HIV testing in a high prevalence urban area in the US: Identifying missed opportunities two ways

Abstract

Background

Routine opt-out HIV testing in healthcare settings is often not implemented to its fullest extent. We assessed factors contributing to missed HIV testing opportunities at an academic medical center in Chicago, Illinois, with a routine HIV screening program.

Methods

Retrospective analysis of HIV testing in clinical encounters was performed using multivariate regession models. Missed opportunities were defined as 1) an encounter during which an HIV test was not conducted on a patient later diagnosed with HIV, or 2) an encounter in which a bacterial STI test was performed without HIV testing.

Results

Of 122 people newly diagnosed with HIV from 2011-2018, 98 patients had 1215 prior encounters, of which 82.8% were missed opportunities. Female gender, persons not known to be men who have sex with men, and encounter location other than inpatient had higher odds of a missed opportunity. Nearly half (48.4%) of 104,678 bacterial STI testing encounters were missed opportunities. Female gender, older age, lack of syphilis testing, and location outside the emergency department had higher odds of a missed opportunity.

Conclusions

We found a high number of missed HIV testing opportunities, which could be reduced by strengthening routine screening and increasing targeted testing concurrent with STI screening.

Keywords

HIV viral disease screening

Introduction

Routine screening for human immunodeficiency virus (HIV) is recommended for all individuals aged 13–64 years once in a lifetime and at least annually for persons at risk for infection per the United States Centers for Disease Control and Prevention (CDC).^1,2 In addition, all persons presenting for sexually transmitted infection (STI) evaluation are recommended to undergo HIV screening regardless of other risk factors and past HIV testing.³ Despite this policy, an estimated 13% of people living with HIV (PLWH) remain unaware of their diagnosis in the United States (US), and late diagnosis of HIV remains too common.^4–7 This delay to diagnosis and care has detrimental consequences to the well-being of individual patients and public health; early diagnosis, linkage to care, and initation of antiretroviral therapy result in improved morbidity and mortality for PLWH as well as decreased community viral load and less transmission.^8–10

Several studies have identified socioeconomic, age-related, and comorbidity-related factors that are associated with missed opportunities for diagnosis of HIV in resource-rich settings in North America.^5,6,11–15 One factor that has been shown to contribute to missed opportunities is the lack of concurrent HIV testing in individuals being tested for other sexually transmitted infections (STIs).¹⁶ In one study of patients presenting to an academic emergency department (ED), less than 4% of individuals tested for chlamydia or gonorrhea were concurrently tested for HIV.¹⁷ Routine screening helps improve rates of HIV testing, but may not be fully implemented in healthcare settings or may not capture those who may need repeat testing over time due to changing or ongoing potential exposure.^5,11,13,15 Routine HIV screening was initiated at University of Chicago Medicine (UCM) in 2011 as part of the public health-funded Expanded HIV Testing and Linkage to Care (xTLC) program, which has been described previously.^18–20 The xTLC program supports routine healthcare-based HIV testing and timely linkage to care. While the program initially used an opt-in model focused on annual screening in the ED, after legislative changes in 2016 it changed to an opt-out model and expanded to include once in a lifetime HIV screening in outpatient primary care clinics and inpatient settings.

UCM’s catchment area is at the intersection of three neighborhoods in Chicago that consistently rank among the community areas with highest HIV incidence rates in the city.²¹ While HIV incidence in Chicago has decreased, HIV disproportionately affects certain populations, including men who have sex with men (MSM) and Black communities.²¹ Late diagnoses account for 18.8% of new HIV diagnoses between 2014 and 2019 in Chicago.^21,22 Understanding patterns of HIV testing in healthcare settings, and missed opportunities for testing, is important as we work to improve early diagnosis in PLWH. In this study we assess sociodemographic and clinical factors associated with missed opportunities for HIV testing at an academic medical center with a routine HIV testing program. In order to best understand opportunites to improve timely HIV diagnosis within our medical center, we assess missed opportunities in two cohorts: persons newly diagnosed with HIV who had a prior encounter in our healthcare system, and persons tested for bacterial STIs.

Methods

We performed a retrospective analysis using data extracted from UCM electronic medical records (EMR) for persons 18 years or older in two cohorts: 1) those newly diagnosed with HIV; and 2) those who underwent STI testing for chlamydia and gonorrhea (CT/GC), and/or syphilis. Data were provided by the Center for Research Informatics (CRI) at UCM. This study was approved by the Institutional Review Board of the Biological Sciences Division at the University of Chicago.

