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Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act (2004)

Chapter: 4 HIV Reporting Data and Title I and II Formulas

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Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

4
HIV Reporting Data and Title I and II Formulas

Seventy percent ($1.3 billion in fiscal year [FY] 2002) of all Ryan White CARE Act (RWCA) funds are distributed under Titles I and II through explicit numerical formulas. These formula allocations are based on estimated living AIDS cases (ELCs),1 which are calculated using data from the AIDS case-reporting system2 (HRSA, 2002). Discussions, testimony, and Congressional committee reports related to the 2000 reauthorization raised questions concerning inequity in the allocations resulting from these formulas (U.S. Congress, 2000a,b). By 2000, concerns about inequity arose from the perception that the epidemic was not truly reflected by AIDS cases alone, and that the effect of addressing HIV disease in areas with emerging epidemics had been underestimated (U.S. Congress, 2000a,b). Jurisdictions were also concerned that they were not compensated for providing early access to care and treatment and thus preventing persons from progressing to AIDS (U.S. Congress, 2000a). The hold-harmless provisions, which were added in the 1996 reauthorization, also raised concerns about equity. Some were concerned that the hold-harmless provisions, which prevent a jurisdiction’s funding falling by

1  

ELCs are calculated by applying annual survival weights to the most recent 10 years of reported AIDS cases and summing the totals. The Centers for Disease Control and Prevention (CDC) updates the survival weights every two years. CDC provides both the survival weights and the most recent 10 years of reported AIDS cases to the Health Resources and Services Administration (HRSA), which performs the award calculations.

2  

See Chapter 3 for background on the AIDS and HIV case-reporting systems.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

more than a set percent each year in order to help sustain needed health care infrastructure and continuity of services, seemed to accomplish their purpose at the expense of states and local areas believed to have younger epidemics and rising need (U.S. Congress, 2000a).

Congress asked the General Accounting Office (GAO) to examine opportunities to enhance the equity of funding to RWCA grantees prior to the 1996 and 2000 reauthorizations. The GAO’s 1995 study found that CARE Act funding formulas led to disparities in per AIDS case funding that could not be completely explained by variations in service costs or the fiscal capacity of states and EMAs.

In a 2000 report, the GAO again found large disparities across Eligible Metropolitan Areas (EMAs) and states in allocations per ELC. The GAO concluded that two formula features in particular, the hold-harmless provision and the “double-counting” of EMA cases in Title I and II formulas,3 contributed to these funding inequities. In particular, states with an EMA had up to 60 percent higher per case allocations than states without an EMA and the hold-harmless provision instituted in the 1996 reauthorization benefited only San Francisco (GAO, 2000).

The GAO report further concluded that the formulas, which were based on living AIDS cases, did not reflect the changing nature of the HIV/AIDS epidemic and recommended the inclusion of HIV case data in the Title I and II formulas to more effectively target and deliver funding to persons in need of care. The GAO noted that, at a minimum, all states would have to report HIV cases to provide an equitable distribution of funds. At the time, only 60 percent of states had HIV reporting systems in place (GAO, 2000).

Congress began the 2000 reauthorization with the expectation that HIV case-reporting data would be of value to the RWCA formula allocations, as well as to planning and evaluation efforts. The 2000 legislation specifies that, if appropriate, the Secretary of Health and Human Services (HHS) should incorporate cases of HIV disease in RWCA Title I and II funding formulas as early as FY2005 but no later than FY2007 (Ryan White CARE Act. 42 U.S.C. § 300ff-28 [2003]). The reauthorization legislation authorized the Institute of Medicine (IOM) to assist the Secretary of HHS in assessing the readiness of states to produce accurate and reliable HIV case-reporting data, determine the accuracy of using HIV cases within the existing allocation formulas, and establish recommendations regarding the manner in which states could improve their HIV case-reporting systems (Ryan White CARE Act. 42 U.S.C. § 300ff-11 [2003]).4

3  

EMA cases are counted in both Title I and II formulas.

4  

See Chapter 1 for legislative language relating to the Committee’s charge.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

At the outset, the Committee recognized the difficulty of defining such terms as “sufficiently accurate,” “adequate,” and “reliable” to characterize the quality of HIV surveillance data. No absolute standards of accuracy, adequacy, or reliability exist; rather these standards and their definition will vary according to the purposes and tasks for which the data are used. Thus, evaluating HIV reporting systems for use in resource allocation formulas requires a different set of performance criteria than evaluating these data for public health purposes (e.g., epidemic surveillance, contact tracing, and partner notification). While CDC (1999) has established performance criteria5 for evaluating the latter functions, it was not the purpose of this Committee to assess these standards. Rather, the Committee defined criteria for “accuracy,” “adequacy,” and “reliability” in terms of over- and underfunding errors to RWCA grantees.

In assessing whether the current surveillance systems provide HIV data that are “sufficiently accurate” for the purpose of formula grants, the Committee focused on the primary argument for including HIV case data in the formulas: that doing so would provide a better representation of HIV disease-related resource needs across jurisdictions and would thus more fairly channel scarce RWCA resources. Four conditions would need to be met for this to occur:

  • First, the HIV reporting systems of all states would need to be capable of providing data that are used for the formulas.

  • Second, the quality of HIV data across jurisdictions would have to be comparable. This means that if there are biases in HIV reporting, those biases should be of similar direction and magnitude across areas.

  • Third, incorporating HIV case-reporting data in the formula would need to produce different and more accurate assessments of “relative disease burden” and resource needs than AIDS data alone.

  • Fourth, including HIV data in the RWCA allocation formulas would have to result in material variation in the relative size of awards to states and EMAs and more equitable allocations. If formula provisions, in

5  

CDC issued surveillance guidelines in December 1999 outlining the performance criteria for states’ HIV/AIDS surveillance systems. The criteria outlined in the document stated that the system had to be timely (66 percent of HIV/AIDS cases reported to the health department within 6 months of diagnoses), provide accurate case counts (≤5 percent mis-matched reports and ≤5 percent duplicate cases in the database), have complete ascertainment of mode of exposure to HIV (≥85 percent of reported cases, or representative sample, must have reported transmission mode after complete epidemiologic follow-up), and must include complete case reporting (≥85 percent of diagnosed cases reported to the health department). In addition, states must show that they can match to other databases of public health importance, follow up cases of public health importance, collect valid and reliable data for key data elements, and use data for public health planning (CDC, 2003i).

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

contrast, limit or dampen the influence of new HIV data, then the formulas may not result in more equitable allocations.

The Committee sought evidence to determine whether each of these conditions would be met if reported HIV cases were used in the formulas. Specifically, the Committee examined:

  • Whether state HIV reporting systems are capable of providing data for the formulas;

  • Whether the quality of HIV data across jurisdictions is comparable;

  • Whether the relative ranking of need among states and EMAs varies depending on whether HIV case data or AIDS case data are employed to measure disease burden; and

  • Whether the RWCA formulas are sensitive enough to translate changes in input data into more equitable allocations.

Each of these conditions proved difficult to verify. The evidence does not lead unequivocally to the conclusion that inclusion of HIV case-reporting data in the formulas would lead to a more equitable allocation of RWCA resources.

Finally, the Committee concluded that it was beyond its capacity to evaluate the HIV case-reporting system of each state and territory. The Committee’s recommendations, however, could be used to make general improvements to HIV case reporting for allocating RWCA resources.

CAPABILITY OF STATE HIV REPORTING SYSTEMS TO PROVIDE DATA FOR THE FORMULAS

Three criteria are particularly relevant for evaluating the capability of HIV reporting systems to provide data for allocating resources under RWCA:

  1. Coverage: Does each state have an HIV reporting system?

  2. Maturity: Has the HIV reporting system of each state had sufficient time for full implementation?

  3. Full use of available data: Would the formulas use HIV reporting data from every state with a system of HIV reporting?

Coverage

For HIV case-reporting data to be used in RWCA funding formulas, all states and territories would need to report HIV cases. As of October

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

2003, all states, territories, and cities except Georgia6 and Philadelphia, had implemented a confidential HIV case-reporting system (CDC, 2003a,h) (see Chapter 3, Table 3-1). Unlike AIDS case reporting, which uses a standardized name-based reporting system, states have adopted different procedures for reporting HIV cases (Chapter 3, Figure 3-1). As of October 2003, 34 states, the Virgin Islands, American Samoa, Puerto Rico, Northern Mariana Islands, and Guam had implemented the same confidential name-based reporting of HIV infection as is used for AIDS reporting and other reportable diseases and conditions. Eight states plus the District of Columbia use a coded identifier rather than the patient name to report HIV cases. Five states use a name-to-code system; initially, names are collected and then converted to codes by the local or state health department after any necessary public health follow-up. Connecticut conducts pediatric surveillance using name-based reporting but allows name or code reporting of adults/adolescents over 13 years of age. New Hampshire allows HIV cases to be reported with or without a name (CDC, 2003a,h). Of the 15 areas that use some form of code, only two use the same code.

Maturity

Case-reporting systems for new diseases take time to mature and become fully operational. For a system to operate well, physicians and other practitioners need to be educated about the need for new requirements for disease reporting. The burden of new reporting obligations can be increased by complex data requirements, such as the creation of encryption codes for patients in states with code-based reporting. For a disease like HIV infection, where physicians may have followed patients prior to the initiation of an HIV reporting requirement, practitioners will need to report a backlog of existing patients when HIV reporting is first implemented. This takes time and clinician effort, particularly in high-morbidity states that have only recently implemented HIV reporting, such as California. Even laboratories, which rely more heavily on information automation, will still require some time to completely develop, refine, and implement reporting procedures. Further, health departments need time to design and pilot test their surveillance systems for capturing and analyzing newly reportable disease data.

