Mitigating Display Fragmentation in the Electronic Health Record with the MedWISER Composable Approach: A Mixed Methods Design (Preprint)

2020 ◽  
Author(s):  
Yalini Senathirajah ◽  
David R. Kaufman ◽  
Kenrick D. Cato ◽  
Elizabeth M. Borycki ◽  
Jaime Allen Fawcett ◽  
...  
Keyword(s):  
Working Memory ◽  
Cognitive Load ◽  
Electronic Health Record ◽  
Patient Care ◽  
Quality Data ◽  
Cognitive Resources ◽  
Health Record ◽  
Needed Information ◽  
Keyhole Effect ◽  
Electronic Health

BACKGROUND Navigational complexity can present formidable challenges for electronic health record (EHR) users. The fragmented design of conventional EHRs can contribute to increased cognitive load for clinician users and poor fit-to-task. First, the ‘keyhole effect’ describes the phenomenon in which due to the large volume of information and limited screen size, users cannot see all information on the same screen (like only seeing part of a large room through a small keyhole). Needed information is spread across several screens, creating fragmented displays and information. This can increase cognitive load – or the use of limited working memory resources – as users must navigate to a screen, identify useful information, and then hold that information in working memory as they navigate to another screen. For clinicians navigating EHRs, this has consequences for patient care as cognitive resources (perception, attention, and memory) are known to be limited. As clinicians expend more cognitive resources navigating and processing information from an EHR, they have fewer cognitive resources for patient care tasks and diagnostic reasoning, leading to possible error. Additionally, two key contextual factors in healthcare settings need to be addressed by EHRs to enable better fit-to-task: (1) clinicians often communicate information via patient records, thus the EHR needs to facilitate that communication; and (2) physicians are prone to interruptions as part of their workflow, which can lead to errors or omissions in perceiving information. Reducing fragmentation in EHR design has the potential to reduce cognitive load and enhance fit-to-task for clinician users. OBJECTIVE Introduce a novel composable approach to EHR design implemented as MedWISER, a composable system where users can freely assemble needed information on the same screen, thus reducing fragmentation. This study protocol introduces methods by which to assess MedWISER’s potential to address the keyhole effect and poor fit-to-task problems by reducing cognitive load, enhancing communication, and mitigating the impact of workflow interruptions. METHODS This multi-study project will involve qualitative and quantitative methods to evaluate how conventional EHRs and the composable approach affect clinician performance. Methods include think-aloud protocols, task completion, simulation studies, screen capture and eye tracking, and interviews and surveys. Key measures include time to complete tasks, error detection/omission, completeness of information review, and gaze direction. Subjects will be clinicians from large university hospital settings. RESULTS This project is supported by the Agency for Healthcare Research and Quality. Data collection and analysis is anticipated to conclude in Spring 2021. CONCLUSIONS Together these studies allow investigators to successfully investigate a range of challenges and contexts associated with EHR design, cognitive load, safety, and fit-to-task and evaluate the usefulness of the composable EHR design in meeting them. CLINICALTRIAL The following is not a clinical trial.

scholarly journals I-THS-1908 A Big Data Electronic Health Record for Patient Care Management and Analytics

2019 ◽  
Author(s):  
Ahmad Hidayat ◽  
Arief Hasani
Keyword(s):  
Big Data ◽  
Electronic Health Record ◽  
Patient Care ◽  
Care Management ◽  
Patient Care Management ◽  
Health Conditions ◽  
Health Record ◽  
Complex Variety ◽  
Electronic Health ◽  
Further Development

The I-THS-1908, a big data electronic health record platform, is capable of establishing its capability as an electronic health record to tackle the large volume of data with high velocity and complex variety of patient data by providing the value to the patient care management and analytics. The further development of I-THS-1908 opens the opportunity to use the electronic health record for patient care management and analytics for all type of health conditions.

scholarly journals Electronic Health Record Adoption – Maybe It’s not about the Money

2011 ◽  
Vol 02 (04) ◽  
pp. 460-471 ◽  
Author(s):  
A. Skinner ◽  
J. Windle ◽  
L. Grabenbauer
Keyword(s):  
Electronic Health Record ◽  
Patient Care ◽  
Resistance To Change ◽  
Medical Center ◽  
Academic Medical Center ◽  
Care Physician ◽  
Health Record ◽  
Record System ◽  
Intuitive Interfaces ◽  
Electronic Health

