# Journal of the American Medical Informatics Association

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## Improving prediction of fall risk among nursing home residents using electronic medical records

Allison Marier, Lauren E.W. Olsho, William Rhodes, William D. Spector
ocv061 First published online: 22 June 2015

## Abstract

Objective Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls.

Methods The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data.

Results In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification.

Conclusions Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables.

• Electronic medical records
• minimum data set 3.0
• nursing home falls
• prediction
• meaningful use

## CONCLUSIONS

We have demonstrated that use of data from an EMR system can materially improve ability to identify those individuals at highest risk for falls. However, standard EMR systems currently provide no easy way to synthesize and summarize information on changing risk factors recorded in disparate parts of the EMR to support clinical decision-making. Recent work by the Agency for Healthcare Research and Quality has focused on developing specifications for easy-to-use reports for staff use, synthesized from EMR data on resident risk factors for falls and other preventable adverse events, including pressure ulcers and avoidable hospitalizations.28 ,30 Further development of such applications, focused both on falls and on other avoidable adverse events for which risk factors can be readily identified, should be a key priority as nursing homes expand their adoption of EMRs in coming years.

## FUNDING

This study was funded by the Agency for Healthcare Research & Quality (AHRQ), Department of Health & Human Services (DHHS), under contract # HHSA290201000031I. The content of this article is solely the responsibility of the authors and does not represent the official views or recommendations of AHRQ or DHHS.

## COMPETING INTERESTS

The authors have no competing interests to declare.

## AUTHOR CONTRIBUTIONS

Contributors L.O. and W.S. were instrumental in obtaining the necessary data for this study. A.M., L.O., and W.E. developed the study idea; W.S. was extensively involved with technical specifications. A.M. led the technical analyses with substantial input from W.R. and L.O. A.M., L.O., and W.R. wrote the first manuscript draft, all authors reviewed manuscript drafts. A.M. and L.O. responded to referee comments.

## SUPPLEMENTARY MATERIAL

Supplementary material is available online at http://jamia.oxford journals.org/.

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