Data Quality: Strategies for Improving Health Care Data
Healthcare Information and Management Systems Society (HIMSS) (09/19/16) Nichols, Joe
Reliable information derived from high-quality, specific, complete and accurate healthcare data is an essential tool for success in a financially constrained environment driven by objective evidence of value. Data quality is more of a human challenge than a technical challenge, writes Joe Nichols, MD, principal, Health Data Consulting. Organizations must have a clear understanding of these challenges and develop a strategy to address them. One challenge is to establish the value proposition for observers and documenters. "Clinicians and those supporting clinicians need to see that the complete and accurate observation and documentation that they were taught in training is still critically important to patient care and to their business," Nichols notes. As a result, organizations should make the case for how data is needed for good patient care, and they should demonstrate how high-quality transactional data about the patient condition is important for payment, quality measurement, accounting for complexity of the patient's condition, and providing information to support the health of the population. Other challenges include standardizing transactional data, and monitoring and sharing data quality metrics. The key to success, concludes Nichols, is for organizations to know their own data and continuously leverage it to improve data.