Using hospital mortality rates to judge hospital performance: a bad idea that just won't go away

Lilford, Richard; Pronovost, Peter J.

doi:10.1136/bmj.c2016

Cited by 242 publications

(197 citation statements)

References 25 publications

Supporting

Mentioning

192

Contrasting

Unclassified

Order By: Relevance

“…Over the past decade public healthcare resource allocation has shifted to PHC services at the expense of tertiary hospital budgets. 15 While there is no evidence that services at GSH have deteriorated during this period, and hospital mortality rates can be problematic as measures of quality of care, 17 these data cannot rule out this possibility.…”

Section: Discussionmentioning

confidence: 97%

Medical inpatient mortality at Groote Schuur Hospital, Cape Town, South Africa, 2002-2009

2012

View full text Add to dashboard Cite

Background. Despite the challenges facing healthcare in South Africa, empirical insights into the performance of healthcare services over time are scarce. Methods. We analysed first admissions of adult medical inpatients to Groote Schuur Hospital, Cape Town, from January 2002 to July 2009. Data included age, sex, medical specialty, and date of admission and discharge. We used population group and hospital billing codes as proxy measures for socio-economic status (SES). We calculated the duration of stay in days from the date of admission to discharge, and inpatient mortality rates per 1 000 patient days. Poisson regression was used to estimate mortality rate ratios (MRR) in unadjusted analysis and after adjusting for potential confounders. Annual increases in mortality rates were highest during the first 2 days following admission (increasing from 30.1 to 50.3 deaths per 1 000), and were associated with increasing age, non-paying patient status, black population group and male sex, and were greatest in the emergency ward (adjusted MRR 1.73, comparing 2009 with 2002; 95% CI 1.49 -2.01). Discussion. Increasing medical inpatient mortality rates at a large South African academic hospital were most marked during the first 2 days after admission and appeared greatest among emergency medical inpatients.

show abstract

Section: Discussionmentioning

confidence: 97%

Medical inpatient mortality at Groote Schuur Hospital, Cape Town, South Africa, 2002-2009

2012

View full text Add to dashboard Cite

show abstract

“…5,6 While many clinicians remain confused and sceptical about mortality measures, the concept of detecting 'preventable' hospital deaths has an intuitive appeal to the public, policymakers and politicians. In this paper, we aim to offer clinicians and NHS leaders some practical ways to learn from deaths in acute hospital care.…”

Section: Introductionmentioning

confidence: 99%

Learning from hospital mortality

2016

View full text Add to dashboard Cite

Understanding and learning from hospital deaths is an important component of good clinical practice but current approaches and measures are complex, controversial and difficult to understand. Patients who die are not a homogeneous group but fall into three distinct categories; most learning will be achieved by recognising this and investigating categories of deaths in different ways, relying heavily on qualitative approaches. Numerical measures of overall hospital mortality, such as hospital standardised mortality ratio (HSMR) or measures of 'preventable' deaths, are most unlikely to be helpful at a hospital level and may even give false reassurance, as accuracy of measurement is strongly influenced by factors apart from quality of care.

show abstract

“…The latter are also more susceptible to case-mix variation, care processes outside the direct control of the QI team and to variation in how the case mix is coded. 10,[13][14][15][16] Practice variation can only be identified by collecting data on several providers or facilities and comparing the results. Therefore, measurement usually occurs at the regional or national level.…”

Section: Measuring Practice Variationmentioning

confidence: 99%

“…However, in clinical practice, it can be difficult to be sure that differences in mortality, or in other frequently used clinical outcomes (eg length of stay, readmission rate or patient-reported outcomes), are really the result of differences in the quality of care, rather than of the case mix ('But my patients are different: we treat sicker patients than other centres'). 14 Therefore, valid comparison between centres requires collection of reliable data on variables that might affect outcome (eg age, comorbidity and functional status) as well as reliable coding of the primary diagnosis. 'Coding depth' should also be assessed: hospitals that are systematically better at coding for comorbidities will appear 'better' in comparisons of mortality after adjustment for comorbidity.…”

Section: Interpreting Practice Variation: the Centre Effectmentioning

confidence: 99%

Learning from practice variation to improve the quality of care

Tomson

Veer

2013

Clinical Medicine

View full text Add to dashboard Cite

-Modern medicine is complex and delivered by interdependent teams. Conscious redesign of the way in which these teams interact can contribute to improving the quality of care by reducing practice variation. This requires techniques that are different to those used for individual patient care. In this paper, we describe some of these quality improvement (QI) techniques. The first section deals with the identification of practice variation as the starting point of a systematic QI endeavour. This involves collecting data in multiple centres on a set of quality indicators as well as on case-mix variables that are thought to affect those indicators. Reporting the collected indicator data in longitudinal run charts supports teams in monitoring the effect of their QI effort. After identifying the opportunities for improvement, the second section discusses how to reduce practice variation. This includes selecting the `package' of clinical actions to implement, identifying subsidiary actions to achieve the improvement aim, designing the implementation strategy and ways to incentivise QI.

show abstract

Using hospital mortality rates to judge hospital performance: a bad idea that just won't go away

Abstract: Standardised mortality rates are a poor measure of the quality of hospital care and should not be a trigger for public inquiries such as the investigation at the Mid Staffordshire hospital, say Richard Lilford and Peter Pronovost

Cited by 242 publications

References 25 publications

Medical inpatient mortality at Groote Schuur Hospital, Cape Town, South Africa, 2002-2009

Medical inpatient mortality at Groote Schuur Hospital, Cape Town, South Africa, 2002-2009

Learning from hospital mortality

Learning from practice variation to improve the quality of care

Contact Info

Product

Resources

About