Despite the cooperative sharing of health information exchange (HIE), various distinct limitations and barriers are found (i.e., substantial time and resources are being used to achieve health information). This paper investigates the limits of healthcare information sharing policy implementation for patient referral systems in Thailand. Mixed-methods research methodology, both quantitative and qualitative mechanisms, are conducted. The study results present the correlation between the current HIE among the hospitals in patient referral systems and the limitations of implementing the HIE policy, composed of technical, economic, political, and legal barriers. The statistical test reveals that these four main barriers could limit information sharing or impede Thailand’s standard healthcare information-sharing policy and practice development. Predominantly, it is further found that there is no standard for data collection and data archiving systems; unclear guidelines, practices, and procedures; and a lack of standard practice due to fragmented administration. Foremost of all, the data ownership of any competent authorities or related regulators could cause any constraints in information sharing (e.g., complexity and processing time). This paper’s findings will be beneficial to stakeholders, such as policymakers interested in achieving meaningful use, facilitating the adoption and implementation of HIE at a national level to ensure patients’ safety and enhance healthcare quality.
Keywords: healthcare information, patient referral systems, data sharing, barriers, HIE, health information exchange
Health information exchange (HIE) is the electronic transfer of health-related information between organizations or healthcare providers (e.g., patient and medical information).1,2 HIE contains several benefits, including improving care coordination and healthcare quality; explicitly enhancing patient safety by reducing medication and medical errors; and eliminating redundant or unnecessary testing, handling, and paperwork.3,4 At present, HIE appears in several transaction forms. However, the primary purposes of facilitating the availability and retrieval of clinical data to patients and healthcare providers are securely sharing a patient’s vital medical information electronically, seamless patient transfer, and safety. For instance, the direct exchange with accessibility and visibility to patient information between care providers will support coordinated care in the patient referral systems. On the contrary, the query-based dialogue for patient referral usually involves delivering unplanned care (i.e., in emergency cases). Implementing HIE will enhance the ability of care providers to find or request information about patients from other persons or institutions.5-7
Despite the cooperative HIE, some distinct limitations and barriers exist. For example, electronic data in the prevailing electronic health records (EHR) systems come from multiple sources in different interfaces, technical specifications, and capabilities. It causes interoperability, which is a significant challenge since substantial time and resources are needed to achieve health information. In addition, healthcare information sharing seems to be asymmetric, resulting in inadequate information sharing between healthcare organizations under concerted consent management.8,9 Likewise, some patient information disclosure is required. The benefits of medical data sharing for patient care and other secondary purposes may be harmful. The most significant ethical concerns about breaches of confidentiality have arisen in situations in which third parties are involved during the patient’s referral processes. Therefore, healthcare information must be shared effectively, covering its traceability to provide visibility in the healthcare system.
While collecting and storing patient and medical data is essential in healthcare, securely distributing information remains a global challenge.10 Although interoperability in the healthcare industry becomes critical in adopting or implementing integrated health information systems,11 standard practice for health information exchange would be a pathway to establish interoperability between various organizations and systems. In conclusion, health information sharing at the national level must consider the accessibility, sharing with the regulatory mandates, standard policies, and technology platforms to initiate all forms of HIE to ensure interoperability for successful policy implementation.
This paper will investigate the limitations and barriers of healthcare information sharing for patient referrals. This paper’s findings will benefit stakeholders interested in the effort to achieve meaningful use, facilitating the implementation and adoption of EHRs, and HIE.
HIE refers to the technologies, standards, and governance that enable the electronic exchange and transfer of clinical and administrative information between the information systems of various health care stakeholders. In addition, HIE will facilitate the related work and accelerate health information integration. Similarly, interoperability is essential to patient care, as vital patient data should be available and shared with the right people at the right time and place, leading to fewer medical errors, unnecessary tests, and more efficient decision-making.
The Challenges for Health Information Exchange in Thailand
The research by Health System Research Institute (HSRI) on the HIS/eHealth situation in Thailand addresses the challenges of national health information system (HIS) and health information technology (HIT) development in Thai health systems. It revealed the country’s inadequately developed health information standards.12 Though the government agencies are actively preparing their organization to be e-government to provide a better service, the investment in information systems and interoperability primarily related to health information standards seems insufficient. From the implementation of some pilot projects under e-government, the transformation has been under apathy for four main reasons: unavailable national data standards, lack of best practices to follow, unclear guidelines for how to start and monitor the project, and a lack of a proactive mindset.13
Health informatics professionals in Thailand have encouraged the adoption of health data standards; however, there are hindrances, such as a lack of human resources in health informatics, lack of awareness, and unfamiliarity with the potential benefits of using standards and terminologies in healthcare among high-level policymakers and healthcare professionals.14 All stakeholders in the healthcare supply chain need accurate and consistent information to efficiently respond to the demand and support in both clinical and logistics activities.15 It is important to note that the demand for healthcare information is significantly rising, especially in unforeseen and emergent circumstances. For instance, a robust set of patient identifiers supports automated patient identity matching and workflow integration in a growing epidemic.16 According to the eHealth Strategy in Thailand, Ministry of Public Health (2017 – 2026), there is an attempt to enhance the use of computational technologies and analysis techniques, intelligent devices, and communication media to support healthcare professionals and patients on healthcare services and tackle the related risks management, as well as promote health and well-being. Conclusively, the lack of interoperability, improving health literacy, and health data standards remain significant challenges in Thai health information systems development.
