1. health and fitness
2. disease
3. aids and hiv

ORIGINAL INVESTIGATION
Physician Specialization and the Quality of Care
for Human Immunodeficiency Virus Infection
Bruce E. Landon, MD, MBA; Ira B. Wilson, MD, MSc; Keith McInnes, MS; Mary Beth Landrum, PhD;
Lisa R. Hirschhorn, MD, MPH; Peter V. Marsden, PhD; Paul D. Cleary, PhD
Background: There is debate over the types of physicians who should treat patients with complex chronic
medical conditions such as human immunodeficiency virus (HIV) infection. We sought to assess the relationship between specialty training and expertise and the quality of care delivered to patients with HIV infection.
Methods: We selected random samples of HIVinfected patients receiving care at 64 Ryan White CARE
(Comprehensive AIDS Resources Emergency) Act–
funded clinics throughout the country and their primary HIV physicians for an observational cohort study
in which quality-of-care measures were assessed by medical record review.
Results: We studied 5247 patients linked to 177 phy-
sicians who responded to a survey. Fifty-eight percent
of the physicians were general medicine physicians (“generalists”) and 42% were infectious diseases specialists.
Sixty-three percent of the generalists (37% overall) considered themselves expert in HIV care. In hierarchical lo-
Author Affiliations: Division of
General Medicine, Beth Israel
Deaconess Medical Center
(Dr Landon), Department of
Health Care Policy
(Drs Landon, Landrum, and
Cleary and Mr McInnes), and
Division of AIDS
(Dr Hirschhorn), Harvard
Medical School, Boston, Mass;
Institute for Clinical Research
and Health Policy Studies and
Department of Medicine,
Tufts–New England Medical
Center, Boston (Dr Wilson);
and Department of Sociology,
Harvard University, Cambridge,
Mass (Dr Marsden).
Financial Disclosure: None.
T
gistic regression models that controlled for patient characteristics, infectious diseases physicians and expert
generalists had similar performance. In contrast, nonexpert generalists delivered lower quality care. More than
80% of the appropriate patients being cared for by infectious diseases physicians and expert generalists were receiving highly active antiretroviral therapy, compared with
73% of appropriate patients of nonexpert generalists
(P⬍.001). Physicians with fewer than 20 patients with
active HIV had fewer appropriate patients on highly
active antiretroviral therapy (73% vs 82% of physicians with ⱖ20 such patients, P=.04) and saw patients
less frequently.
Conclusion: These findings extend previous work by examining a range of quality-of-care measures and suggest that generalists with appropriate experience and expertise in HIV care can provide high-quality care to
patients with this complex chronic illness.
Arch Intern Med. 2005;165:1133-1139
HERE IS DEBATE OVER THE
types of physicians who
should treat patients with
complex chronic medical
conditions, such as human immunodeficiency virus (HIV) infection.1-7 These patients require specialized treatment, including the adjustment
and management of complex medical regimens that might best be handled by specialist physicians.8 However, such patients often have other conditions. For
example, persons with HIV infection often have hepatitis C infection, and increasing numbers of persons receiving highly
active antiretroviral therapy (HAART) have
hyperlipidemia, insulin resistance, and
body shape changes. In addition, they often require a wide range of medical and
social services.9,10 General medicine physicians (“generalists”) may be best trained
to ensure accessibility, coordination, con-
(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1133
tinuity, and comprehensiveness of services.3,11-13
Most studies that have examined this
issue used caseload as a proxy for expertise.4,14,15 When other information was
used, formal specialty training often has
been the only indicator of physician expertise, and variations in expertise within
categories of physicians have been ignored.16-18 Our group has previously assessed the relationship between the quality of care and specialty training and
expertise, defined as experience with treating HIV-infected patients, in a nationally
representative cohort of patients with HIV
infection.1,2 We found that generalists with
HIV expertise adopted and used HAART
at a rate similar to that of infectious diseases–trained (ID) physicians, whereas
nonexpert generalists used HAART less frequently. That study, however, examined
only HAART at a time soon after its in-
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troduction. It is important to know whether differences
in quality between physicians with different training and
expertise have persisted and exist across a broader range
of treatment.
