Hospitalization Rates Among People With HIV/AIDS in New York City, 2013

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1 Clinical Infectious Diseases MAJOR ARTICLE Hospitalization Rates Among People With HIV/AIDS in New York City, 2013 Rachael Lazar, 1,2 Laura Kersanske, 1 Qiang Xia, 1 Demetre Daskalakis, 1 and Sarah L. Braunstein 1 1 New York City Department of Health and Mental Hygiene, New York; and 2 Centers for Disease Control and Prevention/Council of State and Territorial Epidemiologists Applied Epidemiology Fellowship, Atlanta, Georgia Background. Hospitalizations are an important indicator of healthcare quality and access for people with human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS). This study assesses hospitalization rates among people with HIV/AIDS in New York City. Methods. We performed a deterministic match between people in the New York City HIV surveillance registry alive as of 1 January 2013 and diagnosed with HIV as of 31 December 2013 and patient-level inpatient hospitalization records during Event-level data were analyzed to determine characteristics of and reasons for hospitalizations. Primary diagnoses were classified using the International Classification of Diseases, Ninth Revision, Clinical Modification. We estimated hospitalization rates as the number of hospitalizations per 100 person-years for all causes, AIDS-defining illnesses, and non-aids-defining infections. Results. Nearly one-fifth of hospitalizations were attributed to non AIDS-defining infections, whereas AIDS-defining illness diagnoses were infrequent (3.6% of hospitalizations). Other common causes were cardiovascular (10.9%) and substance use (9.8%). The estimated all-cause hospitalization rate was 36.7 per 100 person-years. Higher all-cause hospitalization rates were observed among females (46.8 per 100 person-years), Black and Latino/Hispanic people (41.8 and 39.5 per 100 person-years, respectively), people living in high-poverty neighborhoods (47.4 per 100 person-years), and people with a history of injection drug use (74.9 per 100 person-years). The estimated AIDS-defining illness and non AIDS-defining infection hospitalization rates were 1.3 and 7.2 per 100 person-years, respectively. Conclusions. People with HIV in New York City were frequently hospitalized. While AIDS-defining illnesses were relatively rare, non AIDS-defining infection hospitalizations were more common. Disparities in hospitalization rates indicate a need for targeted improved primary care and comorbid disease management. Keywords. HIV; hospitalization; epidemiology; International Classification of Diseases. Antiretroviral therapy (ART) is effective in reducing morbidity and mortality attributed to human immunodeficiency virus (HIV) infection for people with HIV/acquired immune deficiency syndrome (AIDS) (PWHA) [1, 2]. Nationally and locally, there is a strong focus on the benefits of retaining PWHA in HIV care, initiating and maintaining ART, achieving viral load suppression, and managing potential or existing comorbid diseases [3, 4]. New York City (NYC) has a large population of PWHA [5], and it has become increasingly important to monitor HIV care outcomes and comorbidities as this population ages; as of 2014, approximately half of PWHA in NYC were aged 50 or older [6]. Tracking hospitalizations among PWHA can provide valuable insight into their healthcare utilization patterns, the accessibility of health services, and the quality of HIV care. PWHA may be Received 7 December 2016; editorial decision 29 March 2017; accepted 20 April 2017; published online April 24, Correspondence: R. Lazar, HIV Epidemiology and Field Services Program, New York City Department of Health and Mental Hygiene, th St, Long Island City, NY (rlazar@ health.nyc.gov). Clinical Infectious Diseases 2017;65(3): The Author Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, journals.permissions@oup.com. DOI: /cid/cix343 hospitalized because of poorly managed HIV infection, onset of or complications related to comorbid diseases, or lack of adequate access to high-quality outpatient HIV primary care [7]. Recent studies of hospitalizations among PWHA have been limited to emergency department settings [8, 9], conducted among those in medical care [10 13], or reliant on the hospital record to contain HIV diagnosis codes to identify hospitalizations among PWHA [14, 15]. We sought to quantify and describe inpatient hospitalizations among NYC PWHA by matching 2 population-based data sources, New York inpatient hospital discharge records and the NYC HIV surveillance registry. The primary objectives of this study were to estimate hospitalization rates among NYC PWHA and characterize disparities in hospital admissions. We calculated all-cause hospitalization rates as well as rates specific to AIDS-defining illnesses (ADI) and non AIDS-defining infections to highlight conditions most likely to be affected by HIV-positive status. METHODS Data Sources To identify the population of PWHA hospitalized in New York City, we performed a deterministic match between the Hospitalizations Among People With HIV CID 2017:65 (1 August) 469