Cohort 1: missed opportunities for HIV testing among people newly diagnosed with HIV

We identified persons with a new diagnosis of HIV at UCM from 2011 to 2018 and examined all healthcare encounters from these patients, if any, at UCM in the five year period prior to their diagnosis. This resulted in the inclusion of encounters between 2006 and 2018 that were within the 5 years preceding each patient’s HIV diagnosis. This five year review period for encounters was chosen to be consistent with a recent study that used a similar approach.⁵ Diagnosis of HIV was based on the CDC testing algorithm,²³ defined as a PLWH without a previously documented diagnosis of HIV or prior positive HIV test results. In addition, all new diagnoses were confirmed with the Chicago Department of Public Health by the xTLC linkage to care coordinator at the time of test result. All encounters following a confirmed HIV positive test were excluded, as were encounters from outpatient locations where diagnostic or screening tests are not typically ordered, such as physical therapy, occupational therapy, diagnostic radiology, and interventional procedures. An encounter during which an HIV test was not conducted was considered a missed opportunity. Encounters within six months of a prior HIV test, regardless of whether an HIV test was performed, were not deemed missed opportunities.

Sociodemographic variables included age, race, ethnicity, chart-identified gender, and zip code. Behavioral variables included alcohol use, illicit drug use, tobacco use, sexual activity, and sexual behavior. Encounter-level variables included location (ED, inpatient, or outpatient) and encounter year, dichotomized as 2006-2010 vs. 2011-2018. We chose 2011 as the cutoff for the dichotomization as this coincided with the implementation of UCM’s xTLC routine screening program. As encounter-level insurance data were unavailable, zip code was used to identify patients residing in high economic hardship community areas according to the 2010-2014 Chicago Community Area Economic Hardship Index.²⁴ Zip codes representing communities with a hardship index value of 45.1 or greater were considered to be high hardship community areas.²⁴ Alcohol use, illicit drug use, tobacco use and sexual activity were drawn from structured fields in the ‘social history’ section of the EMR. Patient sexual behavior (e.g. men who have sex with men (MSM)) was confirmed on chart review for all patients diagnosed with HIV. Patients were classified as not known to be MSM (Not MSM), known to be MSM at time of the encounter (Known MSM), or identified as MSM after HIV diagnosis (MSM Later Known). Chart review was performed to determine HIV pre-exposure prophylaxis (PrEP) use prior to HIV diagnosis for those diagnosed in 2012 or later. Finally, we defined late HIV diagnosis as an initial CD4 count <200 cells/mm³.²⁵

Cohort 2: missed opportunities for HIV testing in encounters with bacterial STI evaluation

Concurrent STI and HIV tests were examined for all STI testing encounters from 2011 to 2018. Encounters where bacterial STI testing was performed in the absence of a concurrent HIV test were considered missed opportunities, excluding encounters within 30 days of a previous HIV test. All encounters following a confirmed HIV positive test were excluded. Patient-level variables included age, chart-identified gender, race, and ethnicity, while encounter-level variables included year (examined as discrete 2-year intervals), location, STI test(s) performed (chlamydia & gonorrhea (CT/GC), syphilis, or all), and previous positive STI test results. We performed chi-square analysis of the proportion of missed testing opportunities in two-year intervals (2011-2012, 2013-2014, 2015-2016, and 2017–2018) to assess trends in missed testing opportunities over time in Cohort 2.

To model associations with missed opportunities for HIV testing we created bivariate and multivariate regression models using encounter-level data, which allowed for all encounters from a single patient to be included. In order to control for repeat encounters amongst individuals, Generalized Estimating Equation (GEE) models were used with an exchangeable correlation structure. All p-values are two-sided, and the level of significance was set at 5%. Associations were measured via odds ratios (OR) or adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). Adjusted models apriori contained demographics (race, chart-identified gender, and ethnicity) as well as all factors identified as significant in bivariate analyses. All analysis was performed in SAS Version 9.4 (SAS Institute, Cary, NC).

