Expanding Data to Care Programs to Improve HIV Care Continuum Among Men Who Have Sex With Men and Transgender Persons: Key Processes and Outcomes From Project PrIDE, 2015-2019

Abstract

Objectives:

During 2015-2019, five local and state health department jurisdictions implemented Data to Care (D2C) programs supported by Project PrIDE (Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation) to improve linkage or reengagement in HIV medical care among persons with HIV (PWH) who had gaps in care, particularly among men who have sex with men (MSM) and transgender persons. We describe findings from the cross-jurisdiction evaluation of the project.

Methods:

We conducted a qualitative analysis of the final progress reports submitted by PrIDE jurisdictions to the Centers for Disease Control and Prevention to identify key D2C activities implemented and challenges encountered. We also conducted descriptive analysis on aggregate quantitative data to summarize key D2C program outcomes.

Results:

PrIDE jurisdictions implemented multiple activities to build their D2C capacity, identify PWH who were not in care or virally suppressed, provide linkage/reengagement services, and monitor outcomes. Overall, 11 463 PWH were selected for follow-up, 45% of whom were MSM or transgender persons. Investigations were completed for 8935 (77.9%) PWH. Only 2323 (26.0%) PWH were confirmed not in care or virally suppressed; 1194 (51.4%) were subsequently linked/reengaged in care; among those, 679 (56.9%) were virally suppressed at last test. PrIDE jurisdictions identified data-related (eg, incomplete or delayed laboratory results), program capacity (eg, insufficient staff), and social and structural (eg, unstable housing) challenges that affected their D2C implementation.

Conclusions:

PrIDE jurisdictions successfully enhanced their D2C capacity, reached priority populations who were not in care or virally suppressed, and improved their engagement in care and health outcomes. Data-related and non–data-related challenges limited the efficiency of D2C programs. Findings can help inform other D2C programs and contribute to national HIV prevention goals.

Nearly two-thirds of estimated HIV infections in the United States are attributed to persons who are aware of their HIV diagnosis but are not in care (NIC; 42.6%) and those receiving care but not virally suppressed (NVS; 19.8%). ¹ Approximately 20% of gay, bisexual, and other men who have sex with men (MSM) and transgender persons newly diagnosed with HIV in 2018 were not linked to care within 30 days of their diagnosis. ² One-third or more of MSM and transgender persons diagnosed during or before 2017 and alive in 2018 had markers of not being retained in care (ie, <2 CD4+ or viral load tests) or NVS (ie, viral load >200 copies/mL on a recent test). ² Racial and ethnic minority MSM and transgender persons, particularly Black/African American and Hispanic/Latino persons, have worse HIV continuum-of-care outcomes compared with non-Hispanic/Latino White MSM and transgender persons. ³

One goal of the US Department of Health and Human Services’ HIV National Strategic Plan for the United States: A Roadmap to End the Epidemic 2021-2025 is improving HIV-related health outcomes of persons with HIV (PWH). ⁴ Key activities to achieve this goal include identifying and engaging PWH who are NIC/NVS, increasing their retention in care and adherence to HIV treatment, and achieving sustained viral suppression. ⁴ Data to Care (D2C) is a public health strategy that uses HIV surveillance and other data to identify PWH who need medical care or other services, facilitate their linkage to these services, and improve their health outcomes.^5-7

There are 3 broad approaches to D2C implementation: health department, health care provider, and combined models. In the first 2 models, health departments and health care providers identify, investigate, and reach PWH who are NIC/NVS independently using HIV surveillance and medical records, respectively. The combined model involves collaborations between health departments and health care providers in identifying, investigating, and reaching PWH who are NIC/NVS. ⁵ D2C is an iterative process with some common operational steps, including (1) identifying and creating a list of PWH presumed NIC/NVS using surveillance or other data systems; (2) refining the NIC/NVS list by cross-checking information in other data systems and selecting PWH for follow-up; (3) conducting field investigations to contact those selected for follow-up; (4) determining care status and service needs of those contacted; (5) providing linkage/reengagement and other services for those with unmet needs; (6) monitoring program outcomes (eg, confirming care status); and (7) providing feedback to the surveillance system using information newly acquired during the D2C process.^5,6

Description of Project PrIDE

During 2015-2019, the Centers for Disease Control and Prevention (CDC) funded 5 local and state health department jurisdictions (Baltimore, Chicago, Houston, Louisiana, and San Francisco) to implement D2C programs through Project PrIDE (Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation). Project PrIDE supported jurisdictions to expand or enhance their capacity to use HIV surveillance and other data sources to improve outcomes along the HIV continuum of care for MSM and transgender persons, particularly persons of color, who were NIC/NVS. ⁸ Key expected outcomes included identifying and confirming PWH who were NIC/NVS, linking/reengaging them in care, and achieving viral suppression.

