Healthcare Information Technology Research Articles

Benefits of Information Technology in Healthcare: Artificial Intelligence, Internet of Things, and Personal Health Records.

Systematic evaluations of the benefits of health information technology (HIT) play an essential role in enhancing healthcare quality by improving outcomes. However, there is limited empirical evidence regarding the benefits of IT adoption in healthcare settings. This study aimed to review the benefits of artificial intelligence (AI), the internet of things (IoT), and personal health records (PHR), based on scientific evidence. The literature published in peer-reviewed journals between 2016 and 2022 was searched for systematic reviews and meta-analysis studies using the PubMed, Cochrane, and Embase databases. Manual searches were also performed using the reference lists of systematic reviews and eligible studies from major health informatics journals. The benefits of each HIT were assessed from multiple perspectives across four outcome domains. Twenty-four systematic review or meta-analysis studies on AI, IoT, and PHR were identified. The benefits of each HIT were assessed and summarized from a multifaceted perspective, focusing on four outcome domains: clinical, psycho-behavioral, managerial, and socioeconomic. The benefits varied depending on the nature of each type of HIT and the diseases to which they were applied. Overall, our review indicates that AI and PHR can positively impact clinical outcomes, while IoT holds potential for improving managerial efficiency. Despite ongoing research into the benefits of health IT in line with advances in healthcare, the existing evidence is limited in both volume and scope. The findings of our study can help identify areas for further investigation.

Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study.

Artificial intelligence (AI) is often promoted as a potential solution for many challenges health care systems face worldwide. However, its implementation in clinical practice lags behind its technological development. This study aims to gain insights into the current state and prospects of AI technology from the stakeholders most directly involved in its adoption in the health care sector whose perspectives have received limited attention in research to date. For this purpose, the perspectives of AI researchers and health care IT professionals in North America and Western Europe were collected and compared for profession-specific and regional differences. In this preregistered, mixed methods, cross-sectional study, 23 experts were interviewed using a semistructured guide. Data from the interviews were analyzed using deductive and inductive qualitative methods for the thematic analysis along with topic modeling to identify latent topics. Through our thematic analysis, four major categories emerged: (1) the current state of AI systems in health care, (2) the criteria and requirements for implementing AI systems in health care, (3) the challenges in implementing AI systems in health care, and (4) the prospects of the technology. Experts discussed the capabilities and limitations of current AI systems in health care in addition to their prevalence and regional differences. Several criteria and requirements deemed necessary for the successful implementation of AI systems were identified, including the technology's performance and security, smooth system integration and human-AI interaction, costs, stakeholder involvement, and employee training. However, regulatory, logistical, and technical issues were identified as the most critical barriers to an effective technology implementation process. In the future, our experts predicted both various threats and many opportunities related to AI technology in the health care sector. Our work provides new insights into the current state, criteria, challenges, and outlook for implementing AI technology in health care from the perspective of AI researchers and IT professionals in North America and Western Europe. For the full potential of AI-enabled technologies to be exploited and for them to contribute to solving current health care challenges, critical implementation criteria must be met, and all groups involved in the process must work together.

Dynamic and Energy Efficient Cache Scheduling Framework for IoMT over ICN

The Internet of Medical Things (IoMT) is the network of medical devices, hardware infrastructure, and software applications used to connect the healthcare information technology. Massive traffic growth and user expectations cause challenges in the current exhausting models of IoMT data. To reduce the IoMT traffic, Information Centric Network (ICN) is a suitable technique. ICN uses persistent naming multicast communication that reduces the response time. ICN in IoMT provides a promising feature to reduce the overhead due to the distribution of commonly accessed contents. Some parameters such as energy consumption, communication cost, etc., influence the performance of sensors in the IoMT network. Excessive and unbalanced energy consumption degrades the network performance and lifetime. This article presents a framework called Dynamic Cache Scheme (DCS) that implements energy-efficient cache scheduling in IoMT over ICN to reduce network traffic. The proposed framework establishes a balance between the multi-hop traffic and data item freshness. The technique improves the freshness of data; thus, updated data are provided to the end-users via the effective utilization of caching in IoMT. The proposed framework is tested on important parameters, i.e., cache-hit-ratio, stretch, and content retrieval latency. The results obtained are compared with the state-of-the-art models. Results’ analysis shows that the proposed framework outperforms the compared models in terms of cache-hit-ratio, stretch, and content retrieval latency by 59.42%, 32.66%, and 18.8%, respectively. In the future, it is intended to explore the applicability of DCS in more scenarios and optimize further.

