Healthcare Information Systems Research Articles

ZTCloudGuard: Zero Trust Context-Aware Access Management Framework to Avoid Medical Errors in the Era of Generative AI and Cloud-Based Health Information Ecosystems

Managing access between large numbers of distributed medical devices has become a crucial aspect of modern healthcare systems, enabling the establishment of smart hospitals and telehealth infrastructure. However, as telehealth technology continues to evolve and Internet of Things (IoT) devices become more widely used, they are also increasingly exposed to various types of vulnerabilities and medical errors. In healthcare information systems, about 90% of vulnerabilities emerge from medical error and human error. As a result, there is a need for additional research and development of security tools to prevent such attacks. This article proposes a zero-trust-based context-aware framework for managing access to the main components of the cloud ecosystem, including users, devices, and output data. The main goal and benefit of the proposed framework is to build a scoring system to prevent or alleviate medical errors while using distributed medical devices in cloud-based healthcare information systems. The framework has two main scoring criteria to maintain the chain of trust. First, it proposes a critical trust score based on cloud-native microservices for authentication, encryption, logging, and authorizations. Second, a bond trust scoring system is created to assess the real-time semantic and syntactic analysis of attributes stored in a healthcare information system. The analysis is based on a pre-trained machine learning model that generates the semantic and syntactic scores. The framework also takes into account regulatory compliance and user consent in the creation of the scoring system. The advantage of this method is that it applies to any language and adapts to all attributes, as it relies on a language model, not just a set of predefined and limited attributes. The results show a high F1 score of 93.5%, which proves that it is valid for detecting medical errors.

Cutting through the noise to motivate people: A comprehensive analysis of COVID-19 social media posts de/motivating vaccination

The COVID-19 pandemic exposed significant weaknesses in the healthcare information system. The overwhelming volume of misinformation on social media and other socioeconomic factors created extraordinary challenges to motivate people to take proper precautions and get vaccinated. In this context, our work explored a novel direction by analyzing an extensive dataset collected over two years, identifying the topics de/motivating the public about COVID-19 vaccination. We analyzed these topics based on time, geographic location, and political orientation. We noticed that while the motivating topics remain the same over time and geographic location, the demotivating topics change rapidly. We also identified that intrinsic motivation, rather than external mandate, is more advantageous to inspire the public. This study addresses scientific communication and public motivation in social media. It can help public health officials, policymakers, and social media platforms develop more effective messaging strategies to cut through the noise of misinformation and educate the public about scientific findings.

Prevalence of Leber hereditary optic neuropathy in the Community of Madrid (Spain), estimation with a capture-recapture method

BackgroundLeber hereditary optic neuropathy (LHON) typically presents in young adults as bilateral painless subacute visual loss. Prevalence data are scarce. The aim of this study was to examine the validity of different ascertainment sources used in population-based rare diseases registries to detect cases, and to explore the impact of a capture-recapture method in the estimation of the prevalence of LHON in the Autonomous Community of Madrid (ACM) in 2022.MethodsDescriptive cross-sectional population-based study. Potential LHON cases were detected by automatic capture from the healthcare information sources usually explored for the Regional Registry for Rare Diseases (SIERMA). Ophthalmologists provided data from their clinical registry. Positive predictive values (PPV) and sensitivity with 95% confidence intervals (CI) were estimated. Global and by sex prevalences were calculated with confimed cases and with those estimated by the capture-recapture method.ResultsA total of 102 potential LHON cases were captured from healthcare information sources, 25 of them (24.5%) finally were confirmed after revision, with an overall PPV of 24.5% (95%CI 17.2–33.7). By source, the electronic clinical records of primary care had the highest PPV (51.2, 95%CI 36.7–65.4). The ophthalmologists clinical registry provided 22 cases, 12 of them not detected in the automatic capture sources. The clinical registry reached a sensitivity of 59.5% (95%CI 43.5–73.6) and the combination of automatic capture sources reached a 67.6% (95%CI: 51.5–80.4). The total confirmed cases were 37, with a mean age of 48.9 years, and a men: women ratio of 2.4:1. Genetic information was recovered in 27 cases, with the m.3460 mutation being the most frequent (12 cases). The global prevalence was 0.55 cases/100,000 inhabitants (95%CI 0.40–0.75), and with the capture-recapture method reached 0.79 cases/100,000 (95%CI 0.60–1.03), a 43.6% higher, 1.15 cases/100,000 (95%CI 0.83–1.58) in men and 0.43 cases/100,000 (95%CI 0.26–0.70) in women.ConclusionsThe prevalence of LHON estimated in the ACM was lower than in other European countries. Population-based registries of rare diseases require the incorporation of confirmed cases provided by clinicians to asure the best completeness of data. The use of more specific coding for rare diseases in healthcare information systems would facilitate the detection of cases. Further epidemiologic studies are needed to assess potential factors that may influence the penetrance of LHON.

