ClinicalTrials.gg
CompletedNCT04147832Updated Feb 25, 2025

Epividian / AHF: Positive Pathways - HIV Retention in Care

An observational study in HIV/AIDS, sponsored by Epividian. Completed at 1 site in United States. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-02-25.

Sponsored by Epividian · Observational

Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
10,521
Ages
18 Years and older
Sex
All
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Study summary

The primary objective of this study is to evaluate the effectiveness of a clinical decision support system (CDSS) combined with enhanced patient contact to retain HIV+ patients in care with AIDS Healthcare Foundation. Specifically, the study aims to evaluate the effectiveness of having the patient's primary caregiver (or dedicated case manager) telephone the patient when the patient is identified as a significant risk to loss of follow-up (at-risk patients) based upon pre-defined criteria. The secondary objective Gain a better understanding about the implementation of the study's procedures in clinical practice by evaluating survey responses delivered to participating healthcare providers and AHF staff members engaging with the study's intervention.

Read the detailed description

Retention in care and re-engagement in care is a primary concern in HIV treatment today and a major obstacle in the US to reach the UNAIDS 90-90-90 goal [1]. The U.S. CDC supports the use of HIV surveillance data to identify not-in-care (NIC) patients and re-link them to care (Data-to-Care). The optimal strategy for identifying patients for Data-to-Care is unknown. It has been postulated that by increasing follow up of high-risk patients not meeting the retention in care measures, the number of people living with HIV being retained in care may be increased by 10%.

Multiple HIV clinics within the AHF organization in the US are eligible for study participation. "Primary" HIV provider will be defined as the primary physician or advanced care practitioner following a patient, as recorded in their respective EHRs and identified through CHORUS, a CDSS developed by Epividian. The CDSS will track patient case status as active or inactive (loss to follow-up, transferred medical care, or deceased). Providers will be informed of the study and sites will be contracted to participate in this collaborative research study.

The CDSS will generate alerts to the providers warning of suboptimal patient attendance among the population. The alerts will be generated using the following four criteria of at-risk of loss to follow-up:

  • At Risk #1: No visit in the previous 4 months and no scheduled appointment in the subsequent 2 months.
  • High Risk #2: Single appointment in the previous year, a missed appointment in the previous month and no scheduled appointment in the next 2 months.
  • High Risk #3: Those with 2 missed sequential appointments, and no scheduled appointment in the subsequent 7 days.
  • High Risk #4: Those with an attended appointment >3 months ago and their most recent viral load >1000 copies/ml.
02

Conditions studied

03

In context

Acquired Immunodeficiency Syndrome

3,035 studies on the registry are indexed under Acquired Immunodeficiency Syndrome; 306 are open to participants now.

This study's enrollment of 10,521 is above the median of 287 across 503 observational studies indexed under Acquired Immunodeficiency Syndrome.

Browse Acquired Immunodeficiency Syndrome studies →

Lead sponsor

Epividian is the lead sponsor of 8 studies on the registry; 1 is open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

Patients with HIV-1 diagnosis who are in care at AHF and seen at least once in the last 2 years.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • -1+
  • 18 years old or older
  • Any sex
  • Seen at least once in a US-based AHF clinic in the last 2 years with care documented in the EHR

Exclusion criteria

Exclusion Criteria:

  • Patients known to have left the practice
  • Patients who choose not to be contacted about their care via telephone
Terms in these criteria, in plain language(1)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

HIV

The human immunodeficiency virus, which weakens the immune system.

Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.

05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
10,521 participants (actual)
Patient registry
No

Groups and cohorts

  • HIV-1

    HIV-1+, males, females, transgender, ≥18 years of age, seen at any AHF clinic within the last two years and whose care is documented in the AHF electronic health records system.

    Other: Alert to provider

Interventions

  • OtherAlert to provider

    Provider will receive an alert of sub-optimal patient attendance using 4 rules.

06

What researchers measure

Primary outcomes

  1. Rate of Kept Appointments

    Pre and post-baseline rate of patients who attended their scheduled office visits.

    Time frame: 16 months, 01-Nov-2019 to 30-Apr-2021

Secondary outcomes

  1. Viral suppression

    Proportion of patients with an undetectable viral load defined as patients with a viral load \<50 copies/mL out of all patients seen at the practice in the past 2 years

    Time frame: 16 months, 01-Nov-2019 to 30-Apr-2021

  2. Ranked Scoring of Implementation effectiveness

    Evaluation of healthcare providers' survey responses regarding implementation context of appropriateness, feasibility, adoption, appropriateness and effectiveness. With providers' scores ranked 1 (lowest/worst) to 5 (highest/best), will report pre and post-baseline averages and distributions of scores.

