HIV TesTInG ToolkIT - nastad

HIV TestinG toolkit

Productivity & Yield analysis

For toolkits, training resources, and more, visit NASTAD.org

National Alliance of State & Territorial AIDS Directors (NASTAD) 444 North Capitol Street NW, Suite 339 Washington, DC 20001 Phone: (202) 434.8090 NASTAD.org

NASTAD NASTAD NASTAD1992

This resource was prepared by the National Alliance of State and Territorial AIDS Directors (NASTAD) under cooperative agreement number U65PS004390 from the Centers for Disease Control and Prevention (CDC). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the CDC.

Productivity and Yield Analysis

R

egular monitoring is critical to the success of HIV testing and linkage programs. Regular monitoring of testing and linkage programs helps to assure that services are meeting overarching goals to: (1) identify HIV infections and (2) link HIV-infected persons with HIV medical care, while also optimizing public health resources. The productivity and yield analysis is one tool that health departments and HIV testing and linkage providers can use to monitor services. The productivity and yield analysis will help you to evaluate the extent to which the recruitment, testing, and linkage strategies used by your HIV testing and linkage providers are successful in achieving the overarching goals for HIV testing and linkage programs and for achieving programmatic objectives of assuring access to services among priority populations. The productivity and yield analysis will help you to identify the factors that help or hinder your program’s ability to meet its goals and programmatic objectives and suggest strategies to improve your program.

Regular monitoring is critical to the success of HIV testing and linkage programs.

This tool is intended to help you to conduct a basic productivity and yield analysis, using data that you already collect in conjunction with CDC HIV prevention funding. You should adjust the scope of the analysis and make modifications to the worksheet to better meet your program’s specific needs and priorities. For example, you may wish to adjust the age groupings or risk exposure categories to more closely reflect the populations which are most relevant to your program; add columns to capture linkage to care among patients who were previously diagnosed with HIV; or add columns to examine the success of referral to priority services (e.g., substance abuse treatment) for particular populations. To be most helpful, the productivity and yield analysis can, and should be, conducted at multiple levels and from multiple perspectives. The productivity and yield analysis focused on an individual HIV testing and linkage site will provide different information than when performed for an entire state, which likely represents multiple providers of services and approaches to testing and linkage. Similarly, the productivity and yield analysis could be focused by testing approach (e.g., for routine testing or targeted testing); type of provider (e.g., clinics or community-based providers); populations (e.g., agencies serving men who have sex with men, adolescents, or racial/ethnic populations); venues (e.g., outreach settings, correctional facilities); geographic location (e.g., rural communities, particular zip codes); as well as by other factors (e.g., agencies which use rapid testing, employ linkage navigators, are funded by a particular revenue stream). Health departments are encouraged to share this tool with individual HIV testing and linkage providers to support local use of the tool.

HIV Testing toolkit: Selecting a Strategy

1

Conducting the Productivity and Yield Analysis The productivity and yield analysis process consists of four (4) steps:

1 Set Targets

2 Calculate Productivity and Yield

3 Identify Contributing Factors

4 Determine Strategies for Improvement

Each of these steps are explained below.

1 Set Targets At minimum, the productivity and yield analysis should address the overarching goals for HIV testing and linkage: (1) identifying new HIV infections; and (2) linking newly-diagnosed individuals to HIV medical care. Targets should reflect what is reasonable and feasible given the capacity and resources available to support HIV testing and linkage services. Targets should also reflect your priorities in terms of the populations that are served by your HIV testing and linkage program(s). Sometimes targets are dictated by the requirements of a funder (e.g., percentage of new HIV-positive test results). Targets may also be suggested by other sources such as program standards or guidelines (e.g., proportion of HIV-infected individuals who are successfully linked to HIV medical care). More often, you will need to set targets. One simple way of setting targets involves looking at service data retrospectively, identifying trends over time, and projecting reasonable future achievements. This same approach to setting targets can be used for yield of new positives, successful linkage to care, or other variables you decided to include in the yield and productivity analysis. You should also consider setting targets for specific populations, as relevant for your program(s). Target setting for specific populations should be informed by your epidemiologic profile, and/or the populations served by the agencies and/or programs supported for HIV testing and linkage services.

