Abstract
Background/Aims Healthcare data is highly complex, and considerable effort is required to create rich data resources that are reliable, user-friendly and represent valid utilization. Challenges include identifying appropriate sources, interpreting the data in a given source, matching data between sources, and transforming source data to meet desired specifications. Flaws in any of these aspects of data development can negatively impact data quality and reliability. Creating partnerships for data development across analytic groups within the organization could make the process more efficient by pooling specialized knowledge and increasing opportunities for evaluating data quality. Within Kaiser Permanente in the Mid-Atlantic States, our goal was to (1) identify and implement best practices for data quality, and (2) determine the best method to implement those practices by working in conjunction with not only research staff, but also operations staff and information technology staff.
Methods We leveraged literature review to identify best practices in data quality. We identified 3 pillars of data quality improvement: (1) Assessment and Measurement, (2) System Integration, and (3) Governance and Incident Management. Then we used a combined systems and human factors approach to identify opportunities for partnership across analytic groups. This allowed us to identify resources and the appropriate process to engage the 3 pillars.
Results We have implemented several capacities that allow us to continually improve our data quality. We developed a decision tree that guides us through the process of developing relevant data partnerships. We implemented mechanisms to monitor relevant changes in upstream systems and alert us to the need to modify extract-transform-load scripts. Lastly, we developed processes to report and address concerns related to data quality and use.
Conclusions Improving data quality is not a single act, but rather a journey. The key element identified was the process and governance required to ensure successful partnerships with both the information technology group and operational analytic groups across the institution.
