Student name

NURS-FPX 8022

Capella University

Professor Name

Submission Date

Using Data to Make Evidence-Based Recommendations

The introduction of technology in the healthcare environment has become a pillar of enhancing the patient safety, clinical outcomes, and organizational performance. The Massachusetts general hospital (MGH), which is a prominent academic medical center based in Boston, uses Epic electronic health records (EHR) to improve clinical documentation, facilitate workflow, and aid evidence-based decision-making. The article discusses the advantages and limitations of Epic EHR in the acute care setting and evaluates the performance of MGH based on the Leapfrog and Medicare Compare data and suggests an evidence-based approach to informatics to increase organizational ratings and patient outcomes. The effective use of EHRs may lead to the improved patient safety, more individual approach to the treatment, and further improvement of clinical and administrative procedures.

Benefits of the Chosen Technology

As one of the major academic medical Centres, the MGH has successfully deployed the EHR technology to enhance patient safety and quality of services (Massachusetts General Hospital, n.d.). Epic EHR at MGH has helped in the minimization of medication errors by providing built-in barcode medication administration (BCMA), automated allergy checks, and in-time drug interaction warning. The system will also remain in clinical care decision-making tools that will standardize the care pathway and minimize variability in the treatment (Syrowatka et al., 2023). There is also an improvement in administrative efficiency as the electronic ordering system, discharge summaries, and centralized scheduling played a role in eliminating delays and paperwork overheads (Harbi et al., 2024). MGH also uses the data in the EHR to monitor trends of hospital-acquired infections, performance benchmarking, and predictive risk model creation based on which quality improvement efforts are directed. The MyChart portal allows patients to view laboratory results, contact specialists and schedule appointments, contributes to patient engagement and shared decision-making (Vanderhout et al., 2025). The EHR system is also useful in integrating multidisciplinary care teams through the provision of a single and real-time source of patient information within the department (Calduch et al., 2021). However, such issues as provider alert fatigue, as well as interoperability with external systems and high maintenance costs, are still a concern. As demonstrated by the strategy of MGH, it can be concluded that EHR technology, when wielded in an appropriate way, is a potent facilitator of a safer, more coordinated, and patient-centered healthcare provision.

Obstacles in Utilizing the Chosen Technology

The change in patient care because of the implementation of Epic EHR in MGH is undeniable, and it has also created barriers that affect workflows in everyday life. Provider burnout is one of the major issues since clinicians tend to allocate a lot of time to documentation needs, which may exclude actual interaction with patients. Actually, Arndt et al. (2022) have pointed out that the time spent by physicians working with EHR systems on documentation can take almost two hours per hour of patient care. The clinical decision-making interruptions in the workflow that may also happen include the failure of the templates to be specific to particular specialties and system alerts disrupting the clinical decision-making, leading to inefficiencies during the busy shifts (Shan et al., 2023). The challenges demonstrate the discrepancy between the potentials of technology and the practical application. Thus, whereas Epic helps to make the delivery of care safer, there is a risk that it may create more tension among the providers who do not optimize their workflows to decrease administrative work.

The other major challenge is associated with the expensive nature of Epic EHR and maintenance that imposes financial burden on medical organizations. One large-scale Epic implementation can cost hundreds of millions of dollars and it needs round-the-clock IT services to make updates and solve problems (Chishtie et al., 2023). Also, data interoperability is a continuous obstacle since the transfer of patient data to non-Epic systems or external providers can be restricted, which slows down the processes of care coordination and population health (Chishtie et al., 2023). Walker et al. (2023) demonstrated that merely 46 percent of hospitals have the capacity to share patient information outside the system routinely, which is contrary to national interoperability programs. The challenges indicate that organizations such as MGH with well-established organizations are required to balance financial, technical, and operational realities in order to make the most of the EHR technology.

Workflow for the Chosen Technology

In MGH, Epic EHR system is incorporated in the whole patient experience, starting with admission and ending with discharge. At the admission, demographic and clinical information is entered into Epic, which automatically initiates risk screens on falls, infections, medication safety, and others (Chishtie et al., 2023). The screenings alert providers and nurses about the risks at an early stage in the treatment of the patient in the hospital. Providers then make electronic orders, and the pharmacy staff will confirm all orders of medications inside Epic so that they are safe and appropriate. Nurses utilize BCMA connected to Epic to scan the identification band of the patient and medication barcode during the inpatient stay and thus minimize medication errors (Syrowatka et al., 2023). The clinical encounter and progress notes are recorded in Epic, with a real-time update of the electronic record of the patient, which guarantees continuation of care across the multidisciplinary team. Lastly, upon discharge, Epic automatically creates discharge summaries and patient instructions that are disseminated to the clinical team, as well as the patient via the MyChart portal, to improve patient interactions and communication following hospitalization (Vanderhout et al., 2025).

