Individual and Organizational Characteristics of Effective Frontline Practitioner Performance: A Study of Los Angeles County HIV Testing Organizations

Abstract

AIMS.

This study examines the strategic contributions of three Frontline Practitioner (FP) attributes for effective HIV testing: risk assessment use, having specialized HIV training, and organizational test setting (nonprofit, forprofit, and public).

METHODS.

Data from 621staff in 159 organizations in Los Angeles County, are used to model individual and organizational correlates and use of risk assessment and measures of effective performance (volume of HIV tests, HIV seropositive tests, and referrals to treatment).

RESULTS.

FP with specialized training in HIV care situated in nonprofit outpatient clinics are more likely to use risk assessment. Nonprofit outpatient clinics, FP with specialized training in HIV, and risk assessment use are associated with higher HIV test volume.

DISCUSSION AND IMPLICATIONS FOR POLICY AND PRACTICE.

FP with specialized HIV training in nonprofit outpatient settings offer testing/counseling services qualitatively different from FP in other settings.

Introduction

As of 2008 there are approximately 1.2 million persons living with AIDS (PLH) in the United States, 20% of whom are unaware of their serostatus (CDC, 2011). This translates to about 236,400 persons with an estimated forward transmission of 24,600 per year to seronegative partners (Holtgrave et al, 2012). In addition, of the population of PLH aware of their serostatus, approximately 16% or 150,712 persons continue to engage in high risk behaviors with an estimated forward transmission to 25,600 persons per year (Holtgrave et al, 2012). This places a significant number of the general population at risk of infection; specifically, an estimated 9.2% of the population 15–44 years old engages in behaviors that place them at risk (Holtgrave et al, 2012).

Identifying specific risk behaviors is a critical component of a comprehensive and effective prevention strategy as certain risk behaviors, such as transmission through intravenous drug use, may have both individual and structural determinants (Holtgrave et al, 2012). This implies that there may be distinctive treatment approaches to “disrupt the pathway” of infection depending on the type of group at risk (Holtgrave et al, 2012). A “combination prevention” approach has been advocated that involves behavioral, biomedical, and structural interventions (Holtgrave, 2007; Holtgrave et al, 2012; Merson et al, 2008; Coates et al, 2008). However, HIV testing practitioners may differ with respect to how services are provided and how recommended HIV testing protocols are implemented. This study hypothesizes that three specific frontline practitioner attributes (risk assessment, HIV expertise, and nonprofit outpatient setting) are related to effective testing performance.

Literature Review and Research Questions

Policy is implemented through organizations and further interpreted and enacted by frontline practitioners (FPs) commonly designated as “street-level bureaucrats.” This refers to workers in human service and healthcare organizations who are charged with the task of interacting with clients or patients. A great deal of research in this area has focused on human services caseworkers and police officers. At the policy level, this work has emphasized how the implementation of human service and healthcare organizational goals is greatly impacted by the behavior of these lower-level organizational members (Brodkin, 1997; Lipsky, 1980; Mullen and Bacon, 2004).

For HIV prevention policy, health practitioners and researchers agree that the steps in an effective prevention protocol are to identify, educate, counsel, and test individuals engaging in behaviors that place them at risk of infection. Evidence suggests that when persons who are HIV-infected learn of their seropositivity, they take steps to improve their health and prevent transmittal of the virus to others. Meta-analyses of cross-sectional comparisons of persons living with HIV and longitudinal studies of seroconverting individuals demonstrate that persons living with HIV aware of their serostatus are at least half as likely to engage in sexual risk behaviors compared to unaware persons living with HIV (Weinhardt et al., 1999; Marks, et al., 2005 and 2006; Pinkerton & Galletly, 2007).

FP risk assessment may be an effective tool as a precursor to conducting an HIV test. As part of an initial pre-test counseling session, conducting a risk assessment may help educate clients about their risk behaviors and make them aware of their vulnerability to HIV infection (Smith et al, 2005). This tool may also help enumerate the group of HIV seronegative persons at risk and identify the sub-population of PLH unaware of their seropositivity who are engaging in high-risk behaviors (such as misusing drugs, having multiple partners; not using condoms; etc.). Consequently FP may tailor treatment specific to each client group. The use of a risk assessment tool can also increase the overall volume and efficiency of testing as it may help screen low-risk individuals and focus testing and counseling efforts on high-risk individuals (Manavi, 2006).

Past studies that have examined the use of risk assessment have primarily examined individual level factors. Rountree (2005) in an exploratory study of HIV prevention services in domestic violence shelters, suggests that enhanced training of staff in HIV counseling and education was important in using risk assessments. Similarly, Tessaro & Highriter (1995) in their study of public health nurses’ conduct of HIV education and risk assessment found that greater knowledge of HIV is an important predictor and suggests that nurses should have further, specialized HIV training. It is largely unknown, however, what organizational level factors are associated with the use of risk assessment. The extent to which HIV testing FP follow federal, state, and local public health guidelines and protocols, such as use of risk assessment, is important for both policy and practice. This is particularly relevant for FP in nonprofit organizations, and those receiving federal, state, or local subsidies. For populations at higher risk of infection (i.e., adolescents, young adults, Blacks, Latinos, MSM, etc.), testing accompanied by education and counseling sessions are likely to be more effective at changing risk behaviors (Kaiser Family Foundation, 2011a; 2011b). Given that HIV testing occurs in inpatient and outpatient, as well as health and non-health settings, and that providers may serve distinct populations, it is important to understand how settings differ in their use of risk assessment. At the individual level, specialized training in HIV prevention and services may also be an important predictor for use of risk assessment. This study focuses on four questions:

1. Are nonprofit FP more likely than FP in other organizations to use risk assessment?

2. Are FP with specialized training in HIV care and services more likely than FP without this training to use risk assessment?

