Health Information Exchange Research Articles

A Privacy-Preserving Scheme for Managing Secure Data in Healthcare System

In the world of modern technology and the huge spread of its use, it has been combined with healthcare systems and the establishment of electronic health records (EHR) to follow up on patients. This merging of technology with healthcare has allowed for more accurate EHRs that follow a patient to different healthcare facilities. Timely exchange of electronic health information (EHR) between providers is critical for aiding medical research and providing fast patient treatment. As a result, security issues and privacy problems are viewed as significant difficulties in the healthcare system. Several remote user authentication methods have been suggested. In this research, we present a feasible patient EHR migration solution for each patient. finally, each patient may securely delegate their current hospital’s information system to a hospital certification authority in order to receive migration proof that can be used to transfer their EHR to a different hospital. In addition, the proposed scheme is based on crypto-hash functions and asymmetric cryptosystems by using homomorphic cryptography. The proposed scheme carried out two exhaustive formal security proofs for the work that was provided. Using Scyther, a formal security tool, we present a secure user authentication technique in the proposed healthcare scheme that ensures security and informal analysis.

Health information exchange network under collaboration, cooperation, and competition: A game-theoretic approach.

Health Information Exchange (HIE) network allows securely accessing and sharing healthcare-related information among healthcare providers (HCPs) and payers. HIE services are provided by a non-profit/profit organizations under several subscription plans options. A few studies have addressed the sustainability of the HIE network such that HIE providers, HCPs, and payers remain profitable in the long term. However, none of these studies addressed the coexistence of multiple HIE providers in the network. Such coexistence may have a huge impact on the behavior of healthcare systems in terms of adoption rate and HIE pricing strategies. In addition, in spite of all the effort to maintain cooperation between HIE providers, there is still a chance of competition among them in the market. Possible competition among service providers leads to many concerns about the HIE network sustainability and behavior. In this study, a game-theoretic approach to model the HIE market is proposed. Game-theory is used to simulate the behavior of the three different HIE network agents in the HIE market: HIE providers, HCPs, and payers. Pricing strategies and adoption decisions are optimized using a Linear Programming (LP) mathematical model. Results show that the relation between HIEs in the market is crucial to HCP/Payer adoption decision specially to small HCPs. A small change in the discount rate proposed by a competitive HIE provider will highly affect the decision of HCP/payers to join the HIE network. Finally, competition opened the opportunity for more HCPs to join the network due to reduced pricing. Furthermore, collaborative HIEs provided better performance compared to cooperative in terms of profit and HCP adoption rate by sharing their overall costs and revenues.

Impact of Alignment and Alignment Correction on Outcomes Following Robotic Medial Unicompartmental Knee Arthroplasty

BackgroundThe purpose of this study was to retrospectively examine the relationship between preoperative and postoperative alignment in robotic unicompartmental knee arthroplasty (UKA) and postoperative patient-reported outcome measures. MethodsA retrospective review of 374 patients who underwent robotic-assisted UKA was conducted. Patient demographics, history, and preoperative and postoperative Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS-JR) scores were obtained via chart review. Average follow-up period was 2.4 years (range: 0.4 to 4.5 years) to chart review and 9.5 months (range: 6 to 48 months) to latest KOOS-JR. Preoperative and postoperative robotically-measured knee alignment was obtained from operative reports. Incidence of conversion to total knee arthroplasty (TKA) was determined by review of a health information exchange tool. ResultsMultivariate regressions showed no statistically significant relationship between preoperative alignment, postoperative alignment, or degrees of alignment correction and change in KOOS-JR score or achievement of KOOS-JR minimal clinically important difference (MCID) (P > .05). Patients who had >8 degrees of postoperative varus alignment had on average a 20% lower achievement of KOOS-JR MCID compared to patients who had <8 degrees of postoperative varus alignment; however, this difference was not statistically significant (P > .05). There were 3 patients who required conversion to TKA in the follow-up period, with no significant relationship to alignment variables (P > .05). ConclusionThere was no significant difference in KOOS-JR change for those patients who had a larger or smaller degree of deformity correction, and correction did not predict MCID achievement.