Evaluation of Performance Data

One of the programs that the MGH is involved in is the Leapfrog Hospital Safety Grade program that assesses the performance of hospitals in terms of patient safety across multiple fields. As of the latest statistics, MGH has a total grade of B at the moment. Although there are places which the hospital does well in, the safety performance trends differ in various domains. Medication safety was rated above average in the three patient safety measures chosen, as the hospital successfully used Epic BCMA and decision support tools (LeapFrog, n.d). The level of infection prevention was rated as average, which means that it is possible to enhance the prevention of hospital-related infections, including central line-associated bloodstream infections and surgical site infections (LeapFrog, n.d). Nevertheless, patient falls and injury prevention were rated below average, which indicates that although EHR-based fall-risk screenings are implemented, additional focus on reducing the damage caused by falls is required (LeapFrog, n.d). The findings also point to the strong and weak sides of the current technology-based safety practices of MGH.

In Medicare Care Compare, the type of provider of acute care hospitals was analysed to compare the performance of MGH. The patient safety score of MGH is 3 out of 5 stars, which is average as compared to other similar institutions. Compared to peer educational medical institutions, such as Johns Hopkins Hospital, with the 4-star patient safety rating, MGH lags slightly in the overall safety performance. Other large tertiary centers, including the Cleveland Clinic, also have a score of 3 stars, which puts MGH on a level with some of its colleagues but still below the national leaders (Medicare Compare, 2024). The comparison shows that the rates of infection prevention and fall reduction are average in MGH, yet specific changes should be implemented to increase the safety rates and align the organization with others with the highest scores.

Evidence-Based Recommendation

By introducing a series of evidence-based informatics interventions in Epic, the MGH can enhance the performance of patient safety and uplift the Leapfrog grade of B and Medicare Care Compare rating of 3 stars to high ratings. The initial project, called Med-Safe+, would strengthen the closed-loop medication safety through tightening computerized provider order entry (CPOE) and BCMA compliance (Shermock et al., 2023). Epic can be set to demand eMAR documentation, demand bedside re-scans, and create unit-level level exception dashboards. The practice is justified by evidence that CPOE has the potential to decrease serious medication errors by more than 50 percent and reduce the number of reported errors by 48 percent and the number of errors in the emergency environment by up to 65 percent (Owens et al., 2020). At MGH, an increase in BCMA “scan-match compliance to at least 95% and a 40% reduction in serious medication errors would directly enhance Leapfrog CPOE/BCMA process measures and the PSI-90 harm composite at Medicare.

The second intervention is named Sepsis Right-Time, it is aimed at the implementation of the Epic integrated sepsis early-warning pathway, with tiered sepsis alerts, one- click sepsis order sets, and time-stamped sepsis bundle checklists. Charge nurses would be provided with real-time compliance monitoring to take necessary actions on time. As Kim et al (2024) showed, electronic sepsis warnings enhance bundle compliance, decreased length of stay and mortality rate when responded to in a timely manner. The 80% bundle completion rate in three hours, 15% sepsis mortality and 0.5-day reduction in length of stay are direct ways to enhance the impact of Leapfrog infection-prevention outcomes and Medicare PSI-90 scores in MGH. Likewise, Clean-Hand, Clean-Lines would establish electronic hand-hygiene monitoring systems (EHHMS) in the high-risk units that would show compliance dashboards in Epic SlicerDicer and Clarity modules and connect it with automated infection surveillance of the problems (Chishtie et al., 2023). In order to maintain the work, a Safety Command Center would be created that would include unit-level dashboards updated on a daily basis and mapped to the Leapfrog domains and Medicare Care Compare indicators. The scorecards would monitor real-time performance, peer benchmarks and nudges related to the next best action and would hold the accountable with weekly huddles, monthly service-line reviews, and quarterly executive reviews.

Redesigned Workflow

As Epic integration introduces predictive analytics into the workflow of MGH, the workflow would be shifted towards a more of a risk-preventive model as opposed to the reactive one. The patient data will flow into forecast risk programs upon admission followed by a calculation of personalized risks of developing hospital-acquired infections, sepsis, and fall risks. In high-risk patients, Epic will automatically issue real-time alerts on care plans to the nursing staff, which will trigger measures to address the issue, including increased monitoring, mobility aid, prophylaxis (Chishtie et al., 2023). Pharmacy warning systems will also be optimised to eliminate alert fatigue, only high-severity interactions will be shown with low-value warnings being suppressed. The outcome is that the providers will be kept to clinically significant risks without being deluded with too many notifications. Moreover, unit managers will have a dashboard that will be updated on a daily basis and will be able to monitor the trends of infections, falls, and medication errors in real-time (Harbi et al., 2024). The dashboards will be compared to the Leapfrog metrics, which will give a clear actionable information to frontline teams as well as the leadership. Lastly, the EHR will incorporate predictive scores, treatment interventions and outcomes into a structured discharge summary at the discharge phase to facilitate safe care transfers and Medicare Compare quality measures.

