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Effect of a Standardized Nurse Case-Management Telephone Intervention on Resource Use in Patients With Chronic Heart Failure
Barbara Riegel, DNSc, RN, CS;
Beverly Carlson, MS, RN, CNS, CCRN;
Zoe Kopp, RN, MPH;
Barbara LePetri, MD;
Dale Glaser, PhD;
Alan Unger, PhD
Arch Intern Med. 2002;162:705-712.
ABSTRACT
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Background Case management is believed to promote continuity of care and decrease
hospitalization rates, although few controlled trials have tested this approach.
Objective To assess the effectiveness of a standardized telephonic case-management
intervention in decreasing resource use in patients with chronic heart failure.
Methods A randomized controlled clinical trial was used to assess the effect
of telephonic case management on resource use. Patients were identified at
hospitalization and assigned to receive 6 months of intervention (n = 130)
or usual care (n = 228) based on the group to which their physician was randomized.
Hospitalization rates, readmission rates, hospital days, days to first rehospitalization,
multiple readmissions, emergency department visits, inpatient costs, outpatient
resource use, and patient satisfaction were measured at 3 and 6 months.
Results The heart failure hospitalization rate was 45.7% lower in the intervention
group at 3 months (P = .03) and 47.8% lower at 6
months (P = .01). Heart failure hospital days (P = .03) and multiple readmissions (P = .03) were significantly lower in the intervention group at 6 months.
Inpatient heart failure costs were 45.5% lower at 6 months (P = .04). A cost saving was realized even after intervention costs
were deducted. There was no evidence of cost shifting to the outpatient setting.
Patient satisfaction with care was higher in the intervention group.
Conclusions The reduction in hospitalizations, costs, and other resource use achieved
using standardized telephonic case management in the early months after a
heart failure admission is greater than that usually achieved with pharmaceutical
therapy and comparable with other disease management approaches.
INTRODUCTION
HEART FAILURE (HF) is an extremely common disorder and one that is associated
with significant morbidity, mortality, and cost.1-3
Because of this burden, investigators are actively exploring ways to improve
the outcomes associated with HF. Pharmaceutical therapy reduces hospitalization
from 12%4 to 35%,5
depending on the agent. Higher rates are found when a combined end point of
mortality and rehospitalization is used.6-7
In comparison, in randomized trials of comprehensive disease management, hospital
admission rates were reduced from 27%8 to 73%,9 with most interventions demonstrating reductions in
the 40% to 50% range.10 Disease management
approaches shown to be effective include multidisciplinary disease management,11 heart failure clinics,12
and community outreach programs.13 Telephonic
case management is another approach believed to promote continuity of care
and decrease hospitalization rates in persons with HF. However, few clinical
trials have tested the effectiveness of this approach,14-16
and only 1 study was conducted among patients with HF.14
Case management has been differentiated into community outreach and
telephonic approaches.17 Community outreach
programs typically involve home visits by a registered nurse, physician, and/or
pharmacist.13, 18 The face-to-face
visit in the patient's own home is used to evaluate the living situation,
physically assess the patient, and continue patient education. In contrast,
telephonic methods of case management often involve a nurse calling patients
after discharge from a hospital to ensure that the treatment plan is being
followed: questions are answered, early symptoms are addressed, and teaching
is continued.19 Telephonic case management
may be particularly challenging because of the lack of visual cues and the
inability to physically examine the patient. Therefore, much of the effectiveness
of telephonic case management depends on the unique abilities and experience
of the provider. A recent editorial on HF home care noted that "intermediaries
[are] step[ping] up to the role of a heart failure expert, and frankly, some
do it well while others do it not so well . . . there remains too much variability."20 In the present study, care was standardized using
a decision-support software program from Pfizer Inc called At Home With Heart Failure.21
The primary aim of our study was to assess the effectiveness of a standardized
telephonic nurse case-management intervention in decreasing resource use in
patients with chronic HF. A randomized controlled clinical trial was conducted
to test the primary hypothesis that HF hospitalization rates would be lower
in the intervention group than in the "usual-care" control group. Secondary
hypotheses were that the following would be decreased: all-cause hospitalization,
readmission rates (for HF and all causes), average number of hospital days
(for HF and all causes), and inpatient HF costs at 3 and 6 months. Days to
first rehospitalization, multiple readmissions (ie, >1) for any cause, and
outpatient resource use (ie, emergency department and urgent care visits for
any cause and/or physician office visits) were evaluated at 6 months. Outpatient
resource use was assessed to determine if shifting of costs from inpatient
to outpatient care occurred. Patient satisfaction was assessed at 6 months.