The Development of Health Information Exchange in Thailand
In 2021, a campaign called “Health Link” was launched, which aims to strengthen the HIE system in Thailand. Health Link has been successfully implemented and could serve over 50 hospitals in 2021. This first HIE nationwide platform is keen to improve interoperability, privacy, and security by implementing Fast Healthcare Interoperability Resources (FHIR), pseudonymization, and access control, respectively.17 After implementing Health Link, the authority anticipated escalating the accessibility and visibility of health information. First and foremost, Health Link will be beneficial for healthcare providers to access and retrieve health information. By extension, it will be convenient for healthcare receivers to improve patients’ experience in healthcare, particularly the service time and treatment cost. However, HIE in the prevailing systems is still available in medical terminology. Thus, it will be difficult for patients to understand, and the adverse result may cause confusion or misinterpretation. For this reason, the health information for patients should be simplified and understandable when giving consent.
Barriers and Limitations to Health Information Sharing
In general, the healthcare organizations’ benefits of information technology are perceived and agreeable. The development of nationwide data exchanges with specific criteria can stimulate the adoption of EHRs and facilitate information sharing among healthcare providers.18 However, due to insufficient capital, complex systems, and lack of data standards that enable clinical data exchange, privacy concerns, and legal barriers appear to be obstacles to implementing the practices.
Notably, there is an increasing demand for an interoperable healthcare data system. The essential data should emerge standardized and clear to any healthcare providers involved, irrespective of the location or person or their original affiliation. Nonetheless, cross-organizational collaboration seems not fully compliant with evidence-based, patient-centric, timely, and safe practices. The data redundancy occurs in one hospital database, and ad hoc data collection occurs upon the visit, as the critical information is not available on time. As a result, it affects the continuity of care, and patient care becomes fragmented. Worse, individuals receiving care are often under-supported in their right to access their health data. Thus, essential elements such as a minimal data set, information technology architecture, and legal governance are required.19 Over the past decade, many potential and actual barriers to public health data sharing have been recognized.20 As described above, the barriers to health information sharing can be summarized in six categories, as illustrated in Table 1.
Undeniably, the interactions between the above tangible and intangible barriers at different levels can be rather complicated and severely limit the effectiveness of segregated solutions. Primarily, the concrete walls include technical, motivational, and economic obstacles; these are profoundly inlayed as massive challenges to health information system capacity, particularly in low- and middle-income countries. Solutions such as infrastructure development, capacity building, and efficient financing have been considered and are currently at the outset of the significant international initiatives.21,22 In addition, the factors consist of leadership, trust and commitment, and organizational culture for HIE adoption would be manipulated by organization-specific approaches in three themes (i.e., HIE participation, HIE assessment, and coordination strategies).23 Political, legal, and ethical barriers seem more ethereal and require a different approach. Principally, international agencies (e.g., the World Intellectual Property Organization (WIPO), the World Health Organization (WHO), the World Trade Organization (WTO), countries, development and funding agencies, and experts in ethics and law need to provide outline and present for dialogue together with resolution across sectors. Also, this information requires an intensive discussion to develop a consensus concept, (e.g., strategic plans, reinforcements, or mandates), which should be agreed upon by the majority of stakeholders.24 As a result, the centralized mechanism and governance body should take a significant role in monitoring, mediating, and facilitating information sharing among diverse stakeholders to ensure fair and efficient use of data to advance population health.
A mixed-methods study, namely an in-depth interview and quantitative analysis, would allow for a deeper understanding of existing healthcare information systems, limitations, and requirements for healthcare information sharing in patient referral systems.
Some previous studies on healthcare information sharing explored and summarized limitations to the related policy implementation. The existing barriers from those papers compose of technical barriers, economic barriers, political barriers, legal barriers, and ethical barriers. For the primary data collection, the development of in-depth interview questions relies on these attained barriers. Furthermore, the interviewees’ responses enables us to generate the questionnaire to ideally understand and affirm the limitation of healthcare information sharing in a Thailand healthcare system.
Nonetheless, in our questionnaire’s development, the expert argued that the motivational barrier was likely to be a specific issue or task-related. Hence, we excluded the motivational barriers from the questionnaires to the respondents from the patients’ group. We indicated the given score of current healthcare information sharing as a dependent variable. For internal consistency, the multiple-question Likert scale surveys for both patients and healthcare professionals are reliable based on Cronbach’s alpha at 0.78 and 0.91, respectively.
According to the widespread outbreak of COVID-19, online questionnaires were distributed to both groups of respondents. The questionnaires enabled the respondents to control their personally identifiable information by giving a declaration of data collection purpose and requesting consent to use attained data for research analysis, which authors virtuously intend to understand barriers to HIE policy implementation and how to handle the disputes. In addition, the data collected in this study does not seem to contain any sensitive biological information about respondents in the groups of patients and healthcare professionals. After respondents consent to participate in this survey, the authors shall not discover or publish all respondents’ identifiable information. Additionally, respondents may refuse to participate or to stop the form filling at any time without any loss of health care benefits that they are otherwise receiving. Consequently, the authors considered that this study should not lead to apparent immediate hazards to the participants.
