Progress In Interoperability: Measuring US Hospitals' Engagement In Sharing Patient Data

How Much Does Intravenous Fluid Cause Hematocrit to Drop? Improving Interpretation of Hematocrit Toward Better Post-Hemorrhage Care

INTRODUCTION

Hemorrhage is assessed, at least in part, via hematocrit testing. To differentiate unexpected drops in hematocrit because of ongoing hemorrhage versus expected drops as a result of known hemorrhage and intravenous fluid administration, we model expected post-operative hematocrit values accounting for fluid balance and intraoperative estimated blood loss (EBL) among patients without substantial post-operative bleeding.

MATERIALS AND METHODS

We reviewed patient-level data from the electronic health record of an academic medical center for all non-pregnant adults admitted for elective knee or hip arthroplasty from November 2013 to September 2022 who did not require blood products. We used linear regression to evaluate the association between post-operative hematocrit and predictor variables including pre-operative hematocrit, intraoperative net fluid intake, blood volume, time from surgery to lab testing, EBL, patient height, and patient weight.

RESULTS

We included 6,648 cases. Mean (SD) estimated blood volume was 4,804 mL (1023), mean net fluid intake was 1,121 mL (792), and mean EBL was 144 mL (194). Each 100 mL of EBL and 1,000 mL net positive fluid intake was associated with a decrease of 0.52 units (95% CI, 0.51-0.53) and 2.4 units (2.2-2.7) in post-operative hematocrit. Pre-operative hematocrit was the strongest predictor of post-operative hematocrit. Each 1-unit increase in pre-operative hematocrit was associated with a 0.70-unit increase (95% CI, 0.67-0.73) in post-operative hematocrit. Our estimates were robust to sensitivity analyses, and all variables included in the model were statistically significant with P <.005.

CONCLUSION

Patient-specific data, including fluid received since the time of initial hemorrhage, can aid in estimating expected post-hemorrhage hematocrit values, and thus in assessing for the ongoing hemorrhage.

Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations

Healthcare organizations have realized that Artificial intelligence (AI) can provide a competitive edge through personalized patient experiences, improved patient outcomes, early diagnosis, augmented clinician capabilities, enhanced operational efficiencies, or improved medical service accessibility. However, deploying AI-driven tools in the healthcare ecosystem could be challenging. This paper categorizes AI applications in healthcare and comprehensively examines the challenges associated with deploying AI in medical practices at scale. As AI continues to make strides in healthcare, its integration presents various challenges, including production timelines, trust generation, privacy concerns, algorithmic biases, and data scarcity. The paper highlights that flawed business models and wrong workflows in healthcare practices cannot be rectified merely by deploying AI-driven tools. Healthcare organizations should re-evaluate root problems such as misaligned financial incentives (e.g., fee-for-service models), dysfunctional medical workflows (e.g., high rates of patient readmissions), poor care coordination between different providers, fragmented electronic health records systems, and inadequate patient education and engagement models in tandem with AI adoption. This study also explores the need for a cultural shift in viewing AI not as a threat but as an enabler that can enhance healthcare delivery and create new employment opportunities while emphasizing the importance of addressing underlying operational issues. The necessity of investments beyond finance is discussed, emphasizing the importance of human capital, continuous learning, and a supportive environment for AI integration. The paper also highlights the crucial role of clear regulations in building trust, ensuring safety, and guiding the ethical use of AI, calling for coherent frameworks addressing transparency, model accuracy, data quality control, liability, and ethics. Furthermore, this paper underscores the importance of advancing AI literacy within academia to prepare future healthcare professionals for an AI-driven landscape. Through careful navigation and proactive measures addressing these challenges, the healthcare community can harness AI's transformative power responsibly and effectively, revolutionizing healthcare delivery and patient care. The paper concludes with a vision and strategic suggestions for the future of healthcare with AI, emphasizing thoughtful, responsible, and innovative engagement as the pathway to realizing its full potential to unlock immense benefits for healthcare organizations, physicians, nurses, and patients while proactively mitigating risks.

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

OBJECTIVE

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.

MATERIALS AND METHODS

We combined 2018 Medicare fee-for-service claims to identify beneficiaries with 2 ED encounters within 30 days, 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.

RESULTS

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]).

DISCUSSION

Lower utilization for beneficiaries returning to the same organization could reflect better access to information or other factors such as aligned incentives.

CONCLUSION

HIE is not consistently associated with utilization outcomes reflecting more coordinated care in the ED setting.

Use of Information Technology Systems for Regional Health Care Information-Sharing and Coordination During Large-Scale Medical Surge Events

Medical surge events require effective coordination between multiple partners. Unfortunately, the information technology (IT) systems currently used for information-sharing by emergency responders and managers in the United States are insufficient to coordinate with health care providers, particularly during large-scale regional incidents. The numerous innovations adopted for the COVID-19 response and continuing advances in IT systems for emergency management and health care information-sharing suggest a more promising future. This article describes: (1) several IT systems and data platforms currently used for information-sharing, operational coordination, patient tracking, and resource-sharing between emergency management and health care providers at the regional level in the US; and (2) barriers and opportunities for using these systems and platforms to improve regional health care information-sharing and coordination during a large-scale medical surge event. The article concludes with a statement about the need for a comprehensive landscape analysis of the component systems in this IT ecosystem.

Successes and Barriers of Health Information Exchange Participation Across Hospitals in South Carolina From 2014 to 2020: Longitudinal Observational Study

BACKGROUND

The 2009 Health Information Technology for Economic and Clinical Health Act sets three stages of Meaningful Use requirements for the electronic health records incentive program. Health information exchange (HIE) technologies are critical in the meaningful use of electronic health records to support patient care coordination. However, HIE use trends and barriers remain unclear across hospitals in South Carolina (SC), a state with the earliest HIE implementation.

OBJECTIVE

This study aims to explore changes in the proportion of HIE participation and factors associated with HIE participation, and barriers to exchange and interoperability across SC hospitals.

METHODS

This study derived data from a longitudinal data set of the 2014-2020 American Hospital Association Information Technology Supplement for 69 SC hospitals. The primary outcome was whether a hospital participated in HIE in a year. A cross-sectional multivariable logistic regression model, clustered at the hospital level and weighted by bed size, was used to identify factors associated with HIE participation. The second outcome was barriers to sending, receiving, or finding patient health information to or from other organizations or hospital systems. The frequency of hospitals reporting each barrier related to exchange and interoperability were then calculated.

RESULTS

Hospitals in SC have been increasingly participating in HIE, improving from 43% (24/56) in 2014 to 82% (54/66) in 2020. After controlling for other hospital factors, teaching hospitals (adjusted odds ratio [AOR] 3.7, 95% CI 1.0-13.3), system-affiliated hospitals (AOR 6.6, 95% CI 3.2-13.7), and rural referral hospitals (AOR 8.0, 95% CI 1.2-53.4) had higher odds to participate in HIE than their counterparts, whereas critical access hospitals (AOR 0.1, 95% CI 0.02-0.6) were less likely to participate in HIE than their counterparts reimbursed by the prospective payment system. Hospitals with greater ratios of Medicare or Medicaid inpatient days to total inpatient days also reported higher odds of HIE participation. Despite the majority of hospitals reporting HIE participation in 2020, barriers to exchange and interoperability remained, including lack of provider contacts (27/40, 68%), difficulty in finding patient health information (27/40, 68%), adapting different vendor platforms (26/40, 65%), difficulty matching or identifying same patients between systems (23/40, 58%), and providers that do not typically exchange patient data (23/40, 58%).

CONCLUSIONS

HIE participation has been widely adopted in SC hospitals. Our findings highlight the need to incentivize optimization of HIE and seamless information exchange by facilitating and implementing standardization of health information across various HIE systems and by addressing other technical issues, including providing providers' addresses and training HIE stakeholders to find relevant information. Policies and efforts should include more collaboration with vendors to reduce platform compatibility issues and more user engagement and technical training and support to facilitate effective, accurate, and efficient exchange of provider contacts and patient health information.

Adoption and use of various health information exchange methods for sending inside health information in US hospitals

BACKGROUND

Hospitals may adopt various information transmission methods to participate in health information exchange (HIE) programs. However, even if they adopt multiple mechanisms, they may not actively use all of them to send inside information. This study analyzes the frequently used methods for sending data and the common barriers blocking sending practices in hospital settings.

METHODS

Our sample included 3,015 community hospitals that reported their methods of sending patient health information in the 2019 American Hospital Association Information Technology Supplement Survey. The relationship between obstacles hospitals experienced and their use of the information-sending method was analyzed by using robust Poisson regression models.

