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1.
Res Social Adm Pharm ; 20(1): 19-27, 2024 01.
Artigo em Inglês | MEDLINE | ID: mdl-37704533

RESUMO

BACKGROUND: This study evaluated the cost-effectiveness of an intervention based on a training course for community pharmacists and a smoking cessation service (CESAR©), using limited societal and the health provider perspectives. METHODS: Non-randomized controlled trial of 12-months' follow-up. Spanish community pharmacists who were previously trained with CESAR© formed the intervention group (n = 102), and control group delivered usual care (n = 80). CESAR Patients were smokers identified by the community pharmacists when they attended the pharmacy. Data were self-reported. Outcomes were smoking cessation and quality-of-life (EQ-5D-3L) and were collected at baseline, 6, and 12 months. Costs data included direct health costs, work loss, and intervention costs. Smoking cessation was analyzed through logistic regression models. Generalized linear models were carried out for quality-adjusted life year (QALY) and costs. Incremental cost-effectiveness ratio (ICER) and cost-utility ratio (ICUR) were calculated. RESULTS: In total, 800 smoking patients were included in the intervention group and 278 in the control group. Of these, 487 and 151 patients completed the study, respectively. Costs were lower in the intervention group compared to the control group in both perspectives. At 12 months, 54.3% and 37.1% patients from the intervention and the control groups reported smoking cessation, respectively. The difference in probability of cessation in the intervention compared to the control group was 17.6% (CI:0.05; 0.25). The mean QALY was higher in the intervention group [0.03(CI: 0.01; 0.07)]. The ICER and the ICUR were dominant for the intervention group. CONCLUSION: This intervention for smoking cessation showed that the CESAR© intervention, that combined a training for community pharmacists with a smoking cessation service was efficient for smoking cessation and QALY at 12 months' follow-up. TRIAL REGISTRATION: NCT05461066, retrospectively registered (July 15, 2022).


Assuntos
Farmácias , Abandono do Hábito de Fumar , Humanos , Análise Custo-Benefício , Seguimentos , Farmacêuticos
2.
Open Respir Arch ; 5(4): 100277, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37886027

RESUMO

The Spanish Guideline on the Management of Asthma, better known by its acronym in Spanish GEMA, has been available for more than 20 years. Twenty-one scientific societies or related groups both from Spain and internationally have participated in the preparation and development of the updated edition of GEMA, which in fact has been currently positioned as the reference guide on asthma in the Spanish language worldwide. Its objective is to prevent and improve the clinical situation of people with asthma by increasing the knowledge of healthcare professionals involved in their care. Its purpose is to convert scientific evidence into simple and easy-to-follow practical recommendations. Therefore, it is not a monograph that brings together all the scientific knowledge about the disease, but rather a brief document with the essentials, designed to be applied quickly in routine clinical practice. The guidelines are necessarily multidisciplinary, developed to be useful and an indispensable tool for physicians of different specialties, as well as nurses and pharmacists. Probably the most outstanding aspects of the guide are the recommendations to: establish the diagnosis of asthma using a sequential algorithm based on objective diagnostic tests; the follow-up of patients, preferably based on the strategy of achieving and maintaining control of the disease; treatment according to the level of severity of asthma, using six steps from least to greatest need of pharmaceutical drugs, and the treatment algorithm for the indication of biologics in patients with severe uncontrolled asthma based on phenotypes. And now, in addition to that, there is a novelty for easy use and follow-up through a computer application based on the chatbot-type conversational artificial intelligence (ia-GEMA).


La Guía Española para el Manejo del Asma, mejor conocida por su acrónimo en español, GEMA, está a nuestra disposición desde hace más de veinte años. Veintiuna sociedades científicas o grupos relacionados, tanto de España como de otros países, han participado en la preparación y desarrollo de la edición actualizada de GEMA que, de hecho, se ha posicionado en la actualidad a nivel mundial como la guía de referencia sobre asma en lengua española.Su objetivo es prevenir y mejorar la situación clínica de las personas con asma, aumentando el conocimiento de los profesionales sanitarios involucrados en su cuidado. Su propósito es convertir la evidencia científica en recomendaciones prácticas sencillas y fáciles de seguir. Por lo tanto, no se trata de una monografía que reúna todo el conocimiento científico sobre la enfermedad, sino más bien de un documento conciso con lo esencial, diseñado para ser aplicado rápidamente en la práctica clínica de rutina. Las recomendaciones son necesariamente multidisciplinares, están desarrolladas para ser útiles y una herramienta indispensable para médicos de diferentes especialidades, así como para profesionales de enfermería y farmacia.Seguramente, los aspectos más destacados de la guía son las recomendaciones para: establecer el diagnóstico del asma utilizando un algoritmo secuencial basado en pruebas diagnósticas objetivas; el seguimiento de los pacientes, preferentemente basado en la estrategia de lograr y mantener el control de la enfermedad; el tratamiento según el nivel de gravedad del asma utilizando seis escalones, desde la menor hasta la mayor necesidad de medicamentos, y el algoritmo de tratamiento basado en fenotipos para la indicación de biológicos en pacientes con asma grave no controlada. A esto se suma ahora una novedad para su fácil uso y seguimiento a través de una aplicación informática basada en la inteligencia artificial conversacional de tipo chatbot (ia-GEMA).