Purpose of Evaluation

For this demonstration project, the key goals of PrIDE evaluation were to learn from the implementation of D2C programs and share those lessons to inform future D2C programs. A 2-pronged evaluation strategy was adopted to assess progress toward these goals: (1) a cross-jurisdiction evaluation—a CDC-led evaluation activity designed to monitor implementation processes and outcomes of the project in all 5 jurisdictions, and (2) a local site-specific evaluation—a recipient-led evaluation whereby each jurisdiction conducted in-depth process or outcome evaluations on 1 or more of their Project PrIDE activities. ⁹ This article describes cross-jurisdiction evaluation findings on activities, outcomes, and challenges of D2C programs implemented in PrIDE jurisdictions.

Methods

Monitoring and Evaluation Questions

We addressed 3 evaluation questions:

1. What activities did PrIDE jurisdictions implement to support D2C programs for priority populations?

2. To what extent did PrIDE jurisdictions identify PWH presumptively NIC/NVS, confirm their care status and service needs, provide linkage/reengagement support, and monitor program outcomes among priority populations?

3. What were the key challenges encountered during implementation of D2C programs among priority populations?

Data Sources and Performance Indicators

We used qualitative and quantitative data from final progress reports submitted by PrIDE jurisdictions to CDC to answer the evaluation questions. Qualitative data included descriptions of activities implemented, key accomplishments, and notable challenges. Quantitative data included jurisdiction-level aggregate measures on D2C processes and outcomes, including the number of PWH (1) identified as presumptively NIC/NVS; (2) prioritized and selected for public health follow-up; (3) investigated and care status determined; (4) confirmed as NIC/NVS; (5) offered linkage/reengagement support; (6) linked/reengaged in care; and (7) virally suppressed. These indicators were stratified by age groups (13-29, 30-49, ≥50 years), race and ethnicity (Hispanic/Latino and non-Hispanic Black/African American, non-Hispanic White, and non-Hispanic “other” races, including American Indian/Alaska Native, Asian, Native Hawaiian/Other Pacific Islander, and persons of multiple races), assigned sex at birth (female, male), and key population categories (MSM, transgender persons regardless of their sexual orientation, heterosexual persons, and “other,” which included PWH with other HIV transmission risks [eg, blood transfusion, hemophilia] or PWH for whom HIV transmission risk was not identified). Data collection for this project constituted a routine program monitoring activity; therefore, CDC determined that institutional review board approval was not required.

Data Analysis

We conducted 2 sets of data analyses. First, we performed a simple qualitative content analysis to identify key D2C activities implemented and challenges encountered during the project. The analysis involved the following steps: (1) 2 authors (M.S.M., C.K.M.) independently reviewed the final progress reports to identify key activities and implementation challenges; (2) 4 other authors (J.W.C., C.A.G., W.D.J., A.L.W.), who also served as project officers, reviewed and confirmed the activities implemented and the challenges encountered in the jurisdictions they oversaw during the project; and (3) all authors reviewed and approved the final summary of implemented activities and challenges encountered. Second, following quality assurance procedures, we conducted descriptive analysis on the aggregate data for each performance indicator. In addition, for some program outcomes, we examined group differences between 2 proportions using z tests, where significance was ascertained at P < .05.

Results

Key D2C Activities Implemented

Qualitative analysis indicated that all PrIDE jurisdictions implemented multiple D2C program activities, including capacity building, primarily through hiring and training staff; formation of partnerships with health care and other essential service providers or other health departments; and development or adoption of D2C policies and procedures.

Jurisdictions used different D2C models: health department–based (n = 1), health care provider–based (n = 1), and a combined model (n = 3). As a result, initial D2C lists were generated using HIV surveillance, medical records, or a combination of data sources consistent with the D2C model chosen. All jurisdictions’ D2C lists included PWH presumed NIC; 3 jurisdictions also included PWH who were presumed NVS. Consistent with project objectives, all jurisdictions indicated that MSM, transgender persons, or both were prioritized for follow-up (Table 1). Jurisdictions used ≥4 data systems to supplement HIV surveillance or medical records, including sexually transmitted disease (STD) or hepatitis databases, people search databases (eg, Accurint), and justice system databases. Jurisdictions regularly updated their D2C lists manually or automatically (weekly or biweekly = 2; monthly = 2; and biannually = 1).

Table 1.