2 NYC Department of Health and Mental Hygiene s HIV surveillance registry and inpatient hospitalization records from New York s Statewide Planning and Research Cooperative System (SPARCS) database. The registry contains information on all people with HIV/AIDS ever diagnosed with HIV (since 2001) or AIDS (since 1981) in NYC. Eligible patients for the match included individuals living as of January 1, 2013, and diagnosed with HIV as of December 31, The SPARCS database, established in 1979, includes medical record data for all inpatient hospitalizations at New York state facilities [16]. All hospitalizations with an admission or discharge date in 2013 for inpatient facilities located in NYC were included in the match, regardless of whether the hospital record contained an indication of HIV infection. Input data sets for the match included people diagnosed with HIV and presumed to be living in NYC from the registry and people hospitalized in an NYC facility in 2013 from the SPARCS database. Matching Process The SPARCS data set was de-duplicated at the individual patient level using a unique identifier and date of birth for the purpose of matching. Sixteen match keys were created from the patientlevel registry and SPARCS data set using combinations of 9 identifying elements: first 2 letters of first name, first 2 letters of last name, last 2 letters of last name, birth year, birth month, birth day, last 4 digits of social security number, sex, and patient residential ZIP code. The SPARCS data set was then matched to the registry data set by merging the datasets on each of the 16 keys using SAS version 9.2 (SAS Institute, Cary, NC). The match was hierarchical; patient records matching on Key 1 were considered true matches and removed from both input data sets, and nonmatching records were then evaluated on Key 2, and so forth, for all 16 keys. Manual match review was conducted in the following situations: when multiple SPARCS patients matched to a single patient in the registry (N = 433 individuals in the registry matched to multiple SPARCS records); when fewer than 6 of the 9 identifying elements matched (N = 83 matched pairs); when potential matches involved a person who had no CD4 count or HIV viral load test reported to the registry since 2005, suggesting this person may no longer reside or receive care in NYC and could therefore be falsely matched (N = 267 matched pairs); and when a patient was flagged as HIV-infected in the SPARCS data set based on an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) HIV diagnosis code but did not match to the registry on any of the 16 keys (N = 1287 SPARCS records). Analytic Variables Characteristics of hospitalization were obtained from the SPARCS data set and included type of admission, service type, length of stay, and primary diagnosis. SPARCS records contain between 2 and 26 ICD-9 diagnosis codes for each hospitalization: an admitting diagnosis, a principal diagnosis, and up to 24 other diagnoses listed sequentially. Primary diagnosis was assigned as the first non-hiv diagnosis code (HIV codes were 042, V08, , and ), an approach used previously to determine hospitalization causes among PWHA [17, 18]. Primary diagnoses were grouped into 14 mutually exclusive categories: AIDS-defining illnesses (ADI); non AIDS-defining infections; non AIDS-defining cancers; cardiovascular; gastrointestinal, or hepatic; pulmonary; endocrine or metabolic; renal or genitourinary; neurological; psychiatric; substance use; injury or poisoning; pregnancy and newborn; and all other causes. Hospitalizations in which the only recorded code was for HIV (N = 8) were assigned as missing primary diagnosis. Hospitalizations with a primary diagnosis of chemotherapy treatment (codes V58.11 or V58.12, N = 252) had their first cancer diagnosis assigned as the primary diagnosis. The ADI category included all opportunistic illnesses listed in the 1993 CDC AIDS case definition [19]. We defined recurrent bacterial pneumonia as any primary diagnosis of bacterial pneumonia occurring after an initial hospitalization with a primary diagnosis of bacterial pneumonia during the study period. Primary diagnoses of non-recurrent bacterial pneumonia (excluding Pneumocystis jirovecii), sepsis, and cellulitis were classified as non AIDS-defining infections. Substance use diagnoses included rehabilitation, withdrawal, overdose, and poisoning due to alcohol or nonprescription drugs. Demographic