This study assessed the relationship between specialty
training and expertise and the quality of care delivered recently to patients with HIV infection in a national sample
of patients receiving care from clinics funded by the Ryan
White Comprehensive AIDS Resources Emergency (CARE)
Act. We compared the care provided by generalists with
and without expertise in HIV care with that of ID physicians and assessed the independent impact of HIV caseload. We examined 8 different measures of quality in the
areas of antiretroviral drug use, screening and prophylaxis, and delivery of routine services.
METHODS
OVERVIEW
As part of an evaluation of a quality-improvement program, we
abstracted quality-of-care information from medical records and
surveyed physicians caring for study patients about their background, training, and experience with treating HIV infection.19 The care was delivered in a nationally representative group
of CARE Act–funded clinics.
PARTICIPANTS AND DATA COLLECTION
Study Site Selection
The evaluation study19 included 69 CARE Act–funded clinics
that provided care for at least 100 patients with HIV infection
during 1999. The sites included community health centers, community-based organizations, health departments, hospital outpatient clinics, and university medical centers.19
Patient Sample
We identified random samples of patients at each of the clinics during 2 time periods corresponding to the beginning and
end of the quality-improvement intervention. For the first
sample, sites were asked to provide lists of all HIV-infected patients at least 18 years old seen at the site between January 1
and June 30, 2000, and for the second sample, sites were asked
to provide a list of patients seen at the site between July 1 and
December 31, 2001. We randomly selected up to 75 patients
per sample for medical record reviews. For patients sampled
in both periods, only data from the first period were included.
Clinician Identification and Data Collection
All clinicians providing care to HIV-infected patients at the sites
were eligible for the clinician surveys, which were conducted
in 2000 and 2001. A study facilitator at each of the clinics identified all relevant clinicians (including physicians, nurse practitioners, and physician assistants) with primary responsibility for caring for HIV-infected patients. We randomly sampled
up to 5 clinicians to participate. Each survey was sent with a
$20 incentive.
The overall response rate to the survey was 87%, and 243 distinct clinicians responded across its 2 waves. When a physician
responded to both waves, we used his or her survey data from
the first wave. If 2 surveys were received, the major predictors
were almost always consistent. Sixty-six responses were re(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1134
ceived from nurse practitioners or physician assistants, and those
clinicians were excluded from the current analysis, leaving a total
of 177 physician responses. There were no differences in response rates according to region, type of clinic, or survey wave.
Linking Patients to Clinicians
As part of the medical record review, reviewers who worked at
the clinics were asked to identify the name and qualifications (eg,
physician, nurse practitioner, or physician assistant) of the clinician “who makes most of the major (eg, changing antiretroviral regimen) decisions regarding this patient’s care.” They identified a responsible clinician for 8841 of the 9020 patients in the
study (98.0%). We were able to link 6551 (72.6%) of the 9020
medical record review patients with clinicians who responded
to the survey. After eliminating 1304 patients who were linked
to nonphysicians, the final sample included 5247 patients being
cared for in 64 of the clinics (5 clinics did not have patients linked
to physicians). The other patients were cared for by clinicians
who were not sampled or did not respond to the survey.
Medical Record Review Procedures
Each clinic had 1 or 2 medical records reviewers (typically
nurses). We first pilot tested the medical record review instrument with reviewers at 5 sites and modified the instrument on
the basis of their feedback. We then sent the instrument to each
of the remaining reviewers and asked them to review 2 or 3
charts at their clinics. Each reviewer then participated in a conference call with the investigators to review the instrument, identify problem questions, and clarify instructions.
Data were collected from each sampled patient’s medical record covering a 1-year period of care. No major changes in guidelines for HIV care were released during this period.20-22 The abstracted data included sociodemographic information such as
age and sex, history of AIDS-defining conditions, comorbid
medical or psychiatric conditions including current substance
abuse or psychiatric illness, screening and prophylaxis for HIVrelated conditions, number and timing of visits, CD4 counts,
viral loads, and antiretroviral medications prescribed.
