The Lessons Learned from the Dusit Model and the Feasibility of Applying Integrated Health Services in Urban Areas: A Qualitative Study in Thailand

The Lessons Learned from the Dusit Model and the Feasibility of Applying Integrated Health Services in Urban Areas: A Qualitative Study in Thailand | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Lessons Learned from the Dusit Model and the Feasibility of Applying Integrated Health Services in Urban Areas: A Qualitative Study in Thailand Basmon Manomaipiboon, Jadsada Kunno, Araya Chiangkhong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7691983/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Rapid urbanization has intensified the demand for effective, evidence-based models of integrated health services. However, significant gaps remain in translating such models into practice. This qualitative descriptive study explores lessons learned from the Dusit Model of integrated health services and evaluates its feasibility for adaptation in the Sai Mai District of Bangkok, Thailand. Methods Between May and December 2024, semi-structured interviews were conducted with three key stakeholder groups: administrators, healthcare providers, and patients. Data collection focused on four core components—technologies, institutions, resources, and stakeholders. All interviews were audio-recorded and analyzed systematically to ensure rigor and objectivity. Ethical approval was obtained from the Faculty of Medicine Vajira Hospital, Navamindradhiraj University, and all participants provided informed consent. Results The Dusit Model demonstrated strong potential as a blueprint for integrated urban healthcare, particularly through its use of digital platforms (e.g., Vajira@Home and V-Refer ) and its emphasis on inter-institutional collaboration. These features enhanced service efficiency and care continuity. Nonetheless, challenges were identified, including healthcare workforce shortages and limited digital literacy among older adults. The Sai Mai District was found to be well-positioned for model adoption, given its comparable demographics, robust healthcare network, and strong leadership. To optimize implementation, the district should prioritize workforce development in digital competencies and leverage public health centers as coordination hubs. Conclusions The Dusit Model demonstrates that digital integration and collaborative networks strengthen urban health systems. The Sai Mai District is well-positioned for adoption, provided staff receive targeted digital training and public health centers act as coordination hubs. By addressing a critical research gap, this study offers empirical evidence to guide scalable and sustainable integrated healthcare in rapidly urbanizing contexts. Dusit Model Integrated Health Services Urban Areas Technologies Urban Healthcare Thailand Figures Figure 1 Introduction Integrated health services refer to an approach in which diverse health professionals collaborate to deliver comprehensive, person-centered care ( 1 ). In urban settings, multidisciplinary teams are particularly important for ensuring high-quality care to vulnerable populations ( 2 ). However, integrated health services in urban contexts face persistent challenges, including socioeconomic inequities and fragmented provider networks ( 3 ). Rapid urbanization further exacerbates these issues, creating barriers to equitable and culturally sensitive care delivery ( 3 – 5 ). In this regard, practical models are needed to bridge gaps between public and private healthcare systems and to provide contextually appropriate interventions in complex urban environments. In Thailand, integrated health services face distinct challenges, including limited availability of public primary care facilities, a system fragmented by the predominance of private clinics, and an unequal distribution of healthcare workers ( 6 – 8 ). In Bangkok, these systemic issues are compounded by barriers such as restrictions on access for migrant populations, long waiting times, and high out-of-pocket costs. Healthcare access is further influenced by multiple medical benefit schemes, such as the Universal Coverage Scheme, Social Security Scheme, and the Civil Servant Medical Benefit Scheme. To address these challenges, the Dusit Model was developed as an integrated healthcare initiative within the Dusit zone of Bangkok, encompassing the Dusit, Bang Phlat, Bang Sue, and Phra Nakhon Districts (Fig. 1 ). This model integrates services across seven public and four private health centers, providing accessible, one-stop healthcare. By emphasizing coordination across providers, the Dusit Model has reduced hospital overcrowding and improved healthcare accessibility for urban populations. Building on this success, the Sai Mai District—facing similar challenges, including an aging population, a growing burden of non-communicable diseases (NCDs), and resource limitations—has been identified as a potential site for adaptation. Additionally, rapid urbanization, migration, and fragmented health coverage have intensified inequities, underscoring the urgent need for comprehensive reforms to strengthen urban health systems ( 2 , 5 , 9 ). These issues give rise to two main research objectives: ( 1 ) to identify the key factors driving the success of the Dusit Model and ( 2 ) to evaluate the feasibility of applying the lessons learned from the Dusit Model to the Sai Mai District of Bangkok. Although the need for integrated urban health services is widely recognized, a significant research gap remains in developing and testing practical models to address these challenges, particularly in rapidly urbanizing contexts such as Bangkok. Despite the demonstrated benefits of integrated care, there is still a lack of evidence-based frameworks ( 10 – 12 ) that explicitly address three critical challenges: overcoming fragmentation between public and private healthcare systems ( 13 , 14 ), effectively integrating migrant populations into urban healthcare networks ( 15 , 16 ), and reforming complex health benefit schemes to ensure equitable access for all residents ( 17 , 18 ). Existing studies have largely focused on high-income countries, leaving limited empirical evidence from middle-income urban contexts where health system fragmentation and rapid demographic transitions are most pronounced. To address this knowledge gap, the present qualitative descriptive study examines the lessons learned from the Dusit Model’s integrated health services and evaluates its feasibility for implementation in the Sai Mai District of Bangkok. By incorporating perspectives from administrators, healthcare providers, and patients, this study aims to generate contextually grounded evidence. It is anticipated that the findings will provide a practical blueprint for integrated healthcare, thereby filling a critical gap in the literature and informing policies and practices in similar urban environments, both in Thailand and internationally. Methods Study Design This qualitative descriptive study was conducted between May and December 2024. Ethical approval was obtained, and all participants provided informed consent prior to data collection. Data collection was guided by the Healthcare Ecosystem framework, which emphasizes organizational structure, roles, operational challenges, and legal/cultural constraints within Bangkok’s healthcare management system ( 19 , 20 ). This framework, recognized as a valuable tool for analyzing and strengthening complex health systems ( 20 ), was applied to examine both the Dusit Model and current health services in the Sai Mai District, with particular attention to four key components: technologies, institutions, resources, and stakeholders ( 20 ). Study Areas This study was conducted in two locations: ( 1 ) the Dusit Model service areas, including Vajira Hospital, affiliated health centers, and network clinics; and ( 2 ) healthcare facilities in the Sai Mai District, comprising Bhumibol Adulyadej Hospital, primary care units, and public health centers. These sites were selected to provide a comprehensive overview of the existing healthcare network and to assess its potential for expansion. Data Collection Instruments The semi-structured interview and focus group discussion guides were specifically developed for the purposes of this study, drawing upon the research objectives and the Healthcare Ecosystem framework. These instruments have not been previously published or employed in other studies. For the purpose of transparency and replicability, an English version of the instruments has been provided as Supplementary File S1 and has been cited accordingly in the Methods section of the manuscript. Study Population and Recruitment The study population comprised two stakeholder groups: Dusit Model stakeholders and Sai Mai District stakeholders. Each group included administrators and coordinators, healthcare providers, and patients. Participants were selected based on their diverse expertise and first-hand experience to ensure a comprehensive understanding of both the Dusit Model and its potential application in the Sai Mai District’s urban healthcare context. Dusit Model stakeholders . Recruitment was based on direct involvement in key components such as leadership, patient referral systems, telemedicine, and patient satisfaction programs. This group was subdivided into three categories: ( 1 ) Administrators and coordinators (DM-ADM#), selected for their strategic perspectives on scalability and operational efficiency; ( 2 ) Healthcare providers (DM-HCP#), chosen for their hands-on experience with telemedicine and referral systems, as well as their insights into technical and logistical challenges; and ( 3 ) Patients (DM-PT#), included for their experiences and satisfaction with healthcare services under the Dusit Model. Sai Mai District stakeholders . Recruitment was guided by the ability to evaluate the feasibility of adapting the Dusit Model to a new urban setting while addressing local challenges such as high population density and population aging. This group was subdivided into three categories: ( 1 ) Administrators and coordinators (SM-ADM#), selected for their roles in overseeing healthcare operations and their strategic perspectives on adapting the model to a different context; ( 2 ) Healthcare providers (SM-HCP#), chosen for their practical experience with the district’s existing healthcare infrastructure and their perspectives on the potential integration of telemedicine and referral systems; and ( 3 ) Patients (SM-PT#), selected for their experiences with the district’s healthcare services and their views on accessibility and effectiveness. For both stakeholder groups, participants were identified through publicly available sources, including institutional emails, social media platforms, and professional networks. Data Collection In compliance with physical and social distancing policies, all interviews were conducted remotely via telephone or video conferencing. Prior to participation, written or verbal informed consent was obtained. Each interview was audio-recorded and lasted between 45 and 60 minutes. Semi-structured interview guides were developed for three key informant groups. For administrators and coordinators, questions addressed strategic planning, network management, and policy- and leadership-related challenges and opportunities in the local healthcare system. For healthcare providers, questions focused on patient care, inter-unit collaboration, workforce capacity, and the implementation of digital health programs such as Vajira@Home, Vajira Smile, V-Refer , and V-EMS , as well as their training needs. For patients, questions examined their service experiences, access barriers, and specific care needs, particularly among the elderly and those with chronic illnesses. The interview guide allowed flexibility for participants to reflect freely while ensuring systematic comparability across cases. To ensure comprehensive data coverage, multiple qualitative methods were employed. First, in-depth interviews with open-ended questions explored stakeholder experiences with the Dusit Model and perceptions of its feasibility in the Sai Mai District. Second, focus group discussions facilitated collective insights, addressed operational challenges, and included a SWOT (strengths, weaknesses, opportunities, and threats) analysis of the Dusit Model. Third, participant observations were conducted in healthcare settings, with attention to e-health applications and patient referral systems, to provide contextual understanding. Finally, document analysis examined policy frameworks, program documents, and patient records, contributing to data triangulation. A flexible, participant-led interview approach was adopted to create a safe environment and allow participants to guide discussions toward personally relevant issues. The data collection team included two interviewers, three research staff, and two research assistants, all of whom were trained in qualitative research. The interviewers had no prior relationship with the participants, ensuring objectivity. Training in qualitative interviewing was provided through a 60-minute workshop on best practices led by the principal investigators, supplemented by assigned readings on qualitative interviewing techniques and theory. To maintain data quality and consistency, regular debriefing sessions were held in which interviewers shared field notes and discussed emerging themes. Recruitment continued until data saturation was reached, defined as three consecutive interviews yielding no new information. All interviews were transcribed verbatim, reviewed for accuracy, de-identified, and returned to participants for verification of accuracy and privacy ( 21 ). Data Analysis Four instruments informed the analysis: ( 1 ) in-depth interviews, using open-ended questions to explore stakeholders’ understanding of the Dusit Model; ( 2 ) focus groups, which generated collective insights, performed a SWOT analysis of the Dusit Model, and synthesized strategies through a TOWS Matrix; ( 3 ) participant observations; and ( 4 ) document analyses. Themes were inductively constructed during initial coding and refined deductively through subsequent interpretation using the resilience framework ( 21 ). The analytic process followed the framework of Miles and Huberman ( 21 ), which consists of data organization, data display, and conclusion drawing. To ensure trustworthiness, several strategies were employed: triangulation of data sources (interviews, focus groups, and observations), member checking, and maintenance of an audit trail. Peer debriefing and iterative coding were also applied to refine themes and minimize bias, thereby enhancing the credibility of the findings. With respect to transcription and organization, researchers AC and BM read all transcripts to achieve data familiarization and produced notes to aid recall. Researcher JK then classified the data into major themes, which were further divided into key issues aligned with the study objectives. Tables were developed to categorize these themes systematically, ensuring that the data were clearly organized for analysis. Subsequently, BM, JK, and AC applied content analysis to link the categorized data with descriptive reports, thereby facilitating the interpretation of the phenomenon under study. To conclude and verify the findings, the research team jointly reviewed all data for interpretation and knowledge generation. The accuracy of