Measuring Hospital-Wide Mortality—Pitfalls and Potential

[Hospital standardized mortality ratio: limits and potential of the indicator for assessing hospital performance in the Brazilian Unified National Health System]

Comparative analyses based on clinical performance indicators to monitor the quality of hospital care have been carried out for decades in several countries, most notably the hospital standardized mortality ratio (HSMR). In Brazil, studies and the adoption of methodological tools that allow regular analysis of the performance of institutions are still scarce. This study aimed to assess the use of HSMR to compare the performance of hospitals funded by the Brazilian Unified National Health System (SUS). The Hospital Information System was the source of data on adult hospitalizations in Brazil from 2017 to 2019. The methodological approach to estimate HSMR was adapted to the available data and included the causes of hospitalization (main diagnosis) responsible for 80% of deaths. The number of expected deaths was estimated using a logistic regression model that included predictor variables widely described in the literature. The analysis was conducted in two stages: (i) hospitalization level and (ii) hospital level. The final risk adjustment model showed a C-statistic of 0.774, which is considered adequate. The variation in HSMR was wide, especially among the worst-performing hospitals (1.54 to 6.77). Private hospitals performed better than public hospitals. Although the limits of the available data and the challenges still face its more refined use, HSMR is applicable and has the potential to become an important tool for assessing hospital performance in the SUS.

The Mayo Clinic Hospital Mortality Reduction Project: Description and Results

EXECUTIVE SUMMARY

Quality improvement, regulatory, and payer organizations use various definitions of hospital mortality as clinical outcome measures. In this prospective study, the authors evaluated a multicomponent intervention aimed at reducing inpatient mortality in a multistate healthcare delivery system. The project was initiated because of a statistically nonsignificant upward trend in mortality suggested by a six-quarter rise in the observed/expected mortality ratio generated by the Vizient Clinical Data Base and Resource Manager. The design of the mortality reduction plan was influenced by the known limitations of using hospital-wide mortality as a quality improvement measure. The primary objective was to reduce mortality through focused care redesign. The project leadership team attempted to implement standardized system-wide improvements while allowing individual hospitals to simultaneously pursue site-specific practice redesign opportunities. Between Q3, 2015, and Q4, 2017, system-wide mortality reduced from 1.78 to 1.53 (per 100 admissions; p = .01). The actual plan implemented in Mayo Clinic's hospitals is included as Appendix A to this article, published online as Supplemental Digital Content. The authors included it to allow comparison with similar efforts at other healthcare systems, as well as to stimulate criticism and discussion by readers.

Trends in hospital standardized mortality ratios for stroke in Japan between 2012 and 2016: a retrospective observational study

OBJECTIVE

Stroke is one of the leading causes of death and disability, and imposes a major healthcare burden. The aim of this study was to determine the characteristics of hospital standardized mortality ratios (HSMRs) for stroke in Japan for the year 2012-16 to describe the trend.

DESIGN

Retrospective observational study.

SETTING

Data from the Japanese administrative database.

PARTICIPANTS

All hospital admissions for stroke were identified from diagnostic procedures combination (DPC) database from 2012 to 2016.

MAIN OUTCOME MEASURES

HSMR was calculated using the actual number of in-hospital deaths and expected deaths. To obtain the expected death number, a logistic regression model was developed to get the coefficient with a number of explanatory variables. Predictive accuracy of the logistic models was assessed using c-index and calibration was evaluated using the Hosmer-Lemeshow test.

RESULTS

A total of 63 084 patients admitted for stroke from January 2012 to December 2016 were analyzed. HSMRs showed declining tendency over these 5 years, suggesting stroke-related mortality has been improving. While the HSMRs varied from year to year, a wide variation was also seen among the different hospitals in Japan. The proportion of hospitals with HSMR less than 100 increased from 41.0% in 2012 to 59.0% in 2016.

CONCLUSION

This study demonstrated that HSMR can be calculated using DPC data and found wide variation in HSMR of stroke among hospitals in Japan and enabled us to image the trend. By examining these trends, facilities, authorities and provinces can initiate designs that will ultimately lead to an upgraded healthcare delivery system.