RESULTS

Many-to-many exchanges that involve intermediaries such as a health information service provider (HISP), electronic health record (EHR) vendor-based network, and national network, once adopted, were more often used by hospitals than one-to-one exchange methods such as provider portals and direct access to EHR by login credentials. Hospitals that lacked the technical capability to electronically send patient health information were less likely to use any of the methods (p <.01), while hospitals located in a more concentrated market were more likely to send information to outside providers by using provider portal, interface connection and national network (p <.01).

DISCUSSION

There is still a notable gap between hospitals' adoption and the actual use of different HIE methods to send inside information to outside organizations. Results argue that even if hospitals adopted an HIE method, they might not necessarily participate in the actual sharing of information, and the method may remain unused due to several usage barriers.

CONCLUSION

Hospital and market-level barriers associated with using one-to-one and many-to-many HIE methods for sharing information may affect progress in interoperability. Examining the barriers to using multiple HIE methods and their impact on interoperability could offer implications for health information technology (IT) policy and inform health system leaders.

Assessing the impact of health information exchange on hospital data breach risk

OBJECTIVE

Widespread electronic health information exchange (HIE) across hospitals remains an important policy goal for reducing costs and improving the quality of care. Meanwhile, cybersecurity incidents are a growing threat to hospitals. The relationship between the electronic sharing of health information and cybersecurity incidents is not well understood. The objective of this study was to empirically examine the impact of hospitals' HIE engagement on their data breach risk.

MATERIALS AND METHODS

A balanced panel dataset included 4,936 US community hospitals spanning the period 2010-2017, which was assembled by linking the American Hospital Association annual survey database and the Information Technology (IT) supplement, and the Department of Health and Human Services reports of health data breaches. The relationship between HIE engagement and hospital data breaches was modeled using a difference-in-differences specification controlling for time-varying hospital characteristics.

RESULTS

The percentage of hospitals electronically exchanging information has more than tripled (from 18% to 68%) from 2010 to 2017. Hospital data breaches increased concurrently, largely due to the rise in hacking and unauthorized access. HIE engagement was associated with a 0.672 percentage point increase in the probability of an IT breach three years after the engagement. Hospitals actively engaging in a health information organization and exchanging data with outside providers were associated with a higher risk of IT related breaches in the long run; however, hospitals actively engaging in HIE and exchanging data with inside providers were not associated with any significant risk of IT related breaches.

DISCUSSION

Over time, the increasing amount and complexity of patient information being exchanged can create challenges for cybersecurity if data protection is not up to date. Additionally, data security depends on the weakest link of HIE, and providers with fewer resources for data governance and infrastructure are more vulnerable to data breaches.

CONCLUSION

Moving toward widespread health information exchange has important cybersecurity implications that can significantly impact both patients and healthcare organizations.

The physician CEO advantage and hospital performance during the COVID-19 pandemic: capacity utilization and patient satisfaction

PURPOSE

Prior studies have shown that physician-led hospitals have several advantages over non-physician-led hospitals. This study seeks to test whether these advantages also extend to periods of extreme disruptions such as the COVID-19 pandemic, which affect bed availability and hospital utilization.

DESIGN/METHODOLOGY/APPROACH

The authors utilize a bounded Tobit estimation to identify differences in patient satisfaction rates and in-hospital utilization rates of top-rated hospitals in the United States.

FINDINGS

Among top-rated US hospitals, those that are physician-led achieve higher patient satisfaction ratings and are more likely to have higher utilization rates.

RESEARCH LIMITATIONS/IMPLICATIONS

While the COVID-19 pandemic generated greater demand for inpatient beds, physician-led hospitals improved their hospitals' capacity utilization as compared with those led by non-physician leaders. A longitudinal study to show the change over the years and whether physician Chief Executive Officers (CEOs) are more likely to improve their hospitals' ratings than non-physician CEOs is highly recommended.

PRACTICAL IMPLICATIONS

Recruiting and retaining physicians to lead hospitals, especially during disruptions, improve hospital's operating efficiency and enhance patient satisfaction.

ORIGINALITY/VALUE

The paper reviews prior research on physician leadership and adds further insights into the crisis leadership literature. The authors provide evidence based on quantitative data analysis that during the COVID-19 pandemic, physician-led top-rated US hospitals experienced an improvement in operating efficiency.

Priorities to accelerate workflow automation in health care

Inefficient workflows affect many health care stakeholders including patients, caregivers, clinicians, and staff. Widespread health information technology adoption and modern computing provide opportunities for more efficient health care workflows through automation. The Office of the National Coordinator for Health Information Technology (ONC) led a multidisciplinary effort with stakeholders across health care and experts in industrial engineering, computer science, and finance to explore opportunities for automation in health care. The effort included semistructured key informant interviews, a review of relevant literature, and a workshop to understand automation lessons across nonhealth care industries that could be applied to health care. In this article, we describe considerations for advancing workflow automation in health care that were identified through these activities. We also discuss a set of six priorities and related strategies developed through the ONC-led effort and highlight the role the informatics and research communities have in advancing each priority and the strategies.

Digital Health at Enterprise Scale: An Evaluation Framework for Selecting Patient Facing Software in a Digital First Health System (Preprint)

The digital transformation of our health care system will require not only digitization of existing tools but also a redesign of our care delivery system and collaboration with digital partners. Traditional patient journeys are reactive to symptom presentation and delayed by health care system-centric scheduling, leading to poor experience and avoidable adverse outcomes. Patient journeys will be reimagined to a digital health pathway that seamlessly integrates various care experiences from telemedicine, remote monitoring, to in-person clinic visits. Through centering the care delivery around the patients, they can have more delightful experiences and enjoy the quality of standardized condition pathways and outcomes. To design and implement digital health pathways at scale, enterprise health care systems need to develop capabilities and partnerships in human-centered design, operational workflow, clinical content management, communication channels and mechanisms, reporting and analytics, standards-based integration, security and data management, and scalability. Using a human-centered design methodology, care pathways will be built upon an understanding of the unmet needs of the patients to have a more enjoyable experience of care with improved clinical outcomes. To power this digital care pathway, enterprises will choose to build or partner for clinical content management to operationalize up-to-date, best-in-class pathways. With this clinical engine, this digital solution will engage with patients through multimodal communication modalities, including written, audio, photo, or video, throughout the patient journey. Leadership teams will review reporting and analytics functions to track that the digital care pathways will be iterated to improve patient experience, clinical metrics, and operational efficiency. On the backend, standards-based integration will allow this system to be built in conjunction with the electronic medical record and other data systems to provide safe and efficient use of the digital care solution. For protecting patient information and compliance, a security and data management strategy is critical to derisking breeches and preserving privacy. Finally, a framework of technical scalability will allow digital care pathways to proliferate throughout the enterprise and support the entire patient population. This framework empowers enterprise health care systems to avoid collecting a fragmented series of one-off solutions but develop a sustainable concerted roadmap to the future of proactive intelligent patient care.

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.

Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study

Background

The last decade has seen a considerable increase in the number of mobile health (mHealth) apps in everyday life. These mHealth apps have the potential to significantly improve the well-being of chronically ill patients. However, behavioral engagement with mHealth apps remains low.

Objective

The aim of this study was to describe the behavioral engagement of chronically ill patients with mHealth apps by investigating (1) how it is affected by social factors (ie, physician recommendation) and app-related factors (ie, app integration) and (2) how it affects patient well-being. This study also considers the moderating effect of attachment to traditional health care and the mobile app experience among patients.

Methods

We carried out a scenario-based survey study of chronically ill patients (N=521). A Bayesian structural equation modeling with mediation and moderation analysis was conducted in MPlus.

Results

Both physician recommendations for mHealth app use and app integration have positive effects on the behavioral engagement of chronically ill patients with mHealth apps. Higher behavioral engagement positively affects the hedonic well-being (extent of pleasure) and the eudaemonic well-being (extent of self-efficacy) of chronically ill patients. Mobile app experience, however, positively moderates the relationship between app integration and behavioral engagement, whereas patient attachment to traditional care does not moderate the relationship between physician recommendation and behavioral engagement. Taken together, the proportion of variance explained (R²) equals 21% for behavioral engagement and 52.8% and 62.2% for hedonic and eudaemonic well-being, respectively, thereby providing support for the strong influence of app integration and physician recommendation via the mediation of the patients’ behavioral engagement on both patients’ hedonic and eudaemonic well-being.

Conclusions

Physician recommendation and app integration enable behavioral engagement and promote well-being among chronically ill patients. It is thus important to take social and app-related factors into consideration during and after the development of mHealth apps.

