Futuristic medical interface visualizing data-driven clinical decisions.

Decoding Healthcare's Digital Frontier: Navigating EHR Challenges for Better Patient Outcomes

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Samir D’Costa in Health & Wellness October 2026 • 4 min read.

"How Veterans Affairs' Informatics Strategies Pave the Way for Clinical Decision Support."


In today’s rapidly evolving healthcare landscape, the electronic health record (EHR) stands as a cornerstone of modern medical practice. The U.S. Veterans Administration (VA) has long been at the forefront of this digital transformation, developing a robust infrastructure to support its EHR system. As healthcare providers increasingly rely on digital tools, the ability to effectively utilize and integrate EHR data becomes paramount.

Clinical Decision Support (CDS) systems have emerged as a vital component of EHRs, offering the potential to improve patient outcomes by providing clinicians with timely, patient-specific recommendations. Web-based technologies have further enhanced the accessibility and utility of CDS, allowing for seamless integration into clinical workflows. However, building and implementing these systems within complex healthcare environments is not without its challenges.

This article delves into the informatics challenges and design issues encountered during the development of three web-based CDS systems within the VA EHR environment. Drawing upon the VA's experience, this article will explore the hurdles, solutions, and key insights gained, providing a valuable roadmap for healthcare professionals and IT experts seeking to enhance their own clinical decision support capabilities.

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EHR Data and Decision Support

The CDC's National Electronic Health Records Survey (NEHRS) collects data directly from U.S. office-based physicians and their practices. NEHRS provides information about electronic health record systems and health information exchange. Research reviewed in 2022 examined EHR-integrated or interoperable clinician-facing clinical decision support (CDS) designed to improve care for populations facing disparities, while a March 2026 systematic review updated earlier evidence on EHR-linked computerized decision support systems intended to support continuous, patient-tailored use of evidence in clinical decision-making.

The VA's Informatics Journey: From Data to Decisions

Futuristic medical interface visualizing data-driven clinical decisions.

The VA's journey in leveraging EHR data for clinical decision support is marked by both innovation and practical problem-solving. The VA’s system needed to ensure data security and patient privacy while supporting real-time data access for clinical decision support.

Over several years, the VA has implemented three web-based CDS systems to extract patient data from the VA EHR, each tailored to address specific clinical needs. These projects each tackled a different clinical area:

  • VACS Index Calculator: Estimates prognosis for HIV+ patients, aiding in long-term care planning.
  • Neuropath/CDS: Assists in managing patients with neuropathic pain, optimizing treatment strategies.
  • TRIM (Tool to Reduce Inappropriate Medications): Identifies potentially inappropriate medications in older adults, promoting safer prescribing practices.
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Integrating Clinical Decision Support

Recent work describes CDS tools integrated into EHRs as a way to help providers adopt evidence-based practices. That work also identifies technical challenges that must be addressed for integration to function effectively. A 2024 review reports that CDS integration into electronic medical record systems has become common, while noting that barriers still prevent consistent and effective use for patients and providers.

The Pitfalls of Digital CDS

Clinical decision support systems can provide timely information at the point of care to assist clinical decision-making. However, contemporary CDS increasingly relies on EHR data and complex algorithms, creating a need to balance its promise with potential pitfalls. An analysis published in Nature's npj Digital Medicine identifies data entry and documentation, interoperability, alerts, and clinical decision support among the key challenges of electronic health records.

EHRs, EMRs, and Clinical Guidance

The MSD Manual reports that EHRs make large amounts of patient data and clinical information available for clinical decision support and give patients direct access to much of the same information. EHR-based decision support can include evidence-based clinical practice guidelines and best-practice protocols delivered at the point of care. A 2026 comparison guide distinguishes EHRs from EMRs while examining how each system supports providers in managing patient records.

Each system was designed to provide patient-specific CDS, addressing the need for tailored recommendations that consider individual patient characteristics and medical history. Let's explore the informatics methods and specific challenges that each CDS presents, including their approach to data extraction and integration.

Building a Healthier Future Through Informatics

By openly sharing their experiences, the VA provides a valuable service to the broader healthcare community. As more institutions embrace web-based CDS systems, the lessons learned by the VA can help guide the development of effective, patient-centered solutions. Tackling data access challenges, data availability, and the nuances of patient information paves the way for more powerful and impactful clinical decision support systems that enhance patient care and improve healthcare outcomes for all.

