Reduce Health Care Costs Research Articles

Utilization of smartphone technology and wearable technology following TKA.

The widespread adoption of smartphones and wearable technology has introduced innovative approaches in healthcare, particularly in postoperative rehabilitation. These technologies hold significant promise for improving recovery following lower extremity arthroplasty, especially total knee arthroplasty (TKA). Despite growing interest, the evidence on their effectiveness and long-term impact remains variable. This narrative review evaluates the utilization of smartphone applications, wearable devices, and their combined use in postoperative recovery after TKA. Key studies assessing adherence, functional outcomes, patient satisfaction, and healthcare utilization were analyzed to synthesize insights into their effectiveness compared to traditional rehabilitation approaches. Smartphone applications have demonstrated improvements in adherence to rehabilitation plans, pain management, and functional outcomes. For instance, interventions using text-based prompts or interactive platforms enhanced physical activity, reduced narcotic use, and improved patient-reported outcomes such as PROM adherence and range of motion (ROM). Similarly, wearable devices provided accurate feedback on activity levels and step counts, promoting early mobility and strength recovery. Combined approaches leveraging both technologies further enhanced adherence, functional recovery, and patient engagement while reducing healthcare utilization. The integration of smartphone and wearable technologies in TKA rehabilitation shows potential for improving recovery outcomes. While findings generally indicate noninferiority or superiority to conventional methods, limitations exist in standardization, data accuracy, and long-term benefits. Future research should focus on refining these technologies, establishing standardized guidelines, and evaluating their cost-effectiveness in diverse populations. Smartphone and wearable technologies represent safe and effective tools for enhancing postoperative outcomes in TKA patients. Their integration into clinical practice could optimize rehabilitation protocols, improve patient engagement, and potentially reduce healthcare costs.

Biosimilars: A Critical Review of Development, Regulatory Landscape, and Clinical Implications.

The biopharmaceutical industry has witnessed significant growth in the development and approval of biosimilars. These biosimilars aim to provide cost-effective alternatives to expensive originator biosimilars, alleviating financial pressures within healthcare. The manufacturing of biosimilars is a highly complex process that involves several stages, each of which must meet strict regulatory standards to ensure that the final product is highly similar to the reference biologic. To gain regulatory approval, biosimilars must undergo rigorous analytical characterization including in vitro assays, bioanalytical evaluations, and clinical similarity studies like pharmacokinetic (PK), pharmacodynamic (PD) assessments-to demonstrate safety, efficacy, quality comparability with reference products. Leading regulatory agencies such as the European Medicines Agency (EMA), the World Health Organization (WHO), and the United States Food and Drug Administration (US FDA) have established stringent guidelines for biosimilar evaluation and post-marketing surveillance. Despite this regulatory clarity, challenges around interchangeability, market exclusivity, and patent protection often delay market access and limit adoption, particularly in regions where automatic substitution is restricted. Case studies of biosimilars such as rituximab, adalimumab, filgrastim, and trastuzab reveal both advancements and ongoing hurdles in achieving broader market integration. The introduction of biosimilars has shown potential to reduce healthcare costs; for example, a recent analysis indicates a 20-30% cost reduction in the U.S. due to biosimilar adoption. As the biosimilar market expands, collaborative efforts among regulatory bodies, industry stakeholders, and healthcare providers are essential to enhance access to biologic therapies. This collaboration is poised to improve patient outcomes and catalyse transformative change in global healthcare systems.

Implementation of the I-DECIDED® tool for PIVC assessment and decision making: discussion paper.