Sample Selection and Size
The population in healthcare services seems quite broad; this study identified two relevant groups: 1) healthcare professionals and 2) patients and relatives. Notably, the selection criteria for the in-depth interview, identified by the sample size, were 20 physicians from different fields of specialties or diseases. In addition, the age range was 41 to 50, with at least 10 years of working experience in patient care. This interview would help to identify determinants affecting health information sharing in Thailand’s patient referral systems. During the conversation, we drilled down their perspective on the current information exchange in patients’ referral systems toward smooth patient referral processes for patient safety.
In the following step, we established the quantitative research. In the survey, we defined healthcare professionals as physicians or nurses who may have experience giving healthcare services through the patient referral systems, especially those involved in healthcare information sharing. Therefore, this group of people would possibly reveal their understanding, perception, and expectation for healthcare information exchange in patient referral systems.
Meanwhile, the patients and relatives group refers to any participants aged below 25 and over 55 years old (i.e., adolescents to older adults) who received healthcare services through the patient referral systems. Alternatively, they presumably were patients or ones taking care of their family members in the hospitals. This group of samples can expose their experience and perception in exchanging healthcare information, affecting the diagnosis or treatment process for themselves or family members. Therefore, the typical exclusion criteria concerning the properties of the study sample are to exclude any patients or healthcare professionals without experience in patient referrals from the current study.
The sample size determination for our survey was selected based on Yamane’s formula for healthcare professionals and relied on Roscoe for patients and relatives. According to the Medical Council of Thailand data, around 29,897 physicians live in Bangkok. With this given number at a confidence interval of 95 percent or a P-value of 0.05, our sample size for the healthcare professional would be 397 respondents as a minimum (29,897/ 1+(29,987*0.52) (Yamane,1973). The population of patients and relative groups seems quite large, so we calculated the sample size using the infinite population method (Roscoe, 1969), based on this method with a P-value of 0.05 and a population standard deviation equal to or not more than 10. Then, 384 respondents are the minimum requirement (N = (Zcσ/em)2 = (1.96 x 10)2 = 19.62 = 384.16). Therefore, we reached 903 people as the actual number of participants in the survey, consisting of 479 people and 424 people from the patients and healthcare professionals groups, respectively.
In this study, we examined the attained data by using multiple regression analysis (MRA) to assess the correlation between an outcome or the current healthcare information exchange among the hospitals in patient referral systems (Y= dependent variable) and the limitations of implementing the HIE policy (X= independent variables) composed of technical barrier, motivational barrier, economic barrier, political barrier, legal barrier, and ethical barrier.
From the literature review, the existing barriers to information sharing in other countries could also occur in patient referral systems in a Thailand-specific context.
A total of 20 physicians from different fields participated in the in-depth interview, including allergists, emergency care specialists, infectious disease specialists, internists, neurologists, pediatricians, psychiatrists, and trauma surgeons. Moreover, some of the interviewees had a role as executive management members in the medical school hospitals. This interview is not only to identify the current interoperability landscape, assess cooperative information exchange between the hospitals over time, and verify the barriers that have been listed earlier, but also helped to develop a guideline for the standardization of healthcare information’s conceptual design. During the conversation, we drilled down their perspective on information exchange in patient referral systems under two purpose categories: smooth patient referral processes for patient safety and the basic set of data for better care services quality.
Most of the interviewees asserted policy and practice guidelines were not clear and adequately designed; it became limitations of policy implementation and led to unsuccessfully healthcare information sharing between hospitals presently. Two-thirds of them revealed the lack of national standard practice. Considerably, based on their aspects and personal experience, the suspecting barriers had been identified, as shown in Table 2.
The actual survey consisted of 903 subjects, including 424 respondents from the healthcare professionals group and 479 respondents from the patient group. First, all respondents were asked to evaluate the current HIE and cooperative relationship among the hospitals in patient referral systems. Then, from the previous section, we identified the independent variables according to the list in Table 1, including technical, motivation, economic, political, legal, and ethical.
The question items representing each barrier in the questionnaire are illustrated as follows;
Technical Barrier: The participants would help assess current health information systems from their own experiences on the following items;
Presently, the appropriate data collection, good data archiving, and storage. For example, with the rapid data accessibility and retrieval, patients do not need to repeat form filling for every hospital visit.
The web-based platform used by either patients or healthcare professionals is user-friendly and understandable, or if the systems adequately provide a basic guideline or technical solution for end users and system administrators to create a mutual arrangement.
The national databases and data repositories appear in similar language and coding for comprehensible use.
The data source is identifiable to add information or data correction purposes.
Motivation Barrier: Only the healthcare professionals to confirm the following statements:
There are adequate personal and institutional incentives to generate healthcare information databases or prioritize data sharing over other pressing duties.
Less workload and stress conditions so staff can concentrate on developing health information databases and systems maintenance.
The existing organizational policies or solutions (e.g., public relations strategies and practices also conflict management for both individuals and organizational levels) help prevent or oppose possible criticism caused by data usage or sharing.
Economic Barrier: Each statement will reflect respondents’ perception on whether, for further development, the current health information system receives adequate support on infrastructure, competent personnel, institutional incentives, and resources. Also, if it is agreeable that data sharing (e.g., daily statistics of admitted patients in a particular hospital with COVID-19 or a case of wrong or delayed diagnosis) may cause an impact on organizational reputation and corporate standing. Literally, it may result in an overall national GDP falling and lead to economic crises.
