NPCR Education and Training Series (NETS) Module 3: Quality Control for Central Registries Part 1-Section A: General Overview

Transcription

1 NPCR Education and Training Series (NETS) Module 3: Quality Control for Central Registries Part 1-Section A: General Overview Prepared by Scientific Applications International Corporation (SAIC) CDC Contract Number Centers for Disease Control and Prevention National Program of Cancer Registries Atlanta, Georgia 1

2 Quality Control for Central Registries Division of Cancer Prevention and Control NCCDPHP, CoCHP Centers for Disease Control and Prevention Atlanta, Georgia Note: Some images in this presentation 2008 Jupiterimages Corporation. Used with permission. What we re going to talk about in this session is variously called quality control, quality assurance, total quality management, and continuous quality improvement. Needless to say, the word quality is in each of these processes. We ll get into the subtleties of these various terms throughout the session, but first we need to talk about the basics of quality and then how it applies to cancer registries. 2

3 Overview Quality Theory Types of Quality NAACCR Standards Principles of Data Quality Methods and Tools Audits Developing an Audit Closing the Loop 3 This module will cover many aspects of quality as it applies to cancer registry operations. The theories of quality are not new to manufacturing industries and have been presented in various forms in health care management for at least two decades. But quality in cancer registries is often unfortunately a step-child to the other work of registries, and as a result quality measures seem to be performed only as time allows. We hope by the end of this session that you will appreciate the importance of quality in cancer registries and make the effort to find the time to do a thorough job of improving the data quality in your registry. 3

4 I. Quality Theory and NAACCR Standards The concept of quality is not new. It has been around since Aristotle s time and is deeply ingrained in scientists as the sequence of observation, hypothesis, prediction, and testing and supporting results the scientific method approach we see as the basis for so many advances in medicine and other fields. But formalizing this scientific method specifically for the measurement of quality has a much shorter history. 4

5 Quality Theory Fitness for Use Deming s theories of quality 1986 Developed in manufacturing industry Photo courtesy of The MIT Press 5 Dr. W. Edwards Deming Quality is usually defined as fitness for use or the ability to meet the needs of the user. In other words, assurance that everything is in order so that the product can be used. In the cancer registry setting, the product is cancer data, and quality usually refers to data quality, meaning that the data coming into the registry have been checked and are ready for use in analysis and research. Formal theories of quality have been around since the 1920s, but really came into widespread use starting in the mid-1980s, when W. Edwards Deming published his theories on quality improvement. Deming was a U.S. Census Bureau statistician and expert in statistical quality control methods. He became legendary in post-world War II Japan for advocating changes that changed Japan s manufacturing reputation from producer of cheap, poor quality goods into one of the world s leaders in manufacturing high quality, precision products. 5

6 6 Deming s 14 Points of Management (translated for registries) 1. Create constancy of purpose for improvement Establish a culture of quality 2. Adopt the new philosophy Do not accept poor quality any longer 3. Cease dependence on mass inspections Build quality into the product from the beginning 4. End lowest tender contracts Require high quality for a fair price, not junk from the low bidder 5. Improve every process There s always a better way to do something In 1986, Deming published The New Economics in which he listed his 14 points of management and described the process of continuous quality improvement. Although originally directed at a manufacturing environment, the 14 points that begin on this slide are applicable to nearly every setting where a product is created. In particular, they apply to cancer registry operations and data. So these 14 points are intended to establish a culture of quality wherever they are introduced. 6

7 Deming s 14 Points of Management (translated for registries) 1. Institute training on the job Train everyone, including managers 2. Institute leadership Managers should lead, not simply supervise 3. Drive out fear Allow expression of ideas and asking of questions; communication should be two-way 4. Break down barriers Cross-train, or at least understand what other staff do 7 In the case of registries, there are two major products: the abstracts that go into the registry database and the information that comes out of the registry database. Notice the shift from data or facts that go into the registry to information that comes out of a registry. That s the registry s job converting loose or disparate facts into cohesive information about cancer incidence, mortality, treatment patterns, and everything else a registry analyzes. The users of registry information are like the consumers of manufactured products. Without satisfactory quality of the data and some assurance that the quality can be maintained, there will be no consumers. 7

