Skip to main content
Download PDF

Disparities of Care for African-Americans and Caucasians with Community-Acquired Pneumonia: A Retrospective Cohort Study

BMC Health Services Research volume 10, Article number: 143 (2010) Cite this article

Abstract

Background

African-Americans admitted to U.S. hospitals with community-acquired pneumonia (CAP) are more likely than Caucasians to experience prolonged hospital length of stay (LOS), possibly due to either differential treatment decisions or patient characteristics.

Methods

We assessed associations between race and outcomes (Intensive Care Unit [ICU] variables, LOS, 30-day mortality) for African-American or Caucasian patients over 65 years hospitalized in the Veterans Health Administration (VHA) with CAP (2002-2007). Patients admitted to the ICU were analyzed separately from those not admitted to the ICU. VHA patients who died within 30 days of discharge were excluded from all LOS analyses. We used chi-square and Fisher's exact statistics to compare dichotomous variables, the Wilcoxon Rank Sum test to compare age by race, and Cox Proportional Hazards Regression to analyze hospital LOS. We used separate generalized linear mixed-effect models, with admitting hospital as a random effect, to examine associations between patient race and the receipt of guideline-concordant antibiotics, ICU admission, use of mechanical ventilation, use of vasopressors, LOS, and 30-day mortality. We defined statistical significance as a two-tailed p ≤ 0.0001.

Results

Of 40,878 patients, African-Americans (n = 4,936) were less likely to be married and more likely to have a substance use disorder, neoplastic disease, renal disease, or diabetes compared to Caucasians. African-Americans and Caucasians were equally likely to receive guideline-concordant antibiotics (92% versus 93%, adjusted OR = 0.99; 95% CI = 0.81 to 1.20) and experienced similar 30-day mortality when treated in medical wards (adjusted OR = 0.98; 95% CI = 0.87 to 1.10). African-Americans had a shorter adjusted hospital LOS (adjusted HR = 0.95; 95% CI = 0.92 to 0.98). When admitted to the ICU, African Americans were as likely as Caucasians to receive guideline-concordant antibiotics (76% versus 78%, adjusted OR = 0.99; 95% CI = 0.81 to 1.20), but experienced lower 30-day mortality (adjusted OR = 0.82; 95% CI = 0.68 to 0.99) and shorter hospital LOS (adjusted HR = 0.84; 95% CI = 0.76 to 0.93).

Conclusions

Elderly African-American CAP patients experienced a survival advantage (i.e., lower 30-day mortality) in the ICU compared to Caucasians and shorter hospital LOS in both medical wards and ICUs, after adjusting for numerous baseline differences in patient characteristics. There were no racial differences in receipt of guideline-concordant antibiotic therapies.

Peer Review reports

Background

Prior studies have documented health disparities between African-Americans and Caucasians who present to U.S. hospitals with common infectious diseases [1–4]. Health policies, research initiatives, and targeted educational campaigns have sought to bridge this quality chasm [5–7].

In the treatment of community-acquired pneumonia (CAP), several initial processes of care have been associated with improved survival, including the timely delivery and appropriate selection of antibiotic therapy, and acquisition of blood cultures prior to initiating antibiotic therapy [8–11]. These processes have been recommended by professional medical societies, clinical practice guidelines, hospital accreditation commissions, and federal agencies [12]; however, whether such processes of care are performed in an equitable manner for patients of all races is unclear. While some studies have demonstrated African-American patients are less likely to receive timely initiation of antibiotic therapy, diagnostic bronchoscopy, smoking cessation counseling, and pneumococcal and influenza vaccinations [1, 3, 13, 14], the available evidence suggests no difference between African-Americans and Caucasians in the likelihood of receiving guideline-concordant antibiotic therapy, blood cultures, or assessment of arterial oxygenation [3, 14].

Despite the observed racial disparities in several evidence-based processes of care for CAP, most Veteran and civilian studies to date have found equal or lower adjusted mortality rates for African-Americans compared to Caucasians [15–18], with few exceptions [14]. Other evidence suggests African-Americans admitted to U.S. hospitals with CAP are more likely to experience prolonged hospital stays [13, 19]. It is unclear whether differences in processes of care, hospital length of stay (LOS) and mortality are independently associated with race or due to differences in baseline patient characteristics that vary by race.

The Veterans Health Administration (VHA), the largest vertically integrated healthcare system in the United States, has been at the forefront of a national quality movement to provide high quality and equitable healthcare for all VHA patients. Therefore, we sought to determine whether there were racial differences in processes of care, hospital LOS, or 30-day mortality for African-American and Caucasian VHA patients with CAP, after adjusting for baseline differences in patient characteristics.

Methods

This retrospective, cohort study of hospitalized patients with CAP is a secondary analysis of data collected as part of a project to assess the association of treatment with statins on clinical outcomes (e.g., mortality) of patients hospitalized with CAP and/or sepsis in the Department of Veterans Affairs Health Care System (National Institutes of Health/National Institute of Nursing Research Grant Number R01NR010828). We used administrative data from the VHA to examine trends in pneumonia care and mortality. The VHA databases are repositories of clinical data from more than 150 VHA hospitals and 850 VHA clinics [20]. The Institutional Review Board of the University of Texas Health Science Center at San Antonio and the South Texas Veterans Health Care System Research and Development committee approved this study.

Patient Eligibility

We included VHA patients 65 years and older with a diagnosis of pneumonia in fiscal years 2002-2007. We used previously validated ICD-9 codes (480.0-483.99 or 485-487) for pneumonia to identify potential cases [21]. We excluded patients with a history of HIV/AIDS because these patients might be immunocompromised. We excluded those patients admitted to the hospital or a nursing home within 90 days prior to the CAP admission because these would be considered to be health care associated cases. In addition, we excluded those without antibiotic therapy within 48 hours of admission because these might have had hospital acquired pneumonia. Finally, we excluded those patients with non-veteran status or of races other than African-American or Caucasian.