Sec-Health : A Block Chain-Based Protocol for Securing Health Records

Storing and participating health records through electronic systems pose security pitfalls. To address them, several countries’ regulations have established that healthcare information systems must fulfill security parcels (confidentiality, access control, integrity, cancellation and obscurity) and reciprocal bones (exigency access and interoperability). Upon diving these issues, several proffers present security limitations and/ or specific only. We propose Sec- Health, a block chain- grounded protocol that secures health records, addressing all of the main security and reciprocal parcels defined in current regulations. We show that Sec- Health is a suitable result by assaying it under several attack scripts and describing how it overcomes the problems of being results. likewise, we estimate a Sec- Health evidence of Concept, showing that it can reduce the time to pierce health records, and reduce customer- side outflow, compared to affiliated work.

Protection of Personal Data in Telemedicine

The protection of personal data in telemedicine in the context of current legislation and regulatory acts of the European Union is considered. Social relations in the field of use of personal data in telemedicine are studied, in particular, legal regulation of the use of personal data processed in health care information systems. In the information society, the right to health care and medical care is closely related to the right to access information. The right to access to information is a guarantee of the exercise of the right to health care and medical care, defines its content and contributes to equal access of every person to medical care. It is indicated that ensuring the balance of private and public interests in telemedicine requires differentiation of the conditions for processing personal health data. As an additional condition for the processing of personal data for specific purposes, it is proposed to provide for the consent of the subject of personal data to data processing with the right to refuse processing. Such purposes may include, in particular, the processing of electronic health records in the unified state health information system, the processing of depersonalized personal health data for research purposes. This approach contributes to the protection of public interests in health care and takes into account the autonomy of the will of the subject of personal data, his interests in the field of personal information security, corresponds to approaches to legal regulation in the European Union.

Establishing Robust Data Sharing Through a Blockchain-Driven Standardization Framework in Local Community Healthcare System

The healthcare industry's digitalization has sparked innovation and improved various aspects of the services. Community hospitals in Pangasinan still use conventional paper-based methods for managing patients' health records. However, the healthcare information system is still in a traditional structured excel platform and lacking of communication among healthcare providers. This study aims to design a blockchain-driven standardization framework to establish robust data sharing and increase the confidentiality and security of stakeholders in using the healthcare system. In gathering data, a focus group was organized to give a valuable perspective on the present state of the healthcare system through conducting an online survey, seven respondents are direct users of the healthcare system. The study adopted the IS4H assessment maturity tool concerning data management and information technology in identifying the gaps and challenges in the existing healthcare system. A comprehensive review of related literature regarding the usability of access control models in the study and the potential of blockchain technology in the healthcare system is also essential. Blockchain technology provides features that enhance the accessibility and immutability of the healthcare system and to the stakeholders. The research underscores the paramount importance of integrating blockchain, access control, and security measures to safeguard privacy in the system. The implication of the integration of blockchain is seamless, secure, and patient-centric which has a great potential to contribute to improving the digitalization of healthcare quality of services in the healthcare system.