ANALYTIC VARIABLES
Quality of Care Measures
The quality-of-care measures (Table 1) were developed on the
basis of consensus guidelines available during the study period.20 All measures were dichotomous, with defined criteria
for eligibility for the measure and meeting the measure. Our
primary focus was on rates of HAART use and control of HIV
viral load for appropriate patients because we thought that antiretroviral treatment use would be most reflective of training
and experience. Patients eligible for HAART included those with
CD4 counts less than 500/µL or viral loads greater than 10 000
copies/mL, and patients already receiving HAART. Because of
the variability in viral load assays then available, viral load was
considered controlled if it was undetectable or less than 400
copies/mL. We also assessed the use of screening and prophylaxis, as well as access to care (defined as visits to any clinician
during ⱖ3 possible quarters), and created a summary quality
score that included the sum of all of the indicated measures.
Predictor Variables
Data on Physician Specialization. For these analyses, we used
selected physician characteristics that were identified as predictors of care quality in previous analyses1,2: physician speWWW.ARCHINTERNMED.COM
©2005 American Medical Association. All rights reserved.
cialty training, experience treating HIV-infected patients as measured by current caseload, self-rated HIV-related expertise, and
knowledge of HIV practices. Physicians were classified as being
trained in infectious diseases or as general medicine/other (generalists). Based on previous analyses, we categorized the physicians’ current HIV caseload as low (0-19 patients), medium
(20-299), or high (ⱖ300). The physicians were also asked
whether they considered themselves to be “experts” in the treatment of HIV, a measure that has been previously shown to be
valid in predicting quality of care for HIV.1Only 9 (12%) of 75
ID physicians in the sample did not consider themselves to be
HIV experts. Therefore, to examine the joint effects of training and expertise in multivariable models, we created a composite training/expertise variable with 3 categories: ID physicians, expert generalists, and nonexpert generalists. As a
sensitivity analysis, we also repeated our analyses after removing these 9 physicians and found no difference.
Physician Knowledge. The clinician survey included a series
of 6 questions that asked about the physicians’ knowledge of
current HIV treatment practices related to viral load testing and
antiretroviral therapy. We therefore included the knowledge
scale in analyses related to HAART use and viral load control.
The number of correct responses formed a knowledge index.
“Don’t know” responses were classified as incorrect.
Patient Control Variables. In all analyses, we controlled for
patient age, sex, stage of disease based on lowest recorded CD4
count during the period of care, active psychiatric or substance abuse problem, history of AIDS-defining conditions, and
other comorbid medical conditions.
Table 1. Quality-of-Care Indicators
Quality
Indicator
Eligible Population
Tuberculosis
screening
during review
period*
All patients
Influenza
vaccination
All patients
Hepatitis C
status
All patients
Pap smear
All women
PCP
prophylaxis
All patients with CD4
count ⬍200/µL at
any point during
the review period
All patients with CD4
count ⬍500/µL or
VL ⬎10 000
copies/mL and
those already
receiving HAART
All patients receiving
or eligible for
HAART
HAART at last
visit for
appropriate
patients
STATISTICAL ANALYSIS
We first compared characteristics of the study sites to all Title
III sites in the continental United States. To examine relationships between HIV caseload, the composite training/expertise
variable, and knowledge and the quality-of-care measures, we
estimated a series of hierarchical logistic regression models for
the quality outcomes that controlled for physician, clinical, and
sociodemographic characteristics, and for the clustering of patients within individual physicians and physicians within clinics. Because these coefficients are estimated on a logarithmic
odds scale, we present transformed estimates on the probability scale to make them more interpretable. We first constructed a baseline model that controlled for patient-level effects and the period of care. We then estimated separate models
that examined the individual effects of the joint training/
expertise variable, knowledge (for the 2 antiretroviral treatment–
related measures), and current HIV caseload. The final model
included the joint effects of training/expertise and current HIV
caseload together. For estimating the model for the overall quality scale, we used hierarchical linear regression. In previous
analyses, no differences were found in quality of care between
clinics that participated in the quality improvement intervention and those that did not,19 so participation in the intervention was not controlled for in these analyses.
