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Effect of the Implementation of a New Electronic Health Record System on Surgical Case Turnover Time

  • Joseph McDowell
  • Albert Wu
  • Jesse M. Ehrenfeld
  • Richard D. UrmanEmail author
Mobile & Wireless Health
Part of the following topical collections:
  1. Mobile & Wireless Health

Abstract

Many health care providers, hospitals, and hospital systems have adopted new electronic health records (EHR) to streamline patient care and comply with government mandates. Commercial EHR vendors advertise improved efficiency, but few studies have been performed to validate these claims. Therefore, this study was performed to evaluate the effect of deploying a new EHR system on operating room efficiency and surgical case turnover time (TOT) at our institution. Data on TOT were collected after implementation of a new EHR (Epic) from June 2015 to May 2016, which replaced a legacy system of both paper and electronic records. These TOTs were compared to data from the same months in the preceding year. Mean TOT and standard deviations were calculated. The two-sample t-test was used to compare means by month and the F-test was used to compare standard deviations. There was a significant increase in TOT (63.0 vs. 53.0 min, p < 0.001) in the first month after implementation. This improved by the second month (59.0 vs. 53.0 min, p < 0.001), but the relative increase persisted until the end of the fifth month after which it remained around the pre-implementation baseline until the end of the study. The standard deviation significantly decreased after the fourth month post-implementation and persisted throughout the studied period. We found that implementation of an EHR led to a significant decrease in efficiency that persisted for five months. While EHRs have the potential to improve hospital workflow, caution is advised in the case of operating room implementation. While the mean TOT did not improve beyond the pre-implementation baseline, the standard deviation was significantly improved after the first four months.

Keywords

Electronic health record Epic Operating room Efficiency Turnover time Implementation Anesthesia 

Notes

Compliance with Ethical Standards

Funding

No funding was received for this study.

Conflict of Interest

The authors declare that they have no conflict of interest.

Statement of Human Rights

For this type of study formal consent is not required.