Results

Cohort 1: missed opportunities for HIV testing in people newly diagnosed with HIV

From 2011-2018, 122 persons were confirmed to have new diagnoses of HIV (Table 1). The median age was 32 years (IQR 23–43 years), and the majority of patients were chart-identified as male (71.3%) and of African American race (92.6%). The majority of new HIV diagnoses were made in the ED (44.9%) followed by outpatient (36.7%) and inpatient (18.4%) settings. Of patients linked to care at UCM with a baseline CD4 count available (n = 93, 76%), 28.7% were classified as a late diagnosis. The median time from first encounter to date of HIV diagnosis was 620 days (IQR 134–1130 days). No patients were found to have been prescribed PrEP prior to diagnosis of HIV at UCM.

Table 1.

Demographic information for patients newly diagnosed with HIV from 2011-2018.

Variable	Unique persons (n=122)
Age
Median (IQR)	32 (23-43)
Mean (SD)	34.5 (14.6)
Gender*
Female	35 (28.7%)
Male	87 (71.3%)
Race
African-American	113 (92.6%)
White	5 (4.1%)
Other	4 (3.3%)
Ethnicity
Not Hispanic	118 (96.7%)
Hispanic	4 (3.3%)
Baseline CD4
≥200	58 (47.5%)
<200	35 (28.7%)
Missing	29 (23.8%)
Community area economic hardship**
High	78 (63.9%)
Low	44 (36.1%)
Sexual behavior
Not MSM***	77 (63.1%)
MSM	58 (47.5%)
Sexually active
Yes	23 (18.9%)
No/ not currently	16 (13.1%)
Missing	83 (68.0%)
Encounter prior to HIV diagnosis
Yes	98 (80.3%)
No	24 (19.7%)
Missed opportunity for HIV testing (n = 98)
Yes	94 (95.9%)
No	4 (4.1%)

Abbreviations: IQR, interquartile range; SD, standard deviation; MSM, men who have sex with men.

Gender is a binary male/female categorization drawn from the electronic medical record and represents the patient’s legal gender.

**Economic hardship was determined based on zip code of the patient, using the Chicago Community Area Economic Hardship Index²⁴.

***Includes heterosexual men and all women.

Of newly diagnosed PLWH, 98 (80.3%) had prior encounters at UCM within the previous 5 years and 19 (19.4%) of those persons had ever had a prior HIV test at one or more of these encounters. There were a total of 1215 prior encounters included in the GEE modeling; 209 (17.2%) had an associated HIV test while the remaining 1006 encounters (82.8%) were classified as missed opportunities (Table 2). Of all outpatient encounters, the most common provider specialties represented were Internal Medicine (20.6% of outpatient encounters), Cardiology (9.4%), and Obstetrics/Gynecology (7.6%) (Table 2).

Table 2.

Encounters of patients newly diagnosed with HIV from 2011-2018.

Variable	Unique Encounters* (n = 1215)
Encounters with missed opportunities
Missed opportunity	1006 (82.8%)
No missed opportunity	209 (17.2%)
Encounter location
Outpatient	895 (73.7%)
Emergency department	222 (18.2%)
Inpatient	98 (8.1%)
Outpatient provider specialty (Top 5 Specialties)**
Internal Medicine	184 (20.6%)
Cardiology	84 (9.4%)
Obstetrics/Gynecology	68 (7.6%)
Hematology	56 (6.3%)
Neurology	37 (4.1%)
Year of Encounter
2006-2010	380 (31.3%)
2011-2018	835 (68.7%)

*Encounters for 98 patients newly diagnosed with HIV at University of Chicago Medicine from 2011-2018 with at least one encounter at UCM within 5 years prior to diagnosis.

**Among outpatient encounters with a known specialty identified by the electronic data warehouse.

All variables included in the adjusted model can be seen in Table 3. In adjusted analyses, higher odds of missed opportunities were seen in encounters involving persons who were chart identified as female (aOR 2.68; 95% CI [1.31–5.49]), encounters in the ED as compared to the inpatient setting (aOR 2.80; 95% CI [1.18–6.62]), and encounters before 2011 (aOR 9.02; 95%CI [3.07–26.52]). Persons who were not known to be MSM at the time of the encounter but later disclosed sexual activity with men had increased odds of missed opportunities for HIV testing (aOR 3.29; 95% CI [1.70–9.03]) (Table 3).

Table 3.

Unadjusted & adjusted odds ratios for missed opportunities in persons newly diagnosed with HIV.

