Knowledge and Attitude of Patients Attending Primary Health Care (PHC) or Family Medicine Clinics About Periodic Health Assessment.

Background This study assesses the awareness and perceptions of periodic health assessments (PHA) among patients at primary health care (PHC) and family medicine clinics. Despite PHC's importance in preventive health, previous research indicates a significant gap in the public's knowledge and routine practice of PHA, potentially affected by various demographic factors. Materials & methods A cross-sectional approach was employed in Riyadh, Saudi Arabia, with data gathered via self-administered questionnaires from 382 participants. The survey focused on socio-demographic information, knowledge about PHA, and attitudes towards it. Statistical analysis explored the influence of demographic and clinical factors on individuals' knowledge and attitudes. Results Findings showed that 300 (78.5%) participants had engaged in routine medical examinations, displaying substantial knowledge of PHA. Nevertheless, issues like healthcare accessibility and provider availability were identified as the major barriers, affecting 125 (32.7%) and 84 (22%) participants, respectively. The overall attitude towards PHA was positive, especially among individuals with chronic conditions, emphasizing its perceived benefits in health management. Conclusion The research underscores a generally positive attitude and fair knowledge level regarding PHA among the studied population, alongside significant barriers to participation. Targeted interventions that address these barriers and capitalize on the positive attitudes may enhance PHA uptake, promoting better health outcomes. This study contributes to the understanding of public engagement with PHA, offering insights for improving health promotion and disease prevention strategies.

Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.

BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient data and machine-learning-based targeted learning methods. METHODS: We analyzed electronic health records and laboratory databases from the year 2012 to 2016 of T2D patients from six family medicine clinics (FMCs) delivering the DIABETIMSS program, and five FMCs providing routine care. All FMCs belong to the Mexican Institute of Social Security and are in Mexico City and the State of Mexico. The primary outcome was glycemic control. The study covariates included: patient sex, age, anthropometric data, history of glycemic control, diabetic complications and comorbidity. We measured the effects of DIABETIMSS program through 1) simple unadjusted mean differences; 2) adjusted via standard logistic regression and 3) adjusted via targeted machine learning. We treated the data as a serial cross-sectional study, conducted a standard principal components analysis to explore the distribution of covariates among clinics, and performed regression tree on data transformed to use the prediction model to identify patient sub-groups in whom the program was most successful. To explore the robustness of the machine learning approaches, we conducted a set of simulations and the sensitivity analysis with process-of-care indicators as possible confounders. RESULTS: The study included 78,894 T2D patients, from which 37,767patients received care through DIABETIMSS. The impact of DIABETIMSS ranged, among clinics, from 2 to 8% improvement in glycemic control, with an overall (pooled) estimate of 5% improvement. T2D patients with fewer complications have more significant benefit from DIABETIMSS than those with more complications. At the FMC's delivering the conventional model the predicted impacts were like what was observed empirically in the DIABETIMSS clinics. The sensitivity analysis did not change the overall estimate average across clinics. CONCLUSIONS: DIABETIMSS program had a small, but significant increase in glycemic control. The use of machine learning methods yields both population-level effects and pinpoints the sub-groups of patients the program benefits the most. These methods exploit the potential of routine observational patient data within complex healthcare systems to inform decision-makers.

Costo oportunidad de adolescentes en unidades de medicina familiar / Opportunity cost for adolescents at family medicine clinics

Objective: To determine the opportunity cost for adolescents requiring care at Family Medicine Clinics. Material and Methods: Study of cost performed on 624 patients, 10-19 years of age, Family Medicine Clinics, Pharmacy and Laboratory. A conglomerate sample technique was used (Medical Unit), and proportional sampling internally. Several sociodemographic variables were evaluated, including transfer, waiting time and care. Statistical evaluation included averages, percentages, and confidence intervals of 95 percent. Results: The cost-opportunity for Family Medicine and Pharmacy in the situations evaluated was $10.22 for the teenager, $71.43 for the first family member, and $14.28 for the second person accompanying the child. When they attend all three services, the cost is $12.26, $82.71 and $16.54 respectively. A weighted average cost of opportunity IFOR all three services is $93.18. Conclusions: The largest cost of opportunity for adolescents occurs when waiting for care in Family Medicine. It is suggested that strategies be implemented to decrese waiting times in the various services.

Objetivo. Determinar el costo oportunidad de los adolescentes que demandan atención en las Unidades de Medicina Familiar. Material y Métodos. Estudio de costo oportunidad realizado en 624 usuarios de 10 a 19 años de edad atendidos en tres Unidades de Medicina Familiar, en los servicios de Medicina Familiar, Farmacia y Laboratorio. Se empleó la técnica muestral por conglomerados (Unidad Médica) y al interior por cuota. Se estudiaron variables sociodemográficas y número de acompañantes; se estimó el costo oportunidad para el traslado, espera y atención. El análisis estadístico incluyó promedios, porcentajes e intervalos de confianza del 95 por ciento. Resultados: El costo oportunidad promedio para Medicina Familiar y Farmacia es de $10.22 para el adolescente, de S 71.43 para el acompañante 1 y de $14.28 para el acompañante 2; cuando acuden a los tres servicios es de $12.26, $82.71 y $16.54 respectivamente. El costo oportunidad promedio ponderado cuando acuden a los tres servicios es de $93.18. Conclusión: El mayor costo oportunidad para los adolescentes corresponde a la espera en el servicio de Medicina Familiar. Por lo que se sugiere implementar estrategias que disminuyan el tiempo de espera en los diferentes servicios.