Evidence map›Paper›PMID 28103923›Full record

ArticleBMC health services research2017

Risk-adjustment methods for all-payer comparative performance reporting in Vermont.

Karl Finison, MaryKate Mohlman, Craig Jones, Melanie Pinette, David Jorgenson, Amy Kinner, Tim Tremblay, Daniel Gottlieb

Abstract readComparative StudyMulticenter Study
In one paragraph

Article in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Karl FinisonOnpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA. kfinison@onpointhealthdata.org.ORCID 0000-0002-5928-4445
MaryKate MohlmanVermont Blueprint for Health, 280 State Dr. Waterbury, Vermont, 05671, USA.
Craig JonesU.S. Department Health and Human Services, Vermont Blueprint for Health. Office of the National Coordinator for Health Information Technology, 330 C Street, SW; Floor 7, Washington, DC, 20024, USA.
Melanie PinetteOnpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
David JorgensonOnpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
Amy KinnerOnpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
Tim TremblayVermont Blueprint for Health, 280 State Dr. Waterbury, Vermont, 05671, USA.
Daniel GottliebThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth Hitchcock Medical Center, Lebanon, NH, 03766, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the emphasis in health reform shifts to value-based payments, especially through multi-payer initiatives supported by the U.S. Center for Medicare & Medicaid Innovation, and with the increasing availability of statewide all-payer claims databases, the need for an all-payer, "whole-population" approach to facilitate the reporting of utilization, cost, and quality measures has grown. However, given the disparities between the different populations served by Medicare, Medicaid, and commercial payers, risk-adjustment methods for addressing these differences in a single measure have been a challenge.

methodsThis study evaluated different levels of risk adjustment for primary care practice populations - from basic adjustments for age and gender to a more comprehensive "full model" risk-adjustment method that included additional demographic, payer, and health status factors. It applied risk adjustment to populations attributed to patient-centered medical homes (283,153 adult patients and 78,162 pediatric patients) in the state of Vermont that are part of the Blueprint for Health program. Risk-adjusted expenditure and utilization outcomes for calendar year 2014 were reported in 102 adult and 56 pediatric primary-care comparative practice profiles.

resultsUsing total expenditures as the dependent variable for the adult population, the r

conclusionsResults indicate that more comprehensive risk-adjustment models are effective for comparing cost, utilization, and quality measures across multi-payer populations. Such evaluations will become more important for practices, many of which do not distinguish their patients by payer type, and for the implementation of incentive-based or alternative payment systems that depend on "whole-population" outcomes. In Vermont, providers, accountable care organizations, policymakers, and consumers have used Blueprint profiles to identify priorities and opportunities for improving care in their communities.

Indexed as

AdolescentAdultAgedChildChild, PreschoolCosts and Cost AnalysisFemaleHealth Care ReformHealth ExpendituresHumansInfantMaleMedicaidMedicareMiddle AgedPrimary Health CareAccountable careAPCDPopulation healthPrimary care practiceRisk adjustment

Identifiers

PMID28103923
PMCPMC5248440

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Registered trials

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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.