8 8 Deming s 14 Points of Management (translated for registries) 1. Eliminate slogans and exhortations Leadership actions are more effective than words 2. Eliminate arbitrary numerical quotas Make quality the goal, not an output target 3. Permit pride of workmanship Quality of work should be the goal, not a good performance review 4. Encourage education Continuous learning is part of the quality process 5. Take action to accomplish the transformation A commitment to quality starts at the top Many of Deming s 14 points are directed at the leaders of an organization. Quality concepts must start at the top and must be adopted throughout the organization. Managers must encourage workers to take pride in what they produce by eliminating barriers that frustrate workers and lower quality efforts just to get the job done. 8

9 The Deming Cycle Continuous Quality Improvement a.k.a. Deming Wheel, QI Spiral Foundation for registry quality studies Act Plan 9 Check Do W. Edwards Deming is also the father of continuous quality improvement. He refined a former theory of plan, do, see into what we commonly see in quality improvement studies in registries. The four steps in this cycle are PLAN DO circumstances. CHECK Study the results. Plan for change. Analyze and predict the results. Execute the plan, taking small steps in controlled ACT Take action to standardize or improve the process, sometimes stated as taking remedial action to either correct mistakes or make system improvements. In many settings, Deming s quality cycle only gets as far as step 3, checking the results of the change in process. That s fine, because it is a step forward in the quality improvement process. It is very important to complete the ACT step, which takes the results of the process analysis and formalizes them in a new process at the next level. But what really keeps quality improvement in continuous motion is to bridge that gap between acting and planning. In other words, the cycle should start again at the new level by doing some sort of analysis to see whether the new process is working well and can be improved. This is what we call Closing the Loop. We ll come back to this when we look at developing an audit later in this session. 9

10 Quality Processes Quality control Quality assurance Quality improvement Total quality management 10 We mentioned several of terms at the beginning of this session, all relating to quality. Now it s time to define those terms. Quality control (QC) usually refers to the mechanics of improving quality. Quality control tends to be retrospective. In other words, limits are set on what is acceptable by reviewing what has already been done. With quality control there is little except negative feedback fix this error and return it and there are no mechanisms in place to act on any findings and review the process later to see whether corrections improved it. Quality assurance (QA) is more proactive and encompasses an organization s broader philosophical approach to quality. QA consists of planned or systematic actions necessary to provide adequate confidence that a product or service is of the type and quality needed and expected by the consumer. It has been described by some as providing confidence that requirements will be met. Processes are under continuous scrutiny to make sure that things are working properly. In registries, quality assurance can take shape as management reports and other reviews that monitor whether operations are running smoothly and data are being processed efficiently. Quality improvement (QI) is both proactive and analytical. In addition to the systemic actions to assure quality in QA, QI continuously looks at whether quality can be improved and takes steps to study how improvements can be made. Continuous quality improvement is an approach to quality improvement in which past trials of change are used as the basis of future trials and something is always being tested for its effects on improvement. In a registry, quality improvement takes the form of studies and education. The studies show where education is needed, the education is done, and then the studies are conducted again to measure whether quality has improved. The education and re-study is the process of closing the loop mentioned previously. Total quality management (TQM) as mentioned previously, is a culture that has to be adopted by an organization from top to bottom. It has been defined as an approach that motivates, supports, and enables quality management in all activities of the organization, focusing on the needs and expectations of internal and external customers. In a registry, TQM is an approach that incorporates not only the accuracy of data going into the system, but the quality of the system itself, especially its responsiveness to its customers, the users of registry data. In this session, we may tend to use the terms QC, QA, and QI interchangeably, but it should be understood that they are all parts of total quality management, which in the end, guarantees fitness for use. 10

