Pub Date : 2025-07-25DOI: 10.1016/j.hlpt.2025.101078
Elena Bignami , Luigino Jalale Darhour , Wolfgang Buhre , Maurizio Cecconi , Valentina Bellini
The integration of Artificial Intelligence (AI) in Intensive Care Units (ICUs) has the potential to transform critical care by enhancing diagnosis, management, and clinical decision-making. Generative and Predictive AI technologies offer new opportunities for personalized care and risk stratification, but their implementation must prioritize ethical standards, patient safety, and the sustainability of care delivery. With the EU AI-Act entering into force in February 2025, a structured and responsible adoption of AI is now imperative. This article outlines a strategic framework for ICU AI integration, emphasizing the importance of a formal declaration of intent by each unit, detailing current AI-use, implementation plans, and governance strategies. Central to this approach is the development of tailored AI education programs adapted to four distinct professional profiles, ranging from experienced clinicians with limited AI knowledge to new intensivists with strong AI backgrounds but limited clinical experience. Training must foster critical thinking, contextual interpretation, and a balanced relationship between AI tools and human judgment. A multidisciplinary support team should oversee ethical AI-use and continuous performance monitoring. Ultimately, aligning regulatory compliance with targeted education and practical implementation could enable a safe, effective, and ethically grounded use of AI in intensive care. This balanced approach would support a culture of transparency and accountability, while preserving the central role of human clinical reasoning and improving the overall quality of ICU care.
{"title":"Artificial intelligence in healthcare: Tailoring education to meet EU AI-Act standards","authors":"Elena Bignami , Luigino Jalale Darhour , Wolfgang Buhre , Maurizio Cecconi , Valentina Bellini","doi":"10.1016/j.hlpt.2025.101078","DOIUrl":"10.1016/j.hlpt.2025.101078","url":null,"abstract":"<div><div>The integration of Artificial Intelligence (AI) in Intensive Care Units (ICUs) has the potential to transform critical care by enhancing diagnosis, management, and clinical decision-making. Generative and Predictive AI technologies offer new opportunities for personalized care and risk stratification, but their implementation must prioritize ethical standards, patient safety, and the sustainability of care delivery. With the EU AI-Act entering into force in February 2025, a structured and responsible adoption of AI is now imperative. This article outlines a strategic framework for ICU AI integration, emphasizing the importance of a formal declaration of intent by each unit, detailing current AI-use, implementation plans, and governance strategies. Central to this approach is the development of tailored AI education programs adapted to four distinct professional profiles, ranging from experienced clinicians with limited AI knowledge to new intensivists with strong AI backgrounds but limited clinical experience. Training must foster critical thinking, contextual interpretation, and a balanced relationship between AI tools and human judgment. A multidisciplinary support team should oversee ethical AI-use and continuous performance monitoring. Ultimately, aligning regulatory compliance with targeted education and practical implementation could enable a safe, effective, and ethically grounded use of AI in intensive care. This balanced approach would support a culture of transparency and accountability, while preserving the central role of human clinical reasoning and improving the overall quality of ICU care.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101078"},"PeriodicalIF":3.7,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-23DOI: 10.1016/j.hlpt.2025.101075
Liliana Freitas , Mónica D. Oliveira , Ana C.L. Vieira
Objectives
Stakeholder involvement is recognized as essential in Health Technology Assessment (HTA), yet engagement remains insufficient, particularly in medical device (MD) evaluations. Literature on how to systematically identify and integrate stakeholders remains scarce. This study proposes a reflective framework to support HTA practitioners think about stakeholder inclusion and applies it to explore perspectives within the medical device context in Portugal.
Methods
We adapted Ulrich’s Critical Systems Heuristics (CSH) as a conceptual lens to structure reflection on stakeholder roles and contributions in MD HTA. The framework is organized around four sources of influence (motivation, control, knowledge, and legitimacy) and was operationalized through 26 semi-structured interviews with experts from Portugal’s HTA agency, hospitals, patient associations, and industry. Interview data were analysed using directed content analysis and the Framework Method, allowing to contrast current ('is') and ideal ('ought') views within each source of influence. The common themes were then used to construct interpretative narratives that captured rationales for stakeholder inclusion.
Results
The application of the framework revealed context-specific insights into stakeholder engagement in MD evaluation. Findings show stakeholder roles in MD evaluations extend beyond traditional classifications. For each CSH source of influence, rationales and conditions for stakeholder engagement were identified. Under motivation, stakeholders identified diverse purposes and measures of success, ranging from improved patient access to innovation to system-wide resource optimization. Under control, providers, purchasers, and payers were seen as central decision-makers, yet ideal processes included multidisciplinary governance and clearer procedural support. Under knowledge, multiple actors (including patients) were valued as contributors of contextual expertise, but gaps were highlighted in methodological tools. Under legitimacy, patients and the public were underrepresented and called for stronger mechanisms for direct involvement and broader societal alignment. Across all sources of influence, significant gaps were found between current practices and stakeholder expectations to highlight areas for development.
Conclusions
Rather than prescribing fixed engagement procedures, the proposed reflective framework offers a structured lens to support HTA practitioners in reasoning through stakeholder roles, values, and contributions in MD evaluations. The framework is transferable to other decision-making contexts and fosters more transparent and inclusive deliberation.
