Codesign and Feasibility Testing of a Tool to Evaluate Overweight and Obesity Apps.

BACKGROUND: Digital health interventions and mobile technologies can help to reduce the rates of obesity and overweight conditions. Although weight management apps are widely used, they usually lack professional content and evaluation, so the quality of these apps cannot be guaranteed. The EVALAPPS project aims to design and validate a tool to assess the safety and effectiveness of health-related apps whose main goal is to manage and prevent obesity and overweight conditions. OBJECTIVE: The aim of this paper is two-fold: (a) to co-create and codesign the EVALAPPS assessment tool and (b) to pilot its feasibility among overweight and obese individuals that use weight control apps. METHODS: A mixed-methods approach was used. A multidisciplinary team (n = 12) participated in a co-creation workshop to provide proposals and inputs about the look and feel of the content, usability aspects, appearance, sections, and main features of the EVALAPPS tool. The tool was tested for its feasibility among 31 overweight and obese individuals, attending the CP Endocrinologia i Nutrició SL Clinic for the first time. Participants were asked to use a specific weight control app [Yazio (YAZIO GmbH, Erfurt, Germany), My FitnessPal (MyFitnessPal, Austin, TX, USA) or MyPlate (MyPlate, Santa Monica, CA, USA)] for two weeks and then evaluate them by using the EVALAPPS (EVALAPPS, David Ganyan, Barcelona, Spain) (June 2020, David Ganyan, Barcelona, Spain) tool. Seven participants were phone interviewed to gain more insight into the use of the EVALAPPS tool. RESULTS: The co-creation workshop allowed conceptualizing the EVALAPPS tool. The feasibility study showed that all criteria from the Usability and Functionality dimensions had valid answers, while Reliability, Security, Privacy, and Health indicators were the dimensions with less valid answers. In all three apps, the dimension with the highest score was Usability/functionality, followed by app purpose. Clinical effectiveness and Development were the dimensions with the lowest scores in all three tested weight control apps. CONCLUSIONS: The participation of the multidisciplinary team and end-users in the conceptualization and testing of a tool to assess health apps was feasible and relevant for the usability of the tool.

El rastreo masivo de datos es una segunda oportunidad para mejorar el manejo de los pacientes con fenotipo de hipercolesterolemia familiar / Massive data screening is a second opportunity to improve the management of patients with familial hypercholesterolemia phenotype

Introducción: La Hipercolesterolemia Familiar (HF) es una enfermedad autósómica dominante con una prevalencia estimada entre 1/200-250. Se encuentra infra-tratada e infra-diagnosticada. El rastreo masivo de datos puede incrementar la detección de pacientes con HF. Métodos: Población a estudio: Residentes en la zona sanitaria de cobertura (N: 195.000 habitantes) y con al menos una determinación de colesterol ligado a lipoproteínas de baja densidad (C-LDL) realizada entre el 1 de Enero de 2010 y el 30 de Diciembre de 2019. Se seleccionaron los valores más altos de C-LDL. Criterios de exclusión: síndrome nefrótico, hipotiroidismo, tratamiento hipotiroideo o triglicéridos > 400 mg/dL. Se analizaron 7 algoritmos sugestivos de fenotipo de Hipercolesterolemia Familiar (F-HF).Se seleccionó el algoritmo más eficaz y de fácil traslación a la práctica clínica. Resultados: Partiendo de 6.264.877 asistencias y 288.475 pacientes tras aplicar los criterios de inclusión-exclusión se incluyeron 504.316 analíticas correspondiendo a 106.382 adultos y 10.509 < 18 años. El algoritmo seleccionado presentó una prevalencia de 0.62%.Se detectaron 840 pacientes con fenotipo de Hipercolestereolemia Familiar (F-HF) siendo el 55.8% mujeres y 178 <18 años, El 9.3% tenían antecedentes de enfermedad cardio-vascular (ECV) y 16.4% habían fallecido. El 65% de los pacientes en prevención primaria presentaron valores de C-LDL >130 mg/dL y el 83% en prevención secundaria valores >70mg/dL. Se obtuvo una ratio de 7.64 (1-18) pacientes con HF-P por médico solicitante de analítica.Conclusiones: El rastreo masivo de datos y el perfilado de pacientes son herramientas eficaces y fácilmente aplicables en práctica clínica para la detección de pacientes con HF.(AU)

