Evidence map›Paper›PMID 35759703›Full record

ReviewHealth affairs (Project Hope)2022

Can Alternative Payment Models And Value-Based Insurance Design Alter The Course Of Diabetes In The United States?

Sabrina Wang, George Weyer, Obidiugwu Kenrik Duru, Robert A Gabbay, Elbert S Huang

Abstract readReview
In one paragraph

Review in Health affairs (Project Hope), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sabrina WangSabrina Wang, University of Chicago, Chicago, Illinois.
George WeyerGeorge Weyer, University of Chicago.
Obidiugwu Kenrik DuruObidiugwu Kenrik Duru, University of California Los Angeles, Los Angeles, California.
Robert A GabbayRobert A. Gabbay, American Diabetes Association, Boston, Massachusetts.
Elbert S HuangElbert S. Huang (ehuang@medicine.bsd.uchicago.edu), University of Chicago.

Funding

Voice-Activated Technology to Improve Mobility & Reduce Health Disparities: EngAGEing African American Older Adult-Care Partner DyadsP50MD017349 · NIMHD · UNIVERSITY OF CHICAGO · PI HUISINGH-SCHEETZ, MEGAN J · 2021 to 2025
$24.3M
Research Design, Data, and Analytics CoreP30DK092949 · NIDDK · UNIVERSITY OF CHICAGO · PI MILDA Renne SAUNDERS · 2011 to 2026
$10.0M
Research and Mentorship in Medical Decision Making for Chronic Diseases of Older AdultsK24AG069080 · NIA · UNIVERSITY OF CHICAGO · PI HUANG, ELBERT S. · 2020 to 2024
$583k
NIA NIH HHS K24 AG069080NIDDK NIH HHS P30 DK092949NIMHD NIH HHS P50 MD017349
6 · The paper itself

Abstract

Diabetes process and outcome measures are common quality measures in payment reform models, including Alternative Payment Models (APMs) and value-based insurance design (VBID). In this commentary we review evidence from selected research to examine whether these payment models can improve the value of diabetes care. We found that higher-risk APMs yielded greater improvements in diabetes process measures than lower-risk APMs, and that VBID models appeared to improve medication adherence but not other quality measures. We argue that these models are promising first steps in redesigning the payment system to improve diabetes care. However, greater coordination and alignment across models is needed to enhance their impact on providers' behavior, diabetes care processes, and patient health outcomes.

Indexed as

Diabetes MellitusValue-Based Health InsuranceHumansUnited States

Identifiers

PMID35759703
PMCPMC10155460

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.