3.
Front Pharmacol ; 14: 1105434, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37497107

RESUMO

Background: Data analysis techniques such as machine learning have been used for assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used yet to assist community pharmacists with services such as the Minor Ailment Services These services have been implemented to reduce the burden of primary care consultations in general medical practitioners (GPs) and to allow a better utilization of community pharmacists' skills. However, there is a need to refer high-risk patients to GPs. Aim: To develop a predictive model for high-risk patients that need referral assisting community pharmacists' triage through a minor ailment service. Method: An ongoing pragmatic type 3 effectiveness-implementation hybrid study was undertaken at a national level in Spanish community pharmacies since October 2020. Pharmacists recruited patients presenting with minor ailments and followed them 10 days after the consultation. The main outcome measured was appropriate medical referral (in accordance with previously co-designed protocols). Nine machine learning models were tested (three statistical, three black box and three tree models) to assist pharmacists in the detection of high-risk individuals in need of referral. Results: Over 14'000 patients were included in the study. Most patients were female (68.1%). With no previous treatment for the specific minor ailment (68.0%) presented. A percentage of patients had referral criteria (13.8%) however, not all of these patients were referred by the pharmacist to the GP (8.5%). The pharmacists were using their clinical expertise not to refer these patients. The primary prediction model was the radial support vector machine (RSVM) with an accuracy of 0.934 (CI95 = [0.926,0.942]), Cohen's kappa of 0.630, recall equal to 0.975 and an area under the curve of 0.897. Twenty variables (out of 61 evaluated) were included in the model. radial support vector machine could predict 95.2% of the true negatives and 74.8% of the true positives. When evaluating the performance for the 25 patient's profiles most frequent in the study, the model was considered appropriate for 56% of them. Conclusion: A RSVM model was obtained to assist in the differentiation of patients that can be managed in community pharmacy from those who are at risk and should be evaluated by GPs. This tool potentially increases patients' safety by increasing pharmacists' ability to differentiate minor ailments from other medical conditions.

4.
BMC Geriatr ; 20(1): 501, 2020 11 25.
Artigo em Inglês | MEDLINE | ID: mdl-33238894

RESUMO

BACKGROUND: Aging implies a higher prevalence of chronic pathologies and a corresponding increase in medication. The correct adherence and use of the medication are prerequisites for reducing risks of disease progression, comorbidity, and mortality. Medication literacy (ML) is the specific ability to safely access and understand the information available concerning medication, and to act accordingly. Currently, there are few specific instruments that ascertain the extent of ML in the general population. The aim of this work was to analyse ML in a large cohort of pharmacy customers. METHODS: A total of 400 community pharmacy clients were analyzed to assess the level of ML (documental and numeracy) through the validated MedLitRxSE tool. RESULTS: The results showed that out of a total of 400 community pharmacy clients only 136 (34%) had an adequate degree of ML, while the rest of the clients (n = 264; 66%) were adjudged not to have this ability. Statistically significant differences were found between the different age groups in terms of ML (P < 0.001; OR = 0.312; 95% CI: 0.195-0.499), the 51-65 and >65-year age groups having a lower frequency of adequate ML (23.5 and 7.1%, respectively) than the rest of the age groups. A statistically significant increase in adequate ML was observed as the academic level of the clients increased (P < 0.001; OR = 15.403; 95% CI: 8.109-29.257). Multivariate logistic regression confirmed the influence of both variables on ML. CONCLUSIONS: An inadequate ML level was found in community pharmacy clients over the age of 51, and also in those with primary or non-formal studies. Our data add to our knowledge about ML, and should pharmacists and other health professionals to adopt new strategies to prevent, or at least reduce, errors in taking medicines, thus avoiding the undesirable effects of any misuse.


Assuntos
Assistência Farmacêutica , Farmácias , Adulto , Idoso , Escolaridade , Feminino , Humanos , Alfabetização , Masculino , Adesão à Medicação , Pessoa de Meia-Idade , Farmacêuticos
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