PIVCs often cause pain, irritation, or infection. Regular and careful catheter checks can decrease complications and improve patient outcomes. Implementation of the I-DECIDED® tool led to fewer idle catheters and complications. We present ideas for implementing the tool and how to overcome some common barriers. Peripheral intravenous catheter (PIVC) assessment and decision making should be evidence based to minimize risks and enhance patient care. Exploring implementation strategies from successful outcome studies can raise health care professionals' awareness, boost adherence to evidence-based protocols, and elevate PIVC care standards. To describe the implementation of the I-DECIDED® device assessment and decision tool for PIVC management in the Australian and Brazilian contexts. The Promoting Action on Research Implementation in Health Services (PARIHS) framework (evidence, context, facilitation) was used to prospectively plan the implementation of the tool in adult inpatient units in Australia and to retrospectively analyze the implementation of the tool in a pediatric inpatient unit in Brazil. Similarities and differences in the implementation studies were explored. Implementation of the tool in Australia and Brazil demonstrated that prevention and early detection of PIVC complications is achievable with standardized assessment and decision prompts. Both contexts witnessed a reduction in idle PIVCs, decreased insertion site complications, improved dressing quality, and significant improvements in documentation following implementation. Common implementation strategies included champions, education, badge cards, and posters. Enabling flexibility and context-specific education strategies was essential. Standardization of PIVC assessment and decision making using the I-DECIDED® tool reduced the prevalence of idle catheters and complications in Australia and Brazil. Implementation of the tool in different contexts confirms its utility and relevance for PIVC management in diverse health care settings. Promotion and adoption of the tool as a PIVC management bundle could increase patient safety and reduce health care costs.

P1251 A Care Pathway for Inflammatory Bowel Disease can Reduce Healthcare Costs and is Cost-Effective

Abstract Background Hospitals in the southwest of the Netherlands collaborate to improve inflammatory bowel disease (IBD) care. As part of this initiative, a standardised care pathway (CP) for the treatment of IBD with biologics and small new molecules has been developed. The CP addresses initiation, switching, and discontinuation of therapy, as well as diagnostic testing and treatment follow-up. The CP has been implemented in six of the eight hospitals to improve patient outcomes, standardise care and reduce healthcare costs. This natural experiment provides an opportunity to evaluate the cost-effectiveness of the CP using a quasi-experimental design. We aimed to estimate the causal effect of CP implementation on costs and health outcomes. Methods A cost-utility analysis with a societal perspective was conducted. Adult patients with an IBD diagnosis for at least 3 months and treated with biologics and small new molecules were eligible for inclusion. Costs were assessed for both standard care (December 2020 - December 2021) and the CP over a one-year period (March 2022 – March 2023), without discounting costs and effects and standardizing costs to 2022. Missing data were handled using single imputation nested within a bootstrap procedure. The analysis employed a difference-in-differences (DiD) approach to estimate causal effects of the CP implementation, controlling for pre-existing differences between hospitals and general time trends that would have occurred without the intervention. For the cost-effectiveness analysis, we utilized the cumulative incremental costs and mean incremental quality adjusted life years (QALYs) from the post-intervention DiD effects. The DiD-derived incremental costs and QALYs were used to calculate the incremental cost-effectiveness ratio (ICER) and construct cost-effectiveness acceptability curves using normal approximation. Results Approximately 25% of the eligible population was included. At baseline, patients in intervention (n=842) and control hospitals (n=331) had comparable characteristics in terms of age, sex, diagnosis and comorbidities. The DiD-analysis showed cost savings primarily driven by reduced hospital costs (-€1,107; 95%CI: -€2,130 to -€109) while maintaining quality of life (QALY difference: 0.01; 95%CI: -0.02 to 0.04). The ICER was located in the southeast corner of the cost-effectiveness plane, indicating that the treatment with the CP is a dominant strategy compared to standard care (Figure 1). Conclusion A CP for the treatment of IBD with biologics and small new molecules was developed to improve IBD care and reduce healthcare costs. Our results showed that standardising IBD care is effective for reducing healthcare costs, while maintaining quality of life.

