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

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

Readiness for Change in the Implementation of a 3D Printing Initiative in a Catalan Tertiary Hospital Using the Normalization Process Theory: Survey Study.

BACKGROUND: The high failure rate of innovation projects motivates us to understand the perceptions about resistances and barriers of the main stakeholders to improving success rates. OBJECTIVE: This study aims to analyze the readiness for change in the implementation of a 3D printing project in a Catalan tertiary hospital prior to its implementation. METHODS: We used a web-based, voluntary, and anonymous survey using the Normalization Measurement Development questionnaire (NoMAD) to gather views and perceptions from a selected group of health care professionals at Germans Trias i Pujol University Hospital. RESULTS: In this study, 58 professionals, including heads of service (n=30, 51%), doctors (n=18, 31%), nurses (n=7, 12%), and support staff (n=3, 5%), responded to the questionnaire. All groups saw the value of the project and were willing to enroll and support it. Respondents reported the highest scores (out of 5) in cognitive participation (mean 4.45, SD 0.04), coherence (mean 3.72, SD 0.13), and reflective monitoring (mean 3.80, SD 0.25). The weakest score was in collective action (mean 3.52, SD 0.12). There were no statistically significant differences in scores among professions in the survey. CONCLUSIONS: The 3D printing project implementation should pay attention to preparing, defining, sharing, and supporting the operational work involved in its use and implementation. It should also understand, assess, and communicate the ways in which the new set of practices can affect the users and others around them. We suggest that health officers and politicians consider this experience as a solid ground toward the development of a more efficient health innovation system and as a catalyst for transformation.

Implementation of a vascular access specialist team in a tertiary hospital: a cost-benefit analysis.

BACKGROUND: The use of peripherally inserted central catheters and midline catheters is growing due to their potential benefits. These devices can increase patient safety and satisfaction while reducing the use of resources. As a result, many hospitals are establishing vascular access specialist teams staffed by nurses who are trained in the insertion and maintenance of these catheters. The objective of the study is to evaluate previously to the implementation whether the benefits of introducing ultrasound-guided peripheral venous catheters, midline catheters and peripherally inserted central catheters compared to current practice by a vascular access specialist team outweigh their costs. METHODS: Cost-benefit analysis from the perspective of the healthcare provider based on administrative data. The study estimates the reduction in resources used when changing the current practice for the use of ultrasound-guided midline and PICC catheters, as well as the additional resources required for their use. RESULTS: The use of an ultrasound-guided device on peripherally inserted central carheter, results in a measurable resource reduction of approximately €31. When 3 peripheral venous catheters are replaced by an ultrasound-guided peripherally inserted central catheter, the saving is €63. Similarly, the use of an ultrasound-guided device on a midline catheter, results in a reduction of €16, while each ultrasound-guided midline catheter replacing 3 peripheral venous catheters results in a reduction of €96. CONCLUSION: The benefits of using ultrasound-guided midline and PICC catheters compared to current practice by introducing a vascular access specialist team trained in the implantation of ultrasound-guided catheters, outweigh its cost mainly because of the decrease in hospital stay due to the lowered risk of phebitis. These results motivate the implementation of the service, adding to previous experience suggesting that it is also preferable from the point of view of patient safety and satisfaction.

Cost-effectiveness analysis of the daily HIV pre-exposure prophylaxis in men who have sex with men in Barcelona.

INTRODUCTION: Pre-Exposure Prophylaxis (PrEP) for HIV prevention has been implemented in several countries. Previous literature has shown that its cost-effectiveness (and, under some specifications, cost-saving character) is dependent on the reduction in price due to generics, the time-horizon and its effectiveness. The intervention has never been studied in Catalonia after the approval of the PrEP, a territory with extensive implementation. METHODS: Economic evaluation of the implementation of HIV pre-exposition prophylaxis using administrative data from Men who have Sex with Men (MSM) who receive the treatment (at the generic price) compared with non-implementation. A deterministic compartmental model and a social perspective with a micro-costing approach over the time horizon 2022-2062 are used. A baseline 86% effectiveness of PrEP is assumed. RESULTS: Daily oral PrEP is found to be cost-saving: discounted savings in costs are attained after 16 years, and after 40 years they reach 81 million euros. In terms of health indicators, 10,322 additional discounted QALYs are generated by the intervention. Results are sensitive to sexual behavioral patterns among MSM, the price of PrEP (reduced if offered on-demand), its effectiveness and the discount rate. CONCLUSIONS: The use and promotion of PrEP in Catalonia is predicted to result in substantial health and monetary benefits because of reductions in HIV infections. Short-term investments in the promotion of PrEP will result in important cost-savings in the long term.

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.

Impact of Mass Workplace COVID-19 Rapid Testing on Health and Healthcare Resource Savings.