3. Does the use of risk assessment correlate with testing effectiveness as measured by a higher volume of tests?

4. Does use of risk assessment correlate with the identification of a greater number of HIV-seropositive individuals and their referral to treatment?

HIV test settings: Specification of the model

With the advance of testing techniques and technologies, testing is increasingly occurring in non-health related and thus less-regulated and less-restrictive settings. While this has the potential for increasing the availability of testing for vulnerable populations and those at higher risks for HIV, it also has potential implications for the quality of testing and results. Organizational test settings encompass inpatient health providers such as hospital emergency rooms; outpatient health providers such as private forprofit, nonprofit, or public clinics; and non-health settings such as nonprofit community based service organizations and mobile testing units (CDC, 2001).

Across these different organizational test settings, there may be differences in the populations served, testing outcomes, and HIV testing protocol such as use of risk assessment. For example, among inpatient settings, testing may be confirmatory rather than preventive as some patients are in advanced stages of AIDS and are admitted for symptoms arising from related conditions such as pneumonia. Inpatient test settings require little need for pre-test counseling sessions, education, or other interventions aimed at altering patient behavior. Outpatient test settings, both health and non-health, typically serve a more diverse range of patients and engage in preventive testing that may involve pre-test counseling sessions, risk assessment, and other intervention and educational strategies.

Further, the commoditization of medical services and the shift in HIV/AIDS care to one of chronic illness rather than terminal disease has led profit seeking organizations to enter the HIV/AIDS services industry and have led to what some have referred to as “medical capitalism” (Craddock, 2006). With over US$10 billion in financing for HIV research worldwide in 2007 (Sulzbach et al, 2011), the entry of forprofit business may have shifted incentives for research, prevention and treatment (Craddock, 2006; Beaudin & Chambre, 1996). The impact of this shift on testing outcomes, treatment and testing protocol, and adherence to regulatory guidelines is unclear. Thus, an organization’s ownership structure, such as nonprofit, forprofit, or public, may be indicative of organizational priorities and responsiveness to external influence including mandates or recommendations by regulatory and funding agencies (Powell & DiMaggio, 1991). An organization that is profit-oriented may focus its organizational priorities on revenue generating services (i.e., treatment of HIV positive patients) and those that are nonprofit or publicly owned may serve a greater number of lower income clientele and focus more on non-revenue generating, preventive activities like education, advocacy, and testing-).

Nonprofit providers may also be more knowledgeable and sensitive to the needs of the communities in which they serve. The staff, FP, and counselors are often drawn from those communities (Kelly et al, 2000). Focused on a social mission and as first responders to the HIV/AIDS epidemic (Shilts, 2000; Chambre, 1997; Chambre, 1999), FP working in nonprofit organizations may place greater emphasis on advocacy, education, and increasing awareness.

Specialized training in HIV services may also be an important predictor for using risk assessment. As a form of pre-test counseling, HIV specialists and those trained in counseling and testing may be more concerned with changing behavior and education among high risk individuals rather than just increasing the number of persons tested. General medical practitioners not specifically trained in HIV may be unfamiliar with instruments such as county public health risk assessment. Non-medical FP with certified training in counseling and testing may also value pre-test counseling sessions and use risk assessment because they are drawn from communities in which they serve, particularly in nonprofit test settings. Thus, it is hypothesized that:

H1: FP in nonprofit outpatient test settings, are more likely to use risk assessment compared to FP in other test settings.

H2: FP with certified training in counseling and testing and HIV specialist physicians and nurses are more likely than others to use risk assessment.

Since risk assessment may help streamline the testing service by targeting resources to high-risk individuals and focus on education and counseling, it is hypothesized that:

H3: Nonprofit outpatient test settings with certified FP trained in counseling and testing and/or HIV specialist physicians and nurses who use risk assessment will conduct a higher volume of HIV tests compared to FP in other test settings.

If risk assessment serves to identify high risk individuals and nonprofit FP are more likely to use risk assessment, then:

H4: Nonprofit outpatient test settings with certified FP trained in counseling and testing and/or HIV specialist physicians and nurses who use risk assessment will detect more HIV-seropositive patients than FP in other settings.

Methods, Data, and Measures

Study Design and Sample

Los Angeles County ranks second after New York City among the 12 metropolitan statistical areas with the largest number of HIV/AIDS cases in the nation. The County’s HIV prevention issues are made more complex by its geographical size as its 4,084 square miles makes it the largest county in the U.S. with a population greater than 43 of the 50 states. 2006 census data reveal that the county is ethnically diverse and has 47% Hispanics/Latinos; 29% Whites; 13% Asian/Pacific Islanders; 9% African-Americans; and 2% others or multiple ethnicities. The County Public Health Department estimates that there are 62,800 persons living with HIV/AIDS and that more than one in five (21.5%) are unaware of their infection (Perez M, 2011).

