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Home Research Research Library Family Practices in Transforming Clinical Practice Initiative Showed No Changes in Medicare Costs or Utilization Family Practices in Transforming Clinical Practice Initiative Showed No Changes in Medicare Costs or Utilization 2022 Author(s) Dai, Mingliang, Chung, YoonKyung, Peterson, Lars E, Petterson, Stephen M, and Phillips, Robert L Topic(s) Role of Primary Care Keyword(s) Practice Innovations Volume Medical Care Source Medical Care BACKGROUND: The Centers for Medicare and Medicaid Services proposed that the Transforming Clinical Practice Initiative (TCPI) would improve health outcomes for patients, reduce utilization of institutional services, and generate significant savings for payers by the end of September 2019. OBJECTIVE: The objective of this study was to investigate whether participation in TCPI’s Practice Transformation Networks (PTNs) was associated with improved cost and utilization outcomes for Medicare patients of family medicine-based practices in the first 2 years, that is, 2016-2017, of the Initiative. STUDY DESIGN: A quasi-experimental design with a longitudinal cohort of family medicine-based practices and a propensity-matched comparison sample. SUBJECTS: A total of 761 PTN practices and 3451 non-PTN practices. MEASURES: To measure practice-level patient outcomes, we attributed patients to practice based on the plurality of office visits. We obtained Medicare claims from 2011 to 2017 to assess PTN participation effects for Medicare Part A and B costs, hospital admission, and emergency department visit rates using a Difference-in-Differences design, adjusting for baseline characteristics. RESULTS: The differences in Medicare Part A and B costs (-1.71%, P=0.25), annual rates of hospitalization (-0.59%, P=0.12) and emergency department visit (-0.29%, P=0.46) were not significantly lower among PTN practices (N=761) than among propensity score-matched non-PTN practices (N=3541). CONCLUSIONS: TCPI’s transforming efforts, such as the outcomes examined in the study, might need a longer time frame to manifest and require evaluation after the full 4-year participation period. The indistinguishable effect of PTN participation may also be attributed to the fact that non-PTN practices might have participated in other initiatives that changed their care and curbed health care utilization and costs consequently. ABFM Research Read all 2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? 2024 The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19 Go to The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis Go to Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis
Author(s) Dai, Mingliang, Chung, YoonKyung, Peterson, Lars E, Petterson, Stephen M, and Phillips, Robert L Topic(s) Role of Primary Care Keyword(s) Practice Innovations Volume Medical Care Source Medical Care
ABFM Research Read all 2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? 2024 The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19 Go to The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis Go to Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis
2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care?
2024 The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19 Go to The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19
2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence
2025 Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis Go to Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis