Direct risk standardisation: a new method for comparing casemix adjusted event rates using complex models

BMC Medical Research Methodology

Michael J Campbell¹  Richard M Jacques¹  Jon Nicholl¹ 

[1] School of Health and Related Research (ScHARR), University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK

关键词: Casemix adjustment;    Logistic regression models;    Hospital performance;    Standardised mortality ratio;    Standardisation;   

Others  :  866613
DOI  :  10.1186/1471-2288-13-133

 received in 2013-03-21, accepted in 2013-10-25,  发布年份 2013

【 摘 要 】

Background

Comparison of outcomes between populations or centres may be confounded by any casemix differences and standardisation is carried out to avoid this. However, when the casemix adjustment models are large and complex, direct standardisation has been described as “practically impossible”, and indirect standardisation may lead to unfair comparisons. We propose a new method of directly standardising for risk rather than standardising for casemix which overcomes these problems.

Methods

Using a casemix model which is the same model as would be used in indirect standardisation, the risk in individuals is estimated. Risk categories are defined, and event rates in each category for each centre to be compared are calculated. A weighted sum of the risk category specific event rates is then calculated. We have illustrated this method using data on 6 million admissions to 146 hospitals in England in 2007/8 and an existing model with over 5000 casemix combinations, and a second dataset of 18,668 adult emergency admissions to 9 centres in the UK and overseas and a published model with over 20,000 casemix combinations and a continuous covariate.

Results

Substantial differences between conventional directly casemix standardised rates and rates from direct risk standardisation (DRS) were found. Results based on DRS were very similar to Standardised Mortality Ratios (SMRs) obtained from indirect standardisation, with similar standard errors.

Conclusions

Direct risk standardisation using our proposed method is as straightforward as using conventional direct or indirect standardisation, always enables fair comparisons of performance to be made, can use continuous casemix covariates, and was found in our examples to have similar standard errors to the SMR. It should be preferred when there is a risk that conventional direct or indirect standardisation will lead to unfair comparisons.

【 授权许可】

   
2013 Nicholl et al.; licensee BioMed Central Ltd.

【 图 表 】

【 参考文献 】

• [1]Inskip H, Beral V, Fraser P, Haskey J: Methods for age-adjustment of rates. Stat Med 1983, 2(4):455-466.
• [2]Rothman KJ: Modern epidemiology. Boston: Little, Brown, and Company; 1986.
• [3]Breslow NE, Day NE: Statistical methods in cancer research. Volume II - The design and analysis of cohort studies. Oxford: Oxford University Press; 1987.
• [4]Chan CK, Feinstein AR, Jekel JF, Wells CK: The value and hazards of standardization in clinical epidemiologic research. J Clin Epidemiol 1988, 41(11):1125-1134.
• [5]Roalfe AK, Holder RL, Wilson S: Standardisation of rates using logistic regression: a comparison with the direct method. BMC Health Serv Res 2008, 8:275. BioMed Central Full Text
• [6]Goldman DA, Brender JD: Are standardized mortality ratios valid for public health data analysis? Stat Med 2000, 19(8):1081-1088.
• [7]Glance LG, Osler T, Shinozaki T: Effect of varying the case mix on the standardized mortality ratio and W statistic: a simulation study. Chest 2000, 117(4):1112-1117.
• [8]Julious SA, Nicholl J, George S: Why do we continue to use standardized mortality ratios for small area comparisons? J Public Health Med 2001, 23(1):40-46.
• [9]Julious SA, George S: Are hospital league tables calculated correctly? Public Health 2007, 121(12):902-904. discussion 905–908
• [10]Pouw ME, Peelen LM, Lingsma HF, Pieter D, Steyerberg E, Kalkman CJ, Moons KG: Hospital standardized mortality ratio: consequences of adjusting hospital mortality with indirect standardization. PLoS One 2013, 8(4):e59160.
• [11]Campbell MJ, Jacques RM, Fotheringham J, Maheswaran R, Nicholl J: Developing a summary hospital mortality index: retrospective analysis in English hospitals over five years. BMJ 2012, 344:e1001.
• [12]Goodacre S, Wilson R, Shephard N, Nicholl J: Derivation and validation of a risk adjustment model for predicting seven day mortality in emergency medical admissions: mixed prospective and retrospective cohort study. BMJ 2012, 344:e2904.
• [13]Hollis S, Yates DW, Woodford M, Foster P: Standardised comparison of performance indicators in trauma: a new approach to case-mix variation. J Trauma 1995, 38:763-766.
• [14]Krumholz HM, Lin Z, Normand S: Measuring hospitals’ clinical outcomes. BMJ 2013, 346:f620.
• [15]Evans TA, Seaton SE, Manktelow BN: Quantifying the potential bias when directly comparing standardised mortality ratios for in-unit neonatal mortality. PLOS one 2013, 8(4):e61237.