Adoption of electronic health record systems to enhance the quality of healthcare in low-income countries: a systematic review

BackgroundElectronic health record (EHR) systems are mentioned in several studies as tools for improving healthcare quality in developed and developing nations. However, there is a research gap in presenting the...

HSD68 Improving Care Via Timely Health Information Exchange: A Blue Cross and Blue Shield of Louisiana ADT System Referral Program Evaluation

The admission-discharge-transfer (ADT) system is a key source for member referrals to the Population Health intervention program at Blue Cross and Blue Shield of Louisiana (BCBSLA). It is triggered by an episodic event such as an emergency department visit or hospitalization. The system notifies BCBSLA’s Care Management team in near real time so they may act promptly. Their actions (such as health coaching, personalized disease self-management skills for members to adhere to recommended treatment plans) aim to improve quality of care and reduce health care costs. The purpose of this study is to evaluate the effect of timely referrals for Care Management interventions.

Large scale evaluation of pulmonary nodule workup: A real-world study of over 150,000 patients in New York State.

8559 Background: Around 1.6 million patients in the US annually have a pulmonary nodule (PN) found on imaging. Previous studies suggest 1-12% of PNs represent an underlying malignancy at a potentially curative stage. PNs ≥6mm are considered higher risk. Despite guideline availability, only about one-third of commercially insured patients with a PN receive recommended workup, which may include further investigation via imaging or surgery. In addition, patients and providers may delay workup of PNs identified during COVID-19. We aimed to describe variations in PN workup for different patient demographic and clinical characteristics at 7 healthcare institutions in New York (NY) state. Methods: We used a retrospective cross-sectional design in which structured demographic and unstructured clinical data were used to analyze patient documents from a NY state health information exchange from January 2018 to February 2022. Clinical features were abstracted using a clinical natural language processing platform, CLiX unlock. Results: 58 million documents from 5.5 million unique patients were analyzed. Of the overall 151,436 patients with PNs, workup was found in 47% (71,071). Across institutions, workup ranged between 24% and 52%; 40% (60,749) had evidence of a PN in the upper lung location. We found 52,789 patients (35%) had a maximum PN ≥6mm and of those, 55% (28,958) had a workup (Table). For patients with a PN ≥6mm, workup for non-English speaking patients was 9% lower than for English speaking patients (47% vs 56%), 17% lower for patients 18-44 years than patients 45-90 years (39% vs 56%), 47% lower for patients presenting with a chest injury rather than cancer screening (28% vs 75%), and 9% higher for patients with initial imaging via chest computed tomography (CT) rather than other CT (58% vs 49%). After the start of the COVID-19 pandemic (January 2020), overall workup decreased 3.8% and prevalence of symptoms such as dyspnea and chest pain increased. Conclusions: The descriptive findings of this analysis demonstrate gaps and variations in workup for patients with PNs across different demographics and clinical scenarios. A subsequent project is underway to explore strategies for improvement in adherence to guideline-recommended care to benefit patients by diagnosing lung cancer at an earlier, potentially curative stage. [Table: see text]

Blockchain innovation for consent self-management in health information exchanges

With the increasing digitalization of health data, patients need to make informed decisions about the online sharing of their protected health information. This necessitates a robust technical infrastructure that enables patients to self-manage consent and the trusted exchange of this information across sharing entities. Unfortunately, current health information exchange systems in the U.S. are limited in both these regards. While there is recent work on digital patient consent management, there is limited work that provides effective solutions for patient self-management of consent. Further, interoperability issues in the way health information exchanges are currently architected and differences in regulations across localities exacerbate the challenges of consent management. In this research, we survey potential patients' willingness to self-manage healthcare-related consent. Having established the desire for consent self-management, we propose a solution that enables the seamless sharing of patient consent across different healthcare providers and health information exchanges. Specifically, we use a rigorous design science approach to create a blockchain-based, self-managed patient consent system and we evaluate the design through an instantiated prototype. The results of our study should be useful to researchers in healthcare information management as well as to practitioners designing consent management systems. Our research contributes to design science research with an innovative, rigorously evaluated, design principles-based artifact that addresses a critical problem of sharing protected health information.

