Health Policy and Technology最新文献

{"title":"The impact and challenges of diagnosis-related groups (DRGs) payment reform on china's healthcare system: A critical analysis","authors":"Fumu Wang , Jianjian Ding , Rongfa Li , Xiaochong Shen , Haiming Wang , Yuhui Wang","doi":"10.1016/j.hlpt.2025.101150","DOIUrl":"10.1016/j.hlpt.2025.101150","url":null,"abstract":"","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101150"},"PeriodicalIF":3.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791698","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}

{"title":"Understanding vaccine acceptance in Australia: Evidence from the VaxPref discrete choice experiment","authors":"Stefano Bruzzo-Gallardo ,&nbsp;James A. Gillespie ,&nbsp;Brian Kelly ,&nbsp;Francesco Paolucci","doi":"10.1016/j.hlpt.2025.101151","DOIUrl":"10.1016/j.hlpt.2025.101151","url":null,"abstract":"<div><h3>Objectives</h3><div>This study investigates how Australians make trade-offs between vaccine characteristics and social-restriction mandates to inform future pandemic preparedness policy. We identify attributes influencing vaccine uptake and assess how demographic and behavioural factors shape attitudes to vaccination in Australia's post-COVID-19 context.</div></div><div><h3>Methods</h3><div>We analysed 3004 Australian responses from the VaxPref international survey and discrete choice experiment (DCE). Participants completed 12 choice scenarios comparing hypothetical vaccines varying across seven attributes: five vaccine characteristics and two social-restriction mandates. Multinomial logit (MNL) and latent class (LC) models estimated preference parameters and identified population subgroups.</div></div><div><h3>Results</h3><div>Vaccine effectiveness was the strongest uptake driver, with preferences increasing progressively from 40 % to 90 % effectiveness. Safety concerns significantly reduced acceptance, and Western-manufactured vaccines (EU, UK, USA) were preferred over Chinese alternatives. Latent class analysis revealed two distinct groups: a pro-vaccine majority (Class 1) (81.6 %) and a minority (Class 2) (19.4 %) with a strong preference for the opt-out alternative across choice tasks. The latter demonstrated higher sensitivity to both positive and negative attributes, suggesting more analytical decision-making. Pro-vaccine class membership was associated with trust towards public health bodies, newspapers and social media, COVID-19 exposure, and right-leaning political self-placement, while risk aversion and cognitive skills were negatively associated.</div></div><div><h3>Conclusions</h3><div>Effective pandemic preparedness requires recognising heterogeneous decision-making approaches. While the pro-vaccine majority responds to institutional trust and simplified messaging, a minority requires detailed, transparent communication addressing specific concerns. Investment in vaccine effectiveness, safety monitoring, and differentiated communication strategies may be efficient policy approaches for increasing uptake.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101151"},"PeriodicalIF":3.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791695","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}

{"title":"Digital health and artificial intelligence: a research approach to enable sustainable and personalised local healthcare","authors":"Monica Moroni ,&nbsp;Lisa Novello ,&nbsp;Giulia Malfatti ,&nbsp;Lorenzo Gios ,&nbsp;Roberto Bonmassari ,&nbsp;Maurizio Del Greco ,&nbsp;Massimiliano Maines ,&nbsp;Michele Moretti ,&nbsp;Sandro Inchiostro ,&nbsp;Federica Romanelli ,&nbsp;Elisabetta Racano ,&nbsp;Tania Elena Maggi ,&nbsp;Valentina Fiabane ,&nbsp;Adele Compagnone ,&nbsp;Lorena Filippi ,&nbsp;Roberta Pasquini ,&nbsp;Marta Betta ,&nbsp;Lucia Pavanello ,&nbsp;Andrea Manica ,&nbsp;Diego Cagol ,&nbsp;Giuseppe Jurman","doi":"10.1016/j.hlpt.2025.101149","DOIUrl":"10.1016/j.hlpt.2025.101149","url":null,"abstract":"<div><h3>Background</h3><div>The integration of Artificial Intelligence (AI) into healthcare services and technologies offers substantial potential for personalised medicine. The Autonomous Province of Trento (Italy) provides a unique setting for AI-driven healthcare research, due to its unified healthcare system, advanced IT infrastructure, and strong public-private collaborations. This paper explores an initiative aimed at improving healthcare accessibility and promoting innovation through AI in three clinical domains: Cardiology, Diabetic Retinopathy, and Paediatric Ophthalmology.</div></div><div><h3>Methods</h3><div>The project employs a structured approach, involving specialised working groups addressing clinical needs, AI techniques, legal and ethical compliance and data management. The initiative aims to develop predictive models aligned with European and national data protection regulations.