While the Committee could not identify any standard criterion for

6  

Since the release of this report, Georgia implemented name-based reporting and Philadelphia adopted code-based reporting. All areas of the United States now have HIV reporting.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

how much time is needed to ensure that state reporting systems are fully operational, it was clear from discussions with surveillance experts from multiple states that it takes at least 18 months to several years after a reporting system is introduced for it to reach a reasonable level of completeness and timeliness (Birkhead, 2002; Kopelman, 2002). In a previous assessment by the GAO, CDC officials estimated that it would take 1 to 3 years for the backlog of HIV cases to be entered into a new reporting system (GAO, 2000). The GAO study compared the experience of states that had been reporting HIV for different periods of time and found: “The potential for lags in reporting the older cases was clear when we compared the experience of states that had been reporting HIV cases for different lengths of time. States with long reporting histories had many more HIV cases compared with their number of AIDS cases than did newly reporting states” and that “states that begin reporting more recently may continue for some time into the future to have a larger proportion of previously diagnosed but not reported cases” (GAO, 2000).

Variations in the maturity of systems can create differential errors across states and EMAs. Immature systems capture a lower percentage of prevalent cases and are more likely to be missing key pieces of information. The HIV reporting systems of states are in various stages of maturity. Some, such as Minnesota and Colorado, implemented HIV reporting in the mid-1980s and have mature systems. Other states such as California and Pennsylvania adopted HIV reporting only recently and may require additional time to report the backlog of cases.

Several of the factors determining system accuracy, such as the ability to follow up on a backlog of cases, depend on the capacity to conduct surveillance. As one indicator of capacity, the Committee examined federal and state funding for HIV/AIDS case reporting (Appendix B). This review identified important issues. First, state HIV/AIDS surveillance programs are largely dependent upon federal financing (Appendix B). In addition, neither federal nor state sources of program funding have changed appreciably from 1999 to 2002 when many states were implementing HIV case reporting. Although the 2000 reauthorization of RWCA authorized limited additional funds to help states implement HIV reporting systems (Ryan White CARE Act. 42 U.S.C. § 300ff-13 [2003]), that funding has yet to be appropriated. Even though HIV and AIDS data may be perceived to be readily available for RWCA purposes at no additional cost, states must often include different or more-detailed data for RWCA planning than are provided in standard epidemiological reports. Such efforts can be costly, especially for states that have recently implemented HIV reporting and for states that lack adequate surveillance resources. States are facing financial crises, and state surveillance programs do not

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

anticipate additional state contributions (see Appendix B). Thus, it is important for Congress, HRSA, and RWCA grantees to recognize the burden imposed upon the state surveillance programs as they strive to meet the information needs of RWCA. Additional funds will be required to accommodate the additional informational burdens placed on states by the RWCA.

Full Use of Available Data

Currently, CDC accepts only name-based HIV reports in the national HIV reporting database, largely because algorithms have not been developed to unduplicate HIV data from the 15 code-based states and territories. Duplicate case reporting can occur for several reasons: case reports are completed by different practitioners at several different times (HIV diagnosis, AIDS diagnosis, and death); laboratories may send results from diagnostic and staging laboratory tests (CD4+ cell count or viral load) independently to the health department; and people may move and be reported in both their original and new state of residence (CDC, 2003b). CDC estimates that approximately 5 percent of HIV cases (from name-based reporting states only) in the national dataset represent duplicate reports. CDC suggests the potential for greater duplication grows as state HIV reporting systems mature and as people remain healthier longer owing to antiretroviral therapy (CDC, 2003b).

Name-based reporting is cited as one way to facilitate elimination of duplicate reports (CDC, 1999). However, it is unclear if name-based reporting is intrinsically superior to code-based reporting for eliminating duplicate reports. Due to name variations, even name-based systems do not permit complete unduplication. In addition, code-based reporting systems were developed by some states after substantial political debate, and altering those systems would require significant legislative changes, time, and effort. For this reason, and because name-based reporting is not clearly superior to code-based reporting for the specific goal of accurately estimating the number of known cases for determining RWCA allocations, better methods for unduplicating reports for both code- and name-based reporting states need to be developed and implemented so allocation formulas can include data from all states. At the same time, the Committee recognizes that there are strong feelings, both pro and con, about the use of name-based reporting for other surveillance functions (Colfax and Bindman, 1998; Osmond et al., 1999; Hecht et al., 2000). The Committee did not take a position on these issues because its charge limits its scope of activity to reporting for allocation purposes.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Finding About States’ Capability to Provide Data for the Formulas

Finding 4-1 While the Committee supports Congressional intent to incorporate data into the RWCA allocation formulas that reflect the evolving needs of the epidemic, the Committee finds that states’ HIV reporting systems are neither ready nor adequate for purposes of RWCA resource allocation. One state and one city have yet to implement HIV case reporting, states’ HIV reporting systems are in different stages of maturity across the United States, and the national HIV database does not include HIV cases from code-based reporting states.

COMPARABILITY OF DATA QUALITY ACROSS JURISDICTIONS

Even if states are capable of providing data on HIV cases, data would need to be of comparable quality across jurisdictions before they could be used in the RWCA formulas. Differences in the completeness and timeliness of data across jurisdictions have the potential to create significant biases in allocations. The greater the variability in the way HIV data are collected across states or EMAs, the greater are the chances for bias. The inclusion of data of varying quality across jurisdictions can decrease rather than increase the equity of resulting RWCA allocations.7

It is important to note that not all biases will adversely affect the fairness of resource allocation. Biases in prevalence that are consistent across states or EMAs will not affect allocations if the formulas depend only on the relative value of these measures across states or EMAs rather than the absolute value. For example, if all states underreported cases by 30 percent, then there would not necessarily be an effect on allocations, depending on the nature of the formula used (although such underreporting would be important for determining the gap between prevalent and diagnosed cases). By contrast, if variability across states in underreporting were large, such variability might have a major influence on allocations. Measuring or reducing biases may entail substantial cost. Such costs need to be weighed against the likely improvements in the allocation process. HIV data should be included in the formulas only if doing so enhances the equity of the resulting allocations.

To examine these potential biases, the Committee reviewed published evaluations of the completeness and timeliness of HIV and AIDS case-reporting systems. These studies are summarized in Table 4-1. The Committee found that most evaluations have focused on the completeness of reporting—the degree to which all individuals with these conditions are

7  

The concept of equity is discussed in Chapter 1.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

reported to public health authorities. The accuracy of the elements of the report such as sex, primary risk factor, and place of residence has received less attention. To the extent that characteristics such as sex and primary risk factor are systematically misreported or underreported, estimates of the prevalence of HIV or AIDS based on those characteristics will also be biased. These types of biases would not necessarily affect allocations across states and EMAs if the proportion of such subgroups was similar across jurisdictions.

Given the more recent advent of HIV case reporting, most published evaluations have focused on AIDS rather than HIV case reporting. The Committee found little information from existing evaluations about the completeness, accuracy, and timeliness of HIV case reporting, and about the variation in these factors for HIV reporting across states and EMAs. Because of the inadequacy of available information, the Committee could not fully investigate the potential influence of possible patterns of underreporting or reporting delays on resulting formula allocations.

Completeness of AIDS and HIV Case Reporting

Studies of the completeness of reporting compare AIDS and HIV case reports with independent data on AIDS or HIV cases that should have been reported—typically medical or administrative records or death certificates. The external source may also be incomplete, so capture– recapture methods may be required.8 Accuracy studies typically look at the correspondence between reported characteristics of cases that appear in both sources, so the results may not be representative of individuals who appear in only one or neither source. The Committee notes, however, that not all elements requested in case-reporting forms may be relevant to resource allocation. While certain data elements may be important in determining whether a state’s reporting system serves the state’s own case-finding purposes and identifies populations at risk, such information may not be relevant to resource allocation.

AIDS case reporting is the most complete and highest quality of nearly any disease surveillance system (Doyle et al., 2002). AIDS case reporting

8  

Capture–recapture methods can be used to adjust for incomplete ascertainment using information from two or more distinct sources. Capture–recapture estimates the size of a population (in this case, the number of cases) by making statistical assumptions about the proportion of individuals identified in various samples of the population (in the case of surveillance, reported from different sources) (Hook and Regal, 1995). The U.S. Census Bureau uses a similar method (dual-systems estimation) to estimate the U.S. population and population groups (NRC, 2001).

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

TABLE 4-1 Completeness and Timeliness of HIV and AIDS Case Reporting

Study

AIDS or HIV

Purpose

Methods

AIDS STUDIES

Scheer et al. (2001)

AIDS

To determine whether AIDS surveillance misses a substantial number of persons who die with unreported AIDS.

Cross-sectional survey of decedents examined by San Francisco Medical Examiner. Decedents with positive or indeterminate HIV antibody test results were cross-referenced against the SF AIDS registry. Medical records of unreported cases reviewed to determine whether AIDS had been reported prior to death.

Klevens et al. (2001)

AIDS

To assess the completeness, validity, and timeliness of AIDS surveillance system after the 1993 surveillance case definition change.

In Louisiana and San Francisco, completeness was assessed by comparing the number of persons found in health facilities (hospitals, outpatient clinic, and private providers’ offices) to the number of cases reported to the AIDS surveillance registry. In Massachusetts, completeness assessed using capture–recapture method. Validity was assessed by comparing agreement of case report with medical record for same sites. Timeliness calculated using median delay from time of diagnosis to case report for same sites.

Jara et al. (2000)

AIDS

To assess the completeness of AIDS case reporting in Massachusetts. To determine the effect of the 1993 AIDS case definition on the completeness of AIDS case reporting to the state registry and unreported case based on sex, race, and mode of transmission.

