- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04147832
Epividian / AHF: Positive Pathways - HIV Retention in Care
Epividian, Inc. and AIDS Healthcare Foundation: Positive Pathways - HIV Retention in Care RIC-20190212 (Pro00037143)
Study Overview
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.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
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California
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Los Angeles, California, United States, 90028
- AHF
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- HIV-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:
- Patients known to have left the practice
- Patients who choose not to be contacted about their care via telephone
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
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.
|
Provider will receive an alert of sub-optimal patient attendance using 4 rules.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Rate of Kept Appointments
Time Frame: 16 months, 01-Nov-2019 to 30-Apr-2021
|
Pre and post-baseline rate of patients who attended their scheduled office visits.
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16 months, 01-Nov-2019 to 30-Apr-2021
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Viral suppression
Time Frame: 16 months, 01-Nov-2019 to 30-Apr-2021
|
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
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16 months, 01-Nov-2019 to 30-Apr-2021
|
Ranked Scoring of Implementation effectiveness
Time Frame: 16 months, 01-Nov-2019 to 30-Apr-2021
|
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.
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16 months, 01-Nov-2019 to 30-Apr-2021
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Collaborators and Investigators
Sponsor
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- RNA Virus Infections
- Virus Diseases
- Infections
- Blood-Borne Infections
- Communicable Diseases
- Sexually Transmitted Diseases, Viral
- Sexually Transmitted Diseases
- Lentivirus Infections
- Retroviridae Infections
- Immunologic Deficiency Syndromes
- Immune System Diseases
- Slow Virus Diseases
- HIV Infections
- Acquired Immunodeficiency Syndrome
Other Study ID Numbers
- Pro00037143
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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