</div></div><div><h3>Results</h3><div>Three primary clinical objectives were defined: estimating individual risk profiles in heart failure patients, personalising screening intervals for diabetic retinopathy, and supporting early diagnosis of anterior segment opacities in infants. Data relevant for the selected outcomes were identified. A dedicated platform for compliant, secure and structured access to data was developed. A data analysis plan was designed, including data processing, models selection, optimization and evaluation. All research protocols were approved by the local Ethics Committee.</div></div><div><h3>Discussion</h3><div>The initiative investigates the AI potential to improve clinical outcomes and establish a sustainable, personalised healthcare system. Key challenges include data accessibility, regulatory compliance, and adherence to ethical standards. The project's comprehensive framework offers a model for broader applications. Future research will focus on model validation and expanding the initiative to other clinical domains.</div></div><div><h3>Public Interest Summary</h3><div>This article presents the \"Digital Health and Artificial Intelligence\" project, an initiative funded by The Autonomous Province of Trento (Italy) to enhance healthcare accessibility and foster innovative healthcare models using technology and Artificial Intelligence (AI). The current work presents the design and preparatory work for the implementation of three AI-based solutions for research purposes, encompassing three areas: i) Cardiology, ii) Diabetic Retinopathy, and iii) Paediatric Ophthalmology. The paper outlines the legal and organizational frameworks, mathematical modelling and data management emphasising the necessity of cross-disciplinary endeavour and collaboration. Overall, this project represents a forward-looking initiative promoting research conducted on citizen data to address healthcare needs through innovative AI-driven approaches in line with legal and ethical standards.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101149"},"PeriodicalIF":3.7,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791699","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}

{"title":"Understanding vaccine acceptance through construal-level theory of psychological distance: Evidence from Singapore and South Korea","authors":"Yevgen Bogodistov ,&nbsp;Mesfin Genie ,&nbsp;Ayman Fouda","doi":"10.1016/j.hlpt.2025.101148","DOIUrl":"10.1016/j.hlpt.2025.101148","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;Vaccine acceptance is often studied in relation to clinical characteristics such as efficacy, safety, and side effects. In this study, we argue that acceptance is also influenced by the psychological distance (PD) at which vaccine information is communicated. Specifically, we investigate and compare how temporal, social, spatial, and hypothetical dimensions of PD shape individuals’ willingness to accept a vaccine in Singapore and South Korea.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We conducted a Discrete Choice Experiment (DCE) in Singapore and South Korea to assess how variations in PD framing influence vaccination decisions. The design allowed us to test both direct effects and interactions across the four PD dimensions, capturing linear and non-linear influences on decision-making.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Our findings provide substantive but not uniform support for the proposed role of psychological distance in shaping vaccine preferences. While several effects are consistent with rational evaluation of vaccine attributes (e.g., higher effectiveness, longer protection, and fewer societal restrictions), we also identify interaction and non-linear patterns that suggest more complex perceptual processes beyond immediate utility. Most theorised PD effects were supported; however, the expected spatial-distance relationship was not observed, likely because respondents’ perceptions of vaccine quality and geopolitical trustworthiness outweighed simple geographical proximity.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;The way vaccine information is communicated, particularly in terms of psychological distance, can significantly influence the public’s response. We recommend that policymakers not only consider each PD dimension in their messaging but also strive for consistency across them. Communicating vaccine-related information at an appropriate and congruent psychological distance may enhance public trust and increase vaccine uptake.