D2C model, prior experience, and characteristics of persons with HIV (PWH) who were selected for follow-up investigation, 5 Project PrIDE jurisdictions, 2015-2019

Item	Baltimore	Chicago	Houston	Louisiana	San Francisco
D2C referral model	Combined (ie, health department and health care provider–based)	Primarily health care provider–based	Combined (ie, health department and health care provider–based)	Primarily health department–based	Combined (ie, health department and health care provider–based)
D2C experience prior to Project PrIDE a	Limited or moderate	Limited or moderate	Limited or moderate	Extensive	Extensive
PWH included in D2C list b	Not in care + not virally suppressed	Not in care	Not in care	Not in care + not virally suppressed	Not in care + not virally suppressed
Operational definition of PWH “never in care”	No evidence of care prior to being placed on the D2C list among PWH diagnosed >13 months to 10 years ago (2009-2019)	No evidence of care prior to being placed on the D2C list; no time window specified	No evidence of care prior to being placed on the D2C list; no time window specified	No evidence of care prior to being placed on the D2C list among PWH diagnosed 9-12 months to 5 years ago	No evidence of care prior to being placed on the D2C list; no time window specified
Operational definition of PWH “lost to care”	No evidence of care in the past 18 months prior to being placed on the D2C list among PWH with a history of care	No evidence of care in the past 18 months prior to being placed on the D2C list among PWH with a history of care	No evidence of care in the past 12 months prior to being placed on the D2C list among PWH with a history of care	No evidence of care in the past 9-60 months prior to being placed on the D2C list among PWH with a history of care	No evidence of care in the past 12-15 months prior to being placed on the D2C list among PWH with a history of care
Operational definition of PWH with “high viral load”	PWH with viral load >10 000 copies/mL at last test (identified from surveillance data); PWH with viral load >1000 copies/mL at last test (identified from clinical or provider records)	Viral load values not specified as criteria for inclusion in the D2C list	Viral load values not specified as criteria for inclusion in the D2C list	PWH with viral load >1000 copies/mL in 2 recent tests conducted 90 days apart (identified from surveillance data)	PWH with viral load >1500 copies/mL at last test (identified from surveillance or clinical provider records)
Prioritized population groups	MSM and MSM/PWID	MSM and persons recently lost to care	Transgender persons, MSM, and persons of color	MSM and transgender persons of color; men with unidentified risks	Transgender, African American, and Hispanic/Latino persons

Abbreviations: D2C, Data to Care; MSM, gay, bisexual, and other men who have sex with men; PrIDE, Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation; PWID, persons who inject drugs.

^aAll jurisdictions or their implementation partners had some prior experience with D2C programs. However, Louisiana and San Francisco had implemented other D2C projects and published their experiences prior to Project PrIDE.

^b“Not in care” refers to PWH who were never in care or lost to care. “Not virally suppressed” refers to PWH with a high viral load; cutoff values for high viral load varied by jurisdiction or referral source.

All jurisdictions offered navigation services to HIV medical care. Also, linkage to behavioral health services (n = 5), social services (n = 4), medication adherence services (n = 4), and other HIV/STD prevention services (n = 3) was offered. The linkage/reengagement period ranged from 30 to 90 days after the date of referral for service, and outcomes were monitored via checking for laboratory markers of care or attendance of HIV medical care appointments. All jurisdictions reported outcomes for PWH who received linkage/reengagement services; 3 jurisdictions also checked surveillance records to determine if those who did not receive services were linked/reengaged in care on their own. All jurisdictions developed new or adopted existing protocols to update their HIV surveillance records with newly acquired information from D2C investigations. Four jurisdictions reported to CDC the number of surveillance records updated with new information.

Key D2C Processes and Outcomes

Overall, 18 546 PWH were identified as presumptively NIC/NVS (Figure). Of these, 11 463 (61.8%) were selected for follow-up investigations. The remaining were excluded after cross-checks with other data systems revealed they were deceased, out of jurisdiction, already in care, or virally suppressed. By the end of the project, follow-up investigations were completed for 8935 (77.9%) PWH. Of these, 4239 (47.4%) were deceased, incarcerated, living out of jurisdiction, or not located; 2373 (26.6%) were confirmed to be in care or virally suppressed; and 2323 (26.0%) were confirmed NIC/NVS.

Figure.

Number and percentage of persons with HIV (PWH) at each step in the Data to Care (D2C) process, 5 Project PrIDE jurisdictions, 2015-2019. The 5 Project PrIDE health department jurisdictions were Baltimore, Chicago, Houston, Louisiana, and San Francisco. Health departments applied different inclusion criteria to determine a priority for investigation (eg, PWH who are in the PrIDE-supported metropolitan statistical areas). Follow-up investigations were considered “completed” if a disposition about PWH’s location, care status, or another outcome was determined. “Other outcomes” include death, incarceration, living out of jurisdiction, or other unspecified disposition. PWH were “confirmed to be not in care or virally suppressed” if they were contacted during the field investigation and verified to need linkage/reengagement in care or assistance to achieve viral suppression. PWH were considered “linked/reengaged” in care if they had attended their first HIV medical appointment or had documented viral load test or CD4+ count following contact with linkage/reengagement workers. PWH were considered “virally suppressed” if they achieved a viral load of <200 copies/mL of blood on their recent test. Abbreviation: PrIDE, Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation.