The data for this paper is gathered from a study that surveyed health care organizations providing HIV tests in Los Angeles County from 2003 through 2007. The study assessed all aspects of HIV testing processes including risk screening, pre-test counseling, post-test counseling, supervisory practices, and organizational policies and factors. Organizations were enumerated and sampled from seven strata: forprofit private practices, monprofit community-based organizations, public health STD clinics, and personal health centers, mobile testing units operated by the public health departments or through contracts to community-based organizations, and three strata of hospitals: forprofit, nonprofit, and county public. Within each organization up to six front-line providers of HIV testing and counseling services (such as physicians, nurses, public health investigators, outreach workers) were enumerated and randomly selected for interview. In addition, up to three managers at each organization (such as executives, clinic managers, testing supervisors) were selected for interviews. Overall, 621 staff were interviewed from 159 organizations.

Chief executive or medical officers provided consent for organizational participation. Staff participation was completely voluntary with separate informed consent. Face to face computer-assisted personal interviews (CAPI) assessed respondents’ background characteristics, experience, and training as well as HIV testing expertise, and working roles/responsibilities. Organization-level data was collected in manager interviews in forms completed by administrators, and from local public health departments. The present study was undertaken prior to the adoption and implementation of “opt-out” HIV testing (Institute of Medicine, 2010). The study procedures were approved by the UCLA Office for the Protection of Research Subjects. Table 1 summarizes the final dataset used for analysis.

Table 1.

Organizational Factors in HIV Testing Dataset

Setting	Type of Organization	N of orgs	Org-level response rate	N of respondents
Hospital(a)	Private for profit	15	45%	63
Hospital	Private nonprofit	34	71%	130
Hospital	County government	5	100%	23
Non-hospital(b)	Private for profit	19	51%	50
Non-hospital	Private nonprofit	44	77%	189
Non-hospital	County government	28	88%/100%	121
Mobile	Nonprofit &Co. Govť	14	100%	45
Total		159		621

^(a)Hospital test settings are inpatient test settings.

^(b)Non-hospital test settings are outpatient test settings.

Measures and Analysis Procedures

For use of risk assessment as a precursor to conducting an HIV test, FP were asked about the most recent patient seen in the past six months in which an HIV test was conducted: “How were factors to test brought to their attention?” Respondents were given the following choices: volunteered by the patient, physical symptoms, risk assessment conducted by respondent, indicated in routine medical history, or another way. Respondents who indicated, “risk assessment conducted,” were coded 1 and those who indicated other factors were coded 0. Three additional dependent variables at the organization level were modeled to examine the relationship between the use of risk assessment and organizational effectiveness. These are the total number of tests conducted, the number of HIV-seropositive persons detected, and the number of HIV-seropositive patients referred to treatment. An HIV-seropositive test refers to a positive test result from either OraQuick Advance Rapid HIV ½ antibody, or Western blot test. Detection of HIV-seropositive tests by non-hospitals or outpatient clinics refers to two-three Rapid tests showing positive results, this is a standard testing algorithm employed by many non-hospital outpatient clinic test providers. Hospitals must confirm with the Western blot test all HIV-seropositive patients and in this case, a confirmatory test may also be viewed as detection. Thus, while HIV-seropositive tests among non-hospitals refers primarily to an initial positive screening for HIV; an HIV-seropositive test among hospitals can refer to either an initial positive screening for HIV or a confirmatory Western blot test.

For outcome number one, the use of FP risk assessment, the primary predictor variables at the individual level are FP trained in counseling and testing, coded 1 for certified training and 0 for no certified training; HIV specialist physicians coded 1 for specialist and 0 for non-specialist; HIV specialist nurses coded 1 for specialist and 0 for non-specialist. Respondents’ average scores on an 11- item Likert scale questionnaire regarding their awareness and sensitivity to cultural differences and barriers to HIV health services were also included.

At the organizational level, the primary predictor variable is the seven organizational test settings which include three inpatient test settings: nonprofit, forprofit, and public hospital emergency rooms; and four outpatient test settings: nonprofit community- based organizations and clinics, forprofit clinics, public clinics, and mobile testing units. Additional organizational level covariates include the proportion of HIV tests conducted over total number of patients seen as a measure of organizational size, percentage of public funding received by the organization, and use of Oraquik Rapid tests coded 1 for yes and 0 for no. Table 3 summarizes the risk assessment variable by individual level and organizational level covariates for outcome number one.

Table 3.

Ns and Percent of FP Risk Assessment by Individual and Organizational Level Covariates^(a)

		Risk assessment	No Risk Assessment(b)
Individual Level Covariates
Training in HIV testing and counseling
	No	43 (23%)	44 (47%)
	Yes	146 (77%)	49 (53%)
	Total	189	93
HIV specialist physician
	No	173 (91%)	84 (90%)
	Yes	16 (8%)	9 (10%)
	Total	189	93
HIV specialist nurse
	No	185 (98%)	87 (93%)
	Yes	4 (2%)	6 (6%)
	Total	189	93
Cultural sensitivity(c)		3.4	3.3
Organizational Level Covariates
Organizational test settings
forprofit inpatient hospitals		12 (6%)	7 (8%)
nonprofit inpatient hospitals		28 (15%)	14 (15%)
public inpatient hospitals		4 (2%)	2 (2%)
Forprofit outpatient clinics		18 (10%)	22 (24%)
Nonprofit outpatient clinics		57 (30%)	23 (25%)
Public outpatient clinics		48 (25%)	23 (25%)
mobile testing units		22 (12%)	2 (2%)
Total		189	93
% HIV tests(d)		22.8%	8.3%
% Public Funding		63.8%	54.8%
OraQuick Advance Rapid test		28.9%	17.6%