Estimation of prevalence of chronic Chagas disease in Brazilian municipalitiesEstimación de la prevalencia de la enfermedad de Chagas crónica en los municipios brasileños

The objective of this study is to estimate the prevalence of chronic Chagas disease (CCD) in Brazil: in the general population, in women, and in women of childbearing age. A meta-analysis of the literature was conducted to extract data on the prevalence of CCD in municipalities in Brazil in the 2010-2022 period: in the general population, in women, and in women of childbearing age. Municipal-level CCD indicators available in health information systems were selected. Statistical modeling of the data extracted from the meta-analysis (based on data obtained from information systems) was applied to linear, generalized linear, and additive models. The five most appropriate models were selected from a total of 549 models tested to obtain a consensus model (adjusted R2 = 54%). The most important predictor was self-reported CCD in the primary health care information system. Zero prevalence was estimated in 1 792 (32%) of Brazil's 5 570 municipalities; in the remaining 3 778 municipalities, average prevalence of the disease was estimated at 3.25% (± 2.9%). The number of carriers of CCD was estimated for the Brazilian population (~3.7 million), for women (~2.1 million) and for women of childbearing age (~590 000). The disease reproduction rate was calculated at 1.0336. All estimates refer to the 2015-2016 period. The estimated prevalence of CCD, especially among women of childbearing age, highlights the challenge of vertical transmission in Brazilian municipalities. Mathematical projections suggest that these estimates should be included in the national program for the elimination of vertical transmission of Chagas disease.

Healthcare Information Systems (HIS): Implementation Challenges in Developing Countries

In developing nations, the establishment of sustainable healthcare information systems (HIS) is often hindered by insufficient government policies and outdated technology. Bangladesh is a notable example where many patients lack proper healthcare access due to fragmented and non-digitally recorded data. Research has shown that standardized hospital healthcare systems can streamline patient management, increasing the capacity to serve more patients simultaneously. These systems have the potential to improve healthcare in developing nations significantly. This article offers an overview of the key obstacles that impede HIS implementation in these countries. The study looked at relevant information systems literature using a systematic literature review (SLR). The systematic literature review (SLR) was governed by a review process, and relevant studies were gathered from three databases: IEEE Xplore, EBSCO Databases, and ScienceDirect. A total of 4014 papers were initially found. However, only 11 main studies were included for analysis after a careful selection procedure governed by inclusion and exclusion criteria. This study found 24 obstacles to adopting Healthcare Information Systems (HIS) in developing countries, divided into six groups. These obstacles include a lack of financial assistance, inadequate infrastructure, inadequate education and awareness, cultural and political obstacles, reluctance to change, and poor system quality.
 Bangladesh Journal of Medical Science Vol. 23 No. 02 April’24 Page : 314-326

Nonspecific Effects of the Bacillus Calmette-Guérin Vaccine in Portuguese Children Under 5 Years of Age: Protocol for a Population-Based Historical Birth Cohort Study.

