Improving the effectiveness of drug safety alerts to increase adherence to the guideline for gastrointestinal prophylaxis

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

BACKGROUND

Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.

OBJECTIVE

The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.

METHODS

We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.

RESULTS

We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.

CONCLUSIONS

The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Trends in guideline implementation: an updated scoping review

Background

Guidelines aim to support evidence-informed practice but are inconsistently used without implementation strategies. Our prior scoping review revealed that guideline implementation interventions were not selected and tailored based on processes known to enhance guideline uptake and impact. The purpose of this study was to update the prior scoping review.

Methods

We searched MEDLINE, EMBASE, AMED, CINAHL, Scopus, and the Cochrane Database of Systematic Reviews for studies published from 2014 to January 2021 that evaluated guideline implementation interventions. We screened studies in triplicate and extracted data in duplicate. We reported study and intervention characteristics and studies that achieved impact with summary statistics.

Results

We included 118 studies that implemented guidelines on 16 clinical topics. With regard to implementation planning, 21% of studies referred to theories or frameworks, 50% pre-identified implementation barriers, and 36% engaged stakeholders in selecting or tailoring interventions. Studies that employed frameworks (n=25) most often used the theoretical domains framework (28%) or social cognitive theory (28%). Those that pre-identified barriers (n=59) most often consulted literature (60%). Those that engaged stakeholders (n=42) most often consulted healthcare professionals (79%). Common interventions included educating professionals about guidelines (44%) and information systems/technology (41%). Most studies employed multi-faceted interventions (75%). A total of 97 (82%) studies achieved impact (improvements in one or more reported outcomes) including 10 (40% of 25) studies that employed frameworks, 28 (47.45% of 59) studies that pre-identified barriers, 22 (52.38% of 42) studies that engaged stakeholders, and 21 (70% of 30) studies that employed single interventions.

Conclusions

Compared to our prior review, this review found that more studies used processes to select and tailor interventions, and a wider array of types of interventions across the Mazza taxonomy. Given that most studies achieved impact, this might reinforce the need for implementation planning. However, even studies that did not plan implementation achieved impact. Similarly, even single interventions achieved impact. Thus, a future systematic review based on this data is warranted to establish if the use of frameworks, barrier identification, stakeholder engagement, and multi-faceted interventions are associated with impact.

Trial registration

The protocol was registered with Open Science Framework (https://osf.io/4nxpr) and published in JBI Evidence Synthesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-022-01223-6.

Impact of electronic health records on predefined safety outcomes in patients admitted to hospital: a scoping review

OBJECTIVES

Review available evidence for impact of electronic health records (EHRs) on predefined patient safety outcomes in interventional studies to identify gaps in current knowledge and design interventions for future research.

DESIGN

Scoping review to map existing evidence and identify gaps for future research.

DATA SOURCES

PubMed, the Cochrane Library, EMBASE, Trial registers.

STUDY SELECTION

Eligibility criteria: We conducted a scoping review of bibliographic databases and the grey literature of randomised and non-randomised trials describing interventions targeting a list of fourteen predefined areas of safety. The search was limited to manuscripts published between January 2008 and December 2018 of studies in adult inpatient settings and complemented by a targeted search for studies using a sample of EHR vendors. Studies were categorised according to methodology, intervention characteristics and safety outcome.Results from identified studies were grouped around common themes of safety measures.

RESULTS

The search yielded 583 articles of which 24 articles were included. The identified studies were largely from US academic medical centres, heterogeneous in study conduct, definitions, treatment protocols and study outcome reporting. Of the 24 included studies effective safety themes included medication reconciliation, decision support for prescribing medications, communication between teams, infection prevention and measures of EHR-specific harm. Heterogeneity of the interventions and study characteristics precluded a systematic meta-analysis. Most studies reported process measures and not patient-level safety outcomes: We found no or limited evidence in 13 of 14 predefined safety areas, with good evidence limited to medication safety.

CONCLUSIONS

Published evidence for EHR impact on safety outcomes from interventional studies is limited and does not permit firm conclusions regarding the full safety impact of EHRs or support recommendations about ideal design features. The review highlights the need for greater transparency in quality assurance of existing EHRs and further research into suitable metrics and study designs.

