Achieving Core Indicators for HIV Clinical Care Among New Patients at an Urban HIV Clinic

Abstract

Following the release of the 2010 National HIV/AIDS Strategy for the United States, the Institute of Medicine (IOM) issued core clinical indicators for measuring health outcomes in HIV-positive persons. As early retention in HIV primary care is associated with improved long-term health outcomes, we employed IOM indicators as a guide to examine a cohort of persons initiating HIV outpatient medical care at a university-affiliated HIV clinic in the Southern United States (January 2007–July 2012). Using indicators for visit attendance, CD4 and viral load laboratory testing frequency, and antiretroviral therapy initiation, we evaluated factors associated with achieving IOM core indicators among care- and treatment-naïve patients during the first year of HIV care. Of 448 patients (mean age = 35 years, 35.7% white, 79.0% male, 58.4% education beyond high school, 35.9% monthly income > $1,000 US, 47.3% uninsured), 84.6% achieved at least four of five IOM indicators. In multivariable analyses, persons with monthly income > $1,000 (OR_adj. = 3.71; 95% CI: 1.68–8.19; p = 0.001) and depressive symptoms (OR_adj. = 2.13; 95% CI: 1.02–4.45; p = 0.04) were significantly more likely to achieve at least four of the five core indicators, while patients with anxiety symptoms were significantly less likely to achieve these indicators (OR_adj. = 0.50; 95% CI: 0.26–0.97; p = 0.04). Age, sex, race, education, insurance status, transportation barriers, alcohol use, and HIV status disclosure to family were not associated with achieving core indicators. Evaluating and addressing financial barriers and anxiety symptoms during the first year of HIV outpatient care may improve individual health outcomes and subsequent achievement of the National HIV/AIDS Strategy.

Introduction

In 2010, the White House Office of National AIDS Policy (ONAP) released the National HIV/AIDS Strategy (NHAS) for the United States (US) with the goals of “reducing the number of people who become infected with HIV, increasing access to care, improving health outcomes for people living with HIV, and reducing HIV-related health disparities.”¹ ONAP commissioned the Institute of Medicine (IOM) to establish a set of core indicators for evaluating the effectiveness of NHAS implementation in optimizing HIV care and outcomes.² In response, the IOM established nine core clinical indicators for use with reporting national HIV statistics in a standardized manner (Table 1) to assess timely linkage to HIV primary care, initiation of antiretroviral therapy, monitoring of laboratory values (CD4 cell count and viral load), retention in primary care, virologic control, and all-cause mortality rates.²

Table 1.

Institute of Medicine Core Indicators for HIV Clinical Care

1. Proportion of people newly diagnosed with HIV with a CD4 cell count > 200 cells/mm³ and without a clinical diagnosis of AIDS

2. Proportion of people newly diagnosed with HIV who are linked to clinical care for HIV within 3 months of diagnosis

3. Proportion of people with diagnosed HIV infection who are in continuous care (two or more visits for routine HIV medical care in the preceding 12 months at least 3 months apart) [Visit adherence]

4. Proportion of people with diagnosed HIV infection who received two or more CD4 tests in the preceding 12 months [CD4 lab testing]

5. Proportion of people with diagnosed HIV infection who received two or more viral load tests in the preceding 12 months [VL lab testing]

6. Proportion of people with diagnosed HIV infection in continuous care for 12 or more months and with a CD4 cell count ≥ 350 cells/mm³ [CD4 ≥ 350]

7. Proportion of people with diagnosed HIV infection and a measured CD4 cell count < 500 cells/mm³ who are not on ART [ART initiation]^a

8. Proportion of people with diagnosed HIV infection who have been on ART for 12 or more months and have a viral load below the level of detection

9. All cause mortality rate among people diagnosed with HIV infection

Indicators 3-7 (italicized) were evaluated in this study. For indicator 7, we used 350 cells/mm³ instead of 500 cells/mm³ due to changes in ART initiation guidelines during observation period.