{"title":"Guiding stakeholder involvement in health technology assessment for medical devices: A novel approach for clarifying stakeholders’ roles and contributions","authors":"Liliana Freitas , Mónica D. Oliveira , Ana C.L. Vieira","doi":"10.1016/j.hlpt.2025.101075","DOIUrl":"10.1016/j.hlpt.2025.101075","url":null,"abstract":"<div><h3>Objectives</h3><div>Stakeholder involvement is recognized as essential in Health Technology Assessment (HTA), yet engagement remains insufficient, particularly in medical device (MD) evaluations. Literature on how to systematically identify and integrate stakeholders remains scarce. This study proposes a reflective framework to support HTA practitioners think about stakeholder inclusion and applies it to explore perspectives within the medical device context in Portugal.</div></div><div><h3>Methods</h3><div>We adapted Ulrich’s Critical Systems Heuristics (CSH) as a conceptual lens to structure reflection on stakeholder roles and contributions in MD HTA. The framework is organized around four sources of influence (motivation, control, knowledge, and legitimacy) and was operationalized through 26 semi-structured interviews with experts from Portugal’s HTA agency, hospitals, patient associations, and industry. Interview data were analysed using directed content analysis and the Framework Method, allowing to contrast current ('is') and ideal ('ought') views within each source of influence. The common themes were then used to construct interpretative narratives that captured rationales for stakeholder inclusion.</div></div><div><h3>Results</h3><div>The application of the framework revealed context-specific insights into stakeholder engagement in MD evaluation. Findings show stakeholder roles in MD evaluations extend beyond traditional classifications. For each CSH source of influence, rationales and conditions for stakeholder engagement were identified. Under motivation, stakeholders identified diverse purposes and measures of success, ranging from improved patient access to innovation to system-wide resource optimization. Under control, providers, purchasers, and payers were seen as central decision-makers, yet ideal processes included multidisciplinary governance and clearer procedural support. Under knowledge, multiple actors (including patients) were valued as contributors of contextual expertise, but gaps were highlighted in methodological tools. Under legitimacy, patients and the public were underrepresented and called for stronger mechanisms for direct involvement and broader societal alignment. Across all sources of influence, significant gaps were found between current practices and stakeholder expectations to highlight areas for development.</div></div><div><h3>Conclusions</h3><div>Rather than prescribing fixed engagement procedures, the proposed reflective framework offers a structured lens to support HTA practitioners in reasoning through stakeholder roles, values, and contributions in MD evaluations. The framework is transferable to other decision-making contexts and fosters more transparent and inclusive deliberation.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101075"},"PeriodicalIF":3.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-18DOI: 10.1016/j.hlpt.2025.101072
Tobias Joseph Adams , Joseph Tay Wee Teck , Alexander Baldacchino , Patrice Forget
Objectives
To describe the change in opioid-related deaths (ORDs) recorded across Scotland since National ‘Take Home’ Naloxone Programme (NNP) implementation between baseline pre-implementation (2006 – 2010) and 10-year post implementation (2011 – 2020) periods. To describe and contextualise the change in ORDs within 4 weeks of prison release and hospital discharge across the same pre- and post-implementation periods and evaluate the reach of naloxone to people at risk of opioid overdose during this period.
Methods
Descriptive statistics as part of a pre-post secondary contribution analysis approach. The Better Evaluation Rainbow Framework for impact evaluation was utilised and data was obtained from official statistics and monitoring reports via Public Health Scotland.
Results
An increase in total ORDs nationwide was observed post-NNP implementation. In 2006–10, 9·8 % of ORDs (193 of 1970) were in people released from prison within 4 weeks of death, whereas only 4·4 % of ORDs (281 of 6439) in 2011–20 followed prison release, representing a 55 % reduction. A similar reduction in ORDs following hospital discharge was not observed. Cumulative reach of take-home naloxone to individuals at risk of opioid overdose across the post-implementation period was 58 %.
Conclusions
Implementation of the Scottish NNP has coincided with an increase in total ORDs nationwide, increased availability of take-home naloxone for management of opioid overdose and a reduction in the proportion of opioid-related fatalities among recently released prisoners. Unfortunately, the proportion ORDs after hospital discharge remain unchanged suggesting that this population may benefit from further research and additional distribution approaches.