Multisource capture–recapture using 1994 Massachusetts Uniform Hospital Discharge Data Set (UHDDS) and Medicaid claims was used to evaluate completeness of Massachusetts state registry.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

San Francisco

Diagnosis and reporting of AIDS 93% complete. HIV-infected decedents were more likely than uninfected to be men and <45 years old, less likely to be Asian/Pacific Islander or Native American, and more likely to have died of suicide or drug abuse/overdose.

AIDS case reporting in San Francisco is highly complete. Current surveillance activities which identify cases from health care settings are appropriate.

Louisiana, Massachusetts, San Francisco

Completeness of case reporting in hospitals (≥93%) and outpatient clinics (≥90%); validity/concordance of info for sex was high (>98%), but lower for race/ethnicity (>83%) & mode of exposure to HIV (>67%); median reporting delay was 4 months, but varied by site from 3 to 6 months.

Completeness, validity, and timeliness of AIDS surveillance system remain high after 1993 change in case definition.

Massachusetts

92.6% (95% CI 91.6-93.5) complete using UHDDS; 94.5% (95% CI 93.7-95.3) complete using Medicaid claims dataset. Being unreported was significantly more likely in women than in men (OR = 1.72. 95% CI 1.20-2.46), and slightly more likely in IDU than in MSM (OR = 1.49, 95% CI 1.00-2.23).

Completeness of state AIDS registry is high, but there are differences by gender and mode of transmission of HIV.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Schwarcz et al. (1999)

AIDS

To assess the effect of the 1993 change in the AIDS case definition on the completeness and timeframe of AIDS case reporting in San Francisco.

Reporting completeness was calculated as the number of previously reported cases divided by the number of previously reported cases plus newly identified cases. Reporting delay was calculated as the difference between the case report and the date of AIDS diagnosis. AIDS cases were obtained through retrospective review of records at hospitals, public/community health clinics, and physician offices.

Klevens et al. (1997)

AIDS

To measure the effect of laboratory-initiated reporting of CD4+ results on timeliness of reporting of AIDS in the U.S.

States were categorized by whether CD4+ reporting was required. The study compared the number and percentage of AIDS cases reported through 12/31/1994 based on immunologic criteria, controlling for whether states also required HIV infection reporting.

Payne et al. (1995)

AIDS

To improve methods of identifying possible AIDS-related hospital discharges in administrative databases and to measure AIDS- reporting completeness in MA.

Fiscal year 1998 discharge data from the Massachusetts Rate Setting Commission and data from the MA AIDS Reporting System were reviewed for diagnosis codes which were HIV-specific or pertain to AIDS-defining illnesses. Medical records with HIV/AIDS diagnoses that were not reported to the reporting system were identified.

Greenberg et al. (1993)

AIDS

To assess the completeness of AIDS case reporting in NYC and to determine whether completeness of reporting differs in various populations.

Retrospective record review from 7/1988 to 11/1991 of hospital laboratory logs, death certificates, hospital discharge records, & patient registries at private physicians’ offices and hospital outpatient clinics.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

San Francisco

Reporting completeness was 97%. The median reporting delay was 1 month and was shorter for persons who met the 1993 AIDS case definition (1 month) than for persons who met the 1987 case definition (3 months).

AIDS case reporting in San Francisco is highly complete, but less so for persons diagnosed at physician offices. The 1993 AIDS case definition has resulted in more timely reporting.

All 50 states and DC

States with lab-initiated CD4+ reporting were able to identify proportionately more AIDS cases and with less reporting delay than states without lab reporting.

CD4+ reporting may enable states to report AIDS cases earlier in the course of HIV disease.

Massachusetts

Of the 927 AIDS cases identified from the 3362 discharges, only 36 had not been reported. AIDS cases among women, IV drug users, and persons residing outside the Boston metropolitan area were more likely to be unreported than those among comparison groups.

Using HIV-specific ICD-9-CM codes are useful for identifying AIDS-related hospital discharges and previously unreported AIDS cases.

New York City

Overall completeness was 84%. Completeness ranged from 81 to 87% for all major gender, race, risk, borough of residence, and age subgroups. Outpatients at hospital clinics, out of state residents, persons with diagnosis other than PCP, and recently diagnosed persons less likely to be reported.

Findings indicate that NYC AIDS surveillance system functioned effectively during first decade of epidemic.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Elcock et al. (1993)

AIDS

To assess completeness of AIDS case reporting.

The authors initiated a validation study in seven hospitals. Cases were identified from medical discharge records with ICD-9 codes 042.0 through 042.9 for the period from 1/1989 through 12/1990. Unreported AIDS cases were identified by comparing cases in the San Mateo County AIDS registry. Based on the validation study, active surveillance efforts were initiated in one hospital, and active surveillance protocols were developed for the other hospitals. Underreporting rates were determined by comparing cases reported through the validation study or active surveillance with the total number of cases reported during the time period.

Rosenblum et al. (1992)

AIDS

To evaluate the completeness of AIDS case reporting.

Statewide or hospital-specific 1988 medical records were linked with AIDS surveillance in six sites. Medical records were reviewed for persons with diagnoses suggesting HIV or AIDS but who had not been reported to the registry.

Buehler et al. (1992)

AIDS

To describe the completeness of AIDS surveillance in specific state and local areas and to assess the completeness of reporting at a national level.

State/local completeness assessed by reviewing state and local health dept studies of completeness (conducted after 1987 and w/ ≥20 cases); most studies matched AIDS cases in registry with alternate data sources (death certificates, hospital discharge records, etc.). National completeness assessed by comparing estimate from vital records of HIV-related deaths among men 25–44 in 1988 to mortality data from AIDS case reporting in 1987.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

San Mateo County, CA

The validation study demonstrated that 24% of AIDS cases in all hospitals were not reported through passive surveillance in 1990.

The hospital-based case finding method developed by the authors may be needed to ensure that diagnosed AIDS cases from active surveillance are timely diagnosed, complete, and accurate.

Alabama, Georgia, Los Angeles, Maryland, New Jersey, Washington State

Overall completeness was 92% among 4500 hospitalized persons diagnosed with AIDS through 1988 in six sites. Completeness ranged from 89 to 97% across the sites.

Completeness of AIDS reporting was high, overall and in each major demographic and HIV exposure group. Surveillance data in these six sites were timely and accurate.

Various state and local health departments and at national level

> 80% completeness in most states and localities, but lower levels of reporting found in some outpatient settings. At national level, AIDS surveillance identified 70–90% of all HIV-related deaths in men 25–44 years of age.

Efforts to maintain levels of reporting are challenged by increasing role of outpatient diagnosis of AIDS.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Modesitt et al. (1990)

AIDS

To retrospectively determine the number and characteristics of AIDS cases that had gone unreported under the previous passive surveillance system.

The authors used four active surveillance methods (review of death certificate and medical records, and enhanced infection control practitioner and physician surveillance) to identify unreported cases diagnosed from 2/1/1986 to 1/31/1987, one year before active surveillance began. Cases were classified as reported by passive surveillance if the case was not reported by any reporting source after active surveillance began and more than 6 months after diagnosis.

Lindan et al. (1990)

AIDS

To examine the completeness of reporting of AIDS deaths to the California AIDS registry.

The authors compared death certificates for 1985–1986 where AIDS or an associated condition was listed as cause of death to cases reported to the California AIDS registry. Authors only examined death certificates with race classification of Hispanic, white, or black.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

Oregon

Active surveillance retrospectively identified 29 additional cases. 90% of these cases were diagnosed by a physician and cared for in hospitals that previously reported cases. Under the passive surveillance system, reporting completeness was 64%.

Passive AIDS surveillance is incomplete.

San Francisco

The proportion of deaths not reported to the California AIDS registry was similar among Hispanics, blacks, and whites (5–8%). Race misclassification varied in the AIDS registry. For Hispanics, 20% were misclassified as white, and for blacks, 4% were misclassified as white. On the other hand, only 1% of whites were misclassified as either black or Hispanic. The proportion of deaths still listed as living in the registry varied among the three different race groups. For Hispanics, blacks, and whites, 12%, 9%, and 5% were still considered living in the registry, respectively.

The findings suggest that overrepresentation of minorities among AIDS cases in the United States may be greater than indicated by current reporting data.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Brookmeyer and Liao (1990)

AIDS

To analyze delays in AIDS reporting in the United States.

The authors developed a simple method to analyze delays in AIDS reporting. Cases in the AIDS Public Information Dataset reported to CDC prior to 10/1/1989 were included in the analysis. Reporting delays were assessed by estimating the reporting delay distribution and determining the influence of geographic region of residence, risk group, and calendar year time of diagnosis on reporting.

Conway et al. (1989)

AIDS

To evaluate the completeness and accuracy of AIDS case reporting.

The authors identified hospital discharge records submitted from 1/1/1986 to 6/30/1987 with ICD-9 AIDS-related and AIDS-defining conditions. AIDS cases were compared to those reported in the South Carolina AIDS registry at time of their diagnosis.

Hardy et al. (1987)

AIDS

To assess the completeness of AIDS reporting.

Completeness was assessed by reviewing death certificates for period of 3 months during July through December 1985. Death certificates were selected and matched to the AIDS surveillance registries in each city. Medical records of those not in the AIDS registry were reviewed to determine if AIDS had been diagnosed.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

United States

In cases that met the pre-1987 AIDS surveillance definition, delays were shortest in regions in the Northeast and longest in the South. The influence of risk groups and calendar year of diagnosis was not consistent across each of the geographic regions. Most risk-group variation was due to longer reporting delays in the blood-transfusion and pediatric groups. An overall trend of longer delays with calendar time of diagnosis was attributed to a trend toward longer delays in the Northeast. Results were similar for cases that met the 1987 AIDS surveillance definition, except there was a trend toward shorter delays over calendar year, which was attributed to possible increased awareness of the new surveillance definition.

