Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 80
13
Administrative Data in
Effectiveness Studies:
The Prostatectomy Assessment
Elliott S. Fisher* and John E. Wennberg
Comprehensive, population-based administrative health care data bases
provide an increasingly accessible and important source of data for studies
of the effectiveness of health care (1~. To illustrate their potential uses,
their strengths, and their limitations, we describe the role that administrative
data have played in the ongoing assessment of treatments for benign pros-
tatic hyperplasia, one of the more common conditions affecting elderly men.
OVERVIEW OF THE PROSTATECTOMY ASSESSMENT
Analyses of administrative health care data bases have long documented
marked variations in population-based rates of prostatectomy (2,3~. To
understand the causes of these variations, a multidisciplinary team com-
posed of practicing urologists from Maine and researchers from academic
medical centers in the United States, Canada, and Europe was assembled.
The assessment team, funded under the Patient Outcome Assessment Research
Program of the National Center for Health Services Research, undertook a
comprehensive program of evaluation, the early findings of which are de-
scribed in a series of recent publications (4-8~. These findings are briefly
summarized in Table 1 to provide a context for the description of the analyses
based on administrative data.
The first goal of the assessment process was to identify possible explana-
tions for the observed variations in utilization rates. This entailed both a
*The paper was presented by Dr. Fisher, but it represents the ongoing research of
many investigators in the Prostatectomy Patient Outcomes Research Team of which
Dr. Wennberg is the principal investigator. The work is now part of the Patient
Outcome Research Team program of the Agency for Health Care Policy and Research.
80
OCR for page 81
USE OF LARGE DATA BASES
TABLE 1 Aims, Methods, and Data Sources for Assessment of
Treatments for Benign Prostatic Hyperplasia
81
Aim
Describe patterns of use of
treatments arid characterize
the theories of efficacy
advanced by their proponents
Identify, define, and develop (where
necessary) measures for the full
spectrum of relevant outcomes
Establish the best estimates for
probabilities of the relevant
outcomes of alternative treatments
Assess the efficacy of alternative
treatment theories
Integrate results, identify questions
for further research
Method and Data Source
Geographic variation studies using
insurance claims and other large
data bases
Structured literature review and focus
groups with practicing physicians
Literature review and semi-structured
interviews with patients, physicians
Identification or development of valid and
reliable outcome and case-mix measures
Claims-based cohort studies; linkage
of claims and other data bases
Prospective cohort studies (Maine
Interview Study)
Decision analysis, meta-analysis
Observational studies, randomized trials
where appropriate
Publication of results and impart
. . . . . .
1nc trigs to practicing p ~yslclans
Development of interactive video for
Shared Medical Decision-making
Procedure
review of the scientific literature and discussions with practicing urologists
in Maine. Two conflicting theories concerning the indications for prostatectomy
were identified. Many physicians believed that prostatectomy should be
performed early in the course of symptomatic prostatism on the theory that
if the operation is delayed, the patient will be at higher risk when the
surgery becomes unavoidable. Because overall life expectancy would be
reduced by delay, those who held to this preventive theory believed that watchful
waiting was not a reasonable option. In contrast, urologists who believed
the quality of life theory argued that prostatectomy is not inevitable. For
patients without evidence of actual or impending renal dysfunction, the
primary indication for the procedure should be improvements in functional
status and quality of life. According to this theory, watchful waiting is a
reasonable option.
To evaluate these competing theories, the assessment team identified all
relevant outcomes through discussions with patients and physicians. A
OCR for page 82
82
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
review of the medical literature demonstrated serious gaps in existing knowledge
about these outcomes. Claims-based analyses made possible reliable mea-
sures of the likelihood of mortality in the postoperative period and of reoperation
(41. The probabilities for other outcomes-such as incontinence, impo-
tence, and postoperative symptom relief and improvement in functional sta-
tus required the development of new measurement instruments and the
implementation of a prospective interview study of patients undergoing
prostatectomy in Maine (6~.
The findings of the literature review, the claims-based analyses, and the
interview study provided sufficient data to assess the efficacy of watchful
waiting versus transurethral prostatectomy (TURP) through decision analy-
sis (5~. The decision analysis demonstrated that for most patients the deci-
sion to undergo prostatectomy results in a slight decrease in life expect-
ancy. These findings confirmed the opinion of those physicians who believed
that the operation was justified primarily for its value in reducing symptoms.