{"title":"An impact evaluation of the Scottish take-home naloxone programme","authors":"Tobias Joseph Adams , Joseph Tay Wee Teck , Alexander Baldacchino , Patrice Forget","doi":"10.1016/j.hlpt.2025.101072","DOIUrl":"10.1016/j.hlpt.2025.101072","url":null,"abstract":"<div><h3>Objectives</h3><div>To describe the change in opioid-related deaths (ORDs) recorded across Scotland since National ‘Take Home’ Naloxone Programme (NNP) implementation between baseline pre-implementation (2006 – 2010) and 10-year post implementation (2011 – 2020) periods. To describe and contextualise the change in ORDs within 4 weeks of prison release and hospital discharge across the same pre- and post-implementation periods and evaluate the reach of naloxone to people at risk of opioid overdose during this period.</div></div><div><h3>Methods</h3><div>Descriptive statistics as part of a pre-post secondary contribution analysis approach. The Better Evaluation Rainbow Framework for impact evaluation was utilised and data was obtained from official statistics and monitoring reports via Public Health Scotland.</div></div><div><h3>Results</h3><div>An increase in total ORDs nationwide was observed post-NNP implementation. In 2006–10, 9·8 % of ORDs (193 of 1970) were in people released from prison within 4 weeks of death, whereas only 4·4 % of ORDs (281 of 6439) in 2011–20 followed prison release, representing a 55 % reduction. A similar reduction in ORDs following hospital discharge was not observed. Cumulative reach of take-home naloxone to individuals at risk of opioid overdose across the post-implementation period was 58 %.</div></div><div><h3>Conclusions</h3><div>Implementation of the Scottish NNP has coincided with an increase in total ORDs nationwide, increased availability of take-home naloxone for management of opioid overdose and a reduction in the proportion of opioid-related fatalities among recently released prisoners. Unfortunately, the proportion ORDs after hospital discharge remain unchanged suggesting that this population may benefit from further research and additional distribution approaches.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101072"},"PeriodicalIF":3.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-18DOI: 10.1016/j.hlpt.2025.101076
Augustino Mwogosi
Background
Tanzania has prioritized EHR systems adoption through systems like GoTHoMIS to enhance healthcare delivery and data management. However, the success of EHR implementation depends critically on system usability and healthcare providers’ satisfaction, which influence system acceptance and continued use.
Objectives
This study assessed the determinants of EHR system usability and satisfaction among healthcare providers in Tanzania’s public primary healthcare facilities. Specific objectives were to examine the influence of EHR system usability on provider satisfaction, the role of organizational factors, the contribution of usability to frequency of system use, and variations across demographic and professional groups.
Methods
A cross-sectional quantitative survey was conducted among 288 healthcare providers in Dodoma and Dar es Salaam regions. The regions were purposively selected to represent urban, peri‑urban and rural settings based on EHR system implementation maturity. Data were collected through a structured questionnaire administered via Google Forms. Google Forms data were encrypted and complied with Tanzania’s Data Protection Act 2022. Multiple linear regression and Structural Equation Modeling using SmartPLS were employed to analyze factors associated with EHR systems satisfaction and usage frequency.
Results
Improvement in work efficiency was the strongest predictor of provider satisfaction (β = 0.258, p < 0.001), followed by system reliability, adequate training, and organizational support. Factors such as ease of integration into clinical workflows and enhancement of collaboration significantly predicted the frequency of EHR system use. Demographic variables had limited moderating effects. Generally, system usability, organizational environment, and perceived efficiency gains were critical for successful EHR adoption.
Conclusion
Effective EHR systems implementation in primary healthcare settings in Tanzania requires a complex approach addressing not only technical usability but also organizational support, user training, and workflow integration. Policy interventions should prioritize these areas to enhance user satisfaction and system sustainability.
Public interest summary
This study looked at how healthcare providers in Tanzania use electronic health record systems, which are digital tools for storing patient information. The results showed that healthcare workers were more satisfied and used the systems more often when the records were reliable, easy to use, and supported by strong training and leadership. These insights could help healthcare organizations improve digital systems and make healthcare services better for patients
坦桑尼亚通过GoTHoMIS等系统优先采用电子病历系统，以加强医疗保健服务和数据管理。然而，EHR实施的成功主要取决于系统可用性和医疗保健提供者的满意度，这影响系统的接受度和持续使用。目的：本研究评估坦桑尼亚公共初级卫生保健机构医疗服务提供者的电子病历系统可用性和满意度的决定因素。具体目标是检查EHR系统可用性对提供者满意度的影响，组织因素的作用，可用性对系统使用频率的贡献，以及人口统计学和专业群体之间的差异。方法对多马和达累斯萨拉姆地区288名医疗服务提供者进行横断面定量调查。根据EHR系统实施成熟度，有目的地选择代表城市、城郊和农村的区域。数据通过谷歌表格进行结构化问卷调查收集。谷歌表单数据经过加密，并符合坦桑尼亚2022年数据保护法。采用多元线性回归和SmartPLS结构方程模型分析影响电子病历系统满意度和使用频率的因素。结果工作效率的提高是服务提供者满意度的最强预测因子(β = 0.258, p <；0.001)，其次是系统可靠性、充分的培训和组织支持。整合到临床工作流程的便利性和加强协作等因素显著预测了电子病历系统的使用频率。人口统计变量的调节作用有限。一般来说，系统可用性、组织环境和可感知的效率收益对于成功采用EHR至关重要。结论：在坦桑尼亚初级卫生保健机构实施有效的电子病历系统需要一个复杂的方法，不仅要解决技术可用性问题，还要解决组织支持、用户培训和工作流程集成问题。政策干预应优先考虑这些领域，以提高用户满意度和系统可持续性。本研究着眼于坦桑尼亚的医疗保健提供者如何使用电子健康记录系统，这是存储患者信息的数字工具。结果表明，当记录可靠、易于使用，并得到强有力的培训和领导支持时，卫生保健工作者更满意并更频繁地使用系统。这些见解可以帮助医疗机构改进数字系统，为患者提供更好的医疗服务