Hospital's adoption of multiple methods of obtaining outside information and use of that information

OBJECTIVE

Hospitals have multiple methods available to engage in health information exchange (HIE); however, it is not well understood whether these methods are complements or substitutes. We sought to characterize patterns of adoption of HIE methods and examine the association between these methods and increased availability and use of patient information.

MATERIALS AND METHODS

Cross-sectional analysis of 3208 nonfederal acute care hospitals in the 2019 American Hospital Association Information Technology Supplement.

RESULTS

The median hospital obtained outside information through 4 methods. Hospitals that obtained data through a regional HIE organization were 2.2 times more likely to also obtain data via Direct using a health information service provider (HISP) than hospitals that did not (P < .001). Hospitals in a single electronic health record (EHR) vendor network were no more or less likely to participate in a HISP or HIE. Six of 7 methods were associated with greater information availability. Only 4 of 7 methods (portals, interfaces, single vendor networks and multi-vendor networks but not access to outside EHR, regional exchange or Direct using a HISP) were associated with more frequent use of information, and single vendor networks were most strongly associated with more frequent use (odds ratio = 4.7, P < .001).

DISCUSSION

Adoption of some methods was correlated, indicating complementary use. Few methods were negatively correlated, indicating limited competition. Although information availability was common, low correlation with use indicated that challenges related to integration may be slowing use of information.

CONCLUSION

Complementarities between methods, and the role of integration in supporting information use, indicate the potential value of efforts aimed at ensuring exchange methods work well together, such as the Trusted Exchange Framework and Common Agreement.

Diabetes And The Fragmented State Of US Health Care And Policy

Progress in the prevention and treatment of type 2 diabetes-the dominant form of diabetes-appears to have stalled in the US over the past decade, and diabetes-related morbidity has increased nationally. The most geographically and socioeconomically disadvantaged segments of the population have been especially hard hit, and interventions that reduce the risk for diabetes have not reached these populations. In this overview article we lay out how fragmentation in health policy and governance, payers and reimbursement design, and service delivery in the US has contributed to low accountability and coordination, and thus stagnation and persistent inequities. We also review the evidence regarding past, ongoing, and new reforms that may help address fragmentation, lower diabetes burdens, and narrow disparities.

Digital Health Applications in Oncology: An Opportunity to Seize

Digital health advances have transformed many clinical areas including psychiatric and cardiovascular care. However, digital health innovation is relatively nascent in cancer care, which represents the fastest growing area of health-care spending. Opportunities for digital health innovation in oncology include patient-facing technologies that improve patient experience, safety, and patient-clinician interactions; clinician-facing technologies that improve their ability to diagnose pathology and predict adverse events; and quality of care and research infrastructure to improve clinical workflows, documentation, decision support, and clinical trial monitoring. The COVID-19 pandemic and associated shifts of care to the home and community dramatically accelerated the integration of digital health technologies into virtually every aspect of oncology care. However, the pandemic has also exposed potential flaws in the digital health ecosystem, namely in clinical integration strategies; data access, quality, and security; and regulatory oversight and reimbursement for digital health technologies. Stemming from the proceedings of a 2020 workshop convened by the National Cancer Policy Forum of the National Academies of Sciences, Engineering, and Medicine, this article summarizes the current state of digital health technologies in medical practice and strategies to improve clinical utility and integration. These recommendations, with calls to action for clinicians, health systems, technology innovators, and policy makers, will facilitate efficient yet safe integration of digital health technologies into cancer care.

What Factors Affect Whether Patients Return to the Same Surgeon to Replace the Contralateral Joint? A Study of Over 200,000 Patients

BACKGROUND

Patients with hip and knee arthritis often undergo bilateral total hip arthroplasty (THA) and total knee arthroplasty (TKA) in a staged or simultaneous fashion. However, when staged, the incidence and factors associated with having both procedures performed by the same surgeon or different surgeon are not well studied.

METHODS

All patients undergoing nonsimultaneous bilateral THA or TKA for osteoarthritis were abstracted from the 2010 to 2020 PearlDiver Mariner administrative database. The National Provider Identifier number was used to determine whether the same surgeon performed both surgeries. Demographics, comorbidities, and 90-day complications after the first joint replacement were assessed as possible independent predictors of utilizing a different surgeon for the contralateral joint.

RESULTS

Of 87,593 staged bilateral THAs, the same surgeon performed 40,707 (46.5%) arthroplasties. Of 147,938 staged bilateral TKAs, the same surgeon performed 77,072 (52.1%) arthroplasties. Notably, older cohorts of patients had independent, stepwise, and significantly greater odds of changing surgeons for the contralateral THA and TKA. Those patients who were insured by Medicare and Medicaid had significantly lower odds of changing surgeons. For both THA and TKA, surgical and implant-related adverse events (surgical site infection/periprosthetic joint infection, periprosthetic fracture, dislocation, manipulation) carried the greatest odds of undergoing the contralateral replacement with a different surgeon.

CONCLUSION

Patients covered by Medicaid and sicker patients were significancy less likely to switch surgeons for their contralateral THA or TKA. Additionally, patients experiencing a surgery-related adverse event within 90 days of their first THA or TKA had significantly, increased odds of switching surgeons for their subsequent TJA.

Association of Hospital Interoperable Data Sharing With Alternative Payment Model Participation

Importance

Interoperable patient data exchange across hospitals remains an important policy goal for reducing costs and improving the quality of care. Congress designated 2018 as the goal for nationwide interoperability, and policy makers hoped that aligning financial incentives via alternative payment models (APMs) would help achieve that goal.

Objective

To measure interoperability progress since 2014, assess the association between alternative payment model participation and hospital engagement in interoperable data sharing from 2014 to 2018, and evaluate hospital-reported barriers to interoperability in 2018.

Design Setting and Participants

This cohort study included nonfederal acute care hospitals in the US from January 2014 to December 2018 that responded to the American Hospital Association Annual Survey. Data were analyzed from October 2019 through March 2021.

Exposures

Participation in an APM, including accountable care organizations, bundled payments, or patient-centered medical homes.

Main Outcomes and Measures

Hospital engagement in all 4 domains of interoperability: finding/querying for data, sending data electronically, receiving data electronically, and integrating electronic patient data from external care delivery organizations.

Results

The sample included 3928 hospitals in the US from January 2014 to December 2018. Progress across interoperability domains was uneven, 2430 (88.3%) hospitals sending and 2115 (76.9%) receiving patient data electronically in 2018. However, only 1249 (45.4%) hospitals engaged in all 4 domains of interoperability in 2018, and growth between 2014 and 2018 was slow. There was no evidence that participation in APMs was associated with interoperability, with multivariate models suggesting that participation in an APM was associated with only a non-statistically significant 1-percentage point increase in interoperability engagement (β = 0.01; 95% CI, -0.01 to 0.03). The most commonly cited barrier to interoperability was challenges associated with sharing data across different electronic health record vendors.

Conclusions and Relevance

In this cohort study of hospital interoperability, fewer than half of US hospitals were engaged in interoperable data exchange in 2018. There was no observable evidence that hospital APM participation was associated with interoperability engagement. Many hospitals report technical and governance challenges to data sharing that are unlikely to be addressed by the alignment of financial incentives alone.

EHR-Integrated Monitor Data to Measure Pulse Oximetry Use in Bronchiolitis

BACKGROUND AND OBJECTIVES

Continuous pulse oximetry (oxygen saturation [Spo₂]) monitoring in hospitalized children with bronchiolitis not requiring supplemental oxygen is discouraged by national guidelines, but determining monitoring status accurately requires in-person observation. Our objective was to determine if electronic health record (EHR) data can accurately estimate the extent of actual Spo₂ monitoring use in bronchiolitis.

METHODS

This repeated cross-sectional study included infants aged 8 weeks through 23 months hospitalized with bronchiolitis. In the validation phase at 3 children's hospitals, we calculated the test characteristics of the Spo₂ monitor data streamed into the EHR each minute when monitoring was active compared with in-person observation of Spo₂ monitoring use. In the application phase at 1 children's hospital, we identified periods when supplemental oxygen was administered using EHR flowsheet documentation and calculated the duration of Spo₂ monitoring that occurred in the absence of supplemental oxygen.

