Use of a real-time alert system to identify and re-engage lost-to-care HIV patients Melanie L. Fritza Ronald J. Lubelchek, MD a, b, c* Katelynne J. Finnegan, MPHa William E. Trick,c, d a. Ruth M. Rothstein CORE Center b. Division of Infectious Diseases, John H. Stroger, Jr. Hospital of Cook County c. Department of Internal Medicine, John H. Stroger, Jr. Hospital of Cook County d. Collaborative Research Unit, John H. Stroger, Jr. Hospital of Cook County

Presenter Disclosures Melanie Fritz (1) The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months: No relationships to disclose

HIV new infection rate holding steady since ~2009 Introduction HIV new infection rate holding steady since ~2009 MSM 12% (2008-2010) Young MSM 22% (2008-2010) Young, Black MSM 43% (2006-2009)

linkage to care and retention in care predict better outcomes Diagnosed Linked to Care Retained in Care Prescribed antiretroviral therapy Virally Suppressed Outcomes Improved patient health Reduced transmission in community

Patient-navigation based techniques An EMR-Based Alert Intervention Patient-navigation based techniques Health information technology

Methodology

Setting and Patients Included Ruth M Rothstein CORE CENTER John H Stroger Hospital Patients lost to care for over 7 months

Alert Design Staff log onto password- protected website to access patient and registration event information. Clerk registers patient at CCHHS clinical site Registration information transmitted to Collaborative Research Unit server in real time Query cross references registration information with list of RMR CORE Center lost-to- care patients 1 2 3 Real time alert notifies program staff member 4 5

Outreach Intervention Response to Alert Receive Alert Chart Review Outreach Intervention

Results

Appointment already in system 60 (52%) No appointment in the system 398 Alerts Received Unique patients 198 (50%) Included in analysis 115 (58%) Repeat alerts Appointment already in system 60 (52%) No appointment in the system 55 (48%) In-person outreach 22 (40%) Phone outreach 33 (60%)   Contacted 13 (39%) Unable to contact 20 (61%) No Outreach Attempted Excluded from analysis 83 (42%) Figure2: Summary of lost-to-care patients living with HIV/AIDS triggering our real-time alert system between April 1, 2014 to September 30, 2014

Appt in system (no intervention) Table 1: Demographic/clinical characteristics and rate of return-to-care for alert-triggering lost-to-care HIV+ patients   Appt in system (no intervention) N=60 Successful contact N=35 No successful contact N=20 Total N=115 p-valuea Mean age (95% CI) 46 (43 – 48) 45 (42 -49) 44 (40 – 47) 45 (43 – 47) p = 0.53 Gender Males (%) 43/60 (72) 28/35 (80) 12/20 (60) 83/115 (72) p = 0.28 Race African American (%) 47/60 (78) 25/35 (71) 18/20 (90) 90/115 (78) Ethnicity Hispanic (%) 7/60 (12) 6/35 (17) 1/20 (5) 14/115 (12) p = 0.47 HIV risk factor Men who have sex with men (%) 14/44a (31) 10/24 (42) 7/17 (23) 31/85 (36) p = 0.65

Appt in system (no intervention) Table 1: Demographic/clinical characteristics cont’d   Appt in system (no intervention) N=60 Successful contact N=35 No successful contact N=20 Total N=115 p-valuea Mean time lost to care, days (95% CI) 387 (343 – 431) 316 (270 – 362) 393 (301 – 485) 366 (335 – 398) p = 0.11 Time lost to care < 1 year (%) 39/60 (65) 26/35 (74) 12/20 (60) 77/115 (67) p = 0.49 Median CD4, cells/ml3 (25-75%) 325 (162 – 462) 352 (212 – 517) 321 (157 – 714) 331 (192 – 512) p = 0.71 HIV viral load undetectable (%) 26/54 (48) 23/33 (69) 6/17 (35) 55/104 (53) p = 0.04 Patient attended primary care appt. within 3 months of prompt (%) 44/60 (73) 29/35 (83) 9/20 (45) 82/115 (71) p = 0.01

Table 2: Logistic regression for associations with not following up for care within three months for lost-to-care HIV+ patients   Odd’s ratioa 95% confidence interval p-value Age ≥ 45 years < 45 ref 0.90 0.25 – 3.923 p = 0.87 Gender Male Female 1.61 0.36– 7.19 p = 0.53 Race Non-African American African American 4.18 0.56 – 31.26 P = 0.16 Ethnicity Hispanic Non-Hispanic 0.09 0.01 – 1.62 p = 0.10 HIV risk factor MSM Non-MSM 0.64 0.14 – 2.82 p = 0.56 Time lost-to-care < 1 year < 1 year > 1 year 1.09 0.29 – 4.11 p = 0.90

In-Person Contact: 86% follow-up Table 2: Logistic regression cont’d   Odd’s ratioa 95% confidence interval p-value CD4 count closest to index visit ≥ 200 cells/ml3 < 200 cells/ml3 ref 0.25 0.06 – 0.99 p = 0.05 HIV viral load Undetectable > 40 copies/ml3 1.38 0.35 – 5.40 p = 0.65 Contact success Contacted alert patient Appt. already in system Unable to contact alert patient 1.13 0.15 0.25 – 5.11 0.03 – 0.89 P = 0.87 P = 0.04 On method of contact In-Person Contact: 86% follow-up Attempted Phone Contact: 58% follow-up

Discussion Scheduling an appointment = more likely to return to care In-person contact success rate Phone contact success rate Conclusion: This is one example of a successful intervention.

Limitations No randomized control group Moderate number of patients Located within a single health system

Future Opportunities Utilize alert system as less-intensive intervention Explore more intensive targeted interventions for harder-to-engage patients Regional Health Information Exchange with other health systems

acknowledgements HIV Treatment Cascade administrative supplemental funding from the Chicago Developmental Center for AIDS Research (P30 AI 082151, Alan Landay, Principal Investigator). Anna Hotton, PhD for input on our analysis. Alex Patino, George Markovski, and Francisco Angulo for building the text messaging and secure website alert system.

Thank you! Any questions? Melanie Fritz mfritz3@cookcountyhhs.org