variables including sex at birth, race/ethnicity, age, area-based poverty level (based on the percent of residents in a given ZIP code with income below the federal poverty level), HIV transmission risk, and year of HIV diagnosis were taken from the registry. Time-varying covariates including age and area-based poverty level were fixed at the start of the study period. CD4 cell count prior to hospitalization was obtained from the registry and defined as the latest CD4 count drawn during 2012, representing patients clinical status at the start of the study period. CD4 counts for hospitalized PWHA diagnosed with HIV as of December 31, 2012, were categorized as follows: less than 200 cells/µl, cells/µl, 500 cells/µl or greater, and unavailable (for those with no CD4 count test performed in NYC in 2012). Statistical Analysis We used a retrospective open cohort study design. For all patients diagnosed with HIV prior to 2013, the start of the study period was January 1, 2013; for all patients diagnosed with HIV during 2013, the start of the study period was their HIV diagnosis date. Hospitalization rates were calculated as the number of hospitalizations per 100 person-years (PY). Hospitalizations occurring prior to the patient s HIV diagnosis were excluded from rate calculations. Patients newly diagnosed with HIV at hospitalization, defined as diagnosis date on hospital admission date 470 CID 2017:65 (1 August) Lazar et al

3 or between admission and discharge dates, were also excluded, as these patients would not contribute any person-time to the denominator. An individual patient could contribute multiple hospitalizations during the study period. Rate denominators represent PY among PWHA in New York City in To obtain an accurate measure of person-time for PWHA eligible for hospitalization during the year, we estimated the number of PWHA using a previously established statistical weighting method developed in NYC that aims to account for out-migration [20, 21]. For people living through December 31, 2013, person-time was calculated as either the full year (for those diagnosed with HIV prior to 2013) or the time from HIV diagnosis date until December 31, 2013 (for those diagnosed during 2013). For people who died during 2013, person-time was calculated as the time from January 1, 2013, until the date of death (for those diagnosed with HIV prior to 2013) or the time from HIV diagnosis date until the date of death (for those diagnosed during 2013). Crude rate ratios and 95% confidence intervals were calculated using Poisson regression models. Statistical analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC). RESULTS The matched data set included PWHA and hospitalization events, and the final analytic sample after exclusions included PWHA and hospitalization events (Figure 1). The median number of hospitalizations per patient was one (interquartile range [IQR]: 1 2). Most admissions (88.3%) originated in the emergency department (Table 1). About half (49.0%) of hospitalizations primarily involved medical services, 33.9% surgical services, and 15.1% psychiatric services. The majority of hospitalizations (65.1%) had a duration of less than 1 week, with discharge on the day of admission or the day after for 16.1%. The median length of stay was 5 days (IQR: 3 8). An HIV ICD-9 code was assigned as any one of the 26 possible diagnoses for (84.5%) hospitalizations. Among hospitalization events, 1068 (3.6%) were assigned an ADI as the primary diagnosis. Top specific ADI diagnoses were Pneumocystis jirovecii pneumonia (0.9%), recurrent bacterial pneumonia (0.5%), and candidal esophagitis (0.4%). The most common primary diagnosis categories were non AIDS-defining infections (19.6%), cardiovascular (10.9%), substance use (9.8%), and gastrointestinal or hepatic (8.8%). Among non AIDS-defining infections, frequently occurring diagnoses were bacterial pneumonia due to unspecified organism (3.8%), septicemia (3.3%), and cellulitis (1.2%). A greater proportion of primary diagnoses among males compared with females were categorized as cardiovascular (11.6% vs 9.7%) and substance use (12.3% vs 5.5%). An estimated PWHA contributed PY to the rate analysis, yielding an all-cause hospitalization rate of 36.7 hospitalizations per 100 PY (Table 2). Hospitalization rates were highest among females (46.8 per 100 PY), black and Latino/Hispanics (41.8 and 39.5 per 100 PY, respectively), people living in very high poverty neighborhoods (47.4 per 100 PY), and people with a history of injection drug use (IDU) (74.9 per 100 PY), including men who have sex with men (MSM) with a history of IDU (MSM-IDU, 65.8 per 100 PY). Rates were lowest among Asian/Pacific Islanders (16.2 per 100 PY), people living in low-poverty neighborhoods (24.6 per 100 PY), and MSM (20.0 