The Large-Scale Implementation of a Health Information System in Brazilian University Hospitals: Process and Outcomes.

Governments around the globe are paving the way for healthcare services that can have a profound impact on the overall well-being and development of their nations. However, government programs to implement health information technologies on a large-scale are challenging, especially in developing countries. In this article, the process and outcomes of the large-scale implementation of a hospital information system for the management of Brazilian university hospitals are analyzed. Based on a qualitative approach, this research involved 21 hospitals and comprised a documentary search, interviews with 24 hospital managers and two system user focus groups, and a questionnaire of 736 respondents. Generally, we observed that aspects relating to the wider context of system implementation (macro level), the managerial structure, cultural nuances, and political dynamics within each hospital (meso level), as well as the technology, work activities, and individuals themselves (micro level) acted as facilitators and/or obstacles to the implementation process. The dynamics and complex interactions established between these aspects had repercussions on the process, including the extended time necessary to implement the national program and the somewhat mixed outcomes obtained by hospitals in the national network. Mostly positive, these outcomes were linked to the eight emerging dimensions of practices and work processes; planning, control, and decision making; transparency and accountability; optimization in the use of resources; productivity of professionals; patient information security; safety and quality of care; and improvement in teaching and research. We argued here that to maximize the potential of information technology in healthcare on a large-scale, an integrative and cooperative vision is required, along with a high capacity for change management, considering the different regional, local, and institutional contexts.

Electronic connectivity between hospital pairs: impact on emergency department-related utilization.

To use more precise measures of which hospitals are electronically connected to determine whether health information exchange (HIE) is associated with lower emergency department (ED)-related utilization. We combined 2018 Medicare fee-for-service claims to identify beneficiaries with 2 ED encounters within 30days, and Definitive Healthcare and AHA IT Supplement data to identify hospital participation in HIE networks (HIOs and EHR vendor networks). We determined whether the 2 encounters for the same beneficiary occurred at: the same organization, different organizations connected by HIE, or different organizations not connected by HIE. Outcomes were: (1) whether any repeat imaging occurred during the second ED visit; (2) for beneficiaries with a treat-and-release ED visit followed by a second ED visit, whether they were admitted to the hospital after the second visit; (3) for beneficiaries discharged from the hospital followed by an ED visit, whether they were admitted to the hospital. In adjusted mixed effects models, for all outcomes, beneficiaries returning to the same organization had significantly lower utilization compared to those going to different organizations. Comparing only those going to different organizations, HIE was not associated with lower levels of repeat imaging. HIE was associated with lower likelihood of hospital admission following a treat-and-release ED visit (1.83 percentage points [-3.44 to -0.21]) but higher likelihood of admission following hospital discharge (2.78 percentage points [0.48-5.08]). Lower utilization for beneficiaries returning to the same organization could reflect better access to information or other factors such as aligned incentives. HIE is not consistently associated with utilization outcomes reflecting more coordinated care in the ED setting.

The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions

ABSTRACT In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management).

Electronic Health Record Adolescent Confidentiality in a Safety Net Setting.

The 21st Century Cures Act provides improved access to one's medical record but presents new challenges to adolescent confidentiality in the domain of health care information technology. Adolescent patients, who have the right to confidential care in certain areas as dictated by state law, face the prospect of parents and guardians erroneously accessing their confidential health information. Our institution, the largest safety net hospital in our region, sought to quantify the proportion of adolescent patient portal accounts likely being accessed by guardians and to implement corrective measures for the patient portal sign-up process in our electronic health record (EHR) system. We manually reviewed our institution's adolescent patient portal accounts based on email addresses associated with adolescents' accounts. We implemented EHR changes to address the potential for breach of confidentiality as a result of adolescent patient portal account creation by guardians. One intervention was creating a "guardrail rule" to prevent guardians from creating adolescent patient portal accounts with their own email addresses. After email reminders to adolescent patients to update their accounts, we deactivated accounts with concern for erroneous guardian access. Sixty percent of our institution's adolescent patient portal accounts had possible direct access by guardians. Following requests to update account access, 425 (18.8%) of accounts had email addresses updated by adolescent patients and 1,830 (81.2%) accounts were deactivated. More nuanced EHR functionality for adolescent patients and their guardians can help health care systems provide confidential, patient-centered care for adolescents, while allowing guardians to access appropriate health information to facilitate care. There is an opportunity for a national consensus on how adolescents and their guardians can access health information by patient portal.