interpretations was corroborated by cross-checking with informants’ statements. Finally, validation was achieved through triangulation across multiple data sources, the use of diverse collection methods, and the involvement of multiple analysts. Results Participant Demographics In this study, there was a total of 80 participants. The participant demographics are outlined in Table 1, while Table 2 presents an overview of the identified themes and sub-themes. Specifically, Themes I–IV analyze the success factors of the Dusit Model’s integrated health services, while Themes V–VI determine the feasibility of applying the lessons learned from the Dusit Model to the Sai Mai District. Table 1. Participant Demographics Category Frequency (n) Code Group 1: Dusit Model stakeholders Administrators and coordinators 3 DM-ADM# Healthcare providers 18 DM-HCP# Patients 15 DM-PT# Group 2: Sai Mai District stakeholders Administrators and coordinators 12 SM-ADM# Healthcare providers 16 SM-HCP# Patients 16 SM-PT# Table 2. Overview of the Identified Themes and Sub-themes Themes Sub-themes Part 1: To analyze the success factors of the Dusit Model’s integrated health services I General context, health situation, access to healthcare services, and challenges identified in the Dusit District Geographical and demographic context Healthcare challenges and utilization Healthcare service access Operational challenges II Formation of the Dusit Model task force and network Organizational structure Outcomes of the network establishment III Operational strategies Vajira@Home Vajira Smile V-Refer V-EMS IV SWOT analysis and TOWS Matrix Part 2: To Determine the Feasibility of Applying the Lessons Learned from the Dusit Model to the Sai Mai District V Feasibility of adapting the Dusit Model to the Sai Mai District Alignment with the Sai Mai District’s healthcare landscape Demographic compatibility with the model Healthcare workforce readiness Health network capacity Addressing urban healthcare challenges Policy and leadership support VI Key considerations for implementation Human resource development Strengthening interagency collaboration Addressing unregistered populations Budgetary considerations Part 1: To Analyze the Success Factors of the Dusit Model’s Integrated Health Services Theme I Geographical and demographic context: Situated on the Chao Phraya River, the Dusit District spans 10.66 square kilometers and includes a population of 75,538. Its combination of dense residential zones, businesses, and government offices creates a diverse population, including the elderly, working-age adults, children, and unregistered residents, all with complex healthcare and social needs. Healthcare challenges and utilization: The Dusit District includes major healthcare issues, especially with its aging population and the prevalence of NCDs. It also leads the region in outpatient service use (35%), followed by the Bang Sue, Bang Phlat, and Phra Nakhon Districts. As for inpatient care, the Dusit District is second (32%), just behind the Bang Sue District. The most common health problems for outpatients are musculoskeletal issues, diabetes, and hypertension, while pneumonia and digestive diseases are the most common for inpatients. Healthcare service access: The Dusit Model connects Vajira Hospital, public health centers, and “Warm Clinics” to offer basic through advanced healthcare. This system also uses various technologies such as Vajira@Home for at-home consultations and medication delivery and V-Refer to safely and quickly transfer patients to Vajira Hospital when they require more specialized care. This integration ensures that patients can receive basic care at local clinics and be easily referred to the hospital for more serious conditions. Operational challenges: Vajira Hospital struggles with overcrowding and excessive wait times. Patients also face delays due to the necessary paperwork to transfer their healthcare rights. Meanwhile, local health centers and Warm Clinics are short-staffed, limiting their ability to effectively serve the community. In addition, the district’s unregistered population makes it difficult to plan for resources, while vulnerable groups (e.g., the elderly) have trouble using telemedicine services such as Vajira@Home . Theme II The Dusit Model was created to unite healthcare providers and improve services in the city. This network, which includes the Faculty of Medicine Vajira Hospital, public health centers, and Warm Clinics, aims to build a comprehensive and sustainable healthcare system that meets the needs of everyone in the Dusit District. Organizational structure: The Dusit Model’s healthcare network is well-coordinated, with its members meeting every month to discuss current progress, ongoing challenges, and future plans, including how to manage chronic illnesses and improve the referral system. According to one network manager, “These meetings help all the network ’s units coordinate and immediately exchange solutions to problems ” (DM-ADM01) . This network also uses a group messaging platform ( Line ) for quick updates and emergencies. This platform has been essential for making timely patient referrals and managing medical supplies. As stated by one frontline staff member, “The Line group helps them address issues promptly and builds trust within the team ” (DM-HCP03) . Additionally, through the “Friend Visits Friend” initiative, healthcare agencies can learn from one another. In this case, the staff from Vajira Hospital and public health centers visit other locations to share their best ideas and practices. According to one nurse, “These visits provide practical insights that we can bring back to improve our services” (DM-HCP04). Outcomes of the network establishment: This network has significantly improved service integration. For example, the V-Refer system has cut patient transfer times by 30%. In this regard, one secondary care physician stated, “ V-Refer r educes delays and increases patient satisfaction ” (DM-HCP01) , while one patient who used the system added, “ Before this system, I had to wait hours for a transfer, but now I feel safer and more confident knowing my case is handled faster ” (DM-PT03) . Meanwhile, capacity-building initiatives, such as training programs and knowledge exchanges, have improved staff competence in handling referrals and managing chronic conditions. As one primary care staff member reflected, “The training has increased our confidence in managing referrals and chronic patients” (DM-HCP08) . Similarly, one chronic disease patient stated, “I feel more cared for because the staff can now explain my treatment options clearly and manage my case more effectively” (DM-PT06). Moreover, the “Friend Visits Friend” program has built stronger professional bonds within the network. According to one manager, “It brought us closer together, building trust that allows us to resolve issues more quickly” (DM-ADM02). Likewise, one patient stated, “Seeing different teams working together for my health made me trust the system more” (DM-PT07). Theme III The Dusit Model improves healthcare efficiency and accessibility through four key sub-programs: Vajira@Home is a telemedicine program that allows patients to have doctor consultations and receive care from home, thus reducing hospital overcrowding. As one physician noted, “The system is designed to support patients who cannot travel, but still require comprehensive care” (DM-HCP01). Similarly, one patient stated, “Having consultations from home has made my treatment easier and more comfortable. I no longer need to wait at the hospital” (DM-PT03). Vajira Smile aims to improve the patient experience by training staff to be more welcoming. As one staff member explained, “We strive to create an atmosphere where patients feel cared for with attentiveness and friendliness ” (DM-HCP05). In this regard, one patient stated, “The staff are more understanding and approachable now, which makes the hospital feel less intimidating” (DM-PT07). V-Refer is a referral system that makes patient transfers quicker and safer. As one physician involved in the program noted, “ V-Refer i mproves communication and accelerates patient care ” (DM-HCP05) . Similarly, one patient stated, “I was transferred to the hospital much faster than before, and I felt reassured throughout the process” (DM-PT09). V-EMS is an emergency management system that uses real-time data for faster, more effective responses. According to one emergency responder, “The system enhances efficiency and reduces errors” (DM-HCP04). Moreover, one patient who used the service felt safe because the team was “well-prepared” and “had all the information that they needed beforehand” (DM-PT05). Theme IV Based on a SWOT analysis (Table 3), the Dusit Model includes strong points such as integrated care, advanced technologies (e.g., V-Refer , Vajira@Home ), and high patient satisfaction. Conversely, it faces weaknesses such as staff shortages and a population that is not fully aware of telemedicine. Meanwhile, it can take advantage of opportunities from national policies and new technologies, but it must also deal with threats such as complex entitlement systems and tight budgets. As for the TOWS Matrix analysis (Table 4), it turns the SWOT analysis into a practical roadmap by using the model’s strengths to seize opportunities such as expanding telemedicine services to align with national policies and forming partnerships with private companies. It also provides strategies to counter threats such as improving coordination among agencies and simplifying the referral process. Regarding weaknesses, the matrix recommends training for vulnerable groups by using different technologies and improving staffing in primary care. Overall, Tables 3 and 4 offer a comprehensive picture of the Dusit Model, highlighting its potential to improve urban healthcare and providing a roadmap for its future development and expansion. Table 3. Opportunities and Challenges for Urban Healthcare Integration, Based on a SWOT Analysis of the Dusit Model Category Positive Aspects (Strengths & Opportunities) Challenges (Weaknesses & Threats) Internal Factors Strengths Weaknesses - Integration of health services across primary, secondary, and tertiary levels, exemplified by the V-Refer system, which reduces patient transfer times by 30%. - Insufficient staffing levels in primary healthcare facilities, limiting the ability to provide comprehensive care. - Utilization of advanced technologies, such as Vajira@Home and V-EMS , improves healthcare accessibility and alleviates hospital overcrowding. - Limited public understanding of technological solutions, especially among older populations, impeding telemedicine usage. - High patient satisfaction with services, as demonstrated by a 4.8/5 satisfaction rating for the Vajira Smile initiative. - Complexities in referral processes due to incomplete/fragmented patient information in the database. - Effective inter-agency collaboration supported by regular meetings and initiatives, fostering cohesive teamwork. External Factors Opportunities Threats - National policies promoting health zones provide opportunities to replicate successful models, such as the Dusit Model, in other urban areas. - Challenges in navigating complex healthcare entitlement systems, which create barriers to service access for patients. - Expansion of health technology innovations, including telemedicine and advanced data management, to improve service delivery. - Budgetary and resource limitations present obstacles to scaling the model to other urban areas. - Opportunities for collaboration with private sector entities to enhance resource allocation and workforce training. - Fragmentation and inefficiencies in urban healthcare management due to overlapping responsibilities among multiple agencies. Table 4. Strategic Insights for Urban Healthcare Development, Based on a TOWS Matrix Analysis of the Dusit Model Category Positive Aspects (Strengths & Opportunities) Challenges (Weaknesses & Threats) Internal Factors Strengths Weaknesses - Integration of health services across primary, secondary, and tertiary levels, exemplified by the V-Refer system, which reduces patient transfer times by 30%. - Insufficient staffing levels in primary healthcare facilities, limiting the ability to provide comprehensive care. - Utilization of advanced technologies, such as Vajira@Home and V-EMS , enhances healthcare accessibility and alleviates hospital overcrowding. - Limited public understanding of technological solutions, particularly among older populations, impeding telemedicine usage. - High patient satisfaction with services, as demonstrated by a 4.8/5 satisfaction rating for the Vajira Smile initiative. - Complexities in referral processes due to incomplete or fragmented patient information within the database. - Effective inter-agency collaboration supported by regular meetings and initiatives, fostering cohesive teamwork. External Factors Opportunities Threats - National policies promoting health zones provide opportunities to replicate successful models, such as the Dusit Model, in other urban areas. - Challenges in navigating complex healthcare entitlement systems, which create barriers to service access for patients. - Expansion of health technology innovations, including telemedicine and advanced data management, to improve service delivery. - Budgetary and resource limitations present obstacles to scaling the model to other urban areas. - Opportunities for collaboration with private sector entities to enhance resource allocation and workforce training. - Fragmentation and inefficiencies in urban healthcare management due to overlapping responsibilities among multiple agencies. Part 2: To Determine the Feasibility of Applying the Lessons Learned from the Dusit Model to the Sai Mai District The Dusit Model was evaluated for its potential in the Sai Mai District. In this regard, a feasibility study, including interviews with key stakeholders, identified two main areas: 1) The feasibility of adapting the model; and 2) The key considerations for putting it into practice. Theme V The Dusit Model is well-suited for the Sai Mai District because it matches the area’s health needs and ability to use new technologies. This section examines the feasibility of this model and how it can improve healthcare in this district. Alignment with the Sai Mai District’s healthcare landscape: The Sai Mai District’s healthcare facilities are well-suited for adopting the Dusit Model. As one district administrator stated, “The Sai Mai District’s existing facilities are well-positioned to adopt an integrated system, such as the Dusit Model, ensuring comprehensive and efficient healthcare delivery” (SM-ADM01). Similarly, one public health planner added, “The variety of facilities in the Sai Mai District makes it flexible enough to adopt key parts of the model such as its referral and telemedicine systems” (SM-PT01). Demographic compatibility with the model: The Sai Mai District’s population profile, with its dense communities and large elderly population, is a good match for the Dusit Model. According to one public health nurse, “The similarities make this model highly applicable, especially for addressing the needs of the aging population” (SM-HCP01). In this regard, one elderly care specialist added: “Since more elderly residents need long-term care, a structured model is essential for improving healthcare delivery” (SM-HCP02). Healthcare workforce readiness: The