^(a)How factors in conducting an HIV test were brought to attention of FP patient

^(b)Volunteered by patient, Physical Symptoms, Indicated in routine medical history, or other

^(c)Average score on 11 item cultural sensitivity questionnaire (range 1–4)

^(d)Percent of total patients seen

For outcomes two to four, the number of HIV tests conducted, the number of HIV-seropositive tests detected, and the number of HIV-seropositive patients referred to treatment, the original seven organizational strata were recoded into the following combination of FP attribute groups: (1) nonprofit outpatient test settings with FP who is an HIV specialist physician or nurse and/or trained in HIV counseling and testing and use of risk assessment; (2) nonprofit outpatient test settings with FP who is an HIV specialist physician or nurse and/or trained in HIV counseling and testing; (3) nonprofit outpatient test settings and use of risk assessment; (4) other test settings with FP who is an HIV specialist physician or nurse and/or trained in HIV counseling and testing and use of risk assessment; (5) nonprofit outpatient test settings only; (6) other test settings with FP who is an HIV specialist physician or nurse and/or trained in HIV counseling and testing; (7) other test setting and use of risk assessment only; (8) other test settings with no FP who is an HIV specialist physician or nurse and/or trained in counseling and testing and no risk assessment used. Nonprofit inpatient hospital test settings are not grouped with nonprofit outpatient test settings (Group 1) due to the characteristics of the hospital field, which is highly institutionalized and regulated thus homogenizing activities across all hospitals (this point is elaborated in the discussion section). Table 2 presents a cross tabulation of the original test settings with the recoded test settings.

Table 2.

Cross tabulation of original and recoded outpatient/inpatient test settings

	(Group 1) NP&specialized training&risk	(Group 2) NP&specialized training	(Group 3) NP&risk	(Group 4) Specialized training&risk	(Group 5) NP only	(Group 6) Specialized training only	(Group 7) Risk only	(Group 8) None	Total
forprofit inpatient hospitals	-	-	-	8	-	4	-	3	15
nonprofit inpatient hospitals	-	-	-	21	-	7	-	2	30
public inpatient hospitals	-	-	-	3	-	2	-	-	5
forprofit outpatient non-hospitals	-	-	-	14	-	5	-	-	19
nonprofit outpatient non-hospitals	25	3	3	-	5	-	-	-	36
public outpatient non-hospitals	-	-	-	20	-	2	2	-	24
mobile testing units	-	-	-	11	-	1	0	-	12
Total	25	3	3	77	5	21	2	5	141

The models were fit using a multilevel random effects logistic regression model for the first outcome and a negative binomial regression model for outcomes two to four. One hundred sixty-six individuals were nested within 85 organizations with an average of two persons per organization and a range from a minimum of one to a maximum of five individuals per organization. The final models were fit in Stata 11 using the xtmelogit and nbreg commands (Rabe-Hesketh & Skrondal, 2006).

Results

Descriptive Univariate Statistics

HIV testing/counseling FP (N=616) were 46% male. Their average age was 44 (SD=11); and they were 39% White, 21% Hispanic/Latino, 11% African-American, and 12% Asian. With regard to highest educational degree earned, approximately 31% were medical doctors, 22% had a bachelor’s degree, 15% had a masters degree, 15% an associates degree, 13% a high school GED, and 2% a Ph.D. The average tenure was 8.8 years (SD=8.8) in their respective organizations and 5.6 years (SD=6.6) in their current position.

Approximately 349 or 57% of FP had training in HIV counseling and testing. Thirty five percent are in nonprofit outpatient test settings, followed by 27% in public outpatient test settings and 12% in mobile testing units. There are no FP trained in HIV counseling and testing in FP outpatient clinics. Ten percent of the sample or 61 FP are HIV specialist physicians with 34% in forprofit outpatient settings and 38% in nonprofit inpatient hospital settings. Approximately 13 or 2% of the sample are FP HIV specialist nurses with the majority, 46% in forprofit outpatient test settings followed by 38% in public outpatient test settings. Finally, of the 61 FP who are HIV specialist physicians, 40 or 66%, are also trained in HIV counseling and testing. Among HIV specialist nurses, 54% are also trained in HIV counseling and testing. Henceforth, FP who are either trained in HIV counseling and testing, HIV specialist physicians or nurses, or a combination of these, are referred to as FP with “specialized training in HIV.”

FP were asked to provide a description of their most recent HIV seronegative and HIV seropositive test client/patient. To facilitate accuracy they were encouraged to examine their client/patient charts. Among FP with seronegative test clients (N=301), the client average age was 33 years (SD=11); 68% were male, 31% female, and 1% transgender; 39% were Hispanic/Latino, 32% White, 19% African-American, and 7% Asian/Pacific Islander. Seronegative test clients were also classified according to their County Public Health Department definitions of Behavioral Risk Groups (BRG): 23% were men who have sex with other men (MSM); 16% were women at sexual risk (WSR); 10% were intravenous drug users (IDU); 7% were men who have sex with other men and women (MSM/W); and 43% were other BRG. Among the HIV seropositive clients (N=146), the average age was 34 years (SD=9); 92% were male, 7% female, and 1% transgender; 37% were Hispanic/Latino, 35% were White, 19% African-American, and 1% Asian/Pacific Islander. Among BRG, 61% were MSM, 10% MSM/W, 6% IDU, 3% WSR, and 18% other.