{"title":"Determinants of EHR systems’ usability and provider satisfaction in public primary healthcare facilities in Tanzania","authors":"Augustino Mwogosi","doi":"10.1016/j.hlpt.2025.101076","DOIUrl":"10.1016/j.hlpt.2025.101076","url":null,"abstract":"<div><h3>Background</h3><div>Tanzania has prioritized EHR systems adoption through systems like GoTHoMIS to enhance healthcare delivery and data management. However, the success of EHR implementation depends critically on system usability and healthcare providers’ satisfaction, which influence system acceptance and continued use.</div></div><div><h3>Objectives</h3><div>This study assessed the determinants of EHR system usability and satisfaction among healthcare providers in Tanzania’s public primary healthcare facilities. Specific objectives were to examine the influence of EHR system usability on provider satisfaction, the role of organizational factors, the contribution of usability to frequency of system use, and variations across demographic and professional groups.</div></div><div><h3>Methods</h3><div>A cross-sectional quantitative survey was conducted among 288 healthcare providers in Dodoma and Dar es Salaam regions. The regions were purposively selected to represent urban, peri‑urban and rural settings based on EHR system implementation maturity. Data were collected through a structured questionnaire administered via Google Forms. Google Forms data were encrypted and complied with Tanzania’s Data Protection Act 2022. Multiple linear regression and Structural Equation Modeling using SmartPLS were employed to analyze factors associated with EHR systems satisfaction and usage frequency.</div></div><div><h3>Results</h3><div>Improvement in work efficiency was the strongest predictor of provider satisfaction (β = 0.258, <em>p</em> < 0.001), followed by system reliability, adequate training, and organizational support. Factors such as ease of integration into clinical workflows and enhancement of collaboration significantly predicted the frequency of EHR system use. Demographic variables had limited moderating effects. Generally, system usability, organizational environment, and perceived efficiency gains were critical for successful EHR adoption.</div></div><div><h3>Conclusion</h3><div>Effective EHR systems implementation in primary healthcare settings in Tanzania requires a complex approach addressing not only technical usability but also organizational support, user training, and workflow integration. Policy interventions should prioritize these areas to enhance user satisfaction and system sustainability.</div></div><div><h3>Public interest summary</h3><div>This study looked at how healthcare providers in Tanzania use electronic health record systems, which are digital tools for storing patient information. The results showed that healthcare workers were more satisfied and used the systems more often when the records were reliable, easy to use, and supported by strong training and leadership. These insights could help healthcare organizations improve digital systems and make healthcare services better for patients</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101076"},"PeriodicalIF":3.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-18DOI: 10.1016/j.hlpt.2025.101074
Fatemeh Sadat Hosseini , Mohammadreza Mobinizadeh
{"title":"Towards equity-oriented topic selection in health technology assessment for orphan drugs in Iran: A commentary","authors":"Fatemeh Sadat Hosseini , Mohammadreza Mobinizadeh","doi":"10.1016/j.hlpt.2025.101074","DOIUrl":"10.1016/j.hlpt.2025.101074","url":null,"abstract":"","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101074"},"PeriodicalIF":3.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-16DOI: 10.1016/j.hlpt.2025.101069
Beatriz Araujo Oliveira , Erika Regina Manuli , Fábio Eudes Leal , Edgar Casado Barreta Souza , Ana Paula Illi , Ana Paula Barreto de Paiva , Camila da Silva Fachini , Beatriz Aparecida Munhoz Cano , Priscila de Lima Barros , Ligia Capuani , Helves Humberto Domingues , Maria Rita dos Santos e Passos-Bueno , Ester Cerdeira Sabino , Silvia Figueiredo Costa
Children were the last that were vaccinated during the COVID-19 pandemic. In this scenario, schools were the site of amplification and spread of COVID-19 and new variants during the pandemia.
Objective
To evaluate a respiratory symptoms screening system and test asymptomatic individuals (high school students and employees) at a public school in Brazil.
Methods
An online COVID-19 symptom surveillance platform was implemented for employees and students answered a questionnaire by mobile phone and/or website before going to school. Symptomatic individuals were referred to primary care unit. SARS-CoV-2 reverse transcription loop- mediated isothermal amplification (RT-LAMP) of saliva samples was performed weekly. The test cost was estimated.
Results
A total of 969 samples were tested (mean of 108 tests per week). A professor was symptomatic and tested positive during the study period. However, no asymptomatic participants tested positive for COVID-19, and no cases of SARS-CoV-2 transmission occurred at school despite the high transmissibility of the Delta variant, the local predominant variant at the time of the study and several outbreaks that occurred in public schools in Brazil. The average cost of our test was $13,6 per test.
Conclusion
Implementation of an online system of COVID-19 respiratory symptom screening and testing SARS-CoV-2 through saliva in asymptomatic individuals is a feasible, low-cost and practical option to be used, especially in low-income countries.
