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Maximizing Quality Improvement with Precise Diabetes Data Analysis

Ensure top-tier diabetes care by leveraging NCQA top 10 percentile data for internal feedback and quality improvement among patients aged 18-75 with A1c tests conducted annually. Public data comparison crucial for financial impact, demanding impeccable data quality, consistency, and actionable insights. Data key for care coordination, cost management in specialty care, and procedural focus.

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Maximizing Quality Improvement with Precise Diabetes Data Analysis

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  1. For diabetes patients % with A1c tested within measurement year, age 18-75. Target NCQA top 10 percentile.

  2. Data for internal feedback and QI can be imperfect (“directional & good enough”) • Public data for comparison has a financial impact & must be impeccable: • Measures broadly accepted • From a trusted source and methodology • Consistent across payers • Meaningful • Timely • Actionable • Tied to QI initiatives/tools • Payment reform to support QI work and *financially reward reporting of practice level data • Critical- to improve/coordinate care using data that is collected during the course of routine care • Cost of care- need more focus on specialty care/ procedures

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