Baseline Characteristics

We recorded the patient's age, sex, and marital status (married versus unmarried) at the time of admission. We used VHA Priority Group (PG) as a surrogate for socioeconomic status and disease severity, a previously validated approach [22–24]. Priority Group is used within the VHA to determine a Veteran's eligibility for health benefits and exemption from copayments for pharmacy and health care. When assigning the Veterans to these Priority Groups, the VHA takes into consideration the veteran's physical and mental health status, service history (e.g., Prisoner of War or Purple Heart recipient), and how related the Veteran's illness is to their military service (i.e., "service-connected" disability). Priority Group 1 veterans are exempt from all copayments; Priority Group 5 veterans are eligible for care based on their low income. VHA Priority Group 5 is specifically related to very low income, but a veteran with a higher priority (lower PG, i.e., 1-4) could also be low income. In fact, this is often the case. Priority Group 1 veterans are 50%-100% disabled by a service-connected condition, and thus may be unable to earn a good living (if physically disabled) or form supportive social contacts (if psychiatrically disabled). Catastrophic disablement (PG 4) is independently associated with low income in the U.S. veteran population.

We defined 19 comorbid illnesses using ICD-9 codes in accordance with the Charlson comorbidity scoring system [25], using ICD-9 codes from prior outpatient and inpatient care [26]. We defined alcohol abuse or dependence (ICD-9 codes 291, 303, and 305.0) and drug abuse or dependence (codes 292, 304, 305.2, and 305.9) [27]. Because lung disease is correlated with smoking status, we incorporated several approaches to a smoking indicator, based on prior research with VHA data [28]. Smoking status recorded in the electronic medical record is not included in administrative data extracts, therefore we created an indicator that was true whenever any of the following was found: (a) diagnosis of nicotine dependence (ICD-9 codes 305.1, V15.82), (b) outpatient prescription for smoking cessation products (Zyban, Chantix, varenicline, Nicotrol, nicotine replacement), (c) outpatient visit to smoking cessation clinic, (d) CPT treatment code for smoking cessation (99406, 99407). This measure is expected to undercount patients with a smoking history. VHA enrollees smoke more than the US population per age- and sex-adjusted rates [29], but smoking rates also drop with age and deteriorating health. We also defined organ failure (single or multiple) and sepsis based upon the presence of one or more previously established ICD-9 codes for these conditions [6, 7].

Missing data on VHA measures of health services utilization is rare in the administrative data extracts of the electronic medical record system. However, while VHA race data have been validated especially for Caucasian and African-American patients, [30, 31] missing data on race/ethnicity is a persistent problem. In VHA databases through 2002 (inpatient data) or 2003 (outpatient data), race/ethnicity was recorded by a clinical or clerical observer in inpatient records and was rarely missing, while outpatient records were characterized by higher rates of missing data. A change in policy was then effected to capture self-reported race, leading to high rates of missing data (up to 60% initially). To improve race/ethnicity data, we used all available years of data. Missing-on-race has been associated with increased survival in VHA cohorts defined by outpatient use [32], no doubt reflecting healthy users' lack of inpatient services where race was more likely to be recorded.

Antibiotic Prescribing and Other Pneumonia Processes of Care

We evaluated antibiotics received within the first 48 hours of hospital admission per joint American Thoracic Society (ATS) and Infectious Diseases Society of America (IDSA) CAP medical practice guidelines [12]. We defined the following antibiotics as guideline-concordant for medical ward patients: 1) β-lactam plus doxycycline, 2) β-lactam plus macrolide, or 3) antipneumococcal fluoroquinolone. We defined guideline-concordant for patients admitted to the intensive care unit (ICU) as: 1) β-lactam plus macrolide, 2) β-lactam plus antipneumococcal fluoroquinolone, 3) antipneumococcal fluoroquinolone plus clindamycin, 4) antipneumococcal fluoroquinolone plus vancomycin, or 5) antipneumococcal fluoroquinolone plus aminoglycoside. β-lactams included ampicillin, ampicillin-sulbactam, cefepime, cefotaxime, cefpodoxime, ceftazidime, ceftriaxone, ertapenem, imipenem-cilastatin, meropenem, piperacillin-tazobactam, and ticarcillin. Antipneumococcal fluoroquinolones included ciprofloxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, moxifloxacin, sparfloxacin, and trovafloxacin. Macrolides included azithromycin, clarithromycin, and erythromycin. Any of these guideline-concordant therapies could have had adjunctive linezolid or vancomycin. These antibiotic recommendations for ward and ICU patients have remained consistent through several versions of the guidelines, including those published by IDSA in 1998, 2003, and 2007 and those published by ATS in 1995 and 2007. Thus, no matter which version of the guidelines was followed, these patients managed between 2002 and 2007 should have received the therapies in question.

Additional processes of care included ICU admission, vasopressor use, and mechanical ventilation. We defined mechanical ventilation using ICD-9A code 96.7, recorded during an ICU stay. We defined vasopressor and inotrope use based upon the receipt of any of the following medications during the hospital stay: dobutamine, dopamine, epinephrine, isoproterenol, metaraminol, norepinephrine, phenylephrine, or vasopressin.

Length of Hospital Stay and 30-Day Mortality

We abstracted the admission and discharge dates for each stay, then defined hospital LOS as the date of discharge minus the date of admission plus one day for the overall hospitalization. The VHA vital status file provided date of death to assess 30-day mortality. The 30-day mortality metric includes those patients who died in the hospital as well as those who died outside the hospital. We chose this follow-up duration because previous research demonstrated that 30-day mortality is primarily due to underlying illness with pneumonia, whereas 90-day mortality is generally attributable to other comorbid conditions [33]. Previous research has demonstrated that this methodology has a sensitivity of approximately 98% for detecting VHA patients' deaths and is as accurate as the National Death Index [34]. In fact, National Death Index data were incorporated into the VHA's ascertainment of death [34].

Statistical analysis

We conducted all analyses using JMP 7.0, SAS 9.2 (SAS Corp., Cary, NC), and Stata 10 (StataCorp, College Station, TX). Due to the large sample size, we defined statistical significance as a two-tailed p ≤ 0.0001. Bivariate statistics (chi-square and Student's t-test) compared patient demographics, comorbid conditions, processes of care, LOS, and 30-day mortality for African-American and Caucasian patients with CAP. When assessing study endpoints, patients admitted to the ICU were analyzed separately from those not admitted to the ICU. VHA patients who died within 30 days of discharge were excluded from all LOS analyses. This was done because patients who died rapidly experienced abbreviated lengths of hospital stay. In other words, the length of stay for those very severe patients is artificially short because the patients expired before they could complete an entire episode of care. This approach (i.e., censoring those patients who died from the LOS analyses) is consistent with numerous other peer reviewed publications [35–38].