RESULTS
SITE AND PHYSICIAN CHARACTERISTICS
Study clinics were representative of all CARE Act–
funded clinics nationally (Table 2). Half of the clinics
were hospital-based or community health centers, and 61%
characterized themselves as specialized HIV clinics. The
(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1135
VL controlled at
last visit
(undetectable
or ⬍400
copies/mL)
Visits in 3 or 4
quarters
All patients
Meets Quality Measure
All patients who received
a tuberculosis
screening test or were
known to have had a
positive test result in
the past
Documentation that the
patient received an
influenza vaccination
during the review
period
All patients with hepatitis
C status documented
during the review
period†
Pap smear performed or
offered and refused at
least once during the
review period, or note
of a Pap smear
performed elsewhere
Receipt of PCP
prophylaxis
Receipt of 3-drug HAART
regimen
VL undetectable or ⬍400
copies/mL
Visits in ⱖ3 quarters
Abbreviations: HAART, highly active antiretroviral therapy; Pap,
Papanicolaou; PCP, Pneumocystis jiroveci pneumonia; VL, viral load.
*Patients with documentation of a previous positive tuberculosis
screening test result were counted as having been screened; those with
missing values were counted as not having been screened.
†Includes those with documentation of a previous positive test result for
hepatitis C.
average age of the physicians was 43 years and 61% were
male (Table 3). Fifty-eight percent of the physicians identified themselves as generalists and 42% were ID specialists. Sixty-three percent of the generalists (37% overall)
considered themselves expert in the care of HIV. Compared with ID physicians and generalist experts, fewer nonexpert generalists were from rural clinics. Approximately
10% of the sample was caring for fewer than 20 patients
each, whereas almost 20% had a caseload of 300 patients
or more. The mean knowledge score overall was 5.1 (on
a 6-point scale). Nonexpert generalists had significantly
lower scores (mean, 4.3) than did ID physicians (mean,
5.3; P⬍.001) and expert generalists (mean, 5.2; P⬍.001).
PATIENT CHARACTERISTICS
The average patient was 41 years old and 28% were female (Table 4). Approximately 25% had hepatitis C, 15%
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sured by lowest ever CD4 count, was similar across the
3 physician groups.
Table 2. Characteristics of Study Clinics and CARE
Act–Funded Clinics Nationally*
Characteristic
Urban
Region
Midwest
Northeast
South
West
Clinic type
Community health center
Hospital based
Other
Small site (⬍400 HIV-infected patients)
Specialized HIV site
HIV caseload, mean (median)
PHYSICIAN CHARACTERISTICS AND
INDIVIDUAL MEASURES OF QUALITY OF CARE
All CARE
Act–Funded
Clinics
(N = 208)
Study Clinics
(n = 64)
154 (74.0)
42 (65.6)
32 (15.8)
78 (38.4)
55 (27.1)
38 (18.7)
14 (21.9)
25 (39.1)
17 (26.6)
8 (12.5)
81 (38.9)
23 (11.1)
104 (50.0)
99 (50.5)
111 (53.4)
623 (400)
23 (35.9)
9 (14.1)
32 (50.0)
30 (46.9)
39 (60.9)
637 (400)
Abbreviations: CARE, Comprehensive AIDS Resources Emergency; HIV,
human immunodeficiency virus.
*Data obtained from the Evaluation of Quality Improvement in HIV
(EQHIV) Site Survey supplemented by Title III data obtained from the Health
Resources and Services Administration. Data are given as number
(percentage) unless otherwise indicated. Percentages may vary because of
small amounts of missing data. All P ⬎.05 for the comparison of study
clinics with CARE Act–funded clinics nationally.
