MEASURING THE COST OF PATIENT-GENERATED ELECTRONIC MEDICAL RECORD DATA IN PEDIATRIC INFLAMATORY BOWEL DISEASE PATIENTS

Purpose: To estimate the impact of patient generated data on cost of providing care to children with inflammatory bowel disease (PIBD) using discrete-event-model simulation.
Background: The increasing availability and use of electronic health records allows non-traditional information to be entered by both provider staff and patients. Such technology can change workflow resulting in uncertain temporal and financial impact on providing clinical services. We were interested in studying the costs associated with patient generated data in a typical pediatric gastroenterology practice caring for children with PIBD. We hypothesized that discrete-event-model simulation could estimate the temporal costs related to patient generated data added to the electronic health record at specific data entry and usage points in the workflow.
Method: The Standard of Care for the treatment of PIBD at Nemours calls for entry of patient generated data by patients and staff at various sites in the pathway of workflow during the encounter. The additional time-costs of using these data were modeled and analyzed using constructs of discrete-event-model simulation. Formalizations from previous generic ambulatory clinic simulation studies were used to inform the model construction. Data entry and evaluation occurred at patient kiosks (quality of life indicators), check-in, recording vital signs, physician evaluation and checkout. The time needed for data entry was measured by observation or acquired by provider self-reporting. These values and descriptive statistics were used to populate modeling parameters and constrain embedded stochastics. The simulation was then validated by comparison to actuarial data.
Results: Discrete-event-model simulation provided the means to distinguish segments of PIBD protocol separately and collectively in regard to temporal changes in delivery. The match of observations to staff self-reported estimates varied in accuracy but were sufficient to validate the simulator.
Conclusion: Discrete-event-model simulation permits fine-grained measurement of the provider cost of adding patient generated data to delivery of care for PIBD. The breakout of impact by workflow segments permits exploration of efficient alternatives that may prove beneficial for process improvement. Knowing clearly and measurably where patient generated data will have impact may prove useful to motivate and guide strategic e-health development so as to minimize burden while preserving the benefit of personal health records.