P0952 Effect of a Care Pathway for Inflammatory Bowel Disease on Patient Outcomes and Healthcare Utilization: results of the IBD Value Study

Abstract Background Eight hospitals in the southwest of the Netherlands collaborate to improve care for patients with inflammatory bowel disease (IBD). This collaboration aims to deliver high quality and uniform care across the region. To achieve this, a care pathway (CP) was developed and implemented for the management of IBD with biologicals or small new molecules. The CP is a decision-support tool that provides guidelines for medication prescribing, procedures, treatment adjustments, and recommendations for follow-up. The aim of this study is to evaluate the effect of a CP on patient outcomes and healthcare utilization. Methods We designed a longitudinal multicentre non-randomised cohort study with a baseline observation period (December 2020 – December 2021) and a follow-up period (March 2022 – March 2023), in which adult patients with IBD treated with biologics or small new molecules were included (1). Outcomes were collected according to the International Consortium for Health Outcomes Measurement (ICHOM) standard set from electronic medical records or through validated questionnaires. Effect of the CP on these outcomes were analysed with case-mix adjusted (generalized) linear mixed models. Results A total of 1,173 patients participated in the study, with the majority being female (55%) and a median age of 45 years (IQR 33-58). Most patients had Crohn’s disease (64%). The CP was associated with a 14% increase in the probability of patient-reported disease control (p=0.54). Increases in probability were also observed for patient-reported (β=0.25, p=0.29) and biochemical remission (β=0.17, p=0.37), and the presence of active fistulas (β=0.28, p=0.44). Decreases in probability were found for biological (β=-0.04, p=0.84) and clinician-reported remission (β=-0.16, p=0.48). Emergency room visits (β=-0.32, p=0.18), hospital admissions (β=-0.28, p=0.28), and length of stay (β=-0.23, p=0.20) showed reduction, although these associations were also not significant. The CP had no effect on quality of life (β=0.01, p=0.35) or on anaemia probability (β=0.05, p=0.84). Conclusion A CP for the management of IBD with biologicals and small new molecule has clinically significant potential to reduce healthcare utilization, while improving patient-reported disease control, and biochemical remission. These results emphasize the potential of a CP to improve care for a complex disease as IBD. However, the adherence to the CP and whether these results lead to a reduction in healthcare costs, should be further investigated.

N36 Inflammatory bowel disease helpline use amongst individuals who are culturally and linguistically diverse, Crohn’s Colitis Cure Data Insight’s Programme

Abstract Background Effective management of inflammatory bowel disease (IBD) requires sustained patient engagement in healthcare, with nurse-led IBD helplines proven to improve access to care and reduce healthcare costs. However, individuals who are culturally and linguistically diverse (CALD) face challenges, including impaired access to health information, communication barriers, and interpreter shortages. This study examined how individuals from CALD backgrounds use IBD helplines compared to the English as a first language (EFL) population in Australia and New Zealand. Methods Crohn’s Colitis Care (CCCare) is a cloud-based IBD-specific electronic medical record (EMR) used in Australasia. Deidentified data prospectively entered by clinicians and consumers during routine clinical practice from September 2023 to September 2024 were retrospectively analysed. Individuals with IBD who had an assessment within the past 14 months with their language background documented were included. Results Of 7506 eligible people, only 892 (11.9%) had their language background documented, with 231 (25.9%) from a CALD background. When compared to the EFL cohort, a higher percentage of CALD individuals reside in metropolitan vs non-metro areas (92.2% vs 86.2%, p<0.05) with a lower proportion attaining tertiary or high school education (40.7% vs 45.4% and 44.3% vs 48.2%, respectively; both p=0.01). See table for details. The majority of helpline contacts from people of CALD backgrounds were via e-mail (n=379, 83.3%), a significantly higher proportion compared to the EFL cohort (n=987, 77.4%, p<0.001). The reasons for helpline contact were similar between CALD and EFL groups, mainly concerning medication or investigation queries (26.1% vs 24.3% and 24.3% vs 22.6%, respectively; both p>0.5). See table for patterns of helpline use. Multivariate analysis, considering age, gender, diagnosis, disease duration, education, language, and location, did not identify any factors that significantly influenced helpline use. Conclusion Individuals with a CALD background show preference for email over phone communication when using helplines. The current documentation of language preference is limited, and these findings highlight a need to enhance data collection practices. With more robust data, we can better understand and address the needs of these populations, ensuring equitable access to healthcare and improved outcomes.