SummaryObjective: The slow adoption of electronic health record (EHR) systems has been linked to physician resistance to change and the expense of EHR adoption. This qualitative study was conducted to evaluate benefits, and clarify limitations of two mature, robust, comprehensive EHR Systems by tech-savvy physicians where resistance and expense are not at issue.Methods: Two EHR systems were examined – the paperless VistA / Computerized Patient Record System used at the Veterans‘ Administration, and the General Electric Centricity Enterprise system used at an academic medical center. A series of interviews was conducted with 20 EHR-savvy multi-institutional internal medicine (IM) faculty and house staff. Grounded theory was used to analyze the transcribed data and build themes. The relevance and importance of themes were constructed by examining their frequency, convergence, and intensity.Results: Despite eliminating resistance to both adoption and technology as drivers of acceptance, these two robust EHR’s are still viewed as having an adverse impact on two aspects of patient care, physician workflow and team communication. Both EHR’s had perceived strengths but also significant limitations and neither were able to satisfactorily address all of the physicians’ needs.Conclusion: Difficulties related to physician acceptance reflect real concerns about EHR impact on patient care. Physicians are optimistic about the future benefits of EHR systems, but are frustrated with the non-intuitive interfaces and cumbersome data searches of existing EHRs.

scholarly journals The Use of Electronic Health Record Systems During COVID-19 at a Local Community Hospital on the West Coast

2021 ◽  
pp. 53-58
Author(s):  
Malini Krishnamurthi, Ph.D.
Keyword(s):  
Health Care ◽  
Electronic Health Record ◽  
Patient Care ◽  
Data Privacy ◽  
Local Community ◽  
Quality Care ◽  
The United States ◽  
Health Record ◽  
Privacy And Security ◽  
Electronic Health

The United States Federal government looks toward information technology to curtail health care costs while increasing the quality of patient care through the adoption of electronic health record (EHR)systems. This paper examined the experience of a hospital with its EHR system in the context of the pandemic. Results showed that the hospital maintains a state-of-the-art health care system to provide quality care to its community and was responsive to the recent crisis. The results were consistent with other comparable hospitals examined in this study. The hospitals were successful in adopting EHR systems. They were able to identify gaps that could be filled with technology add-ons from different software vendors to improve their functionality and thereby provide better & timely patient care. Managing large volumes of data generated in the normal process of EHR operation and ensuring data privacy and security were the significant challenges faced and are likely to continue in the future.

scholarly journals A statistical quality assessment method for longitudinal observations in electronic health record data with an application to the VA million veteran program

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hui Wang ◽  
Ilana Belitskaya-Levy ◽  
Fan Wu ◽  
Jennifer S. Lee ◽  
Mei-Chiung Shih ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Quality Assessment ◽  
The Body ◽  
Quality Data ◽  
Health Record ◽  
Continuous Variables ◽  
Electronic Health Record Data ◽  
Thresholding Method ◽  
Electronic Health ◽  
Weight Data

Abstract Background To describe an automated method for assessment of the plausibility of continuous variables collected in the electronic health record (EHR) data for real world evidence research use. Methods The most widely used approach in quality assessment (QA) for continuous variables is to detect the implausible numbers using prespecified thresholds. In augmentation to the thresholding method, we developed a score-based method that leverages the longitudinal characteristics of EHR data for detection of the observations inconsistent with the history of a patient. The method was applied to the height and weight data in the EHR from the Million Veteran Program Data from the Veteran’s Healthcare Administration (VHA). A validation study was also conducted. Results The receiver operating characteristic (ROC) metrics of the developed method outperforms the widely used thresholding method. It is also demonstrated that different quality assessment methods have a non-ignorable impact on the body mass index (BMI) classification calculated from height and weight data in the VHA’s database. Conclusions The score-based method enables automated and scaled detection of the problematic data points in health care big data while allowing the investigators to select the high-quality data based on their need. Leveraging the longitudinal characteristics in EHR will significantly improve the QA performance.