per 100 PY). Hospitalization rates increased with both age and time since HIV diagnosis. The overall ADI hospitalization rate was 1.3 per 100 PY. Females, black and Latino/Hispanics, and those in higher poverty neighborhoods experienced disproportionately high rates of ADI hospitalizations. IDU had particularly high ADI hospitalization rates (2.2 per 100 PY for both IDU and MSM-IDU); additionally, people with perinatal transmission risk had a high ADI hospitalization rate (3.0 per 100 PY). The overall non AIDS-defining Figure 1. NYC HIV surveillance registry and SPARCS data set match process. Abbreviations: HIV, human immunodeficiency virus; NYC, New York City; PWHA, people with HIV/AIDS; SPARCS, Statewide Planning and Research Cooperative System. Hospitalizations Among People With HIV CID 2017:65 (1 August) 471

4 Table 1. Characteristics of Inpatient Hospitalizations Among People With HIV/AIDS, NYC 2013 Total Among Males Among Females N % N % N % Total Type of admission Emergency Elective Other a Service type Medical Surgical Psychiatric Other b Length of stay (days) or more Primary diagnosis Non AIDS-defining infections Cardiovascular Substance use c Gastrointestinal or hepatic Pulmonary Psychiatric Injury and poisoning Endocrine or metabolic Renal or genitourinary Non AIDS-defining cancers AIDS-defining illness Neurological Pregnancy and newborn All other causes Abbreviations: HIV, human immunodeficiency virus; NYC, New York City. a Includes urgent, trauma, newborn, and unavailable. b Includes obstetrical, pediatric, and nursery/newborn. c Includes rehabilitation, withdrawal, overdose, and poisoning due to alcohol or non-prescription drugs. infections hospitalization rate was 7.2 per 100 PY. The demographic distribution of these rates closely corresponded to that of all-cause hospitalization rates, with the exception that the non AIDS-defining infection hospitalization rate was higher among Latino/Hispanic compared with black PWHA. Among hospitalized PWHA diagnosed with HIV prior to 2013, (87.0%) had a CD4 count performed and reported in NYC during Of those with a documented CD4 count, 77.6% had a CD4 count above 200 cells/µl and 39.6% had a CD4 count 500 cells/µl or greater (Figure 2). With increases in prehospitalization CD4 count, PWHA were less likely to have experienced an ADI hospitalization in 2013; among those with a CD4 count less than 200 cells/µl, 14% had at least 1 ADI hospitalization, whereas only 3% and 1% of those with CD4 counts of cells/µl and 500 cells/µl or greater, respectively, had an ADI hospitalization in DISCUSSION We found high hospitalization rates among PWHA in New York City. The rates presented here are higher than those previously published; a recent study estimated the hospitalization rate for PWHA nationally as 26.6 per 100 population in 2009 [15]. However, we were able to assign hospitalizations to patients without any HIV ICD-9 code assigned (N = 4573 hospitalizations in our population), whereas the previous study relied on these codes to identify hospitalizations among PWHA. Furthermore, we calculated censored person-time using revised counts of PWHA that account for out-migration, reducing the population denominators to include only those we believe were living in and therefore eligible for hospitalization in NYC. To our knowledge, other studies calculating hospitalization rates have not made a similar adjustment to their PWHA denominator estimates. 472 CID 2017:65 (1 August) Lazar et al

5 Table 2. All-Cause, AIDS-Defining Illness, and Non AIDS-Defining Infections Inpatient Hospitalizations and Crude Rates Among People With HIV/AIDS, NYC 2013 Person-years of Follow All-cause up a Hospitalizations Rate per 100 Person-Years Rate Ratio (95% CI) AIDS-Defining Illness Hospitalizations Rate per 100 Person-Years Rate Ratio (95% CI) Non AIDS- Defining Infections Hospitalizations Rate per 100 Person-Years Rate Ratio (95% CI) Total Sex at birth Male Female (1.41, 1.47) (1.43, 1.83) (1.38, 1.53) Race/Ethnicity Black Latino/Hispanic (0.92, 0.97) (0.73, 0.95) (1.04, 1.17) White (0.50, 0.54) (0.34, 0.51) (0.51, 0.60) Asian/Pacific Islander (0.34, 0.44) (0.44, 1.14) (0.29, 0.52) Other b (0.52, 0.75) (0.13, 1.22) (0.31, 0.78) Age c (1.21, 1.65) (1.01, 4.25) (0.88, 1.56) (1.32, 1.79) (0.98, 4.05) (0.88, 1.60) (1.82, 2.46) (0.91, 3.71) (1.18, 2.13) (2.26, 3.05) (0.82, 3.33) (1.37, 2.45) (2.50, 3.39) (0.57, 2.43) (1.61, 2.90) Area-based poverty level c Low poverty (<10% below FPL) Medium poverty (10 to <20% below FPL) High poverty (20 to <30% below FPL) Very high poverty ( 30% below FPL) Area-based poverty level not available (1.27, 1.42) (1.51, 2.81) (1.11, 1.39) (1.46, 1.60) (1.89, 3.44) (1.40, 1.73) (1.84, 2.02) (1.96, 3.57) (1.71, 2.11) (0.69, 0.81) (0.92, 2.07) (0.63, 0.89) HIV transmission risk MSM IDU history (3.62, 3.87) (2.37, 3.40) (3.27, 3.78) MSM-IDU (3.10, 3.49) (1.97, 3.79) (2.28, 3.03) Heterosexual (1.91, 2.04) (1.64, 2.33) (1.53, 1.79) Perinatal (1.58, 1.88) (2.79, 5.11) (1.74, 2.43) Other d (2.40, 3.64) (0.79, 7.71) (1.68, 4.26) Unknown (1.80, 1.93) (1.33, 1.92) (1.39, 1.62) Year of HIV diagnosis (1.13, 1.24) (0.68, 1.03) (1.07, 1.32) Hospitalizations Among People With HIV CID 2017:65 (1 August) 473