{"title":"Digital COVID-19 symptom screening and SARS-CoV-2 testing through RT-LAMP saliva of students and asymptomatic employees in a public school in Brazil","authors":"Beatriz Araujo Oliveira , Erika Regina Manuli , Fábio Eudes Leal , Edgar Casado Barreta Souza , Ana Paula Illi , Ana Paula Barreto de Paiva , Camila da Silva Fachini , Beatriz Aparecida Munhoz Cano , Priscila de Lima Barros , Ligia Capuani , Helves Humberto Domingues , Maria Rita dos Santos e Passos-Bueno , Ester Cerdeira Sabino , Silvia Figueiredo Costa","doi":"10.1016/j.hlpt.2025.101069","DOIUrl":"10.1016/j.hlpt.2025.101069","url":null,"abstract":"<div><div>Children were the last that were vaccinated during the COVID-19 pandemic. In this scenario, schools were the site of amplification and spread of COVID-19 and new variants during the pandemia.</div></div><div><h3>Objective</h3><div>To evaluate a respiratory symptoms screening system and test asymptomatic individuals (high school students and employees) at a public school in Brazil.</div></div><div><h3>Methods</h3><div>An online COVID-19 symptom surveillance platform was implemented for employees and students answered a questionnaire by mobile phone and/or website before going to school. Symptomatic individuals were referred to primary care unit. SARS-CoV-2 reverse transcription loop- mediated isothermal amplification (RT-LAMP) of saliva samples was performed weekly. The test cost was estimated.</div></div><div><h3>Results</h3><div>A total of 969 samples were tested (mean of 108 tests per week). A professor was symptomatic and tested positive during the study period. However, no asymptomatic participants tested positive for COVID-19, and no cases of SARS-CoV-2 transmission occurred at school despite the high transmissibility of the Delta variant, the local predominant variant at the time of the study and several outbreaks that occurred in public schools in Brazil. The average cost of our test was $13,6 per test.</div></div><div><h3>Conclusion</h3><div>Implementation of an online system of COVID-19 respiratory symptom screening and testing SARS-CoV-2 through saliva in asymptomatic individuals is a feasible, low-cost and practical option to be used, especially in low-income countries.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101069"},"PeriodicalIF":3.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-13DOI: 10.1016/j.hlpt.2025.101071
Marie-Lien Gerits, Samantha Bielen
Objectives
Contingent valuation (CV) is widely used in health economics, as it enables the quantification of diverse benefits within a single monetary measure. However, a key methodological debate that remains underexplored is whether patients or non-patients should complete the CV task and how this choice may influence willingness to pay (WTP) estimates. This study aimed to investigate that question in the context of two home blood pressure (BP) monitoring approaches for pregnant women at risk of gestational hypertensive disorders, remote monitoring (RM) and patient self-monitoring (PSM). We also examined the role of patient status and treatment experience in shaping WTP.
Methods
The WTP of 199 patients and 222 non-patients was examined using a CV survey, combining a payment card and open-ended question. Propensity score matching analysis with regression adjustment assessed WTP differences between patients and non-patients. Subgroup analyses explored whether these differences were driven solely by being a patient or also by home BP monitoring experience.
Results
The mean WTP was €130 for RM and €85 for PSM. Patients exhibited a €31 higher WTP for RM compared to non-patients, a difference that was marginally significant at the 10 % level. This effect was driven by treatment experience status. We found no significant difference in WTP PSM between patients and non-patients.
Conclusions
Simply being a patient does not affect WTP for home BP monitoring. When patients have treatment experience, this can increase WTP compared to non-patients, but not for approaches for which the potential benefits are apparent without experiencing them, like PSM.
{"title":"Willingness to pay for remote and self-monitoring: Comparing patients and non-patients in gestational hypertensive care","authors":"Marie-Lien Gerits, Samantha Bielen","doi":"10.1016/j.hlpt.2025.101071","DOIUrl":"10.1016/j.hlpt.2025.101071","url":null,"abstract":"<div><h3>Objectives</h3><div>Contingent valuation (CV) is widely used in health economics, as it enables the quantification of diverse benefits within a single monetary measure. However, a key methodological debate that remains underexplored is whether patients or non-patients should complete the CV task and how this choice may influence willingness to pay (WTP) estimates. This study aimed to investigate that question in the context of two home blood pressure (BP) monitoring approaches for pregnant women at risk of gestational hypertensive disorders, remote monitoring (RM) and patient self-monitoring (PSM). We also examined the role of patient status and treatment experience in shaping WTP.</div></div><div><h3>Methods</h3><div>The WTP of 199 patients and 222 non-patients was examined using a CV survey, combining a payment card and open-ended question. Propensity score matching analysis with regression adjustment assessed WTP differences between patients and non-patients. Subgroup analyses explored whether these differences were driven solely by being a patient or also by home BP monitoring experience.</div></div><div><h3>Results</h3><div>The mean WTP was €130 for RM and €85 for PSM. Patients exhibited a €31 higher WTP for RM compared to non-patients, a difference that was marginally significant at the 10 % level. This effect was driven by treatment experience status. We found no significant difference in WTP PSM between patients and non-patients.</div></div><div><h3>Conclusions</h3><div>Simply being a patient does not affect WTP for home BP monitoring. When patients have treatment experience, this can increase WTP compared to non-patients, but not for approaches for which the potential benefits are apparent without experiencing them, like PSM.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101071"},"PeriodicalIF":3.4,"publicationDate":"2025-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144665891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-12DOI: 10.1016/j.hlpt.2025.101073
Ezgi Karataş , Ceren Durmaz Engin
Objectives
This study evaluated the accuracy and comprehensibility of responses from three large language models (LLMs)—ChatGPT-4, Gemini, and Copilot—when addressing patient queries about myopia. Accurate, understandable information is crucial for effective patient education and management of this common refractive error.