Novel Nonproprietary Measures of Ambulatory Electronic Health Record Use Associated with Physician Work Exhaustion

2021 ◽  
Vol 12 (03) ◽  
pp. 637-646
Author(s):  
Amrita Sinha ◽  
Tait D. Shanafelt ◽  
Mickey Trockel ◽  
Hanhan Wang ◽  
Christopher Sharp
Keyword(s):  
Electronic Health Record ◽  
Patient Care ◽  
Dominant Factor ◽  
Health Record ◽  
Occupational Burnout ◽  
Electronic Health ◽  
Perception Of Time ◽  
Professional Fulfillment ◽  
The Impact ◽  
Physician Work

Abstract Background Accumulating evidence indicates an association between physician electronic health record (EHR) use after work hours and occupational distress including burnout. These studies are based on either physician perception of time spent in EHR through surveys which may be prone to bias or by utilizing vendor-defined EHR use measures which often rely on proprietary algorithms that may not take into account variation in physician's schedules which may underestimate time spent on the EHR outside of scheduled clinic time. The Stanford team developed and refined a nonproprietary EHR use algorithm to track the number of hours a physician spends logged into the EHR and calculates the Clinician Logged-in Outside Clinic (CLOC) time, the number of hours spent by a physician on the EHR outside of allocated time for patient care. Objective The objective of our study was to measure the association between CLOC metrics and validated measures of physician burnout and professional fulfillment. Methods Physicians from adult outpatient Internal Medicine, Neurology, Dermatology, Hematology, Oncology, Rheumatology, and Endocrinology departments who logged more than 8 hours of scheduled clinic time per week and answered the annual wellness survey administered in Spring 2019 were included in the analysis. Results We observed a statistically significant positive correlation between CLOC ratio (defined as the ratio of CLOC time to allocated time for patient care) and work exhaustion (Pearson's r = 0.14; p = 0.04), but not interpersonal disengagement, burnout, or professional fulfillment. Conclusion The CLOC metrics are potential objective EHR activity-based markers associated with physician work exhaustion. Our results suggest that the impact of time spent on EHR, while associated with exhaustion, does not appear to be a dominant factor driving the high rates of occupational burnout in physicians.

scholarly journals Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record

2017 ◽  
Vol 08 (04) ◽  
pp. 1159-1172 ◽  
Author(s):  
Timothy Kennell ◽  
James Willig ◽  
James Cimino
Keyword(s):  
Electronic Health Record ◽  
Biomedical Informatics ◽  
Research Result ◽  
Clinical Informatics ◽  
Quality Data ◽  
Health Record ◽  
Next Generation ◽  
Patient Reported ◽  
Data Content ◽  
Electronic Health

Objective Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR. Materials and Methods We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations. Results Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping. Discussion These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics. Conclusion Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.

scholarly journals Time Spent on Dedicated Patient Care and Documentation Tasks Before and After the Introduction of a Structured and Standardized Electronic Health Record

2018 ◽  
Vol 09 (01) ◽  
pp. 046-053 ◽  
Author(s):  
Erik Joukes ◽  
Ameen Abu-Hanna ◽  
Ronald Cornet ◽  
Nicolette de Keizer
Keyword(s):  
Electronic Health Record ◽  
Patient Care ◽  
Time Distribution ◽  
Health Record ◽  
University Hospitals ◽  
Peer Communication ◽  
Significant Difference ◽  
Before And After ◽  
Electronic Health ◽  
Multilevel Linear Regression

Background Physicians spend around 35% of their time documenting patient data. They are concerned that adopting a structured and standardized electronic health record (EHR) will lead to more time documenting and less time for patient care, especially during consultations. Objective This study measures the effect of the introduction of a structured and standardized EHR on documentation time and time for dedicated patient care during outpatient consultations. Methods We measured physicians' time spent on four task categories during outpatient consultations: documentation, patient care, peer communication, and other activities. Physicians covered various specialties from two university hospitals that jointly implemented a structured and standardized EHR. Preimplementation, one hospital used a legacy-EHR, and one primarily paper-based records. The same physicians were observed 2 to 6 months before and 6 to 8 months after implementation.We analyzed consultation duration, and percentage of time spent on each task category. Differences in time distribution before and after implementation were tested using multilevel linear regression. Results We observed 24 physicians (162 hours, 439 consultations). We found no significant difference in consultation duration or number of consultations per hour. In the legacy-EHR center, we found the implementation associated with a significant decrease in time spent on dedicated patient care (−8.5%). In contrast, in the previously paper-based center, we found a significant increase in dedicated time spent on documentation (8.3%) and decrease in time on combined patient care and documentation (−4.6%). The effect on dedicated documentation time significantly differed between centers. Conclusion Implementation of a structured and standardized EHR was associated with 8.5% decrease in time for dedicated patient care during consultations in one center and 8.3% increase in dedicated documentation time in another center. These results are in line with physicians' concerns that the introduction of a structured and standardized EHR might lead to more documentation burden and less time for dedicated patient care.

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