Unwarranted Between-hospital Variation in Mortality, Readmission, and Length of Stay of Urological Admissions: An Important Trigger for Prioritising Quality Targets

Identifying high-impact-opportunity hospitals for improving healthcare quality based on a national population analysis of inter-hospital variation in mortality, readmissions and prolonged length of stay

OBJECTIVES

To study between-hospital variation in mortality, readmissions and prolonged length of stay across Belgian hospitals.

DESIGN

A retrospective nationwide observational study.

SETTING

Secondary and tertiary acute-care hospitals in Belgium.

PARTICIPANTS

We studied 4 560 993 hospital stays in 99 (98%) Belgian acute-care hospitals between 2016 and 2018.

PRIMARY OUTCOME MEASURES

Using generalised linear mixed models, we calculated hospital-specific and Major Diagnostic Category (MDC)-specific risk-adjusted in-hospital mortality, readmissions within 30 days and length of stay above the MDC-specific 90th percentile and assessed between-hospital variation through estimated variance components.

RESULTS

There was strong evidence of between-hospital variation in mortality, readmissions and prolonged length of stay across the vast majority of patient service lines. Overall, should hospitals with upper-quartile risk-standardised rates succeed in improving to the median level, a yearly 4076 hospital deaths, 3671 readmissions and 15 787 long patient stays could potentially be avoided in those hospitals. Our analysis revealed a select set of 'high-impact-opportunity hospitals' characterised by poor performance across outcomes and across a large number of MDCs.

CONCLUSIONS

Analysis of between-hospital variation highlights important differences in patient outcomes that are not explained by known patient or hospital characteristics. Identifying 'high-impact-opportunity hospitals' can help government inspection bodies and hospital managers to establish targeted audits and inspections to generate effective quality improvement initiatives.

Rates Of Patient Safety Indicators In Belgian Hospitals Were Low But Generally Higher Than In US Hospitals, 2016-18

More than two decades ago, the Agency for Healthcare Research and Quality developed its Patient Safety Indicators (PSIs) to monitor potentially preventable and severe adverse events within hospitals. Application of PSIs outside the US was explored more than a decade ago, but it is uncertain whether they remain relevant within Europe, as no up-to-date assessments of overall PSI-associated adverse event rates or interhospital variability can be found in the literature. This article assesses the nationwide occurrence and variability of thirteen adverse events for a case study of Belgium. We studied 4,765,850 patient stays across all 101 hospitals for 2016-18. We established that although adverse event rates were generally low, with an adverse event observed in 0.1 percent of medical hospital stays and in 1.2 percent of surgical hospital stays, they were higher than equivalent US rates and were prone to considerable between-hospital variability. Failure-to-rescue rates, for example, equaled 23 percent, whereas some hospitals exceeded nationwide central line-associated bloodstream infection rates by a factor of 8. Policy makers and hospital managers can prioritize PSIs that have high adverse event rates or large variability, such as failure to rescue or central line-associated bloodstream infections, to improve the quality of care in Belgian hospitals.

Call for Action to Target Interhospital Variation in Cardiovascular Mortality, Readmissions, and Length-of-Stay: Results of a National Population Analysis

BACKGROUND

Excessive interhospital variation threatens healthcare quality. Data on variation in patient outcomes across the whole cardiovascular spectrum are lacking. We aimed to examine interhospital variability for 28 cardiovascular All Patient Refined-Diagnosis-related Groups (APR-DRGs).

METHODS

We studied 103,299 cardiovascular admissions in 99 (98%) Belgian acute-care hospitals between 2012 and 2018. Using generalized linear mixed models, we estimated hospital-specific and APR-DRG-specific risk-standardized rates for in-hospital mortality, 30-day readmissions, and length-of-stay above the APR-DRG-specific 90th percentile. Interhospital variation was assessed based on estimated variance components and time trends between the 2012-2014 and 2016-2018 periods were examined.

RESULTS

There was strong evidence of interhospital variation, with statistically significant variation across the 3 outcomes for 5 APR-DRGs after accounting for patient and hospital factors: percutaneous cardiovascular procedures with acute myocardial infarction, heart failure, hypertension, angina pectoris, and arrhythmia. Medical diagnoses, with in particular hypertension, heart failure, angina pectoris, and cardiac arrest, showed strongest variability, with hypertension displaying the largest median odds ratio for mortality (2.51). Overall, hospitals performing at the upper-quartile level should achieve improvements to the median level, and an annual 633 deaths, 322 readmissions, and 1578 extended hospital stays could potentially be avoided.

CONCLUSIONS

Analysis of interhospital variation highlights important outcome differences that are not explained by known patient or hospital characteristics. Targeting variation is therefore a promising strategy to improve cardiovascular care. Considering their treatment in multidisciplinary teams, policy makers, and managers should prioritize heart failure, hypertension, cardiac arrest, and angina pectoris improvements by targeting guideline implementation outside the cardiology department.

Between-hospital variation in indicators of quality of care: a systematic review

BACKGROUND

Efforts to mitigate unwarranted variation in the quality of care require insight into the 'level' (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores.

METHODS

Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type.

RESULTS

In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%-9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%-33.5%) and lowest for final clinical outcomes (1.4%, 0.6%-4.2%) and patient-reported outcomes (1.0%, 0.9%-1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores.

CONCLUSION

Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered.

PROSPERO REGISTRATION NUMBER

CRD42022315850.