Literature DB >> 30815074

Quantifying and Visualizing Nursing Flowsheet Documentation Burden in Acute and Critical Care.

Sarah Collins1,2, Brittany Couture3, Min Jeoung Kang3,4, Patricia Dykes3,4, Kumiko Schnock3,4, Chris Knaplund2, Frank Chang3, Kenrick Cato2.   

Abstract

Documentation burden is a well-documented problem within healthcare, and improvement requires understanding of the scope and depth of the problem across domains. In this study we quantified documentation burden within EHR flowsheets, which are primarily used by nurses to document assessments and interventions. We found mean rates of 633-689 manual flowsheet data entries per 12-hour shift in the ICU and 631-875 manual flowsheet data entries per 12-hour shift in acute care, excluding device data. Automated streaming of device data only accounted for 5-20% of flowsheet data entries across our sample. Reported rates averaged to a nurse documenting 1 data point every 0.82-1.14 minutes, despite only a minimum data-set of required documentation. Increased automated device integration and novel approaches to decrease data capture burden (e.g., voice recognition), may increase nurses' available time for interpretation, annotation, and synthesis of patient data while also further advancing the richness of information within patient records.

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Year:  2018        PMID: 30815074      PMCID: PMC6371331     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  20 in total

1.  "Reading between the lines" of flow sheet data: nurses' optional documentation associated with cardiac arrest outcomes.

Authors:  Sarah A Collins; David K Vawdrey
Journal:  Appl Nurs Res       Date:  2011-11-12       Impact factor: 2.257

2.  Nursing staff work patterns in a residential aged care home: a time-motion study.

Authors:  Siyu Qian; Ping Yu; David Hailey
Journal:  Aust Health Rev       Date:  2016-11       Impact factor: 1.990

3.  The painful truth: The documentation burden of a trauma surgeon.

Authors:  Joseph F Golob; John J Como; Jeffrey A Claridge
Journal:  J Trauma Acute Care Surg       Date:  2016-05       Impact factor: 3.313

Review 4.  The impact of a Critical Care Information System (CCIS) on time spent charting and in direct patient care by staff in the ICU: a review of the literature.

Authors:  Rebecca L Mador; Nicola T Shaw
Journal:  Int J Med Inform       Date:  2009-03-03       Impact factor: 4.046

5.  Understanding the work of intensive care nurses: a time and motion study.

Authors:  M Abbey; W Chaboyer; M Mitchell
Journal:  Aust Crit Care       Date:  2011-09-21       Impact factor: 2.737

6.  Report of the AMIA EHR-2020 Task Force on the status and future direction of EHRs.

Authors:  Thomas H Payne; Sarah Corley; Theresa A Cullen; Tejal K Gandhi; Linda Harrington; Gilad J Kuperman; John E Mattison; David P McCallie; Clement J McDonald; Paul C Tang; William M Tierney; Charlotte Weaver; Charlene R Weir; Michael H Zaroukian
Journal:  J Am Med Inform Assoc       Date:  2015-05-28       Impact factor: 4.497

7.  The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.

Authors:  Caitlin M Cusack; George Hripcsak; Meryl Bloomrosen; S Trent Rosenbloom; Charlotte A Weaver; Adam Wright; David K Vawdrey; Jim Walker; Lena Mamykina
Journal:  J Am Med Inform Assoc       Date:  2012-09-08       Impact factor: 4.497

8.  Examining Time Use of Dutch Nursing Staff in Long-Term Institutional Care: A Time-Motion Study.

Authors:  Astrid Tuinman; Mathieu H G de Greef; Wim P Krijnen; Roos M B Nieweg; Petrie F Roodbol
Journal:  J Am Med Dir Assoc       Date:  2015-10-09       Impact factor: 4.669

9.  Time-motion analysis of clinical nursing documentation during implementation of an electronic operating room management system for ophthalmic surgery.