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Public interest summary&lt;/h3&gt;&lt;div&gt;Why people accept or reject vaccines is not just about how effective or safe the vaccine is; it also depends on how the information is communicated. We explored how psychological distance (how close or far something feels in terms of time, social connection, location, or likelihood) affects vaccine decisions in Singapore and South Korea. Using a Discrete Choice Experiment, we found that people’s willingness to be vaccinated was influenced by practical factors (such as how long a vaccine had been tested) and by how near or far the message made the vaccine seem. Interestingly, geographical distance did not matter as much, possibly because political impressions of vaccine-producing countries were more important. The study shows that clear, consistent, and relatable communication can make a real difference. Policymakers who present vaccine information in ways that feel close and relevant to people’s everyday lives may boost public tru","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101148"},"PeriodicalIF":3.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791694","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}

{"title":"Prefrailty and health knowledge in the Oldest-Old: A mixed-methods analysis using IoT-based health quizzes","authors":"Yukari Yamada ,&nbsp;Tadahisa Okuda ,&nbsp;Tomoe Uchida ,&nbsp;Tatsuyoshi Ikenoue ,&nbsp;Jun Otsuka ,&nbsp;Takeo Nakayama ,&nbsp;Shingo Fukuma","doi":"10.1016/j.hlpt.2025.101147","DOIUrl":"10.1016/j.hlpt.2025.101147","url":null,"abstract":"<div><h3>Scientific abstract Background</h3><div>Health knowledge is crucial for preventing or delaying frailty, yet the interplay between knowledge and frailty remains unclear in the oldest-old population, where frailty may influence what and how individuals learn about health.</div></div><div><h3>Objective</h3><div>To investigate the relationship between health knowledge and prefrailty among individuals aged 85 and older, using real-world data from IoT-based health quizzes.</div></div><div><h3>Methods</h3><div>Eighty-three community-dwelling adults aged ≥85 participated in tablet-based quizzes on 180 health topics, generating over 24,000 responses between November 2020 and December 2022. Missing data were addressed through multiple imputation. A convergent mixed-methods approach combined ridge regression to identify knowledge areas associated with frailty and topic modeling to extract latent health themes.</div></div><div><h3>Results</h3><div>Prefrail individuals exhibited greater knowledge of acute and condition-specific topics (e.g., heat stroke, blood pressure), while broader health themes (e.g., disease prevention, long-term nutrition) were similarly distributed across frailty groups. No topics were identified where non-frail individuals consistently outperformed pre-frail counterparts.</div></div><div><h3>Conclusions</h3><div>Frailty may shape health knowledge by prompting a goal-driven, selective retention of immediately relevant information, rather than indicating a general knowledge decline. IoT-generated, ecologically valid data, analyzed through a mixed methods lens, offers promising insights to inform needs-based health education strategies for both frail and non-frail oldest-old individuals.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101147"},"PeriodicalIF":3.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841018","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}

{"title":"\"Vaccine hesitancy and acceptance in Latvia and Lithuania after the COVID-19 pandemic \"","authors":"Liubove Murauskiene ,&nbsp;Daiga Behmane ,&nbsp;Ausra Berzanskyte","doi":"10.1016/j.hlpt.2025.101146","DOIUrl":"10.1016/j.hlpt.2025.101146","url":null,"abstract":"<div><h3>Objectives</h3><div>This study investigates vaccine hesitancy and acceptance in Latvia and Lithuania following the COVID-19 pandemic, contextualising current attitudes within historical and institutional frameworks, quantifying public preferences for vaccine features and policy measures, and identifying predictors of vaccine acceptance to inform future public health strategies.</div></div><div><h3>Methods</h3><div>A cross-sectional survey using the VaxPref database was conducted with demographically balanced samples from Latvia (<em>n</em> = 1109) and Lithuania (<em>n</em> = 1010). A discrete choice experiment elicited preferences for vaccine characteristics and public health policies. Latent class analysis explored heterogeneity in vaccine acceptance, incorporating sociodemographic and attitudinal predictors such as trust in public health authorities and prior vaccination behaviour.