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Introduction of a new electronic medical record system has mixed effects on first surgical case efficiency metrics

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Abstract

To evaluate the effect of deploying a new electronic medical record (EMR) system on first case starts in the operating room. Data on first case start times were collected after implementation of a new EMR (Epic) from June 2015 to May 2016, which replaced a legacy system of both paper and electronic records. These were compared to data from the same months in the three proceeding years. First patient in room (FPIR) on time was true if the patient was in operating room before 7:35 AM (or 9:35 AM on Wednesdays) and first case on time start (FCOTS) was true if completion of anesthetic induction was less than 20 min after the patient entered the operating room (or 35 min for cardiac and neurosurgery). Times beyond these cutoffs were quantified as FPIR and FCOTS delays in minutes. Average delays were compared by month with two-sample t tests and 95 % confidence intervals. There was a significant increase in FPIR delays in the first month (11.07 vs. 3.47 min, p < 0.0001), which abated by the fifth month. Post-implementation FCOTS delays improved by the third month (4.53 vs. 7.10 min, p < 0.0001). Both results persisted throughout the study. First month FPIR delays were not limited to any one specialty. EMRs have the potential to improve hospital workflows, but are not without learning curves. FPIR and FCOTS delays return to baseline after a few months, and in the case of FCOTS, can improve beyond baseline.

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References

  1. Hsiao C-J, Hing E, Socey TC, Cai B. Electronic health record systems of office-based physicians: United States, 2009 and preliminary 2010 state estimates. Natl Cent Heal Stat Atlanta. GA; 2009.

  2. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med [Internet]. Mass med soc. 2010 [cited 2016 Mar 6];363:501–4. http://www.nejm.org/doi/full/10.1056/NEJMp1006114.

  3. Centers for Medicare & Medicaid Services. electronic health records (EHR) incentive programs [Internet]. 2016 [cited 2016 Apr 13]. https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html?redirect=/EHRIncentivePrograms/.

  4. Fowles JB, Kind EA, Awwad S, Weiner JP, Chan KS, Coon PJ, et al. Performance measures using Electronic Health Records: five case studies. Commonw Fund 2008;46:6–35.

  5. Elson RB, Connelly DP. Computerized patient records in primary care. Their role in mediating guideline-driven physician behavior change. Arch Fam Med [Internet]. 1995 [cited 2016 Apr 13];4:698–705. http://www.ncbi.nlm.nih.gov/pubmed/7620600.

  6. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA [Internet]. 1998 [cited 2016 Apr 13];280:1339–46. http://www.ncbi.nlm.nih.gov/pubmed/9794315.

  7. O’Connor PJ, Crain AL, Rush WA, Sperl-Hillen JM, Gutenkauf JJ, Duncan JE. Impact of an electronic medical record on diabetes quality of care. Ann Fam Med. 2005;3:300–6.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Feldstein A, Elmer PJ, Smith DH, 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. 2006;54:450–7.

    Article  PubMed  Google Scholar 

  9. Kullar R, Goff DA, Schulz LT, Fox BC, Rose WE. The “epic” challenge of optimizing antimicrobial stewardship: the role of electronic medical records and technology. Clin Infect Dis [Internet]. 2013 [cited 2016 Apr 13];57:1005–13. http://cid.oxfordjournals.org/content/57/7/1005.short.

  10. 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. 2005;24:1103–17.

    Article  Google Scholar 

  11. Wang SJ, Middleton B, Prosser LA, Bardon CG, Spurr CD, Carchidi PJ, et al. A cost-benefit analysis of electronic medical records in primary care. Am J Med. 2003;114:397–403.

    Article  PubMed  Google Scholar 

  12. Hartswood M, Procter R, Rouncefield M, Slack R. Making a case in medical work: implications for the electronic medical record. Comput Support Coop Work [Internet]. 2003;12:241–66. http://link.springer.com/10.1023/A:1025055829026.

  13. Crowson MG, Vail C, Eapen RJ. Influence of electronic medical record implementation on provider retirement at a major academic medical centre. J Eval Clin Pract [Internet]. 2016;22:222–6. http://doi.wiley.com/10.1111/jep.12458.

  14. Forster M, Bailey C, Brinkhof MWG, 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. 2008;86:939–47.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Walker J, Pan E, Johnston D, Adler-Milstein J, Bates DW, Middleton B. The value of health care information exchange and interoperability. Health Aff (Millwood). 2005;Suppl Web.

  16. Gordon T, Paul S, Lyles A, Fountain J. Surgical unit time utilization review: Resource utilization and management implications. J Med Syst [Internet]. 1988 [cited 2015 Oct 19];12:169–79. http://link.springer.com/10.1007/BF00996639.

  17. Eijkemans MJC, van Houdenhoven M, Nguyen T, Boersma E, Steyerberg EW, Kazemier G. Predicting the Unpredictable. Anesthesiology [Internet]. Am Soc Anesthesiol. 2010 [cited 2015 Oct 19];112:41–9. http://anesthesiology.pubs.asahq.org/article.aspx?articleid=1932403.

  18. Peltokorpi A. How do strategic decisions and operative practices affect operating room productivity? Health Care Manag Sci [Internet]. 2011 [cited 2015 Oct 19];14:370–82. http://www.ncbi.nlm.nih.gov/pubmed/21814829.

  19. Gabriel RA, Gimlich R, Ehrenfeld JM, Urman RD. Operating room metrics score card—creating a prototype for individualized feedback. J Med Syst [Internet]. 2014;38:144. http://link.springer.com/10.1007/s10916-014-0144-8.

