Health Information Exchange Systems Research Articles

Health Information Exchange between Specialists and General Practitioners Benefits Rural Patients.

Health information exchange (HIE) may improve diagnostic accuracy, treatment efficacy, and safety by providing treating physicians with expert advice. However, most previous studies on HIE have been observational in nature. To examine whether collaboration between specialists and general practitioners (GPs) in rural areas via HIE can improve outcomes among patients at low-to-moderate risk of cardiovascular disease, kidney disease, and stroke. In this randomized controlled trial, the Miyagi Medical and Welfare Information Network was used for HIE. We evaluated the clinical data of 1,092 patients aged ≥65 years living in the rural areas of the Miyagi Prefecture and receiving care from GPs only. High-risk patients were immediately referred to specialists, whereas low-to-moderate risk patients were randomly assigned to an intervention group in which GPs were advised by specialists through HIE (n = 518, 38% male, mean age = 76 ± 7 years) or a control group in which GPs received no advice by specialists (n = 521, 39% male, mean age = 75 ± 7 years). In the intention-to-treat analysis, all-cause mortality and cumulative incidence of serious adverse events (e.g., hospital admission or unexpected referral to specialists) did not differ between the groups. However, per-protocol analysis controlling for GP adherence with specialist recommendations revealed significantly reduced all-cause mortality (p = 0.04) and cumulative serious adverse event incidence (p = 0.04) in the intervention group compared with the control group. HIE systems may improve outcomes among low-to-moderate risk patients by promoting greater collaboration between specialists and GPs, particularly in rural areas with few local specialists.

The Impact of the Health Information Exchange System for the hospital management in Japan

The Impact of the Health Information Exchange System for the hospital management in Japan

MEXchange: A Privacy-Preserving Blockchain-Based Framework for Health Information Exchange Using Ring Signature and Stealth Address

Health information exchange (HIE) refers to the integrated management and secure sharing of health information among healthcare entities. HIE improves healthcare quality and streamline healthcare administrative work. These advantages have propelled health-care stakeholders to implement HIE. However, challenged by issues such as security, privacy, and costs, HIE is not widespread. Recent studies have suggested blockchain-based HIE for solving security and privacy issues. Unfortunately, existing blockchain-based HIE studies do not consider the privacy issues caused by analyzing senders and receivers of transactions in the blockchain. In this work, we suggest MEXchange, a novel blockchain-based privacypreserving HIE that prevents the privacy issue by obscuring the sender and concealing receiver addresses. We propose smart contracts and workflow that use ring signature and stealth address for blockchainbased HIE. Software components and implementation of MEXchange on the Ethereum private network are discussed. We evaluate MEXchange quantitatively by measuring the transaction latency and throughput of exchanging. Also, we evaluate MEXchange qualitatively using the requirements of the Office of National Coordinator for Health Information Technology (ONC). Moreover, we proceed threat modeling based on STRIDE. Finally, we compare MEXchange with Ancile, FHIRChain, Integrating the Healthcare Enterprise Cross-Enterprise Document Sharing (IHE XDS), and MedRec. The MEXchange lowers barriers to the application of blockchain-based HIE systems by mitigating privacy and security issues among healthcare stakeholders.

Can Orthodontic Informatics Combat the Pandemic Pitfalls?

The largest public health crisis of our time, COVID-19 has recklessly squandered many of the channelized healthcare facilities globally with execution of newer guidelines over the standard architectural norms. There has been unparalleled use of smartphones and internet services to bear the major pitfall- social distancing- especially for elective treatment services. This demands a new paradigm shift from offline to online doctor-patient, student-educator, researcher-researcher operations. This articles provides an insight into potential role of orthodontic informatics to provide a combined platform to generate a learning system that routinely collects, correlates, and analyzes data for developing artificial intelligence programs, lab exploratory systems, clinical decision support systems and health-information exchange systems. In order to develop this system, orthodontic analytic communities as start-ups for developing user-friendly programs must be encouraged, where orthodontic informatics itself can be taken up as a didactic career source.

