Michelle Leavy

	Achieving the best possible outcomes for patients is the ultimate goal of healthcare.  Quality improvement (QI) registries support that goal by helping clinicians identify ways to improve treatment processes and patient outcomes. These types of registries have been used in a broad range of condition areas, with diverse designs, data collection methods and funding models. QI registries may also generate large datasets about specific conditions, which can provide insights into treatment patterns and related outcomes.  Overall, the value of a QI registry depends on developing a design that will achieve the registry’s objectives while maximizing feasibility and sustainability.

	A QI registry uses individual and population-level data to improve patient care. In general, QI registries may be grouped into two major categories: registries that collect data from patients receiving a specific healthcare service or procedure (e.g., hospitalization for heart failure); and registries that collect data over a longer period of time on patients with the same disease or condition. Moreover, the scope of a QI registry may range from a single institution to multiple institutions in multiple countries. 

	Like all patient registries, QI registries collect data systematically and are purpose-driven.  Unlike other types of registries (e.g., disease/condition registries, pregnancy registries, registries to fulfill post-marketing commitments), QI registries focus on promoting rapid cycle quality improvement by continuously feeding actionable information back to care providers to improve care. Other types of registries typically identify key research questions and collect the necessary data to address those questions from a specified number of patients over a specified period of time. The site investigators who enroll patients and enter data are often compensated for their time, and, at the conclusion of the study, the findings are presented at conferences or published in the peer-reviewed literature. 

	In contrast, a QI registry typically begins with a set of clearly defined quality measures (e.g., heart failure readmissions within 30 days) and collects the necessary data to calculate those measures at the physician or institution level. The sample size is not defined in advance-in fact, participating sites are often encouraged to enter as many patients as possible-and the registry has no defined endpoint. Data are collected on a continuous basis, and the participants’ performance on the quality measures is calculated frequently (or even on demand) and shared with the participants for the purpose of encouraging process change. Rather than receiving compensation for entering patient data, sites typically pay to participate in the QI registry and expect to receive value in the form of tools, reports, and possibly public recognition for their participation.

	Due to these differences in purpose, design, and participant motivations, QI registries face different challenges than other types of registries in the design, operation, and analysis phases. 

	This article provides an overview of the major components of QI registries (Table 1), but focuses largely on the design-particularly the design challenges and potential solutions. In addition, the following discussion explores innovative ways to leverage the data generated by QI registries.

	From the outset, QI registry developers should keep in mind three principles:

		Value: maximize value by focusing on relevant, timely objectives that will directly improve treatment processes and patient outcomes

		Feasibility: keep the participant’s burden as low as possible

		Sustainability: plan for change and optimize the use of all of the data.

	Focusing on these three principles throughout the planning and design phases will increase the likelihood of success for the registry. While these principles apply to all types of registries, they are particularly critical for QI registries. QI registries typically charge organizations a fee to participate in the registry, so organizations must see the registry as both valuable and feasible. Sustainability is also essential, as most QI registries plan to operate continuously, with no defined endpoint.

	The first step in planning and designing a QI registry involves identifying the registry stakeholders-the people who will participate in and benefit from the QI registry. Institutions that participate in QI registries must allocate internal resources to support the effort, making it crucially important that these institutions see value in participation. From the start, a QI registry must aim at producing actionable information-often in the form of quality measures that assess compliance with clinical guidelines-that can be used to improve treatment processes and patient outcomes in demonstrable way. Registry developers must consider how the registry data will be analyzed and shared with participants on an ongoing basis to promote a cycle of continuous quality improvement.

	The early planning phase should also consider practical issues, such as funding and legal and ethical requirements. The initial funding source for the registry must be identified, and a business model and plan for sustainability should be developed. Unlike other types of registries, many QI registries are open-ended, meaning that the duration of the registry is not set at the outset and ongoing sources of funding are needed. The overall cost of a QI registry depends largely on data-collection and data-entry costs. Most national registries currently use some form of electronic data capture, in which participating institutions input data remotely via a web-based system. Rather than having institutions manually enter data, some registries offer options to upload data from other sources, such as electronic health records (EHRs). With the growing use of EHRs, new approaches to data integration that take advantage of common standards for the exchange, sharing and retrieval of electronic health information, including Health Level Seven-HL7-are being developed and implemented.

	In addition, consultation with the institution’s legal department and institutional review board (IRB) early in the planning process is advisable to determine what requirements will apply to the proposed QI registry. In contrast to many other types of registries, QI registries may or may not be considered human subjects research in some cases, depending on the design of the registry. In fact, IRBs have reached different conclusions on how to distinguish QI registries from research.1 Effective planning and interactions with legal departments and IRBs in the planning phase will help QI registry developers to make informed decisions about the registry design and avoid unexpected requirements once the registry launches.

