CMMI® Institute and The US Department of Health and Human Services Launch Framework to Address Patient Data
Patient Demographic Data Quality Framework Aims to Improve Patient Safety
According to the 2016 National Patient Misidentification Report, released by the
Defining and adopting standards, as well as implementing sound data management processes, requires increased awareness, effective collaboration and a cultural evolution toward shared responsibility, both within and across healthcare organizations. “Patients and practitioners alike need to have the assurance that medical errors do not occur due to improperly recorded data,” said
“The ONC Community of Practice analyzed available frameworks and selected the CMMI Institute’s Data Management Maturity (DMM)SM model as the baseline for developing the PDDQ framework of best practices,” said
The PDDQ framework contains practical best practices in 19 data management process areas designed to evaluate an organization’s strengths and gaps, and enables a clear formulation of needed quality improvements. The PDDQ will foster collaboration and consensus among stakeholders, to ensure that data is understood, aligned and trusted across the organization and the patient care lifecycle. “The PDDQ provides a comprehensive evaluation of data management practices for patient data through all health care process areas, including registration, patient care, laboratory, pharmacy, claims and billing,” said
The PDDQ’s flexible structure means it can be applied in whole or in part to suit healthcare organizations. Additionally, the PDDQ framework advocates organization-wide alignment on the following key factors:
- Implementation of data governance functions
- Data quality improvements and assurance
- Managing operational components
- Defining and mapping data dependencies
- Supporting access to shared data interoperability
Implementing PDDQ Framework in Healthcare Organizations
As the creators of the Data Management Maturity (DMM)SM framework,
- Determine the necessary participants and stakeholders in the patient demographic data lifecycle
- Conduct interactive workshops and interviews to gain insight on current patient data matching practices and processes, explore existing gaps, and discover strengths
- Provide a report of recommendations used to guide the organization's data quality plan and implementation activity. This provides a benchmark against which future progress can be measured.
A free copy of the PDDQ Framework is available here. To learn more about how the
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