6 Table 2. Continued Rate per 100 Person-Years Rate Ratio (95% CI) Non AIDS- Defining Infections Hospitalizations Rate Ratio (95% CI) Rate per 100 Person-Years AIDS-Defining Illness Hospitalizations Rate per 100 Person-Years Rate Ratio (95% CI) Person-years of Follow All-cause up a Hospitalizations (1.41, 1.53) (0.77, 1.13) (1.35, 1.63) (1.70, 1.85) (0.93, 1.38) (1.75, 2.13) (2.05, 2.24) (1.10, 1.69) (2.27, 2.78) (2.13, 2.40) (0.78, 1.52) (2.25, 2.93) 1983 and prior (2.32, 3.49) (0.28, 4.50) (1.70, 4.46) Rate ratios and 95% confidence intervals calculated using Poisson regression models. Abbreviations: CI, confidence interval; FPL, federal poverty level; HIV, human immunodeficiency virus; IDU, injection drug use; MSM, men who have sex with men; NYC, New York City. a Person-years are rounded to nearest whole number. b Other race/ethnicity includes Native American, multiracial, and unknown. c Age and area-based poverty level are based on most recent information available at the start of the study period (for those diagnosed with HIV prior to 2013, information as of January 1, 2013; for those diagnosed with HIV during 2013, information at HIV diagnosis). d Other HIV transmission risk includes hemophilia, receipt of transfusions or transplants, and non-perinatal risk in pediatric cases (<13 years). Figure 2. CD4 count 1 prior to hospitalization among people hospitalized in 2013 and diagnosed with HIV/AIDS in 2012 or earlier 2, NYC. Abbreviations: HIV, human immunodeficiency virus; NYC, New York City; PWHA, people with HIV/AIDS. 1 CD4 count represents most recent non-missing value collected between January 1, 2012 and December 31, Excludes 299 people both hospitalized and diagnosed with HIV/AIDS in Patients with at least 1 hospitalization in 2013 with a primary diagnosis of an AIDS-defining illness. Reasons for hospitalization among NYC PWHA varied widely. Non AIDS-defining infections were the most common causes of hospitalization, a result that has been reported in previous studies of hospitalizations among non population-based cohorts of PWHA [11, 17]. Consistent ART use can reduce the risk of certain infections, such as bacterial pneumonia [22]; the high frequency of non AIDS-defining infections may point to a need for better clinical management of HIV and improved ART use and adherence. Cardiovascular conditions were also common. A study conducted in NYC demonstrated that many PWHA have elevated cardiovascular disease risk, particularly due to larger waist circumference and cigarette smoking [23]. Data were not available to evaluate these factors in our study population, though there is evidence that NYC PWHA have high rates of cigarette smoking compared with the general population [6]. The finding that many diagnoses were substance use-related, particularly among males, is supported by reports of high rates of alcohol and other drug use among PWHA [24, 25]. People with a history of IDU, including MSM-IDU, had the highest all-cause and non AIDS-defining infection hospitalization rates of the analyzed demographic subpopulations. IDU experience elevated risk of soft tissue injury, infection, and comorbid diseases such as hepatitis C virus infection [26]. The hospitalization rate among IDU may also be high due to inpatient stays for drug or alcohol dependence or rehabilitation, which are included as hospitalizations in the SPARCS database. ADI hospitalization rates were also high among IDU, relative to other subpopulations; this aligns with recent HIV care outcomes in NYC, which are poorer among IDU compared with other PWHA [6]. Despite local efforts to improve access to high-quality HIV care and services for all PWHA to prevent morbidity, there were disparities in hospitalization rates by sex, race/ethnicity, and area-based poverty. We observed high hospitalization rates 474 CID 2017:65 (1 August) Lazar et al