Variable	Unadjusted odds ratio (95% CI)	Unadjusted p-Value	Adjusted odds ratio (95% CI)	Adjusted p-Value
Sexually active
No	Ref	–	Ref	–
Yes	0.54 (0.29–1.00)	0.05	0.49 (0.23–1.05)	0.07
Gender*
Male	Ref	–	Ref	–
Female	1.77 (1.03–3.04)	0.04	2.68 (1.31–5.49)	0.007
Race
African American	Ref	–	Ref	–
White	0.58 (0.11–3.00)	0.52	2.76 (0.72–10.61)	0.14
Other	1.39 (0.25–7.72)	0.71	24.54 (13.69–43.99)	<0.001
Ethnicity
Not Hispanic	1.12 (0.17–7.61)	0.91	15.33 (2.03–110.96)	0.008
Hispanic	Ref	–	Ref	–
Year of Encounter
2006-2010	5.33 (2.75–10.31)	<0.001	9.02 (3.07–26.52)	<0.001
2011-2018	Ref	–	Ref	–
Sexual behavior
Not MSM**	Ref	–	Ref	–
Known MSM	0.07 (0.03–0.15)	<0.001	0.13 (0.05–0.31)	<0.001
MSM later known	2.21 (0.94–5.22)	0.07	3.29 (1.70–9.03)	0.02
Encounter location
Emergency department	2.39 (1.32–4.33)	0.004	2.45 (1.04–5.78)	0.04
Inpatient	Ref	–	Ref	–
Outpatient	1.84 (0.96–3.53)	0.07	2.79 (1.18–6.61)	0.02

Abbreviations: MSM, men who have sex with men

Gender is a binary male/female categorization drawn from the electronic medical record and represents the patient’s legal gender.

Includes heterosexual men and all women.

Cohort 2: missed opportunities for HIV testing in encounters with bacterial STI evaluation

Analysis of Cohort 2 identified 104,678 bacterial STI testing encounters amongst 59,114 unique persons (Table 4). The median age of patients was 31 years (IQR 24–45 years) and the majority of patients were female (73.2%) and African-American (62.1%). The encounters occurred most frequently in the outpatient setting (63.7%), followed by the ED (17.0%) and the inpatient (14.3%) settings. Regarding concurrent STI testing, 44.9% of encounters included only CT/GC assays, 33.0% included only syphilis testing, while the remaining 22.1% included testing for all three STIs. About half (51.6%) of encounters were linked to an HIV screen, while the remaining 48.4% were classified as missed opportunities.

Table 4.

Patient demographics and STI testing encounter information, 2011-2018.

Variable	Unique persons (n = 59,114)	All encounters (n = 104,678)
Age
Median (IQR)	31 Years old (24–45)	30 Years old (23–40)
Gender*
Female	43,266 (73.2%)	82,150 (78.5%)
Male	15,847 (26.8%)	22,527 (21.5%)
Unknown	1 (<.01%)	1 (<.01%)
Race
African American	36,685 (62.1%)	69,691 (66.6%)
White	15,223 (25.8%)	23,847 (22.8%)
Other	4099 (6.9%)	7048 (6.7%)
Unknown	3107 (5.3%)	4092 (3.9%)
Ethnicity
Not Hispanic	52,819 (89.4%)	95,194 (90.9%)
Hispanic	3201 (5.4%)	5498 (5.3%)
Unknown	3094 (5.2%)	3986 (3.8%)
Encounter year
2011- 2012	-	19,407 (18.5%)
2013- 2014	-	23,757 (22.7%)
2015–2016	-	29,670 (28.3%)
2017 - 2018	-	31,844 (30.4%)
Encounter location
Outpatient	-	66,693 (63.7%)
ED	-	17,750 (17.0%)
Inpatient	-	15,011 (14.3%)
Unknown	-	5224 (5.0%)
STI Test
CT/GC	-	47,033 (44.9%)
Syphilis	-	34,540 (33.0%)
CT/GC + syphilis	--	23,105 (22.1%)
STI Positivity
CT	-	4034 (5.8%)
GC	-	1565 (2.2%)
Syphilis	-	1863 (3.2%)
Missed opportunity
Yes	-	50,655 (48.4%)
No	-	54,023 (51.6%)

Abbreviations: STI, sexually transmitted infection; CT/GC, chlamydia/gonorrhea; ED, emergency department

Gender is a binary male/female categorization drawn from the electronic medical record and represents the patient’s legal gender.

