Oregon Health & Science University
Purpose The aim of this study was to evaluate the usability and information completeness of two different methods for structured documentation of dental implant-related clinical data in the electronic health record. The goal is to establish superior methods of clinical documentation that will improve data capture and data search and facilitate future clinical dental implant research and patient care. Methods and Materials Clinical data were collected by licensed dentists enrolled in the advanced training program in periodontal surgery (periodontal residents) as they documented dental implant-related encounters within the electronic health record (EHR), including medical history, restorative treatment plans, treatment details, and postoperative care. Two different methods of structured clinical documentation were used and each was evaluated for their completeness at capturing specific clinical data. The first method used a structured stand-alone data collection form (DCF) in the EHR, set apart from routine treatment documentation. The second method was a structured treatment note (STN) integrated into the treatment documentation which prompted the clinician to answer specific questions during routine treatment documentation. Information was collected using the DCF and STN methods during pre-operative, intra-operative, and post-operative patient encounters. All information was collected in the EHR using unique reference codes for each data field. Twelve matched data fields from DCF and STN were selected and analyzed for documentation completeness: Assessment of healing (AOH), subjective pain (SP), adherence to post-op care instructions (CPI), ASA status (ASA), surgical guide use (SG), occlusal analysis (OA), proposed implant site (PIS), sedation plan (SeP), bone graft (BG), implant system used (IS), and pre-grafted socket (PGS). Eight periodontal residents were surveyed on twenty-one key points after using both data collection methods, by using a 4 point Likert scale: 1 (agree)-4 (disagree). Results Of the eight resident respondents, six evaluations were completed. All respondents agreed (score =1) with the statement that treatment notes must be accurate, that tracking clinical implant data is important, that EHR use is preferred over paper, and that the STN method was easier and faster than the DCF method. Respondents disagreed (score= 4) with the statement that the perceived degree of accuracy when comparing two data field entry methods of the 1) open text box or 2) drop-down list. Users rated the STN higher in perceived accuracy and overall preference. A total of 263 implants procedures were documented in 183 patients utilizing one of these two methods from 7/1/2010 to 8/31/2011. The twelve matched DCF and STN data fields were compared for completeness of information and were respectively: AOH 100%/100%, SP 98%/100%, CPI 97%/98%, ASA 100%/98%, SG 91%/94%, PIS 86%/93 %, SeP 91.3%/93.54%, BG 94%/100%, IS 98%/98%, PGS 97%/95%, -- no significant differences existed between the two methods in these data fields. One data field, OA, did show a significant difference in percent complete, which was 60% (DCF) and 85% (STN). Conclusion The completeness of documented clinical information was similar between the two EHR-based methods evaluated--Data Collection Form (DCF) and Structured Treatment Note (STN), except for OA. However, clinicians demonstrated a strong preference for using the STN method. These results suggest that future clinical research on procedures, like dental implants, may be better facilitated by structuring clinical documentation and integrating it into the existing processes of documentation rather than relying upon separate data collection forms. The STN model can be used to access and assess clinical outcomes like implant survival as well as procedural data and is considered more user-friendly by clinicians.
School of Dentistry
Drake, Sunny L., "Structuring implant data in the electronic health record : a prototype to enhance patient care & research information" (2012). Scholar Archive. 735.