Hospital Comparisons Based on Mortality
Revisiting the Choice of Postadmission Timeframe and Evaluating the Contribution of Cause-of-death Data, France, 2009
Bibliographic Data
| ID | 9104443 |
|---|---|
| Authors | Agathe Lamarche-Vadel, Agathe Lamarche‐Vadel (Université Paris-Sud, corresponding author), Marcus Ngantcha (Centre d'Épidémiologie sur les Causes Médicales de Décès, corresponding author), Marie-Annick Le Pogam, Marie‐Annick Le Pogam (0000-0003-1672-3644, Santé Publique France), Walid Ghosn (0000-0003-2013-4586, Centre d'Épidémiologie sur les Causes Médicales de Décès, corresponding author), Catherine Grenier (0000-0002-8066-3992, Santé Publique France), Laurence Meyer (0000-0001-5707-2062, Bicêtre Hospital), Grégoire Rey (0000-0001-7291-9444, Centre d'Épidémiologie sur les Causes Médicales de Décès, corresponding author) |
| Year | 2015 |
| Volume | 53 |
| Issue | 8 |
| Pages | 736-742 |
| Publication date | 2015-08-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0000000000000376 |
| PMID | 26125416 |
| OpenAlex | W2417740849 |
| Language | EN |
| References cited | 27 |
BACKGROUND: In-hospital mortality is widely used to judge the quality of hospital care, but is biased by discharge patterns. Fixed-timeframe indicators have thus been recommended. However, the 30-day postadmission indicator may underestimate hospital-wide mortality, as patients dying in hospital >30 days after admission are considered as survivors. OBJECTIVES: To identify the most relevant timeframes and to assess the contribution of cause-of-death data. METHODS: The 2009 French hospital discharge database was linked to vital status records and to the causes of death register for 11.5 million hospital stays by beneficiaries of French general health insurance. Correlations and agreements between the 30-day hospital standardized mortality ratio (HSMR) and the in-hospital, 60-, 90-, 180-, and 365-day postadmission HSMRs were estimated. RESULTS: A total of 7.8%, 1.5%, and 0.5% of patients who died during their hospital stay were considered as survivors by the 30-, 60-, and 90-day HSMRs, respectively. The 30-day HSMR correlated strongly with the 60-day HSMR (Pearson coefficient=0.92), and their agreement on outlier status was excellent (κ coefficient=0.80). The association remained substantial at 90 days, but weakened at 180 days and even more so at 365 days. Regardless of the timeframe, exclusion of deaths likely due to independent causes barely modified the indicators. CONCLUSIONS: This nationwide study shows that 60- and 90-day HSMRs encompass in-hospital deaths better than the 30-day HSMR, while capturing the same interhospital variations. They should thus be preferred. The contribution of cause-of-death data to hospital-wide indicators seems negligible
Cause of death · Health care · Hospital care · Mortality rate · Standardized mortality ratio · Demography · Emergency Medicine · Frailty in Older Adults · Heart Failure Treatment and Management · Internal Medicine · Medicine · Sepsis Diagnosis and Treatment · Surgery
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| Citation velocity | historical |
|---|---|
| Highly cited | No |