Political Barrier: The statements will refer to the organizational governance, standard policy, and practice that similarly apply in different hospitals, regardless of public or private. Public relations or shared database initiatives would enhance the patient experiences while ease and allow healthcare professionals to faster data accessibility, less complexity, and avoid time consumption.
Legal Barrier: Given statements will describe the centralized administration and governance at the national level to evaluate whether policies, standard practices, and procedures are available and lucid for practical uses. For example, ad-hoc guidelines to prevent and control data breaches are typically available and depicted.
Ethical Barrier: Each statement will evaluate the current concern on adequate proportionality if there is careful deliberation in assessing the risks and benefits in regular practice. The respondents’ outlooks on the sufficiency of reciprocity and to verify whether data sharing practices are often for mutual benefits.
Next, the participants will run through a statement of possible barriers to identifying the most likely determinants affecting the current healthcare information sharing in patient’s referral based on their experiences with a 5-point Likert scale (1 = strongly disagree, and 5 = strongly agree).
Having the statistical analysis, we formulated the following hypotheses for MRA analysis as follows:
Hypothesis A (H0): All given determinants affect the willingness to share healthcare information equally among hospitals/care providers.
Hypothesis B (H1): Any given determinant will increase or decrease the willingness to share healthcare information among hospitals/care providers.
Study Results from Patient Group
From the survey, a total of 479 participants from different sectors of Bangkok, which ages ranged from below 25 to over 55 years, with 36.3 percent identified the experience in patient referrals between divisions within the same hospital, 51.1 percent patient referrals between hospitals in Bangkok, and 12.5 percent patient referrals for cross-province hospitals. We discovered the participants’ perspective on the current healthcare information sharing in patient referrals is mostly at neutral at 36.7 percent, and 32.8 percent for information sharing is sufficient, but accessibility may take some time. At the same time, 17.7 percent of respondents identified that healthcare information sharing between hospitals is limited (M = 3.38, SD =.9304). See Table 3.
In the following step, using t-test and Sig. to examine the correlation between predictor variables and response variable (t=b1-0/ SE(b1) include Technical (β1) = .679 t = (.679-0)/.054 = 12.670 at significance value = .000 (B = .549) and Political (β3) = .168 t = (.168-0)/.056= 3.010 at significance value = .003 (B value = .148). These two barriers are associated with increasing the willingness to share health information. This study will rise by 0.679 when the technical drawbacks such as lack of standards, data quality, and data archiving system are steadily manipulated and increase by 168 if political barriers (e.g., the lack of standard practice guidelines, unclear policies and procedures) are solved. Concurrently, strategic movement and reinforcement should positively impact the development of the standard practice by increasing information sharing.
On the contrary, we accepted H0 for economic (β2), legal (β4), and ethical (β5), which means these determinants are irrelevant to the response variable; in addition, this result implied no multicollinearity because the VIF value is less than 10, and the tolerance value is higher than 0.25.
From Table 4, the model summary presented that the R-value presents the correlation between dependent and independent variables at 0.676 or 67.6 percent. Implicitly, there are probably other determinants that could affect the willingness of information sharing among hospitals or a way to develop the standard practice for information sharing in patient referral.
According to the Anova statistic, the statistic value shows F = 79.223, and the significance value is 0.000, or below 0.05 (H0 is rejected), so we may conclude that any of these five determinants would affect the willingness of information sharing among hospitals or the development of standard healthcare information systems in patient’s referral.
Study Results from the Healthcare Professionals Group
The 424 participants in the survey were care providers (e.g., physicians including primary care physicians, specialist doctors, nurses, referralists) and some of them are executive members of medical school hospitals, and ranged in age from below 25 to over 55 years with working experience starting from 11 months up to 45 years (M = 15, SD = 11.468). From the survey, 51.9 percent of respondents identified the experience in patient referrals between divisions within the same hospital, 26.4 percent patient referrals between hospitals in Bangkok, and 21.7 percent patient referrals for cross-province hospitals. We discovered the participants’ perspective on the current healthcare information sharing in patient referral. Most of them, or 40.6 percent, agreed that information sharing is sufficient, but accessibility may take some time, and 24.8 percent are satisfied with the current cooperative healthcare information sharing. Likewise, 24.5 percent rated at neutral (M = 3.79, SD =.9450).
Based on the multiple regression analysis (Table 5), the t-value and corresponding p-value confirm that the three determinants, including technical, economic, and legal barriers, are significant. The β value of these variables will correlate with the degree of willingness to information sharing or standard practice development. They include technical = 0.495 (P-value = 0.000), economic = 0.112 (P-value = 0.022) and legal = 0.136 (P-value = 0.033). In the multiple regression model, VIF should be <10 or tolerance >0.25 for all variables, which they are. Given the result in Table 6, motivation, political and ethical barriers are not significant P value (0.881) >0.05, p. (694)>0.05, and p. (784)>0.05, respectively. In other words, the regression model for a group of healthcare professionals’ respondents includes technical, economic, and legal. However, motivation, political, and ethical contribute less to explaining the willingness for information sharing or standard practice development.
