Have Electronic Health Records Improved the Quality of Patient Care?

Nursing education and training on electronic health record systems: An integrative review

AIM

This integrative review aimed to synthesize evidence pertaining to interventions that have been used to facilitate nurse education and training on electronic health records.

BACKGROUND

Inadequate education and training can threaten the adoption of electronic health records and negatively impact the quality of nursing documentation. A review of the literature may help facilitate the development of evidence-based interventions for nursing education and training on electronic health records.

DESIGN

An integrative review framework was used to address the research question: What is the available evidence to inform best practices for nursing education and training on electronic health records?

METHODS

A systematic search was conducted in five databases: the Cumulative Index to Nursing and Allied Health Literature, Scopus, PubMed, CBCA Education, and ProQuest Education Database. Included articles were peer-reviewed studies, published in English, in which nurses participated in an electronic health record education or training intervention.

RESULTS

Fifteen articles, from a search conducted between 2010 and 2020, were reviewed. Findings identified a shift from classroom learning towards blended approaches for nursing education and training on electronic health records, incorporating methods such as e-learning, peer coaching, and simulation. Ongoing staff engagement is needed to develop interventions that allow nurses to integrate electronic health records into their daily workflows. Higher quality studies and more meaningful assessment of learning outcomes are needed to identify the most effective interventions to incorporate in blended learning strategies.

CONCLUSIONS

Consensus in the reviewed literature indicated that electronic health record education and training for nurses should be multipronged and targeted to nurses' clinical workflows. Key findings of this review identified a shift from classroom-based learning towards blended approaches for electronic health record education and training. Blended approaches often incorporated non-traditional methods that could support interactive and workflow-based content. These included e-learning, nurse superusers or peer coaches, and simulation training. The findings of this review also highlighted the need for early and ongoing involvement of frontline nurses during electronic health record education and implementation. However, more rigorous studies that assess both patient and organizational outcomes are needed to identify the most effective "cocktail" of blended learning strategies.

A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients

OBJECTIVE

Phenotyping patients using electronic health record (EHR) data conventionally requires labeled cases and controls. Assigning labels requires manual medical chart review and therefore is labor intensive. For some phenotypes, identifying gold-standard controls is prohibitive. We developed an accurate EHR phenotyping approach that does not require labeled controls.

MATERIALS AND METHODS

Our framework relies on a random subset of cases, which can be specified using an anchor variable that has excellent positive predictive value and sensitivity independent of predictors. We proposed a maximum likelihood approach that efficiently leverages data from the specified cases and unlabeled patients to develop logistic regression phenotyping models, and compare model performance with existing algorithms.

RESULTS

Our method outperformed the existing algorithms on predictive accuracy in Monte Carlo simulation studies, application to identify hypertension patients with hypokalemia requiring oral supplementation using a simulated anchor, and application to identify primary aldosteronism patients using real-world cases and anchor variables. Our method additionally generated consistent estimates of 2 important parameters, phenotype prevalence and the proportion of true cases that are labeled.

DISCUSSION

Upon identification of an anchor variable that is scalable and transferable to different practices, our approach should facilitate development of scalable, transferable, and practice-specific phenotyping models.

CONCLUSIONS

Our proposed approach enables accurate semiautomated EHR phenotyping with minimal manual labeling and therefore should greatly facilitate EHR clinical decision support and research.

Elements of Trust in Digital Health Systems: Scoping Review

BACKGROUND

Information and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored.

OBJECTIVE

The objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health.

METHODS

We performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented.

RESULTS

Overall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third-health administrators-was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health.

CONCLUSIONS

Trust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

Framework to Enhance Nurses' Use of EMR

The ability of nurses to adopt and successfully use EMR is expected to have a significant impact on achieving benefits such as reduction in healthcare costs and improvement in healthcare quality. A review of the current research literature reveals issues and concerns relating to the adoption and use of EMR by nurses in hospital environments. This article presents a literature review of such issues and concerns, and suggests a framework for enhancing the adoption and use of EMR by nurses and hospitals.

Managing Psychiatrist-Patient Relationships in the Digital Age: a Summary Review of the Impact of Technology-enabled Care on Clinical Processes and Rapport

PURPOSE OF REVIEW

Participatory medicine and the availability of commercial technologies have given patients more options to view and track their health information and to communicate with their providers. This shift in the clinical process may be of particular importance in mental healthcare where rapport plays a significant role in the therapeutic process.

RECENT FINDINGS

In this review, we examined literature related to the impact of technology on the clinical workflow and patient-provider rapport in the mental health field between January 2014 and June 2017. Thirty three relevant articles, of 226 identified articles, were summarized. The use of technology clinically has evolved from making care more accessible and efficient to leveraging technology to improve care, communication, and patient-provider rapport. Evidence exists demonstrating that information and communication technologies may improve care by better connecting patients and providers and by improving patient-provider rapport, although further research is needed.