The results demonstrated variation in reporting delays by geographic region, risk factors, and calendar year time of diagnosis. Methods and results are useful for the evaluation of surveillance procedures to improve AIDS reporting.

South Carolina

Only 91 (59.5%) of identified AIDS cases were reported in the South Carolina AIDS registry. There was significant underreporting in blacks (53.1%) compared to whites (71.6%).

There was a degree of underreporting or underrecognition of AIDS that was considerably more extensive than previously reported.

DC, NYC, Boston, Chicago

The estimated completeness of AIDS case reporting in all four cities was 89%. In Boston and Chicago, completeness was 100%. In NYC, completeness was 87%, and in DC, completeness was 83%. Unreported cases were similar to reported cases with respect to sex, race, risk factor, and specific diagnosis.

AIDS case reporting in four participating cities was nearly complete. The study suggests that reviewing death certificates may be useful in evaluating AIDS surveillance efforts.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Chamberland et al. (1985)

AIDS

To evaluate the timeliness of AIDS case reporting in an active surveillance system.

The authors reviewed hospital laboratory and autopsy records in active and modified-active surveillance hospitals. Patients who had opportunistic diseases characteristic of AIDS diagnosed in 1982 (before active surveillance) and 1983 (after active surveillance) were compared to cases reported to the health department’s AIDS surveillance.

HIV STUDIES

Schwarcz et al. (2002)

HIV (Code)

To develop and evaluate the completeness, accuracy, and timeliness of a non-name-based HIV reporting system.

A population-based study of a set of nonname codes and a prospective study of a labinitiated HIV surveillance system was conducted at San Francisco county hospital (site 1) and an HMO (site 2). Participants include persons reported with AIDS in San Francisco or patients with positive tests for HIV, p24 antigen, viral load or CD4+ cell count at the study sites.

Lee et al. (2002) (Note: Unpublished)

HIV (Name) and AIDS

To determine the proportion of adult HIV and AIDS cases reported within 6 months of diagnosis.

Used cases diagnosed from 1995–2000 reported through June 2001. Measured HIV timeliness and AIDS timeliness separately. Provided states with software program to ensure consistent measures.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

New York City

96% of AIDS patients in the active surveillance hospitals and 100% patients in the modified-active surveillance hospitals had been reported to the health department. Delays between diagnosis and reporting to health departments decreased between 1981 and during the first half of 1983 in all hospitals. During this period, the proportion of cases reported within one month of diagnosis increased from 45% to 69%.

The AIDS surveillance program in New York City was effective and that case reporting is complete for accurate analysis of disease trends.

San Francisco

Completeness: 89% at county hospital and 87% at HMO; Accuracy: proper match rate for 95% of records w/complete codes & w/at least 50% of the codes; proper nonmatch rate for 099% of records w/complete codes & 96% w/ at least 50%; Timeliness: 82% completed reports from site 1 and 48% reports from site 2 were returned to the health department within 60 days; median days between test and receipt of test report: 9 (site 1), 7 (site 2); Risk info was present for 84% reports from hospital and on 71% reports from HMO.

A nonname-based laboratory reporting system for HIV is feasible.

For HIV: 27** states with name-based reporting systems.

For AIDS: 52 states

HIV: 83.4% of cases reported within 6 months of diagnosis. AIDS: 71.1% of AIDS cases reported within 6 months.

26 of 27 states met timeliness standard for HIV reporting (>66% of HIV cases reported within 6 months of diagnosis). 45 of 52 states met timeliness standard for AIDS reporting (>66% of AIDS cases reported within 6 months of diagnosis).

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Solomon et al. (1999)

HIV (Code)

To evaluate the uniqueness and completeness of the UI number, the accuracy of the reporting, and the completeness of HIV reporting in a statewide nonname-based HIV surveillance system.

Uniqueness of UI number was assessed by measuring the contribution of each component of the UI to the uniqueness of the number. Accuracy was assessed by examining the AIDS registry for multiples of identical UIs. Completeness of HIV reporting was assessed by matching the HIV counseling and testing (C&T) reports with AIDS registry data.

Marsh et al. (1999) (Note: Unpublished)

HIV (Code)

To evaluate the performance of non-name-coded identifiers to CDC’s performance standards.

13 nonname codes were constructed using preliminary AIDS case reports collected in Los Angeles (from 9/97 to 12/97 and HIV and AIDS reports collected in New Jersey (from 3/98 to 1/99). Each code was then tested to assess proper match rate and proper nonmatch rate.

CDC (1998)

HIV (Code)

To evaluate UI surveillance for HIV for completeness, timeliness, potential for UI matching to other databases, and proportion of reports with full UI code.

The study evaluated cases reported from 1/1995 to 6/1996 in two states (Maryland and Texas) with UI-based HIV surveillance systems. Completeness was assessed by comparing UI-database reports w/AIDS surveillance registry data & HIV counseling/testing sites data. Timeliness was calculated by median delay from time of test to report. Ability for epidemiological follow-up was assessed by evaluating ability to follow UI reports back to patient record (in TX) and by provider compliance in maintain patient surveillance logs (in MD).

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

Maryland

When complete, the 12-digit UI number provided unduplicated count that was 99.8% unique, 99.9% unique with only last 4 digits of SSN, DOB, and race, and 77.7% unique if last 4 digits of SSN were missing. Overall completeness of reporting for HIV tests was 87.8% (matching complete UI with HIV C&T reports) and 84.8% (matching UI w/AIDS registry data).

Findings demonstrate that a nonname-based system can provide accurate, timely, and valid data concerning the scope of the HIV epidemic, without the creation of statewide name-based registry.

Los Angeles County and New Jersey

In Los Angeles, the performance of codes ranged from 87.3% to 96.1% on subset of AIDS reports in which all data used to construct the codes were complete and in which codes matched exactly. In New Jersey, performance of the codes ranged from 74.3% to 90.8%.

Results from these two locations suggest that meeting CDC performance standards in nonname surveillance systems will be a challenge. It is critical for states implementing surveillance based on nonname identifiers to use standardized evaluation methods.

Maryland, Texas

Maryland—50% complete (UI data compared to AIDS cases), 52% complete (UI data compared to HIV counseling/testing site data); median time of HIV test to receipt of report by state health dept: 20 days (range 1–847); 71% of reports with full UI code; Texas—26% complete (UI data compared to AIDS cases); median time of HIV test to receipt of report by state health department: batched reports—173 days (range 26–974), individual reports—59 days (range 2–906); 62% of reports had full UI code; 60% of reports could be matched for follow-up.

Findings suggest some limitations to use of SSN-based UI for HIV surveillance, UIs limited the performance of an HIV surveillance system, and that UIs complicated efforts to collect risk-behavior information. Both systems demonstrated timely reporting.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Study

AIDS or HIV

Purpose

Methods

Klevens et al. (1998)

HIV (Name)

To evaluate the completeness of name-based HIV reporting.

Medical records of potentially HIV-infected patients at a sample of health care facilities in Louisiana were reviewed and matched with HIV/AIDS surveillance registry.

Meyer et al. (1994)

HIV (Name)

To assess the completeness of HIV reporting among hospital inpatients whose records listed diagnostic codes for HIV infection but who did not meet the 1987 case definition.

Hospital discharge data for 1986 through 1990 were searched for patients with any HIV-related discharge codes who did not meet the AIDS case definition. These reports were compared to cases in the state HIV registry.

*All AIDS cases in the United States are reported using a confidential, name-based reporting system.

**Timeliness of reporting of HIV cases from states conducting alternatives to name-based reporting were not included.

completeness has increased over time. Earlier studies (Hardy et al., 1987; Conway et al., 1989; Modesitt et al., 1990; Buehler et al., 1992; Rosenblum et al., 1992; Elcock et al., 1993; Greenberg et al., 1993) demonstrate completeness rates ranging from 60 percent to 92 percent. More recent studies (Schwarcz et al., 1999; Jara et al., 2000; Klevens et al., 2001; Scheer et al., 2001) show completeness rates more consistently higher at 93 percent to 97 percent.

The Committee notes, however, that completeness rates may vary across these studies in part because some examine the completeness of passive reporting systems while others examine active reporting systems.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Setting

Results

Conclusions

Louisiana

Completeness of HIV reporting was 96.8% in hospitals, 98.9% in clinics, 95.6% in private physicians’ offices.

Evaluation indicates that completeness of HIV reporting is comparable to that of AIDS reporting.

South Carolina

Of 396-HIV infected hospital inpatients, 313 (79%) had been reported to the state registry. This proportion varies from 81% in black women to 76% in white men. There are more substantial differences in mode of HIV exposure, varying from 85% in MSM and 81% in IDUs to 61% in blood product recipients. Temporal improvements were observed in completeness of HIV reporting among hospital patients and prior to their first admission. Women were more likely than men to be reported prior rather than during or after their first hospital admission (71% vs. 55%, p<0.01). Of the 155 HIV-infected patients with CD4 counts, 41 met the 1993 case definition but not the 1987 definition.

In SC, most diagnosed, hospitalized, HIV-infected patients had been reported to the state HIV registry, with improvements over time. Findings suggest that the 1993 AIDS case definition will improve the ability to monitor severe morbidity related to HIV.

Passive surveillance typically has lower rates of completeness because it relies on the cooperation of health care professionals to report AIDS cases (Elcock et al., 1993). Active reporting (which involves searching death records, hospital discharges, and other administrative data sources to identify cases that have not been reported to the system) tend to have much higher rates of completeness. All states are now funded by CDC to conduct active surveillance of AIDS (CDC, 1999).