	The first step in the design phase is to determine the type of QI registry that is needed. For example, a QI registry can enhance the quality of care for patients with a particular disease, such as coronary heart disease. In this case, a QI registry would collect data on patients over time and possibly from more than one provider. Other QI registries, however, could focus on improving the treatment of a specific event, such as a myocardial infarction; this type of registry involves one time point for many patients.

	The design of the registry drives the type of data that will be collected. Generally, registries that collect longitudinal patient data require identifiable patient data, whereas registries that collect data on treatment of a specific event may only require a limited dataset or even de-identifiable data. The data can come from one facility or more, and the latter can include one nation or many. Moreover, the source of the data affects the basic design of a QI registry. In a registry designed around a single institution, for instance, developers can integrate the data collection with the institution’s workflow or EHR system. In contrast, the design of a QI registry that covers many institutions-and possibly multiple countries around the world-must accommodate a variety of workflows and participants.

	Before collecting data, a registry’s designers also must consider how the information will be analyzed and reported, including the audience for the reports and the intended content. For example, reports may be intended for use by providers to improve treatment processes; these reports may include only data for a specific provider, or they may include comparisons to the aggregate registry data, perhaps grouped by similar-sized institutions or regions. Other reports may be intended for patients, showing changes in health status over time. Developers must also consider whether provider-level reports will be blinded or unblinded-the latter meaning that the provider can be identified. The types of reports will depend on the registry’s objectives and the needs of stakeholders identified during the planning phase.

	Deciding what to measure marks a crucial step in the development of a QI registry (Table 2). Many QI registries focus on process-of-care measures, but focusing on patient outcome measures is an emerging trend. Next, the designers must decide on the core dataset. The decision may be guided by various factors, but collection of only the minimum data needed to achieve the registry’s objectives should be the underlying principle. To make this decision, developers can start with the desired quality measures and work backward to select the required data to calculate the measures. That basic data, however, may need to be expanded to support subgroup analysis or to align with quality-reporting programs. Again, consultation with stakeholders is essential to ensure that the dataset meets participant needs while remaining feasible.

	In some instances, QI registries benefit from an enhanced dataset, which allows some participants to extend data collection to support additional objectives. With this option, participants can use the same QI registry in different ways, such as for quality reporting, maintenance of certification, policy analysis, and clinical research.

	The design phase also involves identifying the target population and determining if a sampling strategy is needed. Sampling may be needed if the registry will collect data on a large number of patients (e.g., all patients admitted for myocardial infarction at a large hospital). By implementing a sampling strategy, the registry enables sites with high patient volume to enroll only a fraction of eligible patients, thus reducing the data-entry burden, while still attempting to ensure that the enrolled patients provide a representative picture of the overall patient population. Sampling can also be an important component of registries that collect long-term follow-up data; for example, if a registry enrolls 500 patients per year and follows each patient for five years, the registry staff will soon need to collect follow-up data for thousands of patients each year, which may be cost-prohibitive and unsustainable. While sampling may be required for feasibility reasons, it does carry with it the possibility of introducing bias. Registries that employ sampling strategies should consider using statistical tools to predict the bias from a given sampling frame.2

	Because the design of a QI registry involves multiple variables-and often multiple stakeholders-pilot testing can be a valuable step. Pilot testing allows the registry developers to identify and address major issues before the registry formally launches. For example, participants may find that enrollment procedures are confusing, that some required data are not routinely collected or that data definitions are not clear. These issues can be addressed promptly, through either training or modifications to the registry design, thus helping to ensure a smooth registry launch.

	Last, registry developers must plan for change. Because QI registries often collect data for multiple years with no defined endpoint, the registry may need to adapt to changing treatment patterns, the introduction of new therapies ,and revised guidelines and/or quality-reporting requirements. QI registries must be flexible in order to remain relevant to stakeholders in the face of a changing environment.

	The value of the registry is ultimately determined by the quality of the registry data. Registry developers must decide on a plan for quality assurance and implement it once the registry launches. Quality assurance plans for QI registries may emphasize two areas: 1) enrollment procedures; and 2) data entry. Because QI registries are focused on improving care and patient outcomes and documenting provider-level behavior around those objectives, there is a possibility that participants may “cherry pick” patients-that is, selectively entering the patients who received the appropriate care and/or had the best outcomes. This is a particular concern in registries where performance is linked to economic incentives. Quality issues may also arise from honest mistakes. For instance, manual data entry introduces a risk of typographical errors. Some errors can be identified through the incorporation of automated processes that perform range checks, data-format checks and so on (e.g., logical inconsistencies), but other errors are more difficult to identify (e.g., neglecting to document a patient’s history of heart failure).