Table 3. Physician Characteristics
Finding
(N = 177)
Characteristic
Age, mean (SD), y
Female, %
Race, %
White
Black
Hispanic
Asian
Very satisfied with practice, %
Specialty, %
ID physician
Expert generalist
Nonexpert generalist
HIV caseload, No. of patients, %
1-19
20-299
ⱖ300
Knowledge score, mean (SD)*
Outpatients seen in a typical week,
mean (median), No.
Patients seen who have HIV,
mean (median), % of patients
43.4 (8.0)
39.0
66.1
6.2
11.3
16.4
28.8
41.8
36.7
21.5
9.6
71.8
18.6
5.1 (1.0)
48.8 (33.8)
61.2 (37.5)
Abbreviations: HIV, human immunodeficiency virus; ID, infectious
diseases.
*Score consisted of the number of correct answers to 6 questions related
to viral load testing and antiretroviral therapy.
had active drug abuse documented, and 10% had CD4
counts less than 50/µL. Infectious diseases physicians primarily cared for 2176 patients (41%), expert generalists
cared for 2637 patients (50%), and nonexpert generalists cared for 434 patients (8%). Disease stage, as mea(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1136
After controlling for patient characteristics, ID physicians and expert generalists had similar performance on
all of the measures examined (Table 5). In contrast, nonexpert generalists had lower quality scores. More than
80% of the patients being cared for by ID physicians and
expert generalists were receiving HAART, compared with
73% of patients being cared for by nonexpert generalists
(P⬍.001). Thirty-one percent of the patients being cared
for by nonexpert generalists had their viral load controlled, compared with 39% of patients for expert generalists and 41% for ID physicians (P=.01). Nonexpert
generalists also gave influenza vaccinations less frequently and their patients were seen less frequently. For
every 1-point increase in the physician knowledge score,
the odds of patients having their viral load controlled increased by 1.14 (data not shown). Knowledge was not
significantly related to HAART use. Physicians with fewer
than 20 patients with active HIV had fewer appropriate
patients receiving HAART (Table 5, 73% vs 82% of higher
volume physicians, P = .04) and saw patients less frequently (50% with visits in 3 quarters compared with 68%
for higher volume physicians, P=.002).
Findings for the summary quality score were similar
(Figure). When all 3 predictors (including specialty training, caseload, and knowledge) were examined simultaneously, the contrast of nonexpert generalists with other
physicians continued to be significant (P=.02), while the
relationship with caseload was no longer significant.
COMMENT
There has been a long-standing debate about the types of
physicians who should treat patients with chronic medical conditions such as HIV infection.1-4,8,11 In this study,
we examined the influence of both formal training and expertise (including caseload) on the treatment of a representative population of patients with HIV infection receiving their care at CARE Act–funded clinics. Our group
previously found that expert generalists appropriately used
HAART at a rate similar to that of ID physicians.1,2 However, that study examined only a single quality measure
shortly after its introduction. In addition to being more
current, these findings extend previous research by examining a range of quality-of-care measures that represent different aspects of care for patients with HIV infection.1,2 Our results suggest that generalists with appropriate
experience and expertise in a particular area can provide
high-quality care to patients with complex chronic illness. Conversely, the approximately 10% of patients being
cared for by nonexpert and/or low-volume physicians were
less likely to receive the recommended treatments and testing we examined. Our results also suggest that, overall,
the quality of care for these patients with HIV infection
was suboptimal. These findings are consistent with national results from a wide variety of conditions.23
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Table 4. Characteristics of Study Patients by Type of Physician Seen
Characteristic
Patient age, mean (SD), y
Female, %
AIDS-defining conditions, mean (SD), No.
Comorbid conditions, mean (SD), No.
