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Supplemental material, sj-docx-1-dhj-10.1177_20552076231181229 for Integrated health system to assess and manage frailty in community dwelling: Co-design and usability evaluation by Cristian Moral, Rodrigo Pérez-Rodríguez, Elena Villalba-Mora, Jaime Barrio-Cortes, Xavier Ferre and Leocadio Rodríguez-Mañas in DIGITAL HEALTH

Background Clinical practice guidelines (CPGs) have teaching potential for health professionals in training clinical reasoning and decision-making, although their use is limited. The objective was to evaluate the effectiveness of a game-based educational strategy e-EDUCAGUIA using simulated clinical scenarios to implement an antimicrobial therapy GPC compared to the usual dissemination strategies to improve the knowledge and skills on decision-making of family medicine residents. Additionally, adherence to e-EDUCAGUIA strategy was assessed. Methods A multicentre pragmatic cluster-randomized clinical trial was conducted involving seven Teaching Units (TUs) of family medicine in Spain. TUs were randomly allocated to implement an antimicrobial therapy guideline with e-EDUCAGUIA strategy ( intervention) or passive dissemination of the guideline (control). The primary outcome was the differences in means between groups in the score test evaluated knowledge and skills on decision-making at 1 month post intervention. Analysis was made by intention-to-treat and per-protocol analysis. Secondary outcomes were the differences in mean change intrasubject (from the baseline to the 1-month) in the test score, and educational game adherence and usability. Factors associated were analysed using general linear models. Standard errors were constructed using robust methods. Results Two hundred two family medicine residents participated (104 intervention group vs 98 control group). 100 medicine residents performed the post-test at 1 month (45 intervention group vs 55 control group), The between-group difference for the mean test score at 1 month was 11 ( 8.67 to 13.32) and between change intrasubject was 11,9 ( 95% CI 5,9 to 17,9). The effect sizes were 0.88 and 0.75 respectively. In multivariate analysis, for each additional evidence-based medicine training hour there was an increase of 0.28 points (95% CI 0.15–0.42) in primary outcome and in the change intrasubject each year of increase in age was associated with an improvement of 0.37 points and being a woman was associated with a 6.10-point reduction. 48 of the 104 subjects in the intervention group (46.2%, 95% CI: 36.5–55.8%) used the games during the month of the study. Only a greater number of evidence-based medicine training hours was associated with greater adherence to the educational game ( OR 1.11; CI 95% 1.02–1.21). Conclusions The game-based educational strategy e-EDUCAGUIA shows positive effects on the knowledge and skills on decision making about antimicrobial therapy for clinical decision-making in family medicin residents in the short term, but the dropout was high and results should be interpreted with caution. Adherence to educational games in the absence of specific incentives is moderate. Trial registration ClinicalTrials.gov Identifier: NCT02210442. Registered 6 August 2014.

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Additional file 1. Types of chronic diseases considered by the Adjusted Morbidity Group (AMG) in the Community of Madrid at the time of data extraction.