Table 3 summarizes the risk assessment dependent variable along with individual and organizational level predictors. Of the 282 respondents to this question, 189 indicated use of risk assessment while 93 indicated that factors to conduct an HIV test were brought to the attention of the respondent in some other way. Among those with certified training in HIV counseling and testing, 77% (146 respondents) indicated use of risk assessment and 23% (43) without training indicated use of risk assessment. Among HIV specialist physician and nurses, 8% (16) and 2% (4) respectively indicted use of risk assessment. Respondents who used risk assessment also scored, on average 3.4 on a four point 11 item questionnaire regarding respondent’s cultural sensitivity (vs. 3.3 for others).

At the organization level, 30% (57) of respondents who use risk assessment were from a nonprofit outpatient test setting followed by 25% (48) from public outpatient settings, and 15% (28) from nonprofit in-patient settings. Additionally, among organizations in which respondents use risk assessment, on average, 23% of total patients seen were given HIV tests, public funding comprised 64% of total revenue, and 29% indicated use of the OraQuick Advance Rapid test.

Tables 4–6 provide summary statistics of the three organizational outcomes by the recoded organizational test settings. Nonprofit outpatient test settings that use risk assessment conduct on average, the highest number of tests at 6,905; as a percentage of total patients seen, nonprofit outpatient settings with no staff with specialized training and no use of risk assessment conducted the highest percentage 59% (Table 4). For the number of HIV-seropositive patients detected (Table 5), group 1, nonprofit outpatient settings with HIV specialists on staff who use risk assessment, are about equal with group 6, while other test settings with only HIV specialists on staff with no use of risk assessment, with on average 43 and 39 tests respectively. As a percentage of the number of HIV tests conducted, Group 6, specialists only, has the highest percentage at 12% (Table 5). Finally, all groups have a high percentage of referring HIV-seropositive patients to treatment with group 6, specialists only having the highest percentage at 97% (Table 6).

Table 4.

Summary of N and percent of HIV tests conducted by nonprofit outpatient test setting, HIV specialists and/or trained HIV counselors, and risk assessment use

	Mean number of HIV tests (n)	Mean percentage of HIV tests (n)(a)
(Group 1) NP&specialized training&risk	1,692 (16)	38% (14)
(Group 2) NP&specialized training	1,626 (1)	5 (1)
(Group 3) NP&risk	6,905 (2)	52 (2)
(Group 4) Specialized training&risk	1,222 (65)	19 (60)
(Group 5) NP only	1,384 (4)	59 (4)
(Group 6) Specialized training only	1,453 (17)	6 (15)
(Group 7) Risk only	33 (2)	6 (2)
(Group 8) None	700 (5)	1 (4)
Total	1,391 (112)	21 (102)

^(a)Number of HIV tests conducted divided by number of patients seen

Table 6.

Summary of N and percent of HIV-seropositive persons tested referred to treatment by nonprofit outpatient test setting, HIV specialists and/or trained HIV counselors, and risk assessment use

	Mean number of HIV-seropositive persons referred to treatment (n)	Mean percentage of HIV-seropositive persons referred to treatment (n) (a)
(Group 1) NP&specialized training&risk	36 (12)	80% (11)
(Group 2) NP&specialized training	37 (1)	95% (1)
(Group 3) NP&risk	48 (2)	71% (2)
(Group 4) Specialized training&risk	17 (32)	77% (32)
(Group 5) NP only	11 (3)	61% (3)
(Group 6) Specialized training only	8 (5)	97% (5)
(Group 7) Risk only	-	-
(Group 8) None	-	-
Total	21 (55)	79% (54)

^(a)Number of HIV-seropositive persons referred to treatment divided by number of HIV-seropositive persons tested

Table 5.

Summary of N and percent of HIV-seropositive persons tested by nonprofit outpatient test setting, HIV specialists and/or trained HIV counselors and risk assessment use

	Mean number of HIV-seropositive persons (n)	Mean percent of HIV-seropositive persons (n) (a)
(Group 1) NP&specialized training&risk	43 (13)	2% (16)
(Group 2) NP&specialized training	39 (1)	2% (1)
(Group 3) NP&risk	98 (2)	2% (2)
(Group 4) Specialized training&risk	22 (57)	4% (57)
(Group 5) NP only	20 (3)	2% (3)
(Group 6) Specialized training only	39 (15)	12% (14)
(Group 7) Risk only	3 (2)	9% (2)
(Group 8) None	20 (3)	4% (3)
Total	29 (96)	5% (95)

^(a)Number of HIV-seropositive persons divided by number of HIV tests conducted

Multilevel Logistic Regression and Negative Binomial Regression Analysis

Table 7 presents the results of the multilevel model. At the individual level, HIV specialist physicians are predicted to have 17 times higher odds of using risk assessment as a precursor to testing compared to non-HIV specialists. FP trained in counseling and testing are also predicted to have higher odds of using risk assessment (4.6 times higher) compared to those without certification and training.

Table 7.