To meet criteria for indicator 7, patient must have initiated ART if his/her CD4 cell count was below 350 cells/mm³ at least once during observation period; if patient's CD4 cell count never fell below 350 cells/mm³, then patient met criteria for indicator 7 regardless of ART initiation.

Recent studies have demonstrated the critical nature of timely, uninterrupted medical service receipt among HIV patients who initiate outpatient care at a medical facility.^3,4 Unfortunately, studies also have revealed that the rate of missed visits is high during the first year following initiation of care, and antiretroviral treatment is often postponed as a result.^3,5,6 Harmful health consequences are more likely to occur when newly diagnosed HIV patients are not engaged promptly in uninterrupted care.⁷ These include delays in administration of antiretroviral therapy,^4,5 delayed reductions in viral load,^3,7 higher rates of transmission of HIV to other individuals in the community,^7,8 augmented healthcare costs,⁹ and higher rates of mortality.^5,10

Recognizing the urgency of engaging newly diagnosed HIV patients into immediate continuous care, we examined the characteristics of our new-to-care patients in order to better identify potential risk of failing to achieve the IOM core clinical indicators (Table 1) and poorer health outcomes longitudinally. As patients with unmet needs may be less likely to comply with standard and timely recommended treatment programs, ^5,11
–13 we aimed to discover whether specific characteristics within our new-to-care HIV patient population were significantly associated with patients' failure to meet the recommended level of care as outlined by IOM core clinical indicators.

Recent investigations have examined individual indicators similar to those identified by the IOM as discrete outcomes (Table 1).^14,15 However, our goal for this investigation was to investigate whether characteristics of a cohort initiating HIV primary were associated with a composite group of five indicators from the list of nine IOM indicators (Table 1, italicized).

Methods

This retrospective analysis was conducted using a cohort of patients newly initiating care at the 1917 HIV/AIDS Outpatient Clinic Cohort at the University of Alabama at Birmingham (UAB) through the new patient orientation program; details of this academically-affiliated clinical cohort can be found at http://www.uab.edu/medicine/1917cliniccohort/. We selected these indicators based primarily on the importance of each for achieving optimal health outcomes, and in part on our ability to quantify the data required for measurement and analysis accurately. The study database contains socioeconomic, demographic, clinical, and patient-reported data from a structured clinic intake visit.

In this investigation, we included a sample of patients who were at least 19 years of age, had their first HIV primary care appointment within the study observation period (January 2007—July 2012), were new to HIV care (no prior visits at any other HIV outpatient clinics), and were treatment naive (no prior ART). Clinic intake data were obtained from the Project CONNECT (Client Oriented New Patient Navigation to Encourage Connection to Treatment) program that includes an initial clinic orientation visit and baseline assessment of patient needs.^16,17 Sessions are typically conducted within one week of first patient contact or referral and include an evaluation of potential physical and psychosocial barriers to HIV primary care via semi-structured interview and standardized self-report questionnaires; domains include household characteristics, treatment history, structural barriers (including transportation), disclosure, education, income, depression, drug or alcohol usage, and anxiety, among others, as part of a comprehensive needs assessment with trained staff.^16,18

Outcome of interest

For this investigation, we employed a composite of five of the nine IOM indicators that were measurable and relevant to the initial 12 months of outpatient HIV primary care (Table 1, italicized). As early retention is associated with achieving virologic suppression,^2,3 we employed an indicator for retention in HIV care. We also utilized indicators for the achievement of recommended CD4 and viral load laboratory assessments, as these are routinely ordered to assess immune status, evaluate appropriate timing for initiating antiretroviral therapy (ART), prevent the development of opportunistic infections, and for standard surveillance reporting as a definitive measure of disease status.^2,3,19,20 Timely initiation of ART was also of interest, as swift initiation after HIV diagnosis reduces negative effects of the virus and decreases risk of transmission to other individuals.²¹

All five designated indicators were employed with respect to the originally proposed parameters, with the exception of indicator seven. For this indicator, we used 350 cells/mm³ rather than the 500 cells/mm³ parameter to accommodate changes in clinical guidelines for ART initiation during the observation period.¹⁹ To achieve this indicator, the patient must have initiated ART if his/her CD4 cell count was below 350 cells/mm³ at least once during the observation period. However, if the patient's CD4 cell count did not drop below 350 cells/mm³ during this time, s/he was considered to have attained this indicator, regardless of ART initiation.

