Developing and validating a prediction model for frequent attenders at a Swedish emergency department using an electronic medical record system, a retrospective observational study

Background: Frequent attenders (FA) account for a significant number of emergency department (ED) visits but to date there is no prediction model to identify patients at risk of becoming a FA. The aim of this research was to identify and describe FA using readily available data provided by electronic medical records and create a prediction model to identify future FA Method: Adults ≥18 years that visited the ED during 2015 were included. Patients with ≥4 visits were defined as FA, and patients with ≤3 visits were placed in the control group. Numerous variables were analyzed and differences between the groups compared. Logistic regression analysis was used to determine the predictor variables and the model validated using Receiver Operating Characteristic (ROC) on an independent sample. Results: 6635 patients were included in developing the model: 15.3 (n=1012) were classified as FA and 15.4 (n=1011) as the control group. Variables associated with at risk of becoming a FA were the following: age above 60 years OR 1.52 [CI 1.27 – 1.82], ED arrival by ambulance or helicopter OR 1.31 [CI 1.08 – 1.58], sheltered living OR 3.82 [CI 2.37 – 6.17], previous contact with psychiatric department OR 1.52 [CI 1.23 – 1.89], 10 outpatient care visits or more OR 4.81 [CI 3.81 – 6.08] and 10 outpatient care physician visits or more OR 3.94 [CI 3.25 – 4.78]. The ROC in the validation set had an area under the curve of 0.85 [CI 0.84 – 0.86]. Conclusion: Data from electronic medical record software can be used to create and validate the risk of becoming a FA in the ED. We found that age over 60 years, ED arrival by ambulance or helicopter, sheltered living, previous contact with psychiatric departments, and frequent visits at outpatient care together predict the risk of becoming a FA.

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Identifying COPD patients at risk for hospitalizations and Emergency Department Visits using the Electronic Medical Record

10.1183/1393003.congress-2017.pa3641 ◽

2017 ◽

Author(s):

Denitza Blagev ◽

Dave Collingridge ◽

Susan Rea

Keyword(s):

At Risk ◽

Emergency Department ◽

Medical Record ◽

Electronic Medical Record ◽

Emergency Department Visits ◽

Copd Patients ◽

Patients At Risk

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Doctors documenting: an ethnographic and informatics approach to understanding attending physician documentation in the pediatric emergency department

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocaa252 ◽

2020 ◽

Author(s):

Sarah D Fouquet ◽

Laura Fitzmaurice ◽

Y Raymond Chan ◽

Evan M Palmer

Keyword(s):

Emergency Department ◽

Mixed Methods ◽

Medical Record ◽

Electronic Medical Record ◽

Pediatric Emergency ◽

Second Phase ◽

Pediatric Emergency Department ◽

Mixed Methods Approach ◽

Time And Motion ◽

Attending Physician

Abstract Objective The pediatric emergency department is a highly complex and evolving environment. Despite the fact that physicians spend a majority of their time on documentation, little research has examined the role of documentation in provider workflow. The aim of this study is to examine the task of attending physician documentation workflow using a mixed-methods approach including focused ethnography, informatics, and the Systems Engineering Initiative for Patient Safety (SEIPS) model as a theoretical framework. Materials and Methods In a 2-part study, we conducted a hierarchical task analysis of patient flow, followed by a survey of documenting ED providers. The second phase of the study included focused ethnographic observations of ED attendings which included measuring interruptions, time and motion, documentation locations, and qualitative field notes. This was followed by analysis of documentation data from the electronic medical record system. Results Overall attending physicians reported low ratings of documentation satisfaction; satisfaction after each shift was associated with busyness and resident completion. Documentation occurred primarily in the provider workrooms, however strategies such as bedside documentation, dictation, and multitasking with residents were observed. Residents interrupted attendings more often but also completed more documentation actions in the electronic medical record. Discussion Our findings demonstrate that complex work processes such as documentation, cannot be measured with 1 single data point or statistical analysis but rather a combination of data gathered from observations, surveys, comments, and thematic analyses. Conclusion Utilizing a sociotechnical systems framework and a mixed-methods approach, this study provides a holistic picture of documentation workflow. This approach provides a valuable foundation not only for researchers approaching complex healthcare systems but also for hospitals who are considering implementing large health information technology projects.

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