RESULTS

Among 668 infants at 3 hospitals (validation phase), EHR-integrated Spo₂ data from the same minute as in-person observation had a sensitivity of 90%, specificity of 98%, positive predictive value of 88%, and negative predictive value of 98% for actual Spo₂ monitoring use. Using EHR-integrated data in a sample of 317 infants at 1 hospital (application phase), infants were monitored in the absence of oxygen supplementation for a median 4.1 hours (interquartile range 1.4-9.4 hours). Those who received supplemental oxygen experienced a median 5.6 hours (interquartile range 3.0-10.6 hours) of monitoring after oxygen was stopped.

CONCLUSIONS

EHR-integrated monitor data are a valid measure of actual Spo₂ monitoring use that may help hospitals more efficiently identify opportunities to deimplement guideline-inconsistent use.

The effect of participation in accountable care organization on electronic health information exchange practices in U.S. hospitals

BACKGROUND

Accountable care organizations (ACOs) are a recent incentive program that are designed to address inefficiencies in the U.S. health care sector. To meet their design objectives, ACO participants must engage in greater electronic health information exchange (HIE) practices both internally and externally with care participants, such as patients and other providers.

PURPOSE

The aim of this study was to examine the relationship between hospital participation in ACOs and electronic HIE practices with different participants of care and how these practices vary differentially across market types.

APPROACH

Grounding our work in the reward-motivational view of organizational action, we proposed hypotheses that linked hospital participation in ACOs to three dimensions of HIE practices (intraorganizational, interorganizational, and provider-patient HIE practices). We tested our hypotheses by analyzing a sample of 1,926 hospitals.

RESULTS

Hospital participation in ACOs is associated with greater intraorganizational and provider-patient HIE practices, but not interorganizational HIE practices. We also found that whereas the relationship between ACO participation and intra- and interorganizational HIE practices remains unchanged irrespective of the degree of competition in the health care market, the relationship between ACO participation and provider-patient HIE practices holds true only for hospitals operating in noncompetitive markets.

PRACTICE IMPLICATIONS

Our results showed that hospitals participating in ACOs vary in their HIE practices, and attributes of the local market in which ACO participants operate in contribute to this variation. These insights should provide guidance to researchers, policymakers, and hospital administrators who aim to improve the effectiveness of ACOs.

A qualitative study of prevalent laboratory information systems and data communication patterns for genetic test reporting

PURPOSE

The availability of genetic test data within the electronic health record (EHR) is a pillar of the US vision for an interoperable health IT infrastructure and a learning health system. Although EHRs have been highly investigated, evaluation of the information systems used by the genetic labs has received less attention-but is necessary for achieving optimal interoperability. This study aimed to characterize how US genetic testing labs handle their information processing tasks.

METHODS

We followed a qualitative research method that included interviewing lab representatives and a panel discussion to characterize the information flow models.

RESULTS

Ten labs participated in the study. We identified three generic lab system models and their relevant characteristics: a backbone system with additional specialized systems for interpreting genetic results, a brokering system that handles housekeeping and communication, and a single primary system for results interpretation and report generation.

CONCLUSION

Labs have heterogeneous workflows and generally have a low adoption of standards when sending genetic test reports back to EHRs. Core interpretations are often delivered as free text, limiting their computational availability for clinical decision support tools. Increased provision of genetic test data in discrete and standard-based formats by labs will benefit individual and public health.

Identification and Management of Adolescent Depression in a Large Pediatric Care Network

OBJECTIVE

Primary care has been promoted as a setting to identify and manage adolescent depression. This study examined primary care-based adolescent depression identification and follow-up care when elevated symptoms were identified.

METHODS

Data came from a large pediatric care network with an organizational recommendation to screen for depression at age 16 well-visits using an electronic health record (EHR)-integrated standardized measure. Analyses examined rates of screening and elevated symptoms, pediatricians' initial responses to elevated scores, and types of follow-up care received over 1 year using retrospective EHR data extraction and manual chart reviews.

RESULTS

Across program sites, 76.3% (n = 6981) of patients attending their age 16 well-visits were screened. About one-quarter had an elevated score (19.2% mild and 6.7% moderate-to-severe), many of whom received active follow-up on their well-visit date. Over 1 year, three-fourths of patients with scores in the moderate-to-severe range and 40.0% of patients with scores in the mild range received follow-up care (e.g., antidepressant prescriptions) as per EHR extraction. Follow-up rates were higher as per manual chart reviews.

CONCLUSION

Routine adolescent depression screening is feasible across diverse primary care sites. Most patients with elevated scores were not already receiving behavioral health services, suggesting screening identified previously undetected concerns. In turn, many adolescents with elevated scores initiated treatment after screening, which indicates providing screen results at the point of care may facilitate pediatrician actions. Still, gaps in follow-up care demonstrate the need for greater investment in primary care-based behavioral health services to support high-quality treatment and ultimately decrease the burden of adolescent depression.

Identifying Opportunities to Strengthen the Public Health Informatics Infrastructure: Exploring Hospitals' Challenges with Data Exchange

Policy Points Even though most hospitals have the technological ability to exchange data with public health agencies, the majority continue to experience challenges. Most challenges are attributable to the general resources of public health agencies, although workforce limitations, technology issues such as a lack of data standards, and policy uncertainty around reporting requirements also remain prominent issues. Ongoing funding to support the adoption of technology and strengthen the development of the health informatics workforce, combined with revising the promotion of the interoperability scoring approach, will likely help improve the exchange of electronic data between hospitals and public health agencies.

CONTEXT

The novel coronavirus 2019 (COVID-19) pandemic has highlighted significant barriers in the exchange of essential information between hospitals and local public health agencies. Thus it remains important to clarify the specific issues that hospitals may face in reporting to public health agencies to inform focused approaches to improve the information exchange for the current pandemic as well as ongoing public health activities and population health management.

METHODS

This study uses cross-sectional data of acute-care, nonfederal hospitals from the 2017 American Hospital Association Annual Survey and Information Technology supplement. Guided by the technology-organization-environment framework, we coded the responses to a question regarding the challenges that hospitals face in submitting data to public health agencies by using content analysis according to the type of challenge (i.e., technology, organization, or environment), responsible entity (i.e., hospital, public health agency, vendor, multiple), and the specific issue described. We used multivariable logistic and multinomial regression to identify characteristics of hospitals associated with experiencing the types of challenges.

FINDINGS

Our findings show that of the 2,794 hospitals in our analysis, 1,696 (61%) reported experiencing at least one challenge in reporting health data to a public health agency. Organizational issues were the most frequently reported type of challenge, noted by 1,455 hospitals. The most common specific issue, reported by 1,117 hospitals, was the general resources of public health agencies. An advanced EHR system and participation in a health information exchange both decreased the likelihood of not reporting experiencing a challenge and increased the likelihood of reporting an organizational challenge.

CONCLUSIONS

Our findings inform policy recommendations such as improving data standards, increasing funding for public health agencies to improve their technological capabilities, offering workforce training programs, and increasing clarity of policy specifications and reporting. These approaches can improve the exchange of information between hospitals and public health agencies.

Hospital adoption of multiple health information exchange approaches and information accessibility

OBJECTIVE

Hospital engagement in electronic health information exchange (HIE) has increased over recent years. We aimed to 1) determine the change in adoption of 3 types of information exchange: secure messaging, provider portals, and use of an HIE; and 2) to assess if growth in each approach corresponded to increased ability to access and integrate patient information from outside providers.

METHODS

Panel analysis of all nonfederal, acute care hospitals in the United States using hospital- and year-fixed effects. The sample consisted of 1917 hospitals that responded to the American Hospital Association Information Technology Supplement every year from 2014 to 2016.

RESULTS

Adoption of each approach increased by 9-15 percentage points over the study period. The average number of HIE approaches used by each hospital increased from 1.0 to 1.4. Adoption of each approach was associated with increased likelihood that providers routinely had necessary outside information of 4.2-12.7 percentage points and 4.5-13.3 percentage points increase in information integration. Secure messaging was associated with the largest increase in both. Adoption of 1 approach increased the likelihood of having outside information by 10.3 percentage points, while adopting a second approach further increased the likelihood by 9.5 percentage points. Trends in number of approaches and integration were similar.

DISCUSSION/CONCLUSION

No single HIE tool provided high levels of usable, integrated health information. Instead, hospitals benefited from adopting multiple tools. Policy initiatives that reduce the complexity of enabling high value HIE could result in broader adoption of HIE and use of information to inform care.

Ensuring electronic medical record simulation through better training, modeling, and evaluation

OBJECTIVE

Electronic medical records (EMRs) can support medical research and discovery, but privacy risks limit the sharing of such data on a wide scale. Various approaches have been developed to mitigate risk, including record simulation via generative adversarial networks (GANs). While showing promise in certain application domains, GANs lack a principled approach for EMR data that induces subpar simulation. In this article, we improve EMR simulation through a novel pipeline that (1) enhances the learning model, (2) incorporates evaluation criteria for data utility that informs learning, and (3) refines the training process.