Sai Mai District’s healthcare workers are adaptable, but they need more training to get the most out of the digital tools. In this case, one local physician noted, “The staff are familiar with technology, but targeted training will improve their ability to effectively utilize systems such as V-Refer” (SM-HCP03). Meanwhile, one nurse manager added, “While the team is motivated to embrace new technologies, hands-on training is essential for a smooth implementation” (SM-HCP04). Health network capacity: The Sai Mai District’s public health centers are in key locations to coordinate care. According to one health center manager, “The existing healthcare network in the Sai Mai District is well-prepared for the integration of systems, such as e-Referral, enabling smoother patient management” (SM-HCM01). Another manager added, “Strong collaboration across facilities ensures that the Dusit Model can be implemented with minimal disruption to existing services” (SM-HCM02). Addressing urban healthcare challenges: With the increasing prevalence of NCDs and an aging population, the Sai Mai District is facing growing pressure on its healthcare services. As one public health officer observed: “The rising patient numbers underline the urgency of adopting structured systems, such as the Dusit Model, to streamline care delivery and reduce hospital congestion” (SM-HCP03). Similarly, one patient advocate emphasized: “The current system can be challenging for patients to navigate, so integrating the Dusit Model will provide clarity and improve access to care” (SM-PT02). Policy and leadership support: Supportive urban health zone policies and proactive local leaders can make it easier to adopt the Dusit Model in the Sai Mai District. As one district administrator explained, “Policies promoting urban health zones offer a strong foundation for replicating successful frameworks such as the Dusit Model” (SM-ADM02). Moreover, one policy advisor added, “The commitment from local leaders will play a pivotal role in effectively scaling the Dusit Model” (SM-HCP06). Theme VI In order for the Dusit Model to be successfully implemented in the Sai Mai District, several key areas must be addressed, including: improving human resources with targeted training; strengthening collaboration between agencies; providing fair access to healthcare for unregistered residents; and securing sufficient funding. Human resource development: Investing in training is vital so that healthcare staff can effectively use technologies and manage patient care. As one nurse stated: “Training helps staff handle referral systems efficiently and minimize errors” (SM-HCP05). In this regard, one health trainer added, “Focused training on tools, such as V-Refer, can increase staff confidence and efficiency, which is key for a smooth transition to the new model” (SM-HCP06). Strengthening interagency collaboration: Effective collaboration between hospitals, public health centers, and other groups is important for integrated services. As one health center manager stated, “ Strong partnerships within the healthcare network are essential for optimizing patient care and referral processes ” (SM-HCM03) . Meanwhile, one hospital administrator added, “Coordinating efforts will be critical for overcoming operational challenges and ensuring the model’s success” (SM-ADM03). Addressing unregistered populations: The large number of unregistered residents in the Sai Mai District creates challenges for providing equal healthcare to all individuals. As one district administrator emphasized, “Incorporating unregistered residents into the healthcare system is vital to achieving inclusivity and reducing disparities’ (SM-ADM04). Similarly, one community health worker stated, “Addressing the barriers that this group faces will improve healthcare outcomes across the district” (SM-HCP07). Budgetary considerations: To ensure that the model is sustainable, it is essential to secure adequate funding for technology and workforce development. As one project planner explained, “Allocating resources effectively is pivotal for the model’s success” (SM-PT03). In this regard, one financial officer noted, “Budgeting for both technology and staff is crucial for the model’s long-term viability” (SM-ADM05). Discussion This study provides an in-depth understanding of the success factors underpinning the Dusit Model’s integrated health services and evaluates its feasibility for implementation in the Sai Mai District. Insights from stakeholders highlight the changes required at the urban level to reduce challenges and strengthen policy implementation. These findings can inform urban health systems seeking to address major public health concerns, including the rising prevalence of non-communicable diseases (NCDs), limited access to healthy food, and harmful environmental exposures. Part 1: To Analyze the Success Factors of the Dusit Model’s Integrated Health Services The Dusit Model demonstrates strong potential as a framework for integrated healthcare in dense urban populations, encompassing children, working-age adults, the elderly, and unregistered residents. Comparable evidence suggests that enabling healthcare access for aging populations requires attention to social and psychological factors, such as self-efficacy and social support, in addition to clinical services, as these factors can mitigate barriers such as geographic isolation ( 22 ). Furthermore, underserved populations should have universal access to preventive and outpatient services, regardless of immigration status ( 23 ). The findings indicate that the Dusit Model leverages advanced technologies to enhance efficiency and continuity of care. For example, Vajira@Home supports remote consultations to relieve hospital overcrowding, while V-Refer facilitates patient transfers between facilities. Telehealth also enables case management by transmitting information before a patient is transferred to an urban center and serves as an efficient method for follow-up visits, thereby strengthening continuity of care ( 24 ). Consistent with this, previous studies report that triage by physicians and the placement of primary care clinicians in emergency departments improve patient flow ( 25 ). Thus, the Dusit Model provides a clear operational blueprint for improving urban healthcare efficiency. The Dusit Model also emphasizes collaboration through a network of hospitals, public health centers, and Warm Clinics, aligning with earlier findings ( 26 ). Inter-agency meetings and communication platforms (e.g., Line) ensure seamless coordination, while initiatives such as Friend Visits Friend promote professional development and mutual trust through shared learning. Collaborative approaches have been shown to prevent errors, increase efficiency, and improve effectiveness in health systems worldwide ( 27 – 29 ). These findings confirm that strong networks are critical to high-quality, integrated healthcare delivery. Despite its strengths, the Dusit Model also faces challenges. These include workforce shortages in primary care, which constrain service capacity, and low digital literacy among older adults, which hinders telemedicine use. Similar barriers have been identified in rural communities, where limited digital skills impede access to e-health services ( 30 ). Without targeted education and training, older patients may struggle to use these platforms effectively. Although telemedicine use increased during the COVID-19 pandemic, sustained efforts are needed to improve digital literacy and infrastructure for equitable access ( 31 ). Targeted interventions, such as specialized staff training, digital literacy initiatives, and streamlined administrative processes, are therefore essential. Digital tools, including mobile applications and telemedicine platforms, can simultaneously improve health literacy and outcomes ( 32 ). Overall, the Dusit Model integrates services across levels of care, making it both a scalable and sustainable blueprint for urban healthcare systems. Part 2: To Determine the Feasibility of Applying the Lessons Learned From the Dusit Model to the Sai Mai District The study found that the Sai Mai District’s healthcare network, including public health centers, hospitals, and clinics, is well-suited for integrating advanced systems such as V-Refer and Vajira@Home. These platforms can improve patient care through streamlined referrals and remote services. The district’s demographics, particularly its dense and aging population, closely mirror those of the Dusit District, making this model highly relevant for addressing the healthcare needs of older adults and managing the growing burden of NCDs. Previous studies have also suggested that engaging the private sector can leverage its expertise, technologies, and financial resources for health initiatives, especially for NCDs and related emergencies ( 33 ). Healthcare staff in the Sai Mai District are ready to adopt digital tools, but additional training is necessary to optimize their use. Tailored training programs for platforms such as V-Refer could enhance staff confidence and efficiency, ensuring seamless integration of the Dusit Model. In addition, the district’s public health centers are strategically positioned to serve as coordination hubs between primary and secondary care providers, fostering a smooth implementation process. Related research has shown that strong interagency networks are vital for sustainable development, as they pool resources and diverse perspectives to navigate complex challenges ( 34 – 36 ). Policies supporting urban health zones and the active involvement of local leaders can further strengthen Sai Mai’s readiness to adopt the Dusit Model. This framework provides a pathway for integrating technology-driven healthcare solutions while ensuring long-term scalability and sustainability. Prior research underscores that stakeholder alignment, adherence to ethical standards, and innovation are essential for sustainable model adoption ( 37 , 38 ). Accordingly, while the Sai Mai District demonstrates strong potential to apply the Dusit Model, successful implementation will depend on prioritizing digital literacy training for staff and leveraging public health centers as coordination hubs. This study has several strengths. First, it adopted a multi-stakeholder perspective, incorporating the views of administrators, healthcare providers, and patients. This triangulation of perspectives enhances the validity of the findings and provides a holistic view of the Dusit Model’s effectiveness and feasibility. Second, the use of multiple data sources including in-depth interviews, focus groups, participant observations, and document analyses strengthened the rigor of the qualitative approach and allowed for comprehensive data triangulation. Third, the study contributes empirical insights from an urban context in a middle-income country, where evidence on integrated health services remains limited. This adds value to the global discourse on health system reform by demonstrating how locally developed models can be adapted and scaled in other rapidly urbanizing settings. Challenges and Limitations Successful implementation of the Dusit Model requires addressing several challenges. Healthcare staff need comprehensive training to strengthen digital literacy and confidence in using platforms such as Vajira@Home and V-Refer. Improved collaboration among public health centers, hospitals, and other stakeholders is also necessary to reduce duplication and service gaps. In addition, the inclusion of unregistered populations in healthcare planning is vital to reduce inequities, while stable budget allocation and long-term financial strategies are required to support workforce development and sustain digital health initiatives. This study relied primarily on the perspectives of frontline healthcare workers, excluding urban-level policymakers whose insights could clarify upstream barriers and policy priorities. Recruitment also occurred during a period of high workload, resulting in a relatively small sample size and limited representation from remote centers and allied health professionals. Although these factors may restrict generalizability, the findings remain relevant to similar urban contexts given their consistency with existing literature. Future studies should incorporate policymakers and employ larger, more diverse samples, including quantitative surveys, to validate and extend these results. Conclusion This study demonstrates that the Dusit Model’s success derives from its strategic use of digital technologies and inter-organizational collaboration to manage healthcare for diverse urban populations. The findings also indicate that the Sai Mai District is well-positioned to adopt this framework, provided that targeted staff training is conducted and public health centers are strengthened as coordination hubs. More importantly, the study addresses a critical research gap by providing empirical evidence on how integrated health service models can be adapted in rapidly urbanizing, middle-income contexts. Unlike earlier research, which has offered limited practical guidance for overcoming system fragmentation, integrating marginalized populations, or aligning complex benefit schemes, this study identifies both the success factors and the contextual requirements for replication. By doing so, it contributes to the evidence base for designing scalable and sustainable integrated healthcare solutions in Bangkok and other comparable urban environments. Abbreviations NCDs non-communicable diseases DM-ADM Dusit Model-Administrators and coordinators DM-HCP Dusit Model-Healthcare providers DM-PT) Dusit Model-Patients SM-ADM Sai Mai-Administrators and coordinators SM-HCP Sai Mai-Healthcare providers SM-PT Sai Mai-Patients Declarations Supplementary Information Supplementary File S1. The full English language version of the questionnaire on interview & Focus group discussion Statements and declarations The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval and consent to participate The study was approved by the Ethics Committee of the Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand (Approval No. COA 078/2567). The participants were informed that they could leave the study at any time without justifying their decision, and data were not saved until the participants finished the questionnaire and confirmed submitting their answers. To maximize anonymity, no identifying personal data were collected from the participants. All measurements were conducted subsequent to the participants completion of the questionnaire and provision of written consent. All participants have been performed in accordance with the Declaration of Helsinki and have been approved by an appropriate ethics committee. The Institutional Review Board of the Faculty of Medicine at Vajira Hospital complies fully with international guidelines for human research protection, such as the Declaration of Helsinki, The Belmont Report, the CIOMS Guideline, and the International Conference on Harmonization in Good Clinical Practice (ICH-GCP). The study was conducted in accordance with the Declaration of Helsinki and received approval from the appropriate ethics committee. Consent for publication Not applicable Availability of data and materials The datasets generated and analyzed during the current study are described in the protocol titled “Developing Innovative, Integrated Health Service Models to Address Urban Challenges” (Approval No. COA 