Methods
Sixty questions across six categories (definition, etiology, symptoms and diagnosis, myopia control, correction, and new treatments) were presented to ChatGPT-4, Gemini, and Copilot. Responses were assessed for accuracy by two experienced ophthalmologists using a 3-point Likert scale. Quality and reliability were evaluated using the DISCERN and EQIP scales, while readability was measured with the Flesch Reading Ease Score, Flesch-Kincaid Grade Level, and Coleman-Liau Index. Statistical analyses were conducted using SPSS version 25.
Results
ChatGPT-4 provided the most accurate responses in the defsinition, symptoms, and diagnosis categories, with a 75 % overall success rate. Copilot had a similar success rate of 73.3 % but the highest inaccuracy rate (6.7 %). Gemini had a 71.7 % success rate. Copilot scored highest in reliability (DISCERN 76) and readability (Flesch Reading Ease 46.74), followed by ChatGPT-4 and Gemini. No significant differences in accuracy were found among the LLMs across categories.
Conclusions
All three LLMs performed well in providing myopia-related information. Copilot excelled in readability and reliability despite a higher inaccuracy rate. ChatGPT-4 and Copilot outperformed Gemini, likely due to their advanced architectures and training methodologies. These findings highlight the potential of LLMs in patient education and the need for ongoing improvements to ensure accurate, comprehensible AI-generated health information.
{"title":"From accuracy to comprehensibility: Evaluating large language models for myopia patient queries","authors":"Ezgi Karataş , Ceren Durmaz Engin","doi":"10.1016/j.hlpt.2025.101073","DOIUrl":"10.1016/j.hlpt.2025.101073","url":null,"abstract":"<div><h3>Objectives</h3><div>This study evaluated the accuracy and comprehensibility of responses from three large language models (LLMs)—ChatGPT-4, Gemini, and Copilot—when addressing patient queries about myopia. Accurate, understandable information is crucial for effective patient education and management of this common refractive error.</div></div><div><h3>Methods</h3><div>Sixty questions across six categories (definition, etiology, symptoms and diagnosis, myopia control, correction, and new treatments) were presented to ChatGPT-4, Gemini, and Copilot. Responses were assessed for accuracy by two experienced ophthalmologists using a 3-point Likert scale. Quality and reliability were evaluated using the DISCERN and EQIP scales, while readability was measured with the Flesch Reading Ease Score, Flesch-Kincaid Grade Level, and Coleman-Liau Index. Statistical analyses were conducted using SPSS version 25.</div></div><div><h3>Results</h3><div>ChatGPT-4 provided the most accurate responses in the defsinition, symptoms, and diagnosis categories, with a 75 % overall success rate. Copilot had a similar success rate of 73.3 % but the highest inaccuracy rate (6.7 %). Gemini had a 71.7 % success rate. Copilot scored highest in reliability (DISCERN 76) and readability (Flesch Reading Ease 46.74), followed by ChatGPT-4 and Gemini. No significant differences in accuracy were found among the LLMs across categories.</div></div><div><h3>Conclusions</h3><div>All three LLMs performed well in providing myopia-related information. Copilot excelled in readability and reliability despite a higher inaccuracy rate. ChatGPT-4 and Copilot outperformed Gemini, likely due to their advanced architectures and training methodologies. These findings highlight the potential of LLMs in patient education and the need for ongoing improvements to ensure accurate, comprehensible AI-generated health information.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101073"},"PeriodicalIF":3.4,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-12DOI: 10.1016/j.hlpt.2025.101070
Ying Jie Chong , Nitirot Phasitthanaphak , Teerawat Wiwatpanit , Yot Teerawattananon , Yi Wang
<div><h3>Background</h3><div>Target Product Profiles (TPPs) serve as strategic tools for planning medical innovation development, facilitating communication with regulators, and developing market access strategies. Modelling can assist TPPs development and provide guidance on defining attributes. This scoping review aims to outline the general steps in employing models in developing or refining TPPs and to identify the common themes of the attributes informed by modelling.</div></div><div><h3>Methods</h3><div>PRISMA-ScR checklist was used to guide this review. Literature search in PubMed, Scopus, Web of Science, Embase, and the World Health Organization Institutional Repository for Information Sharing (WHO IRIS) was conducted between August and September 2023. Subsequently, two researchers reviewed abstracts independently. Only full text articles used modelling to inform TPPs of health technologies with detailed modelling and methodology reported were included in this review. General information, technology-related information, TPP-related information, and model-related information were extracted from the articles and analysed thematically. EPIFORGE 2020 checklist was used to assess the reporting quality of modelling approach of the included articles.</div></div><div><h3>Results</h3><div>This review included 23 articles published from 2010 onward, reflecting a growing interest in using modelling to inform TPPs development. The studies covered diverse medical innovations, including drugs, vaccines, devices, procedures, and vector control tools. Commonly modelled attributes for devices included health impact, economic value, and efficacy. For non-device innovations, clinical efficacy, economic value, and dosage were the most frequently modelled attributes. The modelling process typically involved three steps: scoping, model development and validation, and analysis with recommendations. Limitations from the modelling process discussed across studies fell into three categories: evidence quality, modelling assumptions and structure, and the generalisability of findings. While some attributes, like clinical efficacy, are straightforward to model, certain attributes such as human factors require considering proxies such as compliance rates or capacity constraints.</div></div><div><h3>Conclusions</h3><div>This review identified common product attributes in TPPs that were informed by modelling, outlined the modelling process, and highlighted key limitations. It provided recommendations to improve the modelling approach in TPPs development and highlighted the need for further research to standardise the modelling process.</div></div><div><h3>Public Interest Summary</h3><div>Target Product Profiles (TPPs) are documents that outline targets for new medical innovations to effectively address specific public health needs. These documents are developed through multiple rounds of consultations with domain experts and stakeholders. We aimed to study how mathemati