Multilevel Random Intercepts Logistic Regression of FP Risk Assessment Use

-	Odds Ratio	Lower Interval	Upper Interval
Individual Level Predictors (a)
HIV Specialist Physician	17.4 *	1.6	188.8
HIV Specialist Nurse	1.1	0.1	9.0
Training	4.6 *	1.3	15.8
cultural sensitivity	0.9	0.4	2.1
Organizational Level Predictors (b)
Ref: Nonprofit outpatient non-hospital
forprofit inpatient hospitals	1.2	0.2	10.1
nonprofit inpatient hospitals	1.1	0.2	5.5
public inpatient hospitals	1.5	0.1	19.4
forprofit outpatient non-hospitals	0.003 *	0.0	0.3
public outpatient non-hospitals	2.1	0.6	7.5
mobile testing units	5.6	0.5	58.1
HIV tests (proportion)	19.1 *	2.4	153.6
Public Funding	0.95 *	0.9	1.0
OraQuick Advance Rapid test	1.4	0.5	4.0
	coef.	se
constant	0.2	1.6
Random effects parameters	est.	se
Organizations	0.2	1.0

^*p<.05

^(a)N=166

^(b)N=85

At the organizational level, forprofit outpatient settings are predicted to have lower odds of using risk assessment compared to nonprofit outpatient settings while controlling for the proportion of HIV tests conducted, public funding, testing technology, and individual level variables. A one percent increase in the proportion of HIV tests (over total number of patients seen) conducted is correlated with higher odds of using risk assessment when controlling for organizational and individual level variables. On the other hand, higher percentage of public funding is correlated with slightly lower odds of using risk assessment. Specifically, a one percent increase in public funding is correlated with 5% lower odds of using risk assessment.

Table 8 present the results of a negative binomial regression model estimating the rate at which tests are conducted (Model 1); the rate at which HIV-seropositive tests are detected (Model 2); and the rate at which HIV-seropositive tests are referred to treatment (Model 3). These three outcomes are compared across the eight recoded test settings with Group 1, nonprofit outpatient test settings with HIV specialists and counselors on staff and who use risk assessment, as the reference group. For Model 1, Group 6, other test settings with HIV specialists and trainers who do not use risk assessment, and Group 8, other test settings with no HIV specialists and trainers on staff and who do not use risk assessment, are predicted to conduct HIV tests at a lower rate compared to Group 1. In Model 2, Group 6 is estimated to detect HIV-seropositive individuals at a higher rate compared to Group 1. Model 3 shows no significant difference between the eight groups in terms of the rate at which HIV-seropositive patients are referred to treatment.

Table 8.

Negative Binomial Regression of HIV Tests, HIV-seropositive Persons, and HIV-seropositive Persons Referred to Treatment

	Model 1 (HIV tests)(N=102)(a)				Model 2 (HIV-seropositive persons) (N=95)(b)				Model 3 (HIV-seropositive persons referred to treatment)(n=54)(c)
REF: (Group 1) NP&specialized training&risk	IRR	p	95% C.I.		IRR	p	95% C.I.		IRR	p	95% C.I.
(Group 2) NP&specialized training	0.14	0.21	0.01	2.94	1.43	0.76	0.14	14.48	1.27	0.50	0.64	2.52
(Group 3) NP&risk	1.38	0.77	0.15	12.51	1.09	0.92	0.20	5.96	0.85	0.57	0.49	1.47
(Group 4) Specialized training&risk	0.50	0.12	0.21	1.19	2.06	0.05	1.02	4.16	0.99	0.96	0.75	1.32
(Group 5) NP only	1.58	0.59	0.30	8.22	0.92	0.92	0.22	3.91	0.72	0.25	0.41	1.26
(Group 6) Specialized training only	0.15	0.00	0.05	0.45	4.99	0.00	1.96	12.71	1.28	0.32	0.79	2.06
(Group 7) Risk only	0.17	0.11	0.02	1.54	5.38	0.08	0.84	34.62	-	-	-	-
(Group 8) None	0.02	0.00	0.00	0.10	2.17	0.31	0.48	9.77	-	-	-	-

^(a)exposure variable: number of patients seen

^(b)exposure variable: number of HIV tests

^(c)exposure variable: number of HIV-seropositive persons tested

Discussion

Three of the four hypotheses are supported by the findings of this study. Specifically, we found support for H1 and H2, that nonprofit outpatient clinic FPs are more likely to use risk assessment compared to forprofit outpatient clinics and specialized training in HIV services is associated with higher odds of using risk assessment. Support was also found for H3, nonprofit outpatient test settings with certified FP trained in counseling and testing and/or HIV specialist physicians and nurses who use risk assessment conduct a higher volume of HIV tests compared to two other test settings. No support was found for H4, nonprofit outpatient test settings with certified FP trained in counseling and testing and/or HIV specialist physicians and nurses who use risk assessment do not detect HIV-seropositive individuals and refer them to treatment at a higher rate compared to other test settings.

Findings from this study have implications for both practice and policy. For practice, the finding that FP with specialized HIV training as well has FP working in nonprofit settings (Table 7), have higher odds of using risk assessment suggests a qualitative difference in how these FP view HIV testing and prevention. As a form of pre-test counseling, risk-assessments may be more valued by HIV specialists and those trained in counseling and testing because, in addition to identifying HIV seropositives, they may also be concerned with identifying and educating other high-risk and at-risk groups, especially HIV seronegatives and seropositives who engage in risky behaviors.