078/2567). These datasets are not publicly available due to institutional restrictions but can be obtained from the corresponding author upon reasonable request. In addition, Figure 1. Dusit zone including four districts in Bangkok, Thailand was adapted from data used in a previous study, “Effect of Dusit zone referral routes on patient satisfaction: A cross-sectional study in Bangkok, Thailand” (manuscript under review). Competing interests The authors declare that they have no conflicts of interest, Not Applicable. Funding This work was supported by the Program Management Unit on Area-based Development (PMU A), Ministry of Higher Education, Science, Research, and Innovation; (grant number: A13F680052). Authors’ contributions Basmon Manomaipiboon: Conceptualization, Methodology, Project administration, Data curation, Formal analysis, Investigation, Validation, Visualization, Supervision, Writing – original draft, Writing – review & editing, Submission. Jadsada Kunno: Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing. Araya Chiangkhong: Conceptualization, Methodology, Project administration, Data curation, Formal analysis, Investigation, Validation, Visualization, Supervision, Writing – original draft, Writing – review & editing, Submission. Acknowledgements The authors would like to thank the Faculty of Medicine Vajira Hospital and Navamindradhiraj University, Bangkok, Thailand, for providing full support for the article processing charges and English language editing of this manuscript. We also gratefully acknowledge the collaboration of healthcare facilities in the Sai Mai District, including Bhumibol Adulyadej Hospital, primary care units, and public health centers. This work was funded by the Program Management Unit on Area-based Development (PMU A), Ministry of Higher Education, Science, Research, and Innovation, Thailand (Grant No. A13F680052). Authors’ information 1 Department of Urban Medicine, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand 2 Department of Research and Medical Innovation, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand. 3 Department of Public Health Nursing and Urban Health Sciences, Kuakarun Faculty of Nursing, Navamindradhiraj University, Bangkok 10300, Thailand. References Goodwin N. Understanding Integrated Care. Int J Integr Care. 2016;16(4):6. Mathur M, Wani VJ, Basu R, Manihar P, Ansari MWF, Mathur N, et al. Urban Health Resilience: Strategies for Strengthening Public Health Systems in Response to Urbanization Challenges. Indian J Community Med. 2024;49(Suppl 2):S159-s63. Cacciatore S, Mao S, Nuñez MV, Massaro C, Spadafora L, Bernardi M, et al. Urban health inequities and healthy longevity: traditional and emerging risk factors across the cities and policy implications. Aging Clin Exp Res. 2025;37(1):143. 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Benjakul N, Wongsin U, Siri S, Prutipinyo C. Factors associated with the acceptance of telemedicine services in Dusit model prototype area. Sci Rep. 2025;15(1):25311. Hedqvist A-T, Lindberg C, Hagerman H, Svensson A, Ekstedt M. Negotiating care in organizational borderlands: a grounded theory of inter-organizational collaboration in coordination of care. BMC Health Services Research. 2024;24(1):1438. Ball E, McManus M, McCoy E, Quigg Z. Implementation of Multi-agency Safeguarding Arrangements Regarding Exploitation of Young People: Aligning Policy and Practice Using Normalisation Processing Theory. Journal of Applied Youth Studies. 2024;7(4):449-68. Shortell SM, Zimmerman JE, Rousseau DM, Gillies RR, Wagner DP, Draper EA, et al. The performance of intensive care units: does good management make a difference? Med Care. 1994;32(5):508-25. Maita KC, Maniaci MJ, Haider CR, Avila FR, Torres-Guzman RA, Borna S, et al. The Impact of Digital Health Solutions on Bridging the Health Care Gap in Rural Areas: A Scoping Review. Perm J. 2024;28(3):130-43. Gobburi RK, Olawade DB, Olatunji GD, Kokori E, Aderinto N, David-Olawade AC. Telemedicine use in rural areas of the United Kingdom to improve access to healthcare facilities: A review of current evidence. Informatics and Health. 2025;2(1):41-8. Fitzpatrick PJ. Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners. Front Digit Health. 2023;5:1264780. Collins TE, Karapici A, Berlina D. Noncommunicable Diseases and Global Health Security: Scaling up Action in Humanitarian Crises for Sustainable Recovery. Ann Glob Health. 2025;91(1):27. Harakan A, Hilman YA, Karso AJ, Awaluddin A, Nurhalijah N, Muin IS, et al. Inter-agency collaboration in building urban fire resilience in Indonesia: how do metropolitan cities address it? Frontiers in Sustainable Cities. 2025;Volume 7 - 2025. Leal Filho W, Fritzen B, Salvia AL, Dinis MAP, Vasconcelos CRP. The transformative power of networking in the implementation of the Sustainable Development Goals. Discover Sustainability. 2024;5(1):380. Ispiryan A, Pakeltiene R, Ispiryan O, Giedraitis A. Fostering Organizational Sustainability Through Employee Collaboration: An Integrative Approach to Environmental, Social, and Economic Dimensions. Encyclopedia [Internet]. 2024; 4(4):[1806-26 pp.]. Kosiol J, Silvester T, Cooper H, Alford S, Fraser L. Revolutionising health and social care: innovative solutions for a brighter tomorrow – a systematic review of the literature. BMC Health Services Research. 2024;24(1):809. Chen A, Li L, Shahid W. Digital transformation as the driving force for sustainable business performance: A moderated mediation model of market-driven business model innovation and digital leadership capabilities. Heliyon. 2024;10(8):e29509. Additional Declarations No competing interests reported. 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Adapted by the authors from unpublished data of a related study on referral routes in the Dusit zone.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7691983/v1/63e8b5332f3259d3ed3491d0.png"},{"id":97902514,"identity":"54619e43-c489-49c6-abe9-a55ef33e6527","added_by":"auto","created_at":"2025-12-10 15:52:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":983172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7691983/v1/36839688-67fb-4555-be52-8d6c45c2dfe4.pdf"},{"id":97893696,"identity":"ec1c0008-340d-4996-acba-8ce0482cc669","added_by":"auto","created_at":"2025-12-10 15:30:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16371,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7691983/v1/b886a537afc430bd06ce9bd2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Lessons Learned from the Dusit Model and the Feasibility of Applying Integrated Health Services in Urban Areas: A Qualitative Study in Thailand","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIntegrated health services refer to an approach in which diverse health professionals collaborate to deliver comprehensive, person-centered care (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In urban settings, multidisciplinary teams are particularly important for ensuring high-quality care to vulnerable populations (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, integrated health services in urban contexts face persistent challenges, including socioeconomic inequities and fragmented provider networks (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Rapid urbanization further exacerbates these issues, creating barriers to equitable and culturally sensitive care delivery (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In this regard, practical models are needed to bridge gaps between public and private healthcare systems and to provide contextually appropriate interventions in complex urban environments.\u003c/p\u003e\u003cp\u003eIn Thailand, integrated health services face distinct challenges, including limited availability of public primary care facilities, a system fragmented by the predominance of private clinics, and an unequal distribution of healthcare workers (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In Bangkok, these systemic issues are compounded by barriers such as restrictions on access for migrant populations, long waiting times, and high out-of-pocket costs. Healthcare access is further influenced by multiple medical benefit schemes, such as the Universal Coverage Scheme, Social Security Scheme, and the Civil Servant Medical Benefit Scheme.\u003c/p\u003e\u003cp\u003eTo address these challenges, the Dusit Model was developed as an integrated healthcare initiative within the Dusit zone of Bangkok, encompassing the Dusit, Bang Phlat, Bang Sue, and Phra Nakhon Districts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This model integrates services across seven public and four private health centers, providing accessible, one-stop healthcare. By emphasizing coordination across providers, the Dusit Model has reduced hospital overcrowding and improved healthcare accessibility for urban populations. Building on this success, the Sai Mai District\u0026mdash;facing similar challenges, including an aging population, a growing burden of non-communicable diseases (NCDs), and resource limitations\u0026mdash;has been identified as a potential site for adaptation. Additionally, rapid urbanization, migration, and fragmented health coverage have intensified inequities, underscoring the urgent need for comprehensive reforms to strengthen urban health systems (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese issues give rise to two main research objectives: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) to identify the key factors driving the success of the Dusit Model and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) to evaluate the feasibility of applying the lessons learned from the Dusit Model to the Sai Mai District of Bangkok. Although the need for integrated urban health services is widely recognized, a significant research gap remains in developing and testing practical models to address these challenges, particularly in rapidly urbanizing contexts such as Bangkok.\u003c/p\u003e\u003cp\u003eDespite the demonstrated benefits of integrated care, there is still a lack of evidence-based frameworks (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) that explicitly address three critical challenges: overcoming fragmentation between public and private healthcare systems (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), effectively integrating migrant populations into urban healthcare networks (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and reforming complex health benefit schemes to ensure equitable access for all residents (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Existing studies have largely focused on high-income countries, leaving limited empirical evidence from middle-income urban contexts where health system fragmentation and rapid demographic transitions are most pronounced.\u003c/p\u003e\u003cp\u003eTo address this knowledge gap, the present qualitative descriptive study examines the lessons learned from the Dusit Model\u0026rsquo;s integrated health services and evaluates its feasibility for implementation in the Sai Mai District of Bangkok. By incorporating perspectives from administrators, healthcare providers, and patients, this study aims to generate contextually grounded evidence. It is anticipated that the findings will provide a practical blueprint for integrated healthcare, thereby filling a critical gap in the literature and informing policies and practices in similar urban environments, both in Thailand and internationally.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis qualitative descriptive study was conducted between May and December 2024. Ethical approval was obtained, and all participants provided informed consent prior to data collection.\u003c/p\u003e\u003cp\u003eData collection was guided by the Healthcare Ecosystem framework, which emphasizes organizational structure, roles, operational challenges, and legal/cultural constraints within Bangkok\u0026rsquo;s healthcare management system (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This framework, recognized as a valuable tool for analyzing and strengthening complex health systems (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), was applied to examine both the Dusit Model and current health services in the Sai Mai District, with particular attention to four key components: technologies, institutions, resources, and stakeholders (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy Areas\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in two locations: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the Dusit Model service areas, including Vajira Hospital, affiliated health centers, and network clinics; and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) healthcare facilities in the Sai Mai District, comprising Bhumibol Adulyadej Hospital, primary care units, and public health centers. These sites were selected to provide a comprehensive overview of the existing healthcare network and to assess its potential for expansion.\u003c/p\u003e\n\u003ch3\u003eData Collection Instruments\u003c/h3\u003e\n\u003cp\u003eThe semi-structured interview and focus group discussion guides were specifically developed for the purposes of this study, drawing upon the research objectives and the Healthcare Ecosystem framework. These instruments have not been previously published or employed in other studies. For the purpose of transparency and replicability, an English version of the instruments has been provided as Supplementary File S1 and has been cited accordingly in the Methods section of the manuscript.\u003c/p\u003e\n\u003ch3\u003eStudy Population and Recruitment\u003c/h3\u003e\n\u003cp\u003eThe study population comprised two stakeholder groups: Dusit Model stakeholders and Sai Mai District stakeholders. Each group included administrators and coordinators, healthcare providers, and patients. Participants were selected based on their diverse expertise and first-hand experience to ensure a comprehensive understanding of both the Dusit Model and its potential application in the Sai Mai District\u0026rsquo;s urban healthcare context.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDusit Model stakeholders\u003c/b\u003e. Recruitment was based on direct involvement in key components such as leadership, patient referral systems, telemedicine, and patient satisfaction programs. This group was subdivided into three categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Administrators and coordinators (DM-ADM#), selected for their strategic perspectives on scalability and operational efficiency; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Healthcare providers (DM-HCP#), chosen for their hands-on experience with telemedicine and referral systems, as well as their insights into technical and logistical challenges; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Patients (DM-PT#), included for their experiences and satisfaction with healthcare services under the Dusit Model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSai Mai District stakeholders\u003c/b\u003e. Recruitment was guided by the ability to evaluate the feasibility of adapting the Dusit Model to a new urban setting while addressing local challenges such as high population density and population aging. This group was subdivided into three categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Administrators and coordinators (SM-ADM#), selected for their roles in overseeing healthcare operations and their strategic perspectives on adapting the model to a different context; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Healthcare providers (SM-HCP#), chosen for their practical experience with the district\u0026rsquo;s existing healthcare infrastructure and their perspectives on the potential integration of telemedicine and referral systems; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Patients (SM-PT#), selected for their experiences with the district\u0026rsquo;s healthcare services and their views on accessibility and effectiveness.