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Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

ABSTRACT: STUDY OBJECTIVE:As electronic health records evolve, integration of computerized clinical decision support offers the promise of sorting, collecting, and presenting this information to improve patient care. We conducted a systematic review to examine the scope and influence of electronic health record-integrated clinical decision support technologies implemented in the emergency department (ED). METHODS:A literature search was conducted in 4 databases from their inception through January 18, 2018: PubMed, Scopus, the Cumulative Index of Nursing and Allied Health, and Cochrane Central. Studies were included if they examined the effect of a decision support intervention that was implemented in a comprehensive electronic health record in the ED setting. Standardized data collection forms were developed and used to abstract study information and assess risk of bias. RESULTS:A total of 2,558 potential studies were identified after removal of duplicates. Of these, 42 met inclusion criteria. Common targets for clinical decision support intervention included medication and radiology ordering practices, as well as more comprehensive systems supporting diagnosis and treatment for specific disease entities. The majority of studies (83%) reported positive effects on outcomes studied. Most studies (76%) used a pre-post experimental design, with only 3 (7%) randomized controlled trials. CONCLUSION:Numerous studies suggest that clinical decision support interventions are effective in changing physician practice with respect to process outcomes such as guideline adherence; however, many studies are small and poorly controlled. Future studies should consider the inclusion of more specific information in regard to design choices, attempt to improve on uncontrolled before-after designs, and focus on clinically relevant outcomes wherever possible.

SUBMITTER: Patterson BW

PROVIDER: S-EPMC6610851 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

Patterson Brian W BW Pulia Michael S MS Ravi Shashank S Hoonakker Peter L T PLT Schoofs Hundt Ann A Wiegmann Douglas D Wirkus Emily J EJ Johnson Stephen S Carayon Pascale P

Annals of emergency medicine 20190103 2

<h4>Study objective</h4>As electronic health records evolve, integration of computerized clinical decision support offers the promise of sorting, collecting, and presenting this information to improve patient care. We conducted a systematic review to examine the scope and influence of electronic health record-integrated clinical decision support technologies implemented in the emergency department (ED).<h4>Methods</h4>A literature search was conducted in 4 databases from their inception through ...[more]

PMID: 30611639

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Project description:Background. While often first treated in the emergency department (ED), identification of sepsis is difficult. Electronic medical record (EMR) clinical decision tools offer a novel strategy for identifying patients with sepsis. The objective of this study was to test the accuracy of an EMR-based, automated sepsis identification system. Methods. We tested an EMR-based sepsis identification tool at a major academic, urban ED with 64,000 annual visits. The EMR system collected vital sign and laboratory test information on all ED patients, triggering a "sepsis alert" for those with ?2 SIRS (systemic inflammatory response syndrome) criteria (fever, tachycardia, tachypnea, leukocytosis) plus ?1 major organ dysfunction (SBP ? 90 mm Hg, lactic acid ?2.0 mg/dL). We confirmed the presence of sepsis through manual review of physician, nursing, and laboratory records. We also reviewed a random selection of ED cases that did not trigger a sepsis alert. We evaluated the diagnostic accuracy of the sepsis identification tool. Results. From January 1 through March 31, 2012, there were 795 automated sepsis alerts. We randomly selected 300 cases without a sepsis alert from the same period. The true prevalence of sepsis was 355/795 (44.7%) among alerts and 0/300 (0%) among non-alerts. The positive predictive value of the sepsis alert was 44.7% (95% CI [41.2-48.2%]). Pneumonia and respiratory infections (38%) and urinary tract infection (32.7%) were the most common infections among the 355 patients with true sepsis (true positives). Among false-positive sepsis alerts, the most common medical conditions were gastrointestinal (26.1%), traumatic (25.7%), and cardiovascular (20.0%) conditions. Rates of hospital admission were: true-positive sepsis alert 91.0%, false-positive alert 83.0%, no sepsis alert 5.7%. Conclusions. This ED EMR-based automated sepsis identification system was able to detect cases with sepsis. Automated EMR-based detection may provide a viable strategy for identifying sepsis in the ED.

Project description:BackgroundThe Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions.ObjectiveOur objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns.MethodsUser-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage.ResultsThe Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool includes a patient injury evaluator based on the Canadian CT Head Rule and provides patient specific risks using pictographs with natural frequencies and cues for discussion about patient concerns.ConclusionsThis tool was designed to align evidence-based practices about CT in minor head injury patients. It establishes trust, empowers active participation, and addresses patient concerns and uncertainty about their condition. We hypothesize that, when implemented, the Concussion or Brain Bleed app will support-not hinder-the clinician-patient relationship, safely reduce CT use, and improve the patient experience of care.

Project description:BackgroundAsthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.ObjectiveWe propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.MethodsWe performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.ResultsThere were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91-0.94) and 0.94 (0.93-0.96), respectively, for EMR and claims data, with positive predictive value of?>?94%. The algorithms are visually presented using nomograms.ConclusionWe were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

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Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

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Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.

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