    Time frame: 16 months, 01-Nov-2019 to 30-Apr-2021

07

Study locations

1 site
  • AHF
    Los Angeles, California 90028, United States
08

References and documents

Publications

  • Kazanjian P. UNAIDS 90-90-90 Campaign to End the AIDS Epidemic in Historic Perspective. Milbank Q. 2017 Jun;95(2):408-439. doi: 10.1111/1468-0009.12265. PubMed 28589602 ↗
  • Bakken S. An informatics infrastructure is essential for evidence-based practice. J Am Med Inform Assoc. 2001 May-Jun;8(3):199-201. doi: 10.1136/jamia.2001.0080199. PubMed 11320064 ↗
  • Bates DW, Gawande AA. Improving safety with information technology. N Engl J Med. 2003 Jun 19;348(25):2526-34. doi: 10.1056/NEJMsa020847. No abstract available. PubMed 12815139 ↗
  • Bakken S, Cimino JJ, Hripcsak G. Promoting patient safety and enabling evidence-based practice through informatics. Med Care. 2004 Feb;42(2 Suppl):II49-56. doi: 10.1097/01.mlr.0000109125.00113.f4. PubMed 14734942 ↗
  • Jenders RA, Osheroff JA, Sittig DF, Pifer EA, Teich JM. Recommendations for clinical decision support deployment: synthesis of a roundtable of medical directors of information systems. AMIA Annu Symp Proc. 2007 Oct 11;2007:359-63. PubMed 18693858 ↗
  • Schulman J, Kuperman GJ, Kharbanda A, Kaushal R. Discovering how to think about a hospital patient information system by struggling to evaluate it: a committee's journal. J Am Med Inform Assoc. 2007 Sep-Oct;14(5):537-41. doi: 10.1197/jamia.M2436. Epub 2007 Jun 28. PubMed 17600095 ↗
  • Middleton B, Hammond WE, Brennan PF, Cooper GF. Accelerating U.S. EHR adoption: how to get there from here. recommendations based on the 2004 ACMI retreat. J Am Med Inform Assoc. 2005 Jan-Feb;12(1):13-9. doi: 10.1197/jamia.M1669. Epub 2004 Oct 18. PubMed 15492028 ↗
  • Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005 Mar 9;293(10):1223-38. doi: 10.1001/jama.293.10.1223. PubMed 15755945 ↗
  • Poon EG, Wald J, Bates DW, Middleton B, Kuperman GJ, Gandhi TK. Supporting patient care beyond the clinical encounter: three informatics innovations from partners health care. AMIA Annu Symp Proc. 2003;2003:1072. PubMed 14728575 ↗
  • Bakken S, Roberts WD, Chen E, Dilone J, Lee NJ, Mendonca E, Markatou M. PDA-based informatics strategies for tobacco use screening and smoking cessation management: a case study. Stud Health Technol Inform. 2007;129(Pt 2):1447-51. PubMed 17911954 ↗
  • Bindoff IK, Tenni PC, Peterson GM, Kang BH, Jackson SL. Development of an intelligent decision support system for medication review. J Clin Pharm Ther. 2007 Feb;32(1):81-8. doi: 10.1111/j.1365-2710.2007.00801.x. PubMed 17286791 ↗
  • Dickey J, Girard DE, Geheb MA, Cassel CK. Using systems-based practice to integrate education and clinical services. Med Teach. 2004 Aug;26(5):428-34. doi: 10.1080/01421590410001730967. PubMed 15369883 ↗
  • Grant RW, Wald JS, Poon EG, Schnipper JL, Gandhi TK, Volk LA, Middleton B. Design and implementation of a web-based patient portal linked to an ambulatory care electronic health record: patient gateway for diabetes collaborative care. Diabetes Technol Ther. 2006 Oct;8(5):576-86. doi: 10.1089/dia.2006.8.576. PubMed 17037972 ↗
  • Hsieh TC, Kuperman GJ, Jaggi T, Hojnowski-Diaz P, Fiskio J, Williams DH, Bates DW, Gandhi TK. Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J Am Med Inform Assoc. 2004 Nov-Dec;11(6):482-91. doi: 10.1197/jamia.M1556. Epub 2004 Aug 6. PubMed 15298998 ↗
  • Lester WT, Ashburner JM, Grant RW, Chueh HC, Barry MJ, Atlas SJ. Mammography FastTrack: an intervention to facilitate reminders for breast cancer screening across a heterogeneous multi-clinic primary care network. J Am Med Inform Assoc. 2009 Mar-Apr;16(2):187-95. doi: 10.1197/jamia.M2813. Epub 2008 Dec 11. PubMed 19074304 ↗