Comparison of SIREN social needs screening tools and Simplified Omaha System Terms: informing an informatics approach to social determinants of health assessments.

Numerous studies indicate that the social determinants of health (SDOH), conditions in which people work, play, and learn, account for 30%-55% of health outcomes. Many healthcare and social service organizations seek ways to collect, integrate, and address the SDOH. Informatics solutions such as standardized nursing terminologies may facilitate such goals. In this study, we compared one standardized nursing terminology, the Omaha System, in its consumer-facing form, Simplified Omaha System Terms (SOST), to social needs screening tools identified by the Social Interventions Research and Evaluation Network (SIREN). Using standard mapping techniques, we mapped 286 items from 15 SDOH screening tools to 335 SOST challenges. The SOST assessment includes 42 concepts across 4 domains. We analyzed the mapping using descriptive statistics and data visualization techniques. Of the 286 social needs screening tools items, 282 (98.7%) mapped 429 times to 102 (30.7%) of the 335 SOST challenges from 26 concepts in all domains, most frequently from Income, Home, and Abuse. No single SIREN tool assessed all SDOH items. The 4 items not mapped were related to financial abuse and perceived quality of life. SOST taxonomically and comprehensively collects SDOH data compared to SIREN tools. This demonstrates the importance of implementing standardized terminologies to reduce ambiguity and ensure the shared meaning of data. SOST could be used in clinical informatics solutions for interoperability and health information exchange, including SDOH. Further research is needed to examine consumer perspectives regarding SOST assessment compared to other social needs screening tools.

Level of Professional Awareness among Health Record Officers in Bayelsa State and Their Implications for Patient Care, Health Systems, and Health Policy

As Electronic health records (EHRs) become more commonplace, and are expected to play a key role in improving the quality of Nigeria health care. Thus, EHRs can improve quality of care delivery in numerous ways such as providing accurate and up-to-date patient information and medical knowledge, rapid retrieval of health information, ability to exchange health information to all authorized participants within or across organizations, automated clinical reminders, improved adherence to treatment guidelines, and accumulation of data for quality monitoring and improvement. Based on regulatory and governmental recommendations, the EHR is being adapted in an increasing number of academic institutions (NDUTH), government hospitals (FMC) and private practice settings. It is incumbent upon HIM leadership to ensure students are skillful users of the technologies that will be in place as they care for patients. The study aimed to explore, identify and understand critical awareness of electronic health records management level to ensure confidentiality in public health care sector (FMC &amp; NDUTH) in Bayelsa State, Nigeria. The cross-sectional descriptive design was used and a total of 159 health professionals who represented a variety of user groups across different specialties within the hospital completed the questionnaire. The collected data were analyzed. both descriptively and inferentially. Frequency and percentages were used to analyse the data and the result presented in tables. Data analysis was facilitated using the Statistical Package for Social Sciences (SPSS version 20.0). Majority of the respondents (90.6%) were aware of the electronic health record management among health record officers. To ensure continuity of care, it is necessary to develop educational and manageable program to improve EHR awareness. The findings may inform other hospitals and healthcare systems on actions that can be taken prior to EHR implementation to reduce concerns for quality, confidentiality, safety of patient care and improve the chance of successful implementation.

Association of Fragmented Readmissions and Electronic Information Sharing With Discharge Destination Among Older Adults