Background: The epidemiological situation generated by COVID-19 has cast into sharp relief the delicate balance between public health priorities and the economy, with businesses obliged to toe the line between employee health and continued production. In an effort to detect as many cases as possible, isolate contacts, cut transmission chains, and limit the spread of the virus in the workplace, mass testing strategies have been implemented in both public health and industrial contexts to minimize the risk of disruption in activity. Objective: To evaluate the economic impact of the mass workplace testing strategy as carried out by a large automotive company in Catalonia in terms of health and healthcare resource savings. Methodology: Analysis of health costs and impacts based on the estimation of the mortality and morbidity avoided because of screening, and the resulting savings in healthcare costs. Results: The economic impact of the mass workplace testing strategies (using both PCR and RAT tests) was approximately €10.44 per test performed or €5575.49 per positive detected; 38% of this figure corresponds to savings derived from better use of health resources (hospital beds, ICU beds, and follow-up of infected cases), while the remaining 62% corresponds to improved health rates due to the avoided morbidity and mortality. In scenarios with higher positivity rates and a greater impact of the infection on health and the use of health resources, these results could be up to ten times higher (€130.24 per test performed or €69,565.59 per positive detected). Conclusion: In the context of COVID-19, preventive actions carried out by the private sector to safeguard industrial production also have concomitant public benefits in the form of savings in healthcare costs. Thus, governmental bodies need to recognize the value of implementing such strategies in private settings and facilitate them through, for example, subsidies.

A Cost-Benefit Analysis of the COVID-19 Asymptomatic Mass Testing Strategy in the North Metropolitan Area of Barcelona.

BACKGROUND: The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures in the management of the epidemic. Mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to detect possible cases, isolate contacts, cut transmission chains and thus limit the spread of the virus. OBJECTIVE: To evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population during the first and second wave of the epidemic in Catalonia, Spain. METHODOLOGY: Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. RESULTS: Excluding the value of monetized health, the Benefit-Cost ratio was estimated at 0.45, a low value that would seem to advise against mass screening policies. However, if monetized health is included, the ratio is close to 1.20, reversing the interpretation. In other words, the monetization of health is the critical element that tips the scales in favour of the desirability of screening. Results show that the interventions with the highest return are those that maximize the percentage of positives detected. CONCLUSION: Efficient management of resources for the policy of mass screening in asymptomatic populations can generate high social returns. The positivity rate critically determines its desirability. Likewise, precocity in the detection of cases will cut more transmissions in the chain of contagion and increase the economic return of these interventions. Maximizing the value of resources depends on screening strategies being accompanied by contact-tracing and specific in their focus, targeting, for example, high-risk subpopulations with the highest rate of expected positives.

Effectiveness and safety of outpatient parenteral antimicrobial therapy in acute exacerbation of chronic obstructive pulmonary disease.

AIM: We analysed the effectiveness and safety of outpatient parenteral antibiotic therapy (OPAT) in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in patients admitted to home hospitalisation units (HHU). METHODS: Retrospective multicentre study of patients with AECOPD included in the Spanish OPAT Registry during 2 years period. RESULTS: Twenty-seven hospitals included 562 episodes in 361 patients diagnosed COPD GOLD III-IV. The most frequently isolated pathogen was Pseudomonas aeruginosa (38%) and the most frequently used antibiotic was piperacillin-tazobactam (20%). The effectiveness of OPAT defined as the rate of improvement or recovery was 93.4%. The safety of OPAT defined as no adverse drug events and no infectious or catheter-related complications was 89.3%. Moreover, the risk of hospital readmission was not greater in patients with AECOPD aged >80 years. No differences in the effectiveness or safety were observed when OPAT was administered by patients and/or caregivers. CONCLUSION: Patients with AECOPD who require parenteral antimicrobial therapy can be managed effectively and safely in HHU, avoiding hospital stays, readmissions and complications.

Intravenous antimicrobial therapy in the hospital-at-home setting: data from the Spanish Outpatient Parenteral Antimicrobial Therapy Registry.

AIM: To evaluate outpatient parenteral antimicrobial therapy (OPAT) in the hospital-at-home (HaH) model, using data from a Spanish registry. PATIENTS & METHODS: We describe episodes/characteristics of patients receiving OPAT. RESULTS: Four thousand and five patients were included (mean age 66.2 years), generating 4416 HaH episodes, 4474 infections and 5088 antibiotic treatments. Most patients were from the hospital admission ward and emergency department. Respiratory, urinary and intra-abdominal infections predominated (72%). Forty-six different antimicrobials were used, including combinations of ≥ 2 drugs (20.7%). Most HaH episodes had a successful outcome (91%). CONCLUSION: Our findings are similar to those obtained previously although our study case profiles differ, suggesting that disease processes of greater severity and complexity can be treated using this healthcare model, without compromising patient safety.

[Hospital at home: an opportunity for change]. / Hospitalización a domicilio: oportunidad para el cambio.

The purpose of this paper is to describe the hospital at home (HaH). The HaH is proposed as a tool of the hospital organization to provide a response to the increasing health care demands. It consists of providing hospital range clinical attention at the patient's home instead of institutional care. Patients depend on the hospital, and their health care professionals constitute the staff that provide care. The characteristics of the HaH are: willingness of the patient, a care provider at home, the task to be carried out must be hospital-based, and can be performed at the patient's home. The development of the HaH requires a prolonged clinical leadership as well as good relationship with the referring clinicians. The evaluation must be carried out as part of a continuum of services of the health system. Both clinical effects and repercussions on the hospital organization must be taken into account. The HaH can provide training and knowledge to physicians about real life patients as well as the opportunity to work alongside a multidisciplinary team. The research must always include a rigorous methodology.