From a paper-based transmission of discharge summaries to electronic communication in health care regions

Schabetsberger, Thomas; Ammenwerth, Elske; Andreatta, Stefan; Gratl, Gordon; Haux, Reinhold; Lechleitner, Georg; Schindelwig, Klaus; Stark, Christian; Vogl, Raimund; Wilhelmy, Immanuel; Wozak, Florian

doi:10.1016/j.ijmedinf.2005.07.018

Cited by 74 publications

(55 citation statements)

References 11 publications

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Section: Discussionmentioning

confidence: 97%

“…Specifically, previous research has shown that electronic discharge instructions lead to more thorough clinician documentation, decreased documentation errors, and increased workflow efficiency, which increases the quality of discharge instructions. [24,32,33] In contrast, Callen and colleagues found no significant difference in the quality of electronic and handwritten discharge instructions [34].The electronic discharge module's use of required fields and automated electronic data entry methods helps explain the observed increase in discharge instruction completeness, particularly for documentation of major procedures and tests performed, which had the largest improvement and was the most important contributor to the overall increased OP-19 compliance. The electronic discharge instructions module used a standardized template comprised of a combination of required free-form text fields and check boxes [35][36][37][38].…”

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confidence: 99%

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Information Technology Improves Emergency Department Patient Discharge Instructions Completeness and Performance on a National Quality Measure

Bell¹,

Takhar²,

Beloff

et al. 2013

Appl Clin Inform

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KeywordsComputerized medical records systems, emergency care information systems, patient discharge, quality improvement, health care reform SummaryObjectives: To compare the completeness of Emergency Department (ED) discharge instructions before and after introduction of an electronic discharge instructions module by scoring compliance with the Centers for Medicare and Medicaid Services (CMS) Outpatient Measure 19 . Methods: We performed a quasi-experimental study examining the impact of an electronic discharge instructions module in an academic ED. Three hundred patients discharged home from the ED were randomly selected from two time intervals: 150 patients three months before and 150 patients three to five months after implementation of the new electronic module. The discharge instructions for each patient were reviewed, and compliance for each individual OP-19 element as well as overall OP-19 compliance was scored per CMS specifications. Compliance rates as well as risk ratios (RR) and risk differences (RD) with 95% confidence intervals (CI) comparing the overall OP-19 scores and individual OP-19 element scores of the electronic and paper-based discharge instructions were calculated. Results: The electronic discharge instructions had 97.3% (146/150) overall OP-19 compliance, while the paper-based discharge instructions had overall compliance of 46.7% (70/150). Electronic discharge instructions were twice as likely to achieve overall OP-19 compliance compared to the paper-based format (RR: 2.09, 95% CI: 1.75 -2.48). The largest improvement was in documentation of major procedures and tests performed: only 60% of the paper-based discharge instructions satisfied this criterion, compared to 100% of the electronic discharge instructions (RD: 40.0%, 95% CI: 32.2% -47.8%). There was a modest difference in medication documentation with 92.7% for paper-based and 100% for electronic formats (RD: 7.3%, 95% CI: 3.2% -11.5%). There were no statistically significant differences in documentation of patient care instructions and diagnosis between paper-based and electronic formats. Conclusions: With careful design, information technology can improve the completeness of ED patient discharge instructions and performance on the OP-19 quality measure. Research ArticleEJ BackgroundThere were approximately 129.8 million visits to United States Emergency Departments (ED) in 2010 and roughly 87 percent of these visits resulted in patient discharge to a home setting following medical work-up [1]. Discharged ED patients are provided with discharge instructions before leaving the ED that describe individualized self-care responsibilities and treatment plan instructions [2][3][4]. Additionally, ED discharge instructions should detail the diagnostic and therapeutic services performed during the ED clinical encounter [2,3]. Discharge instructions that lack important patient information have been linked to poor patient outcomes, inefficient resource utilization, and increased healthcare spending [5][6][7][8][9][10][11][12][13][14][15]. ...

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Section: Discussionmentioning

confidence: 97%

mentioning

confidence: 99%

Information Technology Improves Emergency Department Patient Discharge Instructions Completeness and Performance on a National Quality Measure

Bell¹,

Takhar²,

Beloff

et al. 2013

Appl Clin Inform

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“…The work is mostly accomplished based on named entity recognition and similarity computation, which not only enhance the accessibility and operability of existing structured and free-text data in EHR, but also improve the efficiency of clinical text writing and avoid transcription errors and information missing in some degree compared with the conventional writing mode [7].…”

Section: Discussionmentioning

confidence: 99%

An Intelligent Writing Assistant Module for Narrative Clinical Records Based on Named Entity Recognition and Similarity Computation

Zhou¹,

Li²

2018

Proceedings of Information Science and Cloud Computing — PoS(ISCC 2017)

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Inpatient medical records which contain clinical narrative information generated from medical procedures have rich content and unlimited expression capabilities. In this paper, we proposed a novel method to assist health practitioners to write narrative clinical texts through a more efficient and safer manner. The core technologies supporting this work are named entity recognition (NER) and similarity computation: the CRF-based NER in this work has a good performance whose F-score has reached 89.23%, and the LDA model and similarity test has reached a precision of 71.28%. After these fundamental work, we designed and developed an intelligent writing assistant module: at sentence level, we used a conditional random field (CRF) method to train a NER model. When doctors type in an entity, several input candidates will pop up for selection; at paragraph level, we used a Gibbs-LDA++ tool and named entities to characterize the topics and key entities of existing records. When doctors create a new clinical text, the patient's structured data will be used as input to match similar paragraphs. As doctors keep typing in, the matching paragraphs also might change dynamically according to the input content. ISCC2017

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“…7 In Illinois, slow transmission of discharge summaries to GPs resulted in preventable adverse events. 8 Several electronic discharge systems are used within the NHS; their ease of use and clinical effectiveness vary.…”

Section: Summariesmentioning

confidence: 99%

GP and Hospital Doctor Perspectives on the Hospital Patient Discharge Process

et al. 2011

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From a paper-based transmission of discharge summaries to electronic communication in health care regions

Cited by 74 publications

References 11 publications

Information Technology Improves Emergency Department Patient Discharge Instructions Completeness and Performance on a National Quality Measure

Information Technology Improves Emergency Department Patient Discharge Instructions Completeness and Performance on a National Quality Measure

An Intelligent Writing Assistant Module for Narrative Clinical Records Based on Named Entity Recognition and Similarity Computation

GP and Hospital Doctor Perspectives on the Hospital Patient Discharge Process

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