MATERIALS AND METHODS

We propose a new electronic health record generator using a GAN with a Wasserstein divergence and layer normalization techniques. We designed 2 utility measures to characterize similarity in the structural properties of real and simulated EMRs in the original and latent space, respectively. We applied a filtering strategy to enhance GAN training for low-prevalence clinical concepts. We evaluated the new and existing GANs with utility and privacy measures (membership and disclosure attacks) using billing codes from over 1 million EMRs at Vanderbilt University Medical Center.

RESULTS

The proposed model outperformed the state-of-the-art approaches with significant improvement in retaining the nature of real records, including prediction performance and structural properties, without sacrificing privacy. Additionally, the filtering strategy achieved higher utility when the EMR training dataset was small.

CONCLUSIONS

These findings illustrate that EMR simulation through GANs can be substantially improved through more appropriate training, modeling, and evaluation criteria.

Wireless skin sensors for physiological monitoring of infants in low-income and middle-income countries

Globally, neonatal mortality remains unacceptability high. Physiological monitoring is foundational to the care of these vulnerable patients to assess neonatal cardiopulmonary status, guide medical intervention, and determine readiness for safe discharge. However, most existing physiological monitoring systems require multiple electrodes and sensors, which are linked to wires tethered to wall-mounted display units, to adhere to the skin. For neonates, these systems can cause skin injury, prevent kangaroo mother care, and complicate basic clinical care. Novel, wireless, and biointegrated sensors provide opportunities to enhance monitoring capabilities, reduce iatrogenic injuries, and promote family-centric care. Early validation data have shown performance equivalent to (and sometimes exceeding) standard-of-care monitoring systems in premature neonates cared for in high-income countries. The reusable nature of these sensors and compatibility with low-cost mobile phones have the future potential to enable substantially lower monitoring costs compared with existing systems. Deployment at scale, in low-income countries, holds the promise of substantial improvements in neonatal outcomes.

Leadership Perspectives on Implementing Health Information Exchange: Qualitative Study in a Tertiary Veterans Affairs Medical Center

Background

The US Department of Veterans Affairs (VA) seeks to achieve interoperability with other organizations, including non-VA community and regional health information exchanges (HIEs).

Objective

This study aims to understand the perspectives of leaders involved in implementing information exchange between VA and non-VA providers via a community HIE.

Methods

We interviewed operational, clinical, and information technology leaders at one VA facility and its community HIE partner. Respondents discussed their experiences with VA-HIE, including barriers and facilitators to implementation, and the associated impact on health care providers. Transcribed interviews were coded and analyzed using immersion-crystallization methods.

Results

VA and community HIE leaders found training to be a key factor when implementing VA-HIE and worked cooperatively to provide several styles and locations of training. During recruitment, a high-touch approach was successfully used to enroll patients and overcome their resistance to opting in. Discussion with leaders revealed the high levels of complexity navigated by VA providers and staff to send and retrieve information. Part of the complexity stemmed from the interconnected web of information systems and human teams necessary to implement VA-HIE information sharing. These interrelationships must be effectively managed to guide organizational decision making.

Conclusions

Organizational leaders perceived information sharing to be of essential value in delivering high-quality, coordinated health care. The VA continues to increase access to outside care through the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act. Along with this increase in non-VA medical care, there is a need for greater information sharing between VA and non-VA health care organizations. Insights by leaders into barriers and facilitators to VA-HIE can be applied by other national and regional networks that seek to achieve interoperability across health care delivery systems.

Unfulfilled promises of health information exchange: What inhibits ambulatory clinics from electronically sharing health information?

PURPOSE

This study seeks to understand the key inhibitors for health information exchange (HIE) by ambulatory (outpatient) clinics. We examine the key technological, organizational and environmental factors that inhibit an ambulatory clinic from electronically exchanging health information with external clinics and hospitals.

METHODS

We utilize survey data from 1285 ambulatory clinics in the US state of Minnesota. Using logistic regressions, we assess if the ambulatory clinic's HIE with external clinics and external hospitals are associated with fourteen inhibitors from technological, organizational and environmental contexts in which ambulatory clinics operate.

RESULTS

Among the technological inhibitors, we find lack of adequate technological infrastructure, difficulties in integrating external data with electronic medical record systems, and security concerns to inhibit ambulatory clinics' HIE with both clinics and hospitals. Inadequate technical support was a barrier for HIE with hospitals, whereas inadequate training of staff was an inhibitor for clinic-to-clinic HIE. Of the environmental variables, legal concerns and complexity in framing HIE agreements with partners were found to inhibit ambulatory clinics' HIE with both external clinics and hospitals. Lack of partner readiness and ability was an inhibiting factor for clinic-to-hospital HIE whereas issues in patient consent, and problems in choosing the right vendor with a good fit were inhibiting ambulatory clinics' HIE with other clinics. Among the organizational variables, lack of adequate senior leadership support and complexity of workflow changes inhibited clinic-to-clinic health data sharing, whereas unclear return on investment (ROI) for HIE was a deterrent for ambulatory clinics' HIE with hospitals.

CONCLUSIONS

This study throws light on electronic HIE practices and its key inhibitors in ambulatory clinics, an understudied area in digital health. This paper provides unique insights into specific inhibitors that deter clinic-to-clinic health information sharing versus those that affect and clinic-to-hospital health information exchange.

Assessment of Electronic Health Record Use Between US and Non-US Health Systems

Importance

Understanding how the electronic health record (EHR) system changes clinician work, productivity, and well-being is critical. Little is known regarding global variation in patterns of use.

Objective

To provide insights into which EHR activities clinicians spend their time doing, the EHR tools they use, the system messages they receive, and the amount of time they spend using the EHR after hours.

Design, Setting, and Participants

This cross-sectional study analyzed the deidentified metadata of ambulatory care health systems in the US, Canada, Northern Europe, Western Europe, the Middle East, and Oceania from January 1, 2019, to August 31, 2019. All of these organizations used the EHR software from Epic Systems and represented most of Epic Systems's ambulatory customer base. The sample included all clinicians with scheduled patient appointments, such as physicians and advanced practice practitioners.

Exposures

Clinician EHR use was tracked by deidentified and aggregated metadata across a variety of clinical activities.

Main Outcomes and Measures

Descriptive statistics for clinician EHR use included time spent on clinical activities, note documentation (as measured by the percentage of characters in the note generated by automated or manual data entry source), messages received, and time spent after hours.

Results

A total of 371 health systems were included in the sample, of which 348 (93.8%) were located in the US and 23 (6.2%) were located in other countries. US clinicians spent more time per day actively using the EHR compared with non-US clinicians (mean time, 90.2 minutes vs 59.1 minutes; P < .001). In addition, US clinicians vs non-US clinicians spent significantly more time performing 4 clinical activities: notes (40.7 minutes vs 30.7 minutes; P < .001), orders (19.5 minutes vs 8.75 minutes; P < .001), in-basket messages (12.5 minutes vs 4.80 minutes; P < .001), and clinical review (17.6 minutes vs 14.8 minutes; P = .01). Clinicians in the US composed more automated note text than their non-US counterparts (77.5% vs 60.8% of note text; P < .001) and received statistically significantly more messages per day (33.8 vs 12.8; P < .001). Furthermore, US clinicians used the EHR for a longer time after hours, logging in 26.5 minutes per day vs 19.5 minutes per day for non-US clinicians (P = .01). The median US clinician spent as much time actively using the EHR per day (90.1 minutes) as a non-US clinician in the 99th percentile of active EHR use time per day (90.7 minutes) in the sample. These results persisted after controlling for organizational characteristics, including structure, type, size, and daily patient volume.

Conclusions and Relevance

This study found that US clinicians compared with their non-US counterparts spent substantially more time actively using the EHR for a wide range of clinical activities or tasks. This finding suggests that US clinicians have a greater EHR burden that may be associated with nontechnical factors, which policy makers and health system leaders should consider when addressing clinician wellness.

Reporting of demographic data and representativeness in machine learning models using electronic health records

OBJECTIVE

The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. However, questions have arisen regarding biases in their development that can affect their applicability in specific populations. We sought to evaluate whether studies developing ML models from electronic health record (EHR) data report sufficient demographic data on the study populations to demonstrate representativeness and reproducibility.

MATERIALS AND METHODS

We searched PubMed for articles applying ML models to improve clinical decision-making using EHR data. We limited our search to papers published between 2015 and 2019.