	Data audits-either onsite or remote-are commonly used to assess the registry data quality. With onsite audits, a trained staff person compares registry data with source documents, such as case report forms. In a remote audit, the source documents are sent to a central location for comparison with the registry data. To manage costs, registries typically audit a portion of the data from a portion of the participating sites on a regular basis. Audits may provide valuable information on data elements with low completion rates or identify areas where additional training is needed.

 Audit findings, particularly when they demonstrate a high quality of data within the registry, may also be useful when publishing findings from the registry.

	Ultimately, for a QI registry to achieve its fundamental goal of improving patient care and outcomes, the results from a QI registry must be reported to-at minimum-the participants, and possibly to patients and the public. The Centers for Medicare & Medicaid Services (CMS), for example, is undertaking public reporting in response to the Patient Protection and Affordable Care Act.

 Research on the effect of public reporting, though, produces conflicting results. For example, one study concluded that public reporting significantly decreased mortality after coronary artery bypass surgery.

 Nonetheless, a meta-analysis of 45 studies concluded: “The effect of public reporting on effectiveness, safety, and patient-centeredness remains uncertain.”

 As a result, designers must weigh stakeholder needs and concerns against the available evidence to reach their own conclusions about publicly reporting data from a QI registry.

	Actual examples of QI registries depict some key design features and how to address challenges. The American Heart Association and the American Stroke Association developed Get with the Guidelines

, which is a multipart program for quality improvement for patients in hospitals. In 2003, the associations started Get with the Guidelines

-Stroke to increase the odds that in-hospital patients get the most advanced treatment. This QI registry collects data on the patients and generates real-time reports on outcomes and other results that help hospitals treat patients more effectively. So far, this QI registry includes over two million patients at more than 1,600 hospitals, and many journal articles reveal the ongoing value of this registry (Figure 1).

	To improve in-hospital patient care, Get with the Guidelines

-Stroke incorporates a cycle of plan, do, study, and act (PDSA). That is, a hospital plans initiatives designed for quality improvement, which get put in place and studied; then, hospital members use the outcome to act, by adjusting the initial initiatives. The resulting compliance reports show a hospital how it performs relative to, for example, other hospitals in the same region or similar-size hospitals.

	To accomplish these goals, this registry’s designers needed a core dataset that would provide enough information for evidence-based medicine and still be reasonable to collect. Consequently, the registry required the smallest dataset that would provide actionable results. In addition, hospitals receive no compensation for collecting data for Get with the Guidelines

-Stroke, which adds impetus to keep the process as simple as possible.

	To accommodate the competing interests, the QI registry’s designers started with the desired recognition measures and worked in reverse to the required dataset. The resulting dataset includes questions that assess a facility’s compliance with stroke guidelines for patient care, and the questions evolve to reflect advances in treatment.

	This example shows the value of focusing on the desired outcomes of a QI registry during the design phase, particularly in selecting the elements of the dataset and keeping it as small and simple as possible. Moreover, the developers can update the dataset over time to keep a registry relevant.

	Every QI registry must be designed to meet specific, unique needs, and that proved particularly challenging for the National Parkinson Foundation Quality Improvement Initiative. This QI registry collects longitudinal data on treatments and patient-reported outcomes for Parkinson’s disease (PD) to determine and report on the best clinical care. The National Parkinson Foundation started this registry in 2009, and it now collects data on 5,000 patients at 20 international sites.

	Given PD’s incurable nature, the treatments aim at reducing a patient’s symptoms and improving quality of life. Patient-based outcomes provide the best measurements of these features, but variations in diagnosis and treatment create challenges in selecting the best measures. In fact, this QI registry emerged from the need for evidence-based treatment standards. The resulting dataset includes many elements, from demographics and comorbidities to medications and outcomes-all collected annually on simple forms.

	The registry data help researchers understand the factors that play the biggest roles in quality of life for PD patients

 and offer insights into challenges for caregivers,

 thus illustrating the value of QI registries for chronic, progressive conditions.

	QI registries may collect large amounts of data over many years in support of their primary objectives. These data, however, may be able to support other research, in the form of secondary analyses or through linkage to other datasets. For example, the data may be stratified for analysis-such as grouping patients by gender, age, or geographic location-to examine variations in treatment patterns.

 The data from a QI registry can also be combined or compared with other datasets. For example, one research study combined a QI registry on cardiovascular events with a claims database to determine the validity of claims by Medicare patients.