The Bacillus Calmette-Guérin vaccine (BCG) against tuberculosis (TB) shows beneficial nonspecific effects, which are likely related to innate immune training. Until 2016, a single BCG dose was administered to all newborns in Portugal. In July 2016, a clinical guideline established that only children under 6 years belonging to high-risk groups should receive BCG. This might have prevented nonvaccinated children from developing trained immunological responses as effectively as BCG-vaccinated children. This study aims to investigate if there is variation in TB-related and all-cause mortality, and severe, moderate, or mild morbidity in children under 5 years of age, and whether such variation might be explained by the BCG vaccination policy change in 2016. This population-based historical birth cohort study includes children under 5 years of age born in Portugal between July 1, 2010, and June 30, 2021. Newborns with low birth weight, premature status, or known or suspected HIV infection are excluded. The follow-up period is until the completion of 5 years of age or the end of follow-up (June 30, 2021). The study will use secondary data from the National Health Service user registry, death certificate database, vaccination registry, communicable diseases surveillance system, TB surveillance system, diagnosis-related group information system for hospital admissions and emergency department visits, and primary health care information system. The data will be linked. Primary outcomes include person-time incidence rates of death (all causes and TB), TB diagnosis, and all causes and some specific causes of severe, moderate, or mild morbidity, and the incidence rate ratio of nonvaccinated to BCG-vaccinated children. We will compare the probability of surviving the first and fifth years of life or of not having severe, moderate, or mild morbidity during the follow-up period according to exposure (BCG vaccinated or nonvaccinated, number of doses, and time from birth until the first dose), using the log-rank test for assessing differences in survival rates between exposed and nonexposed children and hazard ratios for quantifying the differences. Moreover, we will perform a proportional hazards regression analysis. Ethics approval has been obtained. In March 2022, database owners were contacted to present the project and discuss the request for data. A unique identifier will be used. In July 2023, a process of redefinition of the variables per database was initiated. Data were received in October and November 2023. In November 2023, further work was conducted. By April 2024, we expect to start analyzing the full data set. The results will contribute to the accumulating body of knowledge and might have relevance to guide global BCG vaccination policy. Data linkage can contribute to a swifter mechanism to use available health data to conduct population-based studies and inform policy decision-making. ClinicalTrials.gov NCT05471167; https://clinicaltrials.gov/study/NCT05471167. DERR1-10.2196/55332.

Cybersecurity Vulnerabilities in Healthcare: A Threat to Patient Security

Healthcare information systems hold significant importance; hence, their cybersecurity is crucial. Exposed networks make it easy for cybercriminals to launch cyberattacks and access healthcare data. Thus, concerns regarding cybersecurity and its link to healthcare privacy, confidential data, and medical devices are growing. Therefore, cybersecurity vulnerabilities in healthcare and patient security are significant issues. Healthcare information systems comprise correlated networks and play a vital role in treating and saving patients. However, advanced circulated ransomware attacks on hospitals prevent access to electronic health records for providing appropriate patient care, thus forcing doctors to turn to other facilities. These cyberattacks can leak patient data, and regaining control of information systems and patient data is highly expensive, thus resulting in extensive monetary losses. Cyberattacks aimed toward electronic medical records, information technology systems, and medical devices have corrupted the best systems across clinics and small offices with physicians, as well as merged health systems. There is an urgency to address cybersecurity vulnerabilities in healthcare; however, opinions differ regarding suitable measures for safeguarding patient data and ensuring infrastructural security. We aimed to reconcile these diverging hypotheses and provide an understanding of the current landscape and directions for further improvements by reviewing several studies on healthcare cybersecurity. We also interviewed healthcare professionals, cybersecurity experts, and administrators and distributed a survey questionnaire to healthcare organizations to gather quantitative data on existing cybersecurity measures and vulnerabilities. Our analyses show that healthcare organizations are vulnerable to a variety of threats, cyberattacks disrupt the health sector, cybersecurity vulnerabilities impact patient security, and implementations of cybersecurity measures are inconsistent across organizations. Owing to the sophisticated nature of cyberattacks, the healthcare industry must prioritize cybersecurity and provide the funding required to develop critical systems for safeguarding patients and their data. The study's findings underscore the need for standardized cybersecurity practices in healthcare to address inconsistencies in measures across organizations. Adequate and ongoing investment in cybersecurity infrastructure is imperative to counter increasingly sophisticated cyberattacks. Additionally, protecting patient data and maintaining trust within the healthcare sector are ethical imperatives that should guide industry actions. By embracing these implications, the healthcare industry can enhance patient security, financial stability, and ethical integrity.

Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis of Hemodialysis Electronic Health Record Implementation.

