4
Defining And Assessing Quality Cancer Care

This chapter provides an overview of how quality of care is defined and measured, why quality assessment is important, and how quality information is collected. Evidence of quality problems is then summarized for two common cancers for which an evidence base exists: breast and prostate cancer.

Defining Quality of Care

The quality of health care can be precisely defined and accurately measured, but there are many different perspectives of quality to consider. Patients tend to evaluate care in terms of its responsiveness to their individual needs and may expect and value access to, and choice of services, doctors, and treatments that maximize their ability to work and enjoy life. Physicians may view quality in terms of their ability to exercise their medical judgment to optimize outcomes for patients. From a health plan's point of view, quality might mean efficiency, appropriate use of diagnostic and therapeutic technologies, and maintenance of high levels of patient satisfaction with care. From a public health perspective, quality might be reflected in high levels of access to primary care, effective prevention, and in low morbidity and mortality rates. A challenge to assessing quality is balancing these sometimes divergent perspectives (MeGlynn, 1997).

The Institute of Medicine (IOM) has defined quality as the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge (IOM, 1990). In practical terms, poor quality can mean too much care (e.g., unnecessary tests, medications, or procedures, with associated risks and side effects); too little care (e.g., not receiving a lifesaving surgical procedure); or the wrong care (e.g., medicines that should not be given together, poor surgical techniques) (IOM, 1999). Good quality means providing patients with appropriate services in a technically competent manner, with good communication, shared decision making, and cultural sensitivity.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



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 79
--> 4 Defining And Assessing Quality Cancer Care This chapter provides an overview of how quality of care is defined and measured, why quality assessment is important, and how quality information is collected. Evidence of quality problems is then summarized for two common cancers for which an evidence base exists: breast and prostate cancer. Defining Quality of Care The quality of health care can be precisely defined and accurately measured, but there are many different perspectives of quality to consider. Patients tend to evaluate care in terms of its responsiveness to their individual needs and may expect and value access to, and choice of services, doctors, and treatments that maximize their ability to work and enjoy life. Physicians may view quality in terms of their ability to exercise their medical judgment to optimize outcomes for patients. From a health plan's point of view, quality might mean efficiency, appropriate use of diagnostic and therapeutic technologies, and maintenance of high levels of patient satisfaction with care. From a public health perspective, quality might be reflected in high levels of access to primary care, effective prevention, and in low morbidity and mortality rates. A challenge to assessing quality is balancing these sometimes divergent perspectives (MeGlynn, 1997). The Institute of Medicine (IOM) has defined quality as the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge (IOM, 1990). In practical terms, poor quality can mean too much care (e.g., unnecessary tests, medications, or procedures, with associated risks and side effects); too little care (e.g., not receiving a lifesaving surgical procedure); or the wrong care (e.g., medicines that should not be given together, poor surgical techniques) (IOM, 1999). Good quality means providing patients with appropriate services in a technically competent manner, with good communication, shared decision making, and cultural sensitivity.

OCR for page 79
--> Why Measure Quality of Cancer Care? There are several reasons for measuring the quality of care: To help consumers and purchasers make informed choices about health care (e.g., selecting health care coverage that balances likely health care effectiveness and costs). To help clinicians and patients make informed treatment and referral decisions (e.g., evaluating mortality and quality of life trade-offs when deciding between two alternative treatments for cancer, comparing the relative success of two hospitals for a high-risk surgical procedure). To help clinicians and health plans improve their care (e.g., assessing levels of cancer screening or monitoring surgical complication rates). To determine the impact of new policies and systems (e.g., evaluating the consequences of increasing Medicare enrollment in health maintenance organizations [HMOs]). To provide clinical input to financial decision-making processes (e.g., determining services to be included in an insurer's benefit package). To guide public policy decisions (e.g., resource allocation decisions pertaining to the Medicaid or Medicare programs). How is Quality Measured? Quality assessment is the measurement of quality by expert judgment (implicit review) or by systematic reference to objective standards (explicit review). Quality may be evaluated at any level of the health care system: for physicians and other health care professionals; for hospitals, clinics, rehabilitation centers, and other institutions; for health plans; and for communities. Different approaches to assessing quality have different strengths and weaknesses, and some approaches work better in one setting than another. An example of implicit review is having a clinician review the medical records of a patient and expressing a judgment on whether the care was good or bad. The clinician may base an opinion on years of experience and understanding of the clinical situation for which care was provided. However, the same rating may not be given on another day, and different colleagues might give a different rating. Explicit review provides a more systematic approach and can be based on one or more of three dimensions: structure, process, and outcomes (Donabedian, 1980). ''Structural quality'' refers to health system characteristics, "process quality" refers to what the provider does, and "outcome" refers to patients' health. Although producing good outcomes is the ultimate goal of the health care system, for a variety of technical reasons, using outcome measures to assess quality is not generally the most effective approach (discussed below). Instead, process measures are used. Structural Quality Structural quality refers to characteristics of the health care system that affect its ability to meet the needs of individual patients or communities. These characteristics include clinician characteristics (e.g., board certification, average years of experience, distribution of specialties), organizational characteristics (e.g., staffing patterns, reimbursement method), patient character-

OCR for page 79
--> istics (e.g., insurance type, illness profile), and community characteristics (e.g., per capita hospital beds, transportation system, environmental risks). Structural measures specifically related to cancer quality could include the availability of a multidisciplinary cancer center, a bone marrow transplant unit, or psychological support services. Structural characteristics are often necessary to provide good care, but they are usually insufficient to ensure excellent quality. The best structural measures are those that can be shown to have a positive influence on the provision of care (process quality) and on patients' health (outcomes), although this relationship has not been found for most measures (Brook et al., 1990). Measures of structural quality have long been the key component in accreditation procedures. Various independent organizations accredit hospitals or health plans based on a set of criteria that generally focus on structural measures such as appropriate capacity for the covered patient population. In recent years, accreditation organizations have also been incorporating process and outcome measures into their accreditation procedures. Process Quality Process quality refers to what providers do for patients and how well they do it, both technically and interpersonally. Technical process refers to whether the right choices are made in diagnosing and treating the patient, and whether care is provided in an effective and skillful manner. Whether care is effective can be judged according to evidence from good studies (e.g., clinical trials) that show a link between a particular process and better outcomes. Quality is often measured according to appropriateness criteria or professional standards, but these may or may not conform to available evidence of effectiveness. The quality of evidence is itself rated according to aspects of the study's design and conduct. Reported "levels" of evidence are often used to evaluate the strength of clinical recommendations (see Box 4.1). An intervention or service (e.g., laboratory test, procedure, medication) is considered appropriate if the expected health benefits (e.g., increased life expectancy, pain relief, decreased anxiety, improved functional capacity) exceed the expected health risks (e.g., mortality, morbidity, anxiety anticipating the intervention, pain caused by the intervention, inaccurate diagnoses) by a wide enough margin to make the intervention or service worthwhile (Brook et al., 1986). Some also distinguish a subset of appropriate care that they term necessary or crucial care. They consider care necessary if there is a reasonable chance of a nontrivial benefit to the patient and if it would be improper not to provide care. In their view, such care is important enough that it might be considered ethically unacceptable not to offer it (Kahan et al., 1994; Laouri et al., 1997). Criteria of appropriateness can be used to measure the overuse of care, which occurs when expected risks exceed expected benefits (which is a problem because of treatment complications and wasted resources), and the underuse of care, which occurs when people are not receiving care that is expected to improve their health. A good example of the use of process measures can be found in the 1988 General Accounting Office (GAO) assessment of the use of seven "breakthrough" cancer treatments in the United States from 1975 to 1985 (e.g., adjuvant chemotherapy for breast cancer) (USGAO, 1988). All of the treatments had been proven to extend patients' survival in controlled experiments, and for many, the evidence had been available for several years. Data for 1985 show considerable variation in use of these innovative therapies (Table 4.1). The results illustrate the