Published studies that primarily examined the effect of the 1993 case definition expansion on completeness of AIDS surveillance in Louisiana, Massachusetts, and San Francisco found that completeness typically tops

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

90 percent and approaches 100 percent (Schwarcz et al., 1999; Jara et al., 2000; Klevens et al., 2001). Reporting completeness by race/ethnicity or risk factors, however, varied. In San Francisco, completeness of AIDS reporting did not differ significantly by race, gender, or age (Schwarcz et al., 1999). In contrast, unreported cases in Massachusetts were significantly more likely to be female (OR = 1.72, 95% CI 1.20-2.46), and injection drug users were slightly more likely to be unreported than cases of transmission between men who have sex with men (OR = 1.49, 95% CI 1.00-2.23) (Jara et al., 2000). These findings are in agreement with findings from earlier studies that demonstrated reporting completeness of around 90 percent (Hardy et al., 1987; Buehler et al., 1992; Rosenblum et al., 1992) and similar reporting variations by race/ethnicity or risk factor (Conway et al., 1989; Lindan et al., 1990). The greater the variability in the completeness of data across states or EMAs, the greater the chance for bias. Minimizing variation is more important for allocation decisions than a high average level of completeness.

Studies examining the completeness of HIV reporting (Meyer et al., 1994; CDC, 1998; Klevens et al., 1998; Marsh et al., 1999; Solomon et al., 1999; Schwarcz et al., 2002) compared reported HIV cases to the number of individuals in care for HIV-related illness. These studies show that HIV case reports are only slightly less complete than AIDS case reports. No published studies have directly scrutinized cross-state variability in HIV completeness rates. CDC is currently conducting an evaluation of cross-state completeness, but results were unavailable when this report was prepared. Cross-state variability is likely to be higher for HIV than for AIDS case reporting, however, because the HIV completeness rate is related to the use of health care services by HIV-infected persons. Persons with asymptomatic HIV infection and those who do not know they are infected may not present for care, while those with syndromic AIDS are more likely to present for care. The aggressiveness of HIV counseling and testing policies also varies greatly across states. It is therefore likely that estimates of HIV prevalence may be both more biased and more variable than are estimates of AIDS prevalence and incidence.

Timeliness of AIDS and HIV Case Reporting

Timing studies identify the lag between the first diagnosis of a case and its report to CDC by comparing reported cases to an external source. Variation in reporting delays across jurisdictions can result in systematic biases in estimates of HIV or AIDS prevalence and incidence. While statistical adjustments are routinely used to account for incompleteness and delays in AIDS reporting (Green, 1998), these adjustments often assume that patterns of delays in missing reports are constant over time and

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

across geographic areas. Estimates of AIDS or HIV incidence or prevalence resulting from an AIDS or HIV case-reporting system will be biased if the assumptions made in correcting for reporting delays are not met, but such assumptions are usually difficult, if not impossible, to assess.

Studies of timeliness of AIDS case reporting (Chamberland et al., 1985; Brookmeyer and Liao, 1990; Schwarcz et al., 1999; Klevens et al., 2001) indicate important variability in reporting delays across state and local reporting systems. Median reporting delays vary from 1 month to 6 months. States with lab-initiated CD4+ cell reporting had less reporting delay than states without such reporting (Klevens et al., 1997).

Brookmeyer and Liao (1990) and Pagano and colleagues (1994) have developed statistical methods for estimating and adjusting for AIDS reporting delays. One earlier study by Brookmeyer and Liao (1990) found significant geographical variation in the timeliness of AIDS reports; delays were shortest in the Northeast and longest in the South. Pagano and colleagues (1994) found significant variation in time trends in AIDS reporting delays by region. From 1983 to 1990, reporting delays appeared to increase most in the Northeast and decrease most in the Central region.

More recent research (Klevens et al., 2001) examined the timeliness of reporting in three locations before and after the 1993 change in the CDC definition of AIDS.9 California saw a substantial decrease in the median reporting delay, from 14 to 3 months. The change in the median reporting delay in Louisiana and Massachusetts was less. After 1993, however, the median reporting delay differed substantially across states, varying from 6 months in Massachusetts to 3 months in California and Louisiana.

At the time of this report, no published studies had examined the timeliness of HIV case reporting. However, CDC provided the Committee with results from an evaluation of the timeliness of HIV and AIDS reporting in 10 areas.10 The CDC specified, as a minimum performance standard, that 66 percent or more of HIV and AIDS cases should be reported to the state within 6 months of diagnosis (CDC, 2003e). The evaluation was designed to determine the proportion of HIV and AIDS cases among adults and adolescents > 13 years of age reported within 6 months

9  

In 1993, CDC expanded the AIDS case definition to include individuals with CD4+ cell counts of ≤ 200 cells/µL, or less than 14 percent of total lymphocyte, and three additional conditions among HIV-infected persons (CDC, 1992).

10  

The evaluation uses standardized protocols to assess the performance of HIV reporting systems for eight attributes: timeliness, accuracy, ascertainment of transmission mode, completeness, validity of data elements, ability to match to other public health databases, ability to follow up on cases of public health importance, and use of data for public health planning. With the exception of the timeliness analyses, the results of this evaluation will not be available until after this report is issued.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

of initial diagnosis of HIV or AIDS. Using the national HIV/AIDS Reporting System (HARS) as the data source for the evaluation, CDC examined HIV and AIDS cases diagnosed from 1995 to 1999.11 HIV timeliness and AIDS timeliness were evaluated separately using an 18-month follow-up (CDC, 2003e). Results show that 88 percent of HIV cases were reported within six months of diagnosis, with all 27 states that reported HIV during this time period meeting the performance standard (CDC, 2003f). Approximately 78 percent of AIDS cases nationally were reported within 6 months of diagnosis, with 50 of 52 (96 percent) states (including the District of Columbia and Puerto Rico) meeting the standard (CDC, 2003f). The evaluation showed variation, however, in the timeliness of reported cases across states.12 The percent of HIV cases reported within 6 months varied from 67 percent to 100 percent across states, while the percent of AIDS cases reported within 6 months varied from 64 percent to 96 percent (CDC, 2003e). The results did indicate that the timeliness of HIV reporting improved over time; in 1995, 86 percent of HIV cases were reported within 6 months of diagnosis, compared with 91 percent of cases in 1999 (Lee et al., 2002).

CDC’s evaluation may shed light on the relative completeness and timeliness of HIV and AIDS case reporting in selected jurisdictions. However, the evaluation was not designed to specifically address the use of these data in RWCA resource allocation studies, and thus may not address key issues related to differential bias across jurisdictions. Additional studies are needed to examine the comparability of data from the HIV case-reporting system across jurisdictions for the purpose of allocating RWCA resources.

Methodological Consistency

The Committee noted three areas in which variation in methods (across states and EMAs) for finding and reporting cases of HIV might introduce differential biases in HIV cases. First, variation across jurisdictions in the rates of migration of people living with HIV or AIDS can affect allocations. The distribution of RWCA funds is based primarily on AIDS cases, which reflect the place of residence at time of the original AIDS diagnosis. Although individuals with AIDS may move to a new state or metropolitan area, the state or metropolitan area where the per-

11  

A timeliness measure for AIDS was calculated for each of the 5 years (1995, 1996, 1997, 1998, and 1999). In states with HIV reporting, an evaluation of the timeliness of HIV reporting was initiated 2 years after the implementation of the reporting system.

12  

Data were provided without state identifiers in this analysis.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

son was originally diagnosed continues to receive funding for that person. As a result, immigration of persons with AIDS after diagnosis can lead to inequitable allocation because jurisdictions that now provide care for those persons do not receive funding for those cases. Many grantees have expressed concern about this issue (LaMendola, 2002). It is important to consider the rate of out-migration as well, as jurisdictions may receive funding for individuals that no longer live there. Individuals with HIV that have not progressed to AIDS may be even more mobile and likely to migrate to another state or EMA over the course of their lifetime than individuals with AIDS. Thus, the potential incorporation of data on HIV cases into the RWCA formulas raises concerns about the possible inequitable allocations that may result from increased migration of people with HIV.

The evidence regarding migration is limited. Early in the epidemic, the vast majority of individuals living with HIV were concentrated in several major urban areas. With time, HIV spread to other areas of the country and into nonmetropolitan areas. Studies concluded that the nonmetropolitan areas were the sites of greatest rate of increase in AIDS cases in the early 1990s (Lam and Liu, 1994). A number of early studies indicated that large numbers of persons who were infected with HIV in an urban area moved home to rural communities (Verghese et al., 1989; Davis and Stapleton, 1991; Ellis and Muschkin, 1996). Other studies documented that a sizable number of persons were diagnosed in one state or metropolitan area, but living in another area (Davis and Stapleton, 1991; Verghese et al., 1995; Beltrami et al., 1999). One study that examined migration of persons with AIDS across states (Buehler et al., 1995) found that approximately 1 in 10 persons with AIDS changed his or her place of residence between diagnosis and death, and half of these individuals moved to another state. The researchers concluded that place of residence at diagnosis was a reasonable measure of the impact of AIDS in large urban communities with heavy concentration of the epidemic, but that residence at time of diagnosis underestimated the impact of AIDS in rural communities. A more recent study (Berk et al., 2003) based on the national probability sample of persons with HIV in care found that only 8 percent of persons with HIV migrated from urban to rural areas. The researchers concluded that urban areas are drawing as many people with HIV as rural areas (Berk et al., 2003).

CDC is currently evaluating migration among people with HIV and the assignment of cases to jurisdictions as part of its interstate deduplication evaluation project (CDC, 2003b), but results were not available at the time of this report. An evaluation of such possible effects should be part of developing standard protocols that would be acceptable to CDC for reporting.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Second, states and territories vary in the procedures laboratories use to report HIV cases (Table 4-2). According to CDC data, in 40 of the 54 states and territories (74 percent), laboratories report CD4+ cell results, and 43 of 54 (80 percent) report plasma viral load results. Those states with laboratory CD4+ reporting vary in the reportable levels; for example, some states set the reportable level at <200 cells/µL, while others set it at <400 cells/µL, <500 cells/µL, or <800 cells/µL. In addition, not all states have viral load laboratory reporting. Twenty-nine (54 percent of) states, Puerto Rico, the U.S. Virgin Islands, American Samoa, and the District of Columbia had some form of electronic laboratory reporting for HIV (CDC, 2003c,d).