Barriers and facilitators to a health information exchange system for general practitioners

Abstract Background Health information exchange (HIE) systems, that are computer-based tools used by healthcare providers for secure access to share patient's medical information electronically, seem to help reduce the use of specific resources and improve the quality of care. This highlights the importance of this issue in the Public Health sector. This research goal is to identify barriers and facilitators perceived by general practitioners (GPs) when using an HIE system in a Southern Switzerland area. Methods we performed a qualitative study using semi-structured interviews, interviewed 10 GPs, randomly selected among some 500 HIE system local users and analysed interview transcripts using thematic content analysis with an abductive approach (a mix of deductive and inductive approaches). Results findings showed the following key facilitators: a) perception of dealing with a secure system; b) possibility of delegating management to secretaries and healthcare assistants; c) technical support and training; d) high quality of the information exchange; e) positive impact on clinical practice; and f) regional context. However, major challenges persist, and GPs reported the following main barriers to using an HIE system: a) frequent lack of all patient information needed; b) no effective workflow improvements; c) lack of some technical features. Conclusions We propose four recommendations based on findings: 1. Future initiatives should focus on developing HIE systems giving GPs access to all possible patient medical information; 2. Crucial data privacy and security issues should never be overlooked; 3. Technical and workflow improvements should particularly consider the socio-technical nature of HIE systems; 4. Much attention needs to be paid to the importance of relationships between health care providers and between these and local health institutions when implementing HIE systems. Key messages This study filled a research gap as it is the first that tackles HIE system barriers and facilitators in Ticino. When information sharing for clinical practice focuses on improving the quality and costs of healthcare, GP's trust in HIE system security is crucial.

Mobile Technology Care Coordination of Long-Term Services and Support: Cluster Randomized Clinical Trial.

The purpose of the study was to assess whether the effects of a mobile predictive intervention used by Service Coordinators (SCs) reduce hospital utilization in a Medicaid Long-Term Services and Supports (LTSS) population in Baltimore city during a 5-month intervention. SC participants (n = 11) were recruited to treatment or control groups. LTSS clients (n = 420) followed their SC randomization assignment. Utilization data were obtained from the Maryland Chesapeake Regional Information System for our Patients (CRISP) Health Information Exchange (HIE) system and linked to service coordination records. Study groups were similar in age, gender, race, and years receiving LTSS. SCs' satisfaction with use of the mobile tool was surveyed. SC perceptions were neutral (mean scores ranged from 2.3 to 3.3 on a 5-point scale). No significant differences between groups were observed for all utilization metrics. The mobile technology software system used in this study did not improve health care utilization for a LTSS population needing ongoing clinical and social services coordinated care.

The effect of the privacy policy of Health Information Exchange (HIE) on patients’ information disclosure intention

Health Information Exchanges (HIEs) enable personal information sharing between providers. Patients’ information disclosure intention is critical for a successful rollout of HIE networks. Existing studies mostly demonstrate that perceived privacy policy only influences the cognitive beliefs of patients about disclosing health information. However, little is know whether it also affects the emotion provoked by the sharing nature of the technology. Based on the Theory of Reasoned Action (TRA), the technology adoption literature, and the trust literature, we theoretically explain and empirically test the impacts of perceived transparency of privacy policy on cognitive trust and emotional trust in an HIE, and the effects of trust dimensions on the intention to disclose health information. An online survey was conducted using data from individuals who were aware of HIE through experiences with a (or multiple) providers participating in an HIE network. The SEM analysis results provide empirical support for the proposed model. The model highlights the critical role of perceived transparency of privacy policy in building trust in HIE. Findings suggest that awareness about HIE security measures and sharing procedures encourages patients to be cognitively and emotionally involved with the HIE system. Consequently, when the trust is formed, they become more likely to disclose health information.

Assessing the Performance of an Integrated Health Information Exchange System Using Unstructured Supplementary Service Data

Assessing the Performance of an Integrated Health Information Exchange System Using Unstructured Supplementary Service Data

Advancing laboratory medicine in hospitals through health information exchange: a survey of specialist physicians in Canada