11 Registry Quality Control Methods Acceptance sampling Process controls Designed studies Use of data 11 There are three basic methods by which a cancer registry monitors the quality of its performance. The terms listed here are quality management jargon; you probably are already familiar with these methods if we give examples. Acceptance sampling is defined as a statistical procedure for accepting or rejecting a batch of merchandise or documents and involves determining the maximum number of defects discovered in a sample before the entire batch is rejected. In a registry, data reporters commonly submit abstracts in batches and the central registry runs computer edit checks on the abstracts to determine if they are acceptable before loading them in the database. Often the central registry has a standard that all cases must pass computer edits or the entire batch is rejected. If the standard is not 100% passing, it is the responsibility of the central registry to determine how many errors will be allowed before the batch is rejected. Computer edit checks are the most cost-effective type of acceptance sampling. Process controls are somewhat more sophisticated and involve statistical methods to establish thresholds of acceptability. In an established registry, one example of a process control might be monitoring the monthly data submissions from facilities with registries. The process controls are based on the facility s month-by-month track record of data submissions. If the expected number of cases for a month falls below the threshold, the process control should flag the facility for contact by central registry staff to find out what happened. In industry, a process control may have an upper and a lower threshold. If, for example, a production line slows down and falls below the lower threshold, it is said to be out of control, a term that has moved into our general vocabulary. Designed studies are perhaps the quality control methods most obvious to most registrars. These include reliability, reabstracting, and recoding studies, all of which we will review later in this module. The ultimate method of measuring quality is to use the data for research. Any time someone looks closely at a series of data, anomalies will appear. For example, a researcher once sorted data on malignant melanoma by the depth of invasion and ran survivals by Breslow groups. In the central registry data, the researcher noted the least invasive melanomas had overall survival that was worse than deeper lesions. After investigation, it was discovered that some of the reported depths were off by a factor of 10 or 100 because of differences in the way Commission on Cancer approved hospital and other facility registries recorded the depth of invasion. In other words, a 1.5 millimeter deep lesion was reported as 002 according to the ROADS rules in effect at the time but recorded as 150 according to central registry rules. Once the cases were reviewed and corrected, the survival rates for the least invasive melanomas fell into line with the other Breslow groups. This problem would have gone undetected if the researcher had not noticed the discrepancy in survival rates. It is especially important to note that any of these methods is a waste of time and resources if errors are detected and no further action is taken. Correction of errors and application of what has been learned during the quality control process is critical to the continued improvement of the data. 11

12 Registry Examples of QC Methods Quality Acceptance Process Study Characteristic Sampling Control Design Accuracy Visual review Edit rejection Reabstrac- Edit checks rates ting studies Case --- % DCO Casefinding completeness audits Data Edit checks % Unknowns --- completeness Timeliness --- Lag time in --- reporting Changes over Reliability time studies 12 Adapted from Hilsenbeck SG. Quality Control. In Menck H and Smart C, eds. Central Cancer Registries: Design, Management and Use, first edition, This table is adapted from Hilsenbeck SG. Quality Control. In Menck H and Smart C, eds. Central Cancer Registries: Design, Management and Use, first edition, 1994, is included in the second edition of the central registries textbook. It shows additional registry examples of the various quality control methods used in industry and mentioned on the previous slide acceptance sampling, process control, and study design. Each of these examples will be discussed in more detail later in this module. 12

13 Quantifiable Aspects of Quality Measurable things Procedural Measurable actions or processes 13 There are two primary types of quality in a registry: quantifiable and procedural. Quantifiable aspects are measurable things, such as the percentage of unknown values for a particular data field. Procedural aspects relate to how things are done, such as work flow, procedures, and the conversion of data into information for consumers. Assessing the completeness of casefinding is a measurable process. In many situations, these two aspects are interrelated. Without quantifiable measures, procedures cannot be assessed, and without procedures, quality can t be quantified. 13

14 14 Quantifiable Quality Measures STANDARDS Reportable list Coding guidelines Data items Valid codes Acceptable percentage of 9s, unknowns, blanks Training Central registry staff Reporters and registrars To quantify quality, there must be some baseline to measure against. Generally we refer to that baseline as a standard. Central Cancer Registry standards in the U.S. and Canada are established by the standard-setting organizations and brought together in a consensus document by the North American Association of Central Cancer Registries. The standard-setting organizations are the National Program of Central Cancer Registries (NPCR), the Surveillance Epidemiology and End Results program (SEER), the Commission on Cancer (COC) of the American College of Surgeons, and Statistics Canada. We ll go over those standards in a few minutes. Quantifiable items in a registry include such things as a reportable list. Without a reportable list, data collectors will not know what to report, and central registry staff will not know what types of cases a data collector might have missed. A central registry must provide a list of required data items for reporters and registrars to collect. The central registry will then have a standard by which to assess the completeness of the cancer abstract. Quantifiable measures also include documentation of valid codes (for example, a numeric field cannot contain letters) and defining acceptable percentages of unknown values, such as 9s, blanks, or other symbols when something is not known. Quantifiable quality measures also include training, both of central registry staff and the people who report data to the central registry. The results of the training are quantifiable. A participant may take a pretest and a posttest during a workshop to measure the amount of improvement. Other results of training are more long term. If the training was done to clarify a problem found in the data, it might be six months or more before the central registry sees improvement in the data, because it might take that long for the registry to receive cases abstracted correctly after the training. Nonetheless, ongoing training is a vital part of quality improvement. 14

