1. Quality improvement and practice-based research in sleep medicine using structured clinical documentation in the electronic medical record
- Author
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Samuel Tideman, Thomas Freedom, Camelia Musleh, Joya Paul, Demetrius M. Maraganore, Rosa Maria Vazquez, Richard Munson, Lori E. Lovitz, Nabeela Nasir, Steven Meyers, Mari Viola-Saltzman, Kelly Claire Simon, Anna Pham, Roberta Frigerio, Richard Chesis, Smita S. Patel, and Laura Hillman more...
- Subjects
medicine.medical_specialty ,Best practices ,Quality management ,Electronic medical record ,lcsh:Medicine ,Clinical decision support system ,Sleep medicine ,Article ,Pittsburgh Sleep Quality Index ,03 medical and health sciences ,0302 clinical medicine ,Documentation ,medicine ,030212 general & internal medicine ,Progress note ,business.industry ,Epworth Sleepiness Scale ,lcsh:R ,Clinical decision support ,Sleep disorders ,medicine.disease ,Biobank ,Structured clinical documentation support ,Medical emergency ,business ,030217 neurology & neurosurgery - 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. more...
- Published
- 2020