With this consideration, we analyzed this cohort in two ways. First, we dichotomized the cohort into persons who fulfilled at least four of the five indicators during their first 12 months in HIV primary care (“achieved”) versus those who achieved three or fewer indicators (“not achieved”). To examine whether the factors associated remained the same, we also dichotomized the cohort into persons who fulfilled all five of the selected indicators versus those who achieved four or less indicators (data not shown).

Independent factors

Based upon clinical significance,¹¹ the independent factors (predictors) that were examined included age, sex, race, education level, individual income, insurance status, reported transportation barriers, depressive symptoms, anxiety symptoms, alcohol risk, and disclosure of HIV status to family.

Depressive symptoms

Depressive symptoms were scored using the Personal Health Questionnaire (PHQ-9) to gauge symptoms of depression during the recent 2-week period.²² Consistent with prior research and scoring recommendations, we divided patients into three groups: those who scored ≥ 10 were classified as having depression, those who scored < 10 were classified as not having depression, and persons with incomplete data were placed into a classification of unknown depression.

Anxiety symptoms

Anxiety symptoms were scored using the PHQ-5.^23,24 A score of zero indicated no anxiety, a score from one to four indicated symptoms of anxiety, with ≥5 indicating panic symptoms. We divided patients into three groups: persons with no anxiety, those with anxiety, and those with unknown anxiety. Patients with anxiety symptoms or panic syndrome were grouped together and placed in the category “anxiety symptoms.” Those patients who had a score of zero were placed in the category “no anxiety.” Finally, those who had either incomplete or no data were placed in the category “unknown anxiety.”

Alcohol risk

On the AUDIT-C measure, which consists of items designed to identify patients whose alcohol use poses a threat to overall health, persons whose scores indicated “at-risk” alcohol use for their respective genders were compared with persons whose scores did not indicate hazardous drinking using standardized gender-specific scoring guidelines.²⁵

Disclosure

We utilized single item responses from clinic orientation data to measure HIV status disclosure to family members: “Since you found out that you are HIV positive, who have you told about your diagnosis in your family?” If a patient reported that s/he had shared her/his status with one or more family members, we considered that patient to have disclosed. We divided patients into two groups: persons who had not disclosed to family members and those who had disclosed their HIV status to one or more family members.

Statistical analyses

Descriptive analyses were used for the overall sample and stratified by “achieved” versus “not achieved” as described previously. The association between independent factors and the composite clinical indicator outcome was examined using univariate and multivariable logistic regression methods reporting crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs), respectively. In multivariable analyses, the clinically relevant factors were included as described previously. Model performance was examined using c-statistics, max-rescaled r-square, and Hosmer-Lemeshow test for model fit. Multicollinearity of the independent factors was examined with variance inflation factor (VIF) by adjusting the linear combinations by the weight matrix used in the maximum likelihood algorithm;²⁶ the VIF for all the factors was <1.5, indicating no multicollinearity. Analyses were conducted using SAS statistical software (Cary, NC), version 9.3.

Results

Among the cohort of 448 new patients, the mean age was 35 years, 35.7% were white, and 79.0% were male (Table 2). More than half (58.4%) reported formal education beyond high school. One third (35.9%) reported an individual monthly income of at least $1,000 US Dollars (USD), and just under half (47.3%) were uninsured.

Table 2.