Those states without laboratory-based reporting will systematically underestimate the number of patients with diagnosed HIV infection, which may bias allocations. While electronic laboratory-based reporting improves the completeness of HIV reporting, it adds substantial workload because patients diagnosed with HIV infection require numerous laboratory tests to manage their antiretroviral therapy, and each test must be linked to a known case or determined to be a new case.

The third methodological phenomenon that might introduce differential estimates among states is the aggressiveness of case finding. Some states screen more people for HIV and conduct more follow-up investigations than other states. For example, states that have more aggressive screening programs (e.g., those that screen high proportions of pregnant women, arrestees and prisoners, and premarital couples) will likely report a greater percentage of cases than states that do not. States that make fuller use of anonymous testing will report a lower percentage of cases than those that make minimal use of this option or prohibit it by law.13 Anonymous testing tends to decrease reporting because there is no identified person to report.

13  

HIV testing is conducted either confidentially or anonymously. With confidential testing, a person’s name is recorded with the test result. Other health care personnel and the state and/or local health department may have access to this information. With anonymous testing, there is no link between the patient’s name or other identifying information and the test result (Kaiser Family Foundation, 2003). All states offer confidential testing. As of October 2003, 10 states (Alabama, Idaho, Iowa, Mississippi, Nevada, North Carolina, North Dakota, South Carolina, South Dakota, Tennessee) and the U.S. Virgin Islands did not offer anonymous testing (See Table 4-1).

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

TABLE 4-2 Status of CD4+ Cell Count and HIV Viral Load Reporting (as of April 2003)

State/Area

CD4+ Reporting

Reportable Level (CD4+ Cell Count/µL)

HIV Viral Load

Alabama

No

 

No

Alaska

Yes

<200

Yes

American Samoa

No

 

No

Arizona

No

 

Yes

Arkansas

Yes

All

Yes

California

No

 

Yes

Colorado

Yes

<500

Yes

Connecticut

Yes

<200

No

Delaware

Yes

<200

Yes

District of Columbia

Yes

<200

No

Florida

No

 

No

Georgia

No

 

No

Hawaii

Yes

<200

Yes

Idaho

Yes

<500

Yes

Illinois

Yes

<200

Yes

Indiana

Yes

All

Yes

Iowa

Yes

<400

Yes

Kansas

Yes

<500

Yes

Kentucky

Yes

All

Yes

Louisiana

Yes

All

Yes

Maine

Yes

<200

Yes

Maryland

Yes

<200

Yes

Massachusetts

Yes

<200

No

Michigan

No

 

No

Minnesota

No

 

Yes

Mississippi

Yes

All

Yes

Missouri

Yes

All

Yes

Montana

No

 

Yes

Nebraska

Yes

<800

Yes

Nevada

Yes

<500

Yes

New Hampshire

Yes

All

Yes

New Jersey

Yes

<200

Yes

New Mexico

Yes

All

Yes

New York

Yes

<500

Yes

North Carolina

No

 

Yes

North Dakota

No

 

Yes

Ohio

Yes

<200

Yes

Oklahoma

Yes

<500

Yes

Oregon

Yes

<200

Yes

Pennsylvania

Yes

<200

Yes

Puerto Rico

Yes

<200

No

Rhode Island

Yes

<200

Yes

South Carolina

Yes

<200

Yes

South Dakota

No

 

No

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

State/Area

CD4 Reporting

Reportable Level (CD4+ Cell Count/µL)

HIV Viral Load

Tennessee

Yes

<200

Yes

Texas

Yes

<200

Yes

Utah

Yes

All

Yes

Vermont

No

 

Yes

Virgin Islands

Yes

<200

No

Virginia

No

 

Yes

Washington

Yes

<200

Yes

West Virginia

Yes

<200

Yes

Wisconsin

Yes

<200

Yes

Wyoming

Yes

<200

Yes

 

SOURCE: CDC, 2003c.

Findings About Comparability of Data

Finding 4-2 Different rates of completeness and timeliness of HIV reports across states and EMAs have the potential to create significant biases in RWCA formula allocations. To date, studies have not answered key questions about the comparability of HIV case-reporting data for use in resource allocation formulas. Additional studies are needed to examine the comparability of data from the HIV case-reporting system across states and EMAs.

RELATIVE DISEASE BURDEN AND RANKING OF NEED ACROSS JURISDICTIONS

Many grantees, researchers, advocates, and policy makers assume that adding HIV reporting data will produce a fairer allocation of resources than will reliance on ELCs alone. One premise underlying this assumption is that the HIV epidemic is in different stages of “maturity” in different areas of the country. Here maturity refers to the length of time that the epidemic of HIV infection has been established in at-risk populations. Because the risk of AIDS is low in the first years after infection and then rises over time, one would expect the ratio of reported HIV to AIDS cases to be higher in more recently infected populations than in populations where the epidemic had been established for a longer period of time, and most infected individuals acquired HIV many years ago. Thus assuming very different stages of maturity of the epidemic would lead one

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

to expect significant variation in this ratio across jurisdictions.14 States that believe their HIV epidemic was established relatively recently suspect that the current measure (based on AIDS cases alone) places them at a disadvantage in RWCA formula allocations. If, however, the epidemic is at similar levels of maturity across jurisdictions, and therefore the ratio of reported AIDS cases to reported HIV cases is relatively constant, including data on HIV cases in the formula will, in fact, have little influence on the relative measure of disease burden, and hence little influence on the awards.

Although it seems reasonable to assume that the epidemic is in various stages of maturity in different jurisdictions, it is difficult to confirm this belief. Some data do suggest the possibility of regional variation—specifically that the epidemic may be growing more quickly in the southern region of the United States than elsewhere. The South is registering a growing share of newly reported AIDS cases, rising from 40 percent to 46 percent between 1996 and 2001 (Kates and Ruiz, 2002).15 While estimated AIDS incidence (new AIDS cases) for the entire United States remained relatively flat (increasing only 1 percent) between 2000 and 2001, estimated AIDS incidence in the South rose by 9 percent during that period (Kates and Ruiz, 2002). AIDS incidence fell in the Northeast by 8 percent and in the West by 4 percent, but rose in the Midwest by 2 percent during the same time period (Kates and Ruiz, 2002).

Inspection of the cumulative distribution of AIDS cases (reported by year of diagnosis and adjusted for reporting delays) by state and EMA from 1981 to 200116 suggests that the AIDS incidence curves have fairly similar—though not identical—shape across states over time (Figures 4-1 and 4-2); similarity in shape implies roughly similar epidemic dynamics. These figures also illustrate shifts over time in these curves, implying that the stage of epidemic maturity differs somewhat from state to state (and from EMA to EMA). Each individual curve in the figure represents the cumulative reporting of AIDS cases in a given jurisdiction (EMA or state) from 1981 to 2001. Hence, all curves begin at 0 percent in 1981 and reach 100 percent by 2001.17

14  

HIV cases refers to reported cases of HIV that have not progressed to AIDS. Reported HIV cases are exclusive of reported AIDS cases.

15  

In Kates and Ruiz (2002), the southern region of the United States was defined as including the following states: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.

16  

These figures include cases reported through December 2002 but in which the diagnosis year was 2001 or earlier.

17  

There is an implicit assumption in the construction of these figures that all jurisdictions have attained the same “100 percent mature” level by 2001, artificially normalizing the distributions to 2001.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

FIGURE 4-1 Cumulative AIDS cases by state and diagnosis year, adjusted for reporting delays, 1981 to 2001.

SOURCE: CDC, 2003g.

For any calendar year between these two anchors, curves denote the cumulative cases reported up to that point in time (as a percent of the eventual total cases reported by 2001). In Figure 4-1, for example, the topmost curve denotes cumulative AIDS cases in state A. This curve indicates that 50 percent of all AIDS cases reported to have occurred by 2001 in state A had been reported by 1992; 75 percent of these cases had been reported by 1995. At any given time, state A had reported a greater fraction of its 2001 cumulative total than any other state; in this sense, this state was at the leading edge of the epidemic. By contrast, the epidemic is least mature in state B (the bottom curve in the figure). More than half of state B’s eventual total AIDS cases were reported after 1994; 75 percent of all cases had not been reported until 1998. The horizontal distance between any two curves represents the time lag between states in attaining the same cumulative proportion of reported AIDS cases—a measure of “epidemic maturity.” Figures 4-1 and 4-2 illustrate the extensive overlap in the cumulative distribution cases over the course of the epidemic across jurisdictions, with the 50th percentile of all cases reached between the earliest and latest state being only 3 years. The conclusion is that while we might expect a higher ratio of HIV to AIDS cases in some jurisdictions than others, this effect is not likely to be particularly large.

Using the ratio of HIV to AIDS cases as a proxy for epidemic maturity has some limitations. Variation in the proportion of HIV to AIDS cases can be plausibly attributed to factors beyond differences in the maturity of the epidemic, such as regional variations in treatment practices that

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

FIGURE 4-2 Cumulative AIDS cases by EMA and diagnosis year, adjusted for reporting delays, 1981 to 2001.

SOURCE: CDC, 2003g.

delay the onset of AIDS. States and EMAs may also differ in the aggressiveness and quality of HIV screening and case finding, with some identifying a higher proportion of new cases, thus increasing the ratio of HIV to AIDS cases.