BackgroundLaboratory testing occupies a prominent place in health care. Information technology systems have the potential to empower laboratory experts and to enhance the interpretation of test results in order to better support physicians in their quest for better and safer patient care. This study sought to develop a better understanding of which laboratory information exchange (LIE) systems and features specialist physicians are using in hospital settings to consult their patients’ laboratory test results, and what benefit they derive from such use.MethodsAs part of a broader research program on the use of health information exchange systems for laboratory medicine in Quebec, Canada, this study was designed as on online survey. Our sample is composed of 566 specialist physicians working in hospital settings, out of the 1512 physicians who responded to the survey (response rate of 17%). Respondents are representative of the targeted population of specialist physicians in terms of gender, age and hospital location.ResultsWe first observed that 80% of the surveyed physicians used the province-wide interoperable electronic health records (iEHR) system and 93% used a laboratory results viewer (LRV) to consult laboratory test results and most (72%) use both systems to retrieve lab results. Next, our findings reveal important differences in the capabilities available in each type of system and in the use of these capabilities. Third, there are differences in the nature of the perceived benefits obtained from the use of each of these two systems. Last, the extent of use of an LRV is strongly influenced by the IT artefact itself (i.e., the hospital’s LRV available capabilities) while the use of the provincial iEHR system is influenced by its organizational context (i.e. the hospital’s size and location).ConclusionsThe main contribution of this study lies in its insights into the role played by context in shaping physicians’ choices about which laboratory information exchange systems to adopt and which features to use, and the different perceptions they have about benefits arising from such use. One related implication for practice is that success of LIE initiatives should not be solely assessed with basic usage statistics.

Opioid-Related Emergency Department Encounters: Patient, Encounter, and Community Characteristics Associated With Repeated Encounters

We describe the prevalence, trends, and factors associated with repeated emergency department (ED) encounters for opioid usage across multiple, independent hospital systems. A statewide regional health information exchange system provided ED encounters from 4 Indiana hospital systems for 2012 to 2017. In accordance with a series of International Classification of Diseases, Ninth Revision (ICD-9) and ICD-10 diagnosis codes for opioid abuse, adverse effects of opioids, opioid dependence and unspecified use, and opioid poisoning, we identified patients with an ED encounter associated with opioid usage (9,295 individuals; 12,642 encounters). Multivariate logistic regression models then described the patient, encounter, prescription history, and community characteristics associated with the odds of a patient's incurring a subsequent opioid-related ED encounter. The prevalence of repeated nonfirst opioid-related ED encounters increased from 9.0% of all opioid encounters in 2012 to 34.3% in 2017. The number of previous opioid-related ED encounters, unique institutions at which the individual had had encounters, the encounter's being heroin-related, the individual's having a benzodiazepine prescription filled within 30 days before the encounter, and being either Medicaid insured or uninsured compared with private insurance were associated with significantly greater odds of having a subsequent encounter. The ED is increasingly a site utilized as the setting for repeated opioid-related care. Characteristics of the individual, encounter, and community associated with repeated opioid-related encounters may inform real-time risk-prediction tools in the ED setting. Additionally, the number of institutions to which the individual has presented may suggest the utility of health information exchange data and usage in the ED setting.

Analysis of economic burden and its associated factors of twenty-three rare diseases in Shanghai

BackgroundIt is estimated that at present there are over 10 million rare disease patients in China. Recently an increased focus from policy perspective has been placed on rare diseases management. Improved disease definitions and the releases of local and national rare disease lists are some of the steps taken already. Despite these developments, few Chinese rare disease-related epidemiology and economic studies exist, thus hindering assessment of the true burden of rare diseases. For a rare disease with an effective treatment, this is a particularly important aspect due to the often-high cost associated.ObjectiveThe goal of this study is to address the data scarcity on the subject of rare diseases economic impact in China. We aim to address an existing knowledge gap and to provide a timely analysis of the economic burden of 23 rare diseases in Shanghai, China.MethodsWe utilized the data from the Health Information Exchange system of Shanghai and employed statistical modeling to analyze the economic burden of rare diseases with an effective treatment in Shanghai.ResultsFirst, we described the actual direct medical expenditure and analyzed its associated factors. Second, we found age, disease type, number of complications, and payment type were significantly associated with rare disease medical direct costs. Third, a generalized linear model was employed to estimate the annual direct cost. The mean direct medical cost was estimated as ¥9588 (US$1521) for inpatients and ¥1060 (US$168) for outpatients, and was over ¥15 million (~US$2.4 million) per year overall.ConclusionOur study is one of the first quantifying the economic burden of an extensive set of rare diseases in Shanghai and China. Our results can serve to inform healthcare-focused policy making, contribute to the increase of public awareness, and incentivize development of rare-disease strategies and treatments specific to the Chinese context.