15 Procedural Quality Measures Registry operations Timeliness Submission from facility Submission to national registry Work flow 15 Procedural quality measures affect registry operations, which are much broader in scope than data quality measures. Registry operations include everything from casefinding to case consolidation to statistical calculations to production of reports and conducting research based on the data. Procedural quality measures for these operations can range from monitoring work flow as cases are processed through the registry to specific procedures for institutional review board approval of requests for data. One example of procedural quality measures starts with standards for timeliness. The central registry sets standards for receiving data from facilities within a certain time limit and can penalize facilities for not submitting cases within that period. In turn, the national registries the National Program of Cancer Registries and the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute require that their participating registries submit data to them within a specified period. Later in this module, we will discuss different types of management reports that monitor registry operations. 15

16 NAACCR Standards Volumes I. Data Exchange Standards and Record Description II. III. IV. Data Standards and Data Dictionary Standards for Completeness, Quality, Analysis, and Management of Data Standard Data Edits V. Pathology Laboratory Electronic Reporting 16 All volumes available from The North American Association of Central Cancer Registries (NAACCR) publishes five volumes of consensus standards on various aspects of central registry operations. Each volume has been prepared by committees comprised of representatives from the many and varied central registry members of NAACCR. For the next few moments, we will focus on Volume III, Standards for Completeness, Quality, Analysis and Management of Data. National Program of Cancer Registries (NPCR) Program Standards that include more specific information will also be included in the presentation. 16

17 Volume III Standards Model registry concept Strictness of recommendations Must necessary for effectiveness and efficiency Should highly desirable May desirable but not necessary 17 According to the NAACCR Web site, Volume III provides central registry structural requirements, process standards and outcome measures for access to source data and completeness of reporting, data quality, data analysis and reporting, and data management. Most recently revised and updated in October 2004 by the NAACCR Registry Operations Committee, Volume III standards are based on the concept of a model central cancer registry, one that is populationbased and includes incidence data including treatment and stage data, but does not necessarily collect follow-up data. It collects information from hospitals, other health care facilities, and physicians. The standards cannot take into account local variations and idiosyncrasies, but are intended to serve as a baseline for operations in a newly established registry. [All states and territories in the U.S. and Canada had established registries by fiscal 1999.] The standards have various strengths of recommendation. MUST: identifies a characteristic necessary for effective and efficient operation of a cancer registry. SHOULD: a characteristic that is strongly recommended, but not absolutely required as the MUST above. MAY: a characteristic that is desirable, but not necessary for the scope of the model registry. 17

18 18 Structural Standards State legislation or regulations establishing population-based registry Legislation/regulations should include Designation of authority Reporting requirements Patient record access Enforceability Data quality and data standards Confidentiality and disclosure of data Liability Specification of funding source All states now have laws or regulations mandating the collection of cancer patient data. The content of the law/regulation varies, but NAACCR standards describe the desired content of the statutes. Each of these aspects of the legislation is defined in more detail in Volume III. 18

19 Reportable list Structural Standards Definitions of reportable cases Reference date Diagnostic confirmation Class of case; type of admission to facility Ambiguous terminology Staffing guidelines Standards for type of staff Standards for continuing education 19 Every central cancer registry must have a list of reportable diagnoses. The definitions must include such factors as Reportable and non-reportable diagnoses and the reference standard Multiple primary rules Reportability of non-residents and residents Reference date Diagnostic confirmation Class of case Type of admission to the reporting facility Ambiguous terminology The next section of the NAACCR structural standards deals with staffing guidelines. Volume III discusses aspects of central registry operations that affect staffing, rather than providing a specific number of staff necessary for data collection and other activities. 19