目标产品简介（TPPs）是规划医疗创新发展、促进与监管机构沟通和制定市场准入战略的战略工具。建模可以帮助ppp开发，并为定义属性提供指导。这一范围审查的目的是概述在开发或改进TPPs中使用模型的一般步骤，并确定建模所告知的属性的共同主题。方法采用sprima - scr检查表进行评价。2023年8月至9月在PubMed、Scopus、Web of Science、Embase和世界卫生组织信息共享机构知识库（WHO IRIS）中进行文献检索。随后，两位研究人员独立审查了摘要。只有全文文章使用模型向TPPs介绍卫生技术，并报告了详细的模型和方法，才被纳入本综述。从文章中提取一般信息、技术相关信息、tpp相关信息和模型相关信息，并进行主题分析。使用EPIFORGE 2020检查表评估纳入文章的建模方法的报告质量。本综述纳入了2010年以来发表的23篇文章，反映了人们对使用模型为TPPs开发提供信息的兴趣日益浓厚。这些研究涵盖了各种医疗创新，包括药物、疫苗、设备、程序和病媒控制工具。设备的常用建模属性包括健康影响、经济价值和功效。对于非器械创新，临床疗效、经济价值和剂量是最常见的建模属性。建模过程通常包括三个步骤：确定范围、模型开发和验证，以及带建议的分析。研究中讨论的建模过程的局限性分为三类：证据质量、建模假设和结构以及研究结果的普遍性。虽然有些属性（如临床疗效）可以直接建模，但某些属性（如人为因素）需要考虑诸如依从率或容量限制等代理。本综述通过建模确定了tpp中常见的产品属性，概述了建模过程，并强调了关键的局限性。它提出了建议，以改进发展合作伙伴计划的建模方法，并强调需要进一步研究以使建模过程标准化。公共利益摘要目标产品概况（TPPs）是概述新的医疗创新目标的文件，以有效地满足特定的公共卫生需求。这些文件是通过与领域专家和利益相关者的多轮磋商制定的。我们的目标是研究如何使用数学建模来支持ppp的发展。通过系统搜索，我们确定并研究了23篇使用建模的论文。我们观察到一个结构化的三步过程：确定合适的模型，测试和调整模型，并使用模型输出来设置目标。建模主要用于建立与医疗创新的功效和经济价值有关的目标。我们的研究结果为建模在TPPs发展中的作用提供了见解，并为潜在的未来方法指导提供了信息。
{"title":"A scoping review of modelling in target product profile development for medical innovation","authors":"Ying Jie Chong , Nitirot Phasitthanaphak , Teerawat Wiwatpanit , Yot Teerawattananon , Yi Wang","doi":"10.1016/j.hlpt.2025.101070","DOIUrl":"10.1016/j.hlpt.2025.101070","url":null,"abstract":"<div><h3>Background</h3><div>Target Product Profiles (TPPs) serve as strategic tools for planning medical innovation development, facilitating communication with regulators, and developing market access strategies. Modelling can assist TPPs development and provide guidance on defining attributes. This scoping review aims to outline the general steps in employing models in developing or refining TPPs and to identify the common themes of the attributes informed by modelling.</div></div><div><h3>Methods</h3><div>PRISMA-ScR checklist was used to guide this review. Literature search in PubMed, Scopus, Web of Science, Embase, and the World Health Organization Institutional Repository for Information Sharing (WHO IRIS) was conducted between August and September 2023. Subsequently, two researchers reviewed abstracts independently. Only full text articles used modelling to inform TPPs of health technologies with detailed modelling and methodology reported were included in this review. General information, technology-related information, TPP-related information, and model-related information were extracted from the articles and analysed thematically. EPIFORGE 2020 checklist was used to assess the reporting quality of modelling approach of the included articles.</div></div><div><h3>Results</h3><div>This review included 23 articles published from 2010 onward, reflecting a growing interest in using modelling to inform TPPs development. The studies covered diverse medical innovations, including drugs, vaccines, devices, procedures, and vector control tools. Commonly modelled attributes for devices included health impact, economic value, and efficacy. For non-device innovations, clinical efficacy, economic value, and dosage were the most frequently modelled attributes. The modelling process typically involved three steps: scoping, model development and validation, and analysis with recommendations. Limitations from the modelling process discussed across studies fell into three categories: evidence quality, modelling assumptions and structure, and the generalisability of findings. While some attributes, like clinical efficacy, are straightforward to model, certain attributes such as human factors require considering proxies such as compliance rates or capacity constraints.</div></div><div><h3>Conclusions</h3><div>This review identified common product attributes in TPPs that were informed by modelling, outlined the modelling process, and highlighted key limitations. It provided recommendations to improve the modelling approach in TPPs development and highlighted the need for further research to standardise the modelling process.</div></div><div><h3>Public Interest Summary</h3><div>Target Product Profiles (TPPs) are documents that outline targets for new medical innovations to effectively address specific public health needs. These documents are developed through multiple rounds of consultations with domain experts and stakeholders. We aimed to study how mathemati","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101070"},"PeriodicalIF":3.7,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-12DOI: 10.1016/j.hlpt.2025.101068
Mees Casper Baartmans , Steffie Marijke Van Schoten , Cordula Wagner
Background and objective
Although most medical device applications in hospitals are safe and effective, in a small number of cases devices are involved in patient safety events causing serious unintended patient harm. These so-called sentinel events are thoroughly investigated by hospitals, with detailed event descriptions filed in reports. Studying these reports may help fill the knowledge gap on the latent contributing factors of sentinel events involving medical devices. This study aims to identify the contributing factors of sentinel events involving medical devices and how these factors lead to unintended patient harm.