We used chi-square and Fisher's exact statistics to compare dichotomous variables, the Wilcoxon Rank Sum test to compare age by race, and Cox Proportional Hazards Regression to analyze hospital LOS. We used separate generalized linear mixed-effect models, with admitting hospital as a random effect, to examine associations between patient race and the receipt of guideline-concordant antibiotics, ICU admission, use of mechanical ventilation, use of vasopressors, hospital LOS, and 30-day mortality. Hazard ratios, odds ratios, and 95% confidence intervals were calculated from the generalized linear mixed-effects models. Covariates included all 18 variables listed in Table 1 plus a hospital-level variable. Hazard ratios were reported for hospital LOS; whereas, odds ratios were reported for everything else. For LOS, hazard ratios <1 indicate shorter lengths of stay; whereas, hazard ratios >1 indicate longer lengths of stay.

Table 1 Comparison of baseline patient characteristics for African-American and Caucasian patients admitted to VHA Hospitals with CAP (n = 40,878)*
Full size table

The 18 variables listed in Table 1 were considered a priori to be clinically important, and we included them as covariates in each of the multivariable models. The bulk of these variables were chosen because they were key components of well-validated scoring systems that predict patient mortality among pneumonia patients (e.g., age, sex, heart failure, cerebrovascular disease, liver disease, renal disease, neoplastic disease) [39, 40]. Other variables were included because we believed they might impact either patient mortality or hospital length of stay (e.g., marital status, priority group [a surrogate for socioeconomic status], chronic obstructive pulmonary disease, tobacco use, alcohol abuse or dependence, substance abuse or dependence, any organ failure, multiple organ failure, or sepsis).

Results

Overall, 4,936 African-American and 35,942 Caucasian VHA patients met all eligibility criteria (n = 40,878). The study population had a median (interquartile range) age of 78 (72-83) years; 98% were male and 53% were married. History of tobacco dependence (37%), chronic obstructive pulmonary disease (51%), diabetes (30%), heart failure (22%), neoplastic disease (21%), and cerebrovascular disease (16%) were common. One-quarter (25%) had organ failure while 4% had sepsis, and 12% were admitted to the ICU at some point during hospitalization.

Baseline Characteristics by Patient Race

As shown in Table 1, compared to Caucasians, a greater proportion of African-American VHA patients were single (57% versus 45%), had a higher prevalence of substance abuse (4% versus 3%), neoplastic disease (24% versus 20%), renal disease (16% versus 10%), and diabetes (32% versus 30%). In contrast, Caucasian VHA patients were more likely to have a history of myocardial infarction (5% versus 4%), heart failure (22% versus 19%), and chronic obstructive pulmonary disease (53% versus 39%). Socioeconomic status, as measured by priority group, also differed significantly between the two cohorts.

Antibiotic Prescribing and Intensive Care Measures by Race

Medical Wards

Among VHA patients managed in the medical wards, African-American and Caucasian patients were equally likely to receive guideline-concordant antibiotic therapy in bivariate (92% versus 93%) and multivariable (adjusted OR = 0.99; 95% CI = 0.81 to 1.20) analyses (Tables 2 and 3). Guideline-concordant antibiotic prescribing rates increased over time, from 90-91% in 2002 to 94-95% in 2007 (Figure 1). This possibly reflects greater awareness and appreciation for the benefits associated with the CAP guidelines in the ward setting.

Table 2 Antibiotic prescribing, Hospital LOS, and 30-day mortality for African-American and Caucasian VHA patients with CAP managed in the medical wards (non-ICU patients) (n = 35,706)*
Full size table
Table 3 Multivariable analyses for antibiotic prescribing, Hospital LOS, and 30-day mortality for African-American and Caucasian VHA patients with CAP managed in the medical wards (non-ICU patients) (n = 35,706)*
Full size table
Figure 1
figure 1

Annual guideline-concordant prescribing for African-American and Caucasian VHA patients with CAP managed in the medical wards (non-ICU patients)*. *The numbers in the figure represent the crude (unadjusted) guideline-concordant antibiotic prescribing rates.

Full size image

Intensive Care Units

African-American and Caucasian VHA patients experienced similar rates of admission to the ICU (12% versus 13%). Of those patients admitted to the ICU, African-American and Caucasian patients were equally likely to receive guideline-concordant antibiotic therapy in bivariate (76% versus 78%, p = 0.3) and multivariable (adjusted OR = 0.99; 95% CI = 0.81 to 1.20) analyses (Tables 4 and 5). Antibiotic prescribing rates did not differ significantly between Black and White patients admitted to the ICU. Guideline-concordant prescribing was less common in the ICU as compared to the ward, and there was no discernible increase in guideline-concordant prescribing for the latter years studied (Figure 2). This possibly reflects a lack of consensus regarding the most appropriate therapies for CAP patients admitted to the ICU. Use of vasopressors (adjusted OR = 1.27; 95% CI = 1.04 to 1.55) and mechanical ventilation (adjusted OR = 1.40; 95% CI = 1.15 to 1.70) was more common for African-Americans than Caucasians.

Table 4 Antibiotic prescribing, intensive care measures, Hospital LOS, and 30-day mortality for African-American and Caucasian VHA patients with CAP admitted to the intensive care units (ICU patients) (n = 5,172)*
Full size table
Table 5 Multivariable analyses for antibiotic prescribing, intensive care measures, Hospital LOS, and 30-day mortality for African-American and Caucasian VHA patients with CAP admitted to the intensive care units (ICU patients) (n = 5,172)*
Full size table
Figure 2
figure 2

Annual guideline-concordant prescribing for African-American and Caucasian VHA patients with CAP admitted to the intensive care units (ICU patients)*. *The numbers in the figure represent the crude (unadjusted) guideline-concordant antibiotic prescribing rates.

Full size image

30-day Mortality and Hospital Length of Stay by Patient Race

Medical Wards

African-American and Caucasian patients managed on medical wards experienced similar adjusted 30-day mortality (adjusted OR = 0.98; 95% CI = 0.87 to 1.10). African-American patients had a shorter adjusted hospital LOS (adjusted HR = 0.95; 95% CI = 0.92 to 0.98) (Tables 2 and 3).

Intensive Care Units

African-American patients admitted to the VHA ICUs experienced lesser adjusted 30-day mortality (adjusted OR = 0.82; 95% CI = 0.68 to 0.99) and shorter adjusted hospital LOS (adjusted HR = 0.84; 95% CI = 0.76 to 0.93) compared to Caucasian patients admitted to VHA ICUs (Tables 4 and 5).

