scholarly journals Structured clinical documentation in the electronic medical record to improve quality and to support practice-based research in epilepsy

Epilepsia ◽  
2016 ◽  
Vol 58 (1) ◽  
pp. 68-76 ◽  
Author(s):  
Jaishree Narayanan ◽  
Sofia Dobrin ◽  
Janet Choi ◽  
Susan Rubin ◽  
Anna Pham ◽  
...  
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Demetrius M. Maraganore ◽  
Thomas Freedom ◽  
Kelly Claire Simon ◽  
Lori E. Lovitz ◽  
Camelia Musleh ◽  
...  

Abstract Background We developed and implemented a structured clinical documentation support (SCDS) toolkit within the electronic medical record, to optimize patient care, facilitate documentation, and capture data at office visits in a sleep medicine/neurology clinic for patient care and research collaboration internally and with other centers. Methods To build our SCDS toolkit, physicians met frequently to develop content, define the cohort, select outcome measures, and delineate factors known to modify disease progression. We assigned tasks to the care team and mapped data elements to the progress note. Programmer analysts built and tested the SCDS toolkit, which included several score tests. Auto scored and interpreted tests included the Generalized Anxiety Disorder 7-item, Center for Epidemiological Studies Depression Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Insomnia Severity Index, and the International Restless Legs Syndrome Study Group Rating Scale. The SCDS toolkits also provided clinical decision support (untreated anxiety or depression) and prompted enrollment of patients in a DNA biobank. Results The structured clinical documentation toolkit captures hundreds of fields of discrete data at each office visit. This data can be displayed in tables or graphical form. Best practice advisories within the toolkit alert physicians when a quality improvement opportunity exists. As of May 1, 2019, we have used the toolkit to evaluate 18,105 sleep patients at initial visit. We are also collecting longitudinal data on patients who return for annual visits using the standardized toolkits. We provide a description of our development process and screenshots of our toolkits. Conclusions The electronic medical record can be structured to standardize Sleep Medicine office visits, capture data, and support multicenter quality improvement and practice-based research initiatives for sleep patients at the point of care.


2016 ◽  
Vol 18 (suppl_6) ◽  
pp. vi158-vi159
Author(s):  
Ryan Merrell ◽  
Nina Martinez ◽  
Susan Stasinos ◽  
James Muresan ◽  
Shaun Walters ◽  
...  

Author(s):  
Katherine Blondon ◽  
Frederic Ehrler

Patient-generated health data (PGHD), when shared with the provider, provides potential as an approach to improve quality of care. Based on interviews and a focus group with stakeholders involved in PGHD integration in the electronic medical record (EMR), we explore the benefits, barriers and possible risks. We propose solutions to address liability concerns, such as clarifying patient and provider expectations for the analyses of PGHD and emphasize considerations for future steps, which include the need to screen PGHD for patient safety.


Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Kelly Gleason ◽  
Maria R. Dahm

Abstract Objectives To explore how patients describe their diagnoses following Emergency Department (ED) discharge, and how this compares to electronic medical record (EMR) documentation. Methods We conducted a cohort study of patients discharged from three EDs. Patients completed questionnaires regarding their understanding of their diagnosis. Inclusion criteria: adult ED patients aged 18 and older seen within the last seven days. We independently compared patient-reported new diagnoses following discharge to EMR-documented diagnoses regarding diagnostic content (identical, insignificantly different, different, not enough detail) and the level of technical language in diagnostic description (technical, semi-technical, lay). Results The majority of participants (n=95 out of 137) reported receiving a diagnosis and stated the given diagnosis. Of those who reported their diagnosis, 66%, were females (n=62), the average age was 43 (SD 16), and a fourth (n=24) were Black and 66% (n=63) were white. The majority (84%) described either the same or an insignificantly different diagnosis. For 11% the patient-reported diagnosis differed from the one documented. More than half reported their diagnosis using semi-technical (34%) or technical language (26%), and over a third (40%) described their diagnosis in lay language. Conclusions Patient-reported diagnoses following ED discharge had moderate agreement with EMR-documented diagnoses. Findings suggest that patients might reproduce verbatim semi-technical or technical diagnoses they received from clinicians, but not fully understood what the diagnosis means for them.


2018 ◽  
Vol 58 (8) ◽  
pp. 1211-1218
Author(s):  
Steven Meyers ◽  
Kelly Claire Simon ◽  
Stuart Bergman-Bock ◽  
Franco Campanella ◽  
Revital Marcus ◽  
...  

2015 ◽  
Vol 5 (5) ◽  
pp. 419-429 ◽  
Author(s):  
Demetrius M. Maraganore ◽  
Roberta Frigerio ◽  
Nazia Kazmi ◽  
Steven L. Meyers ◽  
Meredith Sefa ◽  
...  

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