Objetivos: Describir las características de los pacientes crónicos según el nivel de riesgo asignado por los grupos de morbilidad ajustados (GMA). Analizar los factores asociados al nivel de riesgo alto y estudiar el efecto de cada uno de ellos. Dise˜no: Estudio observacional descriptivo transversal con enfoque analítico. Emplazamiento: Atención Primaria (AP). Servicio Madrile˜no de Salud. Participantes: Población de 18.107 pacientes estratificados por los GMA integrados en la historia clínica electrónica de AP de la Comunidad de Madrid. Mediciones principales: Variables sociodemográficas, clínico-asistenciales y de uso de servicios. Se realizó análisis univariado, bivariado y multivariante. Resultados: De los 18.107 pacientes se identificaron 9.866 (54,4%) pacientes crónicos, 444 (4,5%) estratificados como de alto riesgo, 1.784 (18,1%) como de medio riesgo y 7.638 (77,4%) como de bajo riesgo. Los de alto riesgo, comparados con medio y bajo riesgo, tenían una edad media mayor (77,8 [12,9]; 72,1 [12,9]; 50,6 [19,4]), menor porcentaje de mujeres (52,3%, 65%, 61,1%), mayor número de enfermedades crónicas (6,7 [2,4]; 4,3 [1,5]; 1,9 [1,1]), polimedicación (79,1%, 43,3%, 6,2%) y contactos con AP (33,9 [28]; 21,4 [17,3]; 7,9 [9,9]) (p < 0,01). En el multivariante el nivel de riesgo alto se relacionó de manera independiente con la edad > 65 (OR = 1,43; IC 95% = 1,03-1,99), sexo masculino (OR = 3,46; IC 95% = 2,64-4,52), inmovilidad (OR = 6,33; IC 95% = 4,40-9,11), número de enfermedades crónicas (OR = 2,60; IC 95% = 2,41-2,81) (p < 0,01) y número de contactos con AP > 7 (OR = 1,95; IC 95% = 1,36-2,80). Conclusiones: Más de la mitad de la población fue clasificada por los GMA como crónica, y se estratificó en 3 niveles de riesgo que presentaban diferencias en sexo, edad, deterioro funcional, necesidad de cuidados, morbilidad, complejidad, polifarmacia y contactos con AP. La edad > 65, el sexo masculino, la inmovilidad, el número de enfermedades crónicas y los contactos con AP > 7 fueron los factores asociados al alto riesgo. Aims: To describe the characteristics of patients with chronic conditions according to their risk levels assigned by the adjusted morbidity groups (AMG). To analyse the factors associated with a high risk level and to study their effect. Design: Observational cross-sectional study with an analytical focus. Location: Primary care (PC), Madrid Health Service. Participants: Population of 18,107 patients stratified by their risk levels with the AMG in the computerised clinical records of Madrid PC. Main measurements: The variables studied were: socio-demographic, clinical-nursing care and use of services. Univariate, bivariate, and multivariate analysis were performed. Results: Of the 18,107 patients, 9,866(54.4%) were identified as chronic patients, with 444 (4.5%) stratified as high risk, 1784 (18,1%) as medium risk, and 7,638 (77.4%) as low risk. The high risk patients, compared with medium and low risk, had an older mean age [77.8 (SD = 12.9), 72.1 (SD = 12.9), 50.6 (SD = 19.4)], lower percentage of women (52.3%, 65%, 61.1%), a higher number of chronic diseases [6.7 (SD = 2.4), 4.3 (SD = 1.5), 1.9 (SD = 1.1)], polymedication (79.1%, 43.3%, 6.2%), and contact with PC [33.9 (28), 21.4 (17.3), 7.9 (9.9)] (P 65 [1.43 (1.03-1.99), male gender (OR = 3.46, 95% CI = 2.64-4.52), immobility (OR = 6.33, 95% CI = 4.40-9.11), number of chronic conditions (OR = 2.60, 95% CI = 2.41-2.81), and PC contact > 7 times (OR = 1.95, 95% CI = 1.36- 2.80)] (P < .01). Conclusions: More than half of the population is classified by the AMG as a chronic, and it is stratified into 3 risk levels that show differences in gender, age, functional impairment, need for care, morbidity, complexity, and use of Primary Care services. Age > 65, male gender, immobility, number of chronic conditions, and contact with PC > 7 times were the factors associated with high risk.