P0569 Inflammatory Bowel Disease nursing helpline trends in a large real-world Australasian cohort: Crohn's Colitis Cure (CCC) data insights program

Abstract Background The chronic nature of Inflammatory Bowel Disease (IBD) necessitates ongoing engagement between the healthcare team and patients with IBD. Dedicated nurse led helplines have been demonstrated to improve access to care, reduce healthcare costs and utilisation, and improves satisfaction. IBD nurses and helplines may not be widely available subject to resourcing. We analysed real world IBD-helpline usage across 10 Australasian sites to determine current trends. Methods Crohn’s Colitis Care (CCCare) is a cloud-based IBD-specific electronic medical record used increasingly in Australasia. The inclusion of a helpline augments the service through enabling encounter related documentation. De-identified data is made available from an associated, clinical quality registry (CQR). Helpline-associated data prospectively entered from September 2023 to September 2024 were analysed. Results In our cohort (n=7,493), 55.8% (n=4,181) had Crohn’s Disease (CD), 41.4% (n=3,101) had Ulcerative colitis (UC) and 2.8% (n=211) had IBD-Unclassified (IBDU). The median age was 42 years (IQR 31–56) and the cohort was evenly distributed in gender (49.0%, n=3,670 male). All patients resided in either Australia (73.1%, n=5,478) or New Zealand (23.6%, n=1,477). Three-quarters (75.2%) lived in metropolitan regions compared to regional/rural areas (24.8%). A total of 10,673 helpline encounters were documented, 75.5% (n=8,078) by email and 24.5%, (n=2,622) by phone. Email remained the predominant modality of communication across all age groups except those under 16. Those receiving advanced therapy (biologic or novel small molecule) formed 60% (n=3876) of the cohort but comprised 81.9% of the helpline utilisation likely reflecting increased complexity associated with their care. The most common reasons for helpline encounters related to administrative tasks (33.3%), medication-related issues (24.0%), and investigations/results (14.3%). Clinical concern and care only formed 14.3% of helpline contact encounters. This was consistent across most age groups, however a greater proportion of encounters were related to clinical concern or care in those under 18 (>30%) and over 80 (>20%). Conclusion IBD helplines play an essential role in augmenting the routine care provided to people with IBD, however it is limited by resource allocation, along with the burden of non-clinical and administrative tasks. Digital delivery of the IBD nursing helpline is utilised preferentially across all demographics in our cohort and signals an opportunity for innovative digital solutions to streamline care, reduce administrative burden, and improve overall patient care and satisfaction. Figure 1. Helpline encounter reasons by age groups.

The Impact of Telemedicine on Patient Outcomes During the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

The ongoing global pandemic has precipitated the rapid adoption of telemedicine as an alternative means of delivering healthcare, particularly with a view to reducing direct contact between patients and medical personnel. The objective of this study is to examine the influence of telemedicine on patient health outcomes during the ongoing pandemic through a comprehensive review and meta-analysis of pertinent literature. A qualitative research methodology was employed to analyse 20 articles selected based on pre-established inclusion and exclusion criteria. The findings indicate that telemedicine has a favourable impact on enhancing healthcare accessibility, time efficiency and cost reduction, despite challenges pertaining to technological constraints and patient digital proficiency. This research offers valuable insights for policymakers in optimising the future implementation of telemedicine.

Understanding the growing burden of Malignant Pleural Effusion - epidemiology, health care utilization and cost, a Canadian perspective.

Malignant Pleural Effusion (MPE) is common in advanced malignancy. Data are needed on health care utilization and costs. This population-based retrospective cohort study included patients aged ≥18 years with an MPE diagnosed between January 1, 2004 and December 31, 2018. We described the incidence and prevalence of MPE from 2004 to 2018, and trends in hospital admissions, emergency department (ED) visits, and pleural-based procedures. In patients diagnosed with MPE from 2006 to 2016 we estimated 2-year health care costs (2018 US dollars) from the public payer perspective. The annual incidence and prevalence of MPE increased from 5,090 and 14,579 in 2004 to 6,977 and 23,204 in 2018, respectively. Annual mortality among prevalent patients decreased from 32% to 28%. In 2004, 57% of patients were hospitalized, decreasing to 50% in 2018. ED visits increased (59% to 61%). From 2004 to 2018, the number of patients who had insertions of thoracostomy tube (2,211 to 3,664) and tunnelled pleural catheter (383 to 1,164) increased. The number of patients receiving pleurodesis declined (565 to 284). No change occurred in the number of patients receiving video-assisted thoracoscopy (range 140 - 208/year). Between 2004 and 2016, 76,190 patients were diagnosed with MPE (mean age 71.2; 52% female). The median (interquartile range) health care cost during follow-up was $45,641 ($23,237-$86,700), with $19,753 ($9,590-$38,746) for inpatient hospitalization. Hospitalization and temporizing MPE procedures are associated with high costs. This population-based study may guide clinicians and policy makers to improve MPE management and reduce health care costs.