Discussion

Our principle finding was that African-Americans admitted to VHA hospitals for CAP experienced similar or lower adjusted 30-day mortality compared to Caucasians admitted to VHA hospitals for CAP. Given the size, scope, and inclusion of important covariates, this study is an important addition to the literature. Our analysis of over 40,000 patients from more than 150 VHA hospitals from across the U.S. is one of the largest of its kind. Our study provides a contemporary assessment of guideline-concordant prescribing in both VHA hospital wards and ICUs. Our analysis incorporates patient and hospital characteristics that could be predictive of patient outcome, including patient medical history, social history, socioeconomic status, disease complications, and treatment facility. In so doing, this study provides one of the most robust assessments of health disparities in the U.S. Veteran and civilian literature. The absence of a disadvantage for African-Americans suggests African-American and Caucasian patients admitted to VHA hospitals have equal access to care and receive inpatient treatment of similar quality. Equal access to care is a central goal of health care, and this study brings merit to the initiatives of clinicians striving to care for all patients with the highest standards.

African-American patients admitted to VHA ICUs experienced a survival advantage (i.e., lower 30-day mortality) compared to Caucasian patients admitted to VHA ICUs. While this survival advantage has been documented in other studies [15–18], there is no clear explanation for it. Possibly, the Caucasian patients admitted to VHA ICUs were more severely ill than the African-American patients admitted to VHA ICUs; however, this seems unlikely given that both cohorts had similar rates of ICU admission and vasopressor use and mechanical ventilation were more common among African-Americans. While our study lacked some of the clinical variables required to apply prognostic scoring tools (e.g., PSI, CURB-65, and APACHE-II) [39, 40], we included several key covariates including demographic factors (i.e., age, gender) and all five comorbidities (i.e., neoplastic disease, liver disease, heart failure, cerebrovascular disease, and renal disease) used in the PSI score. Thus, our study was well suited to capture/control for the known effects of comorbid illness on mortality for CAP patients. Nevertheless, it is possible that the difference in mortality was due to some unmeasured comorbidity (i.e., receipt of active chemotherapy, immunosuppressive illness, etc) that may have been more prevalent or more problematic for Caucasian patients admitted to the ICU.

The difference in mortality could also be due to differences in advanced directives between the two cohorts. Caucasian patients admitted to VHA hospitals are more likely to have "do not intubate" or "do not resuscitate" orders on file as compared to African-American patients [41]. If this is indeed true, then patients with advanced directives may receive less aggressive therapy. This may partially explain why the African-American patients in our study had higher rates of vasopressor use and mechanical ventilation than the Caucasian patients.

We acknowledge the growing body of literature on frailty [42–44], and recognize the mortality difference might be attributable to differences in frailty between African-American and Caucasian patients admitted to VHA ICUs. The Caucasian patients could be more frail due to a variety of comorbid conditions (i.e., osteoporosis, weight loss or low BMI, cellulitis or decubitus ulcers, fluid electrolyte imbalances, anemia, age >80, syncope, nursing home residence). Likewise, a growing body of literature suggests the importance of functional status, particularly among nursing home patients admitted with pneumonia [45–51]. Poor functional status may contribute to patient mortality and an increased risk of drug resistant pathogens. Our study did not include any measures of frailty or functional status.

In addition to differences in mortality, Caucasian patients in our study remained hospitalized longer than African-American patients. This was the case for both the ward and ICU subgroups. This finding contradicts previous studies reporting longer stays for African-Americans admitted to U.S. hospitals with CAP [13, 19]. The previous findings were observed in civilian hospitals and Bennett et al point out that the correlations reported were almost entirely attributable to differences in insurance status and hospital characteristics between racial groups. We did account for priority group and admitting hospital in our multivariable, generalized linear mixed-effect models. We also accounted for 18 other baseline patient characteristics, including several that were significantly different between the two cohorts: marital status, myocardial infarction, heart failure, chronic obstructive pulmonary disease, diabetes, renal disease, neoplastic disease, tobacco use, and substance abuse. Nevertheless, it is possible that observed differences in hospital LOS were due to other unmeasured variables.

When differences in hospital LOS are observed between two groups, it is important to consider if the group with the shorter hospital LOS experiences any clinical detriment for having been discharged sooner. This could be evaluated by considering hospital readmission rates or mortality post hospital discharge. We analyzed 30-day mortality and found that African-American and Caucasian patients discharged from VHA hospitals experienced similar 30-day mortality; we can therefore conclude that the African-American patients admitted to VHA ICUs did not experience any additional clinical detriment for having been discharged from the hospital sooner than their Caucasian counterparts.

African-American and Caucasian VHA patients in our study were equally likely to receive guideline-concordant antibiotic therapy in ward and ICU settings, a finding consistent with a previous study [3]. This finding is paramount since numerous studies have previously correlated guideline-concordant prescribing with improved patient survival [10, 52, 53]. The guidelines recommend slightly different antibiotic regimens in ward and ICU settings, so it is not surprising that the guideline adherence rates differ somewhat in these two settings. In addition, the recommendations for ward patients have been validated to a greater extent than the recommendations for ICU patients [38, 54].

We did not evaluate individual guideline-concordant therapies, nor did we attempt to correlate certain guideline-concordant therapies with patient race. We recognize that selection from among the various guideline-concordant therapies must be somewhat customized on the basis of patient history, risk factors for multi-drug resistant pathogens, prior antibiotic exposure, and patient comorbidities. National pneumonia guidelines encourage prescribers to consider these things when selecting empiric antibiotic therapies [12]. Since African-American and Caucasian patients differed on several baseline characteristics and comorbidities, we would expect to see slight variations in prescribing within the guideline-concordant therapies. A few of those divergent baseline characteristics are described here along with possible implications for empiric antibiotic therapy.

African-American VHA patients were more likely to have a history of substance abuse or dependence, neoplastic disease, renal disease, and diabetes. In contrast, Caucasian VHA patients were more likely to use tobacco, or have a history of heart failure or chronic obstructive pulmonary disease. These observed differences in comorbidities are consistent with other studies in various infectious diseases, which demonstrate that African-Americans often present to hospitals with more comorbidities compared to Caucasians [3, 7, 19, 55]. Patients with diabetes or renal disease may be less likely to receive fluoroquinolone antibiotics to avoid accumulation in renal disease or a perpetuation of glycemic abnormalities. On the other hand, if patients with renal disease receive antibiotics that are excreted by the kidneys (i.e., fluoroquinolones or β-lactams), then they get greater antibiotic exposure, and possibly better efficacy, from the same dose due to their renal compromise. This may impact hospital LOS as recent data suggest certain guideline-supported therapies are associated with shorter hospital stays [56].