When an older adult is hospitalized, where they are discharged is of utmost importance. Fragmented readmissions, defined as readmissions to a different hospital than a patient was previously discharged from, may increase the risk of a nonhome discharge for older adults. However, this risk may be mitigated via electronic information exchange between the admission and readmission hospitals. To determine the association of fragmented hospital readmissions and electronic information sharing with discharge destination among Medicare beneficiaries. This cohort study retrospectively examined data from Medicare beneficiaries hospitalized for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, syncope, urinary tract infection, dehydration, or behavioral issues in 2018 and their 30-day readmission for any reason. The data analysis was completed between November 1, 2021, and October 31, 2022. Same hospital vs fragmented readmissions and presence of the same health information exchange (HIE) at the admission and readmission hospitals vs no information shared between the admission and readmission hospitals. The main outcome was discharge destination following the readmission, including home, home with home health, skilled nursing facility (SNF), hospice, leaving against medical advice, or dying. Outcomes were examined for beneficiaries with and without Alzheimer disease using logistic regressions. The cohort included 275 189 admission-readmission pairs, representing 268 768 unique patients (mean [SD] age, 78.9 [9.0] years; 54.1% female and 45.9% male; 12.2% Black, 82.1% White, and 5.7% other race and ethnicity). Of the 31.6% fragmented readmissions in the cohort, 14.3% occurred at hospitals that shared an HIE with the admission hospital. Beneficiaries with same hospital/nonfragmented readmissions tended to be older (mean [SD] age, 78.9 [9.0] vs 77.9 [8.8] for fragmented with same HIE and 78.3 [8.7] years for fragmented without HIE; P < .001). Fragmented readmissions were associated with 10% higher odds of discharge to an SNF (adjusted odds ratio [AOR], 1.10; 95% CI, 1.07-1.12) and 22% lower odds of discharge home with home health (AOR, 0.78; 95% CI, 0.76-0.80) compared with same hospital/nonfragmented readmissions. When the admission and readmission hospital shared an HIE, beneficiaries had 9% to 15% higher odds of discharge home with home health (patients without Alzheimer disease: AOR, 1.09 [95% CI, 1.04-1.16]; patients with Alzheimer disease: AOR, 1.15 [95% CI, 1.01-1.32]) compared with fragmented readmissions where information sharing was not available. In this cohort study of Medicare beneficiaries with 30-day readmissions, whether a readmission is fragmented was associated with discharge destination. Among fragmented readmissions, shared HIE across admission and readmission hospitals was associated with higher odds of discharge home with home health. Efforts to study the utility of HIE for care coordination for older adults should be pursued.

Development and Temporal Validation of an Electronic Medical Record-Based Insomnia Prediction Model Using Data from a Statewide Health Information Exchange.

This study aimed to develop and temporally validate an electronic medical record (EMR)-based insomnia prediction model. In this nested case-control study, we analyzed EMR data from 2011-2018 obtained from a statewide health information exchange. The study sample included 19,843 insomnia cases and 19,843 controls matched by age, sex, and race. Models using different ML techniques were trained to predict insomnia using demographics, diagnosis, and medication order data from two surveillance periods: -1 to -365 days and -180 to -365 days before the first documentation of insomnia. Separate models were also trained with patient data from three time periods (2011-2013, 2011-2015, and 2011-2017). After selecting the best model, predictive performance was evaluated on holdout patients as well as patients from subsequent years to assess the temporal validity of the models. An extreme gradient boosting (XGBoost) model outperformed all other classifiers. XGboost models trained on 2011-2017 data from -1 to -365 and -180 to -365 days before index had AUCs of 0.80 (SD 0.005) and 0.70 (SD 0.006), respectively, on the holdout set. On patients with data from subsequent years, a drop of at most 4% in AUC is observed for all models, even when there is a five-year difference between the collection period of the training and the temporal validation data. The proposed EMR-based prediction models can be used to identify insomnia up to six months before clinical detection. These models may provide an inexpensive, scalable, and longitudinally viable method to screen for individuals at high risk of insomnia.

A Unique Use of Regional Information Exchange by a Statewide Health System Serving Refugees: "Operation Allies Welcome".

