34 Background: Research and quality improvement studies often involve an extensive amount of manual review of medical records. The effective management of this process is critical to the consistent, accurate, and cost effective collection and timely dissemination of quality data. Methods: The purpose of this paper is to introduce “OpenQA”, a data management tool designed specifically to help organize, track, and communicate data related to quality improvement studies. OpenQA is designed with ease of chart abstraction, efficiency of data collection, and data transparency as a goal, while providing reporting that support a range of activities related to data management tasks common to hospital quality management departments. The basic method behind OpenQA is to: (1) Provide a centralized online repository for measure related metadata; (2) automatically identify retrospective and prospective encounters that meet specified study inclusion/exclusion criteria; (3) extract key details from structured and unstructured data sources and then combine them to help quality auditors make compliance decisions; (4) provide a workflow engine that supports work lists, alerting and a feedback mechanism for metric stakeholders; (5) provide audit tracking to enable measurability of data collection efforts. Results: Favorable effects were realized post implementation across all measures of performance despite an increase in case volume. Results indicate a decrease in median audit turnaround time, defined as the time between the patient encounter and a decision is made by the auditor, by 23 days (85%). Results also indicate a decrease in the audit reporting turnaround time, defined as the time between the patient encounter and the compliance decision is made and reported. Both reductions were significant at a p value of < 0.05. Conclusions: We suggest that a tool designed to help streamline and standardize the quality improvement data collection process may offer the advantage of minimizing the resource utilization associated with data collection while improving data integrity and shortening the feedback loop.
Quantitative data management in quality improvement collaboratives