PATIENTS AND METHODS
STUDY SAMPLE
Although it was the physicians who were randomized, patients were the
unit of analysis for this study. It was not feasible to randomize patients
in the same physician practice to different groups because of the possibility
that the physicians would modify care in the control group to mimic aspects
of the intervention. Physicians known to admit patients with HF were matched
by specialty (eg, cardiology or internal medicine), practice size (number
of physicians within a single provider site), and number of HF admissions
in the prior year. After matching, physicians were randomly assigned to the
intervention or usual-care control group. All physicians within a single provider
site were assigned to the same group. A total of 281 physicians were randomized.
Physicians were not informed of the group to which they were assigned.
A 40% decrease in the HF hospitalization rate was anticipated based
on prior studies.10 Assuming a power of 0.80,
a 2-tailed  of .05, and a small to moderate effect size (Cohen d = .33), we required 290 patients (145 per group) to detect
a difference of 40% in HF hospitalization rates. A larger sample size would
have been needed to detect differences in outpatient resource use,15-16 but this outcome was not the focus
of the analysis.
After institutional review board approval was obtained, bilingual nurse
research associates screened patients hospitalized at 2 Southern California
hospitals to determine eligibility. Included were patients with a confirmed
clinical diagnosis of HF as the primary reason for their hospital visit and
those who spoke either English or Spanish. Excluded were patients with cognitive
impairment or psychiatric illness, severe renal failure requiring dialysis,
terminal disease (eg, cancer and/or acquired immunodeficiency syndrome), discharge
to a long-term care facility, or previous enrollment in an HF disease management
program. Approximately 1145 patients were screened and 573 (50%) of these
met eligibility criteria. Of these eligible subjects, 358 (62%) were included
in this study. The rest declined participation (n = 148), were under the care
of a physician who refused the intervention (n = 29), withdrew during the
course of the study (n = 28), or were dropped for reasons such as having moved
out of the country (n = 10).
INTERVENTION
After obtaining informed consent, telephonic case management by a registered
nurse was provided using a decision-support software program developed by
Pfizer Inc.21 The software program was designed
to emphasize those factors previously shown to predict hospitalization in
persons with HF (ie, poor adherence to medication regimens and diet recommendations
and lack of knowledge of the signs and symptoms of worsening illness).22 The software program uses automated tools for setting
priorities for patient education, data collection, and documentation. Important
clinical information is organized within the program to facilitate patient
care by the case managers (Figure 1).
Best practices—derived from published guidelines, prior research, and
input from experts—are supported by the program.23-24
The software was refined after exploring the needs of patients with HF, their
caregivers, and case managers. An advisory board of cardiologists, primary
care physicians, and case managers provided critical feedback throughout the
process of software development.
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Telephonic case management was standardized using a computer software
program21 developed by Pfizer Inc, New York,
NY, in which patients were comprehensively assessed and managed. The frequency
of subsequent phone calls was determined by the case-management level assigned
by the nurse. Calls emphasized monitoring and patient education. Physicians
were kept informed through written reports and by telephone if necessary.
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In this study, the intervention group (n = 130) was telephoned within
5 days after hospital discharge and thereafter at a frequency guided by the
software and case manager judgment based on patient symptoms, knowledge, and
needs. For example, a patient reporting sudden weight gain would receive a
follow-up telephone call the following day to evaluate the response to suggested
interventions and to closely monitor the signs and symptoms of fluid retention.
Patients exhibiting shortness of breath often received an additional telephone
call on the same day to ensure that physician contact had been made and that
his or her instructions were understood by the patient. When access to prescribed
medications was identified as a problem, frequent telephone calls were often
necessary to arrange for a supply of medications.
Patients received an average of 17 phone calls at decreasing levels
of intensity, length, and frequency over the 6-month follow-up period (median,
14 phone calls; interquartile range, 11-22 phone calls). Each patient was
estimated to have received 16 hours of a case manager's time overall. Time
not spent directly with patients was used in speaking with family members,
consulting with community agencies and other professionals (eg, physicians,
dietitians, social workers, and physical therapists), preparing reports for
physicians, and researching drugs, diets, and information requested by patients.
