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State Medicaid Agencies Approaches to Quality Improvement: Implications for Policy, Practice and Health OutcomesNair, Dev 23 April 2009 (has links)
Medicaid provides coverage to approximately 60 million individuals and is the largest single payer of healthcare for children. Given this scope of the program and the concentration of low-income and minority recipients, improvements to the quality of care delivered to Medicaid members represents a significant opportunity to reduce health care disparities and improve the overall delivery and quality of healthcare within the U.S. The current study sought to evaluate the various approaches that state Medicaid agencies are taking to assess and improve the quality of care to their managed care enrollees and the degree to which they have implemented recommendations of various policy experts. A survey was distributed to the Medicaid Directors of all 50 states. A total of 23 states with risk based managed care programs responded, representing 62% of the states that have managed care programs. The results indicated that nearly all states are utilizing standard performance measures as one method to assess quality, with virtually all relying on HEDIS measures for this purpose. Additional strategies that are being used include public reporting of quality data and the use of pay-for-performance incentives; few states are currently focusing on health information technology. Recommendations are made for steps that the Medicaid program could take at both the state and federal level to further develop quality improvement programs.
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Employing Provider Mentoring/Coaching to Improve Preventive Quality OrderingKnox-Woodward, Julie 01 January 2014 (has links)
Preventive quality ordering is a provider intervention aimed at disease prevention through the ordering of industry-recommended health maintenance tests. This pilot study evaluated the effectiveness of provider mentoring/coaching to improve preventive quality ordering using the 2014 Agency for Healthcare Research and Quality best practice preventive clinical services guidelines. Literature indicates provider inconsistency in preventive and quality ordering as the primary cause of disparate health outcomes. Guided by theories of modeling and role-modeling, as well as the theory of cognitive continuum, this pilot study offered provider mentoring/coaching to encourage timely preventative quality ordering. Routinely monitored historic provider practice patterns in a proprietary database were analyzed; 10 providers with the lowest ordering patterns were identified for participation. Mentoring/coaching interventions were provided to improve preventive quality measure ordering. This process included a review of the 2014 Adult Healthcare Effectiveness Data and Information Set documentation criteria, a preventive measures clinical checklist, medical record preparation guidance, clinical shadowing, and post-training discussions. Following the pilot, a 5-person subject matter expert panel of key organizational leaders used on-site observations and standardized semi-structured interviews to evaluate the usefulness of mentoring/coaching and the developed documents to improve timely quality ordering. This small-scale pilot study (a) improved providers' awareness of quality ordering through peer mentoring, communication, and training; and (b) provided a platform for future initiatives. A larger follow-up study will allow healthcare leaders/providers to address disparate health outcomes, and patients will likely benefit from optimal delivery of preventive care.
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A COMPARISON OF QUALITY INDICATORS BETWEEN MEDICARE ACCOUNTABLE CARE ORGANIZATIONS AND HEALTH MAINTENANCE ORGANIZATIONS USING PUBLICLY AVAILABLE DATACampbell, William W, III 01 January 2018 (has links)
The purpose of this study is to explore differences in quality between Medicare Accountable Care Organizations (ACO) and Health Maintenance Organizations (HMO). Three outcomes measures reported by these plans use different methodologies but possess enough alignment to permit comparison: percent of diabetic patients with last HbA1c > 9.0%, colon cancer screening rate and ER visits per 1,000. These outcomes are the dependent variables (DV). A secondary purpose is to explore differences in quality based on the size of the beneficiary population served, using the same measures.
As the Medicare program faces threats to its solvency in coming decades, with 10,000 baby boomers becoming eligible every day, and the ongoing national conversation about healthcare more generally, approaches to Value-Based Purchasing (VBP) are becoming more common. Organizations seeking to identify the types of VBP arrangements in which they should enter have precious little information on the comparative performance of VBP approaches relative to outcomes measures. Different structures create different incentives through the plan design and risk/reward. The convergence or dissipation of the plan incentives at the level of the provider, particularly in primary care, may be a source of variance.
This study is retrospective, non-experimental, and uses publicly available data on the performance of Medicare ACO and HMO plans in calendar year 2015, for the identified measures. Using the Donabedian Structure-Process-Outcome framework, this study explores the impact of structure by type of plan and size of population served, relative to the outcomes. Race, average Hierarchical Condition Category (HCC) risk score and duration of operations are control variables. The analysis uses multiple hierarchical regression to better understand the relationship between the independent variables (IV) and DVs, after the impact of the control variables (CV).
After controls, the IVs did offer some explanation of variation in outcomes. The ACO plans fared better on HbA1c control, while HMO plans had fewer ER visits per 1,000. No discernable difference existed between the HMO and ACO plans with regard to colon cancer screening rate. Serving larger populations led to better performance on all three measures. In general performance was worse on each measure in both models when the percent of not-White patients or average HCC risk score increased. A longer duration of operations also associated to better performance on the outcome measures.
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