The Nephrology Department of Hassan II Hospital in Fez, Morocco, has implemented an Electronic Medical Record (EMR) system for managing patients undergoing acute hemodialysis. This initiative aims to digitize patient monitoring and enhance the management of acute dialysis within the department. Conducting strengths, weaknesses, opportunities, and threats (SWOT) analysis - assessing strengths, weaknesses, opportunities, and threats - was crucial to identifying and understanding the internal strengths and weaknesses, as well as the external opportunities and threats. This article outlines the SWOT analysis findings that may impact the project's success and shape decision-making. It also discusses strategies that could be implemented to allocate resources, mitigate risks, and capitalize on potential advantages. This study involved a multidisciplinary team, including professors, nephrologists, nephrology residents, and a healthcare information system engineer. Brainstorming sessions were held during the specification drafting phase to pinpoint both internal and external factors affecting the project. User feedback during testing further refined these factors, ensuring the project's alignment with real-world needs and challenges. The study identifies the project's strengths as providing safe and immediate access to information, along with strong communication between the department (application users) and the project manager. The significant EMR weakness is the lack of logistical resources and the absence of a long-term maintenance plan for the application. The opportunity presented by this EMR implementation is its functionality's potential to evolve, enabling the solution to be deployed in other dialysis centers across the region. The project's threat is the potential abandonment of EMR use by future practitioners. These SWOT analysis findings enable the development and implementation of strategies to reduce the current deployment's vulnerabilities and ensure the success of future HIS implementations in the nephrology network of the Fez-Meknes region, Morocco.

Design organization and clinical processes around patient characteristics: Evidence from a multiple case study of Hemophilia.

Background: There is growing evidence of the relevance of designing organization of care around patient characteristics; this is especially true in the case of complex chronic diseases.Purpose: The goal of the paper - that focuses on the analysis of the clinical condition hemophilia in three different centers - is to address two different research questions:1. How can we define, within the same clinical condition, different patient profiles homogeneous in terms of intensity of service required (e.g. number of visits or diagnostics)? 2. What are the conditions to re-organize care around these patient profiles in a multidisciplinary and coordinated manner?Research design: The authors have used a multiple case study approach combining both qualitative and quantitative methodologies; in particularly the semi-structured interviews and the direct observation were aimed to map the process in order to come up with an estimate of the cost of the full cycle of care.Study sample: The research methodology has been applied consistently in three different centers. The selection of the structures has been based on two main different criteria: (i) high standards regarding both organizational and clinical aspects and (ii) willingness from management, nurses and physicians to provide data.Results: The study clearly shows that different patient profiles - within the same clinical condition - trigger a different set of diagnostic and therapeutic activities. It is, thus, important considering patient characteristics in the development and implementation of clinical pathways and this will imply relevant differences in terms of organizational and economic impact.Conclusions: These process-based analyses are very much critical especially if we want to move to a bundled and integrated payment system but, as shown by this study itself, require a lot of time and efforts since our healthcare information systems are still fragmented and vertically designed.

State of the Art on the Contributions and Use of Geographic Information Systems (GIS) in Epidemiology in Morocco

Background The Geographic Information System (GIS) plays a significant role in the healthcare information system. The use of GIS as an epidemiological research tool is very little known in Morocco. According to the Moroccan Ministry of Health's Health Plan for 2025, axis 23 aims to complete the deployment of the decision support information system through the implementation of the geographic information system with the goal of improving governance and optimizing resource allocation. This creates constraints in achieving the design of an appropriate GIS for modeling pathologies using remote sensing and spatial statistical methods. The current work aims to understand GIS and its applications in epidemiology, with a focus on the state of scientific knowledge related to GIS in epidemiological research. Methods A state-of-the-art review of the various uses of GIS in epidemiological research was conducted using several university databases, such as PubMed and Scopus, recent articles, and certain reference books, focusing on the following keywords: “utilization,” “GIS,” and “epidemiology,” as well as their synonyms identified by MeSH. Results The majority of GIS research applied to epidemiology primarily involves making observations using GIS, which are then incorporated into action plans to promote population health. Therefore, it is important to break down the aspects of GIS (Geographic Information System) usage in epidemiology into four components. These include epidemiological surveillance, determining primary healthcare needs, healthcare planning, and healthcare quality. Conclusion These results clearly demonstrate the significant contribution of GIS to the improvement of public health. However, there is a need for positive action regarding the integration of this system, especially in developing countries.