OCR for page 79
--> problem of a slow rate of diffusion of innovation of cancer care, but optimal levels of use of each intervention are not known. One factor that might account for some of the underuse is possible underreporting of treatments in the Surveillance, Epidemiology, and End Results Program (SEER) cancer registry data (see description of SEER Program below). BOX 4.1 Levels of Evidence Applied to Clinical Research The "hierarchy of evidence" applied to clinical research (i.e., when the question is whether a given treatment is effective in patients with a specific type of cancer) is well established and agreed upon. The following version is taken from the Well-respected U.S. Preventive Services Task Force, proceeding from the most reliable to the least reliable type of evidence (i.e., from grade I to grade III): I Evidence obtained from at least one properly randomized controlled trial. II-1 Evidence obtained from well-designed controlled trials without randomization. II-2 Evidence obtained from well-designed cohort or case-control (epidemiologic) studies. II-3 Evidence obtained from multiple time series. with or without the intervention—dramatic results in uncontrolled experiments (e.g., the results of the introduction of penicillin treatment in the 1940s) could also be regarded as this type of evidence. III Opinions of respected authorities, based on clinical experience, descriptive studies and case repeals, or repeals of expert committees. SOURCE: U.S. Department of Health and Human Services, 1996. TABLE 4.1 Selected Results from 1988 GAO Report Innovative Therapy Percentage of Eligible Patients Treated, 1985a Adjuvant chemotherapy for breast cancer (premenopausal node-positive) 63 Adjuvant chemotherapy for node-positive colon cancer 6 Adjuvant radiation therapy for rectum cancer 40 Chemotherapy for limited small-cell lung cancer 75 Chemotherapy for non-seminoma testicular cancer 50 Chemotherapy for Stage IIIB or IV Hodgkin's disease 90 Chemotherapy for diffuse intermediate or high grade non-Hodgkin's lymphoma 80b a "Treated" includes the SEER treatment data fields of "given" and "planned.'' b Ten percent decrease from 1979 to 1985. SOURCE: USGAO, 1988.

OCR for page 79
--> Another way to measure process quality is to determine whether care meets evidence-based professional standards. This assessment can be done by creating a list of quality indicators describing a process of care that should (or should not) occur for a particular type of patient or clinical circumstance. Quality indicators are based on standards of care, which are found in the research literature and in statements of professional medical organizations or determined by an expert panel. The performance of physicians and health plans is assessed by calculating rates of adherence to the indicators for a sample of patients (see Chapter 6 for a discussion of quality assurance programs). Current performance can be compared to a physician's or plan's prior performance, to the performance of other physicians and plans, or to benchmarks of performance. Indicators can cover a specific condition (e.g., patients diagnosed with colon cancer who do not have metastatic disease should be offered a wide resection with anastomosis within six weeks of diagnosis), or they can be generic, covering general aspects of care regardless of condition (e.g., patients prescribed a medication should be asked about allergies to medications). Interpersonal quality refers to whether the clinician provides care in a humane manner consistent with the patient's preferences. It includes such topics as whether the clinician supplied sufficient information for the patient to make informed choices and involved the patient in decision making. It is generally assessed using patient survey data. Good process measures are based on research studies and supported by professional consensus. They are also flexible with respect to patient preferences. Some patients may not want what most people would consider proper care. Indicators can be constructed so that they are scored favorably if care was offered but declined. However, there has to be some recognition that a perfect score on indicators is not necessarily a feasible or even a desirable goal. For example, although chemotherapy is highly recommended after surgical resection for colon cancer involving the lymph nodes, some patients might decline treatment because they do not wish to experience its associated toxicities. Therefore, 100 percent adherence may not be a reasonable target for an indicator specifying adjuvant chemotherapy for these patients. Furthermore, such a target might also create incentives to ignore patient preferences in making treatment decisions. An alternative approach would be for an indicator to specify that chemotherapy was offered or recommended. The best process measures are those for which there is evidence from research that better process leads to better outcomes. For example, adjuvant chemotherapy has been shown in several randomized controlled trials to improve survival after surgery for Duke's C colon cancer (NIH, 1990a); performing routine mammography identifies breast cancer at an earlier stage when it is more curable (Kerlikowske et al., 1995); perioperative chemotherapy and radiation therapy have been shown to increase survival for patients with rectal cancer (Krook et al., 1991; Moertel, 1994). Unfortunately, research has not covered all aspects of standard medical practice related to cancer (or other types of disease), so in these cases, expert consensus is used to decide which processes are important measures of quality. If there is not strong consensus supporting the value or superiority of a clinical practice, it generally is not used as a quality measure. Several studies outside of oncology have tied process measures to outcomes. In a study of five hospitals in Los Angeles County, mortality rates were examined for patients who had coronary angiography and for whom a revascularization procedure was deemed "necessary" by explicit criteria. Those who received necessary revascularization within one year had a mortality of 9 percent, compared to 16 percent for those who did not. Those receiving "necessary" revascularization also had less chest pain at follow-up (Kravitz et al., 1995).

OCR for page 79
--> Other research also demonstrates the link between process and outcome. In a study of Medicare enrollees hospitalized with congestive heart failure, heart attack, pneumonia, and stroke in 1981-1982 and 1985-1986, better process quality of care was significantly associated with lower mortality rates 30 days after hospitalization. Patients who went to hospitals in the lowest 25th percentile on a set of process-of-care measures had a 39 percent increased likelihood of dying within 30 days after hospital admission compared to patients who went to hospitals in the highest 25th percentile, after adjustment for patient sickness at admission (Kahn et al., 1990). Outcomes Measurement of health-related outcomes is probably the most intuitively appealing approach to quality monitoring. "Outcomes" refers to the results of a health care delivery process. The three main types of outcomes are (1) clinical status, (2) functional status, and (3) consumer satisfaction. These outcomes, however, depend on myriad factors besides medical care, including characteristics of the patient and the disease process. Outcomes are thus valid measures of quality only to the extent that they have been associated with prior medical processes in well-designed studies. Clinical Status Clinical status is considered with the biological outcomes of disease, for example, how organ systems are functioning. Physicians have traditionally used clinical status to determine treatment success or failure. Cancer research, for example, has long used the outcome of five-year overall survival or five-year progression-free survival. Other clinical measures might include postoperative wound infections or catheter infections. Proxy measures (sometimes called surrogate end points or intermediate outcomes) are also used. They do not measure the outcome of concern directly, but they do provide evidence or likelihood of a good outcome. For example, response rate (decrease in tumor size) is used to assess the impact of therapy, but the goal of therapy may be prolonged life. When used as a measure of quality or as an indicator of impact of therapy, it is important for there to be evidence that the proxy measures are really serving as a proxy. In other words, the effect of the intervention on the proxy should be concordant with the effect on the cancer itself (Schatzkin et al., 1996). Functional Status Measures of functional status assess how disease affects an individual's ability to participate in physical, mental, and social activities. They also cover the ability to meet the regular responsibilities of one's roles in society (e.g., parent, bank teller, volunteer). Health-related quality of life is similar to functional status but includes the person's sense of well-being as well as factors external to the individual such as social support. Functional status assessment is based on the premise that many aspects of health are important to patients and will influence their treatment decisions. Such assessment could help