Measuring and Visualizing Chlamydia and Gonorrhea Inequality: An Informatics Approach Using Geographical Information Systems.

Health inequality measurements are vital in understanding disease patterns in identifying high-risk patients and implementing effective intervention programs to treat and manage sexually transmitted diseases. To measure and identify inequalities among chlamydia and gonorrhea rates using Gini coefficient measurements and spatial visualization mapping from geographical information systems. Additionally, we seek to examine trends of disease rate distribution longitudinally over a ten-year period for an urbanized county. Chlamydia and gonorrhea data from January 2005 to December 2014 were collected from the Indiana Network for Patient Care, a health information exchange system that gathers patient data from electronic health records. The Gini coefficient was used to calculate the magnitude of inequality in disease rates. Spatial visualization mapping and decile categorization of disease rates were conducted to identify locations where high and low rates of disease persisted and to visualize differences in inequality. A multiple comparisons ANOVA test was conducted to determine if Gini coefficient values were statistically different between townships and time periods during the study. Our analyses show that chlamydia and gonorrhea rates are not evenly distributed. Inequalities in disease rates existed for different areas of the county with higher disease rates occurring near the center of the county. Inequality in gonorrhea rates were higher than chlamydia rates. Disease rates were statistically different when geographical locations or townships were compared to each other (p < 0.0001) but not for different years or time periods (p = 0.5152). The ability to use Gini coefficients combined with spatial visualization techniques presented a valuable opportunity to analyze information from health information systems in investigating health inequalities. Knowledge from this study can benefit and improve health quality, delivery of services, and intervention programs while managing healthcare costs.

Diabetes diagnosis from administrative claims and estimation of the true prevalence of diabetes among 4.2 million individuals of the Veneto region (North East Italy)

Background and aimsDiabetes can often remain undiagnosed or unregistered in administrative databases long after its onset, even when laboratory test results meet diagnostic criteria. In the present work, we analyse healthcare data of the Veneto Region, North East Italy, with the aims of: (i) developing an algorithm for the identification of diabetes from administrative claims (4,236,007 citizens), (ii) assessing its reliability by comparing its performance with the gold standard clinical diagnosis from a clinical database (7525 patients), (iii) combining the algorithm and the laboratory data of the regional Health Information Exchange (rHIE) system (543,520 subjects) to identify undiagnosed diabetes, and (iv) providing a credible estimate of the true prevalence of diabetes in Veneto. Methods and resultsThe proposed algorithm for the identification of diabetes was fed by administrative data related to drug dispensations, outpatient visits, and hospitalisations. Evaluated against a clinical database, the algorithm achieved 95.7% sensitivity, 87.9% specificity, and 97.6% precision. To identify possible cases of undiagnosed diabetes, we applied standard diagnostic criteria to the laboratory test results of the subjects who, according to the algorithm, had no diabetes-related claims. Using a simplified probabilistic model, we corrected our claims-based estimate of known diabetes (6.17% prevalence; 261,303 cases) to account for undiagnosed cases, yielding an estimated total prevalence of 7.50%. ConclusionWe herein validated an algorithm for the diagnosis of diabetes using administrative claims against the clinical diagnosis. Together with rHIE laboratory data, this allowed to identify possibly undiagnosed diabetes and estimate the true prevalence of diabetes in Veneto.

Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy).