Design
A cross-sectional retrospective analysis of 20 sentinel event reports involving medical devices from Dutch general hospitals, using a human factors approach and specific classification system for medical device related events.
Results
A total of 105 contributing factors were identified. For most events, factors relating to the operator (e.g., flaws in setting up and checking devices before use), device (e.g., design issues), infrastructure (e.g., poor environmental ergonomics) and patient (e.g., complicating anatomy) mutually contributed and interacted. Jointly these factors triggered events causing unintended patient harm.
Conclusions
In-depth analysis of reports of sentinel events using a human factors approach, showed the underlying patterns of interacting contributing factors leading to unintended patient harm. Sentinel events involving medical devices are triggered by an interplay of factors related to the operator, device, infrastructure, and patient. To prevent future patient harm, an integral approach addressing all these elements is needed.
Public Interest Summary
Medical devices can be involved in events leading to unintended patient harm in hospitals. We know little about the underlying factors contributing to such events. Therefore, 20 reports of events involving a medical device that led to serious patient harm were analysed in depth. In most events, the patient harm was triggered by factors relating to the operator of the device, the device itself, the organisation and environment in which the device was applied, and the patient to whom the device was applied. Jointly, these factors prompted the events and led to patient harm. The insights from this study can be used to further improve the safe application of medical devices in hospitals.
{"title":"Contributing factors of sentinel events involving medical devices: A cross-sectional retrospective human factors analysis","authors":"Mees Casper Baartmans , Steffie Marijke Van Schoten , Cordula Wagner","doi":"10.1016/j.hlpt.2025.101068","DOIUrl":"10.1016/j.hlpt.2025.101068","url":null,"abstract":"<div><h3>Background and objective</h3><div>Although most medical device applications in hospitals are safe and effective, in a small number of cases devices are involved in patient safety events causing serious unintended patient harm. These so-called sentinel events are thoroughly investigated by hospitals, with detailed event descriptions filed in reports. Studying these reports may help fill the knowledge gap on the latent contributing factors of sentinel events involving medical devices. This study aims to identify the contributing factors of sentinel events involving medical devices and how these factors lead to unintended patient harm.</div></div><div><h3>Design</h3><div>A cross-sectional retrospective analysis of 20 sentinel event reports involving medical devices from Dutch general hospitals, using a human factors approach and specific classification system for medical device related events.</div></div><div><h3>Results</h3><div>A total of 105 contributing factors were identified. For most events, factors relating to the operator (e.g., flaws in setting up and checking devices before use), device (e.g., design issues), infrastructure (e.g., poor environmental ergonomics) and patient (e.g., complicating anatomy) mutually contributed and interacted. Jointly these factors triggered events causing unintended patient harm.</div></div><div><h3>Conclusions</h3><div>In-depth analysis of reports of sentinel events using a human factors approach, showed the underlying patterns of interacting contributing factors leading to unintended patient harm. Sentinel events involving medical devices are triggered by an interplay of factors related to the operator, device, infrastructure, and patient. To prevent future patient harm, an integral approach addressing all these elements is needed.</div></div><div><h3>Public Interest Summary</h3><div>Medical devices can be involved in events leading to unintended patient harm in hospitals. We know little about the underlying factors contributing to such events. Therefore, 20 reports of events involving a medical device that led to serious patient harm were analysed in depth. In most events, the patient harm was triggered by factors relating to the operator of the device, the device itself, the organisation and environment in which the device was applied, and the patient to whom the device was applied. Jointly, these factors prompted the events and led to patient harm. The insights from this study can be used to further improve the safe application of medical devices in hospitals.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 6","pages":"Article 101068"},"PeriodicalIF":3.4,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号