In the digital age, the promise of seamless electronic health records (EHR) has long tantalized both patients and healthcare providers alike. Yet, despite significant advancements in health informatics, a frustrating reality persists: when patients switch doctors or visit different healthcare facilities, their medical histories frequently fail to follow them. This discontinuity compromises not only the patient experience but potentially the quality of care delivered. A groundbreaking $1.4 million grant from the National Institutes of Health (NIH), awarded to researchers at the University of Maryland School of Public Health (SPH) and the University of California, San Francisco (UCSF), is now poised to investigate and address this critical issue, exploring how “outside data” – health records originating from institutions outside a primary provider’s system – influences clinical decision-making and patient outcomes.
At the heart of this research is Dr. Nate Apathy, a professor of health policy and management at UMD SPH, who highlights a persistent challenge in healthcare: the siloing of digitized medical records. “For decades, patients have faced the frustration of their digitized health data not moving with them as they transition between providers,” says Dr. Apathy. He notes that multiple systemic barriers—ranging from technological incompatibilities to administrative policies—introduce friction that prevents data sharing. This fragmented landscape leaves providers with incomplete clinical pictures, leading to redundant paperwork, repeated diagnostic tests, and potentially suboptimal care decisions.
The NIH-funded study bridges two academic health systems — UCSF Health and the University of Maryland Medical System — to assess the practical impact of integrated outside data on clinical workflows and outcomes. Both institutions have recently upgraded their IT infrastructure to allow seamless inclusion of external health records into patient EHRs, contingent on patient consent. By comparing clinicians’ data utilization patterns before and after these enhancements, the researchers seek to illuminate how medical decisions evolve in response to improved data availability. This longitudinal comparative approach is vital to understanding the concrete benefits and challenges of interoperable health records at scale.
One striking finding reported by Dr. Apathy is the low uptake of outside data in clinical practice, even when available. In outpatient settings, studies indicate that less than 30% of physicians routinely review external records when making treatment decisions, with some clinicians’ usage as low as 5-10%. Multiple factors contribute to this hesitancy. The relevance of the external data to the patient’s immediate health concern remains a primary concern, alongside the added cognitive and time burden required to review disparate records. These insights underscore that mere availability of data is insufficient; clinicians need intuitive tools that signal the significance of outside data relative to specific clinical contexts.
Addressing these challenges head-on, the UMD-UCSF collaboration plans to harness the power of machine learning and artificial intelligence to develop advanced patient “phenotypes.” These phenotypes will be detailed profiles capturing observable traits and recent clinical diagnoses — for example, a “male over 50 with newly diagnosed hypertension who hasn’t had a visit in six months.” By leveraging such nuanced patient categorization, the research aims to create algorithms capable of flagging the most relevant outside records for each patient, thereby streamlining the clinician’s workflow and enhancing the likelihood that pertinent data will inform clinical decisions.
Beyond optimizing decision-making, this research holds far-reaching implications for healthcare costs and patient satisfaction. Seamless transfer of comprehensive health data can dramatically reduce redundant tests, minimize delays in care, and eliminate frustrating administrative hurdles that currently plague patients and providers alike. Dr. Apathy emphasizes the potential economic benefits, noting that improved data interoperability could lead to significant cost savings for health systems while simultaneously enhancing care quality and efficiency.
Moreover, the open-source tools and frameworks emerging from this project promise to democratize access to cutting-edge health informatics technologies. By making these resources freely available to the medical and research communities, the investigators aim to catalyze widespread adoption and iterative innovation, fostering a healthcare ecosystem that prioritizes patient-centered, data-driven care.
However, the path forward is not devoid of challenges. Ensuring patient privacy and data security remains paramount, especially as health information crosses institutional and sometimes geographic boundaries. The researchers are committed to navigating these ethical and regulatory landscapes carefully, employing robust consent mechanisms and adhering to stringent data governance standards. In doing so, they aim to balance the promise of interoperability with the imperative to protect individual rights.
The study’s mixed-methods approach, combining quantitative analyses of clinical decision patterns with qualitative insights from provider interviews, is designed to capture the multifaceted nature of data utilization in healthcare. Understanding not only what decisions are made but also why clinicians choose to engage or disregard outside data will inform the development of user-centered tools and policies tailored to real-world clinical environments.
As the project unfolds over the next four years, it will generate valuable evidence about how integrated health data influences provider behavior and patient health outcomes. This evidence is essential for informing future investments in health IT infrastructure and shaping policy debates around data sharing standards and incentives. The collaborative model between UMD and UCSF also sets a precedent for multi-institutional research necessary to tackle complex, systemic challenges in modern healthcare.
Ultimately, this endeavor represents a critical step toward realizing the longstanding vision of a truly integrated digital health ecosystem. By illuminating how accessed external medical records shape clinical judgments and by designing AI-driven tools to facilitate data relevance and accessibility, the research promises to transform the patient journey through the often fragmented healthcare landscape. Dr. Apathy succinctly captures this mission: “When health data travels seamlessly between institutions, there is immense promise to drive down healthcare costs, reduce redundant procedures, and improve patient health and satisfaction.” The coming years may indeed herald a new era where medical data belongs to patients and providers alike, unbounded by institutional walls, and fully leveraged to optimize care.
This NIH-supported research, grant 1R01LM014770-01, stands at the forefront of health data interoperability research, combining health policy expertise, informatics innovation, and clinical collaboration. Its findings will not only deepen our understanding of contemporary challenges in EHR utilization but will also furnish actionable solutions to enhance the efficiency and quality of medical care across diverse clinical settings.
Subject of Research:
Impact of integrated external electronic health records on clinical decision-making and patient outcomes.
Article Title:
Bridging the Healthcare Data Divide: How Integrated Outside Records Could Revolutionize Clinical Care
News Publication Date:
[Not specified in provided content]
Web References:
https://sph.umd.edu/people/nate-apathy
https://doi.org/10.1093/jamia/ocaa226
References:
NIH Grant 1R01LM014770-01
Image Credits:
UMD
Keywords:
Health care delivery, Personalized medicine
Tags: addressing barriers in digital health recordschallenges in electronic health record systemscollaboration between healthcare institutionscontinuity of care in healthcare transitionsenhancing clinical decision-making with outside datafunding for health technology researchimpact of health data sharing on patient outcomesimproving patient experience with EHRNIH grant for electronic health records interoperabilityovercoming siloed medical recordsUMD research on health informaticsUniversity of Maryland health policy research
