Analyzing Discussions Around Rural Health on Twitter During the COVID-19 Pandemic: Social Network Analysis of Twitter Data.

Background: Individuals from rural areas are increasingly using social media as a means of communication, receiving information, or actively complaining of inequalities and injustices. Objective: The aim of our study is to analyze conversations about rural health taking place on Twitter during a particular phase of the COVID-19 pandemic. Methods: This study captured 57 days' worth of Twitter data related to rural health from June to August 2021, using English-language keywords. The study used social network analysis and natural language processing to analyze the data. Results: It was found that Twitter served as a fruitful platform to raise awareness of problems faced by users living in rural areas. Overall, Twitter was used in rural areas to express complaints, debate, and share information. Conclusions: Twitter could be leveraged as a powerful social listening tool for individuals and organizations that want to gain insight into popular narratives around rural health.

Long-Term Effects on Preventing Frailty and Health Care Costs Associated with a Multifactorial Intervention in the Elderly: Three-Year Follow-Up Data from the Pre-Frail 80 Study.

INTRODUCTION: Preventing or delaying frailty has important benefits. Studies show the effectiveness of multifactorial interventions in the frail and pre-frail elderly, but few have evaluated their long-term effectiveness. Frailty and its consequences have been shown to increase the use of health resources. The main aim was to evaluate the long-term effect of a multifactorial primary healthcare intervention in pre-frail elderly people at 36 months and determine the health resources used and their cost. METHODS: A follow-up of a cohort study of patients who participated in a randomized clinical trial in an urban primary care centre in Barcelona was carried out. We included 200 non-institutionalized people aged ≥80 years who met the Fried pre-frailty criteria. The intervention group (IG) received a 6-month interdisciplinary intervention based on physical exercise, Mediterranean diet advice, assessment of inadequate prescribing in polypharmacy patients, and social assessment, while the control group (CG) received standard of care primary healthcare treatment. Sociodemographic variables were collected at baseline. The Fried criteria, comorbidities, and geriatric syndromes were collected at baseline and 12 and 36 months. For the analysis of health costs, data were collected on visits, complementary tests, hospital admissions, and surgical interventions in the last 36 months. Complexity, the rate of expected emergency admission, and the rate of expected mortality were collected at 36 months. Between-group characteristics were compared at baseline and 36 months using the χ2 test and the t test for independent samples. The post-intervention (12-month follow-up) versus longitudinal follow-up (36-month follow-up) comparison used McNemar's test for each group. The nonparametric Mann-Whitney test was used to compare health costs. RESULTS: Of the 200 patients initially included, we evaluated 135 (67.5%) patients who completed the 36-month follow-up. The mean age was 88.5 years and 64.4% were female. At 36 months, the transition to frailty was much lower in the IG than in the CG (22.1% vs. 32.8%, p = 0.013). The total mean health cost at 36 months was 3,110 EUR in the CG and 2,679 EUR in the IG. No significant between-group differences were observed according to Clinical Risk Groups. CONCLUSIONS: A multifactorial, interdisciplinary intervention carried out in primary care prevented frailty in pre-frail elderly people at 36-month follow-up. Although the IG was grouped into higher grade Clinical Risk Groups and therefore had greater morbidity, the cost was lower than that in the CG.

[Primary Healthcare management models in Catalonia: May the best win?] / Modelos de gestión de la Atención Primaria en Cataluña: ¿Que gane el mejor?

OBJECTIVE: In Catalonia, the variety of the provision of Primary Healthcare has sparked intense debates over the last 20 years regarding the efficiency of the various management models. Our study analyzed the differences in the three existing management models of primary healthcare in Catalonia (the Catalan Health Institute, public consortiums and associative base entities). METHODS: The primary data were obtained from the reports of the Results Center of The Observatory of the Health System of Catalonia. Representative indicators were selected and compared with the Kruskall-Wallis test. They were later adjusted for confounding factors. RESULTS: There were differences in the average number of visits per population attended, the percentage of the population attended in the subgroup of population over 75 years of age, the percentage of patients over 74 years with more than twelve appointments, the rate of potentially avoidable hospitalizations (total and in the subgroup of patients with chronic obstructive pulmonary disease (COPD)), polypharmacy, the use of lipid-lowering drugs and the detection of prostate-specific antigen (PSA). When adjusting for confounding variables, the differences disappeared in all of them except for the indicator on the detection of PSA. CONCLUSIONS: The differences favoured mainly the associative base entities disappear when they are corrected for confounding variables. The legal status of each provider does not significantly influence the health outcomes.