\u003c/p\u003e\u003cp\u003eFor both stakeholder groups, participants were identified through publicly available sources, including institutional emails, social media platforms, and professional networks.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003e In compliance with physical and social distancing policies, all interviews were conducted remotely via telephone or video conferencing. Prior to participation, written or verbal informed consent was obtained. Each interview was audio-recorded and lasted between 45 and 60 minutes.\u003c/p\u003e\u003cp\u003eSemi-structured interview guides were developed for three key informant groups. For administrators and coordinators, questions addressed strategic planning, network management, and policy- and leadership-related challenges and opportunities in the local healthcare system. For healthcare providers, questions focused on patient care, inter-unit collaboration, workforce capacity, and the implementation of digital health programs such as \u003cem\u003eVajira@Home, Vajira Smile, V-Refer\u003c/em\u003e, and \u003cem\u003eV-EMS\u003c/em\u003e, as well as their training needs. For patients, questions examined their service experiences, access barriers, and specific care needs, particularly among the elderly and those with chronic illnesses. The interview guide allowed flexibility for participants to reflect freely while ensuring systematic comparability across cases.\u003c/p\u003e\u003cp\u003eTo ensure comprehensive data coverage, multiple qualitative methods were employed. First, in-depth interviews with open-ended questions explored stakeholder experiences with the Dusit Model and perceptions of its feasibility in the Sai Mai District. Second, focus group discussions facilitated collective insights, addressed operational challenges, and included a SWOT (strengths, weaknesses, opportunities, and threats) analysis of the Dusit Model. Third, participant observations were conducted in healthcare settings, with attention to e-health applications and patient referral systems, to provide contextual understanding. Finally, document analysis examined policy frameworks, program documents, and patient records, contributing to data triangulation. A flexible, participant-led interview approach was adopted to create a safe environment and allow participants to guide discussions toward personally relevant issues.\u003c/p\u003e\u003cp\u003eThe data collection team included two interviewers, three research staff, and two research assistants, all of whom were trained in qualitative research. The interviewers had no prior relationship with the participants, ensuring objectivity. Training in qualitative interviewing was provided through a 60-minute workshop on best practices led by the principal investigators, supplemented by assigned readings on qualitative interviewing techniques and theory. To maintain data quality and consistency, regular debriefing sessions were held in which interviewers shared field notes and discussed emerging themes. Recruitment continued until data saturation was reached, defined as three consecutive interviews yielding no new information. All interviews were transcribed verbatim, reviewed for accuracy, de-identified, and returned to participants for verification of accuracy and privacy (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eFour instruments informed the analysis: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) in-depth interviews, using open-ended questions to explore stakeholders\u0026rsquo; understanding of the Dusit Model; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) focus groups, which generated collective insights, performed a SWOT analysis of the Dusit Model, and synthesized strategies through a TOWS Matrix; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) participant observations; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) document analyses. Themes were inductively constructed during initial coding and refined deductively through subsequent interpretation using the resilience framework (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe analytic process followed the framework of Miles and Huberman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), which consists of data organization, data display, and conclusion drawing. To ensure trustworthiness, several strategies were employed: triangulation of data sources (interviews, focus groups, and observations), member checking, and maintenance of an audit trail. Peer debriefing and iterative coding were also applied to refine themes and minimize bias, thereby enhancing the credibility of the findings.\u003c/p\u003e\u003cp\u003eWith respect to transcription and organization, researchers AC and BM read all transcripts to achieve data familiarization and produced notes to aid recall. Researcher JK then classified the data into major themes, which were further divided into key issues aligned with the study objectives. Tables were developed to categorize these themes systematically, ensuring that the data were clearly organized for analysis. Subsequently, BM, JK, and AC applied content analysis to link the categorized data with descriptive reports, thereby facilitating the interpretation of the phenomenon under study.\u003c/p\u003e\u003cp\u003eTo conclude and verify the findings, the research team jointly reviewed all data for interpretation and knowledge generation. The accuracy of interpretations was corroborated by cross-checking with informants\u0026rsquo; statements. Finally, validation was achieved through triangulation across multiple data sources, the use of diverse collection methods, and the involvement of multiple analysts.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eParticipant Demographics\u003c/p\u003e\n\u003cp\u003eIn this study, there was a total of 80 participants. The participant demographics are outlined in Table 1, while Table 2 presents an overview of the identified themes and sub-themes. Specifically, Themes I\u0026ndash;IV analyze the success factors of the Dusit Model\u0026rsquo;s integrated health services, while Themes V\u0026ndash;VI determine the feasibility of applying the lessons learned from the Dusit Model to the Sai Mai District.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Participant Demographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCode\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup 1: Dusit Model stakeholders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eAdministrators and coordinators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eDM-ADM#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eHealthcare providers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eDM-HCP#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003ePatients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eDM-PT#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup 2:\u0026nbsp;Sai Mai District stakeholders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eAdministrators and coordinators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eSM-ADM#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eHealthcare providers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eSM-HCP#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003ePatients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eSM-PT#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 622px;\"\u003e\n \u003cp\u003eTable 2. Overview of the Identified Themes and Sub-themes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 328px;\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 622px;\"\u003e\n \u003cp\u003ePart 1:\u0026nbsp;To analyze the success factors of the Dusit Model\u0026rsquo;s integrated health services\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 28px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 300px;\"\u003e\n \u003cp\u003eGeneral context, health situation, access to healthcare services, and challenges identified in the Dusit District\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eGeographical and demographic context\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eHealthcare challenges and utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eHealthcare service access\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eOperational challenges\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 300px;\"\u003e\n \u003cp\u003eFormation of the Dusit Model task force and network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eOrganizational structure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eOutcomes of the network establishment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 28px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 300px;\"\u003e\n \u003cp\u003eOperational strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cem\u003eVajira@Home\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cem\u003eVajira Smile\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cem\u003eV-Refer\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cem\u003eV-EMS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 300px;\"\u003e\n \u003cp\u003eSWOT analysis and TOWS Matrix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 622px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 622px;\"\u003e\n \u003cp\u003ePart 2: To Determine the Feasibility of Applying the Lessons Learned from the Dusit Model to the Sai Mai District\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 28px;\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 300px;\"\u003e\n \u003cp\u003eFeasibility of adapting the Dusit Model to the Sai Mai District\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eAlignment with the Sai Mai District\u0026rsquo;s healthcare landscape\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eDemographic compatibility with the model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eHealthcare workforce readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eHealth network capacity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eAddressing urban healthcare challenges\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003ePolicy and leadership support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 28px;\"\u003e\n \u003cp\u003eVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 300px;\"\u003e\n \u003cp\u003eKey considerations for implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eHuman resource development\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eStrengthening interagency collaboration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eAddressing unregistered populations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003eBudgetary considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePart 1: To Analyze the Success Factors of the Dusit Model\u0026rsquo;s Integrated Health Services\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheme I\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGeographical and demographic context:\u0026nbsp;Situated on the Chao Phraya River, the Dusit District spans 10.66 square kilometers and includes a population of 75,538. Its combination of dense residential zones, businesses, and government offices creates a diverse population, including the elderly, working-age adults, children, and unregistered residents, all with complex healthcare and social needs.\u003c/p\u003e\n\u003cp\u003eHealthcare challenges and utilization:\u0026nbsp;The\u0026nbsp;Dusit District includes major healthcare issues, especially with its aging population and the prevalence of NCDs. It also leads the region in outpatient service use (35%), followed by the Bang Sue, Bang Phlat, and Phra Nakhon Districts. As for inpatient care, the Dusit District is second (32%), just behind the Bang Sue District. The most common health problems for outpatients are musculoskeletal issues, diabetes, and hypertension, while pneumonia and digestive diseases are the most common for inpatients.\u003c/p\u003e\n\u003cp\u003eHealthcare service access: The Dusit Model connects Vajira Hospital, public health centers, and \u0026ldquo;Warm Clinics\u0026rdquo; to offer basic through advanced healthcare. This system also uses various technologies such as \u003cem\u003eVajira@Home\u003c/em\u003e for at-home consultations and medication delivery and \u003cem\u003eV-Refer\u003c/em\u003e to safely and quickly transfer patients to Vajira Hospital when they require more specialized care. This integration ensures that patients can receive basic care at local clinics and be easily referred to the hospital for more serious conditions.\u003c/p\u003e\n\u003cp\u003eOperational challenges: Vajira Hospital struggles with overcrowding and excessive wait times. Patients also face delays due to the necessary paperwork to transfer their healthcare rights. Meanwhile, local health centers and Warm Clinics are short-staffed, limiting their ability to effectively serve the community. In addition, the district\u0026rsquo;s unregistered population makes it difficult to plan for resources, while vulnerable groups (e.g., the elderly) have trouble using telemedicine services such as \u003cem\u003eVajira@Home\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheme II\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Dusit Model was created to unite healthcare providers and improve services in the city. This network, which includes the Faculty of Medicine Vajira Hospital, public health centers, and Warm Clinics, aims to build a comprehensive and sustainable healthcare system that meets the needs of everyone in the Dusit District.\u003c/p\u003e\n\u003cp\u003eOrganizational structure: The Dusit Model\u0026rsquo;s healthcare network is well-coordinated, with its members meeting every month to discuss current progress, ongoing challenges, and future plans, including how to manage chronic illnesses and improve the referral system. According to one network manager, \u003cem\u003e\u0026ldquo;These meetings help all the network\u003c/em\u003e\u003cem\u003e\u0026rsquo;s\u003c/em\u003e\u003cem\u003e\u0026nbsp;units coordinate and immediately exchange solutions to problems\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(DM-ADM01)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e This network also uses a group messaging platform (\u003cem\u003eLine\u003c/em\u003e) for quick updates and emergencies. This platform has been essential for making timely patient referrals and managing medical supplies. As stated by one frontline staff member, \u003cem\u003e\u0026ldquo;The\u0026nbsp;\u003c/em\u003e\u003cem\u003eLine\u003c/em\u003e\u003cem\u003e\u0026nbsp;group helps them address issues promptly and builds trust within the team\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(DM-HCP03)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Additionally, through the \u0026ldquo;Friend Visits Friend\u0026rdquo; initiative, healthcare agencies can learn from one another. In this case, the staff from Vajira Hospital and public health centers visit other locations to share their best ideas and practices. According to one nurse, \u0026ldquo;These visits provide practical insights that we can bring back to improve our services\u0026rdquo; (DM-HCP04).