OCR for page 79
--> someone choose between a treatment that would give many more years of life with major incapacitation and a treatment that would give fewer years of life with full function. For example, treatment success or failure for prostate cancer has historically been assessed by the clinical outcome of whether the patient died from prostate cancer. However, functional status measures would incorporate other treatment outcomes, such as the patient's urinary, sexual, and bowel function (Litwin et al., 1995). Functional status assessment often includes the degree to which disease limits one's ability to participate fully in activities of daily living. Depending on the type of cancer and phase of illness, such activities could include going to work or caring for children. In patients with more advanced disease, however, assessment of whether they are able to go to the market for groceries or to bathe or dress themselves may be more relevant. Performance status is a measure of functional status often used in oncology clinical trials. The Karnofsky Performance Status (Karnofsky and Burchenal, 1949) is a rating of patients' functional status that has been used in clinical trials since 1949 (Grieco and Long, 1984). The rating is performed by a physician or nurse. It has been found to be a strong predictor of survival in some patient populations, most notably patients with lung cancer. However, it covers only one aspect of quality of life—physical performance—and, although significantly correlated with quality of life, accounts for less than 50 percent of the variability in patients' own ratings of their quality of life. Although clinician-rated measures have value, the field is moving more toward the use of patients' assessments of functional status and quality of life (Reifel and Gantz, in press), which are preferable models for quality assessment. Examples of patient-based measures include the Cancer Rehabilitation Evaluation System (CARES) (Ganz et al., 1992b; Schag and Heinrich, 1990), the Functional Living Index-Cancer (FLIC) (Schipper et al., 1984), and the Breast Cancer Chemotherapy Questionnaire (BCQ) (Levine et al., 1988). Consumer Satisfaction Consumer satisfaction refers to patients' feelings about the care they receive and is generally measured by patient surveys. There is a relationship between satisfaction and adherence to treatment regimens. Patients who are satisfied are more likely to take their antibiotics properly (Bartlett et al., 1984), to follow treatment recommendations (Hsieh and Kagle, 1991), and to return for follow-up visits (Deyo and Inui, 1980). Thus, the physician has an incentive to please his or her patients as part of the treatment—so that they will be more likely to follow the physician's advice. Furthermore, dissatisfaction with care can lead patients to switch clinicians and health care institutions (Reichheld, 1996; Rubin et al., 1993; Young et al., 1985). Although consumers are the best source to evaluate their interpersonal care, one limitation of satisfaction ratings is that consumers cannot always tell if the care was appropriate or technically good (Aharony and Strasser 1993); research has not shown a consistent relationship between consumer satisfaction and technical quality of care (Cleary and McNeil, 1988; Davies and Ware, 1988; Hayward et al., 1993). A kind and caring physician may provide care that is technically poor (Aharony and Strasser, 1993). Also, consumer satisfaction may vary with expectations. For example, patients who have a history of poor access to health care may be so appreciative when they actually see a physician that they may report high satisfaction regardless of how well care was delivered. Therefore, it is best not to rely on satisfaction ratings to measure technical quality.

OCR for page 79
--> Clinical and functional status can be measured for more than one purpose. They are described here in the context of quality of care, in which outcomes are compared between two institutions as a sign of whether one institution is delivering better care (with the presumption that better care leads to better outcomes). However, these measures are also used clinically to track a patient's progress and in clinical trials to measure the efficacy or effectiveness of a new drug or intervention. The same measures can sometimes be used for both purposes, but certain measures are better suited for one purpose or the other. Five-year survival rates, for example, are a standard measure used in studies of new cancer treatments. However, when measuring quality of care for purposes of accountability or quality improvement, outcomes with a shorter time horizon than five years are generally needed. If two institutions are compared using five-year survival rates for colon cancer, one institution might have higher survival rates than the other. However, in the interim, there might have been a change in staff or a revamping of procedures that improved or weakened the quality of care at the hospitals, thereby making the comparison historically, but not practically, valuable. Attributes of Good Outcomes Measurement Outcomes measurement has become increasingly popular in the past few years, perhaps because outcomes are the most direct measure of the health of a population. For example, outcomes can be used to assess the quality of care that a health system provides to its cancer patients: outcomes can measure the survival and quality of life of women diagnosed with breast cancer and whether they are satisfied with their care. Their interpretation, however, must be tempered by the fact that many factors other than medical care influence outcomes. Mortality trends are the principal yardstick used to measure overall progress against cancer because they capture the total effects of prevention, early detection, and treatment. The most recent assessment of mortality trends is encouraging—U.S. cancer mortality rates fell in the early 1990s for the first time since statistics have been collected (Wingo et al., 1998). It is difficult to estimate precisely the relative importance of factors contributing to this decline, but much of it stems from reduced smoking (among men) and other improvements in prevention (Cole and Rodu, 1996). Worthwhile advances in treatment may not be easily detected in overall mortality rates. Site-and stage-specific survival rates are better measures of treatment effects when adjusted for patient characteristics (e.g., prognostic factors such as age and extent of other illnesses). The best outcome measures have certain key features or are used in a particular manner. First, they should be risk adjusted (or case-mix adjusted), in other words, adjusted for factors that influence outcomes but are beyond the health care system's control (e.g., age, socioeconomic status, comorbidities). Without such adjustment, it is impossible to determine how much of the improvement or worsening of outcomes is due to the care delivered (or not delivered) by the health care system. A radiation oncologist who receives referrals of patients with multiple medical problems is likely to have worse outcomes than one who takes only patients with early-stage disease and few comorbidities, even though the former may be a better radiation oncologist. To make comparisons in such a system, adjustments are needed for how ill the patients are. Risk adjustment is complex, and the factors to use in risk adjustment must be selected carefully to allow for accurate interpretation of the outcomes (Iezzoni, 1996).

OCR for page 79
--> Outcomes are only useful in quality assessment when the specific processes of care that relate to them are known. Then, if the outcomes are not as good as they should be, it is clear what aspects of care have to be addressed to try to improve them. In other words, if you do not know how an outcome relates to processes of care, you will not know what to do to improve the outcome when you find that it is poor at a particular hospital. It also helps to measure outcomes from different perspectives. For example, palliative chemotherapy for metastatic cancer may decrease a patient's tumor burden and potentially prolong life, but it might also cause severe fatigue and weight loss, so the patient's clinical status might improve while functional status declines. It is also important to use outcomes that can be reasonably related to the health care sys-tem-and the particular part of the system—that one is assessing. It is not reasonable to hold a provider or plan accountable for an outcome, unless the outcome is a direct result of the way care is provided. Sometimes, however, a single outcome may be influenced by many factors over many years, of which health care is only a part. Outcomes for lung cancer, for example, may reflect the quality of care provided over many years, including the quality of smoking prevention and cessation counseling for adolescents and adults. Outcomes for breast cancer may in part depend on the quality of screening and early detection. Given the frequency with which most patients change clinicians or health plans, it could be difficult to relate the quality of any one clinician or plan to some outcomes. Similarly, if one is trying to use outcomes to assess the quality of surgeons treating a sarcoma at various hospitals, it is important to distinguish whether the outcomes are related to the skill of the surgeon, competence of the surgical team, or organizational characteristics of the hospital. One might also want to consider the skill of the medical oncologist prescribing neoadjuvant chemotherapy. For breast cancer, treatment may depend upon an oncologist, a surgeon, and a radiation oncologist. It can be difficult to distribute responsibility among them. In addition, outcomes should be measured on samples that are large enough to detect differences in quality. Adverse outcomes are often uncommon events, so large samples are needed to detect clinically meaningful differences between hospitals. To detect a difference of 2 percentage points in the rate of catheter infections between two hospitals (e.g., 5 percent for one and 7 percent for the other), each hospital would have to have at least 1,900 catheterized patients. In summary, many challenges are inherent in using outcomes to measure quality of care. If these are not addressed, it is difficult to determine whether different outcomes observed among the patients of three physicians are attributable to the physicians themselves. Process measures have their own challenges (e.g., one must make sure that there is a proven link between the process and a desired outcome), but such measures can be quite effective in showing whether providers are doing what they should so that their patients have the best chance of achieving good outcomes. There has been more experience using process measures than outcomes measures to assess quality, and many quality assessment systems depend primarily or exclusively on process measures. However, interest in improving outcomes measurement is increasing, so that outcomes might be used along with process measures to provide more useful assessments of health care quality. In conclusion, to assess quality of care, measures of structure, process, or outcome can be used. If outcomes measures are used, care must be taken to account for differences that might simply reflect differences in other factors, such as patient selection or case mix. If structure or process measures are used, they should be associated with the desired outcomes. In addition, to make inferences about quality, a measure must be compared to a standard.