Introduction: Familial Hypercholesterolemia (FH) is an autosomal dominant disease with an estimated prevalence between 1/200-250. It is under-treated and underdiagnosed. Massive data screening can increase the detection of patients with FH. Methods: Study population: Residents in the health coverage area (N: 195.000 inhabitants) and with at least one determination of cholesterol linked to low-density lipoproteins (LDL-C) carried out between January 1, 2010 and December 30, 2019. The highest LDL-C values were selected. Exclusion criteria: nephrotic syndrome, hypothyroidism, Hypothyroid treatment or triglycerides> 400 mg / dL. Seven algorithms suggestive of Familial Hypercholesterolemia Phenotype (HF-P) were analyzed, selecting the most efficient algorithm that could easily be translated into clinical practice. Results: Based on 6.264.877 assistances and 288.475 patients, after applying the inclusion-exclusion criteria, 504.316 tests were included, corresponding to 106.382 adults and 10.509 <18 years. The selected algorithm presented a prevalence of 0.62%. 840 patients with HF-P were detected, 55.8% being women and 178 <18 years old, 9.3% had a history of cardiovascular disease (CVD) and 16.4% had died. 65% of the patients in primary prevention had LDL-C values> 130 mg / dL and 83% in secondary prevention values> 70mg / dL. A ratio of 7.64 (1-18) patients with HF-P per analytical requesting physician was obtained. Conclusions. Massive data screening and patient profiling are effective tools and easily applicable in clinical practice for the detection of patients with FH.

Massive data screening is a second opportunity to improve the management of patients with familial hypercholesterolemia phenotype. / El rastreo masivo de datos es una segunda oportunidad para mejorar el manejo de los pacientes con fenotipo de hipercolesterolemia familiar.

INTRODUCTION: Familial Hypercholesterolemia (FH) is an autosomal dominant disease with an estimated prevalence between 1/200-250. It is under-treated and underdiagnosed. Massive data screening can increase the detection of patients with FH. METHODS: Study population: Residents in the health coverage area (N: 195.000 inhabitants) and with at least one determination of cholesterol linked to low-density lipoproteins (LDL-C) carried out between January 1, 2010 and December 30, 2019. The highest LDL-C values were selected. EXCLUSION CRITERIA: nephrotic syndrome, hypothyroidism, Hypothyroid treatment or triglycerides> 400 mg / dL. Seven algorithms suggestive of Familial Hypercholesterolemia Phenotype (HF-P) were analyzed, selecting the most efficient algorithm that could easily be translated into clinical practice. RESULTS: Based on 6.264.877 assistances and 288.475 patients, after applying the inclusion-exclusion criteria, 504.316 tests were included, corresponding to 106.382 adults and 10.509 <18 years. The selected algorithm presented a prevalence of 0.62%. 840 patients with HF-P were detected, 55.8% being women and 178 <18 years old, 9.3% had a history of cardiovascular disease (CVD) and 16.4% had died. 65% of the patients in primary prevention had LDL-C values> 130 mg / dL and 83% in secondary prevention values> 70mg / dL. A ratio of 7.64 (1-18) patients with HF-P per analytical requesting physician was obtained. CONCLUSIONS: Massive data screening and patient profiling are effective tools and easily applicable in clinical practice for the detection of patients with FH.

Impacto teórico en la enfermedad coronaria de usar un sistema informatizado de ayuda en la prescripción del tratamiento hipolipemiante / Theoretical impact on coronary disease of using a computerized clinical decision support system in the prescription of lipid-lowering treatment

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Evaluación de un programa de intervención en residencias geriátricas para reducir la frecuentación hospitalaria / Evaluation of an intervention program in Nursing Homes to reduce hospital attendance

Objetivos. Este estudio describe los resultados de un programa de intervención asistencial en residencias geriátricas (RG) y su repercusión en las visitas a urgencias, ingresos hospitalarios urgentes y gasto farmacéutico. Material y métodos. Intervención comunitaria no aleatorizada en RG con un grupo control. Se implanta progresivamente desde 2007 a 2009 en 10 RG (857 plazas) que participaron voluntariamente. Formaron el grupo control 14 RG (1.200 plazas), las que declinaron participar y las que no estaban asignadas a nuestros centros de salud. La intervención consistió en la valoración geriátrica integral y visitas de seguimiento por personal especializado, revisión y adecuación del tratamiento farmacológico, gestión de casos y formación del personal. Resultados. En las RG intervenidas la frecuentación a urgencias disminuyó pasando de1.165‰ (IC 95% 1.100-1.240) en 2006 a 674‰ (IC 95% 620-730) en 2009, mientras que en las no intervenidas se incrementó de 1.071‰ (IC 95% 1.020-1.130) a 1246‰ (IC 95% 1.190-1.310). Los ingresos hospitalarios urgentes se redujeron de 48,4% (IC 95% 45-52) en 2006 a 32,1% (IC 95% 29-35) en 2009, mientras que en el grupo control se incrementó de 43,5% (IC 95% 41-46) a 55,8% (IC 95% 53-59). Se redujo un 9,0% el gasto de farmacia en las RG intervenidas frente a un incremento del 11,9% en las RG control. Conclusiones. El programa de intervención ha demostrado ser efectivo para reducir la frecuentación hospitalaria y de urgencias en los pacientes institucionalizados y permite racionalizar los costes de farmacia(AU)

