Identifying patients with diabetes and the earliest date of diagnosis in real time: an electronic health record case-finding algorithm

Abstract Objectives We sought to make pathologists’ intraoperative consultation (IOC) results immediately available to the surgical team, other clinicians, and laboratory medicine colleagues to improve communication and decrease postanalytic errors. Methods We created an IOC report in our stand-alone laboratory information system that could be signed out prior to, and independent of, the final report, and transfer immediately to the electronic health record (EHR) as a preliminary diagnosis. We evaluated two metrics: preliminary (IOC) result review in the EHR by clinicians and postanalytic errors. Results We assessed 2,886 IOC orders from the first 22 months after implementation. Clinicians reviewed 1,956 (68%) of the IOC results while in preliminary status, including 1,399 (48%) within the first 24 hours. We evaluated 150 cases preimplementation and 300 cases postimplementation for discrepancies between the pathologist’s IOC result and the IOC result recorded by the surgeon in the operative note. Discrepancies dropped from 12 of 150 preimplementation to 6 of 150 and 7 of 150 in postimplementation years 1 and 2. One of the 25 discrepancies had a major clinical impact. Conclusions Real-time reporting of IOC results to the EHR reliably transmits results immediately to clinical teams. This strategy reduces but does not eliminate postanalytic interpretive errors by clinical teams.

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Electronic Health Record–Based Strategy to Promote Medication Adherence Among Patients With Diabetes: Longitudinal Observational Study

Journal of Medical Internet Research ◽

10.2196/13499 ◽

2019 ◽

Vol 21 (10) ◽

pp. e13499 ◽

Cited By ~ 2

Author(s):

Stacy Cooper Bailey ◽

Amisha Wallia ◽

Sarah Wright ◽

Guisselle A Wismer ◽

Alexandra C Infanzon ◽

...

Keyword(s):

Medication Adherence ◽

Electronic Health Record ◽

Low Cost ◽

Clinical Decision ◽

Health Record ◽

Low Literacy ◽

Minimal Impact ◽

Patients With Diabetes ◽

Electronic Health

Background Poor medication adherence is common; however, few mechanisms exist in clinical practice to monitor how patients take medications in outpatient settings. Objective This study aimed to pilot test the Electronic Medication Complete Communication (EMC2) strategy, a low-cost, sustainable approach that uses functionalities within the electronic health record to promote outpatient medication adherence and safety. Methods The EMC2 strategy was implemented in 2 academic practices for 14 higher-risk diabetes medications. The strategy included: (1) clinical decision support alerts to prompt provider counseling on medication risks, (2) low-literacy medication summaries for patients, (3) a portal-based questionnaire to monitor outpatient medication use, and (4) clinical outreach for identified concerns. We recruited adult patients with diabetes who were prescribed a higher-risk diabetes medication. Participants completed baseline and 2-week interviews to assess receipt of, and satisfaction with, intervention components. Results A total of 100 patients were enrolled; 90 completed the 2-week interview. Patients were racially diverse, 30.0% (30/100) had a high school education or less, and 40.0% (40/100) had limited literacy skills. About a quarter (28/100) did not have a portal account; socioeconomic disparities were noted in account ownership by income and education. Among patients with a portal account, 58% (42/72) completed the questionnaire; 21 of the 42 patients reported concerns warranting clinical follow-up. Of these, 17 were contacted by the clinic or had their issue resolved within 24 hours. Most patients (33/38, 89%) who completed the portal questionnaire and follow-up interview reported high levels of satisfaction (score of 8 or greater on a scale of 1-10). Conclusions Findings suggest that the EMC2 strategy can be reliably implemented and delivered to patients, with high levels of satisfaction. Disparities in portal use may restrict intervention reach. Although the EMC2 strategy can be implemented with minimal impact on clinic workflow, future trials are needed to evaluate its effectiveness to promote adherence and safety.

