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Using Electronic Medical Record Systems for Admission Decisions in Emergency Departments: Examining the Crowdedness Effect

Journal of Medical Systems volume 36, pages 3795–3803 (2012)Cite this article

Abstract

Many medical organizations have deployed electronic medical record (EMR) information systems (IS) to improve medical decision-making and increase efficiency. Despite their advantages, however, EMR IS may make less of a contribution in the stressful environment of an emergency department (ED) that operates under tight time constraints. The high level of crowdedness in the EDs itself can cause physicians to make medical decisions resulting in more unnecessary admissions and fewer necessary admissions. Thus this study evaluated the contribution of an EMR IS to physicians by investigating whether EMR IS leads to improved medical outcomes in points of care in EDs under different levels of crowdedness. For this purpose a track log-file analysis of a database containing 3.2 million ED referrals in seven main hospitals in Israel (the whole population in these hospitals) was conducted. The findings suggest that viewing medical history via the EMR IS leads to better admission decisions, and reduces the number of possibly avoidable single-day admissions. Furthermore, although the ED can be very stressful especially on crowded days, physicians used EMR IS more on crowded days than on non-crowded days. These results have implications as regards the viability of EMR IS in complex, fast-paced environments.

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Notes

  1. We chose the average as the threshold value for determining the crowdedness level over other alternative threshold candidates such as the median (consistent with other studies mentioned above). However, we tested the same regressions with a median threshold and found very similar results. We also tested several of other levels above the average (such as one and two standard deviations) and obtained very similar results.

References

  1. Spaite, D. W., Bartholomeaux, F., Guisto, J., Lindberg, E., Hull, B., Eyherabide, A., Lanyon, S., Criss, E. A., Valenzuela, T. D., Conroy, C., Rapid process redesign in a university-based emergency department: decreasing waiting time intervals and improving patient satisfaction. Annals of emergency medicine 39:168–177, 2002.

    Article  Google Scholar 

  2. Schneider, S., Zwemer, F., Doniger, A., Dick, R., Czapranski, T., Davis, E., A decade of emergency department overcrowding. Academic Emergency Medicine 8:1044–1050, 2001.

    Article  Google Scholar 

  3. McCabe, J. B., Emergency department overcrowding: a national crisis. Academic Medicine 76:672–674, 2001.

    Article  Google Scholar 

  4. Bair, A., Song, W., Chen, Y. C., Morris, B., The impact of inpatient boarding on ED efficiency: A discrete-event simulation study. Journal of Medical Systems 34:919–929, 2010.

    Article  Google Scholar 

  5. Hwang, U., Concato, J. Care in the emergency department: how crowded is overcrowded?. Academic Emergency Medicine 11:1097–1101, 2004.

    Article  Google Scholar 

  6. Gillies, A. C., Howard, J., Information as change agent or barrier in health care reform?. International Journal of Healthcare Information Systems and Informatics 6:19–35, 2011.

    Article  Google Scholar 

  7. Leu, J. D., Huang, Y. T., An application of business process method to the clinical efficiency of hospital. Journal of Medical Systems 35:409–421, 2011.

    Article  Google Scholar 

  8. Cooke, M. W., Higgins, J., Kidd, P., Use of emergency observation and assessment wards: a systematic literature review. British Medical Journal 20:138, 2003.

    Google Scholar 

  9. Hripcsak, G., Sengupta, S., Wilcox, A., Green, R., Emergency department access to a longitudinal medical record. Journal of the American Medical Association 14:235–238, 2007.

    Google Scholar 

  10. Walker, J., Pan, E., Johnston, D., Milstein, J. D., Bates, W. D., Middleton, B., The value of health care information exchange and interoperability. Health Affairs 24:10–18, 2005.

    Article  Google Scholar 

  11. Goldman, D., Crum, D., Bromberg, R., Rogovik, A., Langer, J., Analgesia administration for acute abdominal pain in the pediatric emergency department. Pediatric Emergency Care 22:18–21, 2006.

    Article  Google Scholar 

  12. Patel, V. L., Cohen, T., Murarka, T., Olsen, J., Kagita, S., Myneni, S., Buchman, T., Ghaemmaghami, Recovery at the edge of error: Debunking the myth of the infallible expert. Journal of Biomedical Informatics 44:413–424, 2011.

    Article  Google Scholar 

  13. Junankar, P., Mital, D., Haque, S., Srinivasan, S., A clinical decision support system for managing flexor tendon injuries. International Journal of Medical Engineering and Informatics 1:275–289, 2009.

    Article  Google Scholar 

  14. Sox, C., Blatt, A., Higgins, C., Medical decision making. Philadelphia: American College of Physicians, 2007.

    Google Scholar 

  15. Redelmeier, A., Shafir, E., Medical decision making in situations that offer multiple alternatives. JAMA 273:302–305, 1995.

    Article  Google Scholar 

  16. Frisse, M. E., Holmes, R. L., Estimated financial savings associated with health information exchange and ambulatory care referral. Journal of Biomedical Informatics 40:S27–S32, 2007.