Descriptive Characteristics of Cohort Receiving Care at an Urban HIV Clinic Who Met Criteria for (Any) Four of Five Designated Institute of Medicine Core Indicators for HIV Clinical Care (January 2007–July 2012)

Characteristic	Achieved (379) n (%)	Not achieved (69) n (%)	Total (448) N (%)
Age in years, mean (SD)	34.9 (11.0)	36.0 (11.3)	35.1 (11.1)
Male	303 (80.0)	51 (73.9)	354 (79.0)
Race^a
White	139 (37.0)	20 (29.0)	159 (35.7)
Black/African American	229 (60.9)	48 (69.6)	277 (62.3)
Other	8 ( 2.1)	1 ( 1.4)	9 ( 2.0)
Education ≥ college^a	220 (59.1)	35 (53.9)	255 (58.4)
Monthly income > $1,000 USD	150 (39.6)	11 (15.9)	161 (35.9)
Insurance type
Private	155 (40.9)	21 (30.4)	176 (39.3)
Public	46 (12.1)	14 (20.3)	60 (13.4)
Uninsured	178 (47.0)	34 (49.3)	212 (47.3)
Depression^b
Depression	110 (29.0)	18 (26.1)	128 (28.6)
No depression	242 (63.9)	43 (62.3)	285 (63.6)
Unknown	27 ( 7.1)	8 (11.6)	35 ( 7.8)
Anxiety^c
Anxiety	88 (23.2)	23 (33.3)	111 (24.8)
No anxiety	268 (70.7)	42 (60.9)	310 (69.2)
Unknown	23 ( 6.1)	4 ( 5.8)	27 ( 6.0)
Alcohol risk	270 (71.2)	44 (63.8)	314 (70.1)
No HIV status disclosure to family^a	134 (36.5)	24 (36.4)	158 (36.5)

USD, United States Dollars.

Missing data: race = 3 (Achieved = 3); education = 11 (Achieved = 7, Not achieved = 4); disclosure = 15 (Achieved = 12, Not achieved = 3).

Patient Health Questionnaire (PHQ-9); ^cPatient Health Questionnaire (PHQ-5).

Of the 448 patients, 240 (53.6%) met criteria for five of the selected core indicators, 139 (31.0%) met four indicators, 18 (4.0%) three indicators, 19 (4.2%) two indicators, 17 (3.8%) one indicator; and 15 (3.3%) patients did not achieve any of the indicators. For persons who met criteria for all five indicators, achievement of the ART initiation indicator was the highest at 95.3%, followed by VL testing (87.3%), CD4 testing (87.1%), and visit adherence (81.5%). Of the 139 patients who achieved four indicators, the most common indicator that was not achieved was CD4 ≥ 350 (n = 107), followed by visit adherence (n = 26).

Overall, 379 (84.6%) met criteria for four or more indicators. In univariate logistic regression analyses (Table 3) persons with monthly income over $1,000 USD had significantly greater odds of achieving the composite core indicators than those with incomes of ≤ $1,000 USD per month (OR_crude = 3.4; 95% CI: 1.76–6.79; p < 0.001). In multivariable analyses (Table 3) the association of income remained strong and significant (OR_adjusted = 3.71; 95% CI: 1.68–8.19; p = 0.001), even after adjusting for other variables.

Table 3.

Univariate and Multivariable Analyses of Characteristics of Patients at an Urban HIV Clinic Who Met Criteria for (Any) Four of Five Designated Institute of Medicine Core Indicators for HIV Clinical Care (January 2007–July 2012)

	Univariate analyses		Multivariable analyses
Characteristic	Crude ^a OR (95% CI)	p Value	Adjusted ^b OR (95% CI)	p Value
Age (per 1 year increase)	0.99 (0.97–1.01)	0.46	1.00 (0.97–1.03)	0.83
Sex
Male vs. female (ref)	1.41 (0.78–2.55)	0.26	1.32 (0.6–2.67)	0.45
Race
White vs. non-white (ref)	1.44 (0.82–2.52)	0.21	1.10 (0.58–2.09)	0.77
Education
At least some college vs. No college (ref)	1.24 (0.73–2.11)	0.43	0.91 (0.48–1.70)	0.76
Monthly income, USD
>$1,000 vs. ≤ $1,000 (ref)	3.45 (1.76–6.79)	<0.001^c	3.71 (1.6–8.19)	0.001^c
Insurance
Private vs. uninsured (ref)	1.41 (0.79–2.53)	0.25	0.89 (0.44–1.77)	0.73
Public vs. uninsured (ref)	0.63 (0.31–1.27)	0.19	0.66 (0.29–1.54)	0.34
Transportation barriers
Yes vs. no (ref)	0.58 (0.18–1.83)	0.35	1.07 (0.28–4.14)	0.92
Depression^d
Yes vs. no (ref)	1.09 (0.6–1.97)	0.79	2.13 (1.02–4.45)	0.04
Unknown vs. no (ref)	0.60 (0.26–1.41)	0.24	0.72 (0.26–2.03)	0.54
Anxiety^e
Yes vs. no (ref)	0.60 (0.34–1.05)	0.07	0.50 (0.26–0.97)	0.04^c
Unknown vs. no (ref)	0.90 (0.30–2.74)	0.85	1.51 (0.38–6.00)	0.56
Alcohol risk
Yes vs. no (ref)	1.41 (0.82–2.41)	0.21	1.19 (0.63–2.21)	0.59
HIV status disclosure to family
No vs. yes (ref)	1.01 (0.58–1.74)	0.98	1.09 (0.60–1.97)	0.78