RESULTS

Across the 164 studies reviewed, demographic variables were inconsistently reported and/or included as model inputs. Race/ethnicity was not reported in 64%; gender and age were not reported in 24% and 21% of studies, respectively. Socioeconomic status of the population was not reported in 92% of studies. Studies that mentioned these variables often did not report if they were included as model inputs. Few models (12%) were validated using external populations. Few studies (17%) open-sourced their code. Populations in the ML studies include higher proportions of White and Black yet fewer Hispanic subjects compared to the general US population.

DISCUSSION

The demographic characteristics of study populations are poorly reported in the ML literature based on EHR data. Demographic representativeness in training data and model transparency is necessary to ensure that ML models are deployed in an equitable and reproducible manner. Wider adoption of reporting guidelines is warranted to improve representativeness and reproducibility.

Accuracy of an Electronic Health Record Patient Linkage Module Evaluated between Neighboring Academic Health Care Centers

BACKGROUND

Patients often seek medical treatment among different health care organizations, which can lead to redundant tests and treatments. One electronic health record (EHR) platform, Epic Systems, uses a patient linkage tool called Care Everywhere (CE), to match patients across institutions. To the extent that such linkages accurately identify shared patients across organizations, they would hold potential for improving care.

OBJECTIVE

This study aimed to understand how accurate the CE tool with default settings is to identify identical patients between two neighboring academic health care systems in Southern California, The University of California Los Angeles (UCLA) and Cedars-Sinai Medical Center.

METHODS

We studied CE patient linkage queries received at UCLA from Cedars-Sinai between November 1, 2016, and April 30, 2017. We constructed datasets comprised of linkages ("successful" queries), as well as nonlinkages ("unsuccessful" queries) during this time period. To identify false positive linkages, we screened the "successful" linkages for potential errors and then manually reviewed all that screened positive. To identify false-negative linkages, we applied our own patient matching algorithm to the "unsuccessful" queries and then manually reviewed a sample to identify missed patient linkages.

RESULTS

During the 6-month study period, Cedars-Sinai attempted to link 181,567 unique patient identities to records at UCLA. CE made 22,923 "successful" linkages and returned 158,644 "unsuccessful" queries among these patients. Manual review of the screened "successful" linkages between the two institutions determined there were no false positives. Manual review of a sample of the "unsuccessful" queries (n = 623), demonstrated an extrapolated false-negative rate of 2.97% (95% confidence interval [CI]: 1.6-4.4%).

CONCLUSION

We found that CE provided very reliable patient matching across institutions. The system missed a few linkages, but the false-negative rate was low and there were no false-positive matches over 6 months of use between two nearby institutions.

Are Patients Electronically Accessing Their Medical Records? Evidence From National Hospital Data

Substantial policy effort has been directed at improving patients' ability to access and use electronic health records. Using nationwide data from 2,410 hospitals for the period 2014-16, we examined associations between patient- and hospital-level characteristics and access to and use of electronic health record data among discharged patients. On average, hospitals gave 95 percent of discharged patients access to view, download, and transmit their information, but only about 10 percent of those with access used it-levels that were stagnant during the study period. Access rates were highest among system-member, teaching, and for-profit hospitals. In contrast, access rates were lower for hospitals in the highest quartile for disproportionate share hospital status and for hospitals located in counties with high proportions of residents who were dually eligible for Medicare and Medicaid; use rates were lower for hospitals in counties with a high proportion of residents who were dually eligible, lacked computer or internet access, or were Hispanic. Overall, our findings suggest that policy efforts have failed to engage a large proportion of patients in the electronic use of their data or to bridge the "digital divide" that accompanies health care disparities. Additional-possibly targeted-policy incentives, as well as higher thresholds for meeting the requirements of the Promoting Interoperability Program, merit policy makers' consideration.

Potential value of electronic health records in capturing data on geriatric frailty for population health

OBJECTIVES

Despite the availability of many frailty measures to identify older adults at risk, frailty instruments are not routinely used for risk assessment in population health management. Here, we assessed the potential value of electronic health records (EHRs) and administrative claims in providing the necessary data for variables used across various frailty instruments.

SETTING AND PARTICIPANTS

The review focused on studies conducted worldwide. Participants included older people aged 50 and older.

DESIGN

We identified frailty instruments published between 2011 and 2018. Frailty variables used in each of the frailty instruments were extracted, grouped, and categorized across health determinants and various clinical factors.

MEASURES

The availability of the extracted frailty variables across various data sources (e.g., EHRs, administrative claims, and surveys) was evaluated by experts.

RESULTS

We identified 135 frailty instruments, which contained 593 unique variables. Clinical determinants of health were the best represented variables across frailty instruments (n = 516; 87 %), unlike social and health services factors (n = 33; ∼5% and n = 32; ∼5%). Most frailty instruments require at least one variable that is not routinely available in EHRs or claims (n = 113; ∼83 %). Only 22 frailty instruments have the potential to completely rely on EHR (structured or free-text data) and/or claims data, and possibly be operationalized on a population-level.

CONCLUSIONS AND IMPLICATIONS

Frailty instruments continue to be highly survey-based. More research is therefore needed to develop EHR-based frailty instruments for population health management. This will permit organizations and societies to stratify risk and better allocate resources among different older adult populations.

Achieving a Quintuple Aim for Telehealth in Pediatrics

Pediatric practice increasingly involves providing care for children with medical complexity. Telehealth offers a strategy for providers and health care systems to improve care for these patients and their families. However, lack of awareness related to the unintended negative consequences of telehealth on vulnerable populations--coupled with failure to intentional design best practices for telehealth initiatives--implies that these novel technologies may worsen health disparities in the long run. This article reviews the positive and negative implications of telehealth. In addition, to achieve optimal implementation of telehealth, it discusses 10 considerations to promote optimal care of children using these technologies.

Leveraging health information exchange for clinical research: Extreme underreporting of hospital service utilization among patients with substance use disorders

BACKGROUND

Substance use disorders are associated with inefficient and fragmented use of healthcare services. The Chesapeake Regional Information System for Our Patients, Inc. (CRISP) is a Health Information Exchange (HIE) linking disparate systems of care in the mid-Atlantic region.

METHODS

This article describes applications of HIE for tracking hospital service utilization in substance use disorder clinical and services research, drawing upon data from one of the first studies approved to access the CRISP HIE. Participants were 200 medical/surgical inpatients with comorbid opioid, cocaine, and/or alcohol use disorder (45.5 % female; 56.5 % black; 77.5 % opioid use disorder; 42.0 % homeless). This study compared HIE-identified hospital service utilization with conventional methods of participant self-report during in-person research follow-ups (3-, 6-, and 12-months post-discharge) and electronic health record (EHR) review from the hospital system of the index admission.

RESULTS

This sample exhibited high levels of hospital utilization, which would have been underestimated using conventional methods. Relying exclusively on self-report in the 12-month observation period would have identified only 33.8 % of 429 inpatient hospitalizations and 9.0 % of 1,287 ED visits, due to both loss-to-follow-up and failure to report events. Even combining self-report with single-system EHR review identified only 66.2 % of inpatient hospitalizations and 59.8 % of ED visits.

CONCLUSIONS

CRISP HIE data were superior to conventional methods for ascertaining hospital service utilization in this sample of patients exhibiting high-volume and fragmented care. The use of HIE holds implications for improving rigor, safety, and efficiency in research studies.

Technology-facilitated care coordination in rural areas: What is needed?

BACKGROUND

Health is poorer in rural areas and a major challenge is care coordination for complex chronic conditions. The HITECH and 21st Century Cure Acts emphasize health information exchange which underpins activities required to improve care coordination.

OBJECTIVE AND METHODS

Using semi-structured interviews and surveys, we examined how providers experience electronic health information exchange during care coordination since these Acts were implemented, with a focus on rural settings where health disparities exist. We used a purposive sample that included primary care, acute care hospitals, and community health services in the United States.

FINDINGS

We identified seven themes related to care coordination and information exchange: 'insufficient trust of data'; 'please respond'; 'just fax it'; 'care plans'; 'needle in the haystack'; 're-documentation'; and 'rural reality'. These gaps were magnified when information exchange was required between unaffiliated electronic health records (EHRs) about shared patients, which was more pronounced in rural settings.

CONCLUSION

Policy and incentive modifications are likely needed to overcome the observed health information technology (HIT) shortcomings. Rural settings in the United States accentuate problems that can be addressed through international medical informatics policy makers and the implementation and evaluation of interoperable HIT systems.