General medical practitioners may not view risk assessment as a critical component of an overall HIV testing protocol. MDs who are not HIV specialists and/or certified in counseling and testing, may focus on testing rather than counseling and education. Additionally, for some MDs working in forprofit settings, the emphasis may, in part, be placed on income- generating activities such as identifying HIV-seropositive clients and referring them for subsequent anti-retroviral treatment rather than on counseling, education, or other preventive measures. We found that 66% of respondents with medical degrees (MDs) were also trained in counseling and testing compared to 73–100% of non-medical degree holders, including Ph.Ds. Among outpatient clinics, forprofits have a higher percentage of FP with medical degrees compared to other test settings: 48% compared to 12% in nonprofits and 27% in public clinics. Those trained in counseling and testing, on the other hand, were often non-medical professionals and stakeholders drawn in part from communities they serve (e.g., gay men of color). These stakeholders, therefore, may be more likely to view use of risk assessment as an important prevention and education strategy.

FP in nonprofit outpatient test settings are also more likely to use risk assessment and thus provide HIV services qualitatively different compared to FP in forprofit outpatient settings. As scholars suggest, the nonprofit organizational form is suited to provide health, human, and social services (Anheier, 2005; Schlesinger & Gray, 2006). Nonprofits are typically guided by a social mission and legally constrained from distributing profits to managers or directors for personal gain, and therefore are more community-focused and generally more knowledgeable of and sensitive to the needs of the communities they serve (Kelley et al 2006). The founders of nonprofits are frequently altruists and social entrepreneurs motivated by moral and ideological values and therefore have strong beliefs about how to change society, communities, and individual behavior (Rose-Ackerman, 1986). Finally nonprofit providers are considered more trustworthy due to the legal constraint from distributing profits for personal gain, and by favoring investment in its mission, may also result in higher quality and more effective services (Hansmann, 1996). These qualities of nonprofit organizations may help explain why their FPs are more likely to use risk assessment and conduct a higher number of HIV tests.

It is not surprising, therefore, that the three FP attributes of specialized training, risk assessment use, and nonprofit outpatient test setting (Group 1) is significantly different only from two other combinations of FP attributes with respect to volume of HIV tests conducted: specialized training only (Group 6) and FP with none of the three attributes (Group 8). Approximately 86% of the test settings in Group 6, specialized training only, consist of hospital emergency rooms or forprofit outpatient clinics and 100% of test providers in Group 8 are hospital emergency rooms (Table 2). In other words no significant difference was found between nonprofit outpatient clinics or those with test settings that have FP with specialized training in HIV and/or use risk assessment.

By integrating risk assessment into its testing protocol, FP may streamline testing by spending less time on low- risk individuals and targeting testing and counseling efforts to high- risk individuals thereby increasing overall testing efficiency and volume of tests conducted. The finding that use of risk assessment is correlated with higher volume of tests conducted is consistent with Manavi et al (2006). Risk assessment may provide additional value to patients by identifying risky behaviors and making patients aware of their vulnerability to infection.

Nonprofit outpatient settings and FP with specialized HIV training working in nonprofit settings are also effective because services may be offered in a qualitatively different way that focuses on education, prevention, and advocacy. As noted, FP in nonprofit settings are also more likely to be hired from the communities in which they serve. Thus, a higher volume of patients who value education and a more holistic approach to care may be drawn to nonprofit outpatient clinics.

Finally, nonprofits may also serve a more diverse clientele rather than targeting testing to one specific group (such as White MSMs). Evidence from our study suggests that nonprofit outpatient clinics see a higher percentage of clients of color compared to other test settings. FP were asked to provide a profile of their most recent patient’s ethnicity and behavior risk group (BRG) in which an HIV test was conducted. In nonprofit outpatient settings, 50–54% were identified as Hispanic/Latino compared to 11–17% in forprofit outpatient settings. In both nonprofit and forprofit outpatient settings, MSM were reported as the most frequent BRG, 62–89% in forprofit outpatient settings and 29–56% in nonprofit outpatient settings.

Evidence from analysis of the locations of organizations in the sample suggests that nonprofits are located in low-income communities of color and forprofit providers are located in predominately gay communities. Given that geographic proximity may be a factor for individuals in seeking HIV tests (Leibowitz & Taylor, 2007), this provides partial evidence that forprofits may serve primarily the gay community and nonprofits generally serve communities of color. Predominately gay communities are, on average, wealthier than communities of color. Thus, this segment of the gay community may have the resources to pay for private treatment. Indeed, FP that diagnose a patient with an HIV infection are in a position of authority as the patient may be vulnerable to advice about treatment protocols (Hult et al, 2008). Targeted testing and treatment in a specific community with disposable resources places the clinic in a good position to recruit clients for antiretroviral treatment.

In retrospect it is not surprising that forprofit outpatient clinics detect HIV-seropositive persons at a higher rate than nonprofits. This supports the claim that forprofit clinics are more likely to serve white MSMs who are, on average, wealthier than communities of color and can better afford to pay for services out-of-pocket.

We also found that there was no significant difference across test settings with regard to rate at which HIV-seropositive patients are referred to treatment. This may be because referral to treatment both in hospital and nonhospital settings is typically routine in Los Angeles County for nonprofit, forprofit, and county government (public) test settings (SeeTable 8 (Model 3). At the same time, however, it is recognized that referral is very important, which is why “Test and Treat” is a mainstay of CDC HIV prevention protocol (CDC MMWR, 2011).