OCR for page 79
--> Variations In Care Simply comparing variations in the structure or process of care does not provide an evaluation of the quality of care, although it may point to potential quality problems that merit further inquiry. In one such study of variation, five-year survival rates during 1983-1991 varied markedly for several cancer sites. For women with breast cancer, for example, five-year survival ranged from 71.0 percent in Iowa to 79.9 percent in Hawaii (Farrow et al., 1996) (Table 4.2). These differences persisted after adjusting for age and stage. For all cancers other than ovary and bladder, one or more regions were found whose survival rates differed significantly from the overall mean. These differences persisted and were even more pronounced when the analysis was limited to patients less than 70 years of age with local-stage surgically treated disease. However, other important case-mix adjusters, such as the presence of comorbid illnesses, were not included in the model, so interpretation of these results is difficult. Thus, it is not clear whether these regional variations in survival from breast cancer reflect differences in patient populations, regional differences in quality of care, or other factors. TABLE 4.2 Five-Year Survival Comparisons Across Nine SEER Sites, Non-Hispanic Whites, 1983-1991 Cancer Site Range of Relative Risk of Death for All Patients Across Sites (adjusted for sex, age, and stage) Range of Relative Risk of Death—Local Disease, Age <70 (adjusted for surgical treatment) Range of 5-Year Survival All Patients Across Sites for All (unadjusted) Stomach 0.89-1.21 0.69-1.32 10.0-14.9 Colon 0.90-1.10 0.87-1.15 47.1-53.3 Rectum 0.91-1.09 0.76-1.17 45.6-52.4 Lung 0.93-1.12 0.74-1.19 10.5-16.1 Breast 0.82-1.11 0.64-1.34 71.0-79.9 Uterus 0.81-1.21 0.84-1.26 73.2-84.0 Ovary 0.91-1.08 0.82-1.16 34.1-39.2 Prostate 0.84-1.12 0.70-1.20 51.9-64.0 Bladder 0.91-1.15 0.84-1.16 58.4-64.2   SOURCE: Farrow et al., 1996. How is Quality-Of-Care Information Collected? Data for quality assessment can come from several sources. First, administrative records are widely available, and although they are limited in clinical detail, they can be used to show intensity or patterns of utilization. For example, they can be used to determine whether a patient with large-cell non-Hodgkin's lymphoma (NHL) received at least six months of chemotherapy and whether the patient had a white blood cell count performed before receiving chemotherapy. Second, medical records can provide greater clinical detail, the recorded medical history, the results of laboratory tests, and the treatment plan. For example, the medical record can show

OCR for page 79
--> whether the patient with NHL was neutropenic, whether proper components of the physical examination were performed, and whether chemotherapy was administered appropriately. Third, patient surveys can provide additional useful information. Patients can report on what happened during a clinical encounter and thereby provide information relevant to the processes of care. They can also rate their satisfaction with care and provide information on outcomes such as functional status. It is generally more expensive and time-consuming to collect information from medical records and from patients than from administrative data. Cancer registries are also a potential source of information. They collect information on type of cancer, histology, stage at diagnosis, patient age, and initial course of treatment (whether the patient received surgery, chemotherapy, and radiation therapy that would normally be prescribed as part of the initial treatment plan). Registries exist at the regional, state, national, and international levels. There are two main national registries: the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute (NCI) and the National Cancer Data Base (NCDB) (Swan et al., 1998). The SEER program was established as a result of the National Cancer Act of 1971 to assemble, analyze, and distribute information on the prevention, diagnosis, and treatment of cancer. Cancer is the only chronic disease (aside from HIV/AIDS) for which a national surveillance program exists. The program routinely collects information from designated population-based cancer registries in different parts of the country. The different areas have been chosen for their capacity to maintain a cancer reporting system as well as for their ability to report epidemiologically significant population subgroups. Currently, 14 percent of the U.S. population is represented by the nine geographic areas that make up the SEER program's database. Goals of the SEER program include the following: compiling (with the help of the National Center for Health Statistics) estimates of cancer incidence and mortality in the United States; discovering trends and unusual changes in specific cancers based on their geographic, demographic, and social characteristics; providing information about trends in therapy, changes in the extent of disease (stage at diagnosis), and changes in patient survival; and promoting studies that identify the factors that can be controlled through intervention strategies. Health service researchers have linked SEER to Medicare administrative files to evaluate patterns of care, the use of health services, and the costs of treatment (Potosky et al., 1993; Edwards, personal communication to Maria Hewitt, November 1998). Many locations outside of the SEER program's area maintain cancer registries. The National Program of Cancer Registries of the Centers for Disease Control and Prevention (CDC) is bolstering states' capabilities to monitor cancer trends (CDC, 1998). The National Cancer Data Base is a joint project of the Commission on Cancer (COC) of the American College of Surgeons (ACoS) and the American Cancer Society (ACS) to facilitate community, hospital, state, and national assessment of care of patients with cancer (Menck et al., 1997). It began in 1989, and 1,600 hospitals currently report data on 600,000 new cases annually to the NCDB (an estimated 58 percent of new cancer cases) (NCDB, 1998; Swan et al., 1998). NCDB collects information on patient characteristics, tumor characteristics, first course of treat-

OCR for page 79
--> staged. Inappropriate surgery can have significant effects on quality of life because the potential side effects of radical prostatectomy include permanent urinary and sexual dysfunction. Numerous studies have illustrated the prognostic usefulness of pretreatment PSA, clinical stage, and Gleason score in predicting posttreatment outcomes such as risk of recurrence (American Joint Committee on Cancer, 1997; Pisansky et al., 1997). Partin et al. (1993) have developed tabulated estimates for risk of the tumor spreading (called extracapsular extension) using the Gleason score (indicating tumor differentiation) and PSA. The goal of this approach is to attempt to improve the prediction of pathological stage for patient counseling and treatment planning. Estimates from their original tables have been improved by pooling data from patients across multiple facilities (Partin et al., 1997), but concerns about patient representativeness may limit the use of these tables as decision aids for physicians. In addition to PSA, Gleason score, stage, and patient comorbidity can provide independent prognostic information about treatment outcomes. Experts in urology and radiation oncology at academic treatment centers around the United States agree about the importance of comorbidity assessment as part of the pretreatment workup, but there is considerable variation in the methods used for such assessment (Schuster et al., 1998). Suggested information to be used includes: Karnofsky performance status; patient self-reported activity levels; obesity; and history of cardiac disease, vascular disease, pulmonary disease, hypertension, diabetes, and surgeries. Pretreatment urinary, bowel, and sexual functioning have most commonly been assessed by patients' verbal reports. Some physicians have reported using the American Urological Association symptom score to assess obstruction; formal assessment of potency, voiding symptoms, or continence is rarely performed on a routine basis. Although there is evidence in the literature that PSA, stage, Gleason score, and patient comorbidity provide useful prognostic information when treating patients, there is no evidence indicating whether performing these assessments prior to initiating treatment improves patient outcomes. Given the absence of process-outcomes links for the pretreatment evaluation, developing process measures for this aspect of prostate cancer care would have to be based completely on expert opinion. At present, there are no specific guidelines for the staging, workup, or pre-treatment assessment of patient comorbidity. Choice of Treatment Modality The modality used for primary treatment of prostate cancer varies depending on stage of disease, age or life expectancy, and patient preference. Treatment of localized prostate cancer (T1 or T2) can include surgery (radical prostatectomy), radiation therapy (external beam, brachytherapy, or conformal radiation therapy), or expectant management (watchful waiting). However, surgical treatment is not recommended for patients whose life expectancy is less than 10 years because the risks of surgery outweigh the survival benefit (Talcott, 1996). In addition, conformal radiation therapy is still being studied for efficacy and side effects (compared to standard external beam radiation therapy), but it has not yet been widely adopted as standard practice among radiation oncologists. Definitive evidence is lacking about the comparative efficacy of alternative treatment modalities for treating early-stage prostate cancer. The information used to make such decisions may have varying accuracy depending on its source: for example, clinicians' assess-