Past studies have demonstrated that African-American patients are less likely to receive timely antibiotic therapy and diagnostic bronchoscopy [1, 3, 13]. We did not capture or evaluate antibiotic timing in our study. We also did not evaluate bronchoscopy; however, we did quantify and compare use of vasopressors and mechanical ventilation between African-American and Caucasian cohorts. We found that African-Americans were more likely to receive these intensive therapies as compared to Caucasians. We did not evaluate acquisition of blood cultures or oxygenation assessment; two process measures previously found to be similar for African-American and Caucasian VHA patients [3].

Our study has limitations that are inherent to all retrospective cohort studies. The results attributed to one explanatory variable could be the result of some unmeasured variable. Any relationships uncovered cannot be definitively considered causative.

The VHA patients in this study are not necessarily representative of all U.S. patients or even all U.S. veterans [57]. The VHA caters to the most disadvantaged veterans and VHA patients are, on average, poorer and sicker than U.S. residents or U.S. veterans [57]. Those with highly service-connected disabilities also receive entry into the VHA system preferentially, and service-connected disability of 50% or more (VA Priority Group 1) garners care without copayments. Lower priority groups (PG 1-6) generally incur copayments for medication prescription, and the lowest priority VA patients (PG 7-8) also have copayments for care. Also, it is certainly possible that African-Americans managed in the VHA system are different from African-Americans managed in other systems.

Additionally, this study was potentially limited by the fact that the investigators were unable to fully exclude VHA patients with healthcare-associated pneumonia (HCAP); however, the stringent exclusion criteria should have minimized these patients. For instance, VHA patients admitted to the hospital or a nursing home within the 90 days prior to the index admission for CAP were excluded. Prior studies have demonstrated that these two exclusions account for a large proportion of HCAP patients [58, 59]. As with any study with non-prospective data collection, we are unable to fully exclude the possibility of missing data. However, VA data have been demonstrated to have excellent validity and reliability [60]. Finally, while errors occur in all databases, as well as in chart data, the VHA databases have been shown to be extraordinarily valid with respect to coding of diagnoses especially on inpatient encounters [60].

Conclusions

Elderly African-American CAP patients experienced a survival advantage (i.e., lower 30-day mortality) in the ICU compared to Caucasians and shorter hospital LOS in both medical wards and ICUs, after adjusting for numerous baseline differences in patient characteristics. There were no racial differences in receipt of guideline-concordant antibiotic therapies.

References

  1. Fine JM, Fine MJ, Galusha D, Petrillo M, Meehan TP: Patient and hospital characteristics associated with recommended processes of care for elderly patients hospitalized with pneumonia: results from the Medicare quality indicator system pneumonia module. Arch Intern Med. 2002, 162 (7): 827-833. 10.1001/archinte.162.7.827.

    Article  PubMed  Google Scholar 

  2. Keppel KG: Ten largest racial and ethnic health disparities in the United States based on Healthy People 2010 Objectives. Am J Epidemiol. 2007, 166 (1): 97-103. 10.1093/aje/kwm044.

    Article  PubMed  Google Scholar 

  3. Mortensen EM, Cornell J, Whittle J: Racial variations in processes of care for patients with community-acquired pneumonia. BMC Health Serv Res. 2004, 4 (1): 20-10.1186/1472-6963-4-20.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Richardus , Kunst AE: Black-white differences in infectious disease mortality in the United States. American Journal of Public Health. 2001, 91 (8): 1251-1253. 10.2105/AJPH.91.8.1251.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Seid M, Varni JW, Cummings L, Schonlau M: The impact of realized access to care on health-related quality of life: a two-year prospective cohort study of children in the California State Children's Health Insurance Program. J Pediatr. 2006, 149 (3): 354-361. 10.1016/j.jpeds.2006.04.024.

    Article  PubMed  Google Scholar 

  6. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR: Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001, 29 (7): 1303-1310. 10.1097/00003246-200107000-00002.

    Article  CAS  PubMed  Google Scholar 

  7. Martin GS, Mannino DM, Eaton S, Moss M: The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003, 348 (16): 1546-1554. 10.1056/NEJMoa022139.

    Article  PubMed  Google Scholar 

  8. Houck PM, Bratzler DW, Nsa W, Ma A, Bartlett JG: Timing of antibiotic administration and outcomes for Medicare patients hospitalized with community-acquired pneumonia. Arch Intern Med. 2004, 164 (6): 637-644. 10.1001/archinte.164.6.637.

    Article  PubMed  Google Scholar 

  9. Niederman MS, Mandell LA, Anzueto A, Bass JB, Broughton WA, Campbell GD, Dean N, File T, Fine MJ, Gross PA, Martinez F, Marrie TJ, Plouffe JF, Ramirez J, Sarosi GA, Torres A, Wilson R, Yu V: Guidelines for the management of adults with community-acquired pneumonia. Diagnosis, assessment of severity, antimicrobial therapy, and prevention. Am J Respir Crit Care Med. 2001, 163 (7): 1730-1754.

    Article  CAS  PubMed  Google Scholar 

  10. Gleason PP, Meehan TP, Fine JM, Galusha DH, Fine MJ: Associations between initial antimicrobial therapy and medical outcomes for hospitalized elderly patients with pneumonia. Arch Intern Med. 1999, 159 (21): 2562-2572. 10.1001/archinte.159.21.2562.

    Article  CAS  PubMed  Google Scholar 

  11. Kahn KL, Rogers WH, Rubenstein LV, Sherwood MJ, Reinisch EJ, Keeler EB, Draper D, Kosecoff J, Brook RH: Measuring quality of care with explicit process criteria before and after implementation of the DRG-based prospective payment system. JAMA. 1990, 264 (15): 1969-1973. 10.1001/jama.264.15.1969.

    Article  CAS  PubMed  Google Scholar 

  12. Mandell LA, Wunderink RG, Anzueto A, Bartlett JG, Campbell GD, Dean NC, Dowell SF, File TM, Musher DM, Niederman MS, Torres A, Whitney CG: Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis. 2007, 44 (Suppl 2): S27-72. 10.1086/511159.