Of the 2323 PWH confirmed as NIC/NVS, linkage/reengagement services were offered and accepted by 1173 (50.5%). Linkage/reengagement in care was 83.8% (983 of 1173) among those who accepted services and 18.3% (211 of 1150) among those who were not offered or declined services. Taken together, 1194 (51.4%) of the 2323 PWH confirmed NIC/NVS were linked/reengaged in care following contact with D2C programs. Of these, only 477 (20.5%) were linked/reengaged in care within 30 days, and 679 (56.9%) achieved viral suppression at last test. Surveillance records of only 1043 PWH were updated based on newly acquired information from data-matching processes and field investigations, partly because 1 jurisdiction was unable to track data and another only partially tracked data fed back to the surveillance system from its relatively new D2C program.

PrIDE priority populations accounted for 45.0% (MSM: 42.8%; transgender persons: 2.2%) of PWH who were selected for investigations. Non-Hispanic Black/African American PWH (55.3%), males (66.9%), and those aged 30-49 (43%) represented the largest groups by race and ethnicity, sex, and age, respectively. Investigations were more likely to be completed among non-Hispanic Black/African American persons (90.1%; z = 2.93; P < .001) and Hispanic/Latino persons (93.2%; z = 5.42; P < .001) but less likely to be completed among non-Hispanic other racial and ethnic groups (80.6%; z = −3.11; P = .002) compared with non-Hispanic White persons (87.6%). Investigations were more likely to be completed among PWH aged 30-49 (88.2%; z = 7.35; P < .001) and ≥50 (86.8%; z = 5.17; P < .001) than among PWH aged 13-29 years (81.6%). Completion of investigation was also slightly more likely among males (90.6%) than among females (89.0%; z = −2.23; P = .03). We found no difference between the priority populations and heterosexual persons in completion of investigations.

Among PWH whose investigations were completed, MSM were less likely (16.9%; z = −8.62; P < .001) and transgender persons were equally likely (23.7%; z = −0.84; P = .40) than heterosexual persons (26.3%) to be confirmed NIC/NVS. Non-Hispanic Black/African American persons (29.5%) compared with non-Hispanic White persons (18.1%; z = 8.60; P < .001) and females (35.3%) compared with males (23.4%; z = 10.60; P < .001) were more likely to be confirmed NIC/NVS. Adults aged 30-49 (25.1%) were less likely than persons aged 13-29 years (28.5%; z = −2.72; P = .007) to be confirmed NIC/NVS (Table 2).

Table 2.

Outcomes of Data to Care follow-up investigations among PWH presumed not in care or virally suppressed, by demographic characteristics, 5 Project PrIDE jurisdictions, 2015-2019 ^a

Demographic characteristic	Selected for follow-up investigation, no. (column %)	Investigation completed b		Found to be in HIV medical care or virally suppressed c		Confirmed not in care or virally suppressed c
		No. (row %)	z (P value) d	No. (row %)	z (P value) d	No. (row %)	z (P value) d
Race and ethnicity
Non-Hispanic White	1604 (14.0)	1405 (87.6)	Reference	428 (30.5)	Reference	254 (18.1)	Reference
Non-Hispanic Black/African American	6340 (55.3)	5714 (90.1)	2.93 (.003)	1484 (26.0)	−3.41 (.001)	1685 (29.5)	8.60 (<.001)
Hispanic/Latino (all races)	1639 (14.3)	1527 (93.2)	5.42 (<.001)	395 (25.9)	−2.77 (.006)	318 (20.8)	1.84 (.07)
Non-Hispanic other e	268 (2.3)	216 (80.6)	−3.11 (.002)	48 (22.2)	−2.49 (.01)	41 (19.0)	0.32 (.75)
Missing	1612 (14.1)	73 (4.5)	−51.06 (<.001)	18 (24.7)	−1.05 (.29)	25 (34.2)	3.43 (.001)
Age, y
13-29	2089 (18.2)	1705 (81.6)	Reference	470 (27.6)	Reference	486 (28.5)	Reference
30-49	4980 (43.4)	4391 (88.2)	7.35 (<.001)	1169 (26.6)	−0.79 (.43)	1102 (25.1)	−2.72 (.007)
≥50	3268 (28.5)	2838 (86.8)	5.17 (<.001)	733 (25.8)	−1.33 (.18)	735 (25.9)	−1.91 (.06)
Missing	1126 (9.8)	1 (0.1)	−44.17 (<.001)	1 (100.0)	—	0	—
Sex
Male	7666 (66.9)	6943 (90.6)	Reference	1802 (26.0)	Reference	1623 (23.4)	Reference
Female	2198 (19.2)	1957 (89.0)	−2.23 (.03)	565 (28.9)	2.56 (.01)	690 (35.3)	10.60 (<.001)
Missing	1599 (13.9)	35 (2.2)	−74.60 (<.001)	6 (17.1)	−1.20 (.23)	10 (28.6)	0.73 (.47)
Key population group
Heterosexual	2311 (20.2)	1970 (85.2)	Reference	586 (29.7)	Reference	519 (26.3)	Reference
MSM	4901 (42.8)	4201 (85.7)	0.56 (.57)	1087 (25.9)	−3.13 (.002)	709 (16.9)	−8.62 (<.001)
Transgender persons	255 (2.2)	224 (87.8)	1.12 (.26)	41 (18.3)	−3.58 (<.001)	53 (23.7)	−0.84 (.40)
Other f	1086 (9.5)	990 (91.2)	4.87 (<.001)	256 (25.9)	−2.16 (.03)	422 (42.6)	8.99 (<.001)
Missing	2910 (25.4)	1550 (53.3)	−24.43 (<.001)	403 (26.0)	−2.43 (.02)	620 (40.0)	8.63 (<.001)
Total	11 463 (100.0)	8935 (77.9)	—	2373 (26.6)	—	2323 (26.0)	—