Why, what and how do European healthcare managers use performance data? Results of a survey and workshop among members of the European Hospital and Healthcare Federation

Objective of this study was to better understand the use of performance data for evidence-based decision-making by managers in hospitals and other healthcare organisations in Europe in 2019. In order to explore why, what and how performance data is collected, reported and used, we conducted a cross-sectional study based on a self-reported online questionnaire and a follow-up interactive workshop. Our study population were participants of a pan-European professional Exchange Programme and their hosts (n = 125), mostly mid-level hospital managers. We found that a substantial amount of performance data is collected and reported, but could be utilised better for decision-making purposes. Motivation to collect and report performance data is equally internal and external, for improvement as well as for accountability purposes. Benchmarking between organisations is recognised as being important but is still underused. A plethora of different data sources are used, but more should be done on conceptualising, collecting, reporting and using patient-reported data. Managers working for privately owned organisations reported greater use of performance data than those working for public ones. Strategic levels of management use performance data more for justifying their decisions, while managers on operational and clinical levels use it more for day-to-day decision-making. Our study showed that, despite the substantial and increasing use of performance data for evidence-based management, there is room and need to further explore and expand its role in strategic decision-making and supporting a shift in healthcare from organisational accountability towards the model of learning organisations.

Statewide Longitudinal Progression of the Whole-Patient Measure of Safety in South Carolina

Meaningful improvement in patient safety encompasses a vast number of quality metrics, but a single measure to represent the overall level of safety is challenging to produce. Recently, Perla et al. established the Whole-Person Measure of Safety (WPMoS) to reflect the concept of global risk assessment at the patient level. We evaluated the WPMoS across an entire state to understand the impact of urban/rural setting, academic status, and hospital size on patient safety outcomes. The population included all South Carolina (SC) inpatient discharges from January 1, 2008, through to December 31, 2013, and was evaluated using established definitions of highly undesirable events (HUEs). Over the study period, the proportion of hospital discharges with at least one HUE significantly decreased from 9.7% to 8.8%, including significant reductions in nine of the 14 HUEs. Academic, large, and urban hospitals had a significantly lower proportion of hospital discharges with at least one HUE in 2008, but only urban hospitals remained significantly lower by 2013. Results indicate that there has been a decrease in harm events captured through administrative coded data over this 6-year period. A composite measure, such as the WPMoS, is necessary for hospitals to evaluate their progress toward reducing preventable harm.

Reducing Length of Hospital Stay Does Not Increase Readmission Rates in Early-Stage Gastric, Colon, and Lung Cancer Surgical Cases in Japanese Acute Care Hospitals

Background

The Japanese government has worked to reduce the length of hospital stay by introducing a per-diem hospital payment system that financially incentivizes the timely discharge of patients. However, there are concerns that excessively reducing length of stay may reduce healthcare quality, such as increasing readmission rates. The objective of this study was to investigate the temporal changes in length of stay and readmission rates as quality indicators in Japanese acute care hospitals.

Methods

We used an administrative claims database under the Diagnosis Procedure Combination Per-Diem Payment System for Japanese hospitals. Using this database, we selected hospitals that provided data continuously from July 2010 to March 2014 to enable analyses of temporal changes in length of stay and readmission rates. We selected stage I (T1N0M0) gastric, colon, and lung cancer surgical patients who had been discharged alive from the index hospitalization. The outcome measures were length of stay during the index hospitalization and unplanned emergency readmissions within 30 days after discharge.

Results

From among 804 hospitals, we analyzed 42,585, 15,467, and 40,156 surgical patients for gastric, colon, and lung cancer, respectively. Length of stay was reduced by approximately 0.5 days per year. In contrast, readmission rates were generally stable at approximately 2% or had decreased slightly over the 4-year period.

Conclusions

In early-stage gastric, colon, and lung cancer surgical patients in Japan, reductions in length of stay did not result in increased readmission rates.