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Evidence-Based EHR Support

Electronic health records could improve clinical care through clinical decision support and electronic guideline-based reminders and alerts. A study published in JAMA Internal Medicine tested this hypothesis using nationally representative data from U.S. outpatient physicians. Its focus illustrates why the value of EHRs depends not only on storing information, but also on translating that information into usable decision support.

Implementation Beyond Technology

A 2026 review describes EHRs as core eHealth tools that can enhance care quality, provide access to medical data, and improve coordination among healthcare providers. The same review emphasizes that successful implementation requires understanding both challenges and facilitators to inform policymaking and management. A 2023 discussion similarly presents CDS tools as promising ways to enhance the efficiency and effectiveness of medicine amid digital transformation and advances in health information technology.

People and Workflow Matter

One study found that EHR-based clinical decision support was reinforced by changes in clinic rooming procedures, changes in nurse roles, and incentives for physicians and clinic staff. These implementation elements were lacking in previous failed attempts to introduce EHR-based clinical decision support. The source therefore links real-world impact not only to the technology itself, but also to the clinical workflows, responsibilities, and incentives surrounding its use.

What alert overrides reveal-and do not reveal

The reports point to alert timing, severity distinctions, and user interaction as factors that may matter more than the EHR conversion itself. The alert-burden comparison does not isolate which of those factors drove the increase.[1]

How conversion and interoperability compare

A separate report linked automatically filled patient details from interoperable EHRs with more correct patient identification entries than manual entry across participating hospitals. This points to a different side of EHR design: reliable data exchange can support accurate identification, while alert burden may rise during a system change.[1] [2]

An observational analysis of EHR implementation could not fully assess inpatient outcomes by implementation context, hospital, or EHR characteristics. Its findings therefore do not establish how outcomes vary across those settings.[3]

That analysis measured outcomes available in claims, such as mortality and readmissions, but not intermediate process measures such as medication errors. Its outcome measures may therefore miss disruptions that appear in those processes.[3]

What remains uncertain about EHR transitions

  • How would including process measures such as medication errors change the picture of patient outcomes during implementation?[3]
  • Would outcome patterns differ across implementation settings or EHR characteristics that the analysis could not fully separate?[3]

Sources

  1. Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record. (pubmed.ncbi.nlm.nih.gov)
  2. The Impact of Electronic Health Record Interoperability on Safety and Quality of Care in High-Income Countries: Systematic Review (pmc.ncbi.nlm.nih.gov)
  3. Adverse inpatient outcomes during the transition to a new electronic health record system: observational study (pmc.ncbi.nlm.nih.gov)

About this Article -

Written with AI assistance from published research, and reviewed by the Mystum team. See our About page for more information.

Everything You Need To Know

1

What is an Electronic Health Record and why is it important?

An Electronic Health Record (EHR) is a digital version of a patient's chart. EHRs are significant because they improve the quality of patient care by making patient information readily available to healthcare providers. EHRs also allow for better coordination of care and can reduce medical errors.

2

What are Clinical Decision Support systems and why are they important in healthcare?

Clinical Decision Support (CDS) systems are computer programs designed to assist clinicians in making informed decisions about patient care. They are important because they provide clinicians with timely, patient-specific recommendations, potentially improving patient outcomes. Web-based technologies have made CDS systems more accessible, allowing for seamless integration into clinical workflows.

3

What is the VACS Index Calculator and how does it improve patient care?

The VACS Index Calculator is a web-based CDS system used to estimate the prognosis for HIV+ patients. It is important because it aids in long-term care planning by providing clinicians with data-driven insights into the likely course of the disease. This system assists in delivering tailored recommendations that consider individual patient characteristics and medical history.

4

What is Neuropath/CDS and what role does it play in healthcare?

Neuropath/CDS is a web-based CDS system designed to assist in managing patients with neuropathic pain. This system helps optimize treatment strategies by providing clinicians with evidence-based recommendations tailored to the patient's specific condition. By using this system, healthcare providers can offer more effective and personalized care, leading to better outcomes and improved quality of life for patients suffering from neuropathic pain.

5

What is TRIM and how does it help improve safety in prescribing medication?

TRIM (Tool to Reduce Inappropriate Medications) is a web-based CDS system created to identify potentially inappropriate medications in older adults. TRIM promotes safer prescribing practices by alerting clinicians to medications that may pose risks for elderly patients, helping to minimize adverse drug events and improve overall patient safety. This tool ensures that older adults receive the most appropriate and beneficial medications while reducing the potential for harm.

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