OCR for page 79
--> ments of posttreatment complications have been found to greatly underestimate the rate reported by patients themselves (Litwin et al., 1998). This finding may suggest that a potentially important area for quality assessment is differences across providers in the patient counseling process. A specific recommendation from the American Urological Association's (AUA's) clinical guidelines on the management of clinically localized prostate cancer is that all alternative treatment modalities (radical prostatectomy, radiation therapy external beam, interstitial treatment—and expectant management) should be presented to every patient (Middleton et al., 1995). Thus, a potential quality indicator could include whether these recommendations are followed by urologists. Complications Associated With Primary Treatment Of Prostate Cancer Estimates of complications resulting from primary treatment of prostate cancer vary widely across facilities even when stratifying by treatment modality: surgery, external beam radiation, or brachytherapy (interstitial radiation treatment or seed implants) (Middleton et al., 1995). After radical prostatectomy, rates of stress incontinence range from less than 10 to 50 percent and impotence rates range from 25 to 100 percent across series reports. Complications following external beam radiation included proctitis, with rates ranging from less than 10 percent to more than 50 percent; cystitis, ranging from 0 to 80 percent; and impotence, ranging from less than 10 percent to nearly 40 percent. Similarly, complication rates reported for brachytherapy range from 0 to 75 percent for proctitis, less than 10 percent to 90 percent for cystitis, and less than 10 percent to 75 percent for impotence. While these widely varying complication rates may reflect differences in quality of care, it is difficult to draw conclusions based on this type of information (Wasson et al., 1993). First, there may be differences in the way the data were collected, which could account for variations in rates of complications. Second, there may be systematic differences in patient case mix (disease severity and comorbidities) across facilities, and these differences must be accounted for before comparing outcomes across institutions. Even if series reports could be adjusted for case mix, there is usually little information available to link differences in results to differences in the technical process of care. Finally, these series report data from only a small number of providers, often large academic clinics. The results for such providers may not represent those of other institutions or clinics. Effectiveness of Radiation Equipment In Treating Localized Prostate Cancer An early American College of Radiology Patterns of Care study examined the association between types of radiation equipment (a structure measure) and localized prostate cancer treatment outcomes (Hanks et al., 1985). Facilities that used cobalt units were found to have higher stage-adjusted rates of disease recurrence than facilities that used linear accelerators or betatrons. The use of cobalt equipment was also correlated with other structural indicators: these facilities had lower percentages of patients who were staged, had lower staff-patient ratios, and were more

OCR for page 79
--> likely to have parttime therapists, compared to national averages. From these results, the authors recommended that facilities using cobalt units should upgrade their treatment equipment, give palliative treatment only, or close. While this study helped to show that cobalt units were not as good as other types, the evidence available when the care was provided did not indicate that cobalt use was inappropriate. Therefore, this study was quite valuable in showing how to improve care, but it is not evidence of poor quality. Quality has to be judged by the level of knowledge and standards in place at the time care was delivered. Treatment of Advanced Prostate Cancer Treatment for advanced prostate cancer is palliative. Data from randomized controlled trials demonstrate a survival benefit as well as relief from bone pain by treatment with androgen ablation (the elimination of sources of male hormone such as testosterone), which can include orchiectomy alone, monotherapy with a luteinizing hormone-releasing hormone (LHRH) analogue, or "maximal androgen blockade" with either orchiectomy or an LHRH analogue and anti-androgen therapy (Garnick, 1996). When prostate cancer progresses on androgen ablation therapy, treatment is less effective; however, various drugs (ketoconazole or aminoglutethimide, estramustine, suramin, mitoxantrone with prednisone or steroids) can improve pain control and quality of life (Garnick, 1996). Because patients with prostate cancer that has metastasized to the bone often suffer excruciating pain, a primary focus in the care of patients with metastatic prostate cancer is control of their pain, with either narcotics, radiation therapy, or chemotherapy. So, although advanced prostate cancer is not curable, multiple treatment options exist and there is evidence in the scientific literature that they improve quality of life and, in some cases, prolong survival. Thus, there is sufficient evidence for process-outcomes links in advanced prostate cancer that process measures could be developed to evaluate the quality of care. Prostate Cancer Summary Prostate cancer provides a particular challenge for quality-of-care assessment: methods for early detection are available, but there is not yet definitive information about whether early detection improves survival. There are a number of treatment modalities for early-stage disease, but there is not definitive information about the efficacy of early treatment. The results of the PLCO trial will better inform decisions about whether routine screening for prostate cancer should be performed and for whom; and the results of the PIVOT trial will provide information about the efficacy of primary treatment of localized prostate cancer by surgery. One candidate indicator for prostate cancer quality assessment is to identify whether information about alternative treatment modalities was presented to patients, as recommended by the AUA's practice guidelines (Middleton et al., 1995). A second candidate indicator may be to assess the rates of surgical treatment among men with life expectancies less than 10 years, using age 70 to represent a proxy for 10-year remaining life expectancy for the average patient (a high rate of surgical treatment in men with a life expectancy of less than 10 years would be an indicator of poor quality).

OCR for page 79
--> At present, available performance measures do not include quality indicators for prostate cancer treatment (e.g., measures of the National Committee on Quality Assurance and Foundation for Accountability). Investigators at RAND are developing candidate quality indicators based on a structured review of the literature, key informant interviews of prostate cancer experts, and focus groups with patients as part of a RAND study funded by the Bing Foundation. The next phase of this research will be to test the reliability and validity of these candidate measures in evaluating the quality of care, as well as exploring potential process-outcomes links. Key Findings Good indicators of quality are based on evidence from rigorous research, which is not available for most aspects of cancer care. For those aspects of care that have been evaluated, the quality of health care can be precisely defined and accurately measured. Measures of structure, process, and outcomes can all be used to assess quality. An outcomes indicator that is often used to evaluate cancer care has been five-year survival, but more timely and practical measures are becoming available to more precisely assess factors related to health care that can affect outcomes. Process measures can serve as good quality indicators when research has proved that a given process leads to better outcomes. Examples of good process measures for breast cancer include use of screening mammography, use of radiation therapy following breast conserving surgery, and use of adjuvant therapy among women with local or regional breast cancer. In other cases, research suggests that one process does not have an advantage over another in terms of outcomes, so patient preferences should dictate the course of care. For many women with breast cancer, for example, optimal care involves presenting information on alternative treatments and supporting an informed choice. Sometimes, research suggests that providing a service does not have a favorable impact on outcomes, indicating that the service should not be provided. Most elderly men with prostate cancer, for example, would not likely benefit from radical prostatectomy if their life expectancy is less than 10 years. High rates of surgery among very old men could indicate that surgery is being performed too often when there is no expected benefit (and there is potential harm from surgery). Two national databases are available with which to assess the quality of cancer care, but each has limitations in the context of evaluating quality of care. The SEER cancer registry has been valuable when linked to Medicare and other insurance administrative files to assess quality of care for the elderly and other insured populations. It is also useful in identifying cases for in-depth studies of quality-related issues. The SEER registry, however, covers only 14 percent of the U.S. population and thus may not adequately represent the diversity of systems of care. Finding ways to capture measures of process of care, treatment information, and intermediate outcomes and improving the timeliness of reporting would enhance the registry's use in quality assessment. The National Cancer Data Base now includes information on more than one-half of all newly diagnosed cases of cancer and many of the demographic, clinical, and health system