Printed educational material was mailed to patients monthly. Physicians were
sent automated reports produced by the software that updated them on patient
progress and were telephoned by the case managers as needed. Guidelines for
the treatment of systolic HF23 were distributed
to physicians with their first notification of patient progress. Care for
patients in the usual-care control group (n = 228) was not standardized, and
no formal telephonic case-management program was in existence at these institutions.
These patients presumably received some education regarding HF management
prior to hospital discharge.
OUTCOME MEASUREMENT
Demographic (eg, age, sex, primary language, marital status) and clinical
data (eg, HF type) were collected from the medical record at the time of index
hospitalization. Functional status was measured using the New York Heart Association
(NYHA) classification system. Few patients had physician documentation of
NYHA class, so a single master's-prepared nurse practitioner rated NYHA class
on every patient based on information available in the hospital record. Functional
status was also assessed using the Specific Activity Scale.25
Comorbidity was measured using the interview format of the Charlson Index.26 Severity of illness during the index hospitalization
was assessed using the refined diagnostic-related grouping technique from
3M (St Paul, Minn). Baseline drug therapy was obtained from the index hospitalization
medical record. Subsequent drug therapy was obtained by self-report at 3-
and 6-month intervals.
Data on acute care resource use (ie, hospitalization rates, readmission
rates, hospital days, days to first rehospitalization, total number of readmissions,
and HF costs) were gathered from automated financial records at 3 and 6 months
following discharge from the hospital for the index admission. Any out-of-system
inpatient resource use was identified by patient self-report at 3 and 6 months.
Acute care costs were measured using a combination of direct and indirect
costs, which were obtained from the hospital's automated financial records
using Eclipsys (formerly Transition Systems Inc), Atlanta, Ga. Direct costs
reflect the cost of providing care, while indirect costs reflect overhead.
Six months after the index admission, nurse research associates visited
physicians' offices to abstract records to obtain information on outpatient
resource use measured as the number of physician office visits, emergency
department and urgent care visits, and outpatient cardiac tests. A survey
measuring satisfaction with care was administered to patients by telephone
at 6 months. The survey contained 5 questions addressing, respectively, (1)
current treatment, (2) convenience of health care, (3) patient education,
(4) medication schedule, and (5) the care from the physician.
The cost of the intervention was calculated using estimates of the time
required for case manager training and patient care. The nurses received 10
days of intense training and continuing mentoring in case management thereafter
(ie, 15 one-hour sessions); a total of 95 hours of training was provided each
case manager. Each patient was estimated to require approximately 16 hours
of a case manager's time over the 6-month period. An hourly rate of $22.66
plus 17% of that figure for employee benefits was used in the calculations
based on mid-range salary rates during the study period.
STATISTICAL ANALYSIS
The intervention and usual-care control groups were assessed for balance
on demographic and clinical characteristics at baseline. The effectiveness
of the intervention was assessed by comparing outcomes between the intervention
and usual-care control groups at 3 and 6 months following discharge from the
index hospitalization. Analyses were performed using SPSS statistical software,
version 7.5 (SPSS Inc, Chicago, Ill). A P value less
than .05 was predetermined as indicating a statistically significant difference
between the groups. Covariates were used in the analyses if group differences
were evident at baseline and there was a plausible association with the outcome
variables. Cost analyses were conducted using logarithmically transformed
data because of the severe positive skewness caused by multiple zeros. Descriptive
statistics for the untransformed cost data are reported.
Investigators routinely report both hospitalization rates and readmission
rates in the literature. Thus, both are included here. Unadjusted hospitalization
rates represent the mean number of hospitalizations per patient and are calculated
as the number of hospitalizations for the sample within 3 and 6 months of
index hospital discharge divided by the full sample size, regardless of whether
a readmission occurred.11-13,27-28
Unadjusted readmission rates reflect the proportion of the sample admitted
at least once during the study period.22 Unadjusted
readmission rates were calculated as the percentage of patients readmitted
to the hospital after the index admission.
To test the primary hypothesis of group differences in HF hospitalization
rates, the number of hospitalizations per patient within 3 or 6 months of
index discharge was analyzed by analysis of covariance. Readmission rates
were analyzed using multiple logistic regression. The log odds of the probability
of being readmitted at least once within 3 or 6 months of index discharge
was modeled as a linear function of the intervention group after adjusting
for the covariates. Multiple linear regression models were used to analyze
the average number of accumulated hospital days (for HF and all causes) and
inpatient HF costs during the 3- and 6-month follow-up. The mean number of
days between index hospital discharge and the first rehospitalization was
compared using analysis of covariance. The rate of multiple readmission during
the 6-month study period was calculated as the percentage of patients admitted
more than once and tested for group differences using logistic regression.
