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Medical data formatting to improve physician interpretation speed in the military healthcare system

Cite this dataset

Peterson, Jacob (2022). Medical data formatting to improve physician interpretation speed in the military healthcare system [Dataset]. Dryad.


Objective: The purpose of this project was to improve the ease and speed of physician comprehension when interpreting daily laboratory data for patients admitted within the Military Healthcare System (MHS).

Materials and Methods: A JavaScript program was created to convert the laboratory data obtained via the outpatient electronic medical record (EMR) into a “fishbone diagram” format that is familiar to most physicians. Using a balanced crossover design, 35 internal medicine trainees and staff were asked to complete timed comprehension tests for laboratory data sets formatted in the outpatient EMR’s format and in fishbone diagram format. The number of responses per second and error rate per response were measured for each format. Participants were asked to rate relative ease of use for each format and indicate which format they preferred.

Results: Comprehension speed increased 37% (6.28 seconds per interpretation) with the fishbone diagram format with no observed increase in errors. Using a Likert scale of 1 to 5 (1 being hard, 5 easy), participants indicated the new format was easier to use (4.14 for fishbone vs 2.14 for table) with 89% expressing a preference for the new format. 

Discussion: The publically available web application that converts tabular lab data to fishbone diagram format is currently used 10,000-12,000 times per month across the MHS, delivering significant benefit to the enterprise in terms of time saved and improved physician experience.

Conclusions: This study supports the use of fishbone diagram formatting for laboratory data for inpatients within the MHS.


Study Design: De-identified chemistry and hematology results were presented to participants using the two data formats (tabular and fishbone diagram) along with questionnaires requesting the identification of individual values and trends. Participants completed the two questionnaires in a balanced crossover experiment. After completing both questionnaires participants were asked to complete a 3-question survey rating perceived ease of use and indicating an overall preference for one of the data formats.

Participants: A total of 35 participants were recruited at a daily internal medicine residency didactic session. Participants were asked to abstain if they were unfamiliar with either data format. 

Patient Cases: Each laboratory data format was applied to a pair of basic metabolic panels (BMP) and a pair of complete blood counts (CBC) labeled as being from sequential days (one CBC and BMP for each day). The laboratory data were identical in quantity and type of information but individual result values used for each data format differed.

Procedure: Before the study, every participant was informed about the project and confirmed familiarity with both data formats. Participants were each given both questionnaires (one for each data format) and a survey with the lab data hidden by a cover sheet. Participants were informed they would have 60 seconds to answer as many questions as possible about the data set provided and then would answer a set of questions about a set of data. The questions were designed so that each questionnaire requested identical cognitive tasks in the same order. For example, question three asked to identify a trend on both questionnaires but one questionnaire asked about anemia, the other about renal dysfunction. The study materials were distributed randomly but were prepared such that 50% of participants had the questionnaire with data formatted using a table as the first questionnaire. The remaining 50% started the questionnaire with data formatted using fishbone diagrams. Participants completed the two questionnaires in the assigned order and then completed a three-question survey. 

Outcome Measures: Responses were graded manually with incorrect or partially correct answers both counted as erroneous interpretations. Omitted questions, which were rare, were not considered to have undergone interpretation and were counted neither towards total interpretations nor as erroneous. For each questionnaire, the number of questions answered and the number of errors committed were recorded. 

For the survey results, the ratings for ease of use (1-5 on a Likert scale with 5 being easy) were recorded for each data format. The data format preference of each participant was also recorded.

Usage notes

Microsoft Excel or similar spreadsheet software.