Evidence map›Paper›PMID 31250366›Full record

SynthesisJournal of general internal medicine2019

Measures Used to Assess the Impact of Interventions to Reduce Low-Value Care: a Systematic Review.

Jennifer K Maratt, Eve A Kerr, Mandi L Klamerus, Shannon E Lohman, Whit Froehlich, R Sacha Bhatia, Sameer D Saini

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. PERSPECTIVE: A Path to Value-Based Insurance Design for Mental Health Services.The journal of mental health policy and economics · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Review
  12. Article
  13. Article
  14. 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

7 authors.

Jennifer K MarattDepartment of Internal Medicine and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA. jkrai@umich.edu.
Eve A KerrDepartment of Internal Medicine and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
Mandi L KlamerusVeterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA.
Shannon E LohmanWayne State University School of Medicine, Detroit, MI, USA.
Whit FroehlichUniversity of Michigan Medical School, Ann Arbor, MI, USA.
R Sacha BhatiaDepartment of Internal Medicine and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, USA.
Sameer D SainiDepartment of Internal Medicine and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importanceStudies of interventions to reduce low-value care are increasingly common. However, little is known about how the effects of such interventions are measured.

objectiveTo characterize measures used to assess interventions to reduce low-value care. EVIDENCE REVIEW: We searched PubMed and Web of Science to identify studies published between 2010 and 2016 that examined the effects of interventions to reduce low-value care. We also searched ClinicalTrials.gov to identify ongoing studies. We extracted data on characteristics of studies, interventions, and measures. We then developed a framework to classify measures into the following categories: utilization (e.g., number of tests ordered), outcome (e.g., mortality), appropriateness (e.g., overuse of antibiotics), patient-reported (e.g., satisfaction), provider-reported (e.g., satisfaction), patient-provider interaction (e.g., informed decision-making elements), value, and cost. We also determined whether each measure was designed to assess unintended consequences.

findingsA total of 1805 studies were identified, of which 101 published and 16 ongoing studies were included. Of published studies (N = 101), 68% included at least one measure of utilization, 41% of an outcome, 52% of appropriateness, 36% of cost, 8% patient-reported, and 3% provider-reported. Funded studies were more likely to use patient-reported measures (17% vs 0%). Of ongoing studies (registered trials) (N = 16), 69% included at least one measure of utilization, 75% of an outcome, 50% of appropriateness, 19% of cost, 50% patient-reported, 13% provider-reported, and 6% patient-provider interaction. Of published studies, 34% included at least one measure of an unintended consequence as compared to 63% of ongoing studies. CONCLUSIONS AND RELEVANCE: Most published studies focused on reductions in utilization rather than on clinically meaningful measures (e.g., improvements in appropriateness, patient-reported outcomes) or unintended consequences. Investigators should systematically incorporate more clinically meaningful measures into their study designs, and sponsors should develop standardized guidance for the evaluation of interventions to reduce low-value care.

Indexed as

Attitude of Health PersonnelHumansMedical OverusePatient Reported Outcome MeasuresQuality Indicators, Health Careinterventionslow-value caremeasures

Identifiers

PMID31250366
PMCPMC6712188

What OpenQuestion holds

Textmetadata
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.