When patient data quality is not prioritized or accurately matched (often due to a lack of training and standards), the following adverse effects may occur:
- Duplicative testing and incorrect treatment
- Diagnosis decisions made in the absence of valuable information
- Adversely impacted insurance claims and billing processes
The Patient Demographic Data Quality (PDDQ) Framework
The PDDQ framework is provided to the healthcare industry by Health and Human Services, Office of the National Coordinator for Health IT. Its content is derived from the Data Management Maturity (DMM)SM Model, created by the CMMI® Institute as a comprehensive reference model of fundamental data management processes that constitute a gradated path to greater capabilities and maturity.
The goal of the PDDQ framework is to help healthcare organizations ensure that adopted standards and processes will be effective, sustainable, and minimize the number of duplicate records to improve patient safety. It contains practical, implementable best practices in 19 data management process areas designed to evaluate an organization’s current strengths and gaps, enabling a clear formulation of needed quality improvements.
The PDDQ helps to establish, build, sustain, and optimize effective data management across the patient demographic data lifecycle, from initial creation through updating, delivery, use, and archiving or destruction.
Get Started Implementing the PDDQ Framework In Your Healthcare Organization:
- Download free white paper here
- Questions? Contact email@example.com
- Sign up to receive more information on the PDDQ framework here
1HealthIT.gov 22016 National Patient Misidentification Report