Finding Regarding Relative Disease Burden and Ranking of Need

Finding 4-3 The Committee could not confirm the hypothesis that the maturity of the HIV epidemic varies significantly across regions. If the ratio of reported AIDS cases to HIV cases differs across states or EMAs, including data on HIV cases in the RWCA formulas could affect the relative measure of disease burden and the allocations. Data examined by the Committee suggest that the rate of new HIV infections is somewhat greater in the southeastern region of the United States. Due to the lack of HIV case data in all areas, however, assumptions regarding interregional variability in epidemic maturity need further assessment.

SENSITIVITY OF THE FORMULA ALLOCATIONS TO CHANGES IN THE UNDERLYING INPUT DATA

In this section, the Committee examines whether the allocation formula would be sensitive to changes in the underlying data, and whether variation across measures of the relative number of reported cases of HIV

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

in a state or EMA changes the relative allocation of resources. The Committee originally intended to conduct extensive “what-if” policy simulations. That is, it intended to compare different factors in the funding formulas to examine the impact of including HIV cases on resource allocations across regions, and to compare the inclusion of HIV cases to other features, such as hold-harmless provisions, set-asides, minimum funding thresholds, and the potential addition of new EMAs based on a more inclusive definition of HIV burden. The Committee could not examine the effect of including HIV data in the formula because data on HIV cases were not available from all states, including several key states with a high disease burden. Since data from those states could have a large influence on results, any analyses based on partial data could be very misleading. Nevertheless, the analyses and policy assessment in Appendix C highlight the implications of current policies. These findings should allow policy makers to explore the implications of proposed changes in funding allocations.

Instead, the Committee chose to explore how assessments of the “fairness” of those awards might be influenced by including data on estimated HIV and AIDS prevalence.18 In particular, the Committee examined what the current allocation is using the ELCs (the measure now used for RWCA resource allocation) and combined estimates of HIV prevalence and AIDS prevalence.19

The Committee also employed multiple linear regression analysis to identify predictors of RWCA Title I and Title II funding. The findings from these analyses are summarized in the following pages, but are discussed in detail in Appendix C.

In its analyses, the Committee examined total allocations per case (i.e., Title I and II funds) across states and EMAs as a point of departure. The Committee acknowledges that there are many reasons why an equitable system would depart from this standard, including unequal costs of care, unequal need, differences in the efficiency with which jurisdictions apply funds, differences in the quality and comprehensiveness of the

18  

For states with mature name-based HIV reporting systems, estimates of HIV prevalence were based on data from their individual case-reporting systems. For code-based states or states without mature name-based reporting systems, CDC used modeling to produce the HIV prevalence estimates. California and Massachusetts declined to release CDC’s estimates of HIV prevalence, and thus no data were available for these two states.

19  

These data were provided by the CDC based on a data request to the states. The Committee also examined current allocations using AIDS prevalence alone. The differences in allocations using estimated AIDS prevalence and ELCs were not informative, suggesting that any methodological differences between the calculation of ELCs and the calculation of AIDS prevalence is not important for the purposes of identifying allocation variations.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
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existing resource base from one jurisdiction to another, and differences in economies of scale.

In some instances, deviations from the “equal dollars per case” standard will highlight disparities to be corrected; in other instances, they will confirm the view that the system is applying appropriate flexibility to its standards to reflect legitimate differences in need from one jurisdiction to another. Viewed in this light, the Committee’s goal is not to hold up equal dollar allocation as an absolute standard, but rather to make explicit the consequences of allocation formulas that are the product of complex political negotiation, epidemiological evidence, and competing conceptions of fairness.

Findings About the Sensitivity of the Formula to Changes in the Underlying Data

Finding 4-4 When examining combined Title I and II funds, the Committee found that those awards depart from a nationwide standard of equivalent spending per unit of HIV burden. Although such departures may be appropriate, the justification for such departures was not clear. Such departures persist regardless of the measure of disease burden used, but they are most pronounced when using a combined measure of estimated HIV prevalence and AIDS prevalence.

Finding 4-5 With the exception of San Francisco, Title I formula allocations per ELC are quite uniform across EMAs. Because of hold-harmless provisions, the San Francisco EMA receives significantly greater resources per ELC than do other EMAs. Removal of this provision would reduce San Francisco’s allocation to within the reported range for other EMAs. However, removing the hold-harmless protection would have a small influence on other EMAs, which would observe a 2.6 percent increase in their allocation if San Francisco’s allocation were reduced. As noted by others (GAO, 2000), hold-harmless provisions have a small overall effect on allocations to EMAs, yet a large effect on a single EMA.

The Committee identified several structural features that dampen the effect of variation introduced by the addition of HIV cases, including:

  • Presence of an EMA in a state. Disparities in funding per ELC across states and localities appear most pronounced between states that do and do not have an EMA. Although Title II funding formulas include adjustments for non-EMA states, the cumulative effect of these provisions is small compared with cross-state disparities in Title I funding. More-

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

over, states whose ELCs are concentrated within an EMA benefit from current allocation rules. This is because reported cases within an EMA contribute to both a state’s Title I award and its Title II funding. States that lack an EMA face a corresponding disadvantage.

  • Explicit set-asides for non-EMA states under Title II. Several features of the Title II award are designed to compensate jurisdictions that lack an EMA. These include the 20 percent of the Title II award that is reserved for non-EMA states and the minimum Title II base award of $500,000 per state. Both of these formula features would not be affected if HIV plus AIDS cases, instead of just AIDS cases, were used in the formulas.

  • Set-asides for emerging communities. Title II Emerging Communities provisions, defined as cities with 500–1,999 reported AIDS cases in the most recent 5 years, expressly set funds aside for non-EMA localities. While the Emerging Communities provision may be an appropriate response to the geographic expansion of the epidemic, it will reduce the effect of including HIV data in allocation formulas.

Finding 4-6 Several structural features of the Title I and Title II funding formulas—most notably the counting of EMA cases in both Title I and II state formula allocations, but also such measures as hold-harmless provisions and set-asides for emerging communities—have a large influence on resulting allocations. Such structural features may dampen the effect of variation introduced by the addition of HIV cases, and could obviate the potential benefits of adding HIV cases to the CARE Act allocation formulas.

The Committee notes with concern that southeastern states appear to receive the smallest allocations per ELC under current allocation rules. Some of this disparity arises from the rurality of southeastern states. People living with AIDS in the Southeast are less likely to reside in EMAs than are their counterparts in other regions. Viewing combined Title I and Title II funding, southeastern states are thus less likely to benefit from counting of EMA cases in both the Title I and II formulas. Southeastern states might also benefit from changes in RWCA allocation formulas that consider HIV in addition to reported AIDS cases. However, the role of EMAs in RWCA formula allocations appears to matter more than alternative definitions of HIV burden in accounting for regional differences in per ELC funding.

The Committee also notes the discordance between the intent of the RWCA formulas and their structure. RWCA is statutorily limited to acting as a payer of last resort, as it precludes expenditures for anything covered by other public or private insurance or benefit programs. Funds are intended for services to individuals who are low income, and unin-

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

sured or underinsured. Yet formula allocations are made purely on the estimated number of living AIDS cases. Insofar as the current RWCA case-reporting–based formula counts patients that have other sources of insurance or funding, it overestimates the number of cases that qualify for RWCA services, just as it may underestimate the needs of a particular jurisdiction with greater proportions of patients with HIV who are not included in the formula but who would qualify for RWCA services. The current formulas also do not account for variations in the costs of care or fiscal capacity across Title I and II jurisdictions. A 1995 GAO report cited similar concerns with the formulas and concluded that the equity of the formulas could be improved through the use of more appropriate measures of services costs and funding capacity of jurisdictions. Other formula-based programs, including Medicaid and the Substance Abuse and Mental Health block grants, consider costs and/or fiscal capacity (NRC, 2003).

Finding 4-7 RWCA Title I and II formula allocations are determined by the ELC. Thus, they do not take into account factors defining those for whom such funds were intended, such as lack of insurance and special needs. That is, there are no provisions to estimate the number of persons in need of a “payer of last resort.”

METHODS FOR IMPROVING DATA FOR THE FORMULAS

The Committee believes that there are several ways to improve the overall quality and completeness of the HIV case-reporting system for allocating resources under RWCA. First and foremost is the need to include all reported HIV cases in the national database rather than only those reported from states with name-based reporting. Other sources of data, particularly from laboratories, and potentially from pharmacies and other drug providers, can also be more fully utilized to improve the completeness and comparability of HIV reporting systems.20 Twenty-nine states rely on electronic laboratory-based reporting of HIV test results as

20  

Most states specifically require laboratories (as well as medical providers) to report cases of HIV or AIDS to the state health department pursuant to their state disease reporting laws or regulations. The Health Insurance Portability and Accountability Act allows covered entities to release this health information to state health departments in compliance with state disease-reporting laws. States that do not expressly require laboratories to report would have to enact a statute or issue a regulation (depending on the state’s statutory structure) to allow laboratories to report. An amendment to the state’s reporting statute or regulation could accomplish this rather simply and ensure that the laboratory is subject to

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

part of their HIV reporting systems; comparability in the completeness and timeliness of reporting could be enhanced if all states adopted electronic laboratory reporting. States can also boost their completeness of reporting by including laboratory reporting of other tests unique to HIV infection, such as plasma viral load, CD4+ cell counts, and phenotypic and genotypic resistance testing, as well as pharmacy records for antiretroviral drugs unique to HIV infection. Integrating laboratory-based and pharmacy-based reporting with the National Electronic Disease Surveillance System (NEDSS)21 may require additional research. Second, it is important to explore ways of accounting for differential bias in prevalence estimates due to migration.