    Article  CAS  PubMed  Google Scholar 

  13. Bennett CL, Horner RD, Weinstein RA, Dickinson GM, DeHovitz JA, Cohn SE, Kessler HA, Jacobson J, Goetz MB, Simberkoff M, Pitrak D, George L, Gilman SC, Shapiro MF: Racial differences in care among hospitalized patients with Pneumocystis carinii pneumonia in Chicago, New York, Los Angeles, Miami, and Raleigh-Durham. Arch Intern Med. 1995, 155 (15): 1586-1592. 10.1001/archinte.155.15.1586.

    Article  CAS  PubMed  Google Scholar 

  14. Hausmann LR, Ibrahim SA, Mehrotra A, Nsa W, Bratzler DW, Mor MK, Fine MJ: Racial and ethnic disparities in pneumonia treatment and mortality. Med Care. 2009, 47 (9): 1009-1017. 10.1097/MLR.0b013e3181a80fdc.

    Article  PubMed  Google Scholar 

  15. Jha AK, Shlipak MG, Hosmer W, Frances CD, Browner WS: Racial differences in mortality among men hospitalized in the Veterans Affairs health care system. JAMA. 2001, 285 (3): 297-303. 10.1001/jama.285.3.297.

    Article  CAS  PubMed  Google Scholar 

  16. Polsky D, Jha AK, Lave J, Pauly MV, Cen L, Klusaritz H, Chen Z, Volpp KG: Short- and long-term mortality after an acute illness for elderly whites and blacks. Health Serv Res. 2008, 43 (4): 1388-1402. 10.1111/j.1475-6773.2008.00837.x.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Volpp KG, Stone R, Lave JR, Jha AK, Pauly M, Klusaritz H, Chen H, Cen L, Brucker N, Polsky D: Is thirty-day hospital mortality really lower for black veterans compared with white veterans?. Health Serv Res. 2007, 42 (4): 1613-1631. 10.1111/j.1475-6773.2006.00688.x.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Sarrazin MV, Cannon KT, Rosenthal GE, Kaldjian LC: Racial differences in mortality among veterans hospitalized for exacerbation of chronic obstructive pulmonary disease. J Natl Med Assoc. 2009, 101 (7): 656-662.

    Article  PubMed  Google Scholar 

  19. Frei CR, Burgess DS: Cost-effectiveness of 4 empiric antimicrobial regimens in patients with community-acquired pneumonia. Formulary. 2005, 1-7.

    Google Scholar 

  20. Brown SH, Lincoln MJ, Groen PJ, Kolodner RM: VistA--U.S. Department of Veterans Affairs national-scale HIS. Int J Med Inform. 2003, 69 (2-3): 135-156. 10.1016/S1386-5056(02)00131-4.

    Article  PubMed  Google Scholar 

  21. Meehan TP, Fine MJ, Krumholz HM, Scinto JD, Galusha DH, Mockalis JT, Weber GF, Petrillo MK, Houck PM, Fine JM: Quality of care, process, and outcomes in elderly patients with pneumonia. JAMA. 1997, 278 (23): 2080-2084. 10.1001/jama.278.23.2080.

    Article  CAS  PubMed  Google Scholar 

  22. Pugh MJ, Copeland LA, Zeber JE, Cramer JA, Amuan ME, Cavazos JE, Kazis LE: The impact of epilepsy on health status among younger and older adults. Epilepsia. 2005, 46 (11): 1820-1827. 10.1111/j.1528-1167.2005.00291.x.

    Article  PubMed  Google Scholar 

  23. Kazis LE, Miller DR, Clark J, Skinner K, Lee A, Rogers W, Spiro A, Payne S, Fincke G, Selim A, Linzer M: Health-related quality of life in patients served by the Department of Veterans Affairs: results from the Veterans Health Study. Arch Intern Med. 1998, 158 (6): 626-632. 10.1001/archinte.158.6.626.

    Article  CAS  PubMed  Google Scholar 

  24. Shen Y, Hendricks A, Zhang S, Kazis LE: VHA enrollees' health care coverage and use of care. Med Care Res Rev. 2003, 60 (2): 253-267. 10.1177/1077558703060002007.

    Article  PubMed  Google Scholar 

  25. Charlson ME, Pompei P, Ales KL, MacKenzie CR: A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987, 40 (5): 373-383. 10.1016/0021-9681(87)90171-8.

    Article  CAS  PubMed  Google Scholar 

  26. Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992, 45 (6): 613-619. 10.1016/0895-4356(92)90133-8.

    Article  CAS  PubMed  Google Scholar 

  27. Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Med Care. 1998, 36 (1): 8-27. 10.1097/00005650-199801000-00004.

    Article  CAS  PubMed  Google Scholar 

  28. Copeland LA, Mortensen EM, Zeber JE, Pugh MJ, Restrepo MI, Dalack GW: Pulmonary disease among inpatient decedents: Impact of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2007, 31: 720-6. 10.1016/j.pnpbp.2007.01.008.

    Article  PubMed  Google Scholar 

  29. Goldman S, Zadina K, Moritz T, Ovitt T, Sethi G, Copeland JG, Thottapurathu L, Krasnicka B, Ellis N, Anderson RJ, Henderson W, VA Cooperative Study Group #207/297/36: Long-term patency of saphenous vein and left internal mammary artery grafts after coronary artery bypass surgery: results from a Department of Veterans Affairs Cooperative Study. J Am Coll Cardiol. 2004, 44: 2149-56. 10.1016/j.jacc.2004.08.064.

    Article  PubMed  Google Scholar 

  30. Sohn MW, Zhang H, Arnold N, Stroupe K, Taylor BC, Wilt TJ, Hynes DM: Transition to the new race/ethnicity data collection standards in the Department of Veterans Affairs. Popul Health Metr. 2006, 4: 7-10.1186/1478-7954-4-7.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Kressin NR, Chang BH, Hendricks A, Kazis LE: Agreement between administrative data and patients' self-reports of race/ethnicity. Am J Public Health. 2003, 93: 1734-9. 10.2105/AJPH.93.10.1734.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Copeland LA, Zeber JE, Wang CP, Parchman ML, Lawrence VA, Valenstein M, Miller A: Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization. BMC Health Serv Res. 2009, 9: 127-10.1186/1472-6963-9-127.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Mortensen EM, Coley CM, Singer DE, Marrie TJ, Obrosky DS, Kapoor WN, Fine MJ: Causes of death for patients with community-acquired pneumonia: results from the Pneumonia Patient Outcomes Research Team cohort study. Arch Intern Med. 2002, 162 (9): 1059-1064. 10.1001/archinte.162.9.1059.