Objectives. This study describes the outcomes of an intervention program in Nursing Homes and their effects on emergency room attendance, hospital admissions, and pharmaceutical expenditure. Material and methods. This involved non-randomised community intervention in Nursing Homes with a control group. The program was implemented gradually from 2007 to 2009 in 10 Nursing Homes (857 beds) which participated voluntarily. The control group consisted of 14 Nursing homes (1,200 beds), which refused to participate or were not assigned to our Primary Care centres. Intervention consisted of comprehensive geriatric assessment and follow-up visits by trained personnel, review and adjustment of drug treatment, case management and staff training. Results. In the Nursing Homes where the program was carried out, emergency room attendance decreased from 1165‰ (95%CI 1100-1240]) in 2006 to 674‰ (95%CI 620-730) in 2009, while in the control group it increased from 1071 (95%CI 1020-1130) to 1246‰ (95%CI 1190-1310). The hospital admissions also decreased from 48.4% (95%CI 45-52) in 2006 to 32.1% (95%CI 29-35) in 2009, while in the control group increased from 43.5% (95%CI 41-46) to 55.8% (95%CI 53-59). There was also a 9% reduction in pharmacy cost compared with an increase of 11.9% in the control group. Conclusions. The intervention has proved effective at reducing hospital admissions and emergency room attendance in institutionalised patients, thereby streamlining pharmacy costs(AU)

[Evaluation of an intervention program in nursing homes to reduce hospital attendance]. / Evaluación de un programa de intervención en residencias geriátricas para reducir la frecuentación hospitalaria.

OBJECTIVES: This study describes the outcomes of an intervention program in Nursing Homes and their effects on emergency room attendance, hospital admissions, and pharmaceutical expenditure. MATERIAL AND METHODS: This involved non-randomised community intervention in Nursing Homes with a control group. The program was implemented gradually from 2007 to 2009 in 10 Nursing Homes (857 beds) which participated voluntarily. The control group consisted of 14 Nursing homes (1,200 beds), which refused to participate or were not assigned to our Primary Care centres. Intervention consisted of comprehensive geriatric assessment and follow-up visits by trained personnel, review and adjustment of drug treatment, case management and staff training. RESULTS: In the Nursing Homes where the program was carried out, emergency room attendance decreased from 1165‰ (95%CI 1100-1240]) in 2006 to 674‰ (95%CI 620-730) in 2009, while in the control group it increased from 1071 (95%CI 1020-1130) to 1246‰ (95%CI 1190-1310). The hospital admissions also decreased from 48.4% (95%CI 45-52) in 2006 to 32.1% (95%CI 29-35) in 2009, while in the control group increased from 43.5% (95%CI 41-46) to 55.8% (95%CI 53-59). There was also a 9% reduction in pharmacy cost compared with an increase of 11.9% in the control group. CONCLUSIONS: The intervention has proved effective at reducing hospital admissions and emergency room attendance in institutionalised patients, thereby streamlining pharmacy costs.

Prediction of postoperative pulmonary complications in a population-based surgical cohort.

BACKGROUND: Current knowledge of the risk for postoperative pulmonary complications (PPCs) rests on studies that narrowly selected patients and procedures. Hypothesizing that PPC occurrence could be predicted from a reduced set of perioperative variables, we aimed to develop a predictive index for a broad surgical population. METHODS: Patients undergoing surgical procedures given general, neuraxial, or regional anesthesia in 59 hospitals were randomly selected for this prospective, multicenter study. The main outcome was the development of at least one of the following: respiratory infection, respiratory failure, bronchospasm, atelectasis, pleural effusion, pneumothorax, or aspiration pneumonitis. The cohort was randomly divided into a development subsample to construct a logistic regression model and a validation subsample. A PPC predictive index was constructed. RESULTS: Of 2,464 patients studied, 252 events were observed in 123 (5%). Thirty-day mortality was higher in patients with a PPC (19.5%; 95% [CI], 12.5-26.5%) than in those without a PPC (0.5%; 95% CI, 0.2-0.8%). Regression modeling identified seven independent risk factors: low preoperative arterial oxygen saturation, acute respiratory infection during the previous month, age, preoperative anemia, upper abdominal or intrathoracic surgery, surgical duration of at least 2 h, and emergency surgery. The area under the receiver operating characteristic curve was 90% (95% CI, 85-94%) for the development subsample and 88% (95% CI, 84-93%) for the validation subsample. CONCLUSION: The risk index based on seven objective, easily assessed factors has excellent discriminative ability. The index can be used to assess individual risk of PPC and focus further research on measures to improve patient care.