Hepatitis C positive test result, %
Psychological disorders, %
Drug abuse documented, %
Lowest CD4 count during the review period, cells/µL, %
0-49
50-199
200-499
ⱖ500
All Patients
(N = 5247)
Patients Seen
by ID Physicians
(n = 2176)
Patients Seen by
Expert Generalists
(n = 2637)
Patients Seen by
Nonexpert Generalists
(n = 434)
40.7 (8.8)
28.0
0.2 (0.5)
0.4 (0.7)
24.7
31.3
14.8
40.5 (9.0)
31.4
0.20 (0.50)
0.42 (0.70)
24.9
32.2
14.0
40.9 (8.7)
24.6*
0.15 (0.44)‡
0.40 (0.69)
23.2
29.8
13.8
40.5 (8.8)
31.6†
0.16 (0.50)
0.37 (0.65)
32.7*†
35.7§
25.1*†
10.4
20.4
42.7
26.5
11.1
20.5
42.1
26.3
9.6
20.0
43.5
26.9
12.0
22.4
41.2
24.4
Abbreviation: ID, infectious diseases.
*P⬍.01 for ID physicians vs expert generalists or nonexpert generalists.
†P⬍.01 for expert generalists vs nonexpert generalists.
‡P⬍.05 for ID physicians vs expert generalists or nonexpert generalists.
§P⬍.05 for expert generalists vs nonexpert generalists.
Table 5. Association Between Rates of Achieving Individual Quality Measures and Physician Characteristics*
HIV Care
Physician Predictor†
Specialty
ID physician
Expert generalist
Nonexpert generalist
HIV caseload, No.
1-19
20-299
ⱖ300
Screening
Routine Care
HAART
VL
Controlled
PCP
Prophylaxis
PPD
Testing
Hepatitis C
Status
Pap
Smear
Influenza
Vaccination
OP Visits
in 3 Quarters
0.83
0.82
0.73‡
0.41
0.39
0.31§
0.64
0.72
0.69
0.51
0.46
0.46
0.86
0.81
0.81
0.56
0.60
0.52
0.54
0.49
0.41§
0.66
0.69
0.57§
0.73‡
0.82
0.80
0.30
0.39
0.37
0.69
0.73
0.67
0.41
0.50
0.41
0.74
0.83
0.87
0.53
0.57
0.59
0.41
0.52
0.46
0.50㛳
0.68
0.63
Abbreviations: HAART, highly active antiretroviral therapy; HIV, human immunodeficiency virus; ID, infectious diseases; OP, outpatient; PCP, Pneumocystis
jiroveci pneumonia; PPD, purified protein derivative; VL, viral load.
*All results are presented as percentage rates after adjustment for patient characteristics including age, sex, stage of disease based on lowest recorded CD4
count over the period of care, active psychiatric or substance abuse problem, history of HIV-related diagnoses, and other comorbid medical conditions. The
adjusted rates represent the estimated probability of receiving the indicator for a hypothetical person with average characteristics.
†Infectious diseases physician is the omitted category for specialty; caseload of 20 to 299 is the omitted category for HIV caseload.
‡P ⬍.05.
§P⬍.01.
㛳P = .002.
The pattern of findings was not consistent across all
types of measures but conformed to a priori hypotheses.
We expected that the largest differences would relate to
antiretroviral treatment. The advent of multiple new
drugs to treat HIV infection, their use in a variety of different combinations, and the multiple side effects that
accompany HAART regimens make antiretroviral treatment the most challenging routine aspect of caring for
HIV-infected patients.21 Measures related to the adequacy of antiretroviral treatment showed the strongest
and most consistent differences between physicians
with and without expertise. Conversely, with the exception of influenza vaccinations, rates of screening and
preventive measures were similar across all types of
physicians.