References

  1. 1.
    Blumenthal, D., and Tavenner, M., The “meaningful use” regulation for electronic health records. N. Engl. J. Med., 2010. doi: 10.1056/NEJMp1006114.Google Scholar
  2. 2.
    Electronic Health Records (EHR) Incentive Programs. Centers for Medicare and Medicaid Services. Available at: https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html?redirect=/EHRIncentivePrograms/. Accessed 5 November 2016.
  3. 3.
    Fowles, J. B., Kind, E. A., Awwad, S., Weiner, J. P., Chan, K. S., Coon, P. J. et al., Performance measures using electronic health records: five case studies. The Commonwealth Fund 46, 2008. Available at: http://www.commonwealthfund.org/publications/fund-reports/2008/may/performance-measures-using-electronic-health-records--five-case-studies. Accessed 19 January 2017.
  4. 4.
    Elson, R.B., and Connelly, D.P., Computerized patient records in primary care: their role in mediating guideline-driven physician behavior change. Arch. Fam. Med. 4:698–705, 1995.CrossRefPubMedGoogle Scholar
  5. 5.
    Hunt, D.L., Haynes, R.B., Hanna, S.E., and Smith, K., Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 280:1339–1346, 1998.CrossRefPubMedGoogle Scholar
  6. 6.
    O’Connor, P.J., Crain, A.L., Rush, W.A., Sperl-Hillen, J.M., Gutenkauf, J.J., and Duncan, J.E., Impact of an electronic medical record on diabetes quality of care. Ann. Fam. Med. 3:300–306, 2005.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Feldstein, A., Elmer, P.J., Smith, D.H., Herson, M., Orwoll, E., Chen, C., et al., Electronic medical record reminder improves osteoporosis management after a fracture: a randomized, controlled trial. J. Am. Geriatr. Soc. 54:450–457, 2006.CrossRefPubMedGoogle Scholar
  8. 8.
    Kullar, R., Goff, D.A., Schulz, L.T., Fox, B.C., and Rose, W.E., The “epic” challenge of optimizing antimicrobial stewardship: the role of electronic medical records and technology. Clin. Infect. Dis. 57:1005–1013, 2013.CrossRefPubMedGoogle Scholar
  9. 9.
    Hillestad, R., Bigelow, J., Bower, A., Girosi, F., Meili, R., Scoville, R., et al., Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Aff. 24:1103–1117, 2005.CrossRefGoogle Scholar
  10. 10.
    Wang, S.J., Middleton, B., Prosser, L.A., Bardon, C.G., Spurr, C.D., Carchidi, P.J., et al., A cost-benefit analysis of electronic medical records in primary care. Am. J. Med. 114:397–403, 2003.CrossRefPubMedGoogle Scholar
  11. 11.
    Hartswood, M., Procter, R., Rouncefield, M., and Slack, R., Making a case in medical work: implications for the electronic medical record. Comput. Supported Coop. Work. 12:241–266, 2003.CrossRefGoogle Scholar
  12. 12.
    Crowson, M.G., Vail, C., and Eapen, R.J., Influence of electronic medical record implementation on provider retirement at a major academic medical Centre. J. Eval. Clin. Pract. 22:222–226, 2016.CrossRefPubMedGoogle Scholar
  13. 13.
    Forster, M., Bailey, C., Brinkhof, M.W.G., Graber, C., Boulle, A., Spohr, M., et al., Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings. Bull. World Health Organ. 86:939–947, 2008.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Walker, J., Pan, E., Johnston, D., Adler-Milstein, J., Bates, D.W., and Middleton, B., The value of health care information exchange and interoperability. Health Aff. (Millwood)., 2005. doi: 10.1377/hlthaff.w5.10.Google Scholar
  15. 15.
    Gordon, T., Paul, S., Lyles, A., and Fountain, J., Surgical unit time utilization review: resource utilization and management implications. J. Med. Syst. 12:169–179, 1988.CrossRefPubMedGoogle Scholar
  16. 16.
    Eijkemans, M.J.C., van Houdenhoven, M., Nguyen, T., Boersma, E., Steyerberg, E.W., and Kazemier, G., Predicting the unpredictable. Anesthesiology. 112:41–49, 2010.CrossRefPubMedGoogle Scholar
  17. 17.
    Peltokorpi, A., How do strategic decisions and operative practices affect operating room productivity? Health Care Manag. Sci. 14:370–382, 2011.CrossRefPubMedGoogle Scholar
  18. 18.
    Wright, J.G., Roche, A., and Khoury, A.E., Improving on time surgical starts in an operating room. Can. J. Surg. 53(3):167–170, 2010.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Donham, R.T., Defining measurable OR-PR scheduling, efficiency, and utilization data elements: the association of anesthesia clinical directors procedural times glossary. Int. Anesthesiol. Clin. 36:15, 1998.CrossRefPubMedGoogle Scholar
  20. 20.
    Donham, R.T., Mazzei, W.J., and Jones, R.L., Association of anesthesia clinical directors’ procedural times glossary: glossary of times used for scheduling and monitoring of diagnostic and therapeutic procedures. Am. J. Anesthesiol. 23:3–12, 1996.Google Scholar
  21. 21.
    Wong, J., Khu, K.J., Kaderali, Z., and Bernstein, M., Delays in the operating room: signs of an imperfect system. Can. J. Surg. 53:189–195, 2010.PubMedPubMedCentralGoogle Scholar
  22. 22.
    Mazzei, W.J., Operating room start times and turnover times in a university hospital. J. Clin. Anesth. 6:405–408, 1994.CrossRefPubMedGoogle Scholar
  23. 23.
    Harders, M., Malangoni, M.A., Weight, S., and Sidhu, T., Improving operating room efficiency through process redesign. Surgery. 140:509–516, 2006.CrossRefPubMedGoogle Scholar
  24. 24.
    Vitez, T.S., and Macario, A., Setting performance standards for an anesthesia department. J. Clin. Anesth. 10:166–175, 1998.CrossRefPubMedGoogle Scholar
  25. 25.
    Wu, A., Kodali, B. S., Flanagan, H., Urman, R. D., Introduction of a new electronic medical system has mixed effects on first surgical case efficiency metrics. J. Clin. Monit. Comput. 2016.Google Scholar
  26. 26.
    Wu, A., Brovman, E.Y., Whang, E.E., Ehrenfeld, J.M., and Urman, R.D., The impact of overestimations of surgical control times across multiple specialties on medical systems. J. Med. Syst. 40:95, 2016.CrossRefPubMedGoogle Scholar
  27. 27.
    Kodali, B.S., Kim, K.D., Flanagan, H., Ehrenfeld, J.M., and Urman, R.D., Variability of subspecialty-specific anesthesia-controlled times at two academic institutions. J. Med. Syst. 38:11, 2014.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Joseph McDowell
    • 1
  • Albert Wu
    • 1
  • Jesse M. Ehrenfeld
    • 2
  • Richard D. Urman
    • 1
    • 3
    Email author
  1. 1.Department of Anesthesiology, Perioperative and Pain MedicineHarvard Medical School, Brigham and Women’s HospitalBostonUSA
  2. 2.Department of AnesthesiologyVanderbilt University Medical CenterNashvilleUSA
  3. 3.Center for Perioperative ResearchBrigham and Women’s HospitalBostonUSA

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