Abbreviations: —, not applicable; MSM, gay, bisexual, and other men who have sex with men; PrIDE, Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation; PWH, persons with HIV.

^aThe 5 Project PrIDE health department jurisdictions funded to implement Data to Care projects were Baltimore, Chicago, Houston, Louisiana, and San Francisco.

^bRow percentages for column “Investigation completed” were based on the total number of persons selected for follow-up. Investigation was completed when an outcome was determined (ie, when the person was determined to be incarcerated, out of jurisdiction, deceased, in care, or out of care).

^cRow percentages for columns “Found in HIV medical care or virally suppressed” and “Confirmed not in care or virally suppressed” were based on the total number of persons for whom follow-up investigation was completed.

^dz tests used to examine group differences between 2 proportions, where significance was ascertained at P < .05.

^eIncludes American Indian/Alaska Native, Asian, Native Hawaiian/Other Pacific Islander, and persons of multiple races.

^f“Other” in key population group included PWH who had other HIV transmission risks (eg, blood transfusion, hemophilia) and PWH for whom HIV transmission risk was not identified.

Acceptance of linkage/reengagement services was higher among non-Hispanic Black/African American persons (49.6%; z = 2.46; P = .01) and Hispanic/Latino persons (61.9%; z = 4.91; P < .001) than among non-Hispanic White persons (41.3%). Acceptance of services was lower among PWH aged 30-49 (50.4%; z = −6.92; P < .001) and ≥50 (38.4%; z = −10.50; P < .001) than among persons aged 13-29 years (69.1%). We found no difference between the priority populations and heterosexual persons and between males and females in acceptance of services (Table 3).

Table 3.

HIV care outcomes among PWH confirmed not in care or virally suppressed, 5 Project PrIDE jurisdictions, 2015-2019 ^a

Demographic characteristic	Total confirmed NIC/NVS, no. (column %)	Accepted linkage/reengagement services b		Confirmed as linked/reengaged in care b		Virally suppressed at last test c
		No. (row %)	z (P value) d	No. (row %)	z (P value) d	No. (row %)	z (P value) d
Race and ethnicity
Non-Hispanic White	254 (10.9)	105 (41.3)	Reference	144 (56.7)	Reference	106 (73.6)	Reference
Non-Hispanic Black/African American	1685 (72.5)	836 (49.6)	2.46 (.01)	846 (50.2)	−1.93 (.06)	445 (52.6)	−4.69 (<.001)
Hispanic/Latino (all races)	318 (13.7)	197 (61.9)	4.91 (<.001)	175 (55.0)	−0.41 (.68)	107 (61.1)	−2.36 (.02)
Other e	41 (1.8)	23 (56.1)	1.77 (.08)	21 (51.2)	−0.66 (.51)	18 (85.7)	1.20 (.23)
Missing	25 (1.1)	12 (48.0)	0.64 (.52)	8 (32.0)	−2.37 (.02)	3 (37.5)	−2.21 (.03)
Age, y
13-29	486 (20.9)	336 (69.1)	Reference	274 (56.4)	Reference	135 (49.3)	Reference
30-49	1102 (47.4)	555 (50.4)	−6.92 (<.001)	578 (52.5)	−1.44 (.15)	332 (57.4)	2.22 (.03)
≥50	735 (31.6)	282 (38.4)	−10.50 (<.001)	342 (46.5)	−3.39 (.001)	212 (62.0)	3.16 (.002)
Sex
Male	1623 (69.9)	828 (51.0)	Reference	842 (51.9)	Reference	508 (60.3)	Reference
Female	690 (29.7)	343 (49.7)	−0.50 (.57)	352 (51.0)	−0.40 (.69)	171 (48.6)	−3.72 (<.001)
Missing	10 (0.4)	2 (20.0)	−1.95 (.05)	0	—	0	—
Key population group
Heterosexual	519 (22.3)	242 (46.6)	Reference	295 (56.8)	Reference	167 (56.6)	Reference
MSM	709 (30.5)	331 (46.7)	0.04 (.97)	403 (56.8)	0 (>.99)	262 (65.0)	2.25 (.02)
Transgender persons	53 (2.3)	29 (54.7)	1.13 (.26)	24 (45.3)	−1.61 (.11)	13 (54.2)	−0.23 (.82)
Other f	858 (36.9)	502 (58.5)	4.29 (<.001)	412 (48.0)	−3.17 (.002)	193 (46.8)	−2.57 (.01)
Missing	184 (7.9)	69 (37.5)	−2.14 (.03)	60 (32.6)	−5.64 (<.001)	44 (73.3)	2.40 (.02)
Total	2323 (100.0)	1173 (50.5)	—	1194 (51.4)	—	679 (56.9)	—

Abbreviations: MSM, gay, bisexual, and other men who have sex with men; NIC, not in care; NVS, not virally suppressed; PrIDE, Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation; PWH, persons with HIV.