OCR for page 79
--> data elements needed to assess quality of care. The NCDB does not, however, include important aspects of care that take place in outpatient settings. The NCDB has not yet been widely used to assess quality of care but, if enhanced, would have great potential for doing so. It is difficult to evaluate the quality of breast and prostate cancer care from the available evidence because many studies have relied on data from the 1980s, and the care evaluated does not represent current practice; many studies are difficult to interpret since dissimilar groups of patients are compared (e.g., insufficient controls for important clinical characteristics such as comorbidity); studies are confined to a small group of patients, in one or a few institutions, states, or health plans, making it difficult to generalize to all cancer patients; and studies are often based on data from cancer registries, which may not accurately represent some aspects of care (e.g., certain treatments may be underreported). National studies of recently diagnosed individuals with cancer are necessary, using information sources with sufficient detail to allow appropriate comparisons. Ways must be found to produce information from these studies quickly, while they are still relevant to contemporaneous conditions. Although the available evidence has limitations, it is suggestive of quality problems in cancer care. For women with breast cancer, many do not appear to be receiving indicated radiation therapy after breast conserving surgery. Of equal concern, many women with appropriate indications do not appear to be receiving adjuvant chemotherapy. Both treatments are known to improve outcomes. Furthermore, there is evidence of poor quality in essential aspects of the diagnostic process that is likely to compromise outcomes (e.g., inadequate biopsies, poor reporting of pathology studies). Evidence also suggests that a significant number of women with breast cancer and men with prostate cancer are not receiving information about the full range of treatment options available to them. References Acheson MB, Patton RG, Howisey RL, Lane RF, Morgan A. 1997. Histologic correlation of image-guided core biopsy with excisional biopsy of nonpalpable breast lesions. Archives of Surgery 132:815-821. Aharony L, Strasser S. 1993. Patient satisfaction: What we know about and what we still need to explore. Medical Care Review 50:49-79. American Cancer Society. 1998. Cancer Facts and Figures—1998. Atlanta, GA. American Cancer Society. 1999. Cancer Facts and Figures—1999. Atlanta, GA. American Joint Committee on Cancer. 1997. American Joint Committee on Cancer, Cancer Staging Manual, 5th edition, ID Fleming, JS Cooper, DE Henson, et al., (eds.) Philadelphia: Lippincott-Raven. Ballard-Barbash, R, Potosky A, et al. 1996. Factors associated with surgical and radiation therapy for early stage breast cancer in older women. Journal of the National Cancer Institute 88(11): 716-726.

OCR for page 79
--> Bartlett EE, Grayson M, Barker R, et al. 1984. The effects of physician communications skills on patient satisfaction, recall, and adherence. Journal of Chronic Diseases 37(9-10):755-764. Beam CA, Layde PM, Sullivan DC. 1996. Variability in the interpretation of screening mammograms by U.S. radiologists. Findings from a national sample. Archives of Internal Medicine 156(2):209-213. Bonadonna G, Valagussa P. 1985. Adjuvant systemic therapy for resectable breast cancer. Journal of Clinical Oncology 3(2): 259-275. Bostwick DG, Myers RP, Oesterling JE. 1994. Staging of prostate cancer. Seminars in Surgical Oncology 10:60-72. Brook R, Chassin M, Fink A. 1986. A method for detailed assessment of the appropriateness of medical technologies. International Journal of Technology Assessment in Health Care 2:53-63. Brook R, Park R, Chassin M, et al. 1990. Carotid endarterectomy for elderly patients: Predicting complications. Annals of Internal Medicine 113:747-753. Centers for Disease Control and Prevention. 1998. The National Program of Cancer Registries AT-A-GLANCE 1998. http://www.cdc.gov/nccdphp/dcpc/npcr/register.htm. Cleary P, McNeil B. 1988. Patient satisfaction as an indicator of quality care. Inquiry 25:25-36. Cole P, Rodu B. 1996. Declining cancer mortality in the United States. Cancer 78:2045-2048. Correa RJ. 1998. American Urological Association response to AHCPR notice of assessment of PSA test. American Urological Association. Baltimore, MD. Davies A, Ware J. 1988. Involving consumers in quality of care assessment. Health Affairs 7:33-48. Deyo R, Inui T. 1980. Dropouts and broken appointments: A literature review and agenda for future research. Medical Care 18:1146-1157. Donabedian A. 1980. Explorations in Quality Assessment and Monitoring , Volume I: The Definition of Quality and Approaches to Its Assessment . Ann Arbor, MI: Health Administration Press. Early Breast Cancer Trialists' Collaborative Group. 1992. Systemic treatment of early breast cancer by hormonal, cytotoxic, or immune therapy. Lancet 399:1-71. Early Breast Cancer Trialists' Collaborative Group. 1998. Tamoxifen for early breast cancer: An overview of the randomised trials. Lancet 351:1451-1467. Eastman P. 1997. NCI adopts new mammography screening guidelines for women. Journal of the National Cancer Institute 89:538-539. Farrow DC, Hunt WC, Samet JM. 1992. Geographic variation in the treatment of localized breast cancer. New England Journal of Medicine 326:1097-1101. Farrow DC, Samet JM, and Hunt WC. 1996. Regional variation in survival following the diagnosis of cancer. Journal of Clinical Epidemiology 49(8)843-847. Fisher B, Bauer M, Margolese R, et al. 1985. Five-year results of a randomized clinical trial comparing total mastectomy and segmental mastectomy with or without radiation in the treatment of breast cancer. New England Journal of Medicine 312:665-673. Fisher B, Dignam J, Wolmark N, et al. 1997. Tamoxifen and chemotherapy for lymph node-negative, estrogen receptor-positive breast cancer. Journal of the National Cancer Institute 89:1673-1682. Ganz PA, Schag AC, Lee JJ, Polinsky ML, Tan SJ. 1992a. Breast conservation versus mastectomy: Is there a difference in psychological adjustment of quality of life in the year after surgery? Cancer 69:1729-1738. Ganz PA, Schag CA, Lee JJ, Sim MS. 1992b. The CARES: A generic measure of health-related quality of life for patients with cancer. Quality of Life Research 1:19-29. Garnick MB. 1996. Prostate cancer: Screening, diagnosis, and management. Annals of Internal Medicine 118(10):804-818. GIVIO. 1994. Impact of follow-up testing on survival and health-related quality of life in breast cancer patients. A multicenter randomized controlled trial. Journal of the American Medical Association 271 (20):1587-1592.

