Literature DB >> 25656861

Implementation of National HIV Screening Recommendations in the Indian Health Service.

Brigg Reilley1, Jessica Leston2, Scott Tulloch3, Lisa Neel4, Megan Galope5, Melanie Taylor3.   

Abstract

BACKGROUND: The Indian Health Service (IHS), a federal agency, provides direct patient care to an estimated 1.9 million American Indian/Alaska Native patients across a large and decentralized network of health facilities. The IHS sought to implement HIV screening of adults and adolescents per national recommendations. The IHS facilities received technical support such as electronic clinical reminders (ECRs) and sample HIV-testing policies.
PURPOSE: To determine what facility-wide policy and practices were associated with high HIV screening rates.
METHODS: Survey of clinical directors of 61 federal health facilities on use of ECRs, testing policies/standing orders, and other factors associated with HIV screening. These results were correlated with HIV screening performance results for each facility as derived from the IHS national database.
RESULTS: A total of 51 (84%) of 61 facilities were interviewed. In univariate analysis, factors that were correlated with higher rates of HIV screening were having an HIV screening standing order (unadjusted odds ratio [UOR] 8.7, 95% confidence interval [CI] 2.0-37.3), sexually transmitted disease (STD) screening standing order (UOR 5, CI 1.1-21.7), having an HIV ECR in place for a year or longer (UOR 10.2, CI 2.8-37.5), and inclusion of both providers and nurses in offering HIV screening (UOR 4.8, CI 1.4-16.7). In multivariate analysis, ECRs (adjusted odds ratio [AOR] 9.1, 95% CI 1.8-45.1) and STD standing orders (AOR 7.4, 95% CI 1.1-51.0) remained significantly associated with higher HIV screening.
CONCLUSION: Policy and practice interventions such as ECRs and standing order/testing policies and delegation of screening are correlated with high HIV screening, are scalable across health networks, and will be used for improving other infectious disease screening indicators in such as STD and hepatitis C.
© The Author(s) 2015.

Entities:  

Keywords:  American Indian/Alaska Native; HIV; electronic clinical reminders; policy; public health; screening; testing

Mesh:

Year:  2015        PMID: 25656861      PMCID: PMC6749603          DOI: 10.1177/2325957415570744

Source DB:  PubMed          Journal:  J Int Assoc Provid AIDS Care        ISSN: 2325-9574


  27 in total

1.  Primary care clinician attitudes towards electronic clinical reminders and clinical practice guidelines.

Authors:  Tejal K Gandhi; Thomas D Sequist; Eric G Poon; Andrew S Karson; Harvey Murff; David G Fairchild; Gilad J Kuperman; David W Bates
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  Implementation and use of an electronic health record within the Indian Health Service.

Authors:  Thomas D Sequist; Theresa Cullen; Howard Hays; Maile M Taualii; Steven R Simon; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2007-01-09       Impact factor: 4.497

3.  Quality improvement with an electronic health record: achievable, but not automatic.

Authors:  Richard J Baron
Journal:  Ann Intern Med       Date:  2007-10-16       Impact factor: 25.391

Review 4.  Why don't physicians test for HIV? A review of the US literature.

Authors:  Ryan C Burke; Kent A Sepkowitz; Kyle T Bernstein; Adam M Karpati; Julie E Myers; Benjamin W Tsoi; Elizabeth M Begier
Journal:  AIDS       Date:  2007-07-31       Impact factor: 4.177

Review 5.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success.

Authors:  Kensaku Kawamoto; Caitlin A Houlihan; E Andrew Balas; David F Lobach
Journal:  BMJ       Date:  2005-03-14

6.  Exploring barriers and facilitators to the use of computerized clinical reminders.

Authors:  Jason J Saleem; Emily S Patterson; Laura Militello; Marta L Render; Greg Orshansky; Steven M Asch
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

7.  A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease.

Authors:  Thomas D Sequist; Tejal K Gandhi; Andrew S Karson; Julie M Fiskio; Donald Bugbee; Michael Sperling; E Francis Cook; E John Orav; David G Fairchild; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

8.  Identifying barriers to the effective use of clinical reminders: bootstrapping multiple methods.

Authors:  Emily S Patterson; Bradley N Doebbeling; Constance H Fung; Laura Militello; Shilo Anders; Steven M Asch
Journal:  J Biomed Inform       Date:  2004-12-15       Impact factor: 6.317

9.  Barriers to electronic health record use during patient visits.

Authors:  Jeffrey A Linder; Jeffrey L Schnipper; Ruslana Tsurikova; Andrea J Melnikas; Lynn A Volk; Blackford Middleton
Journal:  AMIA Annu Symp Proc       Date:  2006

10.  Current HIV epidemiology and revised recommendations for HIV testing in health-care settings.

Authors:  Bernard Branson
Journal:  J Med Virol       Date:  2007       Impact factor: 2.327

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  3 in total

1.  Assessing New Diagnoses of HIV Among American Indian/Alaska Natives Served by the Indian Health Service, 2005-2014.

Authors:  Brigg Reilley; Dana L Haberling; Marissa Person; Jessica Leston; Jonathan Iralu; Rick Haverkate; Azfar-E-Alam Siddiqi
Journal:  Public Health Rep       Date:  2018-03-08       Impact factor: 2.792

2.  Electronic medical record alert increases HIV screening rates: the Foch hospital pilot POP-up project.

Authors:  Alexandre Vallée; Dimi Sveltlane; Julie Trichereau; Stéphane Neveu; Erwan Fourn; Catherine Majerholc; Philippe Lesprit; Laurence Mazaux; Seheno Harijaona Henintsoa; Grazyna Matejczuk; Marc Vasse; David Zucman
Journal:  BMC Health Serv Res       Date:  2022-06-16       Impact factor: 2.908

3.  Use of an electronic medical record reminder improves HIV screening.

Authors:  Colleen Kershaw; Jessica L Taylor; Gary Horowitz; Diane Brockmeyer; Howard Libman; Gila Kriegel; Long Ngo
Journal:  BMC Health Serv Res       Date:  2018-01-10       Impact factor: 2.655

  3 in total

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