Evidence map›Paper›PMID 27610462›Full record

ArticleAIDS patient care and STDs2016

Potential Impact of Integrating HIV Surveillance and Clinic Data on Retention-in-Care Estimates and Re-Engagement Efforts.

Eva A Enns, Cavan S Reilly, Beth A Virnig, Karen Baker, Nicholas Vogenthaler, Keith Henry

Abstract read
In one paragraph

Article in AIDS patient care and STDs, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Trial
  3. Article
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  5. Article
  6. HIV Data to Care-Using Public Health Data to Improve HIV Care and Prevention.Journal of acquired immune deficiency syndromes (1999) · 2019
    Article
  7. Article
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  9. Observational
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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

6 authors.

Eva A Enns1 Division of Health Policy and Management, University of Minnesota School of Public Health , Minneapolis, Minnesota.
Cavan S Reilly2 Division of Biostatistics, University of Minnesota School of Public Health , Minneapolis, Minnesota.
Beth A Virnig1 Division of Health Policy and Management, University of Minnesota School of Public Health , Minneapolis, Minnesota.
Karen Baker3 Analytic Center of Excellence, Hennepin County Medical Center , Minneapolis, Minnesota.
Nicholas Vogenthaler4 Division of Infectious Diseases, Hennepin County Medical Center , Minneapolis, Minnesota.
Keith Henry4 Division of Infectious Diseases, Hennepin County Medical Center , Minneapolis, Minnesota.

Funding

Mathematical modeling and analysis of HIV care trajectories and retention in care challengesK25AI118476 · NIAID · UNIVERSITY OF MINNESOTA · PI ENNS, EVA A · 2015 to 2019
$649k
NIAID NIH HHS K25 AI118476
6 · The paper itself

Abstract

Retention in care is essential to the health of people living with HIV and also for their communities. We sought to quantify the value of integrating HIV surveillance data with clinical records for improving the accuracy of retention-in-care estimates and the efficiency of efforts to re-engage out-of-care patients. Electronic medical records (EMRs) of HIV+ patients ≥18 years old from a public, hospital-based clinic in Minneapolis, MN between 2008 and 2014 were merged with state surveillance data on HIV-related laboratory tests, out-of-state relocation, and mortality. We calculated levels of retention and estimated the number of required case investigations to re-engage patients who appeared to be out of care over the study period with and without surveillance data integration. Retention was measured as the proportion of years in compliance with Health Resources and Services Administration (HRSA) guidelines (two clinical encounters >90 days apart annually) and the proportion of patients experiencing a gap in care >12 months. With data integration, retention estimates improved from an average HRSA compliance of 70.3% using EMR data alone to 77.5% with surveillance data, whereas the proportion of patients experiencing a >12-month gap in care decreased from 45.0% to 34.4%. If case investigations to re-engage patients were initiated after a 12-month gap in care, surveillance data would avoid 330 (29.3%) investigations over the study period. Surveillance data integration improves the accuracy of retention-in-care estimates and would avert a substantial number of unnecessary case investigations for patients who appear to be out of care but, in fact, receive care elsewhere or have died.

Indexed as

Public Health SurveillanceAdolescentAdultAgedAmbulatory Care FacilitiesAnti-HIV AgentsContinuity of Patient CareElectronic Health RecordsFemaleHIV InfectionsHumansMaleMiddle AgedMinnesotaPatient ComplianceROC CurveAnti-HIV Agents

Identifiers

PMID27610462
PMCPMC5035363

What OpenQuestion holds

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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.