Cost-effectiveness of active tuberculosis screening among high-risk populations in low tuberculosis incidence countries: a systematic review, 2008 to 2023.

BackgroundIn countries with a low TB incidence (≤ 10 cases/100,000 population), active pulmonary tuberculosis (PTB) mostly affects vulnerable populations with limited access to healthcare. Thus, passive case-finding systems may not be successful in detecting and treating cases and preventing further transmission. Active and cost-effective search strategies can overcome this problem.AimWe aimed to review the evidence on the cost-effectiveness (C-E) of active PTB screening programmes among high-risk populations in low TB incidence countries.MethodsWe performed a systematic literature search covering 2008-2023 on PubMed, Embase, Center for Reviews and Dissemination, including Database of Abstracts of Reviews of Effects (DARE), National Health Services Economic Evaluation Database (NHS EED), Global Index Medicus and Cochrane Central Register of Controlled Trials (CENTRAL).ResultsWe retrieved 6,318 articles and included nine in this review. All included studies had an active case-finding approach and used chest X-ray, tuberculin skin test, interferon-gamma release assay and a symptoms questionnaire for screening. The results indicate that screening immigrants from countries with a TB incidence > 40 cases per 100,000 population and other vulnerable populations as individuals from isolated communities, people experiencing homelessness, those accessing drug treatment services and contacts, is cost-effective in low-incidence countries.ConclusionIn low-incidence countries, targeting high-risk groups is C-E. However, due to the data heterogenicity, we were unable to compare C-E. Harmonisation of the methods for C-E analysis is needed and would facilitate comparisons. To outline comprehensive screening and its subsequent C-E analysis, researchers should consider multiple factors influencing screening methods and outcomes.

Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study.

BACKGROUND: For years, in Catalonia and in the rest of Spain, there has been a deficit and an unequal geographical distribution of health professionals specializing in pediatrics, especially in rural areas. Among the proposals to improve this situation is the promotion of the use of information and communication technologies (ICT) among users and professionals. Moreover, with the outbreak of COVID-19, the use of telehealth has become an essential tool, with an overall increase in non-face-to-face visits, including in primary care pediatrics. In this context, telemedicine, when used in primary care pediatrics, can be an effective means of improving families' access to medical care. Currently, in Catalonia, telemedicine involving patients and health professionals is used in pediatric primary care through telephone consultation and asynchronous teleconsultation (eConsulta). Video consultation is in practice not used, although it could have different applications. OBJECTIVE: The aim of this study is to evaluate the feasibility of a video consultation process with physical examination in acute pediatric pathology in rural areas among primary care professionals. In addition, the level of satisfaction with these remote consultations will be assessed from the perspective of both the users and the health care professionals. METHODS: We will conduct a prospective experimental study to analyze the possibility of using video consultation in pediatric acute care in primary care in central Catalonia (Spain). A minimum of 170 children aged between 0 and 14 years attending the primary care center (PCC) for acute illness for a period of 1 year will be included in the study. Initially, the telemetric visit, including a physical examination, will include a nurse at the patient and family's side and a pediatrician who will participate remotely. Subsequently, the pediatrician will visit the patient in person and the physical examination and diagnosis made during the remote visit will be compared with the physical examination and diagnosis of the face-to-face visit, which is considered the gold standard. RESULTS: Recruitment was planned to begin in the second half of 2023 and continue for at least 1 year. It is anticipated to be a good resource for a variety of acute pediatric conditions in primary care. The evaluation will focus on the feasibility of performing live remote visits and comparing their diagnostic accuracy with that of face-to-face visits. CONCLUSIONS: We believe that this study could provide evidence on the feasibility and diagnostic accuracy of video consultation in pediatric acute primary care in a rural setting, as well as on satisfaction with video consultations among both users and professionals. If proven useful in addressing the acute needs of children in a variety of situations, it could become a digital health tool that improves the overall pediatric primary care service in rural areas, for both families and professionals. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52946.

Correction: Machine Learning Model for Predicting Mortality Risk in Patients With Complex Chronic Conditions: Retrospective Analysis.

[This corrects the article DOI: 10.2196/52782.].

Correction: Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study.

[This corrects the article DOI: 10.2196/52946.].

Impact of COVID-19 on the Pediatric Primary Care Model in Catalonia: Analysis of Changes in the Number and Type of Face-to-Face and Remote Visits.

Background: The outbreak of COVID-19 has turned the care model of health systems around the world upside down. The health care crisis has led to opportunities for digital health to deliver quality care, and the system has been redirected toward telemedicine. In Catalonia, Spain, as of March 2020, the pattern of visits in primary care pediatric consultations changed, such that face-to-face visits decreased in favor of non-face-to-face visits. Objective: This study aimed to analyze variations in the types of pediatric visits in primary care centers in Catalonia before and after the onset of COVID-19. Methods: This was a descriptive observational study based on administrative data. The number and type of visits to primary care pediatric services in Catalonia between January 2019 and December 2022 were studied. Results: A drop of more than 80% in face-to-face visits and an increase of up to 15 times in remote visits were observed as of March 2020 compared to the previous year. Subsequently, the face-to-face attendance rate began to recover, although it did not reach the same rate as before COVID-19. Non-face-to-face visits were maintained, representing more than 20% of the total after more than 2 years of the pandemic. Conclusions: COVID-19 has been the trigger for a transition in the types of visits to primary care pediatric services. The COVID-19 pandemic was a clear catalyst for the integration of telemedicine in Catalan pediatric health care. In this context, although face-to-face consultations have recovered in absolute numbers, after the pandemic period, the weight of telemedicine has increased.