In Table 6, the R-value presents the correlation between dependent and independent variables at 0.671 or 67.1 percent. Similar to the result from the patient group, other possible determinants could affect the willingness for information sharing among hospitals or a way to develop the standard practice for information sharing in patient referral.
The F-value in the Anova (Table 6) tests whether the overall regression model is a good fit for the data, which the independent variables statistically predict the dependent variable, F (6,417) = 56.909, p (<0.001) <0.05. Therefore, the regression model is a good fit for the data. Furthermore, it is concludable that the perspectives of healthcare professionals on any of these six determinants would affect the willingness of information sharing among hospitals or the development of standard healthcare information systems in patient referral.
All barriers in this study were considered essential and would impede or facilitate information sharing. However, some barriers may present a higher weight or more substantial impact than others. The statistical results showed that both respondents agreed that one common barrier, technical, could be a critical reason for the unsuccessful policy implementation for healthcare information exchange. This result reflects the lack of national data standards, data collection, and quality, especially in the data silo in various fragmented systems.
In addition, the healthcare professionals mentioned two other barriers, economic, which represent relatively insufficient resources, inadequate competent human resources, and organizational reputation. Then, legal refers to the national level’s lack of standard regulation and ad-hoc guidelines. Whereas, the patients indicated another significant barrier, political, which would signify that different hospital policies can lead to the diverse services experience that could be compared and classified in numerous ways, especially in patient referral process.
In this study, the economic barrier represents an adequate resource, and organizational reputation would affect the willingness to information sharing. Therefore, the patients’ and healthcare professionals’ perspectives on economic barriers may be perceived differently. In particular scenarios, such factors may not impact their decision-making during hospital visits (both regular and emergency cases) since the patients would first consider their health conditions, especially for time-sensitive diseases or injuries from accidents. If the P-value > 0.05 but the coefficient shows a negative value, the current investment in infrastructure and resources seems sufficient. However, regardless of organizational reputation, healthcare information is proprietary. The less concerned about corporate standing, the patient’s perspective, the more willing to share. Eventually, this will benefit the patients in terms of treatment accessibility. Data attained from the literature, in-depth interviews, and survey results showed potential barriers. Besides, it would elaborate on the details of disputes that interrupted the information sharing and policy implementation of standard healthcare information, even smooth patient referrals and safety.
A comparison between the findings of this study and previous studies reveals that all studies present several impediments to information sharing in healthcare; nevertheless, this paper assesses Thailand’s healthcare information sharing practice through patients’ and healthcare professionals’ perspectives, particularly in patient referrals. The four barriers consist of technical, economic, political, and legal being identified and manipulated. The researchers anticipated the relevant competent authorities to have regulatory mandates and reinforcement initiatives that would lead to the successful policy implementation for HIE based on a shared or centralized database-driven.
For instance, a single standard platform for data collection will increase data accessibility and visibility. Escalation of the strategic movement and governance of national eHealth systems are the most essential and critical. Adopting EHRs with meaningful use can improve the quality of care, treatment, and medication quality under the supervision of cybersecurity. In improving healthcare information sharing processes, the development of the national standard of healthcare information, the strategic movement, and governance of national eHealth systems are the most essential and critical parts. As for the regulatory landscape, the governing body should be established and empowered by the related government departments in Thailand (e.g., the Ministry of Public Health or the Ministry of Digital Economy and Society). Such governing body that has authority to control the adoption of standards should announce the mandates.
Further to legislation setting, in terms of sustainable development, the legislative process should include policy evaluation and amendment after a certain period. Given collaborative administration, the commitment from all stakeholders is a necessity. Having a clear roadmap for the designated standards to be implemented and interoperable in the healthcare system is critical.
Meanwhile, advocacy on the potential benefits of using data standards and communication between the organizations and the users greatly benefits from controlling or manipulating the possible conflict and misunderstanding. Above and beyond, the standards maintenance and revision processes are part of the compulsory components of successful implementation and the acquiring resources and personnel in the specific related field. Furthermore, cultivation, incentives, services mindset, and capacity building are essential.
The previous studies noted the positive effect of information sharing on the efficiency of the supply chain. In addition, the advancement of information technology in recent years has empowered healthcare organizations to improve their service flow and the information flow via efficient mechanisms. For instance, information technology and data visibility will increase patients’ accessibility to safe, quality, and appropriate health services and treatment. Therefore, well-organized information sharing will enhance supply chain performance similar to other industries. In addition, it will prevent redundant transactions and unnecessary costs and allow enterprises to refine their supply chain management strategies to evolve service quality and maximize patient benefits. This study draws a possible implementation approach and practice for healthcare information sharing from the previous section. Beyond being the supportive technology for enhancing secure interconnectivity and a secure information-sharing platform of healthcare data, innovative information management such as blockchain delivers health-related data to support decision-making in the care process. Even though stakeholders might run into the emerging conditions, this will remain state of the art about cybersecurity.