(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1137
Our findings contrast with research done in other conditions where specialists tended to provide care deemed
appropriate at higher rates than generalists did when processes of care were examined (using medical record reviews or patients’ reports) for acute myocardial infarction,6,16 unstable angina,17 asthma,24 acute arthritis,25,26
multiple sclerosis,27 and depression.28 In addition, previous research in HIV has shown that patients of physicians with more experience in treating HIV had lower
mortality (early on in the epidemic)14 and earlier access
to antiretroviral therapy.4 Most of these studies, however, did not account for different levels of expertise
among generalists or examine higher cutoffs for volume. A survey by Stone et al29 supports our findings that
generalists can develop expertise in HIV infection. In a
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70
% of Physicians
62.5
61.5
60.2
60
58.5
∗
54.7
†
52.1
50
0
Nonexpert Expert
ID
Generalist Generalist Physician
Specialty
1-19
20-299
≥300
HIV Caseload, No. of Patients
Figure. Association between performance rates on the overall quality scale
and physician characteristics. Results are presented as rates after
adjustment for patient characteristics, including age, sex, stage of disease
based on lowest recorded CD4 count during the period of care, active
psychiatric or substance abuse problem, history of human
immunodeficiency virus–related diagnoses, and other comorbid medical
conditions. Infectious diseases–trained (ID) is the omitted category for
specialty; caseload of 20 to 299 patients is the omitted category for human
immunodeficiency virus (HIV) caseload. Asterisk indicates P=.001; dagger,
P = .004.
national survey using vignettes, they found that generalists who reported providing care for HIV-infected patients were equally likely to appropriately prescribe antiretroviral therapy.
Our findings also suggest that acquiring expertise in
HIV care differs from the “practice makes perfect” model
observed in surgical specialties.30 Previous work by our
group demonstrates that a physician can acquire expertise by virtue of interest in a particular condition and
through multiple means, including attending continuing medical education courses and conferences and keeping up with the literature, without being a high-volume
HIV provider.1 Thus, while we found that lower volume
physicians provided care of lower quality, there did not
seem to be a relationship to volume over a threshold.
Our study has several limitations. First, we studied clinics being funded by Title III of the CARE Act Program.31
In 2001, such programs served more than 150 000 patients.32 Almost two thirds of these low-income patients
were from racial/ethnic minority groups. The clinics in
our study were representative of clinics receiving CARE
Act funding. An advantage of studying this population
is that their health care is supported by the CARE Act
and the patient population is more homogeneous. However, the results may not be generalizable to other outpatient settings. Second, we did not have data on the treating clinician for all of the patients in our sample. This
was due to how physicians were selected as well as nonresponse. Third, we were not able to contact patients for
this study and therefore could not analyze other important outcomes, including patient satisfaction and experiences with care. In addition, other important aspects
of care, including accessibility, counseling, coordination, continuity, and comprehensiveness of services, are
difficult to measure from medical records.33
In summary, in this national study of more than 5000
patients, we found that generalists with expertise in HIV
(REPRINTED) ARCH INTERN MED/ VOL 165, MAY 23, 2005
1138
infection provided a quality of care equal to that of specialists trained in infectious diseases on multiple important components of outpatient care for HIV infection.
Guidelines and strategies to improve care for HIV should
therefore promote the use of expert generalists as well
as ID physicians. Developing strategies to obtain appropriate expert input for patients who receive care from nonexpert generalists might also lead to improved outcomes.
Accepted for Publication: December 19, 2004.
Correspondence: Bruce E. Landon, MD, MBA, Department of Health Care Policy, Harvard Medical School, 180
Longwood Ave, Boston, MA 02115 ([email protected]
.harvard.edu).
Funding/Support: This study was supported by grant
R-01HS10227 from the Agency for Healthcare Research
and Quality, Rockville, Md.
Acknowledgment: We thank our colleagues at the HIV
AIDS Bureau of the Health Resources and Services Administration, Rockville, Md, and the Institute for Health
Care Improvement, Boston, Mass, for their efforts and
expertise. We are indebted to Lin Ding, PhD, for assistance with expert statistical programming; to Deborah
Collins for assistance with manuscript preparation; and
to Carol Cosenza, MSW, and Patricia Gallagher, PhD, of
the Center for Survey Research, Boston, for assistance with
instrument development and survey administration.
REFERENCES
1. Landon BE, Wilson IB, Wenger NS, et al. Specialty training and specialization
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