Impact on Leapfrog and Medicare Compare Scores

The re-designed Epic workflow contributes directly to the increase of both Leapfrog Hospital Safety Grade and Medicare Care Compare star rating. Daily dashboards and predictive infection surveillance focuses on the level of hospital-acquired infection rates, which determines the Leapfrog infection prevention strategy and PSI-90 composite offered by Medicare (LeapFrog, n.d). Streamlined pharmacy alerts and optimized BCMA minimize adverse drug events, which enhance the medication safety domain at Leapfrog and reduce preventable harm as indicated by Medicare scores. Nursing interventions and predictive fall-risk alerts can solve below-average Leapfrog patient falls and injury prevention rating in MGH to mitigate the number of fall-related harm incidents. The predictive analytics and dashboard-based accountability that MGH will implement will enable the hospital to decrease medication errors by 4060 percent, hospital-acquired infections by 1520 percent, and falls causing harm by 25, which is in line with evidence-based targets (LeapFrog, n.d). The cuts place MGH to raise the Leapfrog grade of B to A and Medicare Care Compare patient safety rating 3 to 4 stars, which puts it incomparable to peer leaders like Johns Hopkins Hospital.

Conclusion

The Epic EHR has significant patient safety and care coordination benefits to the MGH organization. Nevertheless, barriers that inhibit the full potential include provider workload and inefficiency in workflow. Using predictive analytics in Epic EHR, MGH is able to prevent falls and infections prior to them happening, which will have a direct impact on Leapfrog and Medicare Compare scores. The redesign of the workflow based on the use of technology will not only reinforce the safety outcomes but also the satisfaction of the provider and organizational excellence.

References for Nurs fpx 8022 Assessment 1

Arndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W.-J., Sinsky, C. A., & Gilchrist, V. J. (2022). Tethered to the EHR: Primary care physician workload assessment using ehr event log data and time-motion observations. The Annals of Family Medicine, 15(5), 419–426. https://doi.org/10.1370/afm.2121

Budd, J. (2023). Burnout related to electronic health record use in primary care. Journal of Primary Care & Community Health, 14(4), 3–7. https://doi.org/10.1177/21501319231166921

Calduch, E., Muscat, N., Krishnamurthy, R. S., & Ortiz, D. (2021). Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews. International Journal of Medical Informatics, 152(1), e104507. https://doi.org/10.1016/j.ijmedinf.2021.104507

Chishtie, J., Sapiro, N., Wiebe, N., Rabatach, L., Lorenzetti, D., Leung, A. A., Rabi, D., Quan, H., & Eastwood, C. A. (2023). Use of Epic electronic health record system for health care research: Scoping review. Journal of Medical Internet Research, 25(1), 1–29. https://doi.org/10.2196/51003

Harbi, S. A., Aljohani, B., Elmasry, L., Baldovino, F. L., Raviz, K. B., Altowairqi, L., & Alshlowi, S. (2024). Streamlining patient flow and enhancing operational efficiency through case management implementation. British Medical Journal Open Quality, 13(1), 1–18. https://doi.org/10.1136/bmjoq-2023-002484

Kim, H.-J., Ko, R.-E., Lim, S. Y., Park, S., Suh, G. Y., & Lee, Y. J. (2024). Sepsis alert systems, mortality, and adherence in emergency departments. JAMA Network Open, 7(7), e2422823. https://doi.org/10.1001/jamanetworkopen.2024.22823

LeapFrog. (n.d.). Massachusetts General Hospital – MA – Hospital Safety Grade. Www.hospitalsafetygrade.org. https://www.hospitalsafetygrade.org/h/massachusetts-general-hospital

Massacheusetts General Hospital. (n.d.). Electronic health records can be a valuable predictor of those likeliest to die from COVID-19. Massachusetts General Hospital. https://www.massgeneral.org/news/press-release/electronic-health-records-can-be-a-valuable-predictor-of-those-likeliest-to-die-from-covid19

Medicare Compare. (2024). Find healthcare providers: Compare care near you | Medicare. Medicare.gov. https://www.medicare.gov/care-compare/details/hospital/220071?city=Boston&state=MA&zipcode