Evidence map›Paper›PMID 35669857›Full record

ArticlePreventive medicine reports2022

The Massachusetts public health data warehouse and the opioid epidemic: A qualitative study of perceived strengths and limitations for advancing research.

Elizabeth A Evans, Elizabeth Delorme, Karl D Cyr, Kimberley H Geissler

Open access · goldAbstract read
In one paragraph

Article in Preventive medicine reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Use of Big Data and Ethical Issues for Populations With Substance Use Disorder.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2023
    Article
  6. Article
  7. Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic.Inquiry : a journal of medical care organization, provision and financing
    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

4 authors at 1 institution in 1 country.

Elizabeth A EvansDepartment of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
Elizabeth DelormeDepartment of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
Karl D CyrDepartment of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
Kimberley H GeisslerDepartment of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
University of Massachusetts Amherst · US

Funding

Massachusetts Justice Cooperative Opioid Innovation Network (JCOIN) Research CenterUG1DA050067 · NIDA · UNIVERSITY OF MASSACHUSETTS AMHERST · PI EVANS, ELIZABETH A., FRIEDMANN, PETER D · 2019 to 2023
$10.5M
NIDA NIH HHS UG1 DA050067
6 · The paper itself

Abstract

Due to the opioid overdose epidemic, Massachusetts created a Public Health Data Warehouse, encompassing individually-linked administrative data on most of the population as provided by more than 20 systems. As others seek to assemble and mine big data on opioid use, there is a need to consider its research utility. To identify perceived strengths and limitations of administrative big data, we collected qualitative data in 2019 from 39 stakeholders with knowledge of the Massachusetts Public Health Data Warehouse. Perceived strengths included the ability to: (1) detect new and clinically significant relationships; (2) observe treatments and services across institutional boundaries, broadening understanding of risk and protective factors, treatment outcomes, and intervention effectiveness; (3) use geographic-specific lenses for community-level health; (4) conduct rigorous "real-world" research; and (5) generate impactful findings that legitimize the scope and impacts of the opioid epidemic and answer urgent questions. Limitations included: (1) oversimplified information and imprecise measures; (2) data access and analysis challenges; (3) static records and substantial lag times; and (4) blind spots that bias or confound results, mask upstream or root causes, and contribute to incomplete understanding. Using administrative big data to conduct research on the opioid epidemic offers advantages but also has limitations which, if unrecognized, may undermine its utility. Findings can help researchers to capitalize on the advantages of big data, and avoid inappropriate uses, and aid states that are assembling big data to guide public health practice and policy.

Indexed as

Administrative data linkageBig dataOpioid epidemicPopulation healthQualitative research

Identifiers

PMID35669857
PMCPMC9166413
OpenAlexW4282012298

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.