</div></div><div><h3>Results</h3><div>Three classes emerged: Provaxers, Refusers, and Hesitants. Nearly half of respondents in both countries were Refusers, a marked increase from earlier surveys.Refusers were indifferent to vaccine attributes and strongly averse to vaccination, while Provaxers and Hesitants preferred higher vaccine effectiveness and Westernmanufactured vaccines. Trust public health authorities and prior COVID-19 vaccination were the strongest predictors of acceptance. Policy-related variables, such as social restrictions and mandates, had statistically significant but minor associations, with both countries preferring the absence of constraints. Gender and religious affiliation influenced hesitancy in a country-specific manner.</div></div><div><h3>Conclusions</h3><div>Vaccine attitudes in Latvia and Lithuania are shaped more by trust public health authorities and prior behaviours than by traditional sociodemographic factors. The high proportion of systematic Refusers poses a significant challenge for pandemic preparedness, highlighting the need for targeted trust-building initiatives and contextspecific policies to improve vaccine uptake.</div></div><div><h3>Public interest summary</h3><div>Our study looked at why many people in Latvia and Lithuania are hesitant or refuse to get vaccinated, even after the COVID-19 pandemic. We found that nearly half of adults in both countries are strongly against vaccines, and this reluctance is not driven by age, education, or income. Instead, the main reasons are a lack of trust in public health authorities and past experiences with vaccination. While some people prefer vaccines that are more effective or made in Western countries, regulations such as societal limitations or mandates little affected their choices. To increase vaccine uptake in the future, context-specific approaches and trust-building are essential.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101146"},"PeriodicalIF":3.7,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791697","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}

{"title":"Perceptions, attitudes, and intention to adopt artificial intelligence in healthcare among medical and pharmacy students","authors":"Luu Thi Thuy ,&nbsp;Hoang Thi Ngoc Sen ,&nbsp;Nguyen Huong Giang ,&nbsp;Huynh Huu Bon ,&nbsp;Vo Thi Ngoc Ha","doi":"10.1016/j.hlpt.2025.101145","DOIUrl":"10.1016/j.hlpt.2025.101145","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to describe medical and pharmacy students' perceptions, attitudes, and intention to adopt artificial intelligence (AI) in healthcare and identify factors influencing their intention to use AI.</div></div><div><h3>Methods</h3><div>This cross-sectional study was conducted in Vietnam in December 2024 using a convenience sampling strategy. A self-administered questionnaire was employed to evaluate students’ perceptions of AI applications, attitudes toward AI, and their intention to integrate AI into healthcare. Hierarchical regression analysis was carried out to identify significant factors influencing intention.</div></div><div><h3>Results</h3><div>Most participants acknowledged AI’s advantages, with 66.9 % recognizing its role in patient documentation, 63.5 % agreeing it supports preventative health recommendations, and 61.9 % endorsing its contribution to capacity planning. However, skepticism remained, as 28.1 % doubted AI’s effectiveness in psychiatric counseling, 25.7 % questioned its application in surgery, and 22.0 % were uncertain about its ability to analyze patient data for prognoses. Attitudinally, 63.1 % expressed concern over AI’s impact on job security, though 47.2 % maintained a generally positive outlook on AI’s role in healthcare. Over half of the respondents expressed a strong willingness to integrate AI into their future practice, with 60.1 % affirming their intent to use AI-based technology. Hierarchical regression analysis highlighted attitudes toward AI (ß = 0.528), perceptions of AI in individual patient care (ß = 0.207), and self-assessed technology skills (ß = -0.121) as significant predictors of intention.</div></div><div><h3>Conclusions</h3><div>Attitudes, perceptions of AI in individual patient care, and technology skills strongly influenced students’ intention to adopt AI. Integrating AI education into medical curricula may improve preparedness for AI-driven healthcare.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101145"},"PeriodicalIF":3.7,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712492","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}