Телемедицина: определение, особенности внедрения в практику, эффективность и перспективы применения в кардиологии

INTRODUCTION: Information and communication technologies in healthcare were realized in the advent of telemedicine (TM). This article presents current definitions, as well as describes the existing difficulties of terminology and classification. The main documents regulating the use of TM technologies in Russia at present are given. It is noted that the development of TM and its introduction into clinical practice is associated with a number of barriers that are associated with patients, medical professionals, as well as various technical, legal, ethical and economic problems. The presented article refers to a narrative review focused on some sources for the purpose of an unstructured description of the direction of interest. The search for literary sources was carried out in PubMed, eLibrary systems for 1995–2023 by keywords: telemedicine, telemedicine technologies, telemedicine in cardiology, telemedicine efficiency, remote control systems, telemonitoring, telemedicine in practice. The article presents the information about the role of TM in certain groups of cardiac patients, namely in patients with implanted medical devices, hypertension, chronic heart failure, high cardiovascular risk, as well as the elderlypatients and in cardiac rehabilitation. Changes in the areas of TM use are discussed, namely, attempts to use it in emergency pathology, in particular in acute coronary syndrome. CONCLUSION: Despite the absence of a common global practice and approaches to TM and the well-known barriers restraining its development, the prospects of this direction are beyond doubt. The spread of new TM technologies contributes to the improvement of providing health services system. It allows doctors to work with patients more efficiently and increases the opportunities of patients to receive expert advice. The accumulated scientific knowledge, the gradual adaptation of TM to the user’s needs, taking into account practical experience, make it possible to use this technology successfully in different groups of cardiac patients. In the future, artificial intelligence will be connected and trained to expand the opportunities for remote data analysis and the possibility of remote monitoring of patients' health, related regulatory issues will be resolved, as well as of the liability of the parties will be clearly defined. In the context of increasing demand for TM with an increase in the level of security of services provided and data protection, a global spread of advanced professional knowledge and skills is expected to improve public health.

Towards interoperability in infection control: a standard data model for microbiology

The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declared antimicrobial resistance one of the top global public health threats that humanity is facing. In this article, we describe how we developed a common model for microbiology data in an interdisciplinary collaborative effort and how we make use of the standard HL7 FHIR and terminologies such as SNOMED CT or LOINC to ensure syntactic and semantic interoperability. The use of international healthcare standards qualifies our data model to be adopted beyond the environment where it was first developed and used at an international level.

Reflections on the history of interoperability in hospitals.

To discuss the origins of HL7 and its subsequent impact on interoperability in hospitals. Reconstruction of historical events from review of personal notes, interviews with key participants and review of relevant publications. The first versions of HL7 were based on the StatLAN protocol developed at the University of California, San Francisco and later commercialized by Simborg Systems Corporation. With the emergence of specialty clinical and departmental systems in the 1990s, a debate ensued between proponents of "open architecture" vs. "single vendor" systems. Although HL7 became the most widely used data-interchange protocol worldwide in healthcare, open architecture did not prevail in healthcare as it did in other industries. This is due to the unique market characteristics of the healthcare provider industry. The result today is the dominance of the healthcare IT marketplace by a small number of large vendors with relatively few options for in-depth specialty clinical systems.

Development of STEM training of specialists in the field of information technology in healthcare through educational collaboration of universities

The article discusses the issues of training STEM specialists in the implementation of joint educational programs (JEP) of medical and technical universities in the field of information technology in healthcare. A model of JEP training is proposed through the collaboration of professional standards, learning outcomes, requirements for specialists imposed by production partners, which allow to increase the efficiency of the do[1]mestic education system.

Leveraging the E-commerce footprint for the surveillance of healthcare utilization.