\u003c/p\u003e\n\u003cp\u003eOutcomes of the network establishment: This network has significantly improved service integration. For example, the \u003cem\u003eV-Refer\u003c/em\u003e system has cut patient transfer times by 30%. In this regard, one secondary care physician stated, \u0026ldquo;\u003cem\u003eV-Refer\u003c/em\u003e\u003cem\u003e\u0026nbsp;r\u003c/em\u003e\u003cem\u003eeduces delays and increases patient satisfaction\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e(DM-HCP01)\u003c/em\u003e\u003cem\u003e,\u003c/em\u003e while one patient who used the system added, \u0026ldquo;\u003cem\u003eBefore this system, I had to wait hours for a transfer, but now I feel safer and more confident knowing my case is handled faster\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(DM-PT03)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Meanwhile, capacity-building initiatives, such as training programs and knowledge exchanges, have improved staff competence in handling referrals and managing chronic conditions. As one primary care staff member reflected, \u003cem\u003e\u0026ldquo;The training has increased our confidence in managing referrals and chronic patients\u0026rdquo; (DM-HCP08)\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eSimilarly, one chronic disease patient stated, \u003cem\u003e\u0026ldquo;I feel more cared for because the staff can now explain my treatment options clearly and manage my case more effectively\u0026rdquo; (DM-PT06).\u003c/em\u003e Moreover, the \u0026ldquo;Friend Visits Friend\u0026rdquo; program has built stronger professional bonds within the network. According to one manager, \u003cem\u003e\u0026ldquo;It brought us closer together, building trust that allows us to resolve issues more quickly\u0026rdquo; (DM-ADM02).\u003c/em\u003e Likewise, one patient stated, \u003cem\u003e\u0026ldquo;Seeing different teams working together for my health made me trust the system more\u0026rdquo; (DM-PT07).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheme III\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Dusit Model improves healthcare efficiency and accessibility through four key sub-programs:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cem\u003eVajira@Home\u003c/em\u003e is a telemedicine program that allows patients to have doctor consultations and receive care from home, thus reducing hospital overcrowding. As one physician noted, \u003cem\u003e\u0026ldquo;The system is designed to support patients who cannot travel, but still require comprehensive care\u0026rdquo; (DM-HCP01).\u003c/em\u003e Similarly, one patient stated, \u003cem\u003e\u0026ldquo;Having consultations from home has made my treatment easier and more comfortable. I no longer need to wait at the hospital\u0026rdquo; (DM-PT03).\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eVajira Smile\u003c/em\u003e aims to improve the patient experience by training staff to be more welcoming. As one staff member explained, \u003cem\u003e\u0026ldquo;We strive to create an atmosphere where patients feel cared for with attentiveness and friendliness\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(DM-HCP05).\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn this regard, one patient stated, \u003cem\u003e\u0026ldquo;The staff are more understanding and approachable now, which makes the hospital feel less intimidating\u0026rdquo; (DM-PT07).\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eV-Refer\u003c/em\u003e is a referral system that makes patient transfers quicker and safer. As one physician involved in the program noted, \u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eV-Refer\u003c/em\u003e\u003cem\u003e\u0026nbsp;i\u003c/em\u003e\u003cem\u003emproves communication and accelerates patient care\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(DM-HCP05)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Similarly, one patient stated, \u003cem\u003e\u0026ldquo;I was transferred to the hospital much faster than before, and I felt reassured throughout the process\u0026rdquo; (DM-PT09).\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eV-EMS\u003c/em\u003e is an emergency management system that uses real-time data for faster, more effective responses. According to one emergency responder, \u003cem\u003e\u0026ldquo;The system enhances efficiency and reduces errors\u0026rdquo; (DM-HCP04).\u003c/em\u003e Moreover, one patient who used the service felt safe because the team was \u003cem\u003e\u0026ldquo;well-prepared\u0026rdquo; and \u0026ldquo;had all the information that they needed beforehand\u0026rdquo; (DM-PT05).\u003c/em\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cem\u003eTheme IV\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBased on a SWOT analysis\u0026nbsp;(Table 3), the Dusit Model includes strong points such as integrated care, advanced technologies (e.g., \u003cem\u003eV-Refer\u003c/em\u003e, \u003cem\u003eVajira@Home\u003c/em\u003e), and high patient satisfaction. Conversely, it faces weaknesses such as staff shortages and a population that is not fully aware of telemedicine. Meanwhile, it can take advantage of opportunities from national policies and new technologies, but it must also deal with threats such as complex entitlement systems and tight budgets.\u003c/p\u003e\n\u003cp\u003eAs for the TOWS Matrix analysis\u0026nbsp;(Table 4), it turns the SWOT analysis into a practical roadmap by using the model\u0026rsquo;s strengths to seize opportunities such as expanding telemedicine services to align with national policies and forming partnerships with private companies. It also provides strategies to counter threats such as improving coordination among agencies and simplifying the referral process. Regarding weaknesses, the matrix recommends training for vulnerable groups by using different technologies and improving staffing in primary care.\u003c/p\u003e\n\u003cp\u003eOverall, Tables 3 and 4 offer a comprehensive picture of the Dusit Model, highlighting its potential to improve urban healthcare and providing a roadmap for its future development and expansion.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eOpportunities and Challenges for Urban Healthcare Integration, Based on a SWOT Analysis of the Dusit Model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive Aspects (Strengths \u0026amp; Opportunities)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChallenges (Weaknesses \u0026amp; Threats)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternal Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStrengths\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeaknesses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Integration of health services across primary, secondary, and tertiary levels, exemplified by the \u003cem\u003eV-Refer\u003c/em\u003e system, which reduces patient transfer times by 30%.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Insufficient staffing levels in primary healthcare facilities, limiting the ability to provide comprehensive care.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Utilization of advanced technologies, such as \u003cem\u003eVajira@Home\u003c/em\u003e and \u003cem\u003eV-EMS\u003c/em\u003e, improves healthcare accessibility and alleviates hospital overcrowding.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Limited public understanding of technological solutions, especially among older populations, impeding telemedicine usage.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- High patient satisfaction with services, as demonstrated by a 4.8/5 satisfaction rating for the \u003cem\u003eVajira Smile\u003c/em\u003e initiative.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Complexities in referral processes due to incomplete/fragmented patient information in the database.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Effective inter-agency collaboration supported by regular meetings and initiatives, fostering cohesive teamwork.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExternal Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOpportunities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- National policies promoting health zones provide opportunities to replicate successful models, such as the Dusit Model, in other urban areas.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Challenges in navigating complex healthcare entitlement systems, which create barriers to service access for patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Expansion of health technology innovations, including telemedicine and advanced data management, to improve service delivery.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Budgetary and resource limitations present obstacles to scaling the model to other urban areas.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Opportunities for collaboration with private sector entities to enhance resource allocation and workforce training.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 276px;\"\u003e\n \u003cp\u003e- Fragmentation and inefficiencies in urban healthcare management due to overlapping responsibilities among multiple agencies.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eStrategic Insights for Urban Healthcare Development, Based on a TOWS Matrix Analysis of the Dusit Model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive Aspects (Strengths \u0026amp; Opportunities)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChallenges (Weaknesses \u0026amp; Threats)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternal Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStrengths\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeaknesses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- Integration of health services across primary, secondary, and tertiary levels, exemplified by the \u003cem\u003eV-Refer\u003c/em\u003e system, which reduces patient transfer times by 30%.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Insufficient staffing levels in primary healthcare facilities, limiting the ability to provide comprehensive care.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- Utilization of advanced technologies, such as \u003cem\u003eVajira@Home\u003c/em\u003e and \u003cem\u003eV-EMS\u003c/em\u003e, enhances healthcare accessibility and alleviates hospital overcrowding.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Limited public understanding of technological solutions, particularly among older populations, impeding telemedicine usage.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- High patient satisfaction with services, as demonstrated by a 4.8/5 satisfaction rating for the \u003cem\u003eVajira Smile\u003c/em\u003e initiative.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Complexities in referral processes due to incomplete or fragmented patient information within the database.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- Effective inter-agency collaboration supported by regular meetings and initiatives, fostering cohesive teamwork.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExternal Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOpportunities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- National policies promoting health zones provide opportunities to replicate successful models, such as the Dusit Model, in other urban areas.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Challenges in navigating complex healthcare entitlement systems, which create barriers to service access for patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- Expansion of health technology innovations, including telemedicine and advanced data management, to improve service delivery.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Budgetary and resource limitations present obstacles to scaling the model to other urban areas.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e- Opportunities for collaboration with private sector entities to enhance resource allocation and workforce training.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e- Fragmentation and inefficiencies in urban healthcare management due to overlapping responsibilities among multiple agencies.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePart 2:\u0026nbsp;To Determine the Feasibility of Applying the Lessons Learned from the Dusit Model to the Sai Mai District\u003c/p\u003e\n\u003cp\u003eThe Dusit Model was evaluated for its potential in the Sai Mai District. In this regard, a feasibility study, including interviews with key stakeholders, identified two main areas: 1) The feasibility of adapting the model; and 2) The key considerations for putting it into practice.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheme V\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Dusit Model is well-suited for the Sai Mai District because it matches the area\u0026rsquo;s health needs and ability to use new technologies. This section examines the feasibility of this model and how it can improve healthcare in this district.\u003c/p\u003e\n\u003cp\u003eAlignment with the Sai Mai District\u0026rsquo;s healthcare landscape:\u0026nbsp;The Sai Mai District\u0026rsquo;s healthcare facilities are well-suited for adopting the Dusit Model. As one district administrator stated,\u0026nbsp;\u003cem\u003e\u0026ldquo;The Sai Mai District\u0026rsquo;s existing facilities are well-positioned to adopt an integrated system, such as the Dusit Model, ensuring comprehensive and efficient healthcare delivery\u0026rdquo; (SM-ADM01).\u003c/em\u003e Similarly, one public health planner added,\u0026nbsp;\u003cem\u003e\u0026ldquo;The variety of facilities in the Sai Mai District makes it flexible enough to adopt key parts of the model such as its referral and telemedicine systems\u0026rdquo; (SM-PT01).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDemographic compatibility with the model:\u0026nbsp;The Sai Mai District\u0026rsquo;s population profile, with its dense communities and large elderly population, is a good match for the Dusit Model. According to one public health nurse,\u0026nbsp;\u003cem\u003e\u0026ldquo;The similarities make this model highly applicable, especially for addressing the needs of the aging population\u0026rdquo; (SM-HCP01).\u003c/em\u003e In this regard, one elderly care specialist added:\u0026nbsp;\u003cem\u003e\u0026ldquo;Since more elderly residents need long-term care, a structured model is essential for improving healthcare delivery\u0026rdquo; (SM-HCP02).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHealthcare workforce readiness:\u0026nbsp;The Sai Mai District\u0026rsquo;s healthcare workers are adaptable, but they need more training to get the most out of the digital tools. In this case, one local physician noted,\u0026nbsp;\u003cem\u003e\u0026ldquo;The staff are familiar with technology, but targeted training will improve their ability to effectively utilize systems such as V-Refer\u0026rdquo; (SM-HCP03).\u0026nbsp;\u003c/em\u003eMeanwhile, one nurse manager added,\u0026nbsp;\u003cem\u003e\u0026ldquo;While the team is motivated to embrace new technologies, hands-on training is essential for a smooth implementation\u0026rdquo; (SM-HCP04).