{"title":"A systematic review on the impact of healthcare consolidation in the digital era","authors":"Min Chen ,&nbsp;Arman Ghafoori ,&nbsp;Wenbin Zhang","doi":"10.1016/j.hlpt.2025.101138","DOIUrl":"10.1016/j.hlpt.2025.101138","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;This systematic review examines how healthcare provider consolidation, particularly among hospitals and health systems, affects Health Information Technology (HIT), with a focus on Electronic Health Records (EHRs) and interoperability.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we reviewed literature published through June 2023 using major databases such as PubMed and Cochrane. Data from 16 peer-reviewed studies covering 125 quantitative analyses were synthesized to analyze how provider consolidation shapes HIT infrastructure and performance, including information exchange, EHR vendor diversity, and downstream outcomes such as healthcare access, cost efficiency, and care quality.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;The findings show that consolidation is significantly associated with improvements in information exchange and increased healthcare utilization, particularly in emergency department and primary care settings. While the improvements are encouraging, they are often incremental and do not yet reflect full interoperability, which involves not only data sharing but also the seamless, meaningful use of information across systems. Evidence on cost-effectiveness, care quality, and patient outcomes is mixed.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;Consolidation may improve certain aspects of digital infrastructure, especially data exchange, but does not guarantee full interoperability or better downstream outcomes. These findings point to the need for future research to go beyond measuring data exchange by assessing actual interoperability performance and examining the real-world challenges of HIT integration in consolidated systems. As healthcare consolidation continues, careful evaluation of its digital, clinical, and organizational impacts will help advance interoperability and support equitable, high-quality care.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Public Interest Summary&lt;/h3&gt;&lt;div&gt;This review explores how hospital and health system consolidations affect Health Information Technology (HIT), particularly Electronic Health Records (EHRs) and interoperability. Through a systematic search, we identified 16 papers and 125 quantitative analyses. The findings show that consolidation is significantly associated with improved information exchange and increased healthcare use. While the improvements are encouraging, they are often partial and do not mean that systems can fully and effectively use shared data across all settings. The impact on cost-effectiveness, care quality, and patient outcomes varies across studies. Our review highlights the need for more research that looks beyond basic data sharing to evaluate how well health systems actually use information and to understand the practical challenges of integrating technology after hospitals or health systems merge. The findings also offer insights to inform policy efforts aimed at promotin","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101138"},"PeriodicalIF":3.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791696","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}

{"title":"Does a tiered diagnosis and treatment system enhance self-rated health outcomes among middle-aged and older patients with hypertension or diabetes? Evidence from China","authors":"Wen He","doi":"10.1016/j.hlpt.2025.101137","DOIUrl":"10.1016/j.hlpt.2025.101137","url":null,"abstract":"<div><h3>Objective</h3><div>Addressing healthcare challenges in aging societies represents a pressing global priority for countries worldwide. To increase healthcare accessibility and equity, China introduced its tiered diagnosis and treatment (TDT) system in 2015. This study examines the impacts of this policy change on self-rated health outcomes among middle-aged and older patients with hypertension or diabetes.</div></div><div><h3>Methods</h3><div>Under a quasi-experimental framework, this study leveraged longitudinal data from four waves (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS) and employed a difference-in-differences (DID) approach to identify the impacts. To supplement this analysis, a moderating effects model was implemented to explore the potential moderating influence of health insurance coverage, primary care utilization, and treatment compliance.</div></div><div><h3>Results</h3><div>The findings revealed that following the implementation of TDT, middle-aged and older patients with hypertension or diabetes experienced a marked 31.03% enhancement in self-rated health outcomes (<em>P</em> &lt; 0.05), with effects intensifying progressively over time. Additionally, moderating analysis demonstrated that patients' health insurance coverage (<em>P</em> &lt; 0.01), expanded insurance benefits (<em>P</em> &lt; 0.05), heightened primary care utilization (<em>P</em> &lt; 0.1), and enhanced treatment compliance (<em>P</em> &lt; 0.01) collectively amplified the positive health impacts.