Revolutionizing healthcare information systems with blockchain.

Revolutionizing healthcare information systems with blockchain.

Facilitators and Barriers to Scaling-Up Integrated Care for Arterial Hypertension and Type 2 Diabetes in Slovenia: Qualitative Study.

Arterial hypertension and type 2 diabetes are significant contributors to global non-communicable disease-related mortality. Integrated care, centred on person-centred principles, aims to enhance healthcare quality and access, especially for vulnerable populations. This study investigates integrated care for these diseases in Slovenia, providing a comprehensive analysis of facilitators and barriers influencing scalability. Qualitative methods, including focus group discussions and semi-structured interviews, were employed in line with the grounded theory approach. Participants represented various levels (micro, meso and macro), ensuring diverse perspectives. Data were collected from May 2019 to April 2020, until reaching saturation. Transcripts were analysed thematically using NVivo software. Nine categories emerged: Governance, Health financing, Organisation of healthcare, Health workforce, Patients, Community links, Collaboration/Communication, Pharmaceuticals, and Health information systems. Some of identified barriers were political inertia and underutilisation of research findings in practice; outdated health financing system; accessibility challenges, especially for vulnerable populations; healthcare workforce knowledge and burnout; patients' complex role in accepting and managing their conditions; collaboration within healthcare teams; and fragmentation of health information systems. Peer support and telemedicine were the only two potential solutions identified. This study offers a comprehensive evaluation of integrated care for hypertension and type 2 diabetes in Slovenia, featuring insights into facilitators and barriers. These findings have implications for policy and practice. Monitoring integrated care progress, refining strategies, and enhancing care quality for patients with these two diseases should be priorities in Slovenia.

Health Data Sharing with the Goal of Value Creation; Trying to Develop a Framework Using Qualitative Content Analysis.

Within the field of data sharing, discussions surrounding privacy concerns and big data management are extensive. This study aimed to provide a comprehensive framework for health data sharing with the objective of creating value. This study is a qualitative content analysis, which was conducted using a combination of written sources through a systematic review method, in conjunction with content derived from interviews with experts in information technology and healthcare within hospital and emergency settings. Grounded theory serves as the qualitative methodology, involving three coding phases: open, axial, and selective, facilitated by MAXQDA software. Qualitative content analysis of the interviews revealed seven main (core) categories and 44 subcategories as driving factors in promoting healthcare data sharing. Simultaneously, inhibiting factors resulted in six main categories and 36 subcategories. The driving factors encompassed technology, education, patient management improvement, data utilization for various purposes, data-related considerations, legal and regulatory aspects, and health-related factors. Conversely, inhibiting factors encompassed security and privacy concerns, legal issues, external organizational influences, monitoring and control activities, financial considerations, and inter-organizational challenges. This study has identified key driving and inhibiting factors that influence the sharing of healthcare data. These factors contribute to a more comprehensive understanding of the dynamics surrounding data sharing within the healthcare information system.

Measuring what counts in Aboriginal and Torres Strait Islander care: a review of general practice datasets available for assessing chronic disease care.