OCR for page 79
--> Goodwin JS, Hunt WC, Samet JM. 1993. Determinants of cancer therapy in elderly patients. Cancer 72(2):594-601. Greenfield S, Blanco DM, Elashoff RM, Ganz PA. 1987. Patterns of care related to age of breast cancer patients. Journal of the American Medical Association 257:2766-2770. Grieco A, Long CJ. 1984. Investigation of the Karnofsky performance status as a measure of quality of life. Health Psychology 3(2): 129-142. Guadagnoli E, Shapiro CL, Gurwitz JH, et al. 1997. Age-related patterns of care: Evidence against ageism in the treatment of early stage breast cancer. Journal of Clinical Oncology 15:2338-2344. Guadagnoli E, Shapiro CL, Weeks JC, et al. 1998a. The quality of care for treatment of early stage breast carcinoma. Is it consistent with national guidelines? Cancer 83(2):302-309. Guadagnoli E, Weeks JC, Shapiro CL, et al. 1998b. Use of breast-conserving surgery for treatment of Stage I and Stage II breast cancer. Journal of Clinical Oncology 16:101-106. Halsted W. 1894. The results of operations for cure of cancer of the breast performed at Johns Hopkins Hospital. Johns Hopkins Hospital Bulletin 4:497. Hammond EH, Flinner RL. 1997. Clinically relevant breast cancer reporting. Using process measures to improve anatomic pathology reporting. Archives of Pathology and Laboratory Medicine 1:1171-1175. Hand R, Sener S, Imperato J, et al. 1991. Hospital variables associated with quality of care for breast cancer patients [see comments]. Journal of the American Medical Association 266:3429-3432. Hanks GE, Diamond JJ, Kramer S. 1985. The need for complex technology in radiation oncology. Correlations of facility characteristics and structure with outcome. Cancer 55(9 Suppl.):2198-2201. Hayes MK, De Bruhl ND, Hirschowitz S, et al. 1996. Mammographically guided fine-needle aspiration cytology of the breast: Reducing the rate of insufficient specimens. American Journal of Roentgenology 167:381-384. Hayward R, Bernard A, Rosevear J, et al. 1993. An evaluation of generic screens for poor quality of hospital care on a general medicine service. Medical Care 31:394-402. Hillner BE, McDonald KM, Penberthy L, et al. 1997. Measuring standards of care for early breast cancer in an insured population. Journal of Clinical Oncology 15:1401-1408. Hillner BE, Penberthy L, Desch CE, et al. 1996. Variation in staging and treatment of local and regional breast cancer in the elderly. Breast Cancer Research and Treatment 40:75-86. Houn F, Finder C. 1997. The Mammography Quality Standards Act and interventional mammography procedures. Bulletin of the American College of Surgeons 82:14-22. Howe JR, Monsees B, Destouet J, et al. 1995. Needle localization breast biopsy: A model for multidisciplinary quality assurance. Journal of Surgical Oncology 58:223-239. Hsieh MO, Kagle JD. 1991. Understanding patient satisfaction and dissatisfaction with health care. Health and Social Work 16:281-290. Iezzoni L. 1996. An introduction to risk adjustment. American Journal of Medical Quality 11 :S8-S11. IOM (Institute of Medicine). 1990. Medicare: A Strategy for Quality Assurance. Volume 1. Committee to Design a Strategy for Quality Review and Assurance in Medicare, Institute of Medicine. Lohr K, ed. Washington, D.C.: National Academy Press. IOM. 1999. Measuring the Quality of Health Care: A Statement by the National Roundtable on Health Care Quality. Donaldson M, ed. Washington, D.C.: National Academy Press. Johnson TP, Ford L, Warnecke RB, et al. 1994. Effect of a National Cancer Institute clinical alert on breast cancer practice patterns. Journal of Clinical Oncology 12:1783-1788. Kahan K, Bernstein S, Leape L, et al. 1994. Measuring the necessity of medical procedures. Medical Care 32:357-365. Kahn K, Rogers W, Rubenstein L, et al. 1990. Measuring quality of care with explicit process criteria before and after implementation of the DRG-based prospective payment system. Journal of the American Medical Association 264:1980-1983.

OCR for page 79
--> Kaluzny AD, Warnecke R, Lacey LM, et al. 1995. Using a community clinical trials network for treatment, prevention, and control research: Assuring access to state-of-the-art cancer care. Cancer Investigation 13:517-525. Karnofsky DA, Burchenal JH. 1949. The clinical evaluation of chemotherapeutic agents in cancer. Pp. 191-205 in MacLeod CM, ed. Evaluation of Chemotherapeutic Agents. New York: Columbia University Press. Kaufman Z, Shpitz B, Shapiro M, et al. 1994. Triple approach in the diagnosis of dominant breast masses: Combined physical examination, mammography, and fine-needle aspiration. Journal of Surgical Oncology 56:254-257. Kerlikowske K, Grady D, Rubin SM, et al. 1995. Efficacy of screening mammography. A meta-analysis. Journal of the American Medical Association 273:149-154. Kiebert GD, de Haes JCJM, van de Velde CJH. 1991. The impact of breast-conserving treatment and mastectomy on the quality of life of early-stage breast cancer patients: A review. Journal of Clinical Oncology 9:1059-1070. Kramer S, Herring DF. 1976. The Patterns of Care study: A nationwide evaluation of the practice of radiation therapy in cancer management. International Journal of Radiation Oncology, Biology, Physics 1(11-12):1231-1236. Kravitz R, Laouri M, Kahan J, et al. 1995. Validity of criteria used for detecting underuse of coronary revascularization. Journal of the American Medical Association 274:632-638. Krook JE, Moertel CG, Gunderson LL, et al. 1991. Effective surgical adjuvant therapy for high-risk rectal carcinoma. New England Journal of Medicine 324:709-715. Kutchner GJ, Smith AR, Fowble BL, et al. 1996. Treatment planning for primary breast cancer: A Patterns of Care study. International Journal of Radiation Oncology, Biology, Physics 36:731-737. Laouri M, Kravitz R, Berstein S, et al. 1997. Underuse of coronary angiography: Application of a clinical method. International Journal for Quality in Health Care 9:5-22. Lazovich D, White E, Thomas DB, Moe RE. 1991. Underutilization of breast-conserving surgery and radiation therapy among women with Stage I or II breast cancer. Journal of the American Medical Association 266:3433-3438. Levine MC, Guyatt GH, Gent M, et al. 1988. Quality of life in Stage II breast cancer: An instrument for clinical trials. Journal of Clinical Oncology 6:1798-1810. Litwin MS, Hays RD, Fink A, et al. 1995. Quality-of-life outcomes in men treated for localized prostate cancer. Journal of the American Medical Association 273:129-135. Litwin MS, Lubeck DP, Henning JM, Carroll PR. 1998. Differences in urologist and patient assessments of health related quality of life in men with prostate cancer: Results of the CaPSURE database. Journal of Urology 159:1988-1992. McGlynn EA. 1997. Six challenges in measuring the quality of health care. Health Affairs 16(3):7-21. Menck HR, Cunningham MP, Jessup JM. 1997. The growth and maturation of the National Cancer Data Base. Cancer 80:2296-2304. Mettlin C, Smart CR. 1994. Breast cancer detection guidelines for women aged 40 to 49 years: Rationale for the American Cancer Society reaffirmation of recommendations. CA—A Cancer Journal for Clinicians 44:248-255. Mettlin CJ, Menck HR, Winchester DP, Murphy GP. 1997a. A comparison of breast, colorectal, lung, and prostate cancers reported to the National Cancer Data Base and the Surveillance, Epidemiology, and End Results Program. Cancer 79:2052-2061. Mettlin CJ, Murphy GP, Cunningham MP, Menck HR. 1997b. The National Cancer Data Base report on race, age, and region variations in prostate cancer treatment. Cancer 80:1261-1266. Mettlin CJ, Murphy GP, Sylvester J, et al. 1997c. Results of hospital cancer registry surveys by the American College of Surgeons: Outcomes of prostate cancer treatment by radical prostatectomy. Cancer 80:1875-1881.

