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Quirós-González V, Bernal JL, Haro-Pérez AM, Maderuelo-Fernández JA, Santos-Jiménez MT, García-Barrio N, Pavón-Muñoz AL, López-Sánchez E, García-Iglesias MA, Serrano P, Eiros JM. [Validity and usefulness of the RAE-CMBD studying patients hospitalised with influenza]. Rev Esp Quimioter 2023; 36:160-168. [PMID: 36651282 PMCID: PMC10066910 DOI: 10.37201/req/074.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Understanding the hospital impact of influenza requires enriching epidemiological surveillance registries with other sources of information. The aim of this study was to determine the validity of the Hospital Care Activity Record - Minimum Basic Data Set (RAE-CMBD) in the analysis of the outcomes of patients hospitalised with this infection. METHODS Observational and retrospective study of adults admitted with influenza in a tertiary hospital during the 2017/2018 and 2018/2019 seasons. We calculated the concordance of the RAE-CMBD with the influenza epidemiological surveillance registry (gold standard), as well as the main parameters of internal and external validity. Logistic regression models were used for risk adjustment of in-hospital mortality and length of stay. RESULTS A total of 907 (97.74%) unique matches were achieved, with high inter-observer agreement (ƙ=0.828). The RAE-CMBD showed a 79.87% sensitivity, 99.72% specificity, 86.71% positive predictive value and 99.54% negative predictive value. The risk-adjusted mortality ratio of patients with influenza was lower than that of patients without influenza: 0.667 (0.53-0.82) vs. 1.008 (0.98-1.04) and the risk-adjusted length of stay ratio was higher: 1.15 (1.12-1.18) vs. 1.00 (0.996-1.001). CONCLUSIONS The RAE-CMBD is a valid source of information for the study of the impact of influenza on hospital care. The lower risk-adjusted mortality of patients admitted with influenza compared to other inpatients seems to point to the effectiveness of the main clinical and organisational measures adopted.
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Affiliation(s)
- V Quirós-González
- Víctor Quirós González, Dirección de Planificación, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, 28041 Madrid, Spain.
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Quirós-González V, Bueno I, Goñi-Echeverría C, García-Barrio N, Del Oro M, Ortega-Torres C, Martín-Jurado C, Pavón-Muñoz AL, Hernández M, Ruiz-Burgos S, Ruiz-Morandy M, Pedrera M, Serrano P, Bernal JL. [What about the weekend effect? Impact of the day of admission on in-hospital mortality, length of stay and cost of hospitalization]. J Healthc Qual Res 2022; 37:366-373. [PMID: 35659444 DOI: 10.1016/j.jhqr.2022.04.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 03/04/2022] [Accepted: 04/18/2022] [Indexed: 11/28/2022]
Abstract
INTRODUCTION There is no agreement on the existence of the weekend effect in healthcare or, if it exists, on its possible causes. The objective of the study was to evaluate the differences in healthcare outcomes between patients admitted on weekdays or weekends in a high-complexity hospital. METHODS Observational and retrospective study of patients admitted between 2016 and 2019 in a public hospital with more than 1300 beds. Hospitalization episodes were classified according to whether admission took place between Friday at 3:00 p.m. and the following Monday at 8:00 a.m. (weekend admission) or not (admission on weekdays). Mortality, length of stay and associated costs were compared, applying their respective risk-adjustment models. RESULTS Of the total 169,495 hospitalization episodes analyzed, 48,201 (28.44%) corresponded to the weekend, presenting an older age (54.9 years vs. 53.9; P<.001), a higher crude mortality rate (5.22% vs. 4.59%; P<0.001), and a longer average length of stay (7.42 days vs. 6.74; P<.001), than those admitted on weekdays. The median crude cost of stay was lower (€731.25 vs. €850.88; P<0.001). No significant differences were found when applying the adjustment models, with a risk-adjusted mortality ratio of 1.03 (0.99-1.08) vs. 0.98 (0.95-1.01), risk-adjusted length of stay of 1.002 (0.98-1.005) vs. 0.999 (0.997-1.002) and risk-adjusted cost of stay of 0.928 (0.865-0.994) vs. 0.901 (0.843-0.962). CONCLUSION The results of the study reveal that the assistance provided during the weekends does not imply worse health outcomes or increased costs. Comparing the impact between hospitals will require a future homogenization of temporal criteria and risk adjustment models.
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Affiliation(s)
- V Quirós-González
- Oficina Estrategia 2020-2024 «Transforma 12», Hospital Universitario 12 de Octubre, Madrid, España.
| | - I Bueno
- Facultada de Ciencias Jurídicas y Sociales, Universidad Carlos III de Madrid, Madrid, España
| | - C Goñi-Echeverría
- Instituto de Investigación Hospital 12 de Octubre (i+12), Madrid, España; Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - N García-Barrio
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - M Del Oro
- Servicio de Gestión Económica y Contabilidad, Hospital Universitario 12 de Octubre, Madrid, España
| | - C Ortega-Torres
- Servicio de Gestión Económica y Contabilidad, Hospital Universitario 12 de Octubre, Madrid, España
| | - C Martín-Jurado
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - A L Pavón-Muñoz
- Oficina Estrategia 2020-2024 «Transforma 12», Hospital Universitario 12 de Octubre, Madrid, España
| | - M Hernández
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - S Ruiz-Burgos
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - M Ruiz-Morandy
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
| | - M Pedrera
- Servicio de Informática, Hospital Universitario 12 de Octubre, Madrid, España
| | - P Serrano
- Dirección de Planificación, Hospital Universitario 12 de Octubre, Madrid, España
| | - J L Bernal
- Servicio de Análisis de Información y Control de Gestión, Hospital Universitario 12 de Octubre, Madrid, España
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