Roadmap to a more useful and usable electronic health record

Making the EHR Work for You-Modifications of an Electronic Health Record System to Improve Tracking and Management of Patients Receiving Outpatient Parenteral Antibiotic Therapy

Background

Managing the complex needs of outpatient parenteral antibiotic therapy (OPAT) patients is challenging and time-consuming. We describe development of multimodal interventions to facilitate patient management within an Epic® (Epic Systems Corporation)-based electronic health record (EHR) platform.

Methods

During 2016-2018, a multidisciplinary team created several modifications in our local EHR to improve gaps in OPAT care, including shared note templates, shared patient lists, automatically triggered notifications, and comprehensive order sets. A SmartForm was created, allowing collection of discrete, self-contained extractable data about each OPAT episode. We reviewed OPAT episodes from January 2019 through December 2022.

Results

The multimodal EHR interventions culminated in the creation of a patient report, the "OPAT Monitoring View" collating OPAT-relevant data from multiple sections of the chart onto 1 screen display. This view is accessible both within the patient chart and from multiple list-based, in-basket, and snapshot-anchored preview functions in the EHR. Implementation of the EHR bundle facilitated management of 3402 OPAT episodes from 2019 to 2022 (850 episodes/year), about 50% higher than anticipated based on 540 OPAT courses in 2016. The OPAT EHR bundle allowed efficient (<3 hours) multidisciplinary rounds for management of 130-145 patients each week, streamlining of care transitions, and increasing staff satisfaction.

Conclusions

Bundled multimodal modifications to the local EHR increased patient care efficiency and staff satisfaction and facilitated data collection to support a large OPAT program. These modifications apply commonly available EHR functionalities to OPAT care and could be adapted to other settings with different EHR platforms.

Real-World Data for Interdisciplinary Health Care Research: A Case Example

Real-word data (RWD) refer to data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources, including electronic health records, medical claims data, and patient-generated data. Data sets that combine personal health data stored in different sources can provide a more complete picture of an individual's health and can be used to improve population health through research and practice. The 2-tiered aim of this article is to provide a brief introduction to using RWD in health care research and to present a case study that demonstrates data curation and data merge from different sources while highlighting the benefits and limitations of using RWD. The current digital health ecosystem and value-based care approach highlight the need to use RWD to catalyze the advancement of health care research and practice. This is an excellent field that nurse researchers can lead, as they have an innate understanding of such data and data sources.

Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record

The electronic health record (EHR) represents a rich source of patient information, increasingly being leveraged for cardiovascular research. Although its primary use remains the seamless delivery of health care, the various longitudinally aggregated structured and unstructured data elements for each patient within the EHR can define the computational phenotypes of disease and care signatures and their association with outcomes. Although structured data elements, such as demographic characteristics, laboratory measurements, problem lists, and medications, are easily extracted, unstructured data are underused. The latter include free text in clinical narratives, documentation of procedures, and reports of imaging and pathology. Rapid scaling up of data storage and rapid innovation in natural language processing and computer vision can power insights from unstructured data streams. However, despite an array of opportunities for research using the EHR, specific expertise is necessary to adequately address confidentiality, accuracy, completeness, and heterogeneity challenges in EHR-based research. These often require methodological innovation and best practices to design and conduct successful research studies. Our review discusses these challenges and their proposed solutions. In addition, we highlight the ongoing innovations in federated learning in the EHR through a greater focus on common data models and discuss ongoing work that defines such an approach to large-scale, multicenter, federated studies. Such parallel improvements in technology and research methods enable innovative care and optimization of patient outcomes.

Leveraging the Electronic Health Record to Implement Emergency Department Delirium Screening

OBJECTIVE

The aim of this study is to understand how emergency departments (EDs) use health information technology (HIT), and specifically the electronic health record (EHR), to support implementation of delirium screening.

METHODS

We conducted semi-structured interviews with 23 ED clinician-administrators, representing 20 EDs, about how they used HIT resources to implement delirium screening. Interviews focused on challenges participants experienced when implementing ED delirium screening and EHR-based strategies they used to overcome them. We coded interview transcripts using dimensions from the Singh and Sittig sociotechnical model, which addresses use of HIT in complex adaptive health care systems. Subsequently, we analyzed data for common themes across dimensions of the sociotechnical model.

RESULTS

Three themes emerged about how the EHR could be used to address challenges in implementation of delirium screening: (1) staff adherence to screening, (2) communication among ED team members about a positive screen, and (3) linking positive screening to delirium management. Participants described several HIT-based strategies including visual nudges, icons, hard stop alerts, order sets, and automated communications that facilitated implementation of delirium screening. An additional theme emerged about challenges related to the availability of HIT resources.

CONCLUSION

Our findings provide practical HIT-based strategies for health care institutions planning to adopt geriatric screenings. Building delirium screening tools and reminders to perform screening into the EHR may prompt adherence to screening. Automating related workflows, team communication, and management of patients who screen positive for delirium may help save staff members' time. Staff education, engagement, and access to HIT resources may support successful screening implementation.

Paving the way for increased e-health record use: elaborating intentions of Gen-Z

This paper presents the determinants of personal e-health records adoption by the Gen-Z population and reveals barriers to use. Gen-Z members are one of the most prominent users of digital health services that have an influence on older generations' technology adoption but have often been overlooked in scholarly research. A survey of 1,000 Gen-Z university students based on modified UTAUT was used to address this research gap. The analysis revealed the vital role of social influence in paving the way for higher adoption among Gen-Z. Moreover, significant influences of performance expectancy, facilitating conditions, and e-health literacy on behavioural intentions were detected. Effort expectancy was found to be insignificant in impacting Gen-Z's intentions to adopt electronic health record systems. Moreover, privacy concerns acted as a barrier to adoption, yet the offsetting effect of users' trust in health systems was shown to be instrumental in overcoming such privacy-related barriers.