Group differences in the rate of emergency department and physician office
visits during the 6-month study period were tested using logistic regression.
Patient satisfaction was analyzed using multiple linear regression.
All analyses were conducted using 2 covariates on which the groups differed
at baseline in spite of randomization:  -blocker use and chronic lung
disease. In no analysis was either covariate significant. Correlations between
the covariates and the outcomes were typically in the .02 to .04 range; none
was higher than .09. Therefore, all reported results reflect group differences
without adjustment for covariates, although results with covariates are shown
in Table 1.
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Table 1. Acute Care Resource Use in Patients Receiving the Case-Management
Intervention Compared With Those Receiving Usual Care
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RESULTS
After randomization, physician agreement to participate was sought,
but not all physicians were willing to allow their patients to be approached.
A final sample of 358 patients (130 intervention and 228 control) was used
for the analysis of acute care resource use. However, data on outpatient resource
use and satisfaction were only available on a subsample of 242 patients who
were divided between the intervention (n = 130) and control (n = 112) groups.
The only significant difference between the subsample of 242 and the 116 on
whom outpatient resource data use were not available was primary language;
more patients whose primary language was Spanish were in the sample of 116
than in the 242 on whom outpatient resource use data were available. All 358
patients were drawn from the a priori randomization of physicians to the intervention
or control group.
PATIENT CHARACTERISTICS
The overall sample was elderly (mean ± SD age, 72 ± 12
years), almost equally divided by sex (51% female), predominantly unmarried
(56% widowed, single, or divorced) (Table
2), and functionally compromised (97% were NYHA class III or IV)
(Table 3). The only significant
differences between the groups on demographic or clinical descriptors were
a higher use of -blockers and a lower incidence of chronic lung disease
in the intervention group.
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Table 2. Demographic Profile of the 358 Study Participants
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Table 3. Summary of Clinical Characteristics at the Time of Enrollment*
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PRIMARY ANALYSIS
Heart failure hospitalization rates were 45.7% lower in the intervention
group than in the usual-care control group at 3 months (P = .03). At 6 months, HF hospitalization rates were 47.8% lower in
the intervention group than in the control group (P
= .01) (Table 1).
SECONDARY ANALYSES
Acute care resource use was consistently lower in the intervention group
than in the usual-care control group at 3 and 6 months. All-cause hospitalization
rates dropped 25.6% at 3 months and stayed 28.2% lower in the intervention
group at 6 months (P = .03). Heart failure readmission
rates (ie, the percentage of patients admitted at least once during the study
period) were 36% lower in the intervention group at 3 and 6 months, but reached
statistical significance only at 6 months. All-cause readmission rates were
not significantly different at either 3 or 6 months. The average number of
days spent in the hospital for HF was 46% lower at both 3 and 6 months, although
only the 6-month difference reached statistical significance. The number of
all-cause days in the hospital was 27% lower at 3 months and 28% lower at
6 months in the intervention group, but not significantly different between
the groups. Inpatient costs for HF admissions were 35% lower at 3 months and
45.5% lower at 6 months, but the difference between groups only reached statistical
significance at 6 months.
The mean time from index hospital discharge to rehospitalization was
longer in the intervention group but not significantly different between the
groups (Table 1). The percentage
of patients experiencing multiple readmissions (2 or more during the 6-month
period) was 43% lower in the intervention group and significantly different
between the groups. There were no significant differences between the groups
in the number of outpatient resources used (ie, physician office visits and/or
emergency department visits) during the 6-month period.
Patient satisfaction information was available from only 184 of the
242 patients we attempted to survey. The others were traveling, in the hospital,
living in an extended care facility, or dead. There were no significant demographic
or clinical differences between the patients who responded to the survey and
those who were unavailable. Patient satisfaction was significantly higher
among persons assigned to the intervention group than among those in the usual-care
control group.
The intervention was calculated to cost $443 per patient, if the cost
of training is included. If each case manager carries 130 patients per year
(2080 working hours in the year/16 hours per patient = 130 patients per year),
the cost of a 16-hour intervention provided over 6 months is $424 per patient.
When training costs were divided among 130 patients, an estimated $19 of training
costs was added to each patient to produce the $443 per patient estimate.