Health Data Sharing in US Nursing Homes: A Mixed Methods Study

OBJECTIVES

(1) To understand the extent to which nursing homes have the capability for data sharing and (2) to explore nursing home leaders' perceptions of data sharing with other health care facilities and with residents and family members.

DESIGN

Exploratory, mixed-methods.

SETTING AND PARTICIPANTS

We conducted a secondary analysis of data from a national survey of nursing home administrative leaders (n = 815) representing every state in the United States. Next, semistructured interviews were used to elicit rich contextual information from (n = 12) administrators from nursing homes with varying data-sharing capabilities.

METHODS

We used descriptive statistics along with Rao-Scott chi-square and logistic regression models to examine the relationship between health data-sharing capabilities and nursing home characteristics such as location, bed size, and type of ownership. Qualitative data were analyzed using content analysis.

RESULTS

Of the 815 nursing homes completing the survey, 95% had computerized (electronic) medical records, and 46% had some capability for health information exchange. Nursing homes located in metropolitan areas had 2.53 (95% confidence interval = 1.53, 4.18) times greater odds for having health information exchange capability compared with nursing homes in small towns. Perceived challenges to health data sharing with residents and family members and external clinical partners include variance in systems and software, privacy and security concerns, and organizational factors slowing uptake of technology. Perceived benefits of health data sharing included improved communication, improved care planning, and anticipating future demand.

CONCLUSIONS AND IMPLICATIONS

As health data sharing becomes more ubiquitous in acute care settings, policy makers, nursing home leaders, and other stakeholders should prepare by working to mitigate barriers and capitalize on potential benefits of implementing this technology in nursing homes.

Association of the Meaningful Use Electronic Health Record Incentive Program With Health Information Technology Venture Capital Funding

Importance

Although the Health Information Technology for Economic and Clinical Health (HITECH) Act has accelerated electronic health record (EHR) adoption since its passage, clinician satisfaction with EHRs remains low, and the association of HITECH with health care information technology (IT) entrepreneurship has remained largely unstudied.

Objective

To determine whether the passage of the HITECH Act was associated with an increase in key measures of health care IT entrepreneurship.

Design, Setting, and Participants

This economic evaluation of venture capital (VC) activity in the US from 2000 to 2019 examined funding trends in health care IT, EHR-related companies, and all VC investments before and after the passage of HITECH. A difference-in-differences analysis compared investments in health care IT companies with those of companies in 3 categories: general health care (non-IT), IT (non-health care), and all US VC transactions. Data were analyzed from September 2018 to August 2019.

Exposures

Venture capital funding received by US companies before and after the HITECH Act.

Main Outcomes and Measures

Venture capital investment in health care IT companies and the proportion of those investments going to seed-stage companies, a proxy for very early-stage entrepreneurship and innovation.

Results

The data included 70 982 investments, of which 9425 (13.3%) were seed stage, 10 706 (15.1%) were early stage, and 50 851 (71.6%) were growth stage. After passage of the HITECH Act, investment in both health care IT companies and EHR-related companies increased at a rate much faster (13.0% and 11.4%, respectively) than VC as a whole (6.9%). In addition, the proportion of investments going to seed-stage health care IT companies increased compared with both overall VC investments and non-IT health care investments. Health care IT companies saw increased probabilities of transactions being seed-stage of 5.1% (SE, 2.2%; 95% CI, 0.8% to 9.3%; P = .02) compared with the entire sample of VC transactions and 13.6% (SE, 1.9%; 95% CI, 9.9% to 17.2%; P < .001) compared with non-IT health care VC transactions. Health care IT had essentially 0 increased probability of a transaction being seed stage compared with IT companies outside health care (-0.8% probability; SE, 2.4%; 95% CI, -5.4% to 3.9%; P = .75).

Conclusions and Relevance

Although widespread clinician dissatisfaction with EHR systems remains a challenge, the HITECH Act's incentive program may have catalyzed early-stage entrepreneurship in health care IT, suggesting an important role for incentives in promoting innovation.

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

BACKGROUND

Laboratory 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.

METHODS

As 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.

RESULTS

We 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).

CONCLUSIONS

The 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.

Impact of document consolidation on healthcare providers' perceived workload and information reconciliation tasks: a mixed methods study

Background

Information reconciliation is a common yet complex and often time-consuming task performed by healthcare providers. While electronic health record systems can receive "outside information" about a patient in electronic documents, rarely does the computer automate reconciling information about a patient across all documents.

Materials and Methods

Using a mixed methods design, we evaluated an information system designed to reconcile information across multiple electronic documents containing health records for a patient received from a health information exchange (HIE) network. Nine healthcare providers participated in scenario-based sessions in which they manually consolidated information across multiple documents. Accuracy of consolidation was measured along with the time spent completing 3 different reconciliation scenarios with and without support from the information system. Participants also attended an interview about their experience. Perceived workload was evaluated quantitatively using the NASA-TLX tool. Qualitative analysis focused on providers' impression of the system and the challenges faced when reconciling information in practice.

Results

While 5 providers made mistakes when trying to manually reconcile information across multiple documents, no participants made a mistake when the system supported their work. Overall perceived workload decreased significantly for scenarios supported by the system (37.2% in referrals, 18.4% in medications, and 31.5% in problems scenarios, P < 0.001). Information reconciliation time was reduced significantly when the system supported provider tasks (58.8% in referrals, 38.1% in medications, and 65.1% in problem scenarios).

Conclusion

Automating retrieval and reconciliation of information across multiple electronic documents shows promise for reducing healthcare providers' task complexity and workload.

Opt-in consent policies: potential barriers to hospital health information exchange

OBJECTIVES

To (1) assess whether hospitals in states requiring explicit patient consent ("opt-in") for health information exchange (HIE) are more likely to report regulatory barriers to HIE and (2) analyze whether these policies correlate with hospital volume of HIE.

STUDY DESIGN

Cross-sectional analysis of US nonfederal acute care hospitals in 2016.

METHODS

We combined legal scholarship surveying HIE-relevant state laws with the American Hospital Association Annual Information Technology Supplement for regulatory barriers and hospital characteristics. Data from CMS reports for hospitals attesting to Meaningful Use stage 2 (MU2; renamed "Promoting Interoperability" in 2018) in 2016 captured hospital HIE volume. We used multivariate logistic regression and linear regression to estimate the association of opt-in state consent policies with reported regulatory barriers and HIE volume, respectively.

RESULTS

Hospitals in states with opt-in consent policies were 7.8 percentage points more likely than hospitals in opt-out states to report regulatory barriers to HIE (P = .03). In subgroup analyses, this finding held among hospitals that did not attest to MU2 (7.7 percentage points; P = .02). Among hospitals attesting, we did not find a relationship between opt-in policies and regulatory barriers (8.0 percentage points; P = .13) or evidence of a relationship between opt-in policies and HIE volume (β = 0.56; P = .76).

CONCLUSIONS

Our findings suggest that opt-in consent laws may carry greater administrative burdens compared with opt-out policies. However, less technologically advanced hospitals may bear more of this burden. Furthermore, opt-in policies may not affect HIE volume for hospitals that have already achieved a degree of technological sophistication. Policy makers should carefully consider the incidence of administrative burdens when crafting laws pertaining to HIE.

Designing Quality Improvement Collaboratives for Dissemination: Lessons from a Multiple Case Study of the Implementation of Obstetric Emergency Safety Bundles

BACKGROUND

Quality improvement collaboratives (QICs) can help to disseminate evidence-based practices, but there is limited guidance from the perspectives of QIC organizers and participants of best practices to support practice change. To address this gap, this study aimed to identify key structures and processes of QICs that support dissemination and implementation of quality improvement projects.

METHODS

Semistructured one-on-one and group interviews were conducted from December 2017 to May 2018 with project administrators (n = 28) at three QICs that had been funded to develop and disseminate obstetric emergency safety bundles in more than 300 hospitals across five states. For further study, the project leads (n = 25) at six hospitals nominated by each QIC were interviewed. A multiple case study design was used to evaluate the dissemination strategies of each of the three QICs. For the QIC interviews, questions asked about dissemination approach, and for the hospital interviews, questions asked about implementation facilitators and barriers. All interviews were transcribed, coded, and analyzed using both deductive and inductive methods.

RESULTS

A key element supporting the dissemination strategy of each QIC was leveraging existing partnerships and relationships and promoting a shared vision with participating hospitals. A robust data infrastructure to support the project was identified as a critical element to support dissemination, yet was a challenge for the QICs.