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHealth network capacity:\u0026nbsp;The Sai Mai District\u0026rsquo;s public health centers are in key locations to coordinate care. According to one health center manager,\u0026nbsp;\u003cem\u003e\u0026ldquo;The existing healthcare network in the Sai Mai District is well-prepared for the integration of systems, such as e-Referral, enabling smoother patient management\u0026rdquo; (SM-HCM01).\u0026nbsp;\u003c/em\u003eAnother manager added,\u0026nbsp;\u003cem\u003e\u0026ldquo;Strong collaboration across facilities ensures that the Dusit Model can be implemented with minimal disruption to existing services\u0026rdquo; (SM-HCM02).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAddressing urban healthcare challenges: With the increasing prevalence of NCDs and an aging population, the Sai Mai District is facing growing pressure on its healthcare services. As one public health officer observed: \u003cem\u003e\u0026ldquo;The rising patient numbers underline the urgency of adopting structured systems, such as the Dusit Model, to streamline care delivery and reduce hospital congestion\u0026rdquo; (SM-HCP03).\u003c/em\u003e Similarly, one patient advocate emphasized: \u003cem\u003e\u0026ldquo;The current system can be challenging for patients to navigate, so integrating the Dusit Model will provide clarity and improve access to care\u0026rdquo; (SM-PT02).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePolicy and leadership support: Supportive urban health zone policies and proactive local leaders can make it easier to adopt the Dusit Model in the Sai Mai District. As one district administrator explained, \u003cem\u003e\u0026ldquo;Policies promoting urban health zones offer a strong foundation for replicating successful frameworks such as the Dusit Model\u0026rdquo; (SM-ADM02).\u003c/em\u003e Moreover, one policy advisor added, \u003cem\u003e\u0026ldquo;The commitment from local leaders will play a pivotal role in effectively scaling the Dusit Model\u0026rdquo; (SM-HCP06).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheme VI\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn order for the Dusit Model to be successfully implemented in the Sai Mai District, several key areas must be addressed, including: improving human resources with targeted training; strengthening collaboration between agencies; providing fair access to healthcare for unregistered residents; and securing sufficient funding.\u003c/p\u003e\n\u003cp\u003eHuman resource development:\u0026nbsp;Investing in training is vital so that healthcare staff can effectively use technologies and manage patient care. As one nurse stated:\u0026nbsp;\u003cem\u003e\u0026ldquo;Training helps staff handle referral systems efficiently and minimize errors\u0026rdquo; (SM-HCP05).\u0026nbsp;\u003c/em\u003eIn this regard, one health trainer added,\u0026nbsp;\u003cem\u003e\u0026ldquo;Focused training on tools, such as V-Refer, can increase staff confidence and efficiency, which is key for a smooth transition to the new model\u0026rdquo; (SM-HCP06).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStrengthening interagency collaboration:\u0026nbsp;Effective collaboration between hospitals, public health centers, and other groups is important for integrated services. As one health center manager stated, \u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eStrong partnerships within the healthcare network are essential for optimizing patient care and referral processes\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;(SM-HCM03)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Meanwhile,\u0026nbsp;one\u0026nbsp;hospital administrator added,\u0026nbsp;\u003cem\u003e\u0026ldquo;Coordinating efforts will be critical for overcoming operational challenges and ensuring the model\u0026rsquo;s success\u0026rdquo; (SM-ADM03).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAddressing unregistered populations:\u0026nbsp;The large number of unregistered residents in the Sai Mai District creates challenges for providing equal healthcare to all individuals. As one district administrator emphasized,\u0026nbsp;\u003cem\u003e\u0026ldquo;Incorporating unregistered residents into the healthcare system is vital to achieving inclusivity and reducing disparities\u0026rsquo; (SM-ADM04).\u003c/em\u003e Similarly,\u0026nbsp;one\u0026nbsp;community health worker stated,\u0026nbsp;\u003cem\u003e\u0026ldquo;Addressing the barriers that this group faces will improve healthcare outcomes across the district\u0026rdquo; (SM-HCP07).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBudgetary considerations:\u0026nbsp;To ensure that the model is sustainable, it is essential to secure adequate funding for technology and workforce development. As one project planner explained,\u0026nbsp;\u003cem\u003e\u0026ldquo;Allocating resources effectively is pivotal for the model\u0026rsquo;s success\u0026rdquo; (SM-PT03).\u0026nbsp;\u003c/em\u003eIn this regard,\u0026nbsp;one\u0026nbsp;financial officer noted,\u0026nbsp;\u003cem\u003e\u0026ldquo;Budgeting for both technology and staff is crucial for the model\u0026rsquo;s long-term viability\u0026rdquo; (SM-ADM05).\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides an in-depth understanding of the success factors underpinning the Dusit Model\u0026rsquo;s integrated health services and evaluates its feasibility for implementation in the Sai Mai District. Insights from stakeholders highlight the changes required at the urban level to reduce challenges and strengthen policy implementation. These findings can inform urban health systems seeking to address major public health concerns, including the rising prevalence of non-communicable diseases (NCDs), limited access to healthy food, and harmful environmental exposures.\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003ePart 1: To Analyze the Success Factors of the Dusit Model\u0026rsquo;s Integrated Health Services\u003c/h2\u003e\u003cp\u003eThe Dusit Model demonstrates strong potential as a framework for integrated healthcare in dense urban populations, encompassing children, working-age adults, the elderly, and unregistered residents. Comparable evidence suggests that enabling healthcare access for aging populations requires attention to social and psychological factors, such as self-efficacy and social support, in addition to clinical services, as these factors can mitigate barriers such as geographic isolation (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, underserved populations should have universal access to preventive and outpatient services, regardless of immigration status (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e The findings indicate that the Dusit Model leverages advanced technologies to enhance efficiency and continuity of care. For example, Vajira@Home supports remote consultations to relieve hospital overcrowding, while V-Refer facilitates patient transfers between facilities. Telehealth also enables case management by transmitting information before a patient is transferred to an urban center and serves as an efficient method for follow-up visits, thereby strengthening continuity of care (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Consistent with this, previous studies report that triage by physicians and the placement of primary care clinicians in emergency departments improve patient flow (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Thus, the Dusit Model provides a clear operational blueprint for improving urban healthcare efficiency.\u003c/p\u003e\u003cp\u003eThe Dusit Model also emphasizes collaboration through a network of hospitals, public health centers, and Warm Clinics, aligning with earlier findings (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Inter-agency meetings and communication platforms (e.g., Line) ensure seamless coordination, while initiatives such as Friend Visits Friend promote professional development and mutual trust through shared learning. Collaborative approaches have been shown to prevent errors, increase efficiency, and improve effectiveness in health systems worldwide (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). These findings confirm that strong networks are critical to high-quality, integrated healthcare delivery.\u003c/p\u003e\u003cp\u003eDespite its strengths, the Dusit Model also faces challenges. These include workforce shortages in primary care, which constrain service capacity, and low digital literacy among older adults, which hinders telemedicine use. Similar barriers have been identified in rural communities, where limited digital skills impede access to e-health services (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Without targeted education and training, older patients may struggle to use these platforms effectively. Although telemedicine use increased during the COVID-19 pandemic, sustained efforts are needed to improve digital literacy and infrastructure for equitable access (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Targeted interventions, such as specialized staff training, digital literacy initiatives, and streamlined administrative processes, are therefore essential. Digital tools, including mobile applications and telemedicine platforms, can simultaneously improve health literacy and outcomes (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Overall, the Dusit Model integrates services across levels of care, making it both a scalable and sustainable blueprint for urban healthcare systems.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePart 2: To Determine the Feasibility of Applying the Lessons Learned From the Dusit Model to the Sai Mai District\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study found that the Sai Mai District\u0026rsquo;s healthcare network, including public health centers, hospitals, and clinics, is well-suited for integrating advanced systems such as V-Refer and Vajira@Home. These platforms can improve patient care through streamlined referrals and remote services. The district\u0026rsquo;s demographics, particularly its dense and aging population, closely mirror those of the Dusit District, making this model highly relevant for addressing the healthcare needs of older adults and managing the growing burden of NCDs. Previous studies have also suggested that engaging the private sector can leverage its expertise, technologies, and financial resources for health initiatives, especially for NCDs and related emergencies (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHealthcare staff in the Sai Mai District are ready to adopt digital tools, but additional training is necessary to optimize their use. Tailored training programs for platforms such as V-Refer could enhance staff confidence and efficiency, ensuring seamless integration of the Dusit Model. In addition, the district\u0026rsquo;s public health centers are strategically positioned to serve as coordination hubs between primary and secondary care providers, fostering a smooth implementation process. Related research has shown that strong interagency networks are vital for sustainable development, as they pool resources and diverse perspectives to navigate complex challenges (\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e Policies supporting urban health zones and the active involvement of local leaders can further strengthen Sai Mai\u0026rsquo;s readiness to adopt the Dusit Model. This framework provides a pathway for integrating technology-driven healthcare solutions while ensuring long-term scalability and sustainability. Prior research underscores that stakeholder alignment, adherence to ethical standards, and innovation are essential for sustainable model adoption (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Accordingly, while the Sai Mai District demonstrates strong potential to apply the Dusit Model, successful implementation will depend on prioritizing digital literacy training for staff and leveraging public health centers as coordination hubs.\u003c/p\u003e\u003cp\u003eThis study has several strengths. First, it adopted a multi-stakeholder perspective, incorporating the views of administrators, healthcare providers, and patients. This triangulation of perspectives enhances the validity of the findings and provides a holistic view of the Dusit Model\u0026rsquo;s effectiveness and feasibility. Second, the use of multiple data sources including in-depth interviews, focus groups, participant observations, and document analyses strengthened the rigor of the qualitative approach and allowed for comprehensive data triangulation. Third, the study contributes empirical insights from an urban context in a middle-income country, where evidence on integrated health services remains limited. This adds value to the global discourse on health system reform by demonstrating how locally developed models can be adapted and scaled in other rapidly urbanizing settings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eChallenges and Limitations\u003c/h2\u003e\u003cp\u003eSuccessful implementation of the Dusit Model requires addressing several challenges. Healthcare staff need comprehensive training to strengthen digital literacy and confidence in using platforms such as Vajira@Home and V-Refer. Improved collaboration among public health centers, hospitals, and other stakeholders is also necessary to reduce duplication and service gaps. In addition, the inclusion of unregistered populations in healthcare planning is vital to reduce inequities, while stable budget allocation and long-term financial strategies are required to support workforce development and sustain digital health initiatives.\u003c/p\u003e\u003cp\u003eThis study relied primarily on the perspectives of frontline healthcare workers, excluding urban-level policymakers whose insights could clarify upstream barriers and policy priorities. Recruitment also occurred during a period of high workload, resulting in a relatively small sample size and limited representation from remote centers and allied health professionals. Although these factors may restrict generalizability, the findings remain relevant to similar urban contexts given their consistency with existing literature. Future studies should incorporate policymakers and employ larger, more diverse samples, including quantitative surveys, to validate and extend these results.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that the Dusit Model\u0026rsquo;s success derives from its strategic use of digital technologies and inter-organizational collaboration to manage healthcare for diverse urban populations. The findings also indicate that the Sai Mai District is well-positioned to adopt this framework, provided that targeted staff training is conducted and public health centers are strengthened as coordination hubs.\u003c/p\u003e\u003cp\u003eMore importantly, the study addresses a critical research gap by providing empirical evidence on how integrated health service models can be adapted in rapidly urbanizing, middle-income contexts. Unlike earlier research, which has offered limited practical guidance for overcoming system fragmentation, integrating marginalized populations, or aligning complex benefit schemes, this study identifies both the success factors and the contextual requirements for replication. By doing so, it contributes to the evidence base for designing scalable and sustainable integrated healthcare solutions in Bangkok and other comparable urban environments.