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Performance of a Rules-Based, Electronic Health Record-Driven Severe Asthma Case Finding Algorithm for Clinical Trial Recruitment

10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a3017 ◽

2020 ◽

Author(s):

D.A. Beuther ◽

R.M. Dunn ◽

P. Zelarney ◽

D.C. Everett ◽

M.E. Wechsler

Keyword(s):

Clinical Trial ◽

Electronic Health Record ◽

Severe Asthma ◽

Case Finding ◽

Health Record ◽

Trial Recruitment ◽

Clinical Trial Recruitment ◽

Electronic Health ◽

Asthma Case

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Estimation of Surgical Resident Duty Hours and Workload in Real Time Using Electronic Health Record Data

Journal of Surgical Education ◽

10.1016/j.jsurg.2021.08.011 ◽

2021 ◽

Author(s):

Joseph A. Lin ◽

Logan Pierce ◽

Sara G. Murray ◽

Hossein Soleimani ◽

Elizabeth C. Wick ◽

...

Keyword(s):

Electronic Health Record ◽

Real Time ◽

Health Record ◽

Electronic Health Record Data ◽

Surgical Resident ◽

Duty Hours ◽

Record Data ◽

Resident Duty ◽

Electronic Health

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Real-Time Surveillance for Tuberculosis Using Electronic Health Record Data from an Ambulatory Practice in Eastern Massachusetts

Public Health Reports ◽

10.1177/003335491012500611 ◽

2010 ◽

Vol 125 (6) ◽

pp. 843-850 ◽

Cited By ~ 22

Author(s):

Michael S. Calderwood ◽

Richard Platt ◽

Xuanlin Hou ◽

Jessica Malenfant ◽

Gillian Haney ◽

...

Keyword(s):

Electronic Health Record ◽

Real Time ◽

Health Record ◽

Electronic Health Record Data ◽

Record Data ◽

Ambulatory Practice ◽

Electronic Health ◽

Eastern Massachusetts

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Linking Electronic Health Record-Extracted Psychosocial Data in Real-Time to Risk of Readmission for Heart Failure

Psychosomatics ◽

10.1016/j.psym.2011.02.007 ◽

2011 ◽

Vol 52 (4) ◽

pp. 319-327 ◽

Cited By ~ 33

Author(s):

Alice J. Watson ◽

Julia O'Rourke ◽

Kamal Jethwani ◽

Aurel Cami ◽

Theodore A. Stern ◽

...

Keyword(s):

Heart Failure ◽

Electronic Health Record ◽

Real Time ◽

Health Record ◽

Electronic Health

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Innovative Approach to Evaluating Trainee Operative Skills: Electronic Health Record-Mediated Real-Time Resident Assessment

Journal of the American College of Surgeons ◽

10.1016/j.jamcollsurg.2019.08.780 ◽

2019 ◽

Vol 229 (4) ◽

pp. e49

Author(s):

Jason C. Fisher ◽

Sabrina Lee ◽

Vikashini Savadamuthu ◽

Julio Garcia ◽

Vivian Stellakis ◽

...

Keyword(s):

Electronic Health Record ◽

Real Time ◽

Innovative Approach ◽

Health Record ◽

Electronic Health ◽

Resident Assessment

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Automated data mining of the electronic health record for investigation of healthcare-associated outbreaks

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2018.343 ◽

2019 ◽

Vol 40 (3) ◽

pp. 314-319 ◽

Cited By ~ 14

Author(s):

Alexander J. Sundermann ◽

James K. Miller ◽

Jane W. Marsh ◽

Melissa I. Saul ◽

Kathleen A. Shutt ◽

...

Keyword(s):

Data Mining ◽

Electronic Health Record ◽

Real Time ◽

Outbreak Detection ◽

Health Record ◽

Transmission Route ◽

Multiple Exposures ◽

Route Of Transmission ◽

Electronic Health ◽

Healthcare Associated

AbstractBackground:Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.Methods:We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.Results:Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.Conclusions:Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.

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