^aThe 5 Project PrIDE health department jurisdictions funded to implement Data to Care projects were Baltimore, Chicago, Houston, Louisiana, and San Francisco.

^bRow percentages for columns “Accepted linkage/reengagement services” and “Confirmed as linked/reengaged” were based on the total number of persons confirmed not in care or virally suppressed. The number of persons “Confirmed as linked/reengaged in care” can be among those who were provided linkage/reengagement services or those who did not receive services but determined to be linked/reengaged in care on their own after checks in the surveillance system.

^cDenominator for row percentages for “Virally suppressed at last test” was the number of persons “Confirmed as linked/reengaged in care.”

^dz tests used to examine group differences between 2 proportions, where significance was ascertained at P < .05.

^eIncludes non-Hispanic American Indian/Alaska Native, Asian, Native Hawaiian/Other Pacific Islander, and persons of multiple races.

^f“Other” in key population group included PWH who had other HIV transmission risks (eg, blood transfusion, hemophilia) and PWH for whom HIV transmission risk was not identified.

Linkage/reengagement in care was similar between priority populations and heterosexual persons and across age, sex, and racial and ethnic groups. However, viral suppression was lower among non-Hispanic Black/African American persons (52.6%; z = −4.69; P < .001) and Hispanic/Latino persons (61.1%; z = −2.36; P = .02) than among non-Hispanic White persons (73.6%). Viral suppression was higher among MSM (65.0%; z = 2.25; P = .02) but not among transgender persons (57.4%; z = −0.23; P = .82) when compared with heterosexual persons (56.6%). Viral suppression was also higher among PWH aged 30-49 (57.4; z = −2.22; P = 0.03) and ≥50 (62.0%; z = 3.16; P = .002) than among PWH aged 13-29 years (49.3%). More male PWH achieved viral suppression (60.3%; z = −3.72; P < .001) than female PWH (48.6%).

Key D2C Implementation Challenges

Qualitative data analysis identified several D2C program implementation challenges, which we classified into 3 themes: data-related challenges, program capacity–related challenges, and social and structural challenges (Table 4). Data-related challenges were common and included limitations in data systems, data quality, and data sharing or reporting. The most consistently reported data-related challenge was data incompleteness due to delays in laboratory results or challenges in integrating surveillance and other data systems. Data incompleteness led to substantial misclassification of PWH as NIC/NVS and wasted limited D2C resources. In jurisdictions with limited D2C experience, building, upgrading, or using an integrated data system was identified as a major challenge. Program capacity–related challenges included difficulties in staffing (mainly delays in hiring and high staff turnover) and collaborating with partner agencies to implement D2C activities, particularly in jurisdictions with a combined health department–provider D2C model. Social and structural challenges included D2C client-related social factors (eg, substance use disorder, unstable housing) and provider-related structural factors (eg, complexity of health care system, lack of gender-affirming providers) that served as barriers to engagement in care.

Table 4.

Summary of challenges encountered during implementation of Data to Care (D2C) programs, 5 Project PrIDE jurisdictions, 2015-2019 ^a