CI, confidence interval; OR, odds ratio; ref, reference category; US, United States.

Univariate logistic regression (N = 448). Missing data: race = 3 (Achieved = 3); education = 11 (Achieved = 7, Not achieved = 4); disclosure = 15 (Achieved = 12, Not achieved = 3).

Multivariable analysis by logistic regression method. Model performance (N = 424): c-statistics = 0.682, max-rescaled r-square = 0.1091, and mode fit p-value by Hosmer-Lemeshow test = 0.38.

Statistically significant at 0.05 level.

Patient Health Questionnaire (PHQ-9).

Patient Health Questionnaire (PHQ-5).

Additionally, depression and anxiety symptoms were found to be significantly associated with achieving indicators in unadjusted analyses. Persons with symptoms of depression showed significantly greater odds of achieving the selected indicators than those without depression (OR_adjusted = 2.13, 95% CI: 1.02–4.45; p = 0.04). Persons with elevated anxiety symptoms, however, had significantly lower odds of achieving the indicators than those without anxiety (OR_adjusted = 0.50; 95% CI: 0.26–0.97; p = 0.04). Other factors in multivariable analyses, including age, sex, race, education level, insurance status, transportation barriers, alcohol risk, and disclosure, were not statistically significant (Table 3).

Additional analyses that evaluated factors associated with meeting criteria for all five indicators were consistent with initial findings (meeting criteria for four or more indicators) with respect to monthly income > $1,000 USD versus those who had a monthly income of less than or equal to $1,000 USD (OR_adjusted = 1.96, 95% CI: 1.20–3.19; p = 0.01). Neither association of depression nor anxiety was found to be statistically significant. Age was found to have a significant association in this model, though the strength of association was not strong (OR_adjusted = 0.97; 95% CI: 0.95–0.99; p = 0.003) (Data not shown).

Discussion

In this study, we found that more than 80% of new patients achieved at least four of five composite IOM core clinical indicators during their first 12 months of outpatient HIV primary care. Among this cohort, reporting an individual income exceeding $1,000 USD per month and reporting no anxiety symptoms were significantly associated with achieving the selected indicators. It is noteworthy that patients with depressive symptoms were significantly more likely to achieve four of the five IOM indicators than those who did not meet criteria for depression. We anticipate that patients in this cohort with reported depression may be more likely to be referred for professional assistance or seek additional resources from the co-located psychology and psychiatry clinics at this site, and may therefore become more engaged in regular care than those who do not experience depression.

These findings are particularly salient, as early retention in HIV primary care is associated with virologic suppression, and patients who do not arrive for regularly scheduled HIV primary care appointments are less likely to begin ART, less likely to respond optimally to ART, more likely to transmit HIV to others, more likely to be hospitalized, and less likely to survive.^{3,5,7,10

–13}

Our findings are consistent with current literature demonstrating that HIV-positive persons with lower socioeconomic status and those with a greater number of unmet service needs are less likely to enter HIV care in a timely fashion and less likely to remain in regular care,⁷ and that poverty is associated with advanced disease at care entry ^27,28 and poorer adherence to ART.²⁹ As poverty is also associated with worse attendance at clinic appointments,³⁰ our results validate the recommendation of the NHAS for increased access to nonmedical, supportive services and HIV-specific programming “to address gaps in essential services for people living with HIV”.¹