COMMENT
Patients with HF who regularly received standardized telephone calls
from a registered nurse case manager required significantly fewer resources
over the 6 months of study than patients receiving usual care. Experts argue
that the key to a successful HF program is access to and continuity of care.10, 24, 29 The results of this
trial support that theory.
Significant cost savings were demonstrated with this intervention. The
cost of acute care for each patient in the usual-care group was $2186, on
average, but the average cost per patient in the intervention group was only
$1192. This difference computes to about $1000 less per patient over the 6
months of the study compared with those in the usual-care control group. This
savings is more than double the estimated $443 cost per patient for the 6-month
case-management intervention.
Although pharmaceutical therapy is the mainstay of HF care, its ability
to limit acute care resource use and decrease costs is rarely as potent as
that of disease management. For example, the angiotensin-converting enzyme
inhibitor ramipril decreased HF hospitalizations only 12%.4
Captopril reduced HF admissions by 22% in the SAVE trial.30
Hospitalization for worsening HF was 23% lower in patients treated with digoxin
than in those given placebo in the DIG trial.31
Bisoprolol decreased the HF hospitalization rate by 32% in the CIBIS II study.32 In the RALES trial, treatment with spironolactone
decreased the frequency of HF hospitalization 35% in comparison with placebo.5 Disease management may have superior outcomes because
the disease management providers typically emphasize the importance of medication
compliance, help patients design dosing systems and ways to remember their
scheduled medications, and "problem-solve" medication adverse effects. In
this way, disease management augments the effectiveness of pharmaceutical
therapy.
Surprisingly, few other investigators have scientifically tested an
intervention of this style with a chronically ill patient population, although
telephonic case management is used widely in disease management programs across
the country.33 We identified 3 controlled clinical
trials in which the intervention was delivered almost entirely by telephone,
but only 1 of these was conducted with HF patients.14-16
Wasson and colleagues15 demonstrated a significant
19% reduction in scheduled and unscheduled clinic visits, 28% fewer days in
the hospital, and 28% lower cost among chronically ill patients called an
average of 8 times over a 2-year period. Patient satisfaction increased significantly.
Infante-Rivard and colleagues16 lowered outpatient
physician office visits 15% in an elderly group who were provided as many
as six 30-minute phone calls over a 48-week period, although the difference
between the intervention and control groups was not statistically significant.
West and colleagues14 provided a primarily
telephonic intervention (a mean of 13.2 calls over a 6-month period) to a
group of patients with HF and significantly reduced physician office visits
(cardiology, 31% lower; general medical, 23% lower), emergency department
visits (HF, 67% lower; all-cause visits, 53% lower), and hospitalization rates
(HF, 87% lower; all-cause rates, 74% lower).
Together, these studies suggest that telephonic case management can
significantly decrease physician office visits, hospital days, emergency department
visits, and rehospitalization rates. The results of this study support this
conclusion, although in this study, emergency department visits increased—perhaps
because patients in the intervention group sought care early enough to avoid
rehospitalization. The published range of decreases in resource use seen in
the various trials suggests that some telephonic case-management interventions
are more effective than others. At this point it is unclear whether intensity
of the intervention, standardization of the approach, patient characteristics
such as severity of illness, or some combination of these factors influences
the effectiveness of the approach. Further research is needed to identify
the best way to implement a telephonic case-management intervention.
A review of studies in which telephone access was included as only 1
component of a multifactorial intervention program suggests that treatment
intensity is partially responsible for the effectiveness of this telephonic
intervention. Two of 4 HF disease management programs that included telephone
access as a component of therapy demonstrated a beneficial effect on acute
care resource use.27, 34 The other
2, which demonstrated no benefit, seem to have offered weak telephone interventions.35-36 For example, in 1 of these latter
studies, an average of 7.5 follow-up telephone calls were provided, but each
call was an average of only 5.7 minutes long.35-36
True case management emphasizing the essential factors that predict rehospitalization
would be difficult to accomplish in that time. In the other study that found
no beneficial effect, a median of 4 telephone calls were made over the entire
5-month follow-up period.35 In contrast, weekly
calls were made in the 2 trials in which benefit was found.27, 34
In the present trial, the case managers expended 16 hours over 6 months, most
of which was spent counseling the patients over the telephone. This observation
suggests that the intensity of the intervention is related to its effectiveness.