Category of key challenges	Specific examples of challenges encountered
Data-related challenges
1. Data system challenges	• Delays in building integrated data systems or reporting tools • Complexity of upgrading existing data systems or reporting tools • Difficulty of learning to use complex data systems or reporting tools • Fragmentation of data systems used in health care and other service provider agencies
2. Data quality challenges	• Misclassification of D2C clients as “not in care” or “not virally suppressed” for the following reasons: ○ Incomplete or incorrect surveillance or clinical data (eg, missing laboratory data, unconfirmed false-positive test results) ○ Incomplete matching or integration of surveillance and other data systems ○ Infrequent updates to the D2C list by cross-checking it against current surveillance or other databases • Limitations in data quality assurance practices, including in identifying and correcting errors in data entry, verification, or reporting • Absence of key data elements in surveillance data to identify priority populations (eg, lack of current gender information to identify transgender persons)
3. Data access and sharing challenges	• Inability of project staff to access relevant databases (eg, Veterans Administration, Ryan White case manager, or partner agency clinical data) to verify care status • Insufficient or delayed access to surveillance data by project staff, particularly in jurisdictions where the surveillance system is not under PrIDE recipient’s health department • Difficulty reaching consensus about how surveillance and program data can be shared between partner agencies for confidentiality and data security reasons • Lengthy and resource-intensive process to conduct record searches and identify clients who might benefit from D2C programs • Infrequent feedback to field staff and back from field staff to surveillance because of data system and implementation challenges
4. Data collection and reporting challenges	• Short window for reporting program outcomes for the project led to unknown outcomes for cases under investigation • Difficulty of collecting D2C program outcomes for clients referred to external service providers • Unanticipated amount of data reporting required from partner agencies to fully implement D2C programs • Inconsistencies in data collection and reporting practices among partner agencies
Program capacity–related challenges
5. Staffing challenges	• Delays in hiring or fully staffing project positions • Delays in D2C-related staff training • Trouble retaining staff or high staff turnover • Budget cuts that eliminate staff positions and activities • Heavy workload on linkage/reengagement staff • Lack of culturally competent staff to serve priority populations
6. Collaboration challenges	• Difficulty in forming and sustaining collaborations between multiple partner agencies • Delays in getting buy-in from the leadership of partner agencies about project processes and outcomes • Inconsistencies in D2C implementation between partner agencies
Social and structural challenges
7. Client-related social challenges	• Comorbidities (eg, mental health or substance use disorders) faced by D2C clients that interfere with linkage or retention in HIV medical care • Social and structural barriers (eg, unstable housing, low health literacy, systemic racism, homophobia, transphobia) that prevent D2C clients from linking and retaining in HIV medical care • Mistrust of the health care system or hesitation to obtain services from government agencies
8. Provider-related structural challenges	• Lack of culturally competent and affirming providers and services to priority populations • Complexity of navigating D2C clients through the health care system • Lengthy and resource-intensive process to provide outreach and link or reengage D2C clients

Abbreviation: PrIDE, Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation.

^aThe 5 Project PrIDE health department jurisdictions funded to implement D2C projects were Baltimore, Chicago, Houston, Louisiana, and San Francisco.

Lessons Learned

PrIDE jurisdictions implemented multiple D2C program activities to improve linkage/reengagement in care and health outcomes among PWH who were confirmed NIC/NVS. As expected, jurisdictions conducted activities to enhance their D2C capacity; generated, cross-checked, and prioritized lists of PWH for follow-up; conducted field investigations; determined care status and unmet needs; provided linkage/reengagement services when indicated; monitored program outcomes; and updated surveillance records with newly acquired information. However, jurisdictions varied in the D2C models used, the criteria for inclusion in the D2C list, and the specific outreach and linkage/reengagement strategies adopted.

Field Investigation of PWH in Need of Engagement in Care

Overall, PrIDE jurisdictions completed follow-up investigations for 78% of >11 000 PWH presumed NIC/NVS, indicating operational success in the initial phases of the D2C process. However, outcomes of subsequent D2C steps indicated both successes and challenges with the strategy.

Nearly one-half of the PWH on the D2C list could not be located or were out of jurisdiction, incarcerated, or deceased, even after the initial D2C list was cross-checked against multiple databases. This challenge, however, is not unique to Project PrIDE, as other D2C studies reported that high percentages (>50%) of PWH investigated could not be reached^6,10 and attributed the challenge to incomplete or out-of-date contact information in surveillance or medical records, inability to effectively integrate data, failure to share data across agencies in a timely fashion, and social or structural barriers encountered by PWH (eg, lack of stable housing).^10-12 These factors were also identified by PrIDE jurisdictions as challenges to their D2C implementation.

Approximately 26% of PWH investigated were confirmed NIC/NVS, consistent with similar programs that confirmed 20% to 40% of PWH on their D2C list were NIC.^6,13-17 PrIDE jurisdictions also found one-fourth of PWH investigated were already in care or virally suppressed. Other D2C investigations found 10% to 45% of PWH were current with their care.^13,15-19 These findings highlight the inefficiency of existing data systems to generate accurate lists of PWH who need linkage/reengagement in HIV medical care. Beyond data limitations, studies indicate that PWH sometimes appear out of care because they are directed by clinicians to wait longer between visits, particularly when they have achieved sustained viral suppression. ¹⁴ Similarly, PrIDE jurisdictions identified several data system, access, and quality challenges that could have affected the accuracy of their D2C lists.

Overall, MSM and transgender persons accounted for about half of the PWH who were investigated. Compared with heterosexual persons, MSM and transgender persons were less likely or equally likely to be confirmed NIC/NVS, which implies that the priority groups may be current with care and have their care status accurately documented. In contrast, the higher likelihood of being NIC/NVS among non-Hispanic Black/African American persons, persons aged 13-29 years, and females suggests that D2C programs need to prioritize these groups to address HIV-related disparities.