Authors:  Sarah Read-Brown; David S Sanders; Anna S Brown; Thomas R Yackel; Dongseok Choi; Daniel C Tu; Michael F Chiang
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

10.  Nurse workload in implementing a tight glycaemic control protocol in a UK hospital: a pilot time-in-motion study.

Authors:  Juliane Gartemann; Elizabeth Caffrey; Nandini Hadker; Sheila Crean; Gary M Creed; Carsten Rausch
Journal:  Nurs Crit Care       Date:  2012-05-02       Impact factor: 2.325

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  14 in total

1.  Defining an Essential Clinical Dataset for Admission Patient History to Reduce Nursing Documentation Burden.

Authors:  Darinda E Sutton; Jennifer R Fogel; April S Giard; Lisa A Gulker; Catherine H Ivory; Amy M Rosa
Journal:  Appl Clin Inform       Date:  2020-07-08       Impact factor: 2.342

2.  Implementing Best Practices to Redesign Workflow and Optimize Nursing Documentation in the Electronic Health Record.

Authors:  Mary R Lindsay; Kay Lytle
Journal:  Appl Clin Inform       Date:  2022-06-03       Impact factor: 2.762

3.  Documentation Burden in Nursing and Its Role in Clinician Burnout Syndrome.

Authors:  Emily Gesner; Patricia C Dykes; Lingling Zhang; Priscilla Gazarian
Journal:  Appl Clin Inform       Date:  2022-10-19       Impact factor: 2.762

4.  Alert burden in pediatric hospitals: a cross-sectional analysis of six academic pediatric health systems using novel metrics.

Authors:  Evan W Orenstein; Swaminathan Kandaswamy; Naveen Muthu; Juan D Chaparro; Philip A Hagedorn; Adam C Dziorny; Adam Moses; Sean Hernandez; Amina Khan; Hannah B Huth; Jonathan M Beus; Eric S Kirkendall
Journal:  J Am Med Inform Assoc       Date:  2021-11-25       Impact factor: 7.942

5.  25 × 5 Symposium to Reduce Documentation Burden: Report-out and Call for Action.

Authors:  Mollie Hobensack; Deborah R Levy; Kenrick Cato; Don E Detmer; Kevin B Johnson; Jeffrey Williamson; Judy Murphy; Amanda Moy; Jennifer Withall; Rachel Lee; Sarah Collins Rossetti; Samuel Trent Rosenbloom
Journal:  Appl Clin Inform       Date:  2022-05-11       Impact factor: 2.762

6.  Nursing Documentation Variation Across Different Medical Facilities Within an Integrated Healthcare System.

Authors:  Min-Jeoung Kang; Sarah Collins Rossetti; Christopher Knaplund; Frank Y Chang; Kumiko O Schnock; Kimberly Whalen; Emily J Gesner; Jose P Garcia; Kenrick D Cato; Patricia C Dykes
Journal:  Comput Inform Nurs       Date:  2021-05-03       Impact factor: 1.985

7.  Let Sleeping Patients Lie, avoiding unnecessary overnight vitals monitoring using a clinically based deep-learning model.

Authors:  Viktor Tóth; Marsha Meytlis; Douglas P Barnaby; Kevin R Bock; Michael I Oppenheim; Yousef Al-Abed; Thomas McGinn; Karina W Davidson; Lance B Becker; Jamie S Hirsch; Theodoros P Zanos
Journal:  NPJ Digit Med       Date:  2020-11-13

8.  Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative.

Authors:  Charlene Esteban Ronquillo; Laura-Maria Peltonen; Lisiane Pruinelli; Charlene H Chu; Suzanne Bakken; Ana Beduschi; Kenrick Cato; Nicholas Hardiker; Alain Junger; Martin Michalowski; Rune Nyrup; Samira Rahimi; Donald Nigel Reed; Tapio Salakoski; Sanna Salanterä; Nancy Walton; Patrick Weber; Thomas Wiegand; Maxim Topaz
Journal:  J Adv Nurs       Date:  2021-05-18       Impact factor: 3.057

9.  Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey.

Authors:  Oliver Maassen; Sebastian Fritsch; Julia Gantner; Saskia Deffge; Julian Kunze; Gernot Marx; Johannes Bickenbach
Journal:  J Med Internet Res       Date:  2020-12-21       Impact factor: 5.428

10.  Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework.

Authors:  Sarah Collins Rossetti; Chris Knaplund; Dave Albers; Patricia C Dykes; Min Jeoung Kang; Tom Z Korach; Li Zhou; Kumiko Schnock; Jose Garcia; Jessica Schwartz; Li-Heng Fu; Jeffrey G Klann; Graham Lowenthal; Kenrick Cato
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

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