Hospital Standardized Mortality Ratio: Consequences of Adjusting Hospital Mortality with Indirect Standardization

Background: The hospital standardized mortality ratio (HSMR) is developed to evaluate and improve hospital quality. Different methods can be used to standardize the hospital mortality ratio. Our aim was to assess the validity and applicability of directly and indirectly standardized hospital mortality ratios. Methods: Retrospective scenario analysis using routinely collected hospital data to compare deaths predicted by the indirectly standardized case-mix adjustment method with observed deaths. Discharges from Dutch hospitals in the period 2003-2009 were used to estimate the underlying prediction models. We analysed variation in indirectly standardized hospital mortality ratios (HSMRs) when changing the case-mix distributions using different scenarios. Sixty-one Dutch hospitals were included in our scenario analysis. Results: A numerical example showed that when interaction between hospital and case-mix is present and case-mix differs between hospitals, indirectly standardized HSMRs vary between hospitals providing the same quality of care. In empirical data analysis, the differences between directly and indirectly standardized HSMRs for individual hospitals were limited. Conclusion: Direct standardization is not affected by the presence of interaction between hospital and case-mix and is therefore theoretically preferable over indirect standardization. Since direct standardization is practically impossible when multiple predictors are included in the case-mix adjustment model, indirect standardization is the only available method to compute the HSMR. Before interpreting such indirectly standardized HSMRs the case-mix distributions of individual hospitals and the presence of interactions between hospital and case-mix should be assessed

Measuring standardised mortality ratios of hospitals : Challenges and recommendations

Objectives of this thesis This thesis has the following objectives: - To study the effects of ‘referral bias’ and ‘casemix and coding issues’ on the current Dutch HSMR calculation. - To identify potential adjustments in the estimation of the HSMR to improve its validity as a performance indicator. Outline of this thesis The thesis starts with investigating the theoretical method underlying the calculation of the HSMR, the so-called indirect standardisation method. In chapter 2, the indirect standardisation method is compared with the direct standardisation method. Also, pitfalls of HSMR resulting from the indirect standardisation method are discussed, and recommendations are given to reduce the shortcomings of this method. Subsequently, the thesis investigates potential modifications of the currently used model for HSMR calculation. To adjust for casemix differences between hospitals, parameters of comorbidities are included in the model underlying the HSMR calculation. In chapter 3, the commonly used Charlson comorbidity measure is compared with the Elixhauser comorbidity measure. Discriminative performance of the casemix correction models based on these two comorbidity measures is compared and their effects on the HSMRs of individual hospitals are explored. The Dutch HSMR is currently based on in-hospital mortality. However, discharge patterns, average length of hospital stay, and transfers all affect inhospital mortality. In chapter 4, effects of the inclusion of post-discharge mortality on HSMRs are compared with those of in-hospital mortality. In the final part of the thesis we zoom in onto the mortality ratios of specific patient populations, rather than that of an entire hospital population. In chapter 5, the focus is on SMRs of specific diagnosis groups requiring specialised care offered by specialised hospitals. The SMRs of specialised and nonspecialised hospitals are compared and the influence of referral patterns on SMRs is investigated. Current HSMR calculation is based on administrative databases and said to lack important clinical predictors. In chapter 6, the casemix adjustment model for cardiac surgery patients, based on an administrative database, is compared with the validated clinical EuroSCORE prediction model, based on a clinical database. Also influences of the two models on eventual SMRs are compared. Finally, in chapter 7, the results and implications of this thesis are summarised and discussed together with insights and recommendations to improve the validity and utility of HSMRs

The Dutch Hospital Standardised Mortality Ratio (HSMR) method and cardiac surgery: benchmarking in a national cohort using hospital administration data versus a clinical database

Cardiolog

Decontamination of the digestive tract and oropharynx in ICU patients.

Contains fulltext : 79996.pdf (publisher's version ) (Open Access)BACKGROUND: Selective digestive tract decontamination (SDD) and selective oropharyngeal decontamination (SOD) are infection-prevention measures used in the treatment of some patients in intensive care, but reported effects on patient outcome are conflicting. METHODS: We evaluated the effectiveness of SDD and SOD in a crossover study using cluster randomization in 13 intensive care units (ICUs), all in The Netherlands. Patients with an expected duration of intubation of more than 48 hours or an expected ICU stay of more than 72 hours were eligible. In each ICU, three regimens (SDD, SOD, and standard care) were applied in random order over the course of 6 months. Mortality at day 28 was the primary end point. SDD consisted of 4 days of intravenous cefotaxime and topical application of tobramycin, colistin, and amphotericin B in the oropharynx and stomach. SOD consisted of oropharyngeal application only of the same antibiotics. Monthly point-prevalence studies were performed to analyze antibiotic resistance. RESULTS: A total of 5939 patients were enrolled in the study, with 1990 assigned to standard care, 1904 to SOD, and 2045 to SDD; crude mortality in the groups at day 28 was 27.5%, 26.6%, and 26.9%, respectively. In a random-effects logistic-regression model with age, sex, Acute Physiology and Chronic Health Evaluation (APACHE II) score, intubation status, and medical specialty used as covariates, odds ratios for death at day 28 in the SOD and SDD groups, as compared with the standard-care group, were 0.86 (95% confidence interval [CI], 0.74 to 0.99) and 0.83 (95% CI, 0.72 to 0.97), respectively. CONCLUSIONS: In an ICU population in which the mortality rate associated with standard care was 27.5% at day 28, the rate was reduced by an estimated 3.5 percentage points with SDD and by 2.9 percentage points with SOD. (Controlled Clinical Trials number, ISRCTN35176830.