However, the assessment also demonstrated (a) that improvements in symp-
toms were only available to those willing to accept the risks of the surgery,
and (b) that patients with identical symptoms differed greatly in their attitudes
toward those symptoms and, presumably, toward the risks of surgery.
The assessment thus revealed that variations in utilization rates induced
by practice style were primarily a function of differences in providers'
attitudes toward the preventive theory and of difficulty in integrating pa-
tients' preferences into the decision to undergo prostatectomy. To help address
these difficulties, the assessment team developed a computer-assisted, inter-
active video presentation that provides a comprehensive description of the
risks and benefits of the alternatives and is tailored to the individual patient
viewing the presentation. This Shared Medical Decision-making Procedure
(SMDP) has been implemented in several participating centers, with both
surgical and watchful waiting patients being followed up to provide further
refinements in the probability estimates for outcomes.
The assessment steps described above required the application of mul-
tiple research methodologies. In the remainder of this chapter, we describe
the role that administrative data bases played both in the assessment of
TURP versus watchful waiting and in addressing a specific question that
emerged from early analyses.
OVERVIEW OF METHODS
Because we are describing the results of a series of studies conducted
over many years, it is impractical to present in detail the methods used in
each of the analyses. The general approach followed, which was similar in
all analyses, will be reviewed briefly. The reader is referred to the primary
publications for additional detail (3,4,8,9~.
OCR for page 83
USE OF LARGE DATA BASES
83
All of the studies relied on administrative or health insurance data bases
as primary sources of data. The Health Care Financing Administration
(HCFA) maintains comprehensive files on inpatient, outpatient, and skilled
nursing home care for virtually the entire U.S. population over the age of 65
(10,11~. Similar files have long been maintained by the Manitoba Health
Services Commission, in the Oxfordshire Region of England, and in Den-
mark (8~.
Three features of these files are essential to the analysis. First, the
eligible population can be precisely defined, the date of death can be ascer-
tained independent of health care utilization, and patients can be located for
long-term follow-up studies. Second, administrative procedures in each
system ensure that virtually all hospital utilization is documented. Third,
unique personal identifiers allow utilization files to be linked to each other,
to the population files, and to other sources of data.
The methods used to define cases for inclusion in the study population
and to define relevant variables were similar in all claims-based analyses
reported here. They thus represent a generalizable approach to the use of
administrative data bases for cohort studies.
CASE IDENTIFICATION AND VARIABLES
All patients were initially identified on the basis of computerized hospi-
tal discharge abstracts or physician claims documenting a prostatectomy
during the various study periods encompassed by the assessments. Where
both physician and hospital claims were available (HCFA and Manitoba),
potential cases were identified, consistency checks carried out, validity of
claims determined, and appropriate exclusions applied. For each case, the
first prostatectomy during the study period was defined as the index opera-
tion. Based on the claims data, three classes of variables were defined.
Outcomes
The population file was searched to determine whether and when patients
might have died. Reoperation was defined based on the presence of subse-
quent claims for prostatectomy. Other possible complications were defined
based on combinations of diagnoses and procedures coded on inpatient hos-
pital records and on physician claims for both inpatient and outpatient services.
Patient Covariables
Diagnoses recorded on the index hospitalization claim and on physician
and hospital claims preceding the index prostatectomy were used to mea-
sure comorbidity.
OCR for page 84
84
Treatment Variables
EFFECTIVENESS ED OUTCOMES IN HEALTH CARE
The specific codes recorded on hospital and physician claims were used
to define the type of prostatectomy received by the patient (open versus
transurethral).
USES OF ADMINISTRATIVE DATA IN
PROSTATECTOMY ASSESSMENT
VARIATIONS IN UTILIZATION RATES
First, and perhaps most important, studies of small-area variations in
prostatectomy rates provided the initial stimulus for the research project
and were critical to engaging the interest of practicing urologists in the
assessment. Early studies documented age-adjusted population-based utili-
zation rates for prostatectomy that varied by a factor of four across small
areas of New England (3~. Other studies documented variations across
large geographic regions (12) and between and within countries with differ-
ent health care financing and organizational structures (131. Discussed
extensively elsewhere (14,15), small-area analyses have highlighted the clinical
uncertainty surrounding many decisions in medicine and underlined the need
for comprehensive assessments of the risks, benefits, and alternatives to
specific treatments.