In September 2021, a military camp in the United States was identified for an initial relocation of over 6,600 Afghanistan refugees. This case report describes a novel use of existing health information exchange to expedite and provide health care for a large refugee population throughout the state during the duration of their entry into the United States. Medical teams of the health systems and military camp partnered to provide a scalable, reliable mechanism for clinical data exchange leveraging an existing regional health information exchange. Exchanges were evaluated for clinical type, originating source, and closed loop communication with the refugee camp and personnel military camp. Approximately 50% of the camp residents were under the age of 18 years. Over 20 weeks, approximately 4.51% of the refugee camp residents were cared for in participating health systems. A total of 2,699 clinical data messages were exchanged, 62% of which were clinical documents. All health systems participating in care were offered support to utilize the tool and process set up using the regional health information exchange. The process and guiding principles may be applied to other refugee health care efforts to provide efficient, scalable, and reliable means of clinical data exchange to health care providers in similar situations.

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.

The clinical narrative in electronic health records (EHRs) carries valuable information for predictive analytics; however, its free-text form is difficult to mine and analyze for clinical decision support (CDS). Large-scale clinical natural language processing (NLP) pipelines have focused on data warehouse applications for retrospective research efforts. There remains a paucity of evidence for implementing NLP pipelines at the bedside for health care delivery. We aimed to detail a hospital-wide, operational pipeline to implement a real-time NLP-driven CDS tool and describe a protocol for an implementation framework with a user-centered design of the CDS tool. The pipeline integrated a previously trained open-source convolutional neural network model for screening opioid misuse that leveraged EHR notes mapped to standardized medical vocabularies in the Unified Medical Language System. A sample of 100 adult encounters were reviewed by a physician informaticist for silent testing of the deep learning algorithm before deployment. An end user interview survey was developed to examine the user acceptability of a best practice alert (BPA) to provide the screening results with recommendations. The planned implementation also included a human-centered design with user feedback on the BPA, an implementation framework with cost-effectiveness, and a noninferiority patient outcome analysis plan. The pipeline was a reproducible workflow with a shared pseudocode for a cloud service to ingest, process, and store clinical notes as Health Level 7 messages from a major EHR vendor in an elastic cloud computing environment. Feature engineering of the notes used an open-source NLP engine, and the features were fed into the deep learning algorithm, with the results returned as a BPA in the EHR. On-site silent testing of the deep learning algorithm demonstrated a sensitivity of 93% (95% CI 66%-99%) and specificity of 92% (95% CI 84%-96%), similar to published validation studies. Before deployment, approvals were received across hospital committees for inpatient operations. Five interviews were conducted; they informed the development of an educational flyer and further modified the BPA to exclude certain patients and allow the refusal of recommendations. The longest delay in pipeline development was because of cybersecurity approvals, especially because of the exchange of protected health information between the Microsoft (Microsoft Corp) and Epic (Epic Systems Corp) cloud vendors. In silent testing, the resultant pipeline provided a BPA to the bedside within minutes of a provider entering a note in the EHR. The components of the real-time NLP pipeline were detailed with open-source tools and pseudocode for other health systems to benchmark. The deployment of medical artificial intelligence systems in routine clinical care presents an important yet unfulfilled opportunity, and our protocol aimed to close the gap in the implementation of artificial intelligence-driven CDS. ClinicalTrials.gov NCT05745480; https://www.clinicaltrials.gov/ct2/show/NCT05745480.

Quality Measurement of Consumer Health Questions: Content and Language Perspectives.

Health information consumers increasingly rely on question-and-answer (Q&A) communities to address their health concerns. However, the quality of questions posted significantly impacts the likelihood and relevance of received answers. This study aims to improve our understanding of the quality of health questions within web-based Q&A communities. We develop a novel framework for defining and measuring question quality within web-based health communities, incorporating content- and language-based variables. This framework leverages k-means clustering and establishes automated metrics to assess overall question quality. To validate our framework, we analyze questions related to kidney disease from expert-curated and community-based Q&A platforms. Expert evaluations confirm the validity of our quality construct, while regression analysis helps identify key variables. High-quality questions were more likely to include demographic and medical information than lower-quality questions (P<.001). In contrast, asking questions at the various stages of disease development was less likely to reflect high-quality questions (P<.001). Low-quality questions were generally shorter with lengthier sentences than high-quality questions (P<.01). Our findings empower consumers to formulate more effective health information questions, ultimately leading to better engagement and more valuable insights within web-based Q&A communities. Furthermore, our findings provide valuable insights for platform developers and moderators seeking to enhance the quality of user interactions and foster a more trustworthy and informative environment for health information exchange.