The proportion of encounters with a missed opportunity was significantly reduced over time between 2011-2012, 2013-2014, 2015-2016, and 2017-2018 (55.9% vs 49.0% vs 46.1% vs 45.5%, respectively, p < .01). All variables included in the adjusted GEE model can be seen in Table 5. Adjusted analysis (Table 5) showed that an STI testing encounter had higher odds of being a missed opportunity with female patients (aOR 2.44; 95% CI [2.33–2.56]), each additional year of age (aOR 1.02; 95% CI [1.02–1.02]), or if CT/GC testing was performed without syphilis testing (aOR 12.51; 95% CI [11.93–13.12]. The odds of having a missed opportunity were highest in 2011–2012 as compared to 2017-2018 (aOR 1.35; 95% CI [1.28–1.41]). Both inpatient (aOR 3.66; 95% CI [3.39–3.95]) and outpatient (aOR 1.36; 95% CI [1.29–1.43]) encounters carried higher odds of being a missed opportunity compared to ED encounters.

Table 5.

Unadjusted & adjusted odds ratios for missed HIV testing opportunities in STI testing encounters.

Variable	Unadjusted odds ratio (95% CI)	Unadjusted p-Value	Adjusted odds ratio (95% CI)	Adjusted p-Value
Age
Each additional year	1.001 (1.001–1.002)	0.001	1.019 (1.018–1.021)	<0.0001
Race
African American	Ref	–	Ref	–
White	0.71 (0.69–0.73)	<0.0001	1.05 (1.01–1.10)	0.016
Other	0.75 (0.72–0.78)	<0.0001	1.06 (1.00–1.13)	0.039
Ethnicity
Not Hispanic	Ref	–	Ref	–
Hispanic	0.79 (0.74–0.83)	<0.0001	0.94 (0.87–1.02)	0.141
Gender*
Male	Ref	–	Ref	–
Female	2.61 (2.52–2.71)	<0.0001	2.44 (2.33–2.56)	<0.0001
Encounter location
Emergency department	Ref	–	Ref	–
Inpatient	0.89 (0.85–0.93)	<0.0001	3.66 (3.39–3.95)	<0.0001
Outpatient	0.58 (0.56–0.60)	<0.0001	1.36 (1.29–1.43)	<0.0001
STI Test
Syphilis only	Ref	–	Ref	–
CT/GC only	6.37 (6.17–6.58)	<0.0001	12.51 (11.93–13.12)	<0.0001
Combined all	0.11 (0.11–0.12)	<0.0001	0.20 (0.19–0.21)	<0.0001
Prior positive STI Test**
CT	1.14 (1.10–1.19)	<0.0001	0.97 (0.91–1.04)	0.411
GC	1.08 (1.02–1.15)	0.016	0.88 (0.79–0.99)	0.189
Syphilis	0.66 (0.61–0.71)	<0.0001	1.20 (1.06–1.37)	0.005
Encounter year
2011-2012	1.48 (1.43–1.54)	<0.0001	1.35 (1.28–1.41)	<0.0001
2013-2014	1.14 (1.10–1.18)	<0.0001	1.01 (0.96–1.05)	0.78
2015-2016	1.03 (1.00–1.07)	0.06	0.91 (0.87–0.94)	<0.0001
2017-2018	Ref	–	Ref	–

Abbreviations: STI, sexually transmitted infection; CT/GC, chlamydia/gonorrhea

Gender is a binary male/female categorization drawn from the electronic medical record and represents the patient’s legal gender.

Versus prior negative STI test.

Discussion

Our analysis includes two different methods to identify and characterize missed opportunities for HIV testing and earlier diagnosis. Overall, missed opportunities remained quite high during the time period assessed, and we found several associated factors. In newly diagnosed PLWH, 83% of prior encounters were missed opportunities, and late diagnosis of HIV was 28.7%, higher than the 23% reported in the US in 2014 and the 18.8% in the city of Chicago from 2014 to 2019.^21,22,26 Targeting factors associated with missed opportunities in future health system initiatives may significantly improve early diagnosis and minimize late presentation of HIV, which is associated with significant morbidity and mortality.²⁷