2 Calculate Productivity and Yield Begin by deciding the scope of your analysis (e.g., statewide, regional, individual site, or group of agencies) and the period of the analysis (e.g., past year, quarter, month). For each analysis you plan to perform, gather the necessary program data. At minimum, you will need the number of: • Tests performed • New HIV infections identified • Newly diagnosed individuals linked to care

2


You should segment these data according to the client characteristics (e.g., risk exposure, age) that you plan to include in your analysis. If you decide to include additional variables not currently on the worksheet, such as previously diagnosed individuals linked to care, you will also need to gather these data. Enter your data into the Yield and Productivity Worksheet (the instructions for completion are included on the first tab of the worksheet). Progress toward meeting your targets will be automatically calculated. The Yield and Productivity Worksheet is provided in an Microsoft Excel format and is unlocked to allow you to add additional variables of interest or adjust the population characteristics. See Figure 1 below for an example of what a portion of a completed worksheet will look like. Figure 1: Example Completed HIV Testing and Linkage Yield and Productivity Analysis Worksheet HIV TESTING AND ANALYSIS HIV TESTING AND LINKAGE LINKAGE PRODUCTIVITY PRODUCTIVITY AAND ND YYIELD IELD ANALYSIS Scope of Analysis: HIV Testing and Linkage in This State Time Period: Fiscal Year 2015 HIV TEST VOLUME CLIENT CHARACTERISTICS

< 13 years 13 -‐ 19 years 20 -‐ 24 years 25 -‐ 29 years 30 -‐ 34 years 35 -‐ 39 years 40 -‐ 44 years 45 -‐ 49 years 50 -‐ 54 years 55 -‐ 59 years > 60 years GENDER

TARGET # # TESTS OF TESTS

% OF TESTS

Date Completed: July 2015 HIV SEROPOSITIVITY % TO TARGET

TOTAL

40000

28185

TOTAL

100 300 2500 5000 7500 7500 8000 7500 1000 500 100 40000

75 245 1501 4593 7329 4997 3326 5089 654 222 154 28185

0.3% 0.9% 5.3% 16.3% 26.0% 17.7% 11.8% 18.1% 2.3% 0.8% 0.5% 100.0%

75.0% 81.7% 60.0% 91.9% 97.7% 66.6% 41.6% 67.9% 65.4% 44.4% 154.0% 70.5%

27000 12450 500 50 40000

16488 11553 132 12 28185

58.5% 41.0% 0.5% 0.0% 100.0%

61.1% 92.8% 26.4% 24.0% 70.5%

250 100 25000 50 14350 200 50 40000 5000

353 1413 17386 291 8259 154 329 28185 570

1.3% 5.0% 61.7% 1.0% 29.3% 0.5% 1.2% 100.0% 2.0%

15000 200 5000 5500 1000 1200 3300 10300 1000 3000 40000

8324 63 6447 3901 2211 107 1583 4366 688 4396 28185

29.5% 0.2% 22.9% 13.8% 7.8% 0.4% 5.6% 15.5% 2.4% 15.6% 100.0%

Male Female Transgender male-‐to-‐female Transgender female-‐to-‐male TOTAL RACE & ETHNICITY American Indian/Alaska Native Asian Black/African American Native Hawaiian/Pacific Islander White Other Unknown TOTAL Hispanic RISK MSM MSM/IDU IDU High Risk Sex Partner Sex Partner to IDU Female Sex Partner to MSM Sex Partner to HIV+ Other Heterosexual Other Risk Unknown Risk TOTAL

70.5%

TARGET # NEW HIV+ 452 AGE 1 10 155 100 100 30 20 20 10 5 1 452

LINKAGE TO CARE TARGET # NEW % OF NEW % NEW % TO LINKED TO # LINKED % HIV+ % TO HIV+ HIV+ HIV+ TARGET CARE TO CARE LINKED TARGET (90%) 272 1.0% 60.2% 245 211 77.6% 86.2% 0 9 29 58 50 34 27 35 28 1 1 272