Provision and Outcomes of Linkage/Reengagement Services

PrIDE jurisdictions were successful in offering linkage/reengagement services, including treatment adherence support, to 87.5% of PWH confirmed NIC/NVS. Of these, 57.7% accepted linkage/reengagement services, comparable to 59.2% acceptance of similar services in another D2C demonstration project. ⁶ Programmatic challenges reported by PrIDE jurisdictions (eg, distrust of public health agencies, unmet housing and mental health needs) may explain why linkage/reengagement services were not accepted when offered. Linkage/reengagement services were equally likely to be accepted by priority groups and heterosexual persons and more likely to be accepted by persons in racial and ethnic minority groups (vs non-Hispanic White persons) and younger PWH (vs older PWH). This level of acceptance is encouraging given that these groups shoulder the burden of HIV and may have a greater need for these services.

PrIDE jurisdictions linked/reengaged in care 51% of persons who were confirmed NIC/NVS. As expected, linkage/reengagement in care was 83.8% for PWH who accepted services offered by PrIDE jurisdictions, which is comparable to the 87.4% linkage/reengagement found in another D2C demonstration project. ⁶ Other studies reported linkage/reengagement percentages ranging from 63% to 78% in different D2C models and settings.^14-17 Clearly, services provided by PrIDE jurisdictions were effective, but they were time consuming given that D2C programs needed >30 days to link/reengage most PWH confirmed as NIC/NVS. The finding that linkage/reengagement outcomes were similar by race and ethnicity, age, sex, and key population categories suggests that D2C-initiated services may facilitate equity in HIV care engagement.

Slightly more than half (56.9%) of PWH who were linked/reengaged in care through D2C programs achieved viral suppression at their last test, which is comparable to findings of other D2C studies that reported viral suppression for 48% ²⁰ and 53% ²¹ of PWH following linkage/reengagement services. However, at the national level, viral suppression among persons who received care in 2018 was much higher, at 85.4%, ² indicating that PWH in need of D2C programs may need intensive support to remain in HIV care and treatment, and D2C programs may need to collaborate with other programs (eg, extended patient navigation, social services) to ensure the availability of needed support services.

Compared with heterosexual persons, MSM and transgender persons were equally likely to be linked/reengaged in care and achieve viral suppression, suggesting potential effectiveness of D2C programs in reducing gaps in care and improving HIV-related health outcomes for the priority populations. In contrast, racial and ethnic minority groups, particularly non-Hispanic Black/African American and Hispanic/Latino persons, were less likely to achieve viral suppression compared with non-Hispanic White persons, consistent with observations at the national level. ² This finding suggests that D2C programs must address unique social and structural barriers to staying in care and treatment among racial and ethnic minority communities.

Improving Surveillance Records Using Newly Acquired Information

An important outcome for D2C programs is improvement of surveillance records with newly acquired information from data cross-checks or field investigations. Although all PrIDE jurisdictions developed protocols for feeding back information to their surveillance system, only a small proportion of surveillance records (<12% of investigated PWH) were improved, partly because of challenges in implementing and monitoring the feedback process in jurisdictions with relatively limited D2C program experience. Integration of D2C activities with already established surveillance protocols might facilitate the collection and transfer of information from the D2C program back to the surveillance system.

Limitations

Our evaluation approach had several limitations. First, we chose a simple approach to summarize the qualitative information about the activities implemented and the challenges encountered. A more in-depth analysis could help uncover other important dimensions of D2C programs. Second, the quantitative data were reported to CDC in aggregate at the jurisdiction level. These data may have been subject to aggregation and other reporting biases and failed to provide specific information about the experiences of D2C clients. Third, the evaluation was not designed to assess the effectiveness of D2C relative to other linkage strategies or the long-term effects of the projects. We did not have comparison groups to eliminate other potential reasons for observed outcomes, nor did we track changes in challenges encountered and program outcomes over time. Fourth, we found variations in program implementation, monitoring, and evaluation across jurisdictions. Findings reported in this evaluation may not have captured important programmatic nuances. Fifth, linkage/reengagement and viral suppression outcomes may have been underestimated in some jurisdictions because of delays in laboratory data or inadequate time to document those outcomes. Sixth, jurisdictions were asked to report in aggregate all transgender-identified persons as “transgender persons” regardless of their sexual orientation. Because of this data reporting method, we were unable to disaggregate data for transgender persons who were also MSM from those who were not. Lastly, we were unable to separate data by referral source (health department vs provider model) or by care and viral suppression status (NIC vs NVS) because of aggregate data reporting.

Conclusions

Our findings show that PrIDE jurisdictions implemented multiple activities and enhanced their D2C capacity; reached MSM, transgender persons, and racial and ethnic minority populations who were confirmed NIC/NVS; and successfully improved their engagement in care and health outcomes. Both qualitative and quantitative data indicate challenges that must be addressed to improve the efficiency of D2C programs, including data-related challenges, limited program capacity, and social and structural barriers that affect delivery and acceptance of services. Lessons from this demonstration project can inform the planning and implementation of other D2C programs and contribute to the national goal of ending the HIV epidemic in the United States by supporting efforts to improve linkage/reengagement in HIV medical care and health outcomes among PWH.