POPULATION-BASED ESTIMATES OF ADVERSE
OUTCOME RATES
As mentioned above, urologists in Maine disagreed in their understand-
ing of the risks and benefits of prostatectomy. Some of this disagreement
could be attributed to gaps and flaws in the existing medical literature.
Physicians usually rely on reports from clinical trials and case series to
estimate the risks of adverse outcomes following specific surgical or medi-
cal interventions. Unfortunately, these sources suffer from several limita-
tions. One problem with case series is reporting bias: only where the
results are better than previously reported is there a strong incentive to
publish. Consequently, published rates of adverse outcomes may underesti-
mate the risk in most clinical settings. Clinical trials usually report findings
on highly selected populations and therefore may be difficult to generalize.
Moreover, sample sizes are usually limited, and follow-up and choice of
outcomes for study vary among case series. Consequently, confidence in-
tervals (CIs) are likely to be wide, rare events may not be documented at
all, and results are difficult to pool. Claims data can overcome these limita-
tions.
OCR for page 85
USE OF LARGE DATA BASES
85
In the mid-1970s, a review of the literature on prostatectomy stated that
mortality rates following TURP were under 1 percent and that patients
rarely required reoperation (16~. Wennberg, Roos, and colleagues, using
claims data from Maine and Manitoba for 1974 through 1976, found that
over 3 percent of patients died within 90 days of surgery and that the
overall rate of reoperation following TURP was 20.2 percent at eight years
(4~. While these findings demonstrate the difficulty of relying on small,
highly selected samples to estimate the likelihood of various outcomes, the
data are by now quite old. What are the current risks of prostatectomy?
We have used Medicare data for New England to examine mortality and
morbidity following prostatectomy in the 1980s (Tables 2 and 3~. Because
of the large sample sizes, mortality rates for prostatectomy can now be
precisely estimated: 30-day mortality ranges from 0.3 percent for patients
between the ages of 65 and 69 to 2.6 percent for patients age 80 and over.
Studies of morbidity are more difficult when relying on claims data alone,
because few of the diagnostic and procedure codes used on hospital discharge
abstracts or physician claims specify that a given complication or procedure
is the direct consequence of a prior prostatectomy. Consequently, using
methods similar to those described by Roos et al. (17), we asked physicians
to group codes into those that were possibly complications of the procedure
(that is, outcomes occurring with increased frequency following any opera-
tion) and those that were probably complications (because they are more
directly related to prostatectomy). More than 10 percent of patients had a
probable complication, while 16 percent had a possible complication. In
all, almost one-quarter of patients had significant adverse outcomes in the
90 days following prostatectomy.
TABLE 2 Mortality Rates Following Prostatectomy Among Medicare
Enrollees Who Were New England Resident Patients Without Indication of
Prostate or Bladder Cancer, 1984-1986
Patient Dead Patient Dead
Within 30 Days Within 90 days
Cases of Surgery of Surgery
Age Group (No.) (Percent) (Percent)
65-69 6,428 0.3 1.2
70-74 6,946 0.8 2.3
75-79 5,740 1.2 3.2
80 and over 5,652 2.6 6.8
Total 24,766 1.2 3.3
NOTE: Based on Medicare Part A and Part B claims and Medicare Enrollment
(HISKEW) files.
OCR for page 86
86
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
TABLE 3 Morbidity Rates Within 90 Days of Transurethral
Prostatectomy Among Patients Without Indication of Prostate or Bladder
Cancer Who Were New England Resident Medicare Enrollees, 1984-1986
Possible Complications Percent Probable Complications Percent
Myocardial infarction 1.0 Bladder infection 2.0
Pulmonary embolus 0.3 Kidney infection 0.1
Respiratory infection 3.0 Prostate infection 0.2
Wound infection 0.3 Other urinary infection 0.3
Congestive heart failure 1.5 One or more urinary infection 2.3
Phlebitis 0.2 Stricture~treatment 3.7
Deep venous thrombosis 0.3 Retention treatment 1.8
Arterial embolus 0.4 Other invasive testing 4.5
Bleeding 7.5 Second prostatectomy 0.6
Miscellaneous 3.3 One or more invasive procedures 8.7
One or more of above 16.0 One or more of above 10.3
One or more possible or probable complications, 23.4 percent
NOTE: Based on Medicare Part A and Part B claims files.