[Variation in hospital performance according to payment sources in the states of São Paulo and do Rio Grande do Sul, Brazil]

In Brazil, the combined presence of public and private interests in financing and provision of healthcare services stands out clearly in hospital care. Financing arrangements adopted by hospitals (the public Brazilian Unified National Health System - SUS and/or health plans and/or out-of-pocket payment) can affect quality of care. Studies have analyzed the hospital standardized mortality ratio (HSMR) in relation to quality improvements. The objective was to analyze HSMR according to source of payment for the hospitalization and the hospital's financing arrangement. The study analyzed secondary data and causes that accounted for 80% of hospital deaths. HSMR was calculated for each hospital and payment source. Hospitals with worse-than-expected performance (HSMR > 1) were mostly large public hospitals. HSMR was higher in the SUS, including between admissions in the hospital. Despite the study's limitations, the findings point to inequalities in results of care. Efforts are needed to improve the quality of hospital services, regardless of the payment sources.

Which clinical scenarios do surgeons record as complications? A benchmarking study of seven hospitals

OBJECTIVES

To investigate agreement and potential differences in the application and interpretation of the definition among surgical departments of various hospitals.

DESIGN

24 cases were formulated including general, trauma, gastrointestinal and vascular surgery, and based on points of discussion about the definition and ambiguities regarding complication registration as encountered in daily practice. The cases were presented to the surgical staff and residents in seven Dutch hospitals, using the national registration system of complications and an electronic response system.

RESULTS

In total, 134 participants responded. Interpretation differences were particularly found regarding: (1) complications considered as logical consequences of a surgical procedure; (2) complications occurring after radiological interventions; (3) severity criteria such as when to consider a complication as a '(probably) permanent damage or function loss'; (4) registering a cancelled operation as a complication and (5) patients with serial complications during hospital stay.

CONCLUSIONS

The definition of surgical complications as currently applied in the Netherlands does not ensure a uniform complication registration. Improvement of this registration system is mandatory before benchmarking of these findings in the public domain is appropriate. Modifications of the current definition of a surgical complication, and improved consensus about specific clinical situations and training of surgeons might improve the quality of benchmarking.

Survival curves to support quality improvement in hospitals with excess 30-day mortality after acute myocardial infarction, cerebral stroke and hip fracture: a before-after study

OBJECTIVES

To evaluate survival curves (Kaplan-Meier) as a means of identifying areas in the clinical pathway amenable to quality improvement.

DESIGN

Observational before-after study.

SETTING

In Norway, annual public reporting of nationwide 30-day in-and-out-of-hospital mortality (30D) for three medical conditions started in 2011: first time acute myocardial infarction (AMI), stroke and hip fracture; reported for 2009. 12 of 61 hospitals had statistically significant lower/higher mortality compared with the hospital mean.

PARTICIPANTS

Three hospitals with significantly higher mortality requested detailed analyses for quality improvement purposes: Telemark Hospital Trust Skien (AMI and stroke), Østfold Hospital Trust Fredrikstad (stroke), Innlandet Hospital Trust Gjøvik (hip fracture).

OUTCOME MEASURES

Survival curves, crude and risk-adjusted 30D before (2008-2009) and after (2012-2013).

INTERVENTIONS

Unadjusted survival curves for the outlier hospitals were compared to curves based on pooled data from the other hospitals for the 30-day period 2008-2009. For patients admitted with AMI (Skien), stroke (Fredrikstad) and hip fracture (Gjøvik), the curves suggested increased mortality from the initial part of the clinical pathway. For stroke (Skien), increased mortality appeared after about 8 days. The curve profiles were thought to reflect suboptimal care in various phases in the clinical pathway. This informed improvement efforts.

RESULTS

For 2008-2009, hospital-specific curves differed from other hospitals: borderline significant for AMI (p=0.064), highly significant (p≤0.005) for the remainder. After intervention, no difference was found (p>0.188). Before-after comparison of the curves within each hospital revealed a significant change for Fredrikstad (p=0.006). For the three hospitals, crude 30D declined and they were non-outliers for risk-adjusted 30D for 2013.

CONCLUSIONS

Survival curves as a supplement to 30D may be useful for identifying suboptimal care in the clinical pathway, and thus informing design of quality improvement projects.