20 Process Standards Hospital reporting Non-hospital sources reporting Physician reporting Physician advisors Advisory board Case sharing 20 The NAACCR process standards describe access to hospital, non-hospital sources, and physician reporting of cancer patient data. Obtaining voluntary cooperation from facilities with registries and establishing mechanisms to identify and capture cases diagnosed and treated completely outside hospitals are discussed in fairly general terms. The standards also recommend that the central registry establish one or more physician advisors to serve in a consultative capacity for the registry, as well as an advisory board consisting of medical professionals, representatives of patient advocacy groups and voluntary agencies, and members of the general public with an interest in cancer data and cancer control measures. NPCR requires that the advisory board also include hospital registrars. NPCR population-based central registries are required to collect information on cancer patients diagnosed and/or treated in their state. NPCR requires central cancer registries to collect information on non-residents treated in the geographic area so that the information can be shared with the patient s state of residence for case completeness. In most situations, this case-sharing is reciprocal. Guidelines for the amount and frequency of information to be shared is provided in the NPCR Program Standards. 20

21 Process Standards Reporting requirements Use of and changes in reporting facilities and practitioners Confidentiality policies HIPAA Release of information Privacy of patient and facility information Data security Personnel 21 Central registries should notify their constituents of their obligation to report cancer cases. The standards outline what should be included in the notification documentation. Population-based registries MUST be able to document that they capture tumors from the entire population at risk for their area. To do so, they MUST be able to document where residents of their population receive tumor diagnoses and how the registry identifies these tumor reports. This baseline standard is an important part of monitoring the quality of reporting completeness. Standards must be defined for confidentiality policies both within the central registry and in dealing with requests for information. The Health Information Portability and Accountability Act (HIPAA) of 1996 (finally implemented in 2003) should be cited, because central registries are exempt from HIPAA standards when they receive information from data collectors, but they are not exempt when releasing information outside of the registry. The central registry must ensure that the privacy of patient and facility information is protected. This includes standards for data security and exchange of information. Registries must have confidentiality guidelines and standards for registry personnel and those using registry data, as well as penalties for breach of confidentiality. 21

22 Other Process Standards Death clearance Follow-up (if part of registry operations) Monitoring completeness of reporting 22 Volume III describes several other process standards for other aspects of registry operations. All population-based registries must perform death clearance as part of their efforts to ascertain all cancer cases. Registries that collect follow-up information must have mechanisms in place to ensure that patient data is up to date. Volume III outlines activities to monitor completeness of reporting as well, including various types of audits. Examples of casefinding and other audits will be described later in this module. 22

23 Outcomes Standards Death certificate only Observed/expected case counts Patterns of cancer incidence Microscopically confirmed Timeliness of reporting Follow-up success rates Results of audits 23 The third type of standard measures outcomes. Volume III discusses, but does not list, specific standards for Percent of patients diagnosed by death certificate only. Observed and expected case counts. Patterns of cancer incidence in certain populations, such as higher incidence of prostate cancer in African-American men. Percent of patients diagnosed microscopically versus clinical diagnosis only. Timeliness of reporting. Follow-up success rates. Results of audits. Any and all of these measures can be the subject of quality improvement studies and actions. 23

24 NAACCR Data Quality Standards Quality assurance program Specified activities Schedule of routine reports Designated quality control staff Designated budget Procedures when quality standards are not met Documentation (procedure and coding manuals, other) 24 Chapter 3 of Volume III of the NAACCR standards discusses data quality standards. It states The registry MUST have a quality assurance program with specified activities integrated into basic central registry operations. The central registry s focus should be on data and procedural quality from top to bottom. Specified activities include documentation of an established schedule for routine reports and procedures to handle situations where quality standards are not met. Two of the most important parts of a registry quality assurance program (written as MUST in the standards) are designated quality control staff members and sufficient budget to carry out the needed quality control activities. Included in the range of quality control expertise in the registry are CTRs, abstractors and coders, one designated manager/supervisor of QC activities, computer expertise, and a statistical analyst. NPCR requires a CTR to oversee and conduct quality assurance activities. The documentation part of the quality assurance program includes both current and historical practices. The documentation can take the form of procedure manuals, coding manuals, and other manuals specific to registry operations, such as a computer disaster preparedness manual. Part of the responsibilities of the QC manager is updating the documentation on a regular schedule. The manual(s) must be readily available to all staff either in hard copy or electronic (online) format. 24