Although these data demonstrate that a variety of adverse events may be
detected through the claims data, several limitations must be acknowledged.
First, the completeness and accuracy of the coding in claims data bases has
been questioned (18,19~. However, if the accuracy of the data could be
confirmed and if administrative safeguards were enacted to ensure their
complete and accurate documentation, then claims-based measures could be
used to monitor the outcomes of care for patients undergoing prostatectomy.
Second, the scope of the data is limited. Many outcomes critical to the
prostatectomy assessment, such as disease-specific functional status and
quality of life, could not be ascertained from the claims data. The next
section provides examples of how these specific limitations of the claims
data can be overcome.
COMPARISONS OF TRANSURETHRAL AND OPEN
PROSTATECTOMY
The initial claims-based analyses of prostatectomy outcomes in Maine
and Manitoba also compared the long-term results of TURP with those of
open prostatectomy. Both operations have the same purpose-to relieve
urinary obstruction. The open procedure is usually performed through an
incision in the abdominal wall, whereas the transurethral procedure is per-
formed through the urethra. Because of its less invasive nature, TURP was
believed by urologists to be both safer and more effective than the open
OCR for page 87
USE OF LARGE DATA BASES
87
operation. Although a randomized clinical trial has never been conducted,
TURP has gradually replaced open prostatectomy to the point where, in the
1980s, only about 5 percent of prostate operations in our data base were
open.
The claims data provided an opportunity to compare the long-term out-
comes of the two procedures. Controlling for both patient and hospital
characteristics, our study showed that patients undergoing TURP were twice
as likely to require reoperation within eight years and appeared to face a
significantly elevated long-term risk of death, compared to patients receiv-
ing the open procedure (4~. These findings raised potentially important
questions about both the safety and the efficacy of TURP compared with
open prostatectomy.
To evaluate further the association between the type of operation re-
ceived by patients and their long-term outcomes, several additional studies
were conducted. The first study sought to determine whether the increased
risk associated with TURP would be found across different time periods and
in different countries. Retrospective cohorts were assembled; these cohorts
consisted of all patients aged 55 through 85 (except those with bladder or
prostate cancer) who underwent prostatectomy between 1977 and 1985 in
Denmark, between 1972 and 1985 in Manitoba, and between 1963 and 1977
in the Oxfordshire region of England (8~. The risk of reoperation was
consistently higher among patients who received a TURP, ranging from a
relative risk of 2.7 at eight years in Denmark to 6.7 at eight years in Oxford.
Also, the risk of death following TURP was consistently higher at five and
eight years, the relative risk of TURP to open being 1.2 to 1.3 at eight
years.
There remained the possibility that physicians were selecting only rela-
tively healthy patients for the open procedure and that increased severity of
illness among TURP patients might explain the excess mortality observed.
Data from a teaching hospital in Manitoba were reviewed to investigate this
possibility. All patients who underwent prostatectomy at the hospital be-
tween July 1974 and December 1983 were identified through the claims
data. Those with bladder or prostate cancer were excluded. All claims
records before and after prostatectomy were identified and used to define
patient covariables, including age, the presence of cancer diagnoses, prior
hospitalizations with high-risk diagnoses, and nursing home residence. A
clinical data base collected by anesthesiologists for a study of all surgical
patients at this hospital was identified, and key clinical variables were ex-
tracted and linked to the prostatectomy records. The linked variables included
the American Society of Anesthesiologists' risk score and medication use.