Evaluating the Cost-Effectiveness of Antenatal Screening for Major Structural Anomalies During the First Trimester of Pregnancy: A Decision Model.

To assess the cost-effectiveness of modifying current antenatal screening by adding first trimester structural anomaly screening to standard of care second trimester anomaly screening. Health economic decision model. National Health Service (NHS) in England and Wales. Pregnant women attending for first trimester antenatal screening. The decision model estimated pregnancy outcomes (maternal and foetal) and 20-year costs for current screening practice and for a policy adding a protocol screening for eight major structural anomalies to the current first trimester ultrasound scan. Event probabilities, costs, and outcomes for the model were informed by meta-analyses, published literature, and expert opinion. Expected numbers of pregnancy outcomes, healthcare costs, and maternal quality-adjusted life years (QALYs). Estimation of the incremental cost-effectiveness ratio (ICER), likelihood of cost-effectiveness, and a value of information (VoI) analysis assessing if further research is needed before making a decision about screening. First trimester anomaly screening increased mean per woman costs by £11 (95% CI £1-£29) and maternal QALYs by 0.002065 (95% CI 0.00056-0.00358). The ICER was £5270 per QALY and the probability of cost-effectiveness at a willingness to pay value for a QALY of £20 000, exceeded 95%. VoI analysis showed further research would be unlikely to represent value for money. The protocol would likely lead to a reduction in infant healthcare costs and QALYs. A protocol to screen for eight major structural anomalies during the first trimester appears to represent value for money for the NHS. The opposing implications for mothers and infants, however, raise complex, challenging, and sensitive issues.

Health Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.

Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantial health care costs related to this condition. This study aimed to explore the perspectives of health care professionals and data scientists regarding the relevance, challenges, and potential benefits of using machine learning (ML) models to predict decompensation from patients with HF. A total of 13 individual, semistructured, qualitative interviews were conducted in Portugal between October 31, 2022, and June 23, 2023. Participants represented different health care specialties and were selected from different contexts and regions of the country to ensure a comprehensive understanding of the topic. Data saturation was determined as the point at which no new themes emerged from participants' perspectives, ensuring a sufficient sample size for analysis. The interviews were audio recorded, transcribed, and analyzed using MAXQDA (VERBI Software GmbH) through a reflexive thematic analysis. Two researchers (JS and AH) coded the interviews to ensure the consistency of the codes. Ethical approval was granted by the NOVA National School of Public Health ethics committee (CEENSP 14/2022), and informed consent was obtained from all participants. The participants recognized the potential benefits of ML models for early detection, risk stratification, and personalized care of patients with HF. The importance of selecting appropriate variables for model development, such as rapid weight gain and symptoms, was emphasized. The use of wearables for recording vital signs was considered necessary, although challenges related to adoption among older patients were identified. Risk stratification emerged as a crucial aspect, with the model needing to identify patients at high-, medium-, and low-risk levels. Participants emphasized the need for a response model involving health care professionals to validate ML-generated alerts and determine appropriate interventions. The study's findings highlight ML models' potential benefits and challenges for predicting HF decompensation. The relevance of ML models for improving patient outcomes, reducing health care costs, and promoting patient engagement in disease management is highlighted. Adequate variable selection, risk stratification, and response models were identified as essential components for the effective implementation of ML models in health care. In addition, the study identified technical, regulatory and ethical, and adoption and acceptance challenges that need to be overcome for the successful integration of ML models into clinical workflows. Interpretation of the findings suggests that future research should focus on more extensive and diverse samples, incorporate the patient perspective, and explore the impact of ML models on patient outcomes and personalized care in HF management. Incorporation of this study's findings into practice is expected to contribute to developing and implementing ML-based predictive models that positively impact HF management.