25 Quality Assurance Program Standards for central registry computer system Edits Process controls Capabilities for special studies Record consolidation 25 Standards for effective data management must be included in the registry s quality assurance plan and are covered in detail in chapter 5 of NAACCR standards Volume III. Design characteristics pertaining to quality control are covered in Chapter 3, Quality Assurance. They include the structure and definitions of data edits, descriptions of process controls for editing data, descriptions of system capabilities to generate ad hoc reports, and standards for record consolidation. 25

26 Areas of Standardization Standardization Codes Text fields Data sets Data exchange formats Procedures Documentation 26 One of the principal messages of the standards for a quality assurance program is not just having standards, but standardization of procedures, codes, data sets, data exchange formats, and documentation. Such standardization permits comparison of data from various facilities that report to the central registry as well as comparison of central registry data with neighboring states. Any nonstandard codes the registry uses should map to standard codes for information exchange. Text fields should be included in the registry data set to allow quality control of coded fields. There should be a minimum set of data edits built in to the central registry software and shared with facility registries to use even before data is transmitted to the central registry. 26

27 Quality Assurance Program Training Must be provided Central registry staff Staff of facilities reporting to central registry Includes Reporting requirements Data collection Quality control Data processing 27 Volume III is very clear that a registry must have a standard stating that training be provided to central registry staff and facility-based registrars. The training should include Reporting requirements (frequency, mechanism, required data items). Data collection (reportable list, casefinding procedures, abstracting requirements, ICD-O coding, staging, treatment coding). Quality control (visual edits, computer edits, feedback regarding edit results). Data processing (use of computer software). The standards do not mandate a particular type of training many methods are listed but do recommend that any training be based on standard references and be eligible for continuing education credits. NPCR requires that the state trainer be a CTR. 27

28 Quality Control Activities Standards Process controls Special assessments Reabstracting audits Recoding audits Reliability studies 28 A central registry quality assurance program needs various types of quality control activities to cover the scope of registry operations. Of particular importance, standards are needed for conducting various types of audits and special assessments (such as targeted case ascertainment studies), as well as statistical process controls on certain aspects of registry operations, such as edit check and visual edit rejection rates. Each of these will be discussed in another section of this module. The final part of the data quality chapter of the NAACCR standards volume is devoted to dissemination of the results of quality control activities, such as reporting audit results, setting target rates for acceptability of missing or unknown information, and other aspects that will be covered later in this session. 28

29 NAACCR Standards Volume III Chapter 4: Data Analysis and Reporting Detailed discussion Confidentiality Population data Aggregating data Statistical methods and rates 29 Chapter 4 of the NAACCR Standards Volume III provides detailed discussion of various aspects of data analysis and reporting. Confidentiality issues described in chapters 2 and 3 are covered in detail, such as confidentiality policies, release of information to researchers, and institutional review boards. The chapter discusses standardized groupings of various types of population data race, and ethnicity, as well as population estimates. Chapter 4 provides references for aggregating data, such as site and histology recode tables, treatment categories, causes of death, and age categories. The discussions of statistical methods and rates cover case counts, incidence and mortality rates, standard populations, survival analysis, and reporting. 29

30 NAACCR Standards Volume III Chapter 5: Data Management Detailed discussion Computer functions Hardware, software requirements Database models Inputs, outputs Record linkage Record consolidation Revisions to database 30 Chapter 5 is a comprehensive discussion of the various information management aspects of a central cancer registry. This chapter includes detailed descriptions (not necessarily standards) for the various functions a software system must have to support a full central cancer registry operation: capacity for caseload, standard and ad hoc reports, data security, and flexibility. The hardware and software requirements section covers aspects to consider when starting a registry as well as upgrading central registry software. Database models (relational, hierarchical), communication requirements, and utility programs are discussed. There is an extensive section on standards for inputs and output and separate sections on the functional requirements of record linkage and record consolidation. Finally, there is a section that discusses the process of updating the database record corrections, record deletions, and adding follow-up to patient records. This information has been included in this module for future reference; detailed discussion and training on the content of Volume III s data management chapter is actually beyond the scope of this module. (Go to Part I Section B). 30

31 The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention. Note: Some images in this presentation 2008 Jupiterimages Corporation. Used with permission. 31

32 For information about CDC s Cancer Prevention and Control Programs and the National Program of Cancer Registries Please visit 32