Evidence map›Paper›PMID 35412467›Full record

ArticleJMIR public health and surveillance2022

Where Opioid Overdose Patients Live Far From Treatment: Geospatial Analysis of Underserved Populations in New York State.

Kayley Abell-Hart, Sina Rashidian, Dejun Teng, Richard N Rosenthal, Fusheng Wang

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 11 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Kayley Abell-HartDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-3887-8025
Sina RashidianDepartment of Computer Science, School of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0003-1210-2939
Dejun TengDepartment of Computer Science, School of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-0103-8348
Richard N RosenthalDepartment of Psychiatry, Stony Brook Medicine, Stony Brook, NY, United States.ORCID 0000-0002-6011-809X
Fusheng WangDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-9369-9361
Stony Brook University · USStony Brook Medicine · US

Funding

Scholars in BioMedical Sciences (SBMS) Training ProgramT32GM127253 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI TSIRKA, STYLIANI-ANNA (STELLA) E · 2018 to 2022
$689k
NIGMS NIH HHS T32 GM127253
6 · The paper itself

Abstract

backgroundOpioid addiction and overdose have a large burden of disease and mortality in New York State (NYS). The medication naloxone can reverse an overdose, and buprenorphine can treat opioid use disorder. Efforts to increase the accessibility of both medications include a naloxone standing order and a waiver program for prescribing buprenorphine outside a licensed drug treatment program. However, only a slim majority of NYS pharmacies are listed as participating in the naloxone standing order, and less than 7% of prescribers in NYS have a buprenorphine waiver. Therefore, there is a significant opportunity to increase access.

objectiveIdentifying the geographic regions of NYS that are farthest from resources can help target interventions to improve access to naloxone and buprenorphine. To maximize the efficiency of such efforts, we also sought to determine where these underserved regions overlap with the largest numbers of actual patients who have experienced opioid overdose.

methodsWe used address data to assess the spatial distribution of naloxone pharmacies and buprenorphine prescribers. Using the home addresses of patients who had an opioid overdose, we identified geographic locations of resource deficits. We report findings at the high spatial granularity of census tracts, with some neighboring census tracts merged to preserve privacy.

resultsWe identified several hot spots, where many patients live far from the nearest resource of each type. The highest density of patients in areas far from naloxone pharmacies was found in eastern Broome county. For areas far from buprenorphine prescribers, we identified subregions of Oswego county and Wayne county as having a high number of potentially underserved patients.

conclusionsAlthough NYS is home to thousands of naloxone pharmacies and potential buprenorphine prescribers, access is not uniform. Spatial analysis revealed census tract areas that are far from resources, yet contain the residences of many patients who have experienced opioid overdose. Our findings have implications for public health decision support in NYS. Our methods for privacy can also be applied to other spatial supply-demand problems involving sensitive data.

Indexed as

BuprenorphineDrug OverdoseOpiate OverdoseOpioid-Related DisordersHumansNaloxoneNarcotic AntagonistsNew YorkVulnerable PopulationsBuprenorphineNaloxoneNarcotic Antagonistsbuprenorphineepidemiologygeospatial analysisnaloxoneopioid overdoseopioid pandemicopioid use disorderpublic health

Identifiers

PMID35412467
PMCPMC9044159
OpenAlexW4223466744

What OpenQuestion holds

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LicenceCC BY
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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.