Because persons who struggle to meet basic needs may be less likely to have resources to devote to healthcare,^31,32 subsidizing intervention programs, such as the Ryan White HIV/AIDS Program²⁷ remains essential for facilitating appointment attendance and for securing prescribed medications for persons initiating HIV care. As two-thirds of our sample reported monthly income of less than or equal to $1,000 USD, our findings underscore the need for adequately funded programming to assist people who struggle with both HIV and poverty.

While recent investigations have examined the influence of mental health co-morbidities in HIV care, anxiety-focused research has demonstrated mixed findings with respect to adherence and health outcomes overall.^31,33

–36 Variation across findings may be the result of differences in characteristics of patient populations, mechanisms of determining the presence and severity of anxiety symptoms, and/or methods for measuring and classifying anxiety.^24,37

In this investigation, new patients with anxiety were less likely to achieve the selected core indicators than persons without anxiety. This may illustrate a need to initiate early referrals for psychiatric treatment or behavioral counseling services for patients whose intake assessments indicate elevated anxiety, as addressing psychosocial needs is an essential step toward improving adherence, retention in care and viral suppression.³⁸ Additionally, resources that evaluate and address anxiety at HIV care initiation may facilitate achievement of the IOM indicators during the first year, potentially improving health outcomes overall, as well as facilitating psychological adjustment to living with HIV.

Age, sex, race, education level, insurance status, transportation barriers, alcohol use, and disclosure of HIV status to family were not associated with achieving the composite core indicator measure. However, the significance of these factors may have been diminished as a result of existing standard of care services at the study site; this includes intensive case management, Ryan White HIV/AIDS Program services, AIDS Drug Assistance Program (ADAP), structured clinic orientation needs assessment, and availability of multiple local HIV service organizations. Notwithstanding this level of available programming, patients who reported monthly income of less than or equal to $1,000 USD were significantly less likely to achieve the selected IOM core indicators.

This study was limited by a modest sample size, which may have constrained the ability to detect statistically significant differences between groups. Second, because follow-up was limited to a 12-month period, we were unable to assess the indicator for all-cause mortality. However, we note the understudied and important role of the dynamic period following initial entry into medical care and potential implications on longer term outcomes.

While we elected to evaluate combined total sums of core indicators per availability, clinical significance, and the cyclical nature of these factors that impact each other (for example, a person who does not attend regularly scheduled visits does not undergo CD4 and viral load testing and may be unable to initiate antiretroviral therapy), similar investigations may elect to weigh each of these indicators according to other considerations, including associated acute or longitudinal clinical consequences, such as morbidity or mortality.^4,39
–41 In addition, this investigation's findings reflect a convenience sample of a cohort of persons initiating care at an urban, academically-affiliated clinic in the Southern US, so results may not be generalizable to HIV clinics nationwide, particularly those in rural or underserved areas, or sites without equivalent resources.

Conclusions

Based upon these findings, it remains crucial to examine the distinct needs of patients entering HIV medical care who report limited income, as well as persons who report elevated anxiety or panic symptoms at clinic intake. Financial assistance or service subsidization for patients whose monthly income is less than or equal to $1,000 USD is essential for addressing socioeconomic healthcare barriers. Early screening for anxiety symptoms may also identify persons who would benefit from additional support services, and may facilitate referrals to counseling and mental health and wellness programs that aim to improve retention in HIV care and adherence to prescribed drug therapies.

Additionally, facilitating early access to psychology, psychiatry, or community mental health professionals who monitor and manage treatment of anxiety symptoms may be crucial for improving HIV outcomes overall. The ongoing development and evaluation of programming to address factors associated with limited income and elevated anxiety at clinical intake will be vital for promoting the achievement of IOM clinical indicators during the first year of HIV outpatient care.

Footnotes

Author Disclosure Statement

No conflicting financial interests exist.

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