The argumentative salience of technology frames of reference: An analysis of argumentative discourse in the development of a health information exchange initiative

This study examines the impact that the argumentative salience of technology frames of references has on the execution of complex IS implementation projects. It employs Toulmin's argument model to develop argument maps that depict the structure of argumentation that took place during the development and implementation of an interorganizational health information exchange initiative (HIE) that took place in southeast USA. Toulmin's argument model faciliated the portrayal of frame salience in terms of three structural properties (i.e., blindness, indifference, and ownership). The study used these properties to show how the breadth, depth and conspicuity of frame structures changed during the course of the project and demonstrated how these changes impacted both the level of contestation observed in the project as well as project outcomes. In addition to lending insights that are specific to this case, our conceptualization of frame structure lends itself to cross-case comparisons and future theory building as the impact of these argument structures can be evaluated in a multitude of different contexts.

Evolution of Health Information Sharing Between Health Care Organizations: Potential of Nonfungible Tokens

This study attempts to explain the development and progress of the technology used for sharing health information across health care organizations (such as hospitals and physicians' offices). First, we describe the strengths and weaknesses of traditional sharing models, health information exchange (HIE), and blockchain-based HIE. Second, the potential use of nonfungible token (NFT) protocols in HIE models is proposed as the next possible move for information-sharing initiatives in health care. In addition to some potential opportunities and distinguishing features (eg, ownability, verifiability, and incentivization), we identify the uncertainty and risks associated with the application of NFTs, such as the lack of a dedicated regulatory framework for legal ownership of digital patient data. This paper is among the first to discuss the potential of NFTs in health care. The use of NFTs in HIE networks could generate a new stream of research for future studies. This study provides practical insights into how the technological foundations of information-sharing efforts in health care have developed and diversified from earlier forms.

Experiences with information blocking in the United States: a national survey of hospitals.

The 21st Century Cures Act Final Rule's information blocking provisions, which prohibited practices likely to interfere with, prevent, or materially discourage access, exchange, or use of electronic health information (EHI), began to apply to a limited set of data elements in April 2021 and expanded to all EHI in October 2022. We sought to describe hospital leaders' perceptions of the prevalence of practices that may constitute information blocking, by actor and hospital characteristics, following the rule's applicability date. Cross-sectional analysis of a national survey of hospitals fielded in 2021. The analytic sample included 2092 nonfederal acute care hospitals in the United States. We present descriptive statistics on the perception of the prevalence of information blocking and results of multivariate regression models examining the association between hospital, health information technology (IT) developer and market characteristics and the perception of information blocking. Overall, 42% of hospitals reported observing some behavior they perceived to be information blocking. Thirty-six percent of responding hospitals perceived that healthcare providers either sometimes or often engaged in practices that may constitute information blocking, while 17% and 19% perceived that health IT developers (such as EHR developers) and State, regional and/or local health information exchanges did the same, respectively. Prevalence varied by health IT developer market share, hospital for-profit status, and health system market share. These results support the value of efforts to further reduce friction in the exchange of EHI and support the need for continued observation to provide a sense of the prevalence of information blocking practices and for education and awareness of information blocking regulations.

Asymmetric Interoperability as a Strategy Among Provider Group Health Information Exchange: Directional Analysis