0.0% 3.3% 10.7% 21.3% 18.4% 12.5% 9.9% 12.9% 10.3% 0.4% 0.4% 100.0%

0.0% 3.7% 1.9% 1.3% 0.7% 0.7% 0.8% 0.7% 4.3% 0.5% 0.6% 1.0%

0.0% 90.0% 18.7% 58.0% 50.0% 113.3% 135.0% 175.0% 280.0% 20.0% 100.0% 60.2%

0 8 26 52 45 31 24 32 25 1 1 245

0 9 18 33 35 30 25 33 26 1 1 211

#DIV/0! 100.0% 62.1% 56.9% 70.0% 88.2% 92.6% 94.3% 92.9% 100.0% 100.0% 77.6%

#DIV/0! 111.1% 69.0% 63.2% 77.8% 98.0% 102.9% 104.8% 103.2% 111.1% 111.1% 86.2%

300 97 50 5 452

190 78 3 1 272

69.9% 28.7% 1.1% 0.4% 100.0%

1.2% 0.7% 2.3% 8.3% 1.0%

63.3% 80.4% 6.0% 20.0% 60.2%

171 70 3 1 245

141 68 1 1 211

74.2% 87.2% 33.3% 100.0% 77.6%

82.5% 96.9% 37.0% 111.1% 86.2%

141.2% 1413.0% 69.5% 582.0% 57.6% 77.0% 658.0% 70.5% 11.4%

4 10 295 1 140 1 1 452 50

3 1 202 0 60 2 4 272 12

1.1% 0.4% 74.3% 0.0% 22.1% 0.7% 1.5% 100.0% 4.4%

0.8% 0.1% 1.2% 0.0% 0.7% 1.3% 1.2% 1.0% 2.1%

75.0% 10.0% 68.5% 0.0% 42.9% 200.0% 400.0% 60.2% 24.0%

3 1 182 0 54 2 4 245 11

1 1 156 0 50 1 2 211 8

33.3% 100.0% 77.2% #DIV/0! 83.3% 50.0% 50.0% 77.6% 66.7%

37.0% 111.1% 85.8% #DIV/0! 92.6% 55.6% 55.6% 86.2% 74.1%

55.5% 31.5% 128.9% 70.9% 221.1% 8.9% 48.0% 42.4% 68.8% 146.5% 70.5%

225 7 65 120 10 10 100 20 5 10 452

114 5 32 90 2 1 87 4 1 26 272

41.9% 1.8% 11.8% 33.1% 0.7% 0.4% 32.0% 1.5% 0.4% 9.6% 100.0%

1.4% 7.9% 0.5% 2.3% 0.1% 0.9% 5.5% 0.1% 0.1% 0.6% 1.0%

50.7% 71.4% 49.2% 75.0% 20.0% 10.0% 87.0% 20.0% 20.0% 260.0% 60.2%

103 5 29 81 2 1 78 4 1 23 245

99 4 17 71 1 1 69 3 1 16 211

86.8% 80.0% 53.1% 78.9% 50.0% 100.0% 79.3% 75.0% 100.0% 61.5% 77.6%

96.5% 88.9% 59.0% 87.7% 55.6% 111.1% 88.1% 83.3% 111.1% 68.4% 86.2%

Once you have entered data into the worksheet and the calculations are complete, review the data to identify progress in meeting targets. In particular, you should identify the areas where you are at, above, and below the targets. This will help you to focus your attention in identifying factors that contribute to your relative success in meeting targets, and for identifying strategies for program improvement. A template to help you organize data for the next steps in your analysis is provided in Attachment A.


3

An example of a partially completed template is provided in Table 2 on page 6. The example uses data from the worksheet illustrated in Figure 1. For each of the three program domains addressed by the productivity and yield analysis, data for population groupings are arranged according to whether the data represents meeting the target (“on target”), exceeding the target (“above target”), or failing to meet the target (“below target”). Services which may not be precisely on target, but may be close (e.g., within 3% - 5%) are included within the “on target.” Table 1: Interpreting Productivity and Yield: Progress Towards Meeting Target

Interpreting Productivity and Yield

Recruitment

On Target

Above Target

Below Target

n
60 yo

n IDU,

Unknown, Sex partner of IDU

n 13-19;

35-54;

>60 yo sex partner HIV+, unknown risk

n MSM/IDU

n 13-19,

n Sex

n MSM, female sex

partner to HIV+

n MSM,

MSM/IDU, other heterosexual

n 60 yo

IDU, Unknown,

n

heterosexual and other risk

Considerations Five new school health centers brought

n

44, 55-59 yo

MSM, MSM/

n

Sex partner of IDU

IDU, other heterosexual

Recruitment

on board, underestimated uptake among adolescents;

