title: Leveraging electronic health record documentation for Failure Mode and Effects Analysis team identification.
abstract: OBJECTIVE
  Using Failure Mode and Effects Analysis (FMEA) as an example quality improvement approach, our objective was to evaluate whether secondary use of orders, forms, and notes recorded by the electronic health record (EHR) during daily practice can enhance the accuracy of process maps used to guide improvement. We examined discrepancies between expected and observed activities and individuals involved in a high-risk process and devised diagnostic measures for understanding discrepancies that may be used to inform quality improvement planning.
  
  
  METHODS
  Inpatient cardiology unit staff developed a process map of discharge from the unit. We matched activities and providers identified on the process map to EHR data. Using four diagnostic measures, we analyzed discrepancies between expectation and observation.
  
  
  RESULTS
  EHR data showed that 35% of activities were completed by unexpected providers, including providers from 12 categories not identified as part of the discharge workflow. The EHR also revealed sub-components of process activities not identified on the process map. Additional information from the EHR was used to revise the process map and show differences between expectation and observation.
  
  
  CONCLUSIONS
  Findings suggest EHR data may reveal gaps in process maps used for quality improvement and identify characteristics about workflow activities that can identify perspectives for inclusion in an FMEA. Organizations with access to EHR data may be able to leverage clinical documentation to enhance process maps used for quality improvement. While focused on FMEA protocols, findings from this study may be applicable to other quality activities that require process maps.
authors: Division of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
authors: Gayle Shier
authors: GS
authors: Kricke
authors: Division of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
authors: Matthew B
authors: MB
authors: Carson
authors: School of Nursing, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
authors: Young Ji
authors: YJ
authors: Lee
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: Corrine
authors: C
authors: Benacka
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: R Kannan
authors: RK
authors: Mutharasan
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: Faraz S
authors: FS
authors: Ahmad
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: Preeti
authors: P
authors: Kansal
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: Clyde W
authors: CW
authors: Yancy
authors: Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, IL, 60611, USA.
authors: Allen S
authors: AS
authors: Anderson
authors: Division of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
authors: Nicholas D
authors: ND
authors: Soulakis
mesh_terms: D016507:Cardiology Service, Hospital / Q000458:organization & administration*; D004282:Documentation / Q000379:methods; D057286:Electronic Health Records; D000067495:Healthcare Failure Mode and Effect Analysis; D006801:Humans; D010351:Patient Discharge; D058996:Quality Improvement
keywords: cardiology hospital service; discharge planning; electronic health record; risk assessment; workflow