Evaluation of the Cow's Milk and Hen's Egg Ladder in Daily Practice: A Parent Perspective.

Evaluation of the cow's milk (CM) and hen's egg (HE) ladder to improve medical care of children with CM and/or HE allergy. Through an anonymous retrospective online questionnaire, we investigated parent perspectives regarding the therapy option of a CM and HE ladder in children with CM and/or HE allergy. Of the 54 families contacted, 29 took part in the study. 19/29 children had already completed the ladders when the survey took place. 19/29 children showed an allergic reaction during the treatment of whom 17 presented skin rashes. 16/29 parents were anxious to rise to the next step in the protocol. 15/29 had difficulties with the implementation of the therapy due to the child refusing the offered food and organizational issues. Medical support as well as the ladder as a therapy option were scored satisfactory. The participating parents were satisfied with the therapy option and medical care. We identified two main areas for improvement: First, the suggested food for every step should be more diverse, according to the families' culture background and nutritional needs/demands. Second, to reduce anxiety regarding the therapy, parents must be informed that although allergic reactions are common, they remain mild. Furthermore, we will suggest step changes under medical supervision, especially in families with a slow progression of the food ladder. With these improvements, the duration of therapy could be shortened, thus reducing the risk of an allergic reaction, the need for medical care by an allergist and therefore reducing healthcare costs.

A Cutting-Edge Approach to Predictive Precision in Oncology Using a Geneto-Neuro-Fuzzy Hybrid Model

Purpose: This study introduces a pioneering hybrid model that combines genetic algorithms, neuro-fuzzy logic, and mobile agent technology to enhance predictive precision for early-stage prostate cancer diagnosis. Design/Methodology/Approach: One hundred and twenty records of prostate cancer patients were initially collected from the Delta State University Teaching Hospital, Oghara, Nigeria. Each patient’s record included relevant data on prostate disease, such as age, PSA levels, clinical history, symptom severity, biopsy results, and other demographic and clinical factors. This data was extracted and stored as rules in a MySQL database, with the MySQL Fuzzy Extension enabling fuzzy data storage and processing. Findings: Extensive simulations and clinical data analyses demonstrate the model’s superior sensitivity and specificity in detecting early-stage prostate cancer compared to traditional diagnostic methods. Medical expert evaluations validate the model’s effectiveness as a promising diagnostic alternative. Research Limitation: While results are promising, the study is limited to simulations and a controlled clinical dataset. Practical Implications: The system offers a practical, scalable early prostate cancer detection solution that could revolutionise current diagnostic practices. Social Implications: Potential social benefits include improved patient outcomes, reduced healthcare costs, and better quality of life. Originality/Value: This study presents an innovative integration of genetic algorithms, neuro-fuzzy systems, and mobile agent technology. This novel approach paves the way for advanced cancer diagnostics and precision medicine.

Impact of Dialysis Modality on Mortality and Complications in Cardiovascular Surgery

Background: Patients receiving maintenance dialysis face high mortality and complication rates following cardiovascular (CV) surgery. With the growing utilization of peritoneal dialysis (PD), it is important to understand the impact of modality (PD vs. center-based hemodialysis [HD]) on outcomes following CV surgery. Methods: This retrospective cohort study used data from the National Inpatient Sample (2016-2020) to compare outcomes of PD and HD patients undergoing coronary artery bypass grafting and surgical valve procedures. Multivariable logistic regression, negative binomial regression, and linear regression models were used, adjusting for demographic factors, comorbidities, and hospital characteristics. The primary outcome was in-hospital mortality, and secondary outcomes included prolonged ventilation, length of stay, and hospital charges. Results: A total of 30,155 patients were included in the study, with 28,015 (92.9%) receiving HD and 2,140 (7.1%) receiving PD. Compared to HD, PD was associated with lower in-hospital mortality (OR 0.61, 95% CI 0.38-0.97), reduced prolonged ventilation (OR 0.51, 95% CI 0.32-0.81), shorter length of stay (IRR 0.85, 95% CI 0.80-0.91), and decreased hospital charges (mean difference -$87,172 USD, 95% CI -$113,523 to -$60,820) compared to HD. Among PD patients, post-operative transition to HD was associated with worse outcomes. Conclusions: Maintaining PD during the perioperative period may confer benefits over HD, including lower hospital charges and improved patient outcomes. Careful consideration of dialysis modality in the management of CV surgery patients is needed to optimize clinical outcomes and reduce healthcare costs.