In addition to these concerns, it is important to evaluate other approaches, such as survey- and modeling-based approaches, for estimating both the overall burden of HIV and the differential disease burden among states and EMAs and to compare these estimates to those produced by case reporting. Such approaches have the potential of providing estimates that are more accurate, more timely, and more consistent across jurisdictions than complete enumeration. One such approach may rely on statistical models and make use of information from a variety of sources. An example of the use of a statistical model is backcalculation of HIV incidence and prevalence from data on AIDS incidence using estimates of the distribution of time from HIV infection to onset of AIDS (Brookmeyer and Gail, 1994). The usefulness of this method, however, has declined over time since the distribution of time from infection to AIDS has become less predictable with the advent of improved therapies. Other attempts to estimate HIV prevalence in specific metropolitan areas have made use of information about sizes of populations at risk and prevalence of HIV infection in those populations from a wide variety of sources (Holmberg, 1996). Holmberg and colleagues suggested as useful sources:

   

the same requirements and privileges as other entities that are required to report, including the duty of the state health department to keep personally identifiable information, if any, confidential. This would allow the state health department to collect relevant data from laboratories in the same manner that it collects data from providers. Thus, statutes protecting the confidentiality of such information should not be a major impediment to collecting information from laboratories and pharmacies to improve the accuracy of HIV case data at the state level.

21  

NEDSS is a project to integrate surveillance systems so that appropriate public health, laboratory, and clinical data can be transferred efficiently and securely over the Internet. NEDSS is designed to integrate and replace several current CDC surveillance systems, including the National Electronic Telecommunications System for Surveillance (NETSS), the HIV/AIDS reporting system, the vaccine preventable diseases and systems for tuberculosis (TB) and infectious diseases. See http://www.cdc.gov/nedss/ for more information on NEDSS.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

specific studies of prevalence and transmission among people at risk of infection; information from sexually transmitted disease (STD) clinics, counseling and testing sites, and drug treatment centers; and information from other sources of population testing, such as the Veterans Administration and other medical centers or household-based surveys. The addition of information from population-based surveys could greatly increase the usefulness of such approaches.

A previous IOM report (2001) recommended the use of sentinel surveillance in conjunction with population-based surveys as a way to estimate HIV incidence, but it could also be applied to obtain estimates of HIV prevalence. In this approach, one obtains prevalence data from targeted samples of special populations. For example, one might use information from blood donors, military recruits, and/or members of some special high-risk group. One then uses information from other, more representative samples, to estimate the prevalence of the characteristics that identify these special populations. For example, one could determine how likely different groups of people (defined by specific characteristics) in specific areas are to donate blood or join the military. Information from the targeted prevalence studies and representative surveys can then be used to develop estimates of the prevalence of HIV infection. Such an approach has the potential of providing estimates that are more accurate, more timely, and more consistent across jurisdictions than complete enumeration. However, there are also limitations to such approaches. For example, adequate data may not be available to produce accurate models and sampling can be both complex and expensive to implement. Many constituencies are also concerned about the confidentiality and ethics of surveillance surveys. Such a strategy should be reconsidered, with a review of the substantial technical, political, and ethical barriers to its implementation that were pointed out after the 2001 IOM report appeared.

Both modeling and survey methods can also be used to estimate cases of undiagnosed HIV infection. Although the primary reasons to have accurate surveillance of the number of persons with known HIV infection are epidemiological, the total number of people with HIV infection is relevant to assessing the size of the population that is likely to need health care services, either currently or in the future, especially if a goal is to encourage everyone to enter care. The resource requirements for treating people who are in care vary widely depending on disease stage, and other factors, such as the patient’s own health insurance status. All HIV-infected persons—even those without clinical symptoms—require some services such as patient education and monitoring as well as treatment of primary infection and associated medical conditions. Most will require extensive medical intervention in the future even if they currently do not. Therefore, information on the total number of HIV infections is impor-

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

tant. Although the RWCA now focuses on providing care to individuals who have been diagnosed, if policy shifts to include more outreach to individuals, allocation decisions will benefit from information on the total HIV-infected population.

Finding 4-8 The completeness of the data from existing HIV case-reporting systems can be improved by making changes, specifically counting all HIV cases that are reported to the national system rather than only those reported from states with name-based reporting, and more fully utilizing data from laboratories and other sources, such as pharmacies, to enhance the completeness of HIV reporting.

Finding 4-9 Techniques exist to estimate the prevalence of HIV infection independently of the HIV case-reporting systems. Sample-based surveys and modeling approaches permit estimates of the total HIV-infected population, regardless of diagnostic status.

Finding 4-10 A surveillance mechanism that provides information about the total population of persons with HIV infection, be they diagnosed or undiagnosed, is highly desirable. Knowing the size and distribution of the undiagnosed HIV-infected population is an important marker of success in providing care to all people with HIV.

RECOMMENDATIONS

The Committee’s recommendations are listed below. These recommendations should be implemented in a timely manner to provide evidence to either (1) justify inclusion of reported HIV cases in RWCA allocations formulas by FY2007, as contemplated by Congress, or (2) conclude that reported HIV cases do not result in more equitable resource allocation so that Congress can reconsider its recommendation prior to implementation in FY2007. Additional resources may be required to implement some of these recommendations.

Recommendation 4-1 For at least the next four years, HRSA should continue to use ELCs in the RWCA Title I and II formulas. During that period, concerted effort should be devoted to improving the consistency, quality, and comparability of HIV case reporting. Specific attention should be paid to two, complementary approaches in this regard: (1) the attainment of coverage, maturity, and comparability standards and the development of de-duplication strategies that permit full use of all reported HIV cases; and (2) implementation of alternative strategies for estimating HIV cases, such as survey- or model-based estimation.

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
×

Recommendation 4-2 The following steps should be taken by states as quickly as possible to improve the consistency, quality, and comparability of HIV case reporting for RWCA allocation purposes.

  1. The CDC should accept reported HIV cases from all states. Until this occurs, large numbers of HIV cases will not be included in the national HIV reporting system, and there will be no reliable centralized way to use reported HIV cases to apportion CARE Act funds. CDC should work with all states to develop and evaluate methods for unduplicating HIV cases regardless of whether such cases are code- or name-based. The Secretary should provide CDC with the funding to provide the technical assistance to states necessary to support the integration of code with name-based data into the national HIV reporting database. Because of the importance of obtaining consistent data from all jurisdictions, CDC should include HIV reporting data from code-based states and estimate the degree of overcounting due to duplication while procedures and infrastructure for definitive unduplication are developed.

  2. CDC should collaborate with all states to periodically assess and compare the completeness and timeliness of their HIV reporting systems.

  3. The Secretary of HHS should provide additional funds to CDC to assist states in improving the completeness and timeliness and overall comparability of their HIV reporting systems. Enhancing electronic laboratory reporting in all states is critical in achieving this goal. Pharmacy-based surveillance, with a focus on the AIDS Drug Assistance Program (ADAP), is another potential source of information for enhancing completeness.

Recommendation 4-3 CDC should obtain estimates of total HIV prevalence (including the undiagnosed population) and evaluate methods other than case reporting for use as an alternative or supplement in estimating HIV cases for RWCA Title I and II formula allocations, with advice and review by an independent body. This assessment should address the accuracy and costs of different strategies and should be repeated periodically.

Recommendation 4-4 Prior to future reauthorizations of the CARE Act, the Secretary of HSS should initiate studies to improve the evidence base for understanding how well HIV case reporting and other methods for estimating HIV cases reflect the relative burden of disease and the relative resources necessary to respond to those needs in different areas. The Secretary should engage an independent body to

Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
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estimate the dollar allocations that would result for Title I and II grantees from alternative input data and alternative RWCA allocation formulas. Specifically:

  1. “What-if” assessments should be reported every five years on the range of each EMA’s and state’s RWCA formula allocation, depending on whether ELCs or total HIV cases are used as the measure of disease burden.

  2. Analyses should be conducted to estimate the dollar allocations that would result from modifying different structural elements of the formula, such as:

    • Hold-harmless provisions,

    • The eligibility requirements for becoming an EMA,

    • The percentage set-aside in the Title II base award for non-EMA states (currently 20 percent),

    • The minimum base Title II award (now $500,000 for states and $50,000 for territories),

    • The eligibility criteria for becoming a Tier 1 and Tier 2 Emerging Community.

  1. Evaluate the extent of interregional variability in HIV epidemic maturity and its effect on relative resource needs.

These activities should be repeated periodically.

Recommendation 4-5 In keeping with the CARE Act’s intent as a payer of last resort, Congress should reevaluate the RWCA formulas to determine whether they allocate resources in proportion to the estimated number of individuals with HIV/AIDS who are uninsured or underinsured in states and EMAs. Readily available data on the insurance coverage of the general population may mirror insurance coverage of people with HIV/AIDS, but additional estimation will likely be required.

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×

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Suggested Citation:"4 HIV Reporting Data and Title I and II Formulas." Institute of Medicine. 2004. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press. doi: 10.17226/10855.
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The Ryan White Comprehensive AIDS Resources Emergency (CARE) Act gives funding to cities, states, and other public and private entities to provide care and support services to individuals with HIV and AIDS who have low-incomes and little or no insurance. The CARE Act is a discretionary program that relies on annual appropriations from Congress to provide care for low-income, uninsured, or underinsured individuals who have no other resources to pay for care. Despite its successes, funding has been insufficient to address all of the inequalities and gaps in coverage for people with HIV.

In response to a congressional mandate, an Institute of Medicine committee was formed to reevaluate whether CARE allocation strategies are an equitable and efficient way of distributing resources to jurisdictions with the greatest needs and to assess whether quality of care can be refined and expanded. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act proposes several types of analyses that could be used to guide the evaluation and improvement of allocation formulas, as well as a framework for assessing quality of care provided to HIV-infected persons.

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