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- Comendeiro-Maaløe, Micaela, et al.
(författare)
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Acknowledging the role of patient heterogeneity in hospital outcome reporting : Mortality after acute myocardial infarction in five European countries
- 2020
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:2, s. 0228425-0228425
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Hospital performance, presented as the comparison of average measurements, dismisses that hospital outcomes may vary across types of patients. We aim at drawing out the relevance of accounting for patient heterogeneity when reporting on hospital performance.METHODS: An observational study on administrative data from virtually all 2009 hospital admissions for Acute Myocardial Infarction (AMI) discharged in Denmark, Portugal, Slovenia, Spain, and Sweden. Hospital performance was proxied using in-hospital risk-adjusted mortality. Multilevel Regression Modelling (MLRM) was used to assess differences in hospital performance, comparing the estimates of random intercept modelling (capturing hospital general contextual effects (GCE)), and random slope modelling (capturing hospital contextual effects for patients with and without congestive heart failure -CHF). The weighted Kappa Index (KI) was used to assess the agreement between performance estimates.RESULTS: We analysed 46,875 admissions of AMI, 6,314 with coexistent CHF, discharged from 107 hospitals. The overall in-hospital mortality rate was 5.2%, ranging from 4% in Sweden to 6.9% in Portugal. The MLRM with random slope outperformed the model with only random intercept, highlighting a much higher GCE in CHF patients [VPC = 8.34 (CI95% 4.94 to 13.03) and MOR = 1.69 (CI95% 1.62 to 2.21) vs. VPC = 3.9 (CI95% 2.4 to 5.9), MOR of 1.42 (CI95% 1.31 to 1.54) without CHF]. No agreement was observed between estimates [KI = -0,02 (CI95% -0,08 to 0.04].CONCLUSIONS: The different GCE in AMI patients with and without CHF, along with the lack of agreement in estimates, suggests that accounting for patient heterogeneity is required to adequately characterize and report on hospital performance.
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| 2. |
- Kristensen, Pia Kjær, et al.
(författare)
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Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture : A cross-classified multilevel analysis in Sweden
- 2020
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:6
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: One-year mortality after hip-fracture is a widely used outcome measure when comparing hospital care performance. However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analyses investigates hospital (or municipality) variation in patient outcomes in isolation rather than as a component of the underlying patient variation. We therefore aimed to extend the traditional approach to simultaneously estimate both case-mix adjusted hospital and municipality comparisons in order to disentangle the amount of the total patient variation in clinical outcomes that was attributable to the hospital and municipality level, respectively.METHODS: We determined 1-year mortality risk in patients aged 65 or above with hip fractures registered in Sweden between 2011 and 2014. We performed cross-classified multilevel analysis with 54,999 patients nested within 54 hospitals and 290 municipalities. We adjusted for individual demographic, socioeconomic and clinical characteristics. To quantify the size of the hospital and municipality variation we calculated the variance partition coefficient (VPC) and the area under the receiver operator characteristic curve (AUC).RESULTS: The overall 1-year mortality rate was 25.1%. The case-mix adjusted rates varied from 21.7% to 26.5% for the 54 hospitals, and from 18.9% to 29.5% for the 290 municipalities. The VPC was just 0.2% for the hospital and just 0.1% for the municipality level. Patient sociodemographic and clinical characteristics were strong predictors of 1-year mortality (AUC = 0.716), but adding the hospital and municipality levels in the cross-classified model had a minor influence (AUC = 0.718).CONCLUSIONS: Overall in Sweden, one-year mortality after hip-fracture is rather high. However, only a minor part of the patient variation is explained by the hospital and municipality levels. Therefore, a possible intervention should be nation-wide rather than directed to specific hospitals or municipalities.
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