Finally, differences between nonprofit outpatient clinics and nonprofit hospital emergency rooms need to be briefly discussed. Nonprofit outpatient clinics differ significantly in structure and goals from nonprofit inpatient hospital emergency rooms. While both testing providers are nonprofit in legal structure, they operate in two distinct fields that differ with respect to regulatory guidelines, resource environment, institutional pressures, and clients served. It is for these reasons that the two test setting were not grouped under the category of “nonprofit.” Indeed findings from this study support the argument that HIV testing in hospitals is distinct from outpatient clinics. First, the nature of the HIV testing and counseling modality practiced in hospitals and the types of clients tested in hospitals differ from non-hospitals. Hospital emergency rooms, and especially non-academic hospitals, frequently do not engage in preventive testing HIV tests are infrequently conducted in hospital emergency departments and if done, serve as a secondary procedure to the primary reason for the patient’s visit. Often, patients are admitted due to symptoms related to pneumonia or other conditions as a result of developing AIDS. Also, it is often the case that hospital emergency departments treat low- income clients to a greater extent who have developed AIDS and thus have a much higher rate of confirmatory tests. Therefore, hospitals detect HIV-seropositive persons at a much higher rate, due to attracting patients who are HIV-seropositive and are experiencing major symptoms of their infection.

An estimated 22% of all persons in the U.S. who tested for HIV and 27% of all those who tested seropositive were seen in hospital emergency departments or other hospital outpatient settings (Branson, 2006a). The 27% who test seropositive in hospital settings is larger than other settings such as private physician/HMO (17%); government community clinics (21%), HIV counseling/testing sites (9%); correctional facilities (5%); STD clinics (6%); or drug treatment clinics (2%). The evidence also shows that late HIV detection occurs frequently despite strong evidence that reveals that antiretroviral treatment is more beneficial if begun early, that is, prior to the development of symptoms. For example, almost half (45%) of 4,127 persons with AIDS were tested for HIV/AIDS within twelve months of their AIDS diagnosis (CDC, 2003). The substantial number of persons who are unaware they are seropositive may have helped stimulate the CDC to instigate policies encouraging routine HIV screening in medical settings and greater use of rapid HIV tests in settings with an HIV prevalence equal to or greater than 1% (CDC, 2006). For a variety of reasons (physicians’ lack of time, concern about follow-up, unavailability of certified counselors, HIV testing unavailable, cost, emergency department subculture stresses acute care, etc.), these new policies have not met with a favorable response from many medical providers and hospitals (Fincher-Mergi et al., 2002; Branson, 2006b; McKenna, 2007). Moreover, earlier strategies for rapid HIV testing in emergency departments have not been successful (CDC, 2007).

Among hospitals, there were no significant differences between nonprofit, forprofit, and public providers with respect to HIV services. However, research does support the argument that nonprofit hospitals in general may differ from forprofit and public hospitals. For example, nonprofit academic hospitals are more focused on training, education and community service compared to forprofit and public hospitals; and both nonprofit and public hospitals are more likely to serve indigent and uninsured patients (Schlesinger & Gray, 2006). However, for HIV testing services specifically, the fact that hospital emergency departments do not differ maybe due to the funding environment for HIV testing. The Center for Disease Control (CDC) is the primary funder for HIV prevention and provides limited resources specifically designated for testing. On the hospital side, HIV testing represents only a small fraction of its menu of services and therefore may not be a high priority. Hospital emergency departments may also not offer HIV testing because of concern that their patients will often not return for their results. In addition, the hospital field is highly regulated and institutionalized with norms and rules guiding professional behavior and practice. That is, hospitals must adhere to many institutional pressures and regulatory guidelines that may lead them to conform to accepted behaviors or face sanctions and closure (Scott et al, 2000). In addition, as mentioned above, there may be a self-selection process among clients in choosing to receive a test in a hospital setting.

Finally, it should be noted that the group of mobile testing units are primarily nonprofit with one mobile testing unit associated with a public clinic. This is consistent with nonprofits’ social mission and community orientation. Once HIV testing technology evolved to a point where testing no longer required blood samples and were less invasive, nonprofit entrepreneurs created a new delivery mechanism to bring testing to those most at risk. These mobile testing units brought testing services to communities where no outpatient clinics previously existed (Grusky, Roberts, Swanson, Rhoades & Lam, 2009).

Conclusions

The CDC estimates that 21% of the 1.1 million persons living with HIV/AIDS in the US are unaware that they are HIV-seropositive (CDC, 2008). There is evidence that persons may reduce their risk behaviors after receiving an HIV diagnosis (Eaton & Kalichman, 2009). The findings from this study suggest that FP risk assessments serve as a useful tool for HIV providers working in HIV testing settings. In order to maximize the public health benefits of HIV treatment and prevention efforts, services can be more carefully tailored to the needs and risk behaviors of specific sub-populations of the public and PLH (Holtgrave et al., 2012). These sub-populations include PLH aware of their seropositivity and engaging in high risk behaviors; PLH unaware of their seropositivty; and seronegatives engaging in high risk behaviors. Risky sexual behaviors or drug injection transmission require services aimed not just at changing individual behaviors but also addressing social and structural factors such as homelessness, poverty, and stigma. Providing “complementary prevention” services such as “test and linkage to care” or “treatment as prevention” can “disrupt the pathway” to HIV transmission (Holtgrave et al, 2012). This study’s findings support Holtgrave’s (2007) and Holtgrave et al’s (2012) suggestion that HIV prevention should focus on a strategy of coupling HIV testing with counseling and referral to treatment. Conducting risk assessments plays an important part in identifying sub-populations at risk of infection and FP in nonprofit outpatient test settings appear well-positioned to provide key structural and behavior interventions to help implement this goal.