With the increasing adoption of health information technology and the growth in the resulting electronic repositories of clinical data, the secondary use of electronic health record data has become one of the most promising approaches to enabling and speeding clinical research. Unfortunately, electronic health record data are known to suffer from significant data quality problems. Awareness of the problem of electronic health record data quality is growing, but methods for measuring data quality remain ad hoc. Clinical researchers must handle this complicated problem without systematic or validated methods. The lack of appropriate or trustworthy electronic health record data quality assessment methodology limits the validity of research performed with electronic health record data. This dissertation documents the development of a data quality assessment framework and guideline for clinical researchers engaged in the secondary use of electronic health record data for retrospective research. Through a systematic literature review and interviews with key stakeholders, we identified core constructs of data quality, as well as priorities for future approaches to electronic health record data quality assessment. We used a data-driven approach to demonstrate that data quality is task-dependent, indicating that appropriate data quality measures must be selected, applied, and interpreted within the context of a specific study. On the basis of these results, we developed and evaluated a dynamic guideline for data quality measures in order to help researchers choose data quality measures and methods appropriately within the context of reusing electronic health record data for research.

Indiana University-Purdue University Indianapolis (IUPUI) / Reducing medical error remains in the forefront of healthcare reform. The use of health information technology, specifically the electronic health record (EHR) is one attempt to improve patient safety. The implementation of the EHR in the Emergency Department changes physician workflow, which can have negative, unintended consequences for patient safety. Inaccuracies in clinical documentation can contribute, for example, to medical error during transitions of care. In this quasi-experimental comparison study, we sought to determine whether there is a difference in document quality, error rate, error type, cognitive load and time when Emergency Medicine (EM) residents use paper charts versus the EHR to complete physician documentation of clinical encounters. Simulated patient encounters provided a unique and innovative environment to evaluate EM physician documentation. Analysis focused on examining documentation quality and real-time observation of the simulated encounter. Results demonstrate no change in document quality, no change in cognitive load, and no change in error rate between electronic and paper charts. There was a 46% increase in the time required to complete the charting task when using the EHR. Physician workflow changes from partial documentation during the patient encounter with paper charts to complete documentation after the encounter with electronic charts. Documentation quality overall was poor with an average of 36% of required elements missing which did not improve during residency training. The extra time required for the charting task using the EHR potentially increases patient waiting times as well as clinician dissatisfaction and burnout, yet it has little impact on the quality of physician documentation. Better strategies and support for documentation are needed as providers adopt and use EHR systems to change the practice of medicine.