Among all cases the adjusted relative risk of death within five years was
1.45 (95 percent CI, 1.15, 1.84) (see Table 4~. Similarly, after excluding all
cases with evidence of significant comorbidity, the relative risk remained
OCR for page 88
88
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
TABLE 4 Relative Risks of Death for Patients Receiving Transurethral
(TURP) and Open Prostatectomy, Operated On at Manitoba University
Hospital, 1974-1983, by Selected Demographic and Clinical Characteristics
All Patients Healthiest Patientsa
Characteristics (N = 1650) (N = 557)
TURP vs. Open
prostatectomy 1.45 (1.15, 1.84)b 1.60 (0.93, 2.77)
Age Groups
85+ vs. 55-69 3.75 (2.75, 5.09) 5.92 (2.44, 14.40)
80-84 vs. 55-69 2.77 (2.07, 3.72) 5.22 (2.57, 10.60)
75-79 vs. 55-69 2.35 (1.78, 3.10) 3.54 (1.85, 6.79)
70-74 vs. 55-69 1.48 (1.12, 1.96 1.60 (0.79, 3.24)
Cancer diagnosis
prior to surgery 3.93 (2.92, 5.28) NAC
Hospitalized with high-risk
diagnoses prior to surgery
Within 6 months 1.46 (1.14, 1.87) NA
Within 7-12 months 1.54 (1.13, 2.10) NA
Nursing home resident 1.17 (0.76, 1.80) NA
ASA Score 3+ 1.91 (1.57, 2.36) NA
On digitalis 1.40 (1.10, 1.78) NA
High-risk diagnosis 1.42 (1.15, 1.76) NA
Prostatic hyperplasia
only diagnosis 0.54 (0.38, 0.77) - .0.41 (0.22, 0.74)
NOTE: Cox regression results based on linked claims and anesthesia data
bases.
aHealthiest defined as not resident in nursing home, had no current or previous
diagnosis of cardiovascular disease, had no diagnosis of cancer, took no medica-
tions preoperatively, had no other high-risk diagnosis, and had a physical status
score of 1 or 2 (healthy or mild disease).
bg5 percent confidence intervals in parentheses.
CNot applicable.
SOURCE: Roos et al. (8) .
elevated at 1.60 (95 percent CI, 0.93, 2.77), although the confidence limits
increased because of the smaller sample size.
There remained a concern that the elevated risk might reflect subtle char-
acteristics of patients known to their physicians and recorded in the medical
record but not in either the claims data or the anesthesiologists' study. To
address this concern, the medical records of a sample of TURP and open
patients were abstracted to obtain a broad range of clinical data from patients'
OCR for page 89
USE OF LARGE DATA BASES
89
histories, physical examinations, and laboratory findings at the time of sur-
gery.
The medical record data were used to determine an index of comorbidity
and a measure of functional health, both of which have been previously
demonstrated to predict long-term survival (20,21~. Two Cox regression
models were developed. In one, we used the indices of comorbidity and
functional health to control for differences in illness levels. In the other we
allowed all variables significantly associated with long-term survival into
the model. Using these models, the relative risk of death within five years
of operation was elevated for patients undergoing TURP compared to open
prostatectomy, and it was similar in magnitude to the relative risk obtained
from the claims data alone (Table 5~.
These analyses suggest several conclusions. First, they confirm our ini-
tial observation of increased mortality and reoperation rates among TURP
patients in the original small sample from Maine and Manitoba. Second,
measures of case mix that were obtained retrospectively did not explain the
findings. However, it is important to note that patients may appear similar
based upon retrospective review of their charts, but that the measures ob-
tained retrospectively may not identify significant prognostic differences.
For example, physicians may record characteristics of patients differently,
based on their own assumptions about the relative safety of TURP compared
to open prostatectomy. Nevertheless, because of the large numbers of patients
undergoing TURP and the potential public health importance of the observed
increased mortality following TURP, the evidence we found should not be
TABLE 5 Relative Risk of Death for Patients Receiving
Transurethral (TURP) versus Open Prostatectomy,
Operated On at Manitoba University Hospital, 1974-1983
Variable
Adjusted Relative Risk
(95% confidence interval)
TURP vs. Open
Age 70-74 vs. under 70
Age over 75 vs. under 70
Comorbidity index > 2
Decreased functional statusa
1.59 (1.06, 2.37)
1.69 (1.05, 2.64)
2.23 (1.38, 3.58)
2.52 (1.74, 4.08)
2.66 (1.74, 4.08)
NOTE: Cox regression results based on linked claims and
chart review data, N = 485.
Decreased functional status defined as a Karnofsly score < 70.
SOURCE: Malenka et al. (9).
OCR for page 90
9o
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
ignored. We are pleased that the American Urological Association has
joined with our assessment team to undertake the prospective clinical trials
needed to resolve the issue.