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNCDs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enon-communicable diseases\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDM-ADM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDusit Model-Administrators and coordinators\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDM-HCP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDusit Model-Healthcare providers\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDM-PT)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDusit Model-Patients\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSM-ADM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSai Mai-Administrators and coordinators\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSM-HCP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSai Mai-Healthcare providers\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSM-PT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSai Mai-Patients\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eSupplementary Information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary File S1.\u003c/strong\u003e The full English language version of the questionnaire on interview \u0026amp; Focus group discussion\u003c/p\u003e\n\u003cp\u003eStatements and declarations\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand (Approval No. COA 078/2567). The participants were informed that they could leave the study at any time without justifying their decision, and data were not saved until the participants finished the questionnaire and confirmed submitting their answers. To maximize anonymity, no identifying personal data were collected from the participants.\u003c/p\u003e\n\u003cp\u003eAll measurements were conducted subsequent to the participants completion of the questionnaire and provision of written consent. All participants have been performed in accordance with the Declaration of Helsinki and have been approved by an appropriate ethics committee. The Institutional Review Board of the Faculty of Medicine at Vajira Hospital complies fully with international guidelines for human research protection, such as the Declaration of Helsinki, The Belmont Report, the CIOMS Guideline, and the International Conference on Harmonization in Good Clinical Practice (ICH-GCP). The study was conducted in accordance with the Declaration of Helsinki and received approval from the appropriate ethics committee.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are described in the protocol titled “Developing Innovative, Integrated Health Service Models to Address Urban Challenges” (Approval No. COA 078/2567). These datasets are not publicly available due to institutional restrictions but can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eIn addition, Figure 1. Dusit zone including four districts in Bangkok, Thailand was adapted from data used in a previous study, “Effect of Dusit zone referral routes on patient satisfaction: A cross-sectional study in Bangkok, Thailand” (manuscript under review).\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest, Not Applicable.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Program Management Unit on Area-based Development (PMU A), Ministry of Higher Education, Science, Research, and Innovation; (grant number: \u0026nbsp;A13F680052).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors’ contributions\u003c/p\u003e\n\u003cp\u003eBasmon Manomaipiboon:\u0026nbsp;Conceptualization, Methodology, Project administration, Data curation, Formal analysis, Investigation, Validation, Visualization, Supervision, Writing – original draft, Writing – review \u0026amp; editing, Submission.\u003c/p\u003e\n\u003cp\u003eJadsada Kunno:\u0026nbsp;Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – original draft, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAraya Chiangkhong:\u0026nbsp;Conceptualization, Methodology, Project administration, Data curation, Formal analysis, Investigation, Validation, Visualization, Supervision, Writing – original draft, Writing – review \u0026amp; editing, Submission.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Faculty of Medicine Vajira Hospital and Navamindradhiraj University, Bangkok, Thailand, for providing full support for the article processing charges and English language editing of this manuscript. We also gratefully acknowledge the collaboration of healthcare facilities in the Sai Mai District, including Bhumibol Adulyadej Hospital, primary care units, and public health centers. This work was funded by the Program Management Unit on Area-based Development (PMU A), Ministry of Higher Education, Science, Research, and Innovation, Thailand (Grant No. A13F680052).\u003c/p\u003e\n\u003cp\u003eAuthors’ information\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Urban Medicine, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Research and Medical Innovation, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of Public Health Nursing and Urban Health Sciences, Kuakarun Faculty of Nursing, Navamindradhiraj University, Bangkok 10300, Thailand.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGoodwin N. Understanding Integrated Care. Int J Integr Care. 2016;16(4):6.\u003c/li\u003e\n\u003cli\u003eMathur M, Wani VJ, Basu R, Manihar P, Ansari MWF, Mathur N, et al. Urban Health Resilience: Strategies for Strengthening Public Health Systems in Response to Urbanization Challenges. Indian J Community Med. 2024;49(Suppl 2):S159-s63.\u003c/li\u003e\n\u003cli\u003eCacciatore S, Mao S, Nu\u0026ntilde;ez MV, Massaro C, Spadafora L, Bernardi M, et al. Urban health inequities and healthy longevity: traditional and emerging risk factors across the cities and policy implications. Aging Clin Exp Res. 2025;37(1):143.\u003c/li\u003e\n\u003cli\u003eRao KD, Bairwa M, Mehta A, Hyat S, Ahmed R, Rajapaksa L, et al. Improving urban health through primary health care in south Asia. The Lancet Global Health. 2024;12(10):e1720-e9.\u003c/li\u003e\n\u003cli\u003eKunno J LT, Manomaipiboon B, Onklin I, Ong-artborirak P, Krainara P, Chaichana T, Gregory Robson M. The Urban Health Themes and Urban Factors Associated with Health: A Brief Review. 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Rethinking Integrated Care: A Systematic Hermeneutic Review of the Literature on Integrated Care Strategies and Concepts. Milbank Q. 2020;98(2):446-92.\u003c/li\u003e\n\u003cli\u003eHazarika R, Purdy S. Integrated care: demonstrating value and valuing patients. Future Hosp J. 2015;2(2):132-6.\u003c/li\u003e\n\u003cli\u003eLitchfield I, Kingston B, Narga D, Turner A. The move towards integrated care: Lessons learnt from managing patients with multiple morbidities in the UK. Health Policy. 2022;126(8):777-85.\u003c/li\u003e\n\u003cli\u003eKhatri RB, Endalamaw A, Erku D, Wolka E, Nigatu F, Zewdie A, et al. Enablers and barriers of community health programs for improved equity and universal coverage of primary health care services: A scoping review. BMC Prim Care. 2024;25(1):385.\u003c/li\u003e\n\u003cli\u003eGatome-Munyua A, Sparkes S, Mtei G, Sabignoso M, Soewondo P, Yameogo P, et al. Reducing fragmentation of primary healthcare financing for more equitable, people-centred primary healthcare. BMJ Global Health. 2025;10(1):e015088.\u003c/li\u003e\n\u003cli\u003eWang Y, Xiao C, Zheng Y, Liu Z, Jiang Z, Li Y. Shaping local identity through public health: the role of social integration among new-generation rural migrants in urban China. BMC Public Health. 2025;25(1):2643.\u003c/li\u003e\n\u003cli\u003eGhiasi K, Mosadeghrad AM, Dargahi H, Jaafaripooyan E, Abbasi M. Strategies for improving migrant health in Iran: a realist review. Globalization and Health. 2025;21(1):42.\u003c/li\u003e\n\u003cli\u003eLangat EC, Ward PR, Gesesew H, Mwanri L. From past to present: tracing Africa\u0026apos;s path to universal health coverage. Front Public Health. 2025;13:1540006.\u003c/li\u003e\n\u003cli\u003eCuevas Barron G, Koonin J, Akselrod S, Fogstad H, Karema C, Ditiu L, et al. Universal health coverage is a matter of equity, rights, and justice. The Lancet Global Health. 2023;11(9):e1335-e6.\u003c/li\u003e\n\u003cli\u003eLeslie HM, Basurto X, Nenadovic M, Sievanen L, Cavanaugh KC, Cota-Nieto JJ, et al. Operationalizing the social-ecological systems framework to assess sustainability. Proceedings of the National Academy of Sciences. 2015;112(19):5979-84.\u003c/li\u003e\n\u003cli\u003eViswanadham N. Ecosystem model for healthcare platform. Sādhanā. 2021;46(4):188.\u003c/li\u003e\n\u003cli\u003eMiles MB, Huberman AM, Saldana J. Qualitative Data Analysis: A Methods Sourcebook: SAGE Publications; 2013.\u003c/li\u003e\n\u003cli\u003eAsante D, McLachlan CS, Pickles D, Isaac V. Understanding Unmet Care Needs of Rural Older Adults with Chronic Health Conditions: A Qualitative Study. Int J Environ Res Public Health. 2023;20(4).\u003c/li\u003e\n\u003cli\u003eOlazagasti C, Duma N. Cancer Care for All? Tales of Caring for Undocumented Patients with Cancer. Oncologist. 2020;25(7):552-4.\u003c/li\u003e\n\u003cli\u003eGagnon M-P, Duplantie J, Fortin J-P, Landry R. Implementing telehealth to support medical practice in rural/remote regions: what are the conditions for success? Implementation Science. 2006;1(1):18.\u003c/li\u003e\n\u003cli\u003eJarvis PR. Improving emergency department patient flow. Clin Exp Emerg Med. 2016;3(2):63-8.\u003c/li\u003e\n\u003cli\u003eBenjakul N, Wongsin U, Siri S, Prutipinyo C. Factors associated with the acceptance of telemedicine services in Dusit model prototype area. Sci Rep. 2025;15(1):25311.\u003c/li\u003e\n\u003cli\u003eHedqvist A-T, Lindberg C, Hagerman H, Svensson A, Ekstedt M. Negotiating care in organizational borderlands: a grounded theory of inter-organizational collaboration in coordination of care. BMC Health Services Research. 2024;24(1):1438.\u003c/li\u003e\n\u003cli\u003eBall E, McManus M, McCoy E, Quigg Z. 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Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners. Front Digit Health. 2023;5:1264780.\u003c/li\u003e\n\u003cli\u003eCollins TE, Karapici A, Berlina D. Noncommunicable Diseases and Global Health Security: Scaling up Action in Humanitarian Crises for Sustainable Recovery. Ann Glob Health. 2025;91(1):27.\u003c/li\u003e\n\u003cli\u003eHarakan A, Hilman YA, Karso AJ, Awaluddin A, Nurhalijah N, Muin IS, et al. Inter-agency collaboration in building urban fire resilience in Indonesia: how do metropolitan cities address it? Frontiers in Sustainable Cities. 2025;Volume 7 - 2025.\u003c/li\u003e\n\u003cli\u003eLeal Filho W, Fritzen B, Salvia AL, Dinis MAP, Vasconcelos CRP. The transformative power of networking in the implementation of the Sustainable Development Goals. Discover Sustainability. 2024;5(1):380.\u003c/li\u003e\n\u003cli\u003eIspiryan A, Pakeltiene R, Ispiryan O, Giedraitis A. Fostering Organizational Sustainability Through Employee Collaboration: An Integrative Approach to Environmental, Social, and Economic Dimensions. Encyclopedia [Internet]. 2024; 4(4):[1806-26 pp.].\u003c/li\u003e\n\u003cli\u003eKosiol J, Silvester T, Cooper H, Alford S, Fraser L. Revolutionising health and social care: innovative solutions for a brighter tomorrow \u0026ndash; a systematic review of the literature. BMC Health Services Research. 2024;24(1):809.\u003c/li\u003e\n\u003cli\u003eChen A, Li L, Shahid W. Digital transformation as the driving force for sustainable business performance: A moderated mediation model of market-driven business model innovation and digital leadership capabilities. Heliyon. 2024;10(8):e29509.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dusit Model, Integrated Health Services, Urban Areas, Technologies, Urban Healthcare, Thailand","lastPublishedDoi":"10.21203/rs.3.rs-7691983/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7691983/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eRapid urbanization has intensified the demand for effective, evidence-based models of integrated health services. However, significant gaps remain in translating such models into practice. This qualitative descriptive study explores lessons learned from the Dusit Model of integrated health services and evaluates its feasibility for adaptation in the Sai Mai District of Bangkok, Thailand.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eBetween May and December 2024, semi-structured interviews were conducted with three key stakeholder groups: administrators, healthcare providers, and patients. Data collection focused on four core components\u0026mdash;technologies, institutions, resources, and stakeholders. All interviews were audio-recorded and analyzed systematically to ensure rigor and objectivity. Ethical approval was obtained from the Faculty of Medicine Vajira Hospital, Navamindradhiraj University, and all participants provided informed consent.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe Dusit Model demonstrated strong potential as a blueprint for integrated urban healthcare, particularly through its use of digital platforms (e.g., \u003cem\u003eVajira@Home\u003c/em\u003e and \u003cem\u003eV-Refer\u003c/em\u003e) and its emphasis on inter-institutional collaboration. These features enhanced service efficiency and care continuity. Nonetheless, challenges were identified, including healthcare workforce shortages and limited digital literacy among older adults. The Sai Mai District was found to be well-positioned for model adoption, given its comparable demographics, robust healthcare network, and strong leadership. To optimize implementation, the district should prioritize workforce development in digital competencies and leverage public health centers as coordination hubs.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe Dusit Model demonstrates that digital integration and collaborative networks strengthen urban health systems. The Sai Mai District is well-positioned for adoption, provided staff receive targeted digital training and public health centers act as coordination hubs. By addressing a critical research gap, this study offers empirical evidence to guide scalable and sustainable integrated healthcare in rapidly urbanizing contexts.\u003c/p\u003e","manuscriptTitle":"The Lessons Learned from the Dusit Model and the Feasibility of Applying Integrated Health Services in Urban Areas: A Qualitative Study in Thailand","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 11:28:24","doi":"10.21203/rs.3.rs-7691983/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-13T06:18:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T18:50:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264099575940951254779844689587844736907","date":"2025-12-07T12:12:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117413499537372585449321525879352439707","date":"2025-12-05T07:30:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T12:50:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-30T06:53:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-07T03:36:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-05T19:53:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-10-05T19:49:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c8f90f5b-3f6e-409a-8951-00245f130a0e","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T11:28:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 11:28:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7691983","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7691983","identity":"rs-7691983","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}