Evidence map›Paper›PMID 30615528›Full record

ArticleHealth affairs (Project Hope)2019

Targeted Incentive Programs For Lung Cancer Screening Can Improve Population Health And Economic Efficiency.

David D Kim, Joshua T Cohen, John B Wong, Babak Mohit, A Mark Fendrick, David M Kent, Peter J Neumann

Abstract read
In one paragraph

Article in Health affairs (Project Hope), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. Article
  5. Article
  6. Article
  7. 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.

David D KimDavid D. Kim ( DKim3@tuftsmedicalcenter.org ) is an assistant professor of medicine in the School of Medicine, Tufts University, and an investigator in the Center for the Evaluation of Value and Risk in Health, Tufts Medical Center, in Boston, Massachusetts.
Joshua T CohenJoshua T. Cohen is a research associate professor of medicine in the School of Medicine, Tufts University, and deputy director of the Center for the Evaluation of Value and Risk in Health, Tufts Medical Center.
John B WongJohn B. Wong is a professor of medicine in the School of Medicine, Tufts University, and chief of the Division of Clinical Decision Making, Tufts Medical Center.
Babak MohitBabak Mohit is a postdoctoral research fellow in the Center for the Evaluation of Value and Risk in Health, Tufts Medical Center.
A Mark FendrickA. Mark Fendrick is a professor in the Department of Internal Medicine, University of Michigan, in Ann Arbor.
David M KentDavid M. Kent is a professor of medicine in the School of Medicine, Tufts University, and director of the Predictive Analytics and Comparative Effectiveness Center, Tufts Medical Center.
Peter J NeumannPeter J. Neumann is a professor of medicine in the School of Medicine, Tufts University, and director of the Center for the Evaluation of Value and Risk in Health, Tufts Medical Center.

Funding

Value of Personalized Risk InformationU01NS086294 · NINDS · TUFTS MEDICAL CENTER · PI KENT, DAVID M, NEUMANN, PETER · 2013 to 2017
$2.6M
NINDS NIH HHS U01 NS086294
6 · The paper itself

Abstract

Because an intervention's clinical benefit depends on who receives it, a key to improving the efficiency of lung cancer screening with low-dose computed tomography (LDCT) is to incentivize its use among the current or former smokers who are most likely to benefit from it. Despite its clinical advantages and cost-effectiveness, only 3.9 percent of the eligible population underwent LDCT screening in 2015. Using individual lung cancer mortality risk, we developed a policy simulation model to explore the potential impact of implementing risk-targeted incentive programs, compared to either implementing untargeted incentive programs or doing nothing. We found that compared to the status quo, an untargeted incentive program that increased overall LDCT screening from 3,900 (baseline) to 10,000 per 100,000 eligible people would save 12,300 life-years and accrue a net monetary benefit (NMB) of $771 million over a lifetime horizon. Increasing screening by the same amount but targeting higher-risk people would yield an additional 2,470-6,600 life-years and an additional $210-$560 million NMB, depending on the extent of the risk-targeting. Risk-targeted incentive programs could include provider-level bonuses, health plan premium subsidies, and smoking cessation programs to maximize their impact. As clinical medicine becomes more personalized, targeting and incentivizing higher-risk people will help enhance population health and economic efficiency.

Indexed as

Cost-Benefit AnalysisMotivationPopulation HealthEarly Detection of CancerHumansLung NeoplasmsMass ScreeningQuality-Adjusted Life YearsRisk FactorsTomography, X-Ray Computed

Identifiers

PMID30615528
PMCPMC6409129

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.