IMPROVING THE USEFULNESS OF
ADMINISTRATIVE DATA BASES
Administrative data have played an important role in stimulating the
current interest in studying the effectiveness of medical care and offer an
important resource for assessments of current treatment patterns. To make
use of their full potential, we should build on their strengths and make the
investment necessary to overcome their limitations.
STRENGTHS
As recognition of the importance of further evaluation of medical prac-
tice has grown, so has advocacy of the Medicare claims files and similar
data bases as sources of data for technology assessment. The assessment of
prostatectomy exploited four major strengths that Medicare data offer for
outcomes research. First, the enrollment file provides not only the popula-
tion counts required for epidemiological studies, but also a means to effi-
ciently ascertain death, eligibility status, and change of residence for long-
term follow-up studies. Second, universal coverage offers the opportunity
to study populations that are free from selection bias and are of sufficient
size to document rare outcomes. Virtually all health care utilization by the
covered population is identified in these files.
Third, individual identification numbers allow records to be linked across
time and providers. Such linkage is essential to longitudinal studies of
health care outcomes and utilization. Finally, the individual identification
numbers provide a mechanism to link Medicare data to other sources of
data. Potential sources of supplemental data include those reported here,
existing clinical data bases, and medical records. It is also feasible to
obtain names and addresses so that individuals could be surveyed to ascer-
tain outcomes not recorded in either the claims themselves or the medical
records, such as functional status and quality of life.
LIMITATIONS
As with any source of data, limitations in Medicare data must be ac-
knowledged and, when possible, overcome. Treatments and diagnoses in
the claims files are recorded in nonresearch settings using International
Classification of Diseases (ICD-9-C~ codes (hospitals) and Common Procedural
OCR for page 91
USE OF LARGE DATA BASES
91
Terminology (CPT-4) codes (physicians). The precision of the codes them-
selves and the accuracy with which they are recorded limit the kind of
studies that may be successfully undertaken. Major surgical procedures
have been found to be accurately coded, and the precision of these codes
allows reasonable cohorts to be defined. In contrast, fine distinctions among
different subgroups of patients with medical conditions are poorly documented
within the existing coding conventions; it would be difficult, for example,
to define a cohort of patients with unstable angina. Similarly, the records
do not document either the timing of the onset of medical conditions within
a hospitalization or the affected side (left vs. right) for procedures or conditions
that may affect either side of the body.
Codes for many new technologies and treatments are rarely introduced in
a timely fashion. Specific codes for coronary angioplasty were introduced
several years after the widespread adoption of the technique in practice.
Finally, the scope of data recorded is limited, and utilization rather than the
incidence of a medical event is recorded. Some patients with adverse out-
comes may not bother or be able to afford to see their physicians. Certain
events (mortality, reoperation) can be accurately measured, but other variables
(clinical risk factors, functional status, quality of life) cannot be ascertained
directly from the claims data.
SUGGESTIONS
These limitations suggest several steps we could take to enhance the
value of administrative data bases for health care research and outcomes
assessment. First, we should improve the completeness and accuracy of the
coding used in claims data bases. Establishing codes for new technologies
as soon as they become eligible for reimbursement would markedly enhance
assessment efforts. Documentation and publication of the accuracy of cod-
ing in administrative data bases by the agency responsible for collecting the
data would enhance the utility of the data bases to all users.
Second, because the scope of the data is limited, additional data will be
required for many analyses. We should be cautious in our strategies for
supplementing data, however. There is a tension between the desire to
collect all possibly relevant data on each patient and the needs of a given
assessment. For example, the specific variables required to study angioplasty
or prostatectomy are not likely to be included in even the most comprehen-
sive data set. Consequently, we should determine efficient, flexible means
of supplementing the data base. These might include not only facilitating
access to medical records to supplement claims data, but also developing
strategies for routine posttreatment interviews to determine functional sta-
tus and quality of life.
OCR for page 92
92
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
REFERENCES
1. Roper, W.L., Winkenwerder, W., Hackbarth, G.M., et al. Effectiveness in
Health Care: An Initiative to Evaluate and Improve Medical Practice. New England
Journal of Medicine 319:1197-1202, 1988.
2. Wennberg, J.E. and Gittelsohn, A.M. Small-Area Variations in Health Care
Delivery. Science 183:1102-1108, 1973.
