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PAPERS: Brian Jarman, Simon Gault, Bernadette Alves, Amy Hider, Susan Dolan, Adrian Cook, Brian Hurwitz, and Lisa I Iezzoni Explaining differences in English hospital death rates using routinely collected data BMJ 1999; 318: 1515-1520 [Abstract] [Full text]

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Admission rate effects may have been under-stated

Tom Hennell   (8 June 1999)

Data won't support authors' conclusions

John P Bunker   (15 July 1999)

Admission rate effects may have been under-stated 8 June 1999
Tom Hennell, strategic analysit NHS Executive North West Send response to journal: Re: Admission rate effects may have been under-stated	EDITOR: Jarman et al. present an intriguing analysis (1) - but I do not yet think we can state with confidence, 'More doctors means fewer deaths'. As the authors make clear, there has been a lively discussion on comparative hospital death rates in the United States. From this debate two points emerge clearly; for any given population the standardised admissions rate is positively correlated with the standardised mortality rate - but is inversely correlated with the standardised hospital death rate (defined as any death within 30 days of a hospital admission)(2,3). Where a population is admitted to hospital more frequently, then a higher proportion of admissions will not be associated with subsequent death, and hence there will be a lower apparent rate of hospital mortality. It was therefore most informative that the authors included with their explanatory variables a calculation of the standardised admission ratio (though not apparently separated into 'all cases' and 'emergencies', for the two versions of their model). Unfortunately, the figures used were the aggregates for the Health Authority of hospital location, rather than individually for each hospital's emergency catchment area (often very different). Even in this half-baked form, standardised admissions entered significantly into both the 'all cases' and 'emergency' multiple regression models. It is not impossible that a fully specified version of this variable might not displace some or both the 'doctor' variables One way to resolve this issue would be to exploit a generally observed feature of the NHS in England, that there tends to be relatively little overlap in the geographical catchment areas of acute hospitals for adult emergency admissions. Hence it should be possible to repeat the authors' analysis exactly - but aggregated by electoral ward of residence rather than by hospital of admission. The aggregate discharge data would be the same (except that true standardised admission rates could be used). The community data could then be used directly (with GP numbers per head calculated using FH registers) - but the hospital data would need to be cross-attributed. It would also then be possible to match the hospital mortality data set with community data on general mortality and life expectancy. Tom Hennell Strategic Analyst NHS Executive North West 1. Jarman B, Gault S, Alves B, Hider A, Dolan S, Cook A, Hurwitx B, Iezzoni LI. Explaining differences in English hospital death rates using routinely collected data. BMJ 1999; 318:1515-20. 2. Welch WP, Miller ME, Welch HG, Fisher ES, Wennberg JE. Geographic variation in expenditures for physicians' services in the United States. N Engl J Med 1993;328:621-7. 3. Health Care Financing Administration. Medicare hospital information report. 1992 Technical supplement. Section D. Hospitalization and mortality data for states. Washington, D.C.: Department of Health and Human Services, 1992. 4. Manheim LM, Feinglass J, Shortell SM, Hughes EFX. Regional variation in Medicare hospital mortality. Inquiry 1992;29:55-66.
Data won't support authors' conclusions 15 July 1999
John P Bunker Send response to journal: Re: Data won't support authors' conclusions	Editor Efforts to compare the quality of care among hospitals have defeated many investigators in the past. To the list of failures the Journal has added the paper by Jarman and his associates that attempts to explain differences in English hospital death rates using routinely collected data (1). Their major finding is an inverse association between hospital mortality rates and the number of hospital doctors and general practitioners, from which they conclude that the ratio of doctors to population "seem to be critical determinants of standardised hospital death rates; the higher these ratios, the lower the death rates". By implication, and as widely interpreted by the press, hospitals with fewer doctors have, as a result, higher death rates. This may well be true, but the data are an inadequate basis for drawing that conclusion. The strength or weakness of such investigations hinges on the accuracy of the measurement of prognostic or risk factors in patients treated by the hospitals being compared. In the present study, severity of the primary illness could not be estimated and comorbidity was limited to a count of sub-diagnoses for each patient in Hospital Episode Statistics. The inadequacy of such routine data has been well documented by the NHS Executive (2), by Iezzoni (3, 4), who is listed as a coauthor of the current paper, and by Jencks (5), while the impact of comorbidity, when measured carefully, on mortality has been demonstrated (6). The dangers of using inadequate information has been shown by Iezonni and her colleagues who reported the counter-intuitive finding that many sub-diagnoses "(eg., adult-onset diabetes mellitus, essential hypertension, previous myocardial infarction, angina, and ventricular premature beats)" were associated with lower death rates (3). Much the same finding had previously been reported by Jencks and his associates (5). Severity of illness and comorbidity are best judged prospectively, preferably in "consultation with physicians" (3). Second best is retrospective individual patient record review comparing condition specific diagnoses and procedures case by case. The least satisfactory approach is to rely on routinely collected undifferentiated data, as was done in the study by Jarman and his associates. The authors are aware of possible shortcomings of their approach, writing that "a matched pair study of patients admitted to hospitals with high and low standardised mortality ratios could help to elucidate [their] findings." Short of such an investigation, the public, as well as the profession, is left to draw conclusions that may very well be incorrect. John P Bunker MD FRCP Visiting Professor Department of Epidemiology and Public Health University College London School of Medicine Nick Black Professor Department of Public Health and Policy London School of Hygiene and Tropical Medicine 1 Jarman B, Gault S, Alves B, Hider A, Dolan S, Cook A, Hurwitz B, Iezzoni LI. Explaining differences in English hospital death rates using routinely collected data. BMJ 1999;318:1515-20. 2 NHS Executive. Quality and performance in the NHS: clinical indicators. NHSE June 1999. 3 Iezonni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T. Comorbidities, complications, and coding bias: does the number of diagnosis codes matter in predicting in-hospital mortality? JAMA 1992;267:2197-2203/ 4 Iezzoni LI, Schwartz M, Ash AS, Mackiernan YD. Does severity explain differences in hospital length of stay for pneumonia patients? J Health Serv Res Policy 1996;1:65-76. 5 Jencks SF, Williams DK, Kay TL. Assessing hospital-associated deaths from discharge data: the role of length of stay and comorbidities JAMA 1988;260:2240-46 6 Imamura K, Black N. Does comorbidity affect the outcome of surgery? Total hip replacement in the UK and Japan . Int J Qual Health Care 1998;10:113-123.