per 100 beds = 2.16, 95% confidence interval (CI) 1.34 to 3.48 for HF, and 2.27, 95% CI 1.40 to 3.66 for COPD] and doctors per 10 beds (OR 0.98; p < 0.001) were significantly associated. Some factors, such as comorbidities, varied in importance depending on the readmission diagnosis. ED visits were common after the index discharge, with 75% resulting in admission. Many predictors of admission at this visit were as for readmission minus comorbidities and plus attendance outside the day shift and numbers of admissions that hour. Hospital-level rates for ED attendance varied much more than those for readmission, but the omega statistics favoured them as a performance indicator.
Limitations:
Data lacked direct information on disease severity and ED attendance reasons; NHS surveys were not specific to HF or COPD patients; and some data sets were aggregated.
Conclusions:
Following an index admission for HF or COPD, older age, prior missed outpatient appointments, LOS and many comorbidities predict both mortality and readmission. Of the aggregated practice and hospital information, only doctors per bed and numbers of hospital beds were strongly associated with either outcome (both negatively). The 30-day ED visits and diagnosis-specific readmission rates seem to be useful performance indicators.
Future work:
Hospital variations in ED visits could be investigated using existing data despite coding limitations. Primary care management could be explored using individual-level linked databases.
Funding:
The National Institute for Health Research Health Services and Delivery Research programme.
Contents
- Plain English summary
- Scientific summary
- Chapter 1. Background and research objectives
- Chapter 2. Methods
- Chapter 3. Results
- Pre-regression analysis
- Objective 1: what are the main patient, primary care and hospital factors associated with variation in readmission and mortality rates?
- Objective 2: should accident and emergency attendance and reattendance data be considered alongside readmission metrics when measuring hospital performance in terms of unplanned activity? If so, how?
- Objective 3: how consistently do hospitals perform across different readmission-type metrics?
- Objective 4: comparison of results for heart failure and for chronic obstructive pulmonary disease
- Chapter 4. Discussion of methods and findings
- Chapter 5. Conclusions
- Acknowledgements
- References
- List of abbreviations
About the Series
Article history
The research reported in this issue of the journal was funded by the HS&DR programme or one of its preceding programmes as project number 14/19/50. The contractual start date was in June 2015. The final report began editorial review in June 2017 and was accepted for publication in September 2017. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HS&DR editors and production house have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the final report document. However, they do not accept liability for damages or losses arising from material published in this report.
Declared competing interests of authors
The authors declare no financial support for the submitted work from anyone other than their employer and the National Institute for Health Research (NIHR) as listed above, no spouses, partners or children with relationships with commercial entities that might have an interest in the submitted work and no non-financial interests that may be relevant to the submitted work. Alex Bottle, Paul Aylin and the rest of the Dr Foster Unit at Imperial College London are part funded by Dr Foster®, an independent health-care information company and part of Telstra Health. The Dr Foster Unit is affiliated with the Imperial Centre for Patient Safety and Service Quality, funded by NIHR. Alex Bottle is now a member of the Health Services and Delivery Research panel. The NIHR funded Faiza Chowdhury’s PhD in ‘Common rehabilitation: The overlap between COPD and Heart Failure Rehabilitation’, which feeds into this research alongside her job as a respiratory and general internal medicine doctor.
Last reviewed: June 2017; Accepted: September 2017.
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