High levels of seamless, bidirectional health information exchange continue to be broadly limited among provider groups despite the vast array of benefits that interoperability entails for patient care and the many persistent efforts across the health care ecosystem directed at advancing interoperability. As provider groups seek to act in their strategic best interests, they are often interoperable and exchange information in certain directions but not others, leading to the formation of asymmetries. We aimed to examine the correlation at the provider group level between the distinct directions of interoperability with regard to sending health information and receiving health information, to describe how this correlation varies across provider group types and provider group sizes, and to analyze the symmetries and asymmetries that arise in the exchange of patient health information across the health care ecosystem as a result. We used data from the Centers for Medicare & Medicaid Services (CMS), which included interoperability performance information for 2033 provider groups within the Quality Payment Program Merit-based Incentive Payment System and maintained distinct performance measures for sending health information and receiving health information. In addition to compiling descriptive statistics, we also conducted a cluster analysis to identify differences among provider groups-particularly with respect to symmetric versus asymmetric interoperability. We found that the examined directions of interoperability-sending health information and receiving health information-have relatively low bivariate correlation (0.4147) with a significant number of observations exhibiting asymmetric interoperability (42.5%). Primary care providers are generally more likely to exchange information asymmetrically than specialty providers, being more inclined to receive health information than to send health information. Finally, we found that larger provider groups are significantly less likely to be bidirectionally interoperable than smaller groups, although both are asymmetrically interoperable at similar rates. The adoption of interoperability by provider groups is more nuanced than traditionally considered and should not be seen as a binary determination (ie, to be interoperable or not). Asymmetric interoperability-and its pervasive presence among provider groups-reiterates how the manner in which provider groups exchange patient health information is a strategic choice and may pose similar implications and potential harms as the practice of information blocking has in the past. Differences in the operational paradigms among provider groups of varying types and sizes may explain their varying extents of health information exchange for sending and receiving health information. There continues to remain substantial room for improvement on the path to achieving a fully interoperable health care ecosystem, and future policy efforts directed at advancing interoperability should consider the practice of being asymmetrically interoperable among provider groups.

127 A formative usability evaluation of a community pharmacist-facing health information exchange (HIE) interface

OBJECTIVES/GOALS: To evaluate the usability of a HIE interface design among community pharmacists and technicians to identify opportunities for design improvements METHODS/STUDY POPULATION: Pharmacists and pharmacy technicians employed at Indiana community pharmacies participated in formative usability testing, via a Rapid Usability Evaluation (RUE), with an interactive, PDF prototype of the HIE interface. Participants were video-recorded to capture first impressions on the usability of the HIE prototype via the think aloud technique. Each participant had up to 1 hour to complete 4 clinical scenarios. Afterwards, participants completed the System Usability Scale (SUS; scale 0–100, with 100 being the best) to rate their satisfaction with the HIE prototype. RESULTS/ANTICIPATED RESULTS: Across 3 community pharmacies, 16 individuals participated in usability testing: 8 pharmacists and 8 technicians. The average SUS score for the HIE interface across participants from all sites was 70. Pharmacists on average scored the interface higher than technicians, 74 vs. 65, respectively. Initial findings from one pharmacy revealed that both pharmacists and technicians expressed a desire for improved efficiency (i.e. fewer clicks ) to access HIE data, alternative placement of HIE links within existing systems, and improved navigation to exit HIE links. DISCUSSION/SIGNIFICANCE: Initial results reveal opportunities to improve the HIE interface usability. Findings will inform design improvements to the interface and the creation of a toolkit to support the sustainable and scalable participation in HIE by community pharmacies.

Opening the Precision Diabetes Care through Digital Healthcare.

The national healthcare systems of every country in the world cannot sustain the rise in healthcare expenditure caused by chronic diseases and their complications. To sustain the national healthcare system, a novel system should be developed to improve the quality of care and minimize healthcare costs. For 20 years, our team developed patient-communicating digital healthcare platforms and proved their efficacy. National scale randomized control trials are underway to systematically measure the efficacy and economic benefits of this digital health care system. Precision medicine aims to maximize effectiveness of disease management by considering individual variability. Digital health technologies enable precision medicine at a reasonable cost that was not available before. The government launched the "National Integrated Bio-big Data Project" which will collect diverse health data from the participants. Individuals will share their health information to physicians or researchers at their will by gateway named "My-Healthway.' Taken together, now we stand in front of the evolution of medical care, so-called "Precision medicine." led by various kinds of technologies and a huge amount of health information exchange. We should lead these new trends as pioneers, not as followers, to establish and implement the best care for our patients that can help them to withstand their devastating diseases.