The utilization of healthcare services serves as a barometer for current and future health outcomes. Even in countries with modern healthcare IT infrastructure, however, fragmentation and interoperability issues hinder the (short-term) monitoring of utilization, forcing policymakers to rely on secondary data sources, such as surveys. This deficiency may be particularly problematic during public health crises, when ensuring proper and timely access to healthcare acquires special importance. We show that, in specific contexts, online pharmacies' digital footprint data may contain a strong signal of healthcare utilization. As such, online pharmacy data may enable utilization surveillance, i.e., the monitoring of short-term changes in utilization levels in the population. Our analysis takes advantage of the scenario created by the first wave of the Covid-19 pandemic in Mainland China, where the virus' spread lead to pervasive and deep reductions of healthcare service utilization. Relying on a large sample of online pharmacy transactions with full national coverage, we first detect variation that is strongly consistent with utilization reductions across geographies and over time. We then validate our claims by contrasting online pharmacy variation against credit-card transactions for medical services. Using machine learning methods, we show that incorporating online pharmacy data into the models significantly improves the accuracy of utilization surveillance estimates.

MedRSS: A blockchain-based scheme for secure storage and sharing of medical records

Due to the rapid advance of Healthcare Information Technology (HIT), the amount of medical data has increased dramatically and highly demands correct and secure storage and exchange. However, centralized medical record management systems suffer from privacy breaches, data manipulation, and insufficient shareability. In this article, we propose a blockchain-based solution for medical record data storage and sharing (MedRSS), where we apply Hyperledger fabric blockchain and encryption technology to create a secure environment for medical record data storage and sharing. Blockchain technology is used to ensure that medical records are proof of tampering, smart contracts are used to control access to data users, and cryptography is used to encrypt medical record data and digitalize sign messages. Experiments have shown that MedRSS ensures the accuracy, integrity, and security of medical records and high access throughput, outperforming existing approaches.

Integrating Information Technology in Healthcare: Recent Developments, Challenges, and Future Prospects for Urban and Regional Health

The use of technology in healthcare has become increasingly popular in recent years, with the potential to improve how healthcare is delivered, patient outcomes, and cost-effectiveness. This review paper provides an overview of how technology has been used in healthcare, particularly in cities and for personalized medicine. The paper discusses different ways technology is being used in healthcare, such as electronic health records, telemedicine, remote monitoring, medical imaging, wearable devices, and artificial intelligence. It also looks at the challenges and problems that come with using technology in healthcare, such as keeping patient data private and secure, making sure different technology systems can work together, and ensuring patients are comfortable using technology. In addition, the paper explores the potential of technology in healthcare, including improving how easily patients can get care, the quality of care they receive, and the cost of care. It also talks about how technology can help personalize care to individual patients. Finally, the paper summarizes the main points, makes recommendations for healthcare providers and policymakers, and suggests directions for future research. Overall, this review shows how technology can be used to improve healthcare, while also acknowledging the challenges that come with using technology in this way.

The Stanford Medicine data science ecosystem for clinical and translational research.

To describe the infrastructure, tools, and services developed at Stanford Medicine to maintain its data science ecosystem and research patient data repository for clinical and translational research. The data science ecosystem, dubbed the Stanford Data Science Resources (SDSR), includes infrastructure and tools to create, search, retrieve, and analyze patient data, as well as services for data deidentification, linkage, and processing to extract high-value information from healthcare IT systems. Data are made available via self-service and concierge access, on HIPAA compliant secure computing infrastructure supported by in-depth user training. The Stanford Medicine Research Data Repository (STARR) functions as the SDSR data integration point, and includes electronic medical records, clinical images, text, bedside monitoring data and HL7 messages. SDSR tools include tools for electronic phenotyping, cohort building, and a search engine for patient timelines. The SDSR supports patient data collection, reproducible research, and teaching using healthcare data, and facilitates industry collaborations and large-scale observational studies. Research patient data repositories and their underlying data science infrastructure are essential to realizing a learning health system and advancing the mission of academic medical centers. Challenges to maintaining the SDSR include ensuring sufficient financial support while providing researchers and clinicians with maximal access to data and digital infrastructure, balancing tool development with user training, and supporting the diverse needs of users. Our experience maintaining the SDSR offers a case study for academic medical centers developing data science and research informatics infrastructure.

