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AMIA Annual Symposium Proceedings logoLink to AMIA Annual Symposium Proceedings
. 2006;2006:900.

Compliance with Use of Automated Fall-Injury Risk Assessment in Three Clinical Information Systems

Leanne M Currie 1, Suzanne Bakken 1,2, Gina Bufe 3, Lourdes V Mellino 3
PMCID: PMC1839478  PMID: 17238519

Abstract

Fall and injury prevention is a high priority in the acute care setting. Automated methods to identify patients at risk for falling and sustaining injury can streamline care processes and facilitate patient fall and injury prevention. The following study reports on the implementation and initial results of an automated Fall-Injury Risk assessment instrument integrated into three clinical information systems. Compliance with use of the automated instrument increased from 43% to 78% on units that did not have complete electronic nursing documentation. Units in which the instrument was integrated into the daily shift assessment, had 99–100% compliance. Further analysis will explore association of compliance with fall and injury rates.

Background

Falls and related injuries are the most commonly reported adverse event in the acute care setting [1]. Assessment for fall risk is a Joint Commission on Accreditation of Healthcare Organizations National Patient Safety Goal (NPSG)[2], and fall prevention is quality indicator in the National Quality Forum’s (NQF) Safe Practices for Better Health Care[3]. The following study reports on compliance with the use of an automated Fall-Injury Risk Assessment instrument integrated into three different platforms across a large multi-site academic medical center.

Methodology

In 2004 we developed the NYPH Fall-Injury Risk Assessment Instrument. The instrument was pilot tested revealing an inverse relationship between compliance with instrument use and fall rates [4]. Once the automated instrument was implemented bedside audits were performed every 5 weeks on a 25% sample of patients in fifty-two nursing units at the three sites. Risk assessment instrument usage data were obtained from the clinical data repositories or for a small subset, from the paper based chart. Descriptive statistics were used to characterize compliance with the use of the instrument.

Results

Bedside audits revealed that baseline computer skills for nurses were varied at the three sites. The nurses at Site 1 had been using a clinical information system (CIS) for ten years, whereas the other two sites were preparing for the implementation of a new CIS. Initial compliance rates were 43% for units with paper-based documentation and a standalone automated instrument, but these increased to 69 and 78% by Quarter 2 (see Figure 3). All but one of the units (Site 3) opted to use the automated instrument.

Conclusion

Experience with using a CIS predicted initial usage of the instrument, but the standalone instrument use was increased over time. Use of the instrument in the daily nurses note, improved compliance with the use of the instrument. Further research to evaluate the association between compliance, nursing interventions and fall rates will be of interest.

Figure 1.

Figure 1

Percent Compliance with Instrument Use

Acknowledgements

This research was supported in part by the Center for Evidence Based Practice in the Underserved P20 NR007799 and the Columbia Alliance for Healthcare Management.

References

  • 1.Agostini J, Baker D, Bogardus S. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. The Agency for Healthcare Research and Quality; 2001. Prevention of Falls in Hospitalized and Institutionalized Older People. [Google Scholar]
  • 2.Joint Commission on the Accreditation of Hospitals. 2005. 2006 Critical Access Hospital and Hospital National Patient Safety Goals. [Google Scholar]
  • 3.National Quality Forum. Washington, DC: National Quality Forum; 2003. National Voluntary Consensus Standards for Hospital Care: An Initial Performance Measure Set. Electronic report. 2003. [Google Scholar]
  • 4.Currie LM, Mellino LV, Cimino JJ, Bakken S. Development and representation of a fall-injury risk assessment instrument in a clinical information system. Medinfo. 2004;11(Pt 1):721–5. [PubMed] [Google Scholar]

Articles from AMIA Annual Symposium Proceedings are provided here courtesy of American Medical Informatics Association

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