Evidence map›Paper›PMID 37145687›Full record

ArticleJAMA health forum2023

A Quantitative Framework to Identify and Prioritize Opportunities in Biomedical Product Innovation: A Proof-of-Concept Study.

Laura Elisabeth Gressler, Kenyon Crowley, Elise Berliner, Hartley Leroy, Esther Krofah, Benjamin Eloff, Danica Marinac-Dabic, Meena Vythilingam

Open access · goldAbstract read
In one paragraph

Article in JAMA health forum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 12% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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 at 6 institutions in 1 country.

Laura Elisabeth GresslerCenter for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
Kenyon CrowleyRobert H. Smith School of Business, University of Maryland, College Park.
Elise BerlinerCerner Enviza, Kansas City, Missouri.
Hartley LeroyCenter for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
Esther KrofahFaster Cures and Center for Public Health, Milken Institute, Washington, DC.
Benjamin EloffOffice of the Assistant Secretary for Health, US Department of Health and Human Services, Washington, DC.
Danica Marinac-DabicCenter for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
Meena VythilingamOffice of the Assistant Secretary for Health, US Department of Health and Human Services, Washington, DC.
Center for Devices and Radiological Health · USOffice of the Assistant Secretary for Health · USAccenture (United States) · USKaw Nation · USMilken Institute · USUnited States Food and Drug Administration · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Prioritization and funding for health initiatives, including biomedical innovation, may not consistently target unmet public health needs. Objective: To (1) develop a quantitative, databased framework to identify and prioritize opportunities for biomedical product innovation investments based on a multicriteria decision-making model (MCDM) that includes comprehensive measures of public health burden and health care costs, and (2) pilot test the model. Design, Setting, and Participants: The Department of Health and Human Services (HHS) convened public and private experts to develop a model, select measures, and complete a longitudinal pilot study to identify and prioritize opportunities for investment in biomedical product innovations that have the greatest public health benefit. Cross-sectional and longitudinal data (2012-2019) for 13 pilot medical disorders were obtained from the Institute for Health Metrics Global Burden of Disease database (IHME GBD) and the National Center for Health Statistics (NCHS). Main Outcome Measures: The main outcome measure was an overall gap score reflecting high public health burden (composite measure of mortality, prevalence, years lived with disability, and health disparities), or high health care costs (composite measure of total, public, and out-of-pocket health spending) relative to low biomedical innovation. Sixteen innovation metrics were selected to reflect the pipeline of biomedical products from research and development to market approval. A higher score indicates a greater gap. Normalized composite scores were calculated for public health burden, cost, and innovation investment using the MCDM Technique for Order of Preference by Similarity to Ideal Solution method. Results: Among the 13 conditions tested in the pilot study, diabetes (0.61), osteoarthritis (0.46), and drug-use disorders (0.39) had the highest overall gap score reflecting high public health burden, or high health care costs relative to low biomedical innovation in these medical disorders. Chronic kidney disease (0.05), chronic obstructive pulmonary disease (0.09), and cirrhosis and other liver diseases (0.10) had the least amount of biomedical product innovation despite similar public health burden and health care cost scores. Conclusions: In this cross-sectional pilot study, we developed and implemented a data-driven, proof-of-concept model that can help identify, quantify, and prioritize opportunities for biomedical product innovation. Quantifying the relative alignment between biomedical product innovation, public health burden, and health care cost may help identify and prioritize investments that can have the greatest public health benefit.

Indexed as

Health Care CostsHealth ExpendituresCross-Sectional StudiesHumansPilot ProjectsPrevalence

Identifiers

PMID37145687
PMCPMC10163391
OpenAlexW4372279285

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.