Standardization of the intervention is another potential explanation
of treatment effectiveness. In the present trial, a computer software program
was used to standardize care and documentation. West and colleagues14 also used a method of standardization and also demonstrated
significant reductions in resource use. However, others who apparently did
not standardize the intervention also found a decrease in resource use.15 The fact that the reductions found with an unstandardized
approach were not as great as those found in the present study and in the
study by West et al14 suggests that standardization
of the content may augment the power of a telephonic intervention by assuring
that essential content is addressed.
Severity of illness may be another factor influencing the outcomes achieved
with a telephone intervention. In the present study, the vast majority (97%)
of the patients were in NYHA class III or class IV at the time of enrollment,
but most (60%) of those studied by West and colleagues14
were less symptomatic (ie, classes I and II). In the study of the intervention
that provided only brief telephone calls (5.7 minutes) and increased resource
use rather than decreased it, many (49%) of the patients were in class III
or class IV.36 This disparity of findings suggests
that there may be an interaction between treatment intensity and illness severity.
Previous research testing a multidisciplinary disease management approach
for patients with HF supports this observation.28
In that study, a moderately intense intervention increased acute care resource
use in patients with asymptomatic disease (NYHA class I) but decreased acute
care resource use in those in the early symptomatic (NYHA class II) stages.
Further research is needed to identify the patient population expected to
benefit most from particular styles and intensities of disease management
approaches.
Limitations of this study may stem from randomization of physicians
rather than patients, which might have introduced a sample selection bias.
However, the randomization strategy yielded 2 groups that were equivalent
in most of the measured variables. Those variables on which the groups differed
were evaluated as potential covariates and not found to be associated with
study outcomes. Another limitation is that the sample size was not adequate
to detect differences in outpatient resource use. However, our concern was
the potential for an increase in outpatient resource use, and no such trend
was observed. Physician blinding may not have been sufficient to prevent bias:
those randomized to the intervention group probably deduced it based on receipt
of reports and intermittent case manager calls. It is possible that these
physicians delivered less care or postponed hospitalization in these patients
because of the support from the case managers. This effect was not unanticipated
or undesired clinically, but it could bias the study results in favor of case
management. Future studies would be enhanced by careful logging and reporting
of actual hours spent per case manager with each patient rather than applying
an estimated average per patient.
In summary, this clinical trial is one of the few testing a commonly
used intervention—telephonic case management. The results of this study
demonstrate that standardized nurse case management provided to an ill HF
patient population by telephone during the early months after an HF admission
can achieve significant cost savings, reductions in resource use, and increases
in patient satisfaction. The reduction in resource use seen in this study
is comparable to that observed with other disease management approaches and
greater than that seen with most pharmaceutical therapy. The effectiveness
of the approach may be a function of the intensity and focus of the intervention,
standardization, patient characteristics such as illness severity, or an interaction
among these factors. Further research is needed to identify which of these
components is essential and if a briefer, less intense intervention will be
as effective in an HF patient population.
AUTHOR INFORMATION
Accepted for publication July 17, 2001.
This study was funded by Pfizer Inc, New York, NY.
We gratefully acknowledge the support and assistance of technical designer
Robin Hertz, PhD; Seterah Williams, PhD; Mary Almas, MS; Elizabeth Fagaly,
BA; case mangagers Julia Charvet, BS, RN, Joyce Nichols, MS, RN, and Barbara
Payne, MS, RN; research assistants Maria Hamon, MS, RN, Sandra Parkington,
BS, RN, and Sophia Jimenez; and data analysts Kevin Scott Strickland, BS,
RN, Elizabeth Ellis, MBA, RN, and Valorie Thomas, MS, RN. We also thank Graham
Nichol, MD, MPH, for his assistance in the cost analyses and for reviewing
a prior version of the manuscript.
Corresponding author and reprints: Barbara Riegel, DNSc, RN, CS,
School of Nursing, San Diego State University, San Diego, CA 92182-4158 (e-mail: briegel{at}mail.sdsu.edu).
From San Diego State University (Dr Riegel and Ms Carlson), the Clinical
Research Department, Sharp HealthCare (Dr Riegel and Ms Carlson), and Pacific
Science and Engineering Group (Dr Glaser), San Diego, Calif; from San Diego
State University (Dr Riegel and Ms Carlson), the Clinical Research Department,
Sharp HealthCare (Dr Riegel and Ms Carlson), and Pacific Science and Engineering
Group (Dr Glaser), San Diego, Calif; Outcomes Research (Ms Kopp) and Safety
Evaluation and Epidemiology (Dr LePetri), Pfizer Inc, New York, NY; and Science
Applications International Corporation, Reston, Va (Dr Unger).
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