Exploring Dental Providers’ Workflow in an Electronic Dental Record EnvironmentThe authors thank the MCHS dental centers for their participation in this study. The authors also thank Dr. Ingrid Glurich and Ms. Dixie Schroeder for help with the final review of the manuscript. This project was supported, in part, by a grant from Delta Dental of Wisconsin, and funds from Marshfield Clinic Research Foundation and Family Health Center of Marshfield, Inc.
13 November 2015
accepted: 01 April 2016
16 December 2017 (online)
A workflow is defined as a predefined set of work steps and partial ordering of these steps in any environment to achieve the expected outcome. Few studies have investigated the workflow of providers in a dental office. It is important to understand the interaction of dental providers with the existing technologies at point of care to assess breakdown in the workflow which could contribute to better technology designs.
The study objective was to assess electronic dental record (EDR) workflows using time and motion methodology in order to identify breakdowns and opportunities for process improvement.
A time and motion methodology was used to study the human-computer interaction and workflow of dental providers with an EDR in four dental centers at a large healthcare organization. A data collection tool was developed to capture the workflow of dental providers and staff while they interacted with an EDR during initial, planned, and emergency patient visits, and at the front desk. Qualitative and quantitative analysis was conducted on the observational data.
Breakdowns in workflow were identified while posting charges, viewing radiographs, e-prescribing, and interacting with patient scheduler. EDR interaction time was significantly different between dentists and dental assistants (6:20 min vs. 10:57 min, p = 0.013) and between dentists and dental hygienists (6:20 min vs. 9:36 min, p = 0.003).
On average, a dentist spent far less time than dental assistants and dental hygienists in data recording within the EDR.
- 1 Schleyer TK, Thyvalikakath TP, Spallek H, Torres-Urquidy MH, Hernandez P, Yuhaniak J. Clinical computing in general dentistry. J Am Medical Inform Assoc 2006; 13 (03) 344-352.
- 2 Irwin JY, Torres-Urquidy MH, Schleyer T, Monaco V. A preliminary model of work during initial examination and treatment planning appointments. Br Dent J 2009; 206 (01) E1.
- 3 Wagner IV, Ireland RS, Eaton KA. Digital clinical records and practice administration in primary dental care. Br Dent J 2008; 204 (07) 387-395.
- 4 Niazkhani Z, Pirnejad H, Berg M, Aarts J. The impact of computerized provider order entry systems on inpatient clinical workflow: a literature review. J Am Medical Inform Assoc 2009; 14 (04) 539-549.
- 5 Zheng K, Haftel HM, Hirschl RB, O’Reilly M, Hanauer DA. Quantifying the impact of health IT implementation on clinical workflow: a new methodological perspective. J Am Medical Inform Assoc 2010; 17 (04) 454-461.
- 6 HealthIT.gov. Benefits of EHRs. Improved diagnostics & patient outcomes. [updated 2014 March 19]. Available at: https://www.healthit.gov/providers-professionals/improved-diagnostics-patient-outcomes. [Accessed 2015 July 23].
- 7 Levingston SA. Opportunities in physician electronic health records: a road map for vendors. Bloomberg Government. 2012
- 8 Why adopt EHRs?. 2014 Available at: http://www.healthit.gov/providers-professionals/why-adopt-ehrs. [Accessed 2015 July 23].
- 9 Ellis CA. Workflow technology. In: Beaudouin-Lafon M. ed. Computer Supported Cooperative Work. Chichester: UK: John Wiley & Sons; 1999: 29-54.
- 10 Keohane CA, Bane AD, Featherstone E, Hayes J, Woolf S, Hurley A, Bates DW, Ghandi TK, Poon EG. Quantifying nursing workflow in medication administration. J Nurs Admin. 2008 38. 19-26.
- 11 Wong DH, Gallegos Y, Weinger MB, Clack S. Slagle J, Andearson CT. Changes in intensive care unit nurse task activity after installation of a third-generation intensive care unit information system. Crit Care Med 2003; 31 (10) 2488-2494.
- 12 Overhage JM, Perkins S, Tierney WM, McConald CJ. Controlled trial of direct physician order entry: effects on physicians’ time utilization in ambulatory primary care internal medicine practices. J Am Medical Inform Assoc 2001; 08 (04) 361-371.
- 13 Lo HG, Newmark LP, Yoon C, Volk LA, Carlson VL, Kittler AF, Lippincott M, Wang T, Bates DW. Electronic health records in specialty care: a time-motion study. J Am Medical Inform Assoc 2007; 14 (05) 609-615.
- 14 Hollingworth W, Devine EB, Hansen RN, Lawless NM, Comstock BA, Wilson-Norton JL, Tharp KL, Sullivan SD. The impact of e-prescribing on prescriber and staff time in ambulatory care clinics: a time–motion study. J Am Medical Inform Assoc 2007; 14 (06) 722730.
- 15 Pizziferri L, Kittler AF, Volk LA, Honour MM, Gupta S, Wang S, Lippincott M, Li Q, Bates DW. Primary care physician time utilization before and after implementation of an electronic health record: a time-motion study. J Biomedical Inform 2005; 38 (03) 176-188.
- 16 Starren J, Chan S, Tahil F, White T. When seconds are counted: tools for mobile, high-resolution time-motion studies. Proc AMIA Symp 2000; 833-837.
- 17 Allen SI, Johannes RS, Brown CS, Kafonek DM, Plexico PS. Prescription-writing with a PC. Comput Methods Programs Biomed 1986; 22 (01) 127-135.
- 18 Asaro PV, Boxerman SB. Effects of computerized provider order entry and nursing documentation on workflow. Acad Emerg Med 2008; 15 (10) 908-915.
- 19 Achary A, Yoder N, Nycz G. An integrated medical-dental electronic health record environment: a Marshfield experience. In: Powell V, Din FM, Acharya A, Torres-Urquidy MH. eds. Integration of Medical and Dental Care and Patient Data. London: Springer-Verlag; 2012: 331-351.
- 20 Parterns Healthcare. Agency for Healthcare Research and Quality. National Resource Center fro Health Information Technology. Time and Motion Study Tool: Ambulatory Practice (TMS-AP). Available at: https://healthit.ahrq.gov/sites/default/files/docs/page/AHRQ%20NRC%20Time-Motion%20Study%20Tool%20Guide_0.pdf. [Accessed 2015 July 23].
- 21 Elo S, Kyngä H. The qualitative content analysis process. J Adv Nurs 2008; 62 (01) 107-115.
- 22 Fleiss JL. Statistical methods for rates and proportions. 2nd ed.. New York: John Wiley & Sons, Ltd; 1981
- 23 American Dental Association, 2014 Characteristics of private dental practices. [cited Janaury 19, 2016] 2012 available from http://www.ada.org/en/science-research/health-policy-institute/data-center/dental-practice.