The case of Wellness Valley: promoting physical activity and exercise medicine for a sustainable health care system

ABSTRACT Today’s health care systems primarily focus on treating noncommunicable diseases (NCDs) rather than preventing them. Currently, this approach is not sustainable and requires innovative transformations to face the challenges posed by the aging population, the increasing NCD prevalence, widespread physical inactivity, and growing obesity rates. Regular physical activity and exercise improve quality of life and are effective for the prevention and treatment of numerous NCDs and to reduce health care costs. Physical activity promotion and exercise medicine thus represent cost-effective solutions for a sustainable model of health. The Wellness Valley initiative in Emilia-Romagna, Italy, exemplifies this model by fostering active, healthy lifestyles. In Wellness Valley, physical activity is promoted through multi-stakeholder initiatives of education and engagement, and exercise medicine is supported in the medical community through continuous education and dedicated infrastructure, such as certified health-promoting gyms. With these initiatives in place, the population of Wellness Valley is more physically active compared to the Italian national average. Overall, shifting health models toward preventative strategies centered on healthy active lifestyles and exercise can increase physical activity levels and contribute to alleviating the growing burden of NCDs on health care systems.

For Myself or for Others? The Influence of Family Communication Patterns on Family Health History Communication and Online Health Information Seeking

With innovations in health information technology, there are increasing opportunities to search for health information online, with the potential to reduce health care costs and improve health outcomes for the family. This study aims to investigate how family communication processes influence online health information seeking for oneself (self OHIS) and for another person (surrogate OHIS). An online survey was conducted among 325 adults in China. The results showed that family conversation orientation was positively related to family health history (FHH) communication intentions, whereas family conformity orientation was negatively related to FHH communication intentions. Family conversation orientation was positively related to self and surrogate OHIS through the partial and masking mediation effects of FHH communication intentions, respectively. Family conformity orientation was negatively related to self OHIS through the full mediating effect of FHH communication intentions, while FHH communication intentions played a masking mediating role between conformity orientation and surrogate OHIS. Implications for extending family communication patterns research to health communication and cultural forces on OHIS are discussed.

Mapping the landscape of Hospital at home (HaH) care: a validated taxonomy for HaH care model classification

BackgroundHospital at home (HaH) care models have gained significant attention due to their potential to reduce healthcare costs, improve patient satisfaction, and lower readmission rates. However, the lack of a standardized classification system has hindered systematic evaluation and comparison of these models. Taxonomies serve as classification systems that simplify complexity and enhance understanding within a specific domain.ObjectiveThis paper introduces a comprehensive taxonomy of HaH care models, aiming to categorize and compare the various ways HaH services are delivered as an alternative to traditional hospital care.MethodsWe developed a taxonomy of characteristics for HaH care models based on scientific literature and by applying a taxonomy development framework. To validate the taxonomy, and to analyze the current landscape of HaH models we matched the taxonomy to HaH care models described in literature. Finally, to identify types of HaH care implementations, we applied the k-means clustering method to care models represented using the taxonomy.ResultsOur taxonomy consists of 12 unique dimensions structured into 5 perspectives following the progression from triaging, through care delivery, operational processes, and metrics for success: Persons and roles (2 dimensions), Target population (1 dimension), Service delivery and care model (6 dimensions), outcomes and quality metrics (2 dimensions), and training and education (1 dimension). Cluster analysis of 34 HaH care models revealed three distinct types: One cluster (50%, 17/34) focuses on patient eligibility and home environment suitability, a care model to be chosen for clinically complex patients. A second cluster (29.4%, 10/34) aggregates technology-enabled models using telemedicine and remote monitoring that are adaptable across settings. This type could be chosen for generalizable care. The third cluster (20.6%, 7/34) includes complex interventions involving informal caregivers and advanced medical devices, requiring caregiver training, supportive policies, and user-friendly technology to reduce caregiver burden and improve safety.ConclusionsThe clusters identified highlight practical considerations for adapting HaH care approaches to patient and contextual needs. These findings can guide policymakers in developing guidelines and assist practitioners in tailoring HaH care models to specific patient populations. The challenges encountered in collecting information on different characteristics of the taxonomy underscore the urgent need for more comprehensive and standardized reporting in scientific papers on HaH interventions.

Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future.

Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI's applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. Results: A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. Conclusions: AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery.

<b>Machine Learning Enabled In-Home ECG: A Review</b>

Machine learning (ML)-based in-home electrocardiogram (ECG) systems have emerged as transformative tools, advancing beyond traditional cardiology methods by offering innovative techniques for cardiac care. These systems enable sustained data collection, real-time monitoring of cardiac status, and individualized treatment plans, all while minimizing the need for frequent clinic visits. By leveraging advanced analytics and ML algorithms, in-home ECG systems analyze large-scale datasets to detect patterns and anomalies that might otherwise go unnoticed, providing early alerts and improving patient outcomes. This review examines the latest trends in ML-enhanced in-home ECG technology, emphasizing its functionality in anomaly detection, continuous monitoring, and decision-making processes. The integration of ML not only enhances diagnostic precision but also opens avenues for scalable, personalized, and remote healthcare solutions. Despite these advancements, significant challenges remain, including issues related to data privacy, algorithmic biases, and the reliability of real-world implementations. Addressing these challenges is essential for optimizing the performance and ethical use of these systems. This review also explores opportunities for future research, particularly in improving algorithm robustness and addressing biases to ensure equitable and accurate cardiac care for diverse populations. By integrating state-of-the-art ML techniques, in-home ECG systems are poised to revolutionize contemporary cardiology, reducing healthcare costs and enabling a progressive shift toward accessible, patient-centered care. This comprehensive exploration highlights the potential of ML-based in-home ECG systems to redefine cardiac monitoring and treatment, contributing to the broader transformation of modern healthcare. Received: 13 September 2024 | Revised: 11 December 2024 | Accepted: 31 December 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Aqsa Bibi: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Project administration. Jawwad Sami Ur Rahman: Methodology, Validation, Investigation, Resources, Writing - review & editing, Supervision, Project administration.

Exploring the associative relationship between general practice engagement and hospitalisation in older carers to potentially reduce hospital burden.

Background Caregiving is an essential yet often overlooked component of health care. Although carers play a pivotal role in reducing healthcare costs and improving patient outcomes, they are also prone to psychological and physical burdens that can lead to their own hospitalisation. This study aimed to explore the relationship between the frequency of interactions with general practitioners and hospitalisation rates among caregivers aged ≥45years in New South Wales, Australia. Methods This cohort study retrospectively identified participants from the Sax Institute's 45 and Up Study in New South Wales, linked with national datasets. The cohort comprised 26,004 individuals aged ≥45years who were caregivers. The primary outcome was hospitalisation within a 7-year period, and the intervention was whether the patient was a high or low general practice (GP) user, ascertained by determining if the average number of annual GP visits was above or below 11, respectively. Data analysis included descriptive statistics and Poisson regression models. Results The study found a statistically significant association between high GP use and reduced rates of hospitalisation among caregivers. Caregivers with frequent GP interactions had a relative risk of hospitalisation of 0.514 (95% CI: 0.479-0.550) compared with their counterparts who infrequently used GP services. This association remained significant, even after adjusting for various demographic and health-related factors with an adjusted relative risk of 0.619 (95% CI: 0.554-0.690). Conclusions The findings underscore the potential of primary care interventions in reducing hospitalisations among caregivers, in turn providing economic and societal benefits. They also highlight the need for future research to understand the specific aspects of GP interactions that contribute to this protective effect.