Fundamentos: Los pacientes crónicos sufren mayor número de problemas de salud y tienen mayores necesidades de asistencia y cuidados. El objetivo de este estudio fue describir la utilización de servicios de salud de Atención Primaria en los pacientes crónicos según el nivel de riesgo asignado por los grupos de morbilidad ajustados (GMA), así como analizar los factores asociados. Sujetos y métodos: Se realizó un estudio transversal. Se incluyeron pacientes ≥ 18 años identificados como crónicos por el estratificador GMA en una zona básica de salud de la Comunidad de Madrid, con una población adscrita de 18.107 habitantes. Se recogieron variables sociodemográficas, clínico-asistenciales y de utilización de servicios, y se clasificaron según el modelo “conductual” en “factores predisponentes”, “factores de necesidad” o “factores facilitadores”. Se empleó un análisis univariado, bivariado y multivariante, ajustando un modelo de regresión lineal múltiple con estimadores robustos. Resultados: Se incluyeron 9.443 pacientes crónicos (el 52,1% de la población de la zona seleccionada), con una edad media de 57,8 años (Desviación estándar [DE]=18,7), siendo mujeres el 62,1%. El 4,7% eran pacientes de alto riesgo, el 18,7% de medio riesgo y el 76,6% presentaba bajo riesgo. La media de contactos/año fue de 14,1 (DE=15,2). 34,4 (DE=27,9) en alto riesgo, 21,8 (DE=17,2) en riesgo medio y 10,1 (DE=10,2) en bajo riesgo. De estos contactos, 7,5 (DE=7,1) fueron con médico y 12,9 (DE=12,9) presenciales. Los factores asociados a mayor utilización fueron el riesgo alto (Coeficiente B [CB]=12,6; IC95%=11,1-14,2), el estar inmovilizado (CB=8,8; IC95%=7,3-10,4), la polimedicación (CB=6; IC95%=5,1-6,9), el ser mujer (CB=1; IC95%=0,4-1,5), el número de enfermedades crónicas (CB=1; IC95%=0,8-1,2) y la edad (CB=0,03; IC95%=0,01-0,05). Conclusiones: La utilización de servicios de Atención Primaria en los pacientes crónicos es elevada y aumenta según el nivel de riesgo asignado por los GMA. El contacto con el médico es superior frente al de la enfermería, y el tipo más frecuente es presencial. La mayor utilización responde a factores predisponentes (ser mujer y la edad) y, sobre todo, de necesidad clínica (alto riesgo, multimorbilidad, polimedicación e inmovilidad). Background: Chronic patients suffer a greater number of health problems and have greater needs for assistance and care. The objective was to describe the use of health services in Primary Care in patients with chronic conditions according to risk level by adjusted morbidity groups (AMG) and analyze the associated factors. Methods: Cross-sectional study. We included patients ≥18 years-old identified as chronic by the stratification tool according to AMG in a basic health area in the Community of Madrid with an assigned population of 18,107 inhabitants. Sociodemographic, clinical-care and use of services variables were collected and were classified according to the “behavioral” model in predisposing, need or facilitators factors. Univariate, bivariate and multiple linear regression adjusted with robust estimators was performed. Results: 9,443 chronic patients (52.1% of the population in the selected zone) were identified, mean age of 57.8 (SD=18.7); 62.1% women. According to their risk level 4.7% were high risk, 18.7% medium risk and 76.6% low risk. The mean number of contacts per year was 14.1 (SD=15.2); 34.4 (SD=27.9) in high risk; 21.8 (SD=17.2) in medium risk and 10.1 (SD=10.2) in low risk. 7.5 (SD=7.1) contacts were with the doctor and 12.9 (SD=12.9) were face- to-face. The factors associated with higher use of services were high risk (Coefficient B[CB]=12.6; IC95%=11-14.2), immobilization (CB=8.8; IC95%=7.3-10.4), polypharmacy (CB=6; IC95%=5- 8.6), female sex (CB=1; IC95%=0.4-1.5), number of chronic diseases (CB=1; IC95%=0.8-1.2) and age (CB=0.03; IC95%=0.01-0.05). Conclusions: The health services utilization in Primary Care in chronic patients is high and increased according with the risk level by AMG. The contact with the doctor is superior to nurse and the most frequent type is face-to-face. The greater utilization of services responds to predisposing factors (female sex and age) and above all to need factors (high risk, immobility, multimorbidity and polypharmacy). Ayuda para la elaboración de tesis doctorales de la Fundación para la Investigación e Innovación Biomédica de Atención Primaria (FIIBAP) de la Comunidad de Madrid.