    Article  Google Scholar 

  17. Connelly, D. P., Park, Y. T., Du, J., Ampornpunt, N. T., Gordon, B. D., Bershow, B. A., Gensinger, R. A., Shrift, M., Routhe, D. T., Speedie, S. M. The impact of electronic health records on care of heart failure patients in the emergency room. Journal of the American Medical Association, doi:10.1136/amiajnl-2011-000271, 2011.

  18. Hoeksema, L. J., Bazzy-Asaad, A., Lomotan, E. A., Edmonds, D. E., Ramírez-Garnica, G., Shiffman, R. N., Horwitz, L. I., Accuracy of a computerized clinical decision-support system for asthma assessment and management. Journal of the American Medical Association 18:243–250, 2011.

    Google Scholar 

  19. Shabtai, I., Leshno, M., Blondheimc, O., Kornbluth, J., The value of Information for Decision-Making in the Healthcare Environment. Medical and Care Compunetics 4:91–97, 2007.

    Google Scholar 

  20. Richardson, D., No relationship between emergency department activity and triage categorization. Academic Emergency Medicine 5:141–145, 1998.

    Article  Google Scholar 

  21. Denman, J. M., Bingham, P., George, S., A confidential enquiry into emergency hospital admissions on the Isle of Wight, UK. British Medical Journal 51:386–390, 1997.

    Google Scholar 

  22. Vest, J. R., Health information exchange and healthcare utilization. Journal of Medical Systems 33:223–231, 2009.

    Article  Google Scholar 

  23. Kleinbaum, D. G., Klein, M., Pryor, E. R., Logistic regression: A self-learning text, Springer New York, Second Edition, 2002.

    MATH  Google Scholar 

  24. Cabrera, A. F., Logistic regression analysis in higher education: An applied perspective. Higher education: Handbook of theory and research 10:225–256, 1994.

  25. Kooperberg, C., Petitti, D. B., Using logistic regression to estimate the adjusted attributable risk of low birth weight in an unmatched case–control study. Epidemiology 2:363–366, 1991.

    Article  Google Scholar 

  26. Liao, D., Arnett, D. K., Tyroler, H. A., Riley, W. A., Chambless, L. E., Szklo, M., Heiss, G., Arterial stiffness and the development of hypertension. The ARIC study, American Heart Association 34:201–206, 1999.

    Google Scholar 

  27. Ford, E. S., Does exercise reduce inflammation? Physical activity and C-reactive protein among US adults. Epidemiology 13:561–568, 2002.

    Article  Google Scholar 

  28. Baker, D. W., Parker, R. M., Williams, M. V., Clark, W. S., Health literacy and the risk of hospital admission. Journal of General Internal Medicine 13:791–798, 1998.

    Article  Google Scholar 

  29. Fonarow, G. C., Adams, K. F., Abraham, W. T., Yancy, C. W., Boscardin, W. J., Risk stratification for in-hospital mortality in acutely decompensated heart failure classification and regression tree analysis. Journal of the American Medical Association 293:572–580, 2005.

    Article  Google Scholar 

  30. Michalowski, W., Kersten, M., Wilk, S., Slowinski, R., Designing man–machine interactions for mobile clinical systems: MET triage support using Palm handhelds. European Journal of Operational research 177:1409–1417, 2007.

    MATH  Article  Google Scholar 

  31. Hersh, R., Hickam, H., How Well Do Physicians Use Electronic Information Retrieval Systems? A Framework for Investigation and Systematic Review. Journal of the American Medical Association 280:1347–1352, 1998.

    Article  Google Scholar 

  32. Wyatt, J., Spiegelhalter, D., Evaluating medical expert systems: what to test and how?. Informatics for Health and Social Care 15:205–217, 1990.

    Article  Google Scholar 

  33. Reeder, B., Demiris, G., Building the PHARAOH framework using scenario based design: a set of pandemic decision-making scenarios for continuity of operations in a large municipal public health agency. Journal of Medical Systems 34:735–739, 2010.

    Article  Google Scholar 

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Author information

Affiliations

  1. Ono Academic College, Kiryat Ono, 55451, Israel

    Ofir Ben-Assuli

  2. Tel-Aviv University, Tel-Aviv, 69978, Israel

    Moshe Leshno

  3. College of Management Academic Studies, Rishon LeZion, 75490, Israel

    Itamar Shabtai

Authors
  1. Ofir Ben-Assuli
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  2. Moshe Leshno
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  3. Itamar Shabtai
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Corresponding author

Correspondence to Ofir Ben-Assuli.

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Ben-Assuli, O., Leshno, M. & Shabtai, I. Using Electronic Medical Record Systems for Admission Decisions in Emergency Departments: Examining the Crowdedness Effect. J Med Syst 36, 3795–3803 (2012). https://doi.org/10.1007/s10916-012-9852-0

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  • DOI: https://doi.org/10.1007/s10916-012-9852-0

Keywords

  • Crowdedness in emergency medicine
  • Electronic medical record
  • Medical informatics
  • Medical decision-making