Urgent care out-posting demo project

n

disproportionately reached >60 pop; failed to reach younger pops as intended

Closure of City STD clinic decreased

n

access to 20-24 yo and MSM

Needle exchange sites expanded test-

n

ing for hepatitis C, created more interest in HIV testing and brought in partners

Partners counseling and testing

n

expansion has had lower uptake than anticipated

N/A

n

13-19, 35-54,

n

60 yo

MSM/IDU, sex

n

testing for 20-24 yo and MSM — previously accounted for 15% of new HIV+;

MSM, IDU,

n

partner HIV+, unknown risk

Identifying New HIVInfections

Closure of City STD clinic decreased

n

55-59 yo sex partner to IDU, other heterosexual, other risk

IDU and sex partner to IDU incidence

n

of HIV is very low, but HCV infection identified through expanded testing in needle exchange sites was 30%

Yield of new HIV+ decreased dramati-

n

cally in community health centers that previously accounted for 50% of new positives in 25-35 yo — substantially impacts overall progress to achieving target

MSM/IDU

n

13-19, 44-

n

60+ yo

Sex partner

n

to HIV+

Linking HIV-infected Clients to Care

6

MSM, female

n

sex partner to MSM, other risk

20-39 yo

n

DPH policy sets target at 90% — ACME

n

testing services accounts for approximately 1/3 of new positives in 20-39 yo group, with only 60% successful linkage, this is affecting overall progress to achieving target

IDU, sex part-

n

ner to IDU, unknown risk

IDU linkage to care consistently

n

below other populations, all testing providers except at ACME community health services (95%) where opiate dependency treatment integrated into HIV primary care


4 Determine Strategies for Improvement The final step in the productivity and yield analysis is to determine strategies for program improvement. This step should be undertaken in consultation with staff familiar with and/or involved in delivery of services. It may also be helpful and appropriate to involve members of the target population in discussions to identify strategies for improvement. For each of the population-specific, operational, policy, and structural factors identified, you should identify one or more strategies to address the factor. The template provided in Attachment A will help you organize information regarding strategies to address contributing factors and to complete your analysis. Building on the prior example and using data provided in Figure 1, examples of how strategies should be included in the analysis are provided in Table 3, below. Table 3: Interpreting Productivity and Yield: Strategies for Improvement

Recruitment

Contributing Factors

Strategies

n

Five new school health centers brought on board, underestimated uptake among adolescents;

n

Maintain health center support; identify strategies to promote testing to increase uptake of testing services

n

Urgent care out-posting demo project disproportionately reached >60 pop; failed to reach younger pops as intended

n

Review recruitment strategies used in urgent care demo to determine reasons for suboptimal testing in younger populations present in the venue

n

Closure of City STD clinic decreased access to 20-24 yo and MSM

n

n

Needle exchange sites expanded testing for hepatitis C, created more interest in HIV testing and brought in partners

Conduct evaluation (e.g., focus groups) with young MSM to determine appropriate locations for testing; assess feasibility of expanding hours of LGBT clinic run by ACME Community Health Services

n

Continue integrated HIV-HCV testing at needle exchange

n

Review recruitment strategies to determine reasons for lower than anticipated uptake

n

Partners counseling and testing expansion has had lower uptake than anticipated

In the example above, evaluation of appropriate locations for HIV testing and linkage services was identified as a strategy for improvement (highlighted by the red box). It is important to note in some circumstances, such as when the contributing factors have been identified are structural (e.g., clinic closures), further investigation may be an appropriate strategy to achieve program improvement.


7

Implementation of strategies for program improvement should be monitored and the status and outcome of implementation efforts should be considered in future productivity and yield analyses, particularly in setting targets. Program improvement is generally incremental so your future targets should reflect this. In the example illustrated in Table 3, a clinic closure substantially impacted testing among men who have sex with men. The formative evaluation needed to identify appropriate venues and build or assure organizational capacity may take some time and your targets should reflect this.

8


Recruitment

Identifying New HIVInfections

Linking HIV-infected Clients to Care

On Target

Below Target

Contributing Factors

InterpretIng productIvIty and yIeld Above Target

attachment a: InterpretIng productIvIty and yIeld

Strategies