scholarly journals Harnessing the Electronic Health Record and Computerized Provider Order Entry Data for Resource Management During the COVID-19 Pandemic: Development of a Decision Tree (Preprint)

2021 ◽  
Author(s):  
Hung S Luu ◽  
Laura M Filkins ◽  
Jason Y Park ◽  
Dinesh Rakheja ◽  
Jefferson Tweed ◽  
...  
Keyword(s):  
Decision Tree ◽  
Electronic Health Record ◽  
Personal Protective Equipment ◽  
Protective Equipment ◽  
Health Record ◽  
Care Providers ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Asymptomatic Patients ◽  
Electronic Health

BACKGROUND The COVID-19 pandemic has resulted in shortages of diagnostic tests, personal protective equipment, hospital beds, and other critical resources. OBJECTIVE We sought to improve the management of scarce resources by leveraging electronic health record (EHR) functionality, computerized provider order entry, clinical decision support (CDS), and data analytics. METHODS Due to the complex eligibility criteria for COVID-19 tests and the EHR implementation–related challenges of ordering these tests, care providers have faced obstacles in selecting the appropriate test modality. As test choice is dependent upon specific patient criteria, we built a decision tree within the EHR to automate the test selection process by using a branching series of questions that linked clinical criteria to the appropriate SARS-CoV-2 test and triggered an EHR flag for patients who met our institutional persons under investigation criteria. RESULTS The percentage of tests that had to be canceled and reordered due to errors in selecting the correct testing modality was 3.8% (23/608) before CDS implementation and 1% (262/26,643) after CDS implementation (<i>P</i>&lt;.001). Patients for whom multiple tests were ordered during a 24-hour period accounted for 0.8% (5/608) and 0.3% (76/26,643) of pre- and post-CDS implementation orders, respectively (<i>P</i>=.03). Nasopharyngeal molecular assay results were positive in 3.4% (826/24,170) of patients who were classified as asymptomatic and 10.9% (1421/13,074) of symptomatic patients (<i>P</i>&lt;.001). Positive tests were more frequent among asymptomatic patients with a history of exposure to COVID-19 (36/283, 12.7%) than among asymptomatic patients without such a history (790/23,887, 3.3%; <i>P</i>&lt;.001). CONCLUSIONS The leveraging of EHRs and our CDS algorithm resulted in a decreased incidence of order entry errors and the appropriate flagging of persons under investigation. These interventions optimized reagent and personal protective equipment usage. Data regarding symptoms and COVID-19 exposure status that were collected by using the decision tree correlated with the likelihood of positive test results, suggesting that clinicians appropriately used the questions in the decision tree algorithm.

scholarly journals Association of Display of Patient Photographs in the Electronic Health Record With Wrong-Patient Order Entry Errors

2020 ◽  
Vol 3 (11) ◽  
pp. e2019652
Author(s):  
Hojjat Salmasian ◽  
Bonnie B. Blanchfield ◽  
Kelley Joyce ◽  
Kaila Centeio ◽  
Gordon B. Schiff ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Health Record ◽  
Order Entry ◽  
Electronic Health

scholarly journals Development of a Cancer Care Summary Through the Electronic Health Record

2016 ◽  
Vol 12 (2) ◽  
pp. e231-e240 ◽  
Author(s):  
Laurie L. Carr ◽  
Pearlanne Zelarney ◽  
Sarah Meadows ◽  
Jeffrey A. Kern ◽  
M. Bronwyn Long ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Cancer Care ◽  
Query Language ◽  
Primary Care Providers ◽  
Urgent Care ◽  
Health Record ◽  
Patient Portal ◽  
Care Providers ◽  
Improvement Project ◽  
Electronic Health