The Role of Cloud Computing in Modernizing Healthcare IT Infrastructure

The modernization of healthcare IT infrastructure has been aided by cloud computing, which has revolutionized the methods for storing, processing, and accessing medical data. In order to better understand how cloud computing is contributing to the advancement of healthcare technology, this study will concentrate on how it affects the handling of data, seamless integration, and system efficiency in general. Significant benefits come from the use of cloud computing in healthcare, including improved scalability and flexibility in managing enormous volumes of patient data. By leveraging storage via cloud solutions, health care providers can seamlessly multiply the information they store storage capabilities, welcoming an increasing number of medical data and diagnostic imaging. Healthcare practitioners may now access data more easily thanks to its scalability, which encourages prompt and well-informed decision-making. Furthermore, cloud computing promotes smooth communication and data interchange by facilitating interoperability across heterogeneous healthcare systems. The integration of electronic medical records, or EHRs, and other health information systems is made possible by standardized interfaces and protocols, which foster a cohesive healthcare ecosystem. This interoperability promotes a more comprehensive approach to the treatment of patients in addition to improving provider collaboration. The study also addresses the consequences of cloud computing for maintaining data security and regulatory compliance. To protect sensitive patient data, cloud service providers frequently have strong security measures in place, like encryption and access controls. Furthermore, cloud infrastructure's flexibility enables healthcare companies to easily adjust to changing regulatory requirements. A critical first step toward modernization is the incorporation of cloud computing into healthcare IT infrastructure. Cloud-based solutions' scalability, interoperability, and security not only solves immediate problems but also sets the healthcare sector up for future advancements in healthcare and information storage.

The Role of Healthcare Information Technology (HIT) in Health Care Level of Pakistan: A Literature Review

The Role of Healthcare Information Technology (HIT) in Health Care Level of Pakistan: A Literature Review

The gap between bachelor’s degree graduates in health informatics and employer needs in Saudi Arabia

BackgroundIn the field of health informatics (HI), there is a crucial gap between employers’ needs and the output of academic programmes. Although industrial organisations and government agencies recognise the importance of training and education in the development and operation of health-information systems, advancements in educational programmes have been comparatively slow in terms of investment in healthcare information technology. This study aims to determine the gap between employer demands and academic programmes in HI in Saudi Arabia.MethodsThis mixed-methods study collected both qualitative and quantitative data. A qualitative content analysis was performed to identify the role of advertised HI jobs using two sources: Google and LinkedIn. In addition, university websites were searched to determine job opportunities for graduates with a bachelor’s degree in HI. Next, a quantitative, cross-sectional self-report questionnaire was administered to validate the findings of the qualitative data. Data obtained were analysed using SPSS, N-Vivo, and Microsoft Excel.ResultsThe study’s data were obtained from four sources: Google search engine, LinkedIn, five Saudi university websites, and 127 HI experts. The results show a discrepancy between academic programmes’ outputs and employer recruitment needs. In addition, the results reveal a preference for post-graduate degrees, either a master’s or PhD degree, with a bachelor’s degree in a health or medical discipline.ConclusionsEmployers tend to prefer applicants with a bachelor’s degree in computer science or information technology over those with a degree in HI. Academic programmes should incorporate more practical applications and provide students with a thorough understanding of the healthcare industry to better equip them as efficient future HI professionals.

Differential Perceptions of What Constitutes a Medical Error Associated with Electronic Medical Records.

Perceptions of errors associated with healthcare information technology (HIT) often depend on the context and position of the viewer. HIT vendors posit very different causes of errors than clinicians, implementation teams, or IT staff. Even within the same hospital, members of departments and services often implicate other departments. Organizations may attribute errors to external care partners that refer patients, such as nursing homes or outside clinics. Also, the various clinical roles within an organization (e.g., physicians, nurses, pharmacists) can conceptualize errors and their root causes differently. Overarching all these perceptual factors, the definitions, mechanisms, and incidence of HIT-related errors are remarkably conflictual. There is neither a universal standard for defining or counting these errors. This paper attempts to enumerate and clarify the issues related to differential perceptions of medical errors associated with HIT. It then suggests solutions.

In support of interoperability: A laboratory perspective.

Healthcare in the United States has become increasingly digital since the passage of the HITECH Act in 2009. As a result, there is a growing need to optimize healthcare IT to allow for the interoperable exchange of data. As a result, the Office of the National Coordinator for Health IT has implemented their Final Rule for the 21st Century Cures Act. This requires certified health IT systems to use modernized messaging standards for the safe and secure exchange of data within health information networks and also requires the use of terminology standards including LOINC, SNOMED CT, and UCUM for coding clinical and laboratory data. Given the critical importance of laboratory results in the delivery of healthcare, laboratorians must become familiar with these principles of interoperability. Their clinical laboratory expertise is needed to appropriately structure and code test results to safeguard against improper aggregation or misinterpretation by downstream users and systems.