Female gender was a strong risk factor for having a missed opportunity, consistent with other studies,¹² despite women comprising 30% of new HIV diagnoses at our health center and a quarter of new diagnoses in the US.^7,20 Yet women remain an important population to engage in HIV testing and prevention efforts, particularly African American women who are disproportionately impacted by HIV.²⁸ Women may be at increased risk for a missed opportunity due to frequent asymptomatic CT/GC testing as part of routine gynecologic evaluations or due to clinician perception of lower risk. Further, we found that concurrent syphilis testing, which requires a blood draw, carried lower odds of a missed opportunity as compared to GC/CT testing alone; this may reflect a desire to avoid additional blood draws, which has been described as a barrier to HIV testing, particularly in younger persons.²⁹ Some routine HIV testing programs have linked the HIV screening to other orders requiring a blood draw, such as a complete blood count.¹⁸ However, this limits the reach of routine testing and may be a particular limitation for patients presenting only for STI testing or routine gynecologic care.

In newly diagnosed PLWH, chart documentation of MSM sexual behavior was associated with lower odds of a missed opportunity. The majority of new HIV diagnoses in the US continue to be among gay and bisexual men, and physicians likely have awareness of this sexual behavior as a “can’t-miss” indication for HIV testing.^14,15,17,30 However, failure to accurately obtain and/or document MSM sexual behavior in the EMR is a barrier to appropriate testing, as encounters in persons who were identified as MSM only after HIV diagnosis had higher odds of a missed opportunity. Sexual history taking remains a major weakness,³¹ and some patients may also be reluctant to disclose sexual orientation, activity, and behaviors,³² all of which may hinder understanding of current need for initial and repeat testing.

Encounters in later years (after 2011 in newly diagnosed PLWH and after 2012 in those evaluated for bacterial STI) were less likely to have a missed opportunity. Of note, we also examined dichotomizing encounters around 2016 (data not shown) in newly diagnosed PLWH (2006-2015, 2016–2018) and similar results were seen with the later period of encounters having a reduced risk of missed opportunities (unadjusted OR 0.41; 95% CI [0.23–0.74]). This follows national trends in HIV testing and may also have resulted from the implementation of routine HIV screening.^19,33 However, true opt-out testing could not be performed until 2016 when the Illinois AIDS Confidentiality Act was revised, allowing HIV testing to occur under the consent for general medical care rather than a separate consent process.³⁴ This legislation allowed for EMR-prompted ordering to be implemented in the ED if patients did not opt out of screening. Leveraging EMR tools such as best practice advisories and linked orders sets may also prove beneficial in the outpatient setting, where the majority of STI-related missed testing opportunities occurred.

There are several limitations worth noting in our study. First, our data did not allow us to determine if an HIV test was offered by a physician but declined by the patient. Additionally, there were limitations based on our EMR system, including that information on sexual behavior of patients is not always collected in structured fields that can be drawn from the electronic data warehouse. We were also unable to analyze the effects of birth sex versus gender, as our EMR system only collected information on legal sex at the time of this study. We did not have information on PrEP use in the STI testing cohort, and were unable to differentiate between symptomatic and asymptomatic STI testing. While a prior positive syphilis result was associated with higher odds of a missed opportunity in STI testing encounters, this is likely explained by the need for serial rapid plasma reagin (RPR) quantification in patients diagnosed and treated for syphilis in shorter intervals than HIV testing may be required. This is supported by the fact that this variable did not become significant until we included the 31–180 day range following a prior encounter to qualify as a missed opportunity—a period of time when the first post-treatment RPR would likely be assessed without an absolute need for repeat HIV testing. While inpatient encounters were associated with lower odds of a missed opportunity in Cohort 1 and higher odds of a missed opportunity in Cohort 2, we were unable to account for severity of illness at time of encounter, which may impact HIV testing. Finally, our data were drawn from a single, urban academic medical center in an area of high HIV incidence and prevalence, so our findings may not be generalizable to other healthcare settings or geographic areas.

