Identification of Design Criteria to Improve Patient Care in Electronic Health Record Downtime

2019 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Ethan P. Larsen ◽  
Ali Haskins Lisle ◽  
Bethany Law ◽  
Joseph L. Gabbard ◽  
Brian M. Kleiner ◽  
...  
2019 ◽  
Author(s):  
Ahmad Hidayat ◽  
Arief Hasani

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.


2011 ◽  
Vol 02 (04) ◽  
pp. 460-471 ◽  
Author(s):  
A. Skinner ◽  
J. Windle ◽  
L. Grabenbauer

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.


Author(s):  
Malini Krishnamurthi, Ph.D.

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.


2021 ◽  
Vol 12 (03) ◽  
pp. 637-646
Author(s):  
Amrita Sinha ◽  
Tait D. Shanafelt ◽  
Mickey Trockel ◽  
Hanhan Wang ◽  
Christopher Sharp

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.


2012 ◽  
Vol 03 (03) ◽  
pp. 349-355 ◽  
Author(s):  
L.N. Guptha Munugoor Baskaran ◽  
P.J. Greco ◽  
D.C. Kaelber

SummaryMedical eponyms are medical words derived from people’s names. Eponyms, especially similar sounding eponyms, may be confusing to people trying to use them because the terms themselves do not contain physiologically descriptive words about the condition they refer to. Through the use of electronic health records (EHRs), embedded applied clinical informatics tools including synonyms and pick lists that include physiologically descriptive terms associated with any eponym appearing in the EHR can significantly enhance the correct use of medical eponyms. Here we describe a case example of two similar sounding medical eponyms – Wegener’s disease and Wegner’s disease – which were confused in our EHR. We describe our solution to address this specific example and our suggestions and accomplishments developing more generalized approaches to dealing with medical eponyms in EHRs. Integrating brief physiologically descriptive terms with medical eponyms provides an applied clinical informatics opportunity to improve patient care.


2014 ◽  
Vol 23 (01) ◽  
pp. 97-104 ◽  
Author(s):  
M. K. Ross ◽  
Wei Wei ◽  
L. Ohno-Machado

Summary Objectives: Implementation of Electronic Health Record (EHR) systems continues to expand. The massive number of patient encounters results in high amounts of stored data. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals for many decades, and this work is now increasingly recognized outside our field. In reviewing the literature for the past three years, we focus on “big data” in the context of EHR systems and we report on some examples of how secondary use of data has been put into practice. Methods: We searched PubMed database for articles from January 1, 2011 to November 1, 2013. We initiated the search with keywords related to “big data” and EHR. We identified relevant articles and additional keywords from the retrieved articles were added. Based on the new keywords, more articles were retrieved and we manually narrowed down the set utilizing predefined inclusion and exclusion criteria. Results: Our final review includes articles categorized into the themes of data mining (pharmacovigilance, phenotyping, natural language processing), data application and integration (clinical decision support, personal monitoring, social media), and privacy and security. Conclusion: The increasing adoption of EHR systems worldwide makes it possible to capture large amounts of clinical data. There is an increasing number of articles addressing the theme of “big data”, and the concepts associated with these articles vary. The next step is to transform healthcare big data into actionable knowledge.


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