Initially, the data collection of this study is supposed to be nationwide to move toward a national innovative management; however, the authors unfortunately narrowed the data collection area in Bangkok according to the coronavirus pandemic. Consequently, the result of this study phase may not well represent standardization. Nonetheless, this phase of the study focuses on healthcare information sharing. Furthermore, surveying Bangkok would also minimize the adverse impact caused by the delay in getting the response from respondents. In addition, some barriers in this survey may not be what patients and healthcare professionals can conceive or experience; however, as the bottom-up approach to policy evaluation, the authors believe this survey data will be beneficial in reflecting the overview of current HIE policy implementation. Therefore, from the end user’s perspective, operators’ feedback would deliver thoughtful comments and constructive remarks to policymakers or shareholders for consideration and enable them to stipulate top-down policy and mandates. To reflect the current interaction and future cooperative platform, the authors proposed expanding the scope of analysis in a future study to cover all stakeholders in the healthcare supply chain (e.g., suppliers, society, regulators, and administrators, including The National Health Security Office (NHSO) and insurance companies).
Conclusions and Further Research
Thailand is a leading medical tourism hub and plans to transform into an Asia-Pacific medical hub; however, the initiative policy management and strategic movement remain a current and forthcoming challenge in Thailand’s health system development. The main objective of this study is to determine the potential barriers to implementing a health information sharing policy in Thailand’s patient referral systems. Furthermore, the study proposed conceptual healthcare information management for patient referrals to ensure the critical patients and healthcare information available when needed through the manipulated and standardized process, regardless of time and distance. In this paper, technical, economic, political, and legal are the four determinants influencing the implementation of healthcare information sharing policy and significantly affecting the practice.
The personalized feedback from healthcare professionals and patients would benefit from identifying the specific ways they could offer alternatives for improvement and development in the healthcare system. The driving force of the influential regulators or the decisive direction from the public health policymakers is an imperative component.
Nonetheless, prosperous and sustainable healthcare information systems require the central body to earnestly consider the distinct level of health information literacy and competencies. Therefore, further research on the distinctive health information literacy on an individual level will help address and contribute to developing health information literacy and competencies in Thai citizens.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research(s), authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
1. Akhlaq, Ather, Aziz Sheikh, and Claudia Pagliari. "Defining health information exchange: scoping review of published definitions." BMJ Health & Care Informatics 23, no. 4 (2016).
2. Esmaeilzadeh, Pouyan, and Murali Sambasivan. "Health Information Exchange (HIE): A literature review, assimilation pattern and a proposed classification for a new policy approach." Journal of biomedical informatics 64 (2016): 74-86.
3. Dixon, Brian E. "What is health information exchange?." In Health information exchange, pp. 3-20. Academic Press, 2016.
4. Lengel, Aaron J., Elise ML Carpenter, Andrew G. Azzi, and Kristen L. DiDonato. "Identifying barriers that prevent the usage of health information exchange in Ohio." Journal of Pharmacy Technology 36, no. 4 (2020): 148-156.
5. Williams, Claudia, Farzad Mostashari, Kory Mertz, Emily Hogin, and Parmeeth Atwal. "From the Office of the National Coordinator: the strategy for advancing the exchange of health information." Health affairs 31, no. 3 (2012): 527-536.
6. Ancker, Jessica S., Alison M. Edwards, Melissa C. Miller, and Rainu Kaushal. "Consumer perceptions of electronic health information exchange." American journal of preventive medicine 43, no. 1 (2012): 76-80
7. Vest, Joshua R., Thomas R. Campion, and Rainu Kaushal. "Challenges, alternatives, and paths to sustainability for health information exchange efforts." Journal of medical systems 37, no. 6 (2013): 1-8.
8. Fongtanakit, Ratchada, Sudawan Somjai, Amnaj Prasitdumrong, and Kittisak Jermsittiparsert. "The determinants of the medical tourism supply chain of Thailand." International Journal of Supply Chain Management 8, no. 6 (2019): 291-300.
9. Spanakis, Emmanouil G., Stelios Sfakianakis, Silvia Bonomi, Claudio Ciccotelli, Sabina Magalini, and Vangelis Sakkalis. "Emerging and Established Trends to Support Secure Health Information Exchange." Frontiers in Digital Health 3 (2021): 636082.
10. Bogaert, Petronille, Marieke Verschuuren, Herman Van Oyen, and Hans Van Oers. "Identifying common enablers and barriers in European health information systems." Health Policy 125, no. 12 (2021): 1517-1526.
11. Kondylakis, Haridimos, Cristian Axenie, Dhundy Kiran Bastola, Dimitrios G. Katehakis, Angelina Kouroubali, Daria Kurz, Nekane Larburu et al. "Status and recommendations of technological and data-driven innovations in cancer care: Focus group study." Journal of medical Internet research 22, no. 12 (2020): e22034.
12. Kijsanayotin, Boonchai, Win Min Thit, Warithnan Thanapak, Niramai Nareenuch, Benjakarn Leelakittisin, Phatcharanan Khongmun, Wanchana Ponthongmak, and Panu Looareesuwan. EHealth in Thailand: Interoperability and health information standards. Thai Health Information Standards Development Center, Health System Research Institute, 2016.
13. Kawtrakul, Asanee, Intiraporn Mulasastra, Tawa Khampachua, and Somchoke Ruengittinun. "The challenges of accelerating connected government and beyond: Thailand perspectives." Electronic Journal of e-Government 9, no. 2 (2011): pp183-202.
14. Kijsanayotin, Boonchai, 2016.
15. Kritchanchai, Duangpun, Sineenart Krichanchai, Soriya Hoeur, and Albert Tan. "Healthcare supply chain management: macro and micro perspectives." LogForum 15, no. 4 (2019).
