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Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting.

Publication ,  Journal Article
Lopez, KD; Gerling, GJ; Cary, MP; Kanak, MF
Published in: Journal of the American Medical Informatics Association : JAMIA
August 2010

OBJECTIVE: To identify factors in the nursing work domain that contribute to the problem of inpatient falls, aside from patient risk, using cognitive work analysis. METHODS: A mix of qualitative and quantitative methods were used to identify work constraints imposed on nurses, which may underlie patient falls. METHODS: Data collection was done on a neurology unit staffed by 27 registered nurses and utilized field observations, focus groups, time-motion studies and written surveys (AHRQ Hospital Survey on Patient Culture, NASA-TLX, and custom Nursing Knowledge of Fall Prevention Subscale). RESULTS: Four major constraints were identified that inhibit nurses' ability to prevent patient falls. All constraints relate to work processes and the physical work environment, opposed to safety culture or nursing knowledge, as currently emphasized. The constraints were: cognitive 'head data', temporal workload, inconsistencies in written and verbal transfer of patient data, and limitations in the physical environment. To deal with these constraints, the nurses tend to employ four workarounds: written and mental chunking schemas, bed alarms, informal querying of the previous care nurse, and informal video and audio surveillance. These workarounds reflect systemic design flaws and may only be minimally effective in decreasing risk to patients. CONCLUSIONS: Cognitive engineering techniques helped identify seemingly hidden constraints in the work domain that impact the problem of patient falls. System redesign strategies aimed at improving work processes and environmental limitations hold promise for decreasing the incidence of falls in inpatient nursing units.

Duke Scholars

Published In

Journal of the American Medical Informatics Association : JAMIA

DOI

ISSN

1527-974X

Publication Date

August 2010

Volume

17

Issue

3

Start / End Page

313 / 321

Related Subject Headings

  • United States
  • Time and Motion Studies
  • Task Performance and Analysis
  • Safety Management
  • Nursing Staff, Hospital
  • Nursing Care
  • Middle Aged
  • Medical Informatics
  • Inpatients
  • Humans
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Lopez, K. D., Gerling, G. J., Cary, M. P., & Kanak, M. F. (2010). Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting. Journal of the American Medical Informatics Association : JAMIA, 17(3), 313–321. https://doi.org/10.1136/jamia.2009.000422
Lopez, K. D., G. J. Gerling, M. P. Cary, and M. F. Kanak. “Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting.Journal of the American Medical Informatics Association : JAMIA 17, no. 3 (August 2010): 313–21. https://doi.org/10.1136/jamia.2009.000422.
Lopez KD, Gerling GJ, Cary MP, Kanak MF. Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting. Journal of the American Medical Informatics Association : JAMIA. 2010 Aug;17(3):313–21.
Lopez, K. D., et al. “Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting.Journal of the American Medical Informatics Association : JAMIA, vol. 17, no. 3, Aug. 2010, pp. 313–21. Manual, doi:10.1136/jamia.2009.000422.
Lopez KD, Gerling GJ, Cary MP, Kanak MF. Cognitive work analysis to evaluate the problem of patient falls in an inpatient setting. Journal of the American Medical Informatics Association : JAMIA. 2010 Aug;17(3):313–321.
Journal cover image

Published In

Journal of the American Medical Informatics Association : JAMIA

DOI

ISSN

1527-974X

Publication Date

August 2010

Volume

17

Issue

3

Start / End Page

313 / 321

Related Subject Headings

  • United States
  • Time and Motion Studies
  • Task Performance and Analysis
  • Safety Management
  • Nursing Staff, Hospital
  • Nursing Care
  • Middle Aged
  • Medical Informatics
  • Inpatients
  • Humans