Assessing the impact of haemodynamic monitoring with CardioMEMS on heart failure patients: a cost-benefit analysis.

AIMS: The objective of this study was to perform a cost-benefit analysis of the CardioMEMS HF System (Abbott Laboratories, Abbott Park, IL, USA) in a heart failure (HF) clinic in Spain by evaluating the real-time remote monitoring of pulmonary artery pressures, which has been shown to reduce HF-related hospitalizations and improve the quality of life for selected HF patients. Particularly, the study aimed to determine the value of CardioMEMS in Southern Europe, where healthcare costs are significantly lower and its effectiveness remains uncertain. METHODS AND RESULTS: This single-centre study enrolled all consecutive HF patients (N = 43) who had been implanted with a pulmonary artery pressure sensor (CardioMEMS HF System); 48.8% were females, aged 75.5 ± 7.0 years, with both reduced and preserved left ventricular ejection fraction; 67.4% of them were in New York Heart Association Class III. The number of HF hospitalizations in the year before and the year after the sensor implantation was compared. Quality-adjusted life years gained based on a literature review of previous studies were calculated. The rate of HF hospitalizations was significantly lower at 1 year compared with the year before CardioMEMS implantation (0.25 vs. 1.10 events/patient-year, hazard ratio 0.22, P = 0.001). At the end of the first year, the usual management outperformed the CardioMEMS HF System. By the end of the second year, the CardioMEMS system is estimated to reduce costs compared with usual management (net benefits of €346). CONCLUSIONS: Based on the results, we suggest that remote monitoring of pulmonary artery pressure with the CardioMEMS HF System represents a midterm and long-term efficient strategy in a healthcare setting in Southern Europe.

Machine Learning Model for Predicting Mortality Risk in Patients With Complex Chronic Conditions: Retrospective Analysis.

Background: The health care system is undergoing a shift toward a more patient-centered approach for individuals with chronic and complex conditions, which presents a series of challenges, such as predicting hospital needs and optimizing resources. At the same time, the exponential increase in health data availability has made it possible to apply advanced statistics and artificial intelligence techniques to develop decision-support systems and improve resource planning, diagnosis, and patient screening. These methods are key to automating the analysis of large volumes of medical data and reducing professional workloads. Objective: This article aims to present a machine learning model and a case study in a cohort of patients with highly complex conditions. The object was to predict mortality within the following 4 years and early mortality over 6 months following diagnosis. The method used easily accessible variables and health care resource utilization information. Methods: A classification algorithm was selected among 6 models implemented and evaluated using a stratified cross-validation strategy with k=10 and a 70/30 train-test split. The evaluation metrics used included accuracy, recall, precision, F1-score, and area under the receiver operating characteristic (AUROC) curve. Results: The model predicted patient death with an 87% accuracy, recall of 87%, precision of 82%, F1-score of 84%, and area under the curve (AUC) of 0.88 using the best model, the Extreme Gradient Boosting (XGBoost) classifier. The results were worse when predicting premature deaths (following 6 months) with an 83% accuracy (recall=55%, precision=64% F1-score=57%, and AUC=0.88) using the Gradient Boosting (GRBoost) classifier. Conclusions: This study showcases encouraging outcomes in forecasting mortality among patients with intricate and persistent health conditions. The employed variables are conveniently accessible, and the incorporation of health care resource utilization information of the patient, which has not been employed by current state-of-the-art approaches, displays promising predictive power. The proposed prediction model is designed to efficiently identify cases that need customized care and proactively anticipate the demand for critical resources by health care providers.

Evaluating Person-Centred Integrated Care to People with Complex Chronic Conditions: Early Implementation Results of the ProPCC Programme.

Introduction: The evaluation of integrated care programmes for high-need high-cost older people is a challenge. We aim to share the early implementation results of the ProPCC programme in the North-Barcelona metropolitan area, in Catalonia, Spain. Methods: We analysed the intervention with retrospective data from May 2018 to December 2021 by describing the cohort complexity and by showing its 6-months pre-post impact on time spent at home and resources used: primary care visits, emergency department visits, hospital admissions and hospital stay. Findings: 264 cases were included (91% at home; 9% in nursing homes). 6-month pre vs. 6-months post results were (mean, p-value): primary care visits 8.2 vs. 11.5 (p < 0.05); emergency department visits 1.4 vs. 0.9 (p < 0.05); hospital admissions 0.7 vs. 0.5 (p < 0.05); hospital stay 12.8 vs. 7.9 days (p < 0.05). Time spent at home was 169.2 vs.174.2 days (p < 0.05). Conclusion: Early implementation of the ProPCC programme results in an increase in time spent at home (up to 3%) and significant reductions in emergency department attendance (-37.2%) and hospital stays (-38.3%). The increased use of primary care resources is compensated by the hospital resources savings, with a result in the average total cost of -46.3%.