    Article  PubMed  Google Scholar 

  34. Sohn MW, Arnold N, Maynard C, Hynes DM: Accuracy and completeness of mortality data in the Department of Veterans Affairs. Popul Health Metr. 2006, 4: 2-10.1186/1478-7954-4-2.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Frei CR, Koeller JM, Burgess DS, Talbert RL, Johnsrud MT: Impact of atypical coverage for patients with community-acquired pneumonia managed on the medical ward: results from the United States Community-Acquired Pneumonia Project. Pharmacotherapy. 2003, 23: 1167-74. 10.1592/phco.23.10.1167.32764.

    Article  PubMed  Google Scholar 

  36. Frei CR, Restrepo MI, Mortensen EM, Burgess DS: Impact of guideline-concordant empiric antibiotic therapy in community-acquired pneumonia. Am J Med. 2006, 119 (10): 865-871. 10.1016/j.amjmed.2006.02.014.

    Article  CAS  PubMed  Google Scholar 

  37. Chokshi R, Restrepo MI, Weeratunge N, Frei CR, Anzueto A, Mortensen EM: Monotherapy versus combination antibiotic therapy for patients with bacteremic Streptococcus pneumoniae community-acquired pneumonia. Eur J Clin Microbiol Infect Dis. 2007, 26: 447-51. 10.1007/s10096-007-0307-3.

    Article  CAS  PubMed  Google Scholar 

  38. Frei CR, Attridge RT, Mortensen EM, Restrepo MI, Yu Y, Oramasionwu CU, Ruiz JL, Burgess DS: Guideline-concordant antibiotic use and survival among patients with community-acquired pneumonia admitted to the intensive care unit. Clin Ther. 2010, 32: 293-9. 10.1016/j.clinthera.2010.02.006.

    Article  CAS  PubMed  Google Scholar 

  39. Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, Coley CM, Marrie TJ, Kapoor WN: A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med. 1997, 336 (4): 243-250. 10.1056/NEJM199701233360402.

    Article  CAS  PubMed  Google Scholar 

  40. Lim WS, Eerden van der MM, Laing R, Boersma WG, Karalus N, Town GI, Lewis SA, Macfarlane JT: Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003, 58 (5): 377-382. 10.1136/thorax.58.5.377.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Rousseau PC: Racial disparity in advance care planning. J Palliat Med. 1999, 2 (3): 295-297. 10.1089/jpm.1999.2.295.

    Article  CAS  PubMed  Google Scholar 

  42. Lunney JR, Lynn J, Hogan C: Profiles of older Medicare decedents. J Am Geriatr Soc. 2002, 50 (6): 1108-1112. 10.1046/j.1532-5415.2002.50268.x.

    Article  PubMed  Google Scholar 

  43. Lunney JR, Lynn J, Foley DJ, Lipson S, Guralnik JM: Patterns of functional decline at the end of life. JAMA. 2003, 289 (18): 2387-2392. 10.1001/jama.289.18.2387.

    Article  PubMed  Google Scholar 

  44. Copeland LA, Zeber JE, Rosenheck RA, Miller AL: Unforeseen inpatient mortality among veterans with schizophrenia. Med Care. 2006, 44 (2): 110-116. 10.1097/01.mlr.0000196973.99080.fb.

    Article  PubMed  Google Scholar 

  45. Lim WS, Macfarlane JT: A prospective comparison of nursing home acquired pneumonia with community acquired pneumonia. Eur Respir J. 2001, 18: 362-8. 10.1183/09031936.01.00204401.

    Article  CAS  PubMed  Google Scholar 

  46. El-Solh AA, Sikka P, Ramadan F, Davies J: Etiology of severe pneumonia in the very elderly. Am J Respir Crit Care Med. 2001, 163: 645-51.

    Article  CAS  PubMed  Google Scholar 

  47. El-Solh AA, Aquilina AT, Dhillon RS, Ramadan F, Nowak P, Davies J: Impact of invasive strategy on management of antimicrobial treatment failure in institutionalized older people with severe pneumonia. Am J Respir Crit Care Med. 2002, 166: 1038-43. 10.1164/rccm.200202-123OC.

    Article  PubMed  Google Scholar 

  48. El Solh AA, Pietrantoni C, Bhat A, Bhora M, Berbary E: Indicators of potentially drug-resistant bacteria in severe nursing home-acquired pneumonia. Clin Infect Dis. 2004, 39: 474-80. 10.1086/422317.

    Article  PubMed  Google Scholar 

  49. Marrie TJ, Wu L: Factors influencing in-hospital mortality in community-acquired pneumonia: a prospective study of patients not initially admitted to the ICU. Chest. 2005, 127: 1260-70. 10.1378/chest.127.4.1260.

    PubMed  Google Scholar 

  50. Trick WE, Weinstein RA, DeMarais PL, Kuehnert MJ, Tomaska W, Nathan C, Rice TW, McAllister SK, Carson LA, Jarvis WR: Colonization of skilled-care facility residents with antimicrobial-resistant pathogens. J Am Geriatr Soc. 2001, 49: 270-6. 10.1046/j.1532-5415.2001.4930270.x.

    Article  CAS  PubMed  Google Scholar 

  51. Wiener J, Quinn JP, Bradford PA, Goering RV, Nathan C, Bush K, Weinstein R: Multiple antibiotic-resistant Klebsiella and Escherichia coli in nursing homes. JAMA. 1999, 281: 517-23. 10.1001/jama.281.6.517.

    Article  CAS  PubMed  Google Scholar 

  52. Mortensen EM, Restrepo M, Anzueto A, Pugh J: Effects of guideline-concordant antimicrobial therapy on mortality among patients with community-acquired pneumonia. Am J Med. 2004, 117 (10): 726-731. 10.1016/j.amjmed.2004.06.028.

    Article  PubMed  Google Scholar 

  53. Houck PM, MacLehose RF, Niederman MS, Lowery JK: Empiric antibiotic therapy and mortality among Medicare pneumonia inpatients in 10 western states: 1993, 1995, and 1997. Chest. 2001, 119 (5): 1420-1426. 10.1378/chest.119.5.1420.

