Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study

Abstract

BackgroundHeart failure (HF) and chronic obstructive pulmonary disease (COPD) lead to unplanned hospital activity, but our understanding of what drives this is incomplete.ObjectivesTo 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.DesignObservational study.SettingEnglish NHS.ParticipantsAll patients admitted to acute non-specialist hospitals as an emergency for HF or COPD.InterventionsNone.Main outcome measuresOne-year mortality and 30-day emergency readmission following the patient’s first unplanned admission (‘index admission’) for HF or COPD.Data sourcesPatient-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.ResultsOne-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.LimitationsData 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.ConclusionsFollowing 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 workHospital variations in ED visits could be investigated using existing data despite coding limitations. Primary care management could be explored using individual-level linked databases.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

Risk factors for all-cause hospital readmission following exacerbation of COPD: a systematic review and meta-analysis

“…Previous COPD and non-COPD hospitalisations in the previous year also significantly increased the risk for 30-day readmission by 53% to 56% and 60% to 64%, respectively [38,39]. Consistent with other studies, GOTO et al [31] found that frequent exacerbators (defined as two hospitalisations in the past year) BOTTLE [21] GERSHON [32] GOTO [31] JACOBS [35] SHARIF [44] SIMMERING [45] TZY-CHYI YU [48] Overall (I 2 =95.4%, p=0.000) had a 2.5-fold increase in odds of readmission compared to non-frequent exacerbators. Disease severity of COPD was also a risk factor for readmission and has been evaluated using different tools.…”

“…Patients' insurance was reported as a risk/protective factor in five studies: four in the USA and one in Europe [19,31,35,38,40] (tables S2 and S3). Smaller hospital size (<100 beds) and fewer doctors were reported as significant readmission risk factors with 2.27-fold and 67% increased odds of readmission, respectively [21]. Staying in medium-sized hospitals compared to large hospitals decreased the odds of readmission by 5% [35].…”

“…Health system-related risk factors Length of stay (LOS) was reported to be a significant risk factor for 30-day readmission; whilst in general a longer LOS was associated with increased risk of readmission, some studies found patients with the [19] BOLLU [20] BOTTLE [21] CANDRILLI [22] GOTO [31] JACOBS [35] SHAH [43] SHARIF [44] SIMMERING [45] Overall HIJJAWI [34] JACOBS [35] SHARIF [44] SIMMERING [45] SINGH [46] Overall (I 2 =59%, p=0.029) shortest LOS were at higher risk than those who stayed slightly longer. For example, compared to 1-3 days, CANDRILLI et al [22] found patients who stayed for >10 days or for 8-10 days had increased odds of readmission by 64% and 25%, respectively, but there was 18% reduced odds of readmission for those who stayed for 4-7 days.…”

Prediction of 30-Day Readmission for COPD Patients Using Accelerometer-Based Activity Monitoring

“…A previous study emphasized the clinical index, including age, prior missed outpatient appointments, length of hospital stay, and comorbidities, to predict readmission [15]. However, the most valuable index is still unknown.…”

Low Skeletal Muscle Mass Independently Predicts Mortality in Patients with Chronic Heart Failure after an Acute Hospitalization

“…Similarly, sarcopenia was associated with 1-year mortality in individuals < 75 years old but not in older patients. It is likely that other factors (e.g., cognitive and socioeconomic factors, adherence to follow-up, type of comorbidities, and number of comorbidities) exert a more consequential effect than sarcopenia on the survival of the elderly [20, 21]. …”