The effect of medication related clinical decision support at the time of physician order entry

Background In advanced clinical decision support systems, patient characteristics and laboratory values are included in the algorithms that generate alerts. These alerts have a higher specificity than basic medication surveillance alerts. The alerts of advanced clinical decision support systems can be shown directly to the prescriber during order entry, without the risk of generating an overload of irrelevant alerts. We implemented five advanced algorithms that are shown directly to the prescriber. These algorithms are for gastrointestinal prophylaxis, folic or folinic acid prescribed with orally or subcutaneously administered methotrexate, vitamin D prescribed with bisphosphonates, hyponatremia and measuring plasma levels for vancomycin and gentamicin. Objective We evaluated the effect of the implementation of the algorithms. Setting We performed prospective intervention studies with a historical group for comparison in both inpatients and outpatients at a teaching hospital in the Netherlands. Methods We compared the time period after implementation of the algorithm with the time period before implementation, using data from the hospital information system Epic. Difference in guideline adherence were analyzed using Chi square tests. Main outcome measure The outcome measures were the number of alerts, the acceptance rate of the advice in the alert, and for the algorithm measuring plasma levels for vancomycin and gentamicin the time to the correct dose. Results For all algorithms, the implementation resulted in a significant increase in guideline adherence, varying from 11 to 36%. The acceptance rate varied from 14% for hyponatremia to 90% for methotrexate. For gastrointestinal prophylaxis the acceptance rate was 4.4% for basic drug-drug interaction alerts when no gastrointestinal prophylaxis was prescribed and increased to 44.7% after implementation of the advanced algorithm. This algorithm substantially decreased the number of alerts from 812 before implementation to 217 after implementation. After implementation of the algorithm for measuring plasma levels for vancomycin and gentamicin, the proportion of patients receiving the correct dose after 48 h increased from 73 to 84% (p = 0.03). Conclusion Implementation of advanced algorithms that take patient characteristics into account and are shown directly to the physician during order entry, result in an increased guideline adherence.

Drug Safety in Geriatric Patients: Current Status and Proposed Way Forward

Elderly patients are the main users of drugs and they differ from younger patients. They are a heterogeneous population that cannot be defined only by age but should rather be stratified based on their frailty. The elderly have distinctive pharmacokinetic and pharmacodynamic characteristics, are frequently polymorbid, and are therefore treated with multiple drugs. They may experience adverse reactions that are difficult to recognize, since some of them present non-specific symptoms easily mistaken for geriatric conditions. Paradoxically, the elderly are underrepresented in clinical trials, especially the frail individuals whose pharmacological response and expected treatment outcome can be different from those of non-frail patients. This means that the benefit-risk balance of drugs used in frail elderly patients is frequently unknown. We present some proposals to overcome the barriers preventing the enrollment of frail elderly patients in clinical trials, and strategies for monitoring their therapy to minimize the risk of adverse reactions. Automated alerts for drug and drug-disease interactions could help appropriate prescribing but should flag only clinically relevant interactions. Pharmaceutical forms should be designed to allow easy dose adjustment and, together with packaging and labeling, should account for the physical and cognitive limitations of frail elderly patients. Aggregate pharmacovigilance reports should summarize the safety profile in the elderly, but rather than presenting the results by age they should focus on patients' frailty, perhaps using the number of comorbidities as a proxy when information on frailty is not available.

Contributions from the 2016 Literature on Clinical Decision Support

Objectives: To summarize recent research and select the best papers published in 2016 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Methods: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs). The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting of the IMIA editorial team finally selected the best papers on the basis of all reviews and section editor evaluation. Results: Among the 1,145 retrieved papers, the entire review process resulted in the selection of four best papers. The first paper describes machine learning models used to predict breast cancer multidisciplinary team decisions and compares them with two predictors based on guideline knowledge. The second paper introduces a linked-data approach for publication, discovery, and interoperability of CDSSs. The third paper assessed the variation in high-priority drug-drug interaction (DDI) alerts across 14 Electronic Health Record systems, operating in different institutions in the US. The fourth paper proposes a generic framework for modeling multiple concurrent guidelines and detecting their recommendation interactions using semantic web technologies. Conclusions: The process of identifying and selecting best papers in the domain of CDSSs demonstrated that the research in this field is very active concerning diverse dimensions, such as the types of CDSSs, e.g. guideline-based, machine-learning-based, knowledge-fusion-based, etc., and addresses challenging areas, such as the concurrent application of multiple guidelines for comorbid patients, the resolution of interoperability issues, and the evaluation of CDSSs. Nevertheless, this process also showed that CDSSs are not yet fully part of the digitalized healthcare ecosystem. Many challenges remain to be faced with regard to the evidence of their output, the dissemination of their technologies, as well as their adoption for better and safer healthcare delivery.