Integrating Electronic Health Records into Clinical Workflow: An Application of Human Factors Modeling Methods to Specialty Care in ‘Obstetrics and Gynecology’ and ‘Ophthalmology’

Despite the need for addressing usability issues within Electronic Health Records (EHR), health care organizationshave struggled to systemically involvehuman factors practitioners (HFP). Thereare several challenges to supporting EHR-related work as HFP. Simple design changes mayhavedependencies or create downstream consequences that are not typical of other software systems, or not be feasible to change without overhaul of functionality from theEHR vendor. This panel will present successes and lessons learned bya group of HFP embeddedin healthcare systemswho have extendedexperience working on EHR configurationand design changes. They will discuss challengesand strategies in adopting human factorstechniquesto improve EHR design and related outcomes. By the end of the panel, audience members will learn not only howhuman factors is having animpact in this aspect ofhealthcare delivery, but also learn approaches that may be applicable to other complextechnical systems.

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Detecting moderate or complex congenital heart defects in adults from an electronic health records system

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocy127 ◽

2018 ◽

Vol 25 (12) ◽

pp. 1634-1642

Author(s):

Alpha Oumar Diallo ◽

Asha Krishnaswamy ◽

Stuart K Shapira ◽

Matthew E Oster ◽

Mary G George ◽

...

Keyword(s):

Electronic Health Records ◽

Risk Score ◽

Congenital Heart Defects ◽

Congenital Heart ◽

Heart Defects ◽

Specialty Care ◽

Brier Score ◽

Health Records ◽

Logistic Regression Models ◽

Electronic Health

Abstract Background The prevalence of moderate or complex (moderate-complex) congenital heart defects (CHDs) among adults is increasing due to improved survival, but many patients experience lapses in specialty care or their CHDs are undocumented in the medical system. There is, to date, no efficient approach to identify this population. Objective To develop and assess the performance of a risk score to identify adults aged 20-60 years with undocumented specific moderate-complex CHDs from electronic health records (EHR). Methods We used a case-control study (596 adults with specific moderate-complex CHDs and 2384 controls). We extracted age, race/ethnicity, electrocardiogram (EKG), and blood tests from routine outpatient visits (1/2009 through 12/2012). We used multivariable logistic regression models and a split-sample (4: 1 ratio) approach to develop and internally validate the risk score, respectively. We generated receiver operating characteristic (ROC) c-statistics and Brier scores to assess the ability of models to predict the presence of specific moderate-complex CHDs. Results Out of six models, the non-blood biomarker model that included age, sex, and EKG parameters offered a high ROC c-statistic of 0.96 [95% confidence interval: 0.95, 0.97] and low Brier score (0.05) relative to the other models. The adult moderate-complex congenital heart defect risk score demonstrated good accuracy with 96.4% sensitivity and 80.0% specificity at a threshold score of 10. Conclusions A simple risk score based on age, sex, and EKG parameters offers early proof of concept and may help accurately identify adults with specific moderate-complex CHDs from routine EHR systems who may benefit from specialty care.

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Finding Meaning in Medication Reconciliation Using Electronic Health Records: Qualitative Analysis in Safety Net Primary and Specialty Care (Preprint)

10.2196/preprints.10167 ◽

2018 ◽

Author(s):

George Yaccoub Matta ◽

Elaine C Khoong ◽

Courtney R Lyles ◽

Dean Schillinger ◽

Neda Ratanawongsa

Keyword(s):

Electronic Health Records ◽

Qualitative Analysis ◽

Medication Reconciliation ◽

Safety Net ◽

Specialty Care ◽

Health Records ◽

Finding Meaning ◽

Electronic Health

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Finding Meaning in Medication Reconciliation Using Electronic Health Records: Qualitative Analysis in Safety Net Primary and Specialty Care

JMIR Medical Informatics ◽

10.2196/10167 ◽

2018 ◽

Vol 6 (2) ◽

pp. e10167 ◽

Cited By ~ 2

Author(s):

George Yaccoub Matta ◽

Elaine C Khoong ◽

Courtney R Lyles ◽

Dean Schillinger ◽

Neda Ratanawongsa

Keyword(s):

Electronic Health Records ◽

Qualitative Analysis ◽

Medication Reconciliation ◽

Safety Net ◽

Specialty Care ◽

Health Records ◽

Finding Meaning ◽

Electronic Health

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Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Applied Clinical Informatics ◽

10.1055/s-0041-1730033 ◽

2021 ◽

Vol 12 (03) ◽

pp. 417-428

Author(s):

Jordan R. Hill ◽

Shyam Visweswaran ◽

Xia Ning ◽

Titus K. Schleyer

Keyword(s):

Electronic Health Records ◽

Patient Information ◽

Scoping Review ◽

Point Of Care ◽

Clinical Use ◽

Clinical Workflow ◽

Health Records ◽

Advanced Search ◽

Full Text Review ◽

Electronic Health

Abstract Objective Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient's record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient's record. Conclusion Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering.

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Characterizing Multitasking and Workflow Fragmentation in Electronic Health Records among Emergency Department Clinicians: Using Time-Motion Data to Understand Documentation Burden

Applied Clinical Informatics ◽

10.1055/s-0041-1736625 ◽

2021 ◽

Vol 12 (05) ◽

pp. 1002-1013

Author(s):

Amanda J. Moy ◽

Lucy Aaron ◽

Kenrick D. Cato ◽

Jessica M. Schwartz ◽

Jonathan Elias ◽

...

Keyword(s):

Emergency Department ◽

Electronic Health Records ◽

Average Duration ◽

Clinical Information ◽

Future Research ◽

Clinical Workflow ◽

Health Records ◽

Time Motion ◽

Electronic Health ◽

The Impact

Abstract Background The impact of electronic health records (EHRs) in the emergency department (ED) remains mixed. Dynamic and unpredictable, the ED is highly vulnerable to workflow interruptions. Objectives The aim of the study is to understand multitasking and task fragmentation in the clinical workflow among ED clinicians using clinical information systems (CIS) through time-motion study (TMS) data, and inform their applications to more robust and generalizable measures of CIS-related documentation burden. Methods Using TMS data collected among 15 clinicians in the ED, we investigated the role of documentation burden, multitasking (i.e., performing physical and communication tasks concurrently), and workflow fragmentation in the ED. We focused on CIS-related tasks, including EHRs. Results We captured 5,061 tasks and 877 communications in 741 locations within the ED. Of the 58.7 total hours observed, 44.7% were spent on CIS-related tasks; nearly all CIS-related tasks focused on data-viewing and data-entering. Over one-fifth of CIS-related task time was spent on multitasking. The mean average duration among multitasked CIS-related tasks was shorter than non-multitasked CIS-related tasks (20.7 s vs. 30.1 s). Clinicians experienced 1.4 ± 0.9 task switches/min, which increased by one-third when multitasking. Although multitasking was associated with a significant increase in the average duration among data-entering tasks, there was no significant effect on data-viewing tasks. When engaged in CIS-related task switches, clinicians were more likely to return to the same CIS-related task at higher proportions while multitasking versus not multitasking. Conclusion Multitasking and workflow fragmentation may play a significant role in EHR documentation among ED clinicians, particularly among data-entering tasks. Understanding where and when multitasking and workflow fragmentation occurs is a crucial step to assessing potentially burdensome clinician tasks and mitigating risks to patient safety. These findings may guide future research on developing more scalable and generalizable measures of CIS-related documentation burden that do not necessitate direct observation techniques (e.g., EHR log files).

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