16. Cummins, Mollie R., Guilherme Del Fiol, Barbara I. Crouch, Pallavi Ranade-Kharkar, Aly Khalifa, Andrew Iskander, Darren Mann et al. "Enabling health information exchange at a US Poison Control Center." Journal of the American Medical Informatics Association 27, no. 7 (2020): 1000-1006.
17. Taechoyotin, Pawin, Patipan Prasertsom, Mullika Phanhong, Patchara Wongsutthikoson, Ravi Laohasurayodhin, Napassawan Pasuthip, and Ben Ruktantichoke. "Health Link: Scalable Health Information Exchange Platform in Thailand." In 2021 2nd International Conference on Big Data Analytics and Practices (IBDAP), pp. 101-106. IEEE, 2021.
18. Mahapatra, Prasanta, Kenji Shibuya, Alan D. Lopez, Francesca Coullare, Francis C. Notzon, Chalapati Rao, and Simon Szreter. "Civil registration systems and vital statistics: successes and missed opportunities." The Lancet 370, no. 9599 (2007): 1653-1663.
19. Azarm, Mana, Chantal Backman, Craig Kuziemsky, and Liam Peyton. "Breaking the healthcare interoperability barrier by empowering and engaging actors in the healthcare system." Procedia computer science 113 (2017): 326-333.
20. Van Panhuis, Willem G., Proma Paul, Claudia Emerson, John Grefenstette, Richard Wilder, Abraham J. Herbst, David Heymann, and Donald S. Burke. "A systematic review of barriers to data sharing in public health." BMC public health 14, no. 1 (2014): 1-9.
22. Keller, Mikaela, Michael Blench, Herman Tolentino, Clark C. Freifeld, Kenneth D. Mandl, Abla Mawudeku, Gunther Eysenbach, and John S. Brownstein. "Use of unstructured event-based reports for global infectious disease surveillance." Emerging infectious diseases 15, no. 5 (2009): 689.
23. Guerrazzi, Claudia, and Sue S. Feldman. "Health information exchange: What matters at the organizational level?." Journal of Biomedical Informatics 102 (2020): 103375.
24. Whitworth, Jimmy. "Data sharing: reaching consensus." Bulletin of the World Health Organization 88, no. 6 (2010): 468-468.
Akhlaq, Ather, Aziz Sheikh, and Claudia Pagliari. "Defining health information exchange: scoping review of published definitions." BMJ Health & Care Informatics 23, no. 4 (2016).
Ancker, Jessica S., Alison M. Edwards, Melissa C. Miller, and Rainu Kaushal. "Consumer perceptions of electronic health information exchange." American journal of preventive medicine 43, no. 1 (2012): 76-80
Anderson, Margo J., and William Seltzer. "Federal statistical confidentiality and business data: Twentieth century challenges and continuing issues." Journal of Privacy and Confidentiality 1, no. 1 (2009).
Azarm, Mana, Chantal Backman, Craig Kuziemsky, and Liam Peyton. "Breaking the healthcare interoperability barrier by empowering and engaging actors in the healthcare system." Procedia computer science 113 (2017): 326-333.
Bogaert, Petronille, Marieke Verschuuren, Herman Van Oyen, and Hans Van Oers. "Identifying common enablers and barriers in European health information systems." Health Policy 125, no. 12 (2021): 1517-1526.
Cummins, Mollie R., Guilherme Del Fiol, Barbara I. Crouch, Pallavi Ranade-Kharkar, Aly Khalifa, Andrew Iskander, Darren Mann et al. "Enabling health information exchange at a US Poison Control Center." Journal of the American Medical Informatics Association 27, no. 7 (2020): 1000-1006.
Dixon, Brian E. "What is health information exchange?." In Health information exchange, pp. 3-20. Academic Press, 2016.
Esmaeilzadeh, Pouyan, and Murali Sambasivan. "Health Information Exchange (HIE): A literature review, assimilation pattern and a proposed classification for a new policy approach." Journal of biomedical informatics 64 (2016): 74-86.
Feldman, Sue S., Benjamin L. Schooley, and Grishma P. Bhavsar. "Health information exchange implementation: lessons learned and critical success factors from a case study." JMIR medical informatics 2, no. 2 (2014): e3455.
Fongtanakit, Ratchada, Sudawan Somjai, Amnaj Prasitdumrong, and Kittisak Jermsittiparsert. "The determinants of the medical tourism supply chain of Thailand." International Journal of Supply Chain Management 8, no. 6 (2019): 291-300.
Guerrazzi, Claudia, and Sue S. Feldman. "Health information exchange: What matters at the organizational level?." Journal of Biomedical Informatics 102 (2020): 103375.
Kawtrakul, Asanee, Intiraporn Mulasastra, Tawa Khampachua, and Somchoke Ruengittinun. "The challenges of accelerating connected government and beyond: Thailand perspectives." Electronic Journal of e-Government 9, no. 2 (2011): pp183-202.
Keller, Mikaela, Michael Blench, Herman Tolentino, Clark C. Freifeld, Kenneth D. Mandl, Abla Mawudeku, Gunther Eysenbach, and John S. Brownstein. "Use of unstructured event-based reports for global infectious disease surveillance." Emerging infectious diseases 15, no. 5 (2009): 689.