  • Lester WT, Grant R, Barnett GO, Chueh H. Facilitated lipid management using interactive e-mail: preliminary results of a randomized controlled trial. Stud Health Technol Inform. 2004;107(Pt 1):232-6. PubMed 15360809 ↗
  • Lester WT, Grant RW, Barnett GO, Chueh HC. Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease. J Gen Intern Med. 2006 Jan;21(1):22-9. doi: 10.1111/j.1525-1497.2005.00268.x. PubMed 16423119 ↗
  • Cowen M, Halasyamani LK, McMurtrie D, Hoffman D, Polley T, Alexander JA. Organizational structure for addressing the attributes of the ideal healthcare delivery system. J Healthc Manag. 2008 Nov-Dec;53(6):407-18; discussion 419. PubMed 19070335 ↗
  • Doebbeling BN, Chou AF, Tierney WM. Priorities and strategies for the implementation of integrated informatics and communications technology to improve evidence-based practice. J Gen Intern Med. 2006 Feb;21 Suppl 2(Suppl 2):S50-7. doi: 10.1111/j.1525-1497.2006.00363.x. PubMed 16637961 ↗
  • McGowan JJ, Cusack CM, Poon EG. Formative evaluation: a critical component in EHR implementation. J Am Med Inform Assoc. 2008 May-Jun;15(3):297-301. doi: 10.1197/jamia.M2584. Epub 2008 Feb 28. PubMed 18308984 ↗
  • Rind DM, Safran C, Phillips RS, Wang Q, Calkins DR, Delbanco TL, Bleich HL, Slack WV. Effect of computer-based alerts on the treatment and outcomes of hospitalized patients. Arch Intern Med. 1994 Jul 11;154(13):1511-7. PubMed 8018007 ↗
  • Ruland CM, Bakken S. Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration. J Biomed Inform. 2002 Oct-Dec;35(5-6):313-21. doi: 10.1016/s1532-0464(03)00037-6. PubMed 12968780 ↗
  • Crawford TN. Poor retention in care one-year after viral suppression: a significant predictor of viral rebound. AIDS Care. 2014;26(11):1393-9. doi: 10.1080/09540121.2014.920076. Epub 2014 May 21. PubMed 24848440 ↗
  • Yehia BR, French B, Fleishman JA, Metlay JP, Berry SA, Korthuis PT, Agwu AL, Gebo KA; HIV Research Network. Retention in care is more strongly associated with viral suppression in HIV-infected patients with lower versus higher CD4 counts. J Acquir Immune Defic Syndr. 2014 Mar 1;65(3):333-9. doi: 10.1097/QAI.0000000000000023. PubMed 24129370 ↗
  • Robertson M, Laraque F, Mavronicolas H, Braunstein S, Torian L. Linkage and retention in care and the time to HIV viral suppression and viral rebound - New York City. AIDS Care. 2015;27(2):260-7. doi: 10.1080/09540121.2014.959463. Epub 2014 Sep 22. PubMed 25244545 ↗
  • Hemming K, Haines TP, Chilton PJ, Girling AJ, Lilford RJ. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ. 2015 Feb 6;350:h391. doi: 10.1136/bmj.h391. No abstract available. PubMed 25662947 ↗
  • Wohlfeiler MB, Weber RP, Brunet L, Fusco JS, Uranaka C, Cochran Q, Palma M, Evans T, Millner C, Fusco GP. HIV retention in care: results and lessons learned from the Positive Pathways Implementation Trial. BMC Prim Care. 2022 Nov 23;23(1):297. doi: 10.1186/s12875-022-01909-2. PubMed 36424550 ↗

Individual participant data

Plan to share: No

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Feb 25, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04147832
Lead sponsor
Epividian
Collaborators
AIDS Healthcare Foundation, ViiV Healthcare
Responsible party
Sponsor
First posted
Nov 1, 2019
Start date
Oct 5, 2020
Primary completion
Jul 31, 2021
Completion
Jul 31, 2021
Last update
Feb 25, 2025

Study contacts

Michael Wohlfeiler, MD
principal investigator · AIDS Healthcare Foundation

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Aug 2021. You cannot join it, but the record below documents what was studied.

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