In this study, missed opportunities for HIV testing remained common among both persons eventually diagnosed with HIV and those who received bacterial STI testing. Routine, opt-out HIV testing has reduced missed opportunities over time, but these could be reduced further by strengthening targeted and repeat testing. Employing complementary HIV screening approaches is likely to be most effective at identifying new diagnoses.³⁵ To supplement routine screening in a systemic way, we need better sexual history-taking and structured EMR documentation to identify those patients with reasons to test more frequently, as well as coupling HIV testing with other bacterial STI testing, all while leveraging automated processes within the EMR as much as possible.^36,37 Expanding the reach of HIV testing can improve earlier diagnosis of HIV and increase the number of PLWH who are aware of their diagnosis. Improving HIV screening among persons being tested for STIs may also help identify persons who would benefit from HIV PrEP, as HIV testing serves as entry into care for prevention services,³⁸ a key component in ending the HIV epidemic. Further work is needed to understand and document barriers to testing for patients and providers as well as to incorporate PrEP linkage into HIV testing programs across inpatient, outpatient, and ED settings.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Data for this study were provided by the Clinical Research Data Warehouse maintained by the Center for Research Informatics (CRI) at University of Chicago. CRI is funded by the Biological Sciences Division, the Institute for Translational Medicine/CTSA (NIH UL1 TR000430) at the University of Chicago. The Expanded Testing and Linkage to Care Program is funded by the Chicago Department of Public Health. Moira McNulty is supported by the National Institute of Mental Health (K23MH118969).

ORCID iD

Moira C McNulty

References

Branson

Handsfield

Lampe

, et al. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep 2006; 55: 1–17.

Centers for Disease Control and Prevention . Previous HIV testing among adults and adolescents newly diagnosed with HIV infection - National HIV Surveillance System, 18 jurisdictions, United States, 2006-2009. MMWR Morb Mortal Wkly Rep 2012; 61: 441–445.

Workowski

Bachmann

Chan

, et al. Sexually Transmitted Infections Treatment Guidelines, 2021. MMWR Recomm Rep 2021; 70: 1–187. DOI: 10.15585/mmwr.rr7004a1.

Darling

Hachfeld

Cavassini

, et al. Late presentation to HIV care despite good access to health services: current epidemiological trends and how to do better. Swiss Medical Weekly 2016; 146: w14348

Nanditha

NGA

St-Jean

Tafessu

, et al. Missed opportunities for earlier diagnosis of HIV in British Columbia, Canada: A retrospective cohort study. PloS One 2019; 14: e0214012.

Mannheimer

Wang

Wilton

, et al. Infrequent HIV testing and late HIV diagnosis are common among a cohort of Black men who have sex with men (BMSM) in six US cities. J Acquired Immune Deficiency Syndromes 2014; 67: 438–445.

Centers for Disease Control and Prevention . Estimated HIV incidence and prevalence in the United States, 2015–2019. Atlanta, GA: CDC. Report no. 26 (No. 1), 2021.

Prabhu

Harwell

Kumarasamy

. Advanced HIV: diagnosis, treatment, and prevention. The Lancet HIV 2019; 6: e540–e551. DOI: 10.1016/s2352-3018(19)30189-4.

Das

Chu

Santos

, et al. Decreases in community viral load are accompanied by reductions in new HIV infections in San Francisco. PLoS One 2010; 5: e11068. DOI: 10.1371/journal.pone.0011068.

10.

Cohen

Chen

McCauley

, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med 2011; 365: 493–505. DOI: 10.1056/NEJMoa1105243.

11.

Centers for Disease Control and Prevention . Missed opportunities for earlier diagnosis of HIV infection--South Carolina, 1997-2005. MMWR Morbidity Mortality Weekly Report 2006; 55: 1269–1272.

12.

Liddicoat

Horton

Urban

, et al. Assessing missed opportunities for HIV testing in medical settings. J General Internal Medicine 2004; 19: 349–356.

13.

Downing

Garcia-Diaz

. Missed opportunities for HIV diagnosis. J Int Assoc Providers AIDS Care (JIAPAC) 2017; 16: 14–17.

14.

O'Byrne

Orser

. Avoiding missed opportunities to screen for HIV. J Am Assoc Nurse Pract 2020; 32: 408–414.

15.

Powell

Krentz

Eagles

, et al. Missed opportunities within healthcare for an earlier diagnosis of HIV. Int Journal STD & AIDS 2020; 31: 1169–1177.

16.

Traynor

Rosen-Metsch

Feaster

. Missed opportunities for HIV testing among STD clinic patients. J Community Health 2018; 43: 1128–1136.

17.

Klein

Martin

Quinlivan

, et al. Missed opportunities for concurrent HIV-STD testing in an academic emergency department. Public Health Rep 2014; 129: 12–20.

18.

Rucker

Eavou

Allgood

, et al. Implementing routine HIV screening in three Chicago hospitals: lessons learned. Public Health Rep 2016; 131: 121–129.

19.