OBJETIVO: En Cataluña, la diversificación de la provisión de la Atención Primaria ha suscitado en los últimos 20 años intensos debates en torno a la eficiencia de los diversos modelos de gestión. El objetivo de este trabajo fue analizar las diferencias existentes en resultados de salud entre los modelos clásicos de gestión de la Atención Primaria existentes en Cataluña (Institut Català de la Salut, consorcios públicos y entidades de base asociativa). METODOS: Los datos primarios se obtuvieron de los informes de la Central de resultados del Observatori del Sistema de Salut de Catalunya de la Generalitat de Cataluña. Se seleccionaron indicadores representativos y se compararon con la prueba de Kruskall-Wallis. Posteriormente, se ajustaron por factores de confusión. RESULTADOS: Se observaron diferencias en los indicadores sobre la media de visitas por población atendida, el porcentaje de población asignada atendida en el subgrupo de mayores de 75 años, el porcentaje de pacientes mayores de 74 años con más de doce visitas, la tasa de hospitalizaciones potencialmente evitables, tanto total como en el subgrupo de pacientes con enfermedad pulmonar obstructiva crónica (EPOC), la polimedicación, el uso de hipolipemiantes y la detección del antígeno prostático específico (PSA). Al ajustar por variables confusoras, las diferencias desaparecieron en todos ellos excepto en el indicador sobre la detección del PSA. CONCLUSIONES: Las diferencias favorables a las entidades de base asociativas desaparecen cuando se corrigen por variables confusoras. La fórmula jurídica o de provisión de servicios no parece influir de forma significativa en los resultados de salud poblacionales.

The relationship between effectiveness and costs measured by a risk-adjusted case-mix system: multicentre study of Catalonian population data bases.

BACKGROUND: The main objective of this study is to measure the relationship between morbidity, direct health care costs and the degree of clinical effectiveness (resolution) of health centres and health professionals by the retrospective application of Adjusted Clinical Groups in a Spanish population setting. The secondary objectives are to determine the factors determining inadequate correlations and the opinion of health professionals on these instruments. METHODS/DESIGN: We will carry out a multi-centre, retrospective study using patient records from 15 primary health care centres and population data bases. The main measurements will be: general variables (age and sex, centre, service [family medicine, paediatrics], and medical unit), dependent variables (mean number of visits, episodes and direct costs), co-morbidity (Johns Hopkins University Adjusted Clinical Groups Case-Mix System) and effectiveness.The totality of centres/patients will be considered as the standard for comparison. The efficiency index for visits, tests (laboratory, radiology, others), referrals, pharmaceutical prescriptions and total will be calculated as the ratio: observed variables/variables expected by indirect standardization.The model of cost/patient/year will differentiate fixed/semi-fixed (visits) costs of the variables for each patient attended/year (N = 350,000 inhabitants). The mean relative weights of the cost of care will be obtained. The effectiveness will be measured using a set of 50 indicators of process, efficiency and/or health results, and an adjusted synthetic index will be constructed (method: percentile 50).The correlation between the efficiency (relative-weights) and synthetic (by centre and physician) indices will be established using the coefficient of determination. The opinion/degree of acceptance of physicians (N = 1,000) will be measured using a structured questionnaire including various dimensions. STATISTICAL ANALYSIS: multiple regression analysis (procedure: enter), ANCOVA (method: Bonferroni's adjustment) and multilevel analysis will be carried out to correct models. The level of statistical significance will be p < 0.05.