    Article  CAS  PubMed  Google Scholar 

  54. Bodi M, Rodriguez A, Sole-Violan J, Gilavert MC, Garnacho J, Blanquer J, Jimenez J, de la Torre MV, Sirvent JM, Almirall J, Doblas A, Badía JR, García F, Mendia A, Jordá R, Bobillo F, Vallés J, Broch MJ, Carrasco N, Herranz MA, Rello J: Antibiotic prescription for community-acquired pneumonia in the intensive care unit: impact of adherence to Infectious Diseases Society of America guidelines on survival. Clin Infect Dis. 2005, 41: 1709-16. 10.1086/498119.

    Article  CAS  PubMed  Google Scholar 

  55. McGinnis KA, Fine MJ, Sharma RK, Skanderson M, Wagner JH, Rodriguez-Barradas MC, Rabeneck L, Justice AC: Understanding racial disparities in HIV using data from the veterans aging cohort 3-site study and VA administrative data. Am J Public Health. 2003, 93 (10): 1728-1733. 10.2105/AJPH.93.10.1728.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Frei CR, Jaso TC, Mortensen EM, Restrepo MI, Raut MK, Oramasionwu CU, Ruiz AD, Makos BR, Ruiz JL, Attridge RT, Mody SH, Fisher A, Schein JR: Medical resource utilization among community-acquired pneumonia patients initially treated with levofloxacin 750 mg daily versus ceftriaxone 1000 mg plus azithromycin 500 mg daily: a US-based study. Curr Med Res Opin. 2009, 25 (4): 859-868. 10.1185/03007990902779749.

    Article  CAS  PubMed  Google Scholar 

  57. Morgan RO, Teal CR, Reddy SG, Ford ME, Ashton CM: Measurement in Veterans Affairs Health Services Research: veterans as a special population. Health Serv Res. 2005, 40 (5 Pt 2): 1573-1583. 10.1111/j.1475-6773.2005.00448.x.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Micek ST, Kollef KE, Reichley RM, Roubinian N, Kollef MH: Health care-associated pneumonia and community-acquired pneumonia: a single-center experience. Antimicrob Agents Chemother. 2007, 51 (10): 3568-3573. 10.1128/AAC.00851-07.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Carratala J, Mykietiuk A, Fernandez-Sabe N, Suarez C, Dorca J, Verdaguer R, Manresa F, Gudiol F: Health care-associated pneumonia requiring hospital admission: epidemiology, antibiotic therapy, and clinical outcomes. Arch Intern Med. 2007, 167 (13): 1393-1399. 10.1001/archinte.167.13.1393.

    Article  PubMed  Google Scholar 

  60. Kashner TM: Agreement between administrative files and written medical records: a case of the Department of Veterans Affairs. Med Care. 1998, 36: 1324-36. 10.1097/00005650-199809000-00005.

    Article  CAS  PubMed  Google Scholar 

Pre-publication history

Download references

Acknowledgements

The authors would like to thank Christine Oramasionwu and Warunee Srisupha-Olarn for their editorial review of this manuscript. The project described herein was supported by Grant Number R01NR010828 from the National Institute of Nursing Research. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Nursing Research or the National Institutes of Health. This material is the result of work supported with resources and the use of facilities at the South Texas Veterans Health Care System and The University of Texas at Austin. Dr. Frei is supported by a Loan Repayment award from the National Institute of Allergy and Infectious Diseases of the National Institutes of Health, salary support from The University of Texas at Austin College of Pharmacy, and research support from AstraZeneca, Élan, and Ortho-McNeil Janssen. Dr Copeland is funded by Merit Review Entry Program grant MRP-05-145 from the VA Health Services Research and Development program. Dr. Restrepo is supported by a National Institutes of Health Grant KL2 RR025766, salary support by the South Texas Veterans Health Care System Audie L. Murphy Division and The University of Texas Health Science Center at San Antonio. The funding agencies had no role in conducting the study, or role in the preparation, review, or approval of the manuscript. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. This manuscript was presented, in part, at the American Thoracic Society International Conference, May 15-20, 2009, San Diego, CA.

Author information

Authors and Affiliations

  1. The University of Texas at Austin College of Pharmacy, 1 University Station, A1900, Austin, TX, 78712, USA

    Christopher R Frei & Russell T Attridge

  2. The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA

    Christopher R Frei, Eric M Mortensen, Laurel A Copeland, Russell T Attridge, Mary Jo V Pugh, Marcos I Restrepo, Antonio Anzueto & Brandy Nakashima

  3. South Texas Veterans Health Care System, Audie L. Murphy Division, 7400 Merton Minter Blvd, San Antonio, TX, 78229, USA

    Eric M Mortensen, Laurel A Copeland, Mary Jo V Pugh, Marcos I Restrepo, Antonio Anzueto & Brandy Nakashima

  4. VERDICT Research Program, South Texas Veterans Health Care System, 7400 Merton Minter Blvd, San Antonio, TX, 78229, USA

    Eric M Mortensen, Laurel A Copeland, Mary Jo V Pugh, Marcos I Restrepo & Brandy Nakashima

  5. Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, 7180 Highland Drive (151C-H), Pittsburgh, PA, 15206, USA

    Michael J Fine

  6. Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA, 15213, USA

    Michael J Fine

Authors
  1. Christopher R Frei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eric M Mortensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Laurel A Copeland
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Russell T Attridge
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mary Jo V Pugh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marcos I Restrepo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Antonio Anzueto
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Brandy Nakashima
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Michael J Fine
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eric M Mortensen.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

CRF participated in the design, data analysis and interpretation, performed statistical analyses, and was the primary person responsible for drafting the manuscript. EMM conceived and designed the primary study; and participated in the design, data analysis and interpretation, performed statistical analyses, and revised the manuscript for important intellectual content. MJP participated in the design, data acquisition, and manuscript revisions. RTA participated in data analysis and interpretation and was the secondary person responsible for drafting the manuscript. MJP and LAC participated in the design, data acquisition, and manuscript revisions. MIR, AA, BN, and MJF participated in the design and manuscript revisions. All authors read and approved the final manuscript.

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Frei, C.R., Mortensen, E.M., Copeland, L.A. et al. Disparities of Care for African-Americans and Caucasians with Community-Acquired Pneumonia: A Retrospective Cohort Study. BMC Health Serv Res 10, 143 (2010). https://doi.org/10.1186/1472-6963-10-143

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1472-6963-10-143

Keywords

BMC Health Services Research

ISSN: 1472-6963

Contact us