  20. Malapero RJ, Gabriel R a., Gimlich R, Ehrenfeld JM, Philip BK, Bates DW, et al. An anesthesia medication cost scorecard—concepts for individualized feedback. J Med Syst [Internet]. 2015;39. http://link.springer.com/10.1007/s10916-015-0226-2.

  21. Wu A, Brovman EY, Whang EE, Ehrenfeld JM, Urman RD. The impact of overestimations of surgical control times across multiple specialties on medical systems. J Med Syst [Internet]. 2016 [cited 2016 Feb 11];40:95q. http://www.ncbi.nlm.nih.gov/pubmed/26860918.

  22. Chen Y, Gabriel RA, Kodali BS, Urman RD. Effect of anesthesia staffing ratio on first-case surgical start time. J Med Syst [Internet]. 2016;40:115. http://link.springer.com/10.1007/s10916-016-0471-z.

  23. Donham RT, Mazzei WJ, Jones RL. Association of anesthesia clinical directors’ procedural times glossary. Glossary of times used for scheduling and monitoring of diagnostic and therapeutic procedures. Am J Anesthesiol. 1996;23:3–12.

    Google Scholar 

  24. Wong J, Khu KJ, Kaderali Z, Bernstein M. Delays in the operating room: signs of an imperfect system. Can J Surg [Internet]. 2010 [cited 2016 Apr 13];53:189–95. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2878989&tool=pmcentrez&rendertype=abstract.

  25. Mazzei WJ. Operating room start times and turnover times in a university hospital. J Clin Anesthesiol [Internet]. [cited 2016 Apr 13];6:405–8. http://www.ncbi.nlm.nih.gov/pubmed/7986513.

  26. Harders M, Malangoni MA, Weight S, Sidhu T. Improving operating room efficiency through process redesign. Surgery [Internet]. 2006 [cited 2016 Apr 13];140:509–14; discussion 514–6. http://www.ncbi.nlm.nih.gov/pubmed/17011897.

  27. Vitez TS, Macario A. Setting performance standards for an anesthesia department. J Clin Anesthesiol [Internet]. 1998 [cited 2016 Apr 13];10:166–75. http://www.ncbi.nlm.nih.gov/pubmed/9524906.

  28. Parvathaneni A, O. Peter A, Wilson C. Wheels on Time: A six sigma approach to reduce delay in operating room starting time. Surg Curr Res [Internet]. 2011;01:1–4. http://www.omicsonline.org/2161-1076/2161-1076-1-102.digital/2161-1076-1-102.html.

  29. Wright JG, Roche A, Khoury AE, Ann Roche RN, Khoury AE. Improving on-time surgical starts in an operating room. Can J Surg [Internet]. Canadian Medical Association; 2010 [cited 2016 Aug 19];53:167–70. http://www.ncbi.nlm.nih.gov/pubmed/20507788.

  30. Macario A. What does one minute of operating room time cost? J Clin Anesth [Internet]. 2010 [cited 2015 Oct 27];22:233–6. http://www.sciencedirect.com/science/article/pii/S0952818010000917.

  31. Frazee R, Cames A, Maldonado YM, Bittenbinder T, Papaconstantiou HT. The impact of electronic medical record implementation on operating room efficiency. J Hosp Adm [Internet]. 2015;5:48–51. http://www.sciedu.ca/journal/index.php/jha/article/view/8075.

  32. Sanders DS, Read-Brown S, Tu DC, Lambert WE, Choi D, Almario BM, et al. Impact of an electronic health record operating room management system in ophthalmology on documentation time, surgical volume, and staffing. JAMA Ophthalmol [Internet]. 2014 [cited 2016 Aug 15];132:586–92. http://www.ncbi.nlm.nih.gov/pubmed/24676217.

  33. McIntosh C, Dexter F, Epstein RH. The impact of service-specific staffing, case scheduling, turnovers, and first-case starts on anesthesia group and operating room productivity: a tutorial using data from an Australian hospital. Anesthesiol Analg [Internet]. 2006 [cited 2016 Apr 15];103:1499–516. http://www.ncbi.nlm.nih.gov/pubmed/17122231.

  34. Phieffer L, Hefner JL, Rahmanian A, Swartz J, Ellison CE, Harter R, et al. Improving operating room efficiency: First case on-time start project. J Healthc Qual [Internet]. 2016 [cited 2016 Apr 15]. http://www.ncbi.nlm.nih.gov/pubmed/26991350.

  35. On-time operating room starts can be improved, increasing patient/staff satisfaction and cost savings [Internet]. Anesthesiology. 2013 [cited 2016 Aug 16]. https://www.asahq.org/about-asa/newsroom/news-releases/2013/10/on-time-or-starts?page=8.

  36. Kodali BS, Kim KD, Flanagan H, Ehrenfeld JM, Urman RD. Variability of subspecialty-specific anesthesia-controlled times at two academic institutions. J Med Syst [Internet]. 2014 [cited 2016 Jan 9];38:11. http://link.springer.com/10.1007/s10916-014-0011-7.

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Wu, A., Kodali, B.S., Flanagan, H.L. et al. Introduction of a new electronic medical record system has mixed effects on first surgical case efficiency metrics. J Clin Monit Comput 31, 1073–1079 (2017). https://doi.org/10.1007/s10877-016-9933-6

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  • DOI: https://doi.org/10.1007/s10877-016-9933-6

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