OCR for page 79
--> Middleton RG, Thompson IM, Austenfeld MS, et al. 1995. Prostate cancer clinical guidelines panel summary report on the management of clinically localized prostate cancer. Journal of Urology 154: 2144-2148. Moertel CG. 1994. Chemotherapy for colorectal cancer. New England Journal of Medicine 330(16): 1136-1142. Nakleh RE, Jones B, Zarbo RJ. 1997. Mammographically directed breast biopsies. A college of American Pathologists Q-Probes Study of clinical physician expectations and of specimen handling and reporting characteristics in 434 institutions. Archives of Pathology and Laboratory Medicine 121:11-18. National Cancer Data Base. 1998. http://www.facs.org/about-college/acsdept/cancer-dept/programs/ncdb/ncdb.html. National Institutes of Health. 1990a. NIH Consensus Statement. Adjuvant Therapy for Patients with Colon and Rectum Cancer. 8:1-25. Bethesda, MD: National Institutes of Health. National Institutes of Health. 1990b. NIH Consensus Statement. Treatment of Early Stage Breast Cancer. 8:1-19. Bethesda, MD: National Institutes of Health. Nattinger AB, Gottlieb MS, Hoffman RG, et al. 1996. Minimal increase in use of breast-conserving surgery from 1986 to 1990. Medical Care 34:479-489. Nattinger AB, Gottlieb MS, Veum J, et al. 1992. Geographic variation in the use of breast conserving treatment for breast cancer. New England Journal of Medicine 326:1102-1107. Nyström L, Rutqvist LE, Wall S, et al. 1993. Breast cancer screening with mammography: Overview of Swedish randomised trials. Lancet 341:973-978. Osborne CK, Clark GM, Ravdin PM. 1996. Adjuvant systemic therapy of primary breast cancer. Pp. 548-578 in Harris JR, Morrow M, Lippman ME, Hellman S, eds. Diseases of the Breast. New York: Lippincott-Raven Publishers. Osteen RT. 1992. Breast cancer. Pp. 29-38 in Steele GD, Winchester DP, Menck HR, Murphy GP, eds. National Cancer Data Base, 1992. Atlanta, GA: American Cancer Society. Osuch JR. 1996. Abnormalities on Physical Examination. Pp. 110-114 in Harris JR, Morrow M, Lippman ME, Hellman S, eds. Diseases of the Breast. New York: Lippincott-Raven Publishers. Partin AW, Kattan MW, Subong EN, et al. 1997. Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer. A multi-institutional update. Journal of the American Medical Association 277(18): 1445-1451. Partin AW, Yoo J, Carter HB, et al. 1993. The use of prostate-specific antigen, clinical stage and Gleason score to predict pathological stage in men with localized prostate cancer. Journal of Urology 150:110-114. Pisansky TM, Kahn M J, Rasp GM, et al. 1997. A multiple prognostic index predictive of disease outcome after irradiation for clinically localized prostate carcinoma. Cancer 79(2):337-344. Potosky AL, Riley GF, Lubitz JD, et al. 1993. Potential for cancer related health services research using a linked Medicare-tumor registry database. Medical Care 31(8):732-748. Potosky AL, Miller BA, Albertson PC, Kramer BS. 1995. The role of increasing detection in the rising incidence of prostate cancer. Journal of the American Medical Association 273:548-552. Reichheld FF. 1996. Learning from customer defections: Customers can help point out what is wrong with services. Harvard Business Review 74:56-69. Reifel J, Ganz P. In press. Clinical applications of quality of life research. In Cancer Policy. Norwell, MA: Kluwer Academic Publishers. Ries LAG, Kosary CL, Hankey BF, et al., eds. 1998. SEER Cancer Statistics Review, 1973-1995. Bethesda, MD: National Cancer Institute. Roberts MM, Alexander FE, Anderson TJ, et al. 1990. Edinburgh trial of screening for breast cancer: Mortality at seven years. Lancet 335:241-246.

OCR for page 79
--> Rubin HR, Gandek B, Rogers WH, et al. 1993. Patients' ratings of outpatient visits in different practice settings. Results from the medical outcomes study. Journal of the American Medical Association 270:835-840. Samet JM, Hunt WC, Farrow DC. 1994. Determinants of receiving breast-conserving surgery. The Surveillance, Epidemiology, and End Results Program, 1983-1986. Cancer 73:2344-2351. Sarrazin D, Le M, Rouesse J, et al. 1984. Conservative treatment versus mastectomy in breast cancer tumors with macroscopic diameter of 20 millimeters or less: The experience of the Institut Gustave-Roussy. Cancer 53:1209-1213. Schag CA, Heinrich RL. 1990. Development of a comprehensive quality of life measurement tool: CARES. Oncology 4:135-138. Schatzkin A, Freedman LS, Dorgan J, et al. 1996. Surrogate end points in cancer research: A critique. Cancer Epidemiology, Biomarkers, and Prevention 5:947-953. Schipper H, Clinch J, McMurray A, et al. 1984. Measuring the quality of life of cancer patients: The Functional Living Index—Cancer: Development and validation. Journal of Clinical Oncology 2:472-483. Schleifer S, Bhardwaj S, Lebovits A, et al. 1991. Predictors of physician nonadherence to chemotherapy regimens. Cancer 67: 945-951. Schuster MA, McGlynn EA, Brook RH. 1998. How good is the quality of health care in the United States? Milbank Quarterly 76(4):509, 517-563. Segal M. 1994. Mammography facilities must meet quality standards. FDA Consumer 8-12. Shapiro S, Venet W, Strax P, et al. 1988. Periodic Screening for Breast Cancer—The Health Insurance Plan Project and Its Sequelae, 1963-1986. Baltimore, MD: Johns Hopkins University Press. Simon MS, Stano M, Severson RK, et al. 1996. Clinical surveillance for early stage breast cancer: An analysis of claims data. Breast Cancer Research and Treatment 40:119-128. Stolier AJ. 1997. Stereotactic breast biopsy: A surgical series. Journal of the American College of Surgeons 185:224-228. Surveillance, Epidemiology, and End Results Program. 1998. http://www-seer.ims.nci.nih.gov Swan J, Wingo P, Clive R, et al. 1998. Cancer surveillance in the U.S.: Can we have a national system? Cancer 83:1282-1291. Tabar L, Fagerberg G, Chen H-H, et al. 1995. Efficacy of breast cancer screening by age. New results from the Swedish two-county trial. Cancer 75:2507-2517. Talamonti MS, Morrow M. 1996. The abnormal mammogram. Pp. 114-122 in Harris JR, Morrow M, Lippman ME, Hellman S, eds. Diseases of the Breast. New York: Lippincott-Raven Publishers. Talcott JA. 1996. Quality of life in early prostate cancer: Do we know enough to treat? Hematology/Oncology Clinics of North America 10(3):691-701. U.S. Department of Health and Human Services. 1996. Guide to Clinical Preventive Services. Report of the U.S. Preventive Services Task Force. Second Edition. Washington, D.C. U.S. General Accounting Office. 1988. Cancer Treatments 1975-85: The Use of Breakthrough Treatments for Seven Types of Cancer. PIC ID No. 3068.1:1-21. Washington, D.C. U.S. General Accounting Office. 1998a. Mammography Quality Standards Act: X-ray quality improved, access unaffected, but impact on health outcomes unknown. GAO/T-HEHS-98-164. U.S. General Accounting Office. 1998b. Mammography services: Impact of federal legislation on quality, access, and health outcomes. GAO/HEHS-98-11. Veronesi U, Saccozzi R, Del Vecchio M, et al. 1981. Comparing radical mastectomy with quandrantectomy, axillary dissection, and radiotherapy in patients with small cancers of the breast. New England Journal of Medicine 305:6-11. von Eschenbach A, Ho R, Murphy GP, Cunningham M, Lins N. 1997. American Cancer Society guideline for the early detection of prostate cancer: Update 1997. CA: Cancer Journal for Clinicians 47:261-264.

OCR for page 79
--> Wasson JH, Cushman CC, Bruskewitz RC, et al. 1993. A structured literature review of treatment for localized prostate cancer. Prostate disease patient outcome research. Archives of Family Medicine 2:487-493. Weeks JC. 1997. Outcomes assessment in the NCCN. Oncology 11 (11A): 137-140. Wells WAS, Carney PA, Eliassen MS, et al. 1998. Statewide study of diagnostic agreement in breast pathology. Journal of the National Cancer Institute 90:142-145. Wennberg JE, McAndrew CM. 1996. Pp. 128-129 in The Dartmouth Atlas of Health Care in the United States. Chicago: American Hospital Publishing, Inc. Wilson NJ, Kizer KW. 1998. Oncology management by the ''new'' Veterans Health Administration. Cancer 82(10 Suppl.):2003-2009. Wingo PA, Ries LA, Rosenberg HM, et al. 1998. Cancer incidence and mortality, 1973-1995: A report card for the U.S. Cancer 82(6): 1197-1207. Young PC, Wasserman RC, McAullife T, et al. 1985. Why families change pediatricians. Factors causing dissatisfaction with pediatric care. American Journal of Diseases of Children 139:683-686. Young WW, Marks SM, Kohler SA, Hsu AY. 1996. Dissemination of clinical results. Mastectomy versus lumpectomy and radiation therapy. Medical Care 34:1003-1017.