CONCLUSION

These findings highlight specific elements of a dissemination approach that QICs can deploy to support their dissemination efforts. In particular, building data infrastructure may be a useful strategy to support ongoing quality improvement projects.

Assessing the impact of health system organizational structure on hospital electronic data sharing

Objective

Horizontal consolidation in the hospital industry has gained momentum in the United States despite concerns over rising costs and lower quality. Hospital systems frequently point to potential gains in interoperability and electronic exchange of patient information as consolidation benefits. We sought to assess whether hospitals in different health system structures varied in their interoperable data sharing.

Materials and methods

We created a cross-sectional national hospital sample from the 2014 AHA Annual Survey and 2015 IT Supplement. We combined the existing taxonomy of health system organizational forms and the ONC's functionality-based, technology-agnostic definition of interoperability. We used logistic regression models to assess the relationship between health systems' organizational forms and interoperability engagement, controlling for hospital characteristics.

Results

We found that interoperability engagement varied greatly across hospitals in different health system structures, with facilities in more centralized health systems more likely to be interoperable. Hospitals in one system type, featuring centralized insurance product development but diverse service offerings across member organizations, had significantly higher odds of being engaged in interoperable data sharing in our multivariate regression results.

Discussion

The heterogeneity in health system interoperability engagement indicates that incentives to share data vary greatly across organizational strategies and structures. Our results suggest that horizontal consolidation in the hospital industry may not bring significant gains in interoperability progress unless that consolidation takes a specific business alignment form.

Conclusion

Policymakers should be wary of claims that horizontal consolidation will lead to interoperability gains. Future research should explore the specific mechanisms that lead to greater interoperability in certain health system organizational structures.

Gaps in health information exchange between hospitals that treat many shared patients

Objective

Hospitals that routinely share patients are those that most critically need to engage in electronic health information exchange (HIE) with each other to ensure clinical information is available to inform treatment decisions. We surveyed pairs of hospitals in a nationwide sample to describe whether and how hospitals within each hospital referral region (HRR) that have the highest shared patient (HSP) volume engaged in HIE with each other.

Methods

We used Medicare's Physician Shared Patient Patterns data to identify hospital pairs with the highest shared patient volume in each hospital referral region. We surveyed a purposeful sample of pairs and then calculated descriptive statistics to compare: (1) HIE with the HSP hospital vs HIE with other hospitals, and (2) HIE with the HSP hospital versus federal measures of HIE engagement that are not partner-specific.

Results

We received responses from 25.5% of contacted hospitals and 33.5% of contacted pairs, allowing us to examine information sharing among 68 hospitals in 63 pairs. 23% of respondents reported worse information sharing with their HSP hospital than with other hospitals while 17% indicated better sharing with their HSP hospital and 48% indicated no difference. Our HSP-specific measures of HIE differed from federal measures of HIE engagement: while 97% of respondents are classified as routinely sending information electronically in federal measures, in our data only 63% did so with their HSP hospital.

Conclusions

Despite increased HIE engagement, our descriptive results indicate that HIE is not developing in a way that facilitates information exchange where it might benefit the most patients. New policy efforts, particularly those emerging from the 21st Century Cures Act, need to explicitly pursue strategies that ensure that HSP providers engage in exchange with each other.

Improving data sharing between acute hospitals in England: an overview of health record system distribution and retrospective observational analysis of inter-hospital transitions of care

OBJECTIVES

To determine the frequency of use and spatial distribution of health record systems in the English National Health Service (NHS). To quantify transitions of care between acute hospital trusts and health record systems to guide improvements to data sharing and interoperability.

DESIGN

Retrospective observational study using Hospital Episode Statistics.

SETTING

Acute hospital trusts in the NHS in England.

PARTICIPANTS

All adult patients resident in England that had one or more inpatient, outpatient or accident and emergency encounters at acute NHS hospital trusts between April 2017 and April 2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

Frequency of use and spatial distribution of health record systems. Frequency and spatial distribution of transitions of care between hospital trusts and health record systems.

RESULTS

21 286 873 patients were involved in 121 351 837 encounters at 152 included trusts. 117 (77.0%) hospital trusts were using electronic health records (EHR). There was limited regional alignment of EHR systems. On 11 017 767 (9.1%) occasions, patients attended a hospital using a different health record system to their previous hospital attendance. 15 736 863 (73.9%) patients had two or more encounters with the included trusts and 3 931 255 (25.0%) of those attended two or more trusts. Over half (53.6%) of these patients had encounters shared between just 20 pairs of hospitals. Only two of these pairs of trusts used the same EHR system.

CONCLUSIONS

Each year, millions of patients in England attend two or more different hospital trusts. Most of the pairs of trusts that commonly share patients do not use the same record systems. This research highlights significant barriers to inter-hospital data sharing and interoperability. Findings from this study can be used to improve electronic health record system coordination and develop targeted approaches to improve interoperability. The methods used in this study could be used in other healthcare systems that face the same interoperability challenges.

Blockchain-Enabled iWellChain Framework Integration With the National Medical Referral System: Development and Usability Study

Background

Medical referral is the transfer of a patient’s care from one physician to another upon request. This process involves multiple steps that require provider-to-provider and provider-to-patient communication. In Taiwan, the National Health Insurance Administration (NHIA) has implemented a national medical referral (NMR) system, which encourages physicians to refer their patients to different health care facilities to reduce unnecessary hospital visits and the financial stress on the national health insurance. However, the NHIA’s NMR system is a government-based electronic medical referral service, and its referral data access and exchange are limited to authorized clinical professionals using their national health smart cards over the NHIA virtual private network. Therefore, this system lacks scalability and flexibility and cannot establish trusting relationships among patients, family doctors, and specialists.

Objective

To eliminate the existing restrictions of the NHIA’s NMR system, this study developed a scalable, flexible, and blockchain-enabled framework that leverages the NHIA’s NMR referral data to build an alliance-based medical referral service connecting health care facilities.

Methods

We developed a blockchain-enabled framework that can integrate patient referral data from the NHIA’s NMR system with electronic medical record (EMR) and electronic health record (EHR) data of hospitals and community-based clinics to establish an alliance-based medical referral service serving patients, clinics, and hospitals and improve the trust in relationships and transaction security. We also developed a blockchain-enabled personal health record decentralized app (DApp) based on our blockchain-enabled framework for patients to acquire their EMR and EHR data; DApp access logs were collected to assess patients’ behavior and investigate the acceptance of our personal authorization-controlled framework.

Results

The constructed iWellChain Framework was installed in an affiliated teaching hospital and four collaborative clinics. The framework renders all medical referral processes automatic and paperless and facilitates efficient NHIA reimbursements. In addition, the blockchain-enabled iWellChain DApp was distributed for patients to access and control their EMR and EHR data. Analysis of 3 months (September to December 2018) of access logs revealed that patients were highly interested in acquiring health data, especially those of laboratory test reports.

Conclusions

This study is a pioneer of blockchain applications for medical referral services, and the constructed framework and DApp have been applied practically in clinical settings. The iWellChain Framework has the scalability to deploy a blockchain environment effectively for health care facilities; the iWellChain DApp has potential for use with more patient-centered applications to collaborate with the industry and facilitate its adoption.

Quantifying the competitiveness of the electronic health record market and its implications for interoperability

OBJECTIVE

The objective of this study was to quantify both the competitiveness of the EHR vendor market in the United States of America (US) and the degree of fragmentation of individual Medicare beneficiaries' medical records across the differing EHR vendors found in the US healthcare system.

METHODS AND MATERIALS

We determined the Part A and Part B Medicare-expenditure weighted market shares of EHR vendors and estimated the rate of attestation of meaningful use (MU) for EHRs among Medicare Part A & B providers from 2011 to 2016. Based on these data we calculated the annual Herfindahl-Hirschman Index to quantify the competitiveness of the EHR market as well as the number of vendors individual Medicare beneficiaries' medical records were stored in for the period 2014-2016.

RESULTS

We find that as of 2016 the EHR vendor environment was competitive but trending towards becoming highly concentrated soon. We also found that patient medical records were highly fragmented as only 4.5 % of expenditure-weighted individual Medicare beneficiaries had their MU medical records associated with a single vendor, while 19.8 % of expenditure-weighted beneficiaries had their MU medical records stored in 8 or more vendors.

DISCUSSION

These results indicate that there are tradeoffs between EHR market competition, and the challenges associated with achieving interoperability across numerous competing vendors.

CONCLUSION

Uncertainty of interoperability among different EHR vendors may make transmission of medical records among different providers challenging, mitigating the benefit of vendor competition. This highlights the critical importance of current interoperability efforts moving forward.