Diabetes is a chronic illness characterised by elevated blood glucose levels, driving excess mortality. Its prompt detection and accurate management are critical for delaying complications. Nevertheless, diabetes can remain undiagnosed for years from the onset. The identification of undiagnosed diabetes is a public health priority: in Italy, it is estimated that up to 30% of diabetes cases remain undetected, i.e., that ~1.8 million citizens may be unaware they need medical help. Sometimes, this happens even though these subjects undergo routine or emergency check-ups. Veneto, a region in North-East Italy with 4.9 million residents, implements a regional Health Information Exchange system (rHIE) to collect healthcare data, including laboratory reports, and integrate them with administrative claims. Their combination may be instrumental in finding otherwise undetected cases of diabetes. On the one hand, known diabetic patients should have disease management-generated claims; on the other, laboratory test results can be independently evaluated against diagnostic criteria. In the present work, we examined the anonymised claims and laboratory data, extracted from the rHIE, of 23,376 citizens of the Veneto region. We compared their exemptions, diabetes-related hospitalisation discharge codes, and antidiabetic drugs between 2012 and 2018 to the results of their fasting glucose, glycated haemoglobin, and oral glucose tolerance tests in 2017-2018. We identified 1,407 (6.02%) subjects who, according to administrative claims, appear to be free from diabetes, but met at least one laboratory diagnostic criterion. Such a discrepancy suggests that these people may be undiagnosed diabetic patients. To the best of our knowledge, this is the first proof of concept of an automatic system for the detection of undiagnosed diabetes in Italy. Its full integration in the rHIE and its consequent capillary application could potentially reveal thousands of hidden cases throughout Veneto.

The Potential of Blockchain Technology for Health Information Exchange: Experimental Study From Patients' Perspectives.

BackgroundNowadays, a number of mechanisms and tools are being used by health care organizations and physicians to electronically exchange the personal health information of patients. The main objectives of different methods of health information exchange (HIE) are to reduce health care costs, minimize medical errors, and improve the coordination of interorganizational information exchange across health care entities. The main challenges associated with the common HIE systems are privacy concerns, security risks, low visibility of system transparency, and lack of patient control. Blockchain technology is likely to disrupt the current information exchange models utilized in the health care industry.ObjectiveLittle is known about patients’ perceptions and attitudes toward the implementation of blockchain-enabled HIE networks, and it is still not clear if patients (as one of the main HIE stakeholders) are likely to opt in to the applications of this technology in HIE initiatives. Thus, this study aimed at exploring the core value of blockchain technology in the health care industry from health care consumers’ views.MethodsTo recognize the potential applications of blockchain technology in health care practices, we designed 16 information exchange scenarios for controlled Web-based experiments. Overall, 2013 respondents participated in 16 Web-based experiments. Each experiment described an information exchange condition characterized by 4 exchange mechanisms (ie, direct, lookup, patient-centered, and blockchain), 2 types of health information (ie, sensitive vs nonsensitive), and 2 types of privacy policy (weak vs strong).ResultsThe findings show that there are significant differences in patients’ perceptions of various exchange mechanisms with regard to patient privacy concern, trust in competency and integrity, opt-in intention, and willingness to share information. Interestingly, participants hold a favorable attitude toward the implementation of blockchain-based exchange mechanisms for privacy protection, coordination, and information exchange purposes. This study proposed the potentials and limitations of a blockchain-based attempt in the HIE context.ConclusionsThe results of this research should be of interest to both academics and practitioners. The findings propose potential limitations of a blockchain-based HIE that should be addressed by health care organizations to exchange personal health information in a secure and private manner. This study can contribute to the research in the blockchain area and enrich the literature on the use of blockchain in HIE efforts. Practitioners can also identify how to leverage the benefit of blockchain to promote HIE initiatives nationwide.

Introduction to and Application Analysis of Taiwan’s NHI-MediCloud System

Between 2013 and 2016, Taiwan’s National Health Insurance (NHI) expenditure increased by 4.22%. The main expenses driving this growth were examination and test fees as well as medication costs, which accounted for 73% of all NHI expenses. In addition, patients repeating the same examinations or being prescribed the same medication at different hospitals caused a serious waste of resources. To inhibit the growth of NHI expenditure and improve medical safety, the NHI Administration established the NHI-MediCloud System. This health information exchange system assists doctors in consulting patients’ medical information, such as medication records from anywhere in the country, examination and test results, and image data. This study determined the current implementation status and difficulties of health information exchange systems and the development of medical cloud information systems. Furthermore, it introduced in detail the categories in and contents of the NHI-MediCloud System. In addition, this study presented hospitals’ application experiences and proposed suggestions for future applications. The results revealed that from 2014 to 2017, reducing the days of repeat medication saved approximately US$ 9.63 million in expenditure for the six main categories of medication. Among the 20 most common examinations and tests, cloud sharing saved approximately US$ 38.5 million. Integrating cloud data with hospital information systems and establishing a comparison and notification function in the medical cloud system remarkably increased doctors’ willingness to use the systems. Moreover, this function helped to reduce medical procedures such as prescribing medication, performing examinations and tests, conducting surgeries, and providing rehabilitation, as well as mitigated medication interactions and drug allergies. Thus, medical safety for patients was improved and the growth of NHI expenditure was effectively inhibited.