7 for all causes, ADI, and non AIDS-defining infections among black and Latino/Hispanic PWHA and PWHA living in higher poverty neighborhoods. Other studies have documented similar disparities in hospitalization among PWHA [14, 27], though recent national hospitalization rates were lower for Latino/ Hispanic compared with white PWHA [15]. Higher hospitalization rates among female PWHA have also been observed in previous studies, even after accounting for pregnancyrelated hospitalizations [10, 14, 15]. Our results parallel recently published age-adjusted death rates for NYC PWHA, in which rates among females, blacks and Latino/Hispanics, IDU and MSM-IDU, and people living in high-poverty neighborhoods are greater than those citywide [28]. Given that these PWHA subpopulations experience worse outcomes, special focus must be given to optimizing their outpatient HIV primary care and improving prevention and treatment for comorbid diseases and exposures, such as tobacco and alcohol. Although the majority of hospitalized PWHA had CD4 counts 200 cells/µl or greater prior to hospitalization, PWHA with CD4 counts less than 200 cells/µl were more likely to be hospitalized for an ADI. This pattern aligns with the established CD4 count criteria for AIDS diagnosis and underscores the well-established clinical benefits of early HIV diagnosis and ART initiation to maintain CD4 counts and prevent progression to AIDS [19, 29, 30]. A main strength of this analysis is its use of 2 population-based data sources; the results represent all inpatient hospitalizations during the year among NYC PWHA. Furthermore, using a matched data set allowed us to capture PWHA admissions not assigned HIV ICD-9 codes and to assign multiple hospitalizations to individuals. We calculated person-time using revised, more accurate estimates of NYC PWHA and complete data on HIV diagnosis and death dates. Finally, use of the registry allowed us to examine risk factors not typically documented in hospital records, such as year of HIV diagnosis, HIV transmission risk factor, and area-based poverty, a measure of socioeconomic status. This study has several limitations. Although the registry contains full patient names, the full name could not be used as the primary identifier for the match because SPARCS data only contain partial names. This may have resulted in undermatching and an underestimate of hospitalization rates among PWHA. The match also excluded patients who received HIV care in NYC but were hospitalized at a facility outside of NYC. Due to the nature of the weighting estimation method used to calculate person-time, we were unable to use models with generalized estimating equations to account for individual patients being hospitalized more than once, which may have affected the confidence limits presented. However, the median number of hospitalizations per patient was 1, and our hospitalized sample was large, which should minimize the impact of within-person correlation. Primary diagnosis ICD-9 codes, while the best available proxy for reason for hospitalization, are primarily intended for insurance purposes and may not reflect the full spectrum of clinical complaints or diagnoses a patient experienced during the hospitalization. Finally, these results do not include people with undiagnosed HIV infection, though the estimated proportion of people with undiagnosed HIV infection in NYC is low [5]. Our study demonstrates that while hospitalizations for ADI are relatively rare, PWHA are frequently admitted to hospitals for inpatient care. HIV infection can increase susceptibility to or exacerbate non-adi conditions, particularly infections, which accounted for nearly one-fifth of all hospitalizations. We observed notable disparities in hospitalization rates, with PWHA of color, IDUs, and those living in high-poverty neighborhoods more likely to be hospitalized for all causes as well as for ADI and non AIDS-defining infections. Efforts to improve the outpatient management of PWHA are critical in preventing hospitalizations. Although viral suppression and maintenance of CD4 counts are central to HIV care, many hospitalizations were among PWHA with high CD4 counts; holistic primary care requires management of HIV-related medical issues and other comorbid medical, psychiatric, and substance-related conditions as well as risk factors such as tobacco use. Despite significant strides in preventing hospitalization among PWHA, further improvements in outpatient care and access may reduce utilization of inpatient services. Notes Financial support. This work was supported in part by an appointment to the Council of State and Territorial Epidemiologists (CSTE) Applied Epidemiology Fellowship Program administered by CSTE and funded by the Centers for Disease Control and Prevention Cooperative Agreement number 1U38OT Potential conflict of interest. L. K.: no conflict. Q. X.: no conflict. D. D.: no conflict. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. References 1. Palella FJ Jr, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV outpatient study investigators. N Engl J Med 1998; 338: Volberding PA, Deeks SG. Antiretroviral therapy and management of HIV infection. Lancet 2010; 376: White House Office of National AIDS Policy. 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