Bares

Eavou

Bertozzi-Villa

, et al. Expanded HIV testing and linkage to care: conventional vs. point-of-care testing and assignment of patient notification and linkage to care to an HIV care program. Public Health Rep 2016; 131: 107–120.

20.

Almirol

McNulty

Schmitt

, et al. Gender differences in HIV testing, diagnosis, and linkage to care in healthcare settings: identifying African American women with HIV in Chicago. AIDS Patient Care and STDs 2018; 32: 399–407.

21.

Chicago Department of Public Health . HIV/ STI Surveillance Report. Chicago: Chicago Department of Public Health, 2019, p. IL2019.

22.

Sullivan

Woodyatt

Koski

, et al. A data visualization and dissemination resource to support HIV prevention and care at the local level: analysis and uses of the AIDSVu Public Data Resource. J Medical Internet Research 2020; 22: e23173.

23.

Branson

Owen

Wesolowski

, et al. Laboratory Testing for the Diagnosis of HIV Infection: updated recommendations, Atlanta, GA: CDC; 2014.

24.

Wilson

Tailor

Linares

. Fact Sheet: Chicago Community Area Economic Hardship Index. Chicago: Great Cities Institute, University of Illinois at Chicago, 2019.

25.

Selik

Mokotoff

Branson

, et al. Revised surveillance case definition for HIV infection—United States. Morbidity Mortality Weekly Rep Recommendations Rep 2014; 63: 1–10.

26.

Centers for Disease Control and Prevention . CDC Fact Sheet: Today’s HIV/AIDS Epidemic, Atlanta, GA: CDC; 2015.

27.

Justice

Goetz

Stewart

, et al. Delayed presentation of HIV among older individuals: a growing problem. The Lancet HIV 2022; 9: e269–e280. DOI: 10.1016/s2352-3018(22)00003-0.

28.

Centers for Disease Control and Prevention . HIV Surveillance Report: Diagnoses of HIV Infection in the United States and Dependent Areas. Atlanta, GA: CDC; 2020.

29.

Ibitoye

Bennett

Bugaghis

, et al. provider perspectives on barriers to routine HIV testing of adolescent and young adult patients in emergency department settings. Behav Med 2021: 1–8. DOI: 10.1080/08964289.2021.2020207.

30.

Kapadia

Singh

Jones

, et al. Missed opportunities for HIV testing of patients tested for sexually transmitted infections at a large urban health care system from 2010 to 2015. Open Forum Infect Dis 2018; 5: ofy165. DOI: 10.1093/ofid/ofy165.

31.

Lanier

Castellanos

Barrow

, et al. Brief sexual histories and routine HIV/STD testing by medical providers. AIDS Patient Care STDS 2014; 28: 113–120. DOI: 10.1089/apc.2013.0328.

32.

Qiao

Zhou

. disclosure of same-sex behaviors to health-care providers and uptake of HIV testing for men who have sex with men: a systematic review. Am J Mens Health 2018; 12: 1197–1214. DOI: 10.1177/1557988318784149.

33.

Patel

Johnson

Krueger

, et al. Trends in HIV Testing Among US Adults, Aged 18-64 Years. AIDS Behav 2020; 24: 532–539. DOI: 10.1007/s10461-019-02689-0

34.

Illinois General Assembly . AIDS confidentiality act [(410 ILCS 305/, Illinois General Assembly; 2015.

35.

Skaathun

Pho

Pollack

, et al. Comparison of effectiveness and cost for different HIV screening strategies implemented at large urban medical centre in the United States. J Int AIDS Soc 2020; 23: e25554. DOI: 10.1002/jia2.25554.

36.

Ridgway

Lee

Devlin

, et al. machine learning and clinical informatics for improving HIV care continuum outcomes. Curr Hiv/aids Rep 2021; 18: 229–236. DOI: 10.1007/s11904-021-00552-3.

37.

Lin

Mauntel-Medici

Heinert

, et al. harnessing the power of the electronic medical record to facilitate an opt-out HIV screening program in an urban academic emergency department. J Public Health Manag Pract 2017; 23: 264–268. DOI: 10.1097/PHH.0000000000000448.

38.

McNulty

Schneider

. Care continuum entry interventions: seek and test strategies to engage persons most impacted by HIV within the United States. AIDS 2018; 32: 407–417. DOI: 10.1097/QAD.0000000000001733.