Quality Improvement
The processes and measurements behind our outcomes

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Quality improvement

CCNC's approach to quality improvement

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Quality Improvement: Changing the System

The processes that make health care delivery more effective — and less costly

CCNC has used performance measurement and feedback to help meet its goals of improving the quality of care for Medicaid recipients while controlling costs since 1998. Quality measurement is intended to stimulate or facilitate quality improvement (QI) efforts in CCNC practices and local networks, and to help evaluate the performance of the program as a whole. Despite rapid growth in CCNC enrollment and number of participating practices, CCNC clinical leaders have remained committed to monitoring quality at the individual practice level, engaging providers in the QI process and reporting on progress at the practice, county, network, and statewide level.

As the CCNC program expanded to serve a larger population with multiple complex comorbidities, a broader array of quality measures was adopted, based on evidence-based care guidelines for diabetes, asthma, hypertension, cardiovascular disease, and heart failure. A workgroup with representation from all 14 CCNC networks was convened in 2007, and met over the course of a year for in-depth review of candidate measures. Goals were to identify a broad set of quality measures with: 1) clinical importance (based on disease prevalence and impact, and potential for improvement), 2) scientific integrity (strength of evidence underlying the clinical practice recommendation; evidence that the measure itself improves care; and the reliability, validity, and comprehensibility of the measure), 3) implementation feasibility, and 4) synergy with other state and national quality measures or quality improvement programs. Measures are not intended to capture every aspect of good clinical care. QMAF measures are reviewed via both claims analyses and chart reviews on an annual basis, and final measures are approved by vote of the CCNC Clinical Directors.

Reports on chart review measures

Practices get reports annually which include their QMAF measures. This has been formatted in 3 different ways in accordance with requests from the practice. One view has this year’s results for the practice. The second view shows this year’s results compared with last year’s results for the practice (shown below). The third view shows this year’s results for the practice compared to with just this year’s results for the practice’s network, and the statewide CCNC enrollment as well as NCQA, HEDIS and IPIP benchmarks.

Outcome indicators

Outcome indicators are typically gathered from claims data and the process indicators from external chart reviews. Community Care has contracted and partnered with Area Health Education Centers (AHECs) for nurse reviewers to perform randomized chart audits that provide practice specific feedback and monitoring on these process measures. To manage the expanding scope of the chart review process, we moved from a paper chart abstraction tool to a fully electronic, streamlined system in 2009. This tool is used to audit either paper or electronic medical records -- close to 30,000 medical record reviews are now performed in over 1350 primary care practices statewide on an annual basis. Nurse reviewers use Medicaid claims to generate a random sample of eligible patients with a given diagnosis and to pre-populate audit tool elements according to an individual’s identified chronic conditions. Secure client-server software allows independent auditors to work offline when Internet access is not available in the clinic location. When access to Internet is available, the system automatically synchronizes data with the server. Data is fully encrypted offline and in transit. Data sent to the server automatically updates a variety of process, progress, and analysis web-based reports. Practices and CCNC networks then have immediate access to chart review results through a secure web-based report site, with patient-level information as well as practice-level statistics.