3. Wennberg, J.E. arid Gittelsohn, A.M. Variations in Medical Care Among
Small Areas. Scientific American 246: 120-134, 1982.
4. Wennberg, J.E, Roos, N.P., Sola, L., et al. Use of Claims Data Systems to
Evaluate Health Care Outcomes: Mortality and Reoperation Following Prostatectomy.
Journal of the American Medical Association 257:933-936, 1987.
5. Barry, M.J., Mulley, A.G., Fowler, F.J., et al. Watchful Waiting vs. Immedi-
ate Transurethral Resection for Symptomatic Prostatism: The Importance of Patients'
Preferences. Journal of the American Medical Association 259:3010-3017, 1988.
6. Fowler, P.J., Wennberg, J.E., Timothy, R.P., et al. Symptom Status and
Quality of Life Following Prostatectomy. Journal of the American Medical Asso-
ciation 259:3018-3022, 1988.
7. Wennberg, J.E., Mulley, A.G., Hanley, D., et al. An Evaluation of Prostatectomy
for Benign Urinary Tract Obstruction: Geographic Variations and the Assessment of
Medical Care Outcomes. Journal of the American Medical Association 259:3027-3030,
1988.
8. Roos, N.P., Wennberg, J.E., Malenka, D.J., et al. Mortality and Reoperation
After Open and Transured~ral Resection of the Prostate for Benign Prostatic Hyperplasia.
New England Journal of Medicine 320:1120-1124, 1989.
9. Malenka, D.J., Roos, N.P., Fisher, E.S., et al. Further Study of the Increased
Mortality Following Transurethral Prostatectomy. Urology. In press.
10. Lave, J., Dobson, A., and Walton, C. The Potential Use of Health Care
Financing Administration Data Sets for Health Care Services Research. Health Care
Financing Review 5 :93-98, 1983.
11. Hatten, J. Medicare's Common Denominator: The Covered Population.
Health Care Financing Review 2:53-63, 1980.
12. Chassin, M.R., Brook, R.H., Park, R.E., et al. Variations in the Use of
Medical and Surgical Practices by the Medicare Population. New England Journal
of Medicine 314:285-290, 1986.
13. McPherson, K., Wennberg, J.E., Hovind, O.B., et al. Small-Area Variation
in the Use of Common Surgical Procedures: An International Comparison of New
England, England and Norway. New England Journal of Medicine 307:1310-1314,
1982.
14. Wennberg, J.E. Dealing with Medical Practice Variations: A Proposal for
Action. Health Affairs 3 :6-33, 1984.
15. Paul-Shaheen, P., Clark, J.D., and Williams, D. Small Area Analysis, A
Review and Analysis of the North American Literature. Journal of Health Politics,
Policy and Law 12:741 -809, 1987.
16. Grayhack, J.T. and Sadlowski, R.W. Results of Surgical Treatment of
Benign ProstaticHyperplasia Pp.125-134InBenignProstaticlIyperplasia. Grayhack,
OCR for page 93
USE OF LARGE DATA BASES
93
J.T., Wilson, J.D. and Scherbenske, M.J., eds. DHEW Publication No. (NIH) 76-
1113. Washington, DC: Government Printing Office, Washington, D.C., 1976.
17. Roos, L.L., Cageorge, S.M., Austen, E., et al. Using Computers to Identify
Complications After Surgery. American Journal of Public [health 75: 1288-1295, 1985.
18. Greenfield, S., Aronow, H.U., Elashoff, R.M., et al. Flaws in Mortality
Data: The Hazards of Ignoring Comorbid Disease. Journal of the American Medical
Association 260:2253-2255, 1988.
19. Jencks, S.F., Williams, D.K., and Kay, T.L. Assessing Hospital-Associated
Deaths from Discharge Data: The Role of Length of Stay and Comorbidities. Journal
of the American Medical Association 260:2240-2246, 1988.
20. Charlson, M.E., Pompei, P., Ales, K.L., et al. A New Method for Classify-
ing Prognostic Comorbidity in Longitudinal Studies: Development and Validation.
Journal of Chronic Diseases 40:373-383, 1987.
21. Stanley, K.E. Prognostic Factors for Survival in Patients with Inoperable
Lung Cancer. Journal of the National Cancer Institute 65:25-33, 1980.
Representative terms from entire chapter:
administrative data
