000121216 001__ 121216
000121216 005__ 20240319081021.0
000121216 0247_ $$2doi$$a10.3389/fmed.2022.1012437
000121216 0248_ $$2sideral$$a131654
000121216 037__ $$aART-2022-131654
000121216 041__ $$aeng
000121216 100__ $$aCouso-Viana, Sabela
000121216 245__ $$aAnalysis of the impact of social determinants and primary care morbidity on population health outcomes by combining big data: A research protocol
000121216 260__ $$c2022
000121216 5060_ $$aAccess copy available to the general public$$fUnrestricted
000121216 5203_ $$aIn recent years, different tools have been developed to facilitate analysis of social determinants of health (SDH) and apply this to health policy. The possibility of generating predictive models of health outcomes which combine a wide range of socioeconomic indicators with health problems is an approach that is receiving increasing attention. Our objectives are twofold: (1) to predict population health outcomes measured as hospital morbidity, taking primary care (PC) morbidity adjusted for SDH as predictors; and (2) to analyze the geographic variability of the impact of SDH-adjusted PC morbidity on hospital morbidity, by combining data sourced from electronic health records and selected operations of the National Statistics Institute (Instituto Nacional de Estadística/INE).MethodsThe following will be conducted: a qualitative study to select socio-health indicators using RAND methodology in accordance with SDH frameworks, based on indicators published by the INE in selected operations; and a quantitative study combining two large databases drawn from different Spain’s Autonomous Regions (ARs) to enable hospital morbidity to be ascertained, i.e., PC electronic health records and the minimum basic data set (MBDS) for hospital discharges. These will be linked to socioeconomic indicators, previously selected by geographic unit. The outcome variable will be hospital morbidity, and the independent variables will be age, sex, PC morbidity, geographic unit, and socioeconomic indicators.AnalysisTo achieve the first objective, predictive models will be used, with a test-and-training technique, fitting multiple logistic regression models. In the analysis of geographic variability, penalized mixed models will be used, with geographic units considered as random effects and independent predictors as fixed effects.DiscussionThis study seeks to show the relationship between SDH and population health, and the geographic differences determined by such determinants. The main limitations are posed by the collection of data for healthcare as opposed to research purposes, and the time lag between collection and publication of data, sampling errors and missing data in registries and surveys. The main strength lies in the project’s multidisciplinary nature (family medicine, pediatrics, public health, nursing, psychology, engineering, geography).
000121216 536__ $$9info:eu-repo/grantAgreement/ES/ISCIII-RICAPPS/RD21-0016-0022$$9info:eu-repo/grantAgreement/ES/MINECO ISCIII FEDER PI21-01470
000121216 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000121216 590__ $$a3.9$$b2022
000121216 592__ $$a0.926$$b2022
000121216 591__ $$aMEDICINE, GENERAL & INTERNAL$$b58 / 169 = 0.343$$c2022$$dQ2$$eT2
000121216 593__ $$aMedicine (miscellaneous)$$c2022$$dQ1
000121216 594__ $$a3.6$$b2022
000121216 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000121216 700__ $$0(orcid)0000-0002-7213-1718$$aBentué-Martínez, Carmen$$uUniversidad de Zaragoza
000121216 700__ $$aDelgado-Martín, María Victoria
000121216 700__ $$aCabeza-Irigoyen, Elena
000121216 700__ $$aLeón-Latre, Montserrat
000121216 700__ $$aConcheiro-Guisán, Ana
000121216 700__ $$aRodríguez-Álvarez, María Xosé
000121216 700__ $$aRomán-Rodríguez, Miguel
000121216 700__ $$aRoca-Pardiñas, Javier
000121216 700__ $$0(orcid)0000-0002-9541-5609$$aZúñiga-Antón, María$$uUniversidad de Zaragoza
000121216 700__ $$aGarcía-Flaquer, Ana
000121216 700__ $$aPericàs-Pulido, Pau
000121216 700__ $$aSánchez-Recio, Raquel
000121216 700__ $$aGonzález-Álvarez, Beatriz
000121216 700__ $$aRodríguez-Pastoriza, Sara
000121216 700__ $$aGómez-Gómez, Irene
000121216 700__ $$aMotrico, Emma
000121216 700__ $$aJiménez-Murillo, José Luís
000121216 700__ $$0(orcid)0000-0003-3154-0723$$aRabanaque, Isabel$$uUniversidad de Zaragoza
000121216 700__ $$aClavería, Ana
000121216 7102_ $$13006$$2435$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Geografía Humana
000121216 773__ $$g9 (2022), 1012437 [9 pp.]$$pFront. med.$$tFrontiers in Medicine$$x2296-858X
000121216 8564_ $$s326883$$uhttps://zaguan.unizar.es/record/121216/files/texto_completo.pdf$$yVersión publicada
000121216 8564_ $$s2270517$$uhttps://zaguan.unizar.es/record/121216/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
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000121216 951__ $$a2024-03-18-16:10:04
000121216 980__ $$aARTICLE