</div></div><div><h3>Conclusions</h3><div>This study offers compelling new causal evidence that strengthening primary care systems and strategically refining healthcare resource allocation have provided tangible health benefits to vulnerable populations. Notably, as China's TDT operates on a voluntary basis, its experience provides valuable insights for countries grappling with escalating medical demands alongside fragmented healthcare systems.</div></div><div><h3>Public Interest Summary</h3><div>This study explored the impacts of the tiered diagnosis and treatment reform in China on self-rated health outcomes among middle-aged and older patients with hypertension or diabetes. By leveraging longitudinal data from a national survey and conducting a DID analysis, it provides novel evidence that the policy reform significantly enhanced the health status of this vulnerable population, with health insurance coverage and benefits, primary care utilization, and treatment compliance acting as pivotal factors in amplifying these health benefits.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 1","pages":"Article 101137"},"PeriodicalIF":3.7,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684798","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}

{"title":"\"...it saves so much time\": A qualitative exploration of the use of Generative Artificial Intelligence by the health workforce","authors":"Mia Nazir ,&nbsp;Jane Ellen Carland ,&nbsp;Melanie Keep ,&nbsp;Anna Janssen","doi":"10.1016/j.hlpt.2025.101136","DOIUrl":"10.1016/j.hlpt.2025.101136","url":null,"abstract":"<div><h3>Objectives</h3><div>Generative Artificial Intelligence (Gen AI) has become an increasingly prevalent conversation in healthcare over the past few years. Though there have been research projects and articles exploring the administrative and clinical uses of such technologies, there has been little exploration of health professional perspectives, hopes and concerns. This study sought to explore perspectives and examine the barriers and enablers of Gen AI in healthcare.</div></div><div><h3>Methodology</h3><div>Australian health professionals participated in a mixed-methods study. A survey (n=31) explored the Six Dimensions of Healthcare Quality Framework, capturing quantitative (Likert-scale responses) and qualitative (free-text) data. Semi-structured interviews (n=10) explored participant perceptions of Gen AI. Quantitative data was analysed using descriptive statistics. Qualitative data was thematically analysed.</div></div><div><h3>Results</h3><div>Most survey respondents (74.14 %) reported having used Gen AI to support their work, but only a few (25.81 %) reported organisational supports for use of these technologies. Analysis of the qualitative data aligned with the survey responses. Five themes were generated through thematic analysis, aligning with health professional’s perceived use of Gen AI chatbots, benefits, risks, as well as drivers of safe use and opportunities for the future.</div></div><div><h3>Conclusion</h3><div>Health professionals see potential for using Gen AI to support their work, with enthusiasm about the potential of Gen AI to reduce workloads, particularly in offloading administrative tasks. There is also awareness that Gen AI chatbots pose risks both at the individual level such as limited capability in using these technologies and at the organisational level such as lack of training to support in upskilling, and systemic concerns around policy gaps.</div></div><div><h3>Public Interest Summary</h3><div>Generative Artificial Intelligence (Gen AI) is increasingly topical in all aspects of life, and the health sector is no exception. Though there have been research projects focusing on Gen AI in healthcare, there has been little exploration of health professional views and concerns. This study spoke to health professionals and found that though there is a lot of interest in potential applications of Gen AI in healthcare, particularly in administrative offloading and clinical support, however, the benefits don’t yet outweigh the risks. Software developers must work alongside health professionals in developing a substantially beneficial program to support the safe use of Gen AI in healthcare as well as be well supported on an organisational level. There are also opportunities to develop education to build health professionals capacity to use GenAI safely and effectively, and for health service organisations to develop guidance and policies to clearly articulate what safe use looks like.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 1","pages":"Article 101136"},"PeriodicalIF":3.7,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614464","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}