Kijsanayotin, Boonchai, Narong Kasitipradith, and Supasit Pannarunothai. "eHealth in Thailand: the current status." MEDINFO 2010 (2010): 376-380.
Kondylakis, Haridimos, Cristian Axenie, Dhundy Kiran Bastola, Dimitrios G. Katehakis, Angelina Kouroubali, Daria Kurz, Nekane Larburu et al. "Status and recommendations of technological and data-driven innovations in cancer care: Focus group study." Journal of medical Internet research 22, no. 12 (2020): e22034.
Kritchanchai, Duangpun, Sineenart Krichanchai, Soriya Hoeur, and Albert Tan. "Healthcare supply chain management: macro and micro perspectives." LogForum 15, no. 4 (2019).
Lengel, Aaron J., Elise ML Carpenter, Andrew G. Azzi, and Kristen L. DiDonato. "Identifying barriers that prevent the usage of health information exchange in Ohio." Journal of Pharmacy Technology 36, no. 4 (2020): 148-156.
Lluch, Maria. "Healthcare professionals’ organisational barriers to health information technologies—A literature review." International journal of medical informatics 80, no. 12 (2011): 849-862.
Mahapatra, Prasanta, Kenji Shibuya, Alan D. Lopez, Francesca Coullare, Francis C. Notzon, Chalapati Rao, and Simon Szreter. "Civil registration systems and vital statistics: successes and missed opportunities." The Lancet 370, no. 9599 (2007): 1653-1663.
Moher, David, Alessandro Liberati, Jennifer Tetzlaff, Douglas G. Altman, and Prisma Group. "Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement." International journal of surgery (London, England) 8, no. 5 (2010): 336-341.
Ondieki, F. "Effects of health records management on service delivery: a case study of Kisii Teaching and Referral hospital." Journal of Hospital & Medical Management 3, no. 01 (2017): 1-5.
Roscoe, J. T. "The t test for two related samples." Fundamental research statistics for the behavioral sciences. New York: Holt, Rinehart and Winston, lnc (1969): 170-174.
Schulz, Stefan, Robert Stegwee, and Catherine Chronaki. "Standards in healthcare data." Fundamentals of Clinical Data Science (2019): 19-36.
Spanakis, Emmanouil G., Stelios Sfakianakis, Silvia Bonomi, Claudio Ciccotelli, Sabina Magalini, and Vangelis Sakkalis. "Emerging and Established Trends to Support Secure Health Information Exchange." Frontiers in Digital Health 3 (2021): 636082.
Sakunphanit, Thaworn. "Universal health care coverage through pluralistic approaches: experience from Thailand." Bangkok, ILO Subregional Office for East Asia (2006).
Taechoyotin, Pawin, Patipan Prasertsom, Mullika Phanhong, Patchara Wongsutthikoson, Ravi Laohasurayodhin, Napassawan Pasuthip, and Ben Ruktantichoke. "Health Link: Scalable Health Information Exchange Platform in Thailand." In 2021 2nd International Conference on Big Data Analytics and Practices (IBDAP), pp. 101-106. IEEE, 2021.
Kijsanayotin, Boonchai, Win Min Thit, Warithnan Thanapak, Niramai Nareenuch, Benjakarn Leelakittisin, Phatcharanan Khongmun, Wanchana Ponthongmak, and Panu Looareesuwan. EHealth in Thailand: Interoperability and health information standards. Thai Health Information Standards Development Center, Health System Research Institute, 2016.
Van Panhuis, Willem G., Proma Paul, Claudia Emerson, John Grefenstette, Richard Wilder, Abraham J. Herbst, David Heymann, and Donald S. Burke. "A systematic review of barriers to data sharing in public health." BMC public health 14, no. 1 (2014): 1-9.
Vest, Joshua R., Thomas R. Campion, and Rainu Kaushal. "Challenges, alternatives, and paths to sustainability for health information exchange efforts." Journal of medical systems 37, no. 6 (2013): 1-8.
Watkinson, Fiona, Kanika I. Dharmayat, and Nikolaos Mastellos. "A mixed-method service evaluation of health information exchange in England: technology acceptance and barriers and facilitators to adoption." BMC health services research 21, no. 1 (2021): 1-13.
Whitworth, Jimmy. "Data sharing: reaching consensus." Bulletin of the World Health Organization 88, no. 6 (2010): 468-468.
Williams, Claudia, Farzad Mostashari, Kory Mertz, Emily Hogin, and Parmeeth Atwal. "From the Office of the National Coordinator: the strategy for advancing the exchange of health information." Health affairs 31, no. 3 (2012): 527-536.
Yamane, T. Statistics, an introductory analysis. Harper and Row, 1973.
Veerawan Aumpanseang (email@example.com) is a graduate school student at Chulalongkorn University in Thailand and currently working as an office manager of Siriraj Center of Research Excellence Strategic Management Unit at the Faculty of Medicine Siriraj Hospital, Mahidol University in Thailand.
Kamonchanok Suthiwartnarueput (firstname.lastname@example.org) is a member of the commerce and accountancy faculty at Chulalongkorn University in Thailand.
Pongsa Pornchaiwiseskul (email@example.com) is a member of the economics faculty at Chulalongkorn University in Thailand