Background Large datasets exist in Australia that make de-identified primary healthcare data extracted from clinical information systems available for research use. This study reviews these datasets for their capacity to provide insight into chronic disease care for Aboriginal and Torres Strait Islander peoples, and the extent to which the principles of Indigenous Data Sovereignty are reflected in data collection and governance arrangements. Methods Datasets were included if they collect primary healthcare clinical information system data, collect data nationally, and capture Aboriginal and Torres Strait Islander peoples. We searched PubMed and the public Internet for data providers meeting the inclusion criteria. We developed a framework to assess data providers across domains, including representativeness, usability, data quality, adherence with Indigenous Data Sovereignty and their capacity to provide insights into chronic disease. Datasets were assessed against the framework based on email interviews and publicly available information. Results We identified seven datasets. Only two datasets reported on chronic disease, collected data nationally and captured a substantial number of Aboriginal and Torres Strait Islander patients. No dataset was identified that captured a significant number of both mainstream general practice clinics and Aboriginal Community Controlled Health Organisations. Conclusions It is critical that more accurate, comprehensive and culturally meaningful Aboriginal and Torres Strait Islander healthcare data are collected. These improvements must be guided by the principles of Indigenous Data Sovereignty and Governance. Validated and appropriate chronic disease indicators for Aboriginal and Torres Strait Islander peoples must be developed, including indicators of social and cultural determinants of health.

Measuring what counts in Aboriginal and Torres Strait Islander care: a review of general practice datasets available for assessing chronic disease care.

Background Large datasets exist in Australia that make de-identified primary healthcare data extracted from clinical information systems available for research use. This study reviews these datasets for their capacity to provide insight into chronic disease care for Aboriginal and Torres Strait Islander peoples, and the extent to which the principles of Indigenous Data Sovereignty are reflected in data collection and governance arrangements. Methods Datasets were included if they collect primary healthcare clinical information system data, collect data nationally, and capture Aboriginal and Torres Strait Islander peoples. We searched PubMed and the public Internet for data providers meeting the inclusion criteria. We developed a framework to assess data providers across domains, including representativeness, usability, data quality, adherence with Indigenous Data Sovereignty and their capacity to provide insights into chronic disease. Datasets were assessed against the framework based on email interviews and publicly available information. Results We identified seven datasets. Only two datasets reported on chronic disease, collected data nationally and captured a substantial number of Aboriginal and Torres Strait Islander patients. No dataset was identified that captured a significant number of both mainstream general practice clinics and Aboriginal Community Controlled Health Organisations. Conclusions It is critical that more accurate, comprehensive and culturally meaningful Aboriginal and Torres Strait Islander healthcare data are collected. These improvements must be guided by the principles of Indigenous Data Sovereignty and Governance. Validated and appropriate chronic disease indicators for Aboriginal and Torres Strait Islander peoples must be developed, including indicators of social and cultural determinants of health.

Evaluation of the impact of the implementation of the new primary health care information system on records of patient care and home visits in Brazil

The replacement of the Primary Care Information System (SIAB, 1998-2015), as of January 2016, by the new Health Information System for Primary Care (SISAB) determined new forms of collecting, processing, and using information, with a possible impact on the records of activities carried out in primary health care in Brazil. This study aimed to evaluate the implementation impact of the new information system on records of physicians' and nurses' patient care and home visits of community health workers (CHW) in Brazil from 2007 to 2019. To this end, a Bayesian structural time-series model approach was used, based on a diffuse state-space regression. From 2016 to 2019, 463.47 million physician care, 210.61 million nursing care, and 1.28 billion CHW visits were recorded. Following the trend recorded before the implementation, 598.86 million, 430.46 million, and 1.5 billion physician and nursing appointments and CHW visits would be expected, respectively. In relative terms, there was a decrease of 25% in physician care, 51% in nursing care, and 15% in CHW visits when compared to the value expected by the Bayesian method. The negative impact on the records of patient care and home visits identified in this study, whether due to difficulties in adapting to the new system or a reduction in improper records, must be investigated so that the challenge of improving the primary care information system can be understood and overcome in a planned way.

Artificial Intelligence Research in Healthcare Information Systems Management: A Systematic Review using Thematic Analysis and Topic Modelling

Artificial Intelligence Research in Healthcare Information Systems Management: A Systematic Review using Thematic Analysis and Topic Modelling