Analytics: Making Data Meaningful
As an integral component of the Quality Solutions Group, the Analytics team supports NCQA’s measurement and research enterprise. We implement a systematic approach to create standards, measure performance and validate quality data. We also provide data solutions to meet the complex health care needs of our clients.
All this helps drive improvement, save lives, keep people healthy and save money.
Applying risk adjustment methods
Plan All-Cause Readmission Measure. The Analytics team designed predictive models from claims and encounter data to develop this NQF-endorsed measure for the CMS Star Rating system. The models adjust for demographic and clinical characteristics of patients to allow fair comparison among health plans.
The analytic efforts for this measure leveraged a decade of work on risk-adjusted resource use measurement for chronic conditions. In 2016 NCQA will debut all-cause, risk-adjusted inpatient and ED utilization measures to address the gap in measures of health plan value.
Patient-Driven Outcomes for Older Adults With LTSS Needs. NCQA is developing performance measures focused on patient-driven outcomes for quality oversight by states and CMS. The Analytics team will use psychometric techniques to select measures customized to patient goals for improved physical, mental and social functioning. We will drive a new generation of measures away from processes of care and toward what is meaningful to patients’ daily lives and to help clinicians set goals for patient outcome.
Pediatric Centers of Excellence. NCQA led one of seven Pediatric Centers of Excellence, funded by AHRQ, to develop quality measures for adolescent well-care and depression management. As part of the project, the Analytics team identified critical measurement gaps and data validity issues found in reporting measures from electronic data sources. The measures developed from this project, now used in HEDIS, were adapted for use in adult and geriatric populations and are under review for endorsement by the NQF.
Identifying high performers
High Performance in Childhood Immunizations. NCQA conducted a study to characterize high performance and best practices in childhood immunizations among commercial and Medicaid plans. Using performance results from the Childhood Immunization Status HEDIS measure, the Analytics team conducted fuzzy-cluster analysis to determine highest-performing plans over a six-year period (2006–2011). The team developed two final reports: one highlighted the novel use of fuzzy-cluster analysis to examine performance over time, the other highlighted best practices and strategies.
Talent Highlights: Our Strength Is Our People
- PhD, Molecular Biology, Bioinformatics and Parasitology
- MPH, Biostatics & Epidemiology
- Statistical Programming (SAS, SPSS, R, STATA)
Specialty: Statistical analysis and study design.
Current Project: Physician Quality Reporting System (PQRS) Data Validation.
Situation: Support the development of business rules and analytic techniques for identifying potentially inaccurate incentive payments to eligible providers.
Task: Develop methods to detect outlier and atypical performance results, including cluster analysis and multivariate outlier patterns.
Result: Developed nearly 20 indicators of potential data inaccuracies per provider measure to support improvements to the quality of reported data used in federal incentive programs.
Upcoming projects: Benchmarking risk-adjusted outcome measures for ACOs serving patients with ESRD; validation studies for risk-adjusted inpatient and ED measures.
PhD, Social Neuroscience, Health Psychology and Statistics
- MA, Social Neuroscience and Statistics
- Statistical Programming (SAS, SPSS, R, Tableau)
Specialty:Health research and analysis.
Current Project: Agency for Healthcare Research and Quality (AHRQ) Meaningful Use HIT Analysis.
Situation: Examine the feasibility, measurability and clinical relevance of six proposed Meaningful Use Stage 3 objectives related to care coordination.
Task:Create a survey development plan, develop a survey recruitment and tracking plan and analyze results using multivariate linear and logistic regression.
Result: Successfully completed analyses that led to the revision of federal policy objectives to Meaningful Use Stages 2/3. Results were published in the Annals of Family Medicine.
Upcoming projects: NCQA PCMH program redesign to simplify participation, incorporate value-based measurement and extend to specialty practices.
Senior Research Associate
- MPH, Epidemiology
- Statistical Programming (SAS, R)
Specialty: Psychometrics, experimental psychology, research design and analysis.
Current Project: Office of Personnel Management (OPM) Modeling.
Situation: Create a transparent and objective rating system that evaluates plan performance using 20 HEDIS® and CAHPS® measures to reward high performing plans.
Task:Create a plan rating system for assessing performance among the FEHB plans and to develop and evaluate a methodology for measuring plan performance improvement from year to year.
Result: Successfully completed the report card and is concluding improvement modeling.
Upcoming projects: Assessment of patient experience surveys and review of NCQA Health Plan Ratings methodology.