Introduction: Our objective was to improve communication concerning lung cancer patients by developing and distributing a Cancer Care Summary that would provide clinically useful information about the patient’s diagnosis and care to providers in diverse settings. Methods: We designed structured, electronic forms for the electronic health record (EHR), detailing tumor staging, classification, and treatment. To ensure completeness and accuracy of the information, we implemented a data quality cycle, composed of reports that are reviewed by oncology clinicians. The data from the EHR forms are extracted into a structured query language database system on a daily basis, from which the Summaries are derived. We conducted focus groups regarding the utility, format, and content of the Summary. Cancer Care Summaries are automatically generated 4 months after a patient’s date of diagnosis, then every 6 months for those receiving treatment, and on an as-needed basis for urgent care or hospital admission. Results: The product of our improvement project is the Cancer Care Summary. To date, 102 individual patient Summaries have been generated. These documents are automatically entered into the National Jewish Health (NJH) EHR, attached to correspondence to primary care providers, available to patients as electronic documents on the NJH patient portal, and faxed to emergency departments and admitting physicians on patient evaluation. Conclusion: We developed a sustainable tool to improve cancer care communication. The Cancer Care Summary integrates information from the EHR in a timely manner and distributes the information through multiple avenues.

scholarly journals Using a certified electronic health record technology platform to screen, test and refer patients with prediabetes

JAMIA Open ◽  
2021 ◽  
Vol 4 (4) ◽  
Author(s):  
Kate Kirley ◽  
Tamkeen Khan ◽  
Gina Aquino ◽  
Ameldia Brown ◽  
Scott Meier ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Diabetes Prevention Program ◽  
Screen Test ◽  
Primary Care Providers ◽  
Baseline Period ◽  
Health Record ◽  
Patient Portal ◽  
Care Providers ◽  
Conversion Rates ◽  
Electronic Health

Abstract The objective of this study was to determine if certified electronic health record technology (CEHRT) can be used to identify and refer patients with prediabetes to lifestyle change programs (LCPs) recognized by the National Diabetes Prevention Program (DPP). This pilot utilized a prediabetes registry, patient portal, and clinical decision support to increase referrals. Data from 36 primary care providers showed 4930 patients were eligible for DPP LCP, 293 referrals were generated, compared to 20 referrals in the baseline period, and 116 patients enrolled. Referral to enrollment conversion rates were 41% in the study period and 69% in the post-study 1-year period. CEHRT functionalities can support systematic identification and management of prediabetes. The referral rate increased 7-fold compared to the baseline period, with high referral to enrollment conversion rates. CEHRT coupled with active provider engagement can serve as a tool to identify prediabetes patients and facilitate LCP referrals and enrollment.

scholarly journals Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings

2021 ◽  
Vol 12 (04) ◽  
pp. 737-744
Author(s):  
Amrita Sinha ◽  
Lindsay A. Stevens ◽  
Felice Su ◽  
Natalie M. Pageler ◽  
Daniel S. Tawfik
Keyword(s):  
Electronic Health Record ◽  
Pediatric Intensive Care ◽  
Clinical Activity ◽  
Inpatient Setting ◽  
Health Record ◽  
Full Time ◽  
Care Providers ◽  
Provider Type ◽  
Full Time Equivalent ◽  
Electronic Health

Abstract Background Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider clinical activity. Objective The aim of our study was to validate audit-log based EHR times using observed EHR-times extracted from screen recordings of EHR usage in the inpatient setting. Methods This study was conducted in a 36-bed pediatric intensive care unit (PICU) at Lucile Packard Children's Hospital Stanford between June 11 and July 14, 2020. Attending physicians, fellow physicians, hospitalists, and advanced practice providers with ≥0.5 full-time equivalent (FTE) for the prior four consecutive weeks and at least one EHR session recording were included in the study. Citrix session recording player was used to retrospectively review EHR session recordings that were captured as the provider interacted with the EHR. Results EHR use patterns varied by provider type. Audit-log based total EHR time correlated strongly with both observed total EHR time (r = 0.98, p < 0.001) and observed active EHR time (r = 0.95, p < 0.001). Each minute of audit-log based total EHR time corresponded to 0.95 (0.87–1.02) minutes of observed total EHR time and 0.75 (0.67–0.83) minutes of observed active EHR time. Results were similar when stratified by provider role. Conclusion Our study found inpatient audit-log based EHR time to correlate strongly with observed EHR time among pediatric critical care providers. These findings support the use of audit-log based EHR-time as a surrogate measure for inpatient provider EHR use, providing an opportunity for researchers and other stakeholders to leverage EHR audit-log data in measuring clinical activity and tracking outcomes of workflow improvement efforts longitudinally and across provider groups.

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