Potential impact of data source and interoperability messaging on health information technology (HIT) users: a study series from the United States Department of Veterans Affairs

BackgroundThe promise of Health Information Exchange (HIE) systems rests in their potential to provide clinicians and administrative staff rapid access to relevant patient data to support judgement and decision-making. However,...

A National Assessment of Access to Technology Among Nursing Home Residents: A Secondary Analysis.

BackgroundAccording to the National Center for Health Statistics, there are over 1.7 million nursing home residents in the United States. Nursing home residents and their family members have unique needs and stand to benefit from using technology empowering them to be more informed and engaged health care consumers. Although there is growing evidence for benefits of patient-facing technologies like electronic patient portals on patient engagement in acute and outpatient settings, little is known about use of this technology in nursing homes.ObjectiveThe purpose of this study was to report findings from a secondary analysis of data from a national nursing home study of information technology (IT) adoption, called IT sophistication. We describe the extent to which nursing homes (n=815) allow residents or their representatives to access technology including electronic health records, patient portals, and health information-exchange systems as well as the ability of the residents or representatives to self-report data directly into the electronic health record.MethodsWe used descriptive statistics and regression techniques to explore relationships between information technology adoption (IT sophistication) and residents’ or their representatives’ access to technology. Covariates of location, bed size, and ownership were added to the model to understand their potential influence on the relationship between IT sophistication and resident access to technology.ResultsFindings revealed that resident access to technology was a significant predictor of the nursing home IT sophistication (P<.001). The inclusion of covariates—nursing home location, bed size, and ownership—with their interactions produced a nonsignificant effect in the model. Residents’ or their representatives’ use of electronic health records and personal health records were both significant predictors of overall IT sophistication (P<.001).ConclusionsAs nursing homes continue to progress in technological capabilities, it is important to understand how increasing IT sophistication can be leveraged to create opportunities to engage residents in their care. Understanding the impact of health information technology on outcomes and which technologies make a difference will help nursing home administrators make more informed decisions about adoption and implementation.

Privacy-Preserving Similar Patient Queries for Combined Biomedical Data

Abstract The decreasing costs of molecular profiling have fueled the biomedical research community with a plethora of new types of biomedical data, enabling a breakthrough towards more precise and personalized medicine. Naturally, the increasing availability of data also enables physicians to compare patients’ data and treatments easily and to find similar patients in order to propose the optimal therapy. Such similar patient queries (SPQs) are of utmost importance to medical practice and will be relied upon in future health information exchange systems. While privacy-preserving solutions have been previously studied, those are limited to genomic data, ignoring the different newly available types of biomedical data. In this paper, we propose new cryptographic techniques for finding similar patients in a privacy-preserving manner with various types of biomedical data, including genomic, epigenomic and transcriptomic data as well as their combination. We design protocols for two of the most common similarity metrics in biomedicine: the Euclidean distance and Pearson correlation coefficient. Moreover, unlike previous approaches, we account for the fact that certain locations contribute differently to a given disease or phenotype by allowing to limit the query to the relevant locations and to assign them different weights. Our protocols are specifically designed to be highly efficient in terms of communication and bandwidth, requiring only one or two rounds of communication and thus enabling scalable parallel queries. We rigorously prove our protocols to be secure based on cryptographic games and instantiate our technique with three of the most important types of biomedical data – namely DNA, microRNA expression, and DNA methylation. Our experimental results show that our protocols can compute a similarity query over a typical number of positions against a database of 1,000 patients in a few seconds. Finally, we propose and formalize strategies to mitigate the threat of malicious users or hospitals.

Reducing hospital admissions for adverse drug events through coordinated pharmacist care: learning from Hawai’i without a field trip

Adverse drug events among older adults are common and serious. Approximately 9% of all hospital admissions for older adults are attributable to adverse drug reactions.1 Moreover, up to one in...