ArticleAmerican journal of accountable care2019
Implementation Variation in Natural Experiments of State Health Policy Initiatives.
Article in American journal of accountable care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Effect of State-Led Delivery System and Payment Reforms on Population-Level Detection and Management of Diabetes.Diabetes care · 2022Article
- The CMS State Innovation Models Initiative and Improved Health Information Technology and Care Management Capabilities of Physician Practices.Medical care research and review : MCRR · 2021Article
- The Early Impact of the Centers for Medicare & Medicaid Services State Innovation Models Initiative on 30-Day Hospital Readmissions Among Adults With Diabetes.Medical care · 2020Article
- Leveraging Implementation Science in the Public Health Response to COVID-19 : Child Food Insecurity and Federal Nutrition Assistance Programs.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
objectivesAn increasing number of federal initiatives allow states flexibility in selecting the strategies used to achieve initiative-specific goals. Variation in the foci and intensity of implementation may explain why federal policy initiatives succeed in some states and fail in others. The CMS State Innovation Models (SIM) initiative is a complex policy intervention implemented with substantial variation across states and may have variable impacts. This paper presents a method to characterize and account for that variation in states' implementation foci and intensity in natural policy experiments. STUDY
designA combination of quantitative and qualitative measures of SIM implementation was used to characterize the foci of payment and delivery system reforms across states.
methodsA modified Delphi expert panel process was used to prioritize the features of SIM implementation that would differentiate grantee states with respect to improved health outcomes. Three researchers then reviewed summaries of published evaluations and reports to characterize and score states on each implementation feature. Expert panelists guided the researchers on developing the criteria and weights applied to the focus areas when calculating SIM implementation intensity scores for states.
resultsOver 3 years of an expert panel process, 4 dimensions of SIM implementation that would most affect health outcomes were prioritized: 1) extent and breadth of stakeholder engagement, (2) extent that SIM implementation was focused on improving behavioral health, (3) amount of SIM funding per capita, and (4) breadth and depth of value-based payment reforms. Scoring states based on the prioritized factors resulted in composite scores that differentiated states into 3 categories: high, moderate, and low implementation intensity.
conclusionsWe developed a stakeholder-driven method to measure and account for variation in implementation foci and intensity in a federal policy initiative that was implemented heterogeneously across grantee states. Our method for characterizing state implementation variation may be useful for natural policy experiments examining the variable impact of policy initiatives.
Identifiers
31750412PMC6866654What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.