	A QI registry can also be modified to support research; for example, some sites may participate in a substudy that collects long-term follow-up information, while other sites collect only the core registry data. Modifying QI registries in this manner requires clear objectives, training, and a continued focus on minimizing burden for participants.

	The central goal of a QI registry is to improve healthcare outcomes for patients, and, like all types of registries, QI registries must define clear, relevant objectives, select an appropriate design, and focus on data quality. In addition, QI registries must work with stakeholders to maximize value, remain feasible, and ensure sustainability.

Michelle Leavy, MPH, Manager, Health Policy, Real-World & Late Phase Research, Quintiles; and Daniel M. Campion, MBA, Research Director, Real-World & Late Phase Research, Quintiles

	1. N. Johnson, L. Vermeulen, K.M. Smith. “A survey of academic medical centers to distinguish between quality improvement and research activities,” 

 “Selection bias in population-based cancer case-control studies due to incomplete sampling frame coverage,” 

Cancer Epidemiology, Biomarkers & Prevention

 “Data quality in the American Heart Association Get With The Guidelines-Stroke (GWTG-Stroke): results from a national data validation audit,” 

 “The National Cardiovascular Data Registry (NCDR) Data Quality Brief: the NCDR Data Quality Program in 2012,” 

Journal of the America College of Cardiology

	5. Centers for Medicare & Medicaid Services. Public Reporting.  

http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/physician-compare-initiative/Public_Reporting.html

 “Improving the outcomes of coronary artery bypass surgery in New York State,” 

Journal of the American Medical Association

 “Systematic review: the evidence that publishing patient care performance data improves quality of care,” 

	8. L.H. Schwamm et al. “Temporal trends in patient characteristics and treatment with intravenous thrombolysis among acute ischemic stroke patients at Get With The Guidelines-Stroke hospitals,” 

Circulation: Cardiovascular Quality Outcomes

	9. E. Cumbler et al. “Quality of care and outcomes for in-hospital ischemic stroke: findings from the National Get With The Guidelines-Stroke,” 

 “Get With the Guidelines-Stroke is associated with sustained improvement in care for patients hospitalized with acute stroke or transient ischemic attack,” 

	11. J.G. Nut et al. “Mobility, mood and site of care impact health related quality of life in Parkinson’s disease,” 

	12. O. Oguh et al. “Caregiver strain in Parkinson’s disease: national Parkinson Foundation Quality Initiative study,” 

	13. Y. Xian et al. “Racial/ethnic differences in process of care and Outcomes among patients hospitalized with intracerebral hemorrhage,” 

, DOI: 10.1161/STROKEAHA.114.005620, 2014.

 “Validity of claims-based definitions of left ventricular systolic dysfunction in Medicare patients,” 

Articles

Designing Quality Improvement Registries

With more than 25 million people affected in the United States—and 50 million worldwide—rare disease research and treatment is an important medical necessity. Yet, little research has been done on many rare diseases, leaving both physicians and patients with a lack of treatment options, and, in some cases, with only a basic understanding of the disease itself. New studies focusing on rare diseases often face challenges related to small patient populations, the lifelong nature of the diseases, and variations among disease sub types. Increasingly, researchers are turning to patient registries to fill some knowledge gaps, as registries offer an opportunity to learn much about the way patients are diagnosed and treated and about how they respond to various management approaches. Patient registries have considerable potential to help improve understanding of rare diseases and provide the knowledge base necessary to support development of effective treatments. >

The US Food and Drug Administration (FDA) and the National Institutes of Health (NIH) define a rare or "orphan" disease as any disease that afflicts fewer than 200,000 people in the United States.

  Over 6,800 rare diseases, affecting 25 million Americans, have been identified to date. Rare diseases can cause a wide range of symptoms and may be chronic, progressive, disabling, and life-threatening. About 75 percent of these diseases affect children, and about 80 percent are related to genetic defects.

  Some of the more well-known rare diseases include sickle cell anemia, hemophilia, Tourette syndrome, and Tay-Sachs disease. Less well-known examples include Wilson's disease, Turner Syndrome, and Gaucher disease.   

In general, little is known about most rare diseases. The small number of patients with a rare disease often results in limited clinical experience within individual treatment centers. The clinical description of the disease may be incomplete or skewed, and the medical literature often consists of individual case reports or small case series, limiting understanding of the natural history of the disease. Both the lack of available treatments and the poor understanding of many rare diseases can be linked to the unique challenges that rare disease research poses. The challenges occur across the life cycle of a research study, affecting the study design, ethical considerations, and subject recruitment and retention.  

When designing a rare disease study, it may be impossible to find fundamental information on the disease on which to base the study protocol. For example, data on the disease prevalence and incidence may be unavailable, making it difficult to determine an appropriate study size. Diagnosis may be complex, particularly in cases where there is no definitive test. The development of the study data set may be hindered by a lack of information on the full range of disease symptoms or treatment practices. Selecting appropriate study durations may be difficult, particularly for diseases where new treatments are extending life spans.  

Ethical concerns may also arise in rare disease research. The majority of rare diseases affect children, who are considered a vulnerable population. Designing and conducting studies that enroll children may be more complex than designing studies for adults. For example, the International Conference on Harmonization (ICH) has released detailed operational guidelines for clinical trials in pediatric populations; these guidelines recommend, for example, that studies be performed in institutions with a pediatric infrastructure and appropriate personnel. Parents may be reluctant to consent to research, and there is ongoing debate about what age assent from the child, in addition to parental consent, is necessary for participation.

  Rare disease research may also focus on other vulnerable populations, such as cognitively impaired persons or pregnant women. Rare disease studies need to be sensitive to the needs of these populations. 

Once a study has begun, it may face patient recruitment challenges. By definition, rare diseases have limited patient populations. Patient recruitment can become even more complicated if there are multiple, simultaneous studies of a rare disease, as enrollment in one trial may make a patient ineligible for another trial. Patients with the disease are likely to be widely scattered across the United States or globally. Recruitment may involve a large number of physician offices or specialty centers, and studies may need to include patients from several countries to obtain a sufficient study population. Lastly, retention of patients for the duration of the study is often extremely important, given the small study sizes. Studies generally need to devote significant effort to following up with patients who move or seek care at other locations to keep these patients enrolled in the study. 

Efforts to encourage rare disease research

Economic factors create an additional hurdle to rare disease research, particularly research aimed at developing new treatments for these diseases. For most rare diseases, the costs of developing, researching, and producing effective treatments exceed the expected revenues. This economic reality led to enactment of the Orphan Drug Act in January of 1983. The act established tax and market incentives for developing treatments, also called orphan drugs, for rare diseases. The incentives have been largely successful. Since 1983, the FDA has approved over 350 orphan drugs.

  In contrast, the decade prior to 1983 saw fewer than 10 such products come to market.  

In addition to financial incentives, the FDA encourages rare disease research through the educational activities of the Office of Orphan Products Development (OOPD). The OOPD promotes collaboration among pharmaceutical companies, professional organizations, patient organizations, and academic centers. The office hosts training sessions on developing clinical trials for small sample sizes and provides assistance for product developers in gaining the orphan drug designation. These programs are intended to facilitate rare disease research and orphan drug development. However, it should be noted that orphan drugs are subject to the same regulatory requirements for obtaining approval as other products. Adequate, well-controlled studies must be used to establish safety and efficacy for these products prior to approval.

The US government also encourages rare disease research through the Office of Rare Disease Research (ORDR) at the NIH. The ORDR was established in 1993, but gained significant new funding and authority in 2002 with the passage of the Rare Diseases Act and the Rare Diseases Orphan Product Development Act. The ORDR coordinates research, sponsors educational programs for investigators, recommends national research priorities, and funds new studies of these diseases. The office also sponsors the Rare Diseases Clinical Research Network. Recently, the NIH launched a new effort specifically aimed at producing new treatments for rare diseases. The Therapeutics for Rare and Neglected Diseases program (TRND) is a collaborative effort involving the ORDR, the NIH Chemical Genomics Center, and the National Human Genome Research Institute. The program will create a drug development pipeline within NIH to stimulate research in rare disease treatments. The goal of the program, which will focus on pre-clinical drug development, will be to support drug research until a drug meets the FDA requirements for an Investigational New Drug (IND) application, at which time the drug will be transferred to an outside organization for further development.

Despite these efforts to encourage research into rare diseases, significant knowledge gaps still remain, and randomized controlled trials—the gold standard in clinical research—may be extremely difficult to conduct in rare disease populations due to sample size and length of follow-up limitations. Innovative research methods are needed to overcome the barriers of rare disease research. 

Patient registries are emerging as new tools with considerable potential for rare disease research. A patient registry can be defined as "an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes."

In recent years, patient registries have played an increasingly important role in medical research as stakeholders have emphasized the need for real-world data on patient outcomes and effectiveness from a broad range of patients. In 2007, the Agency for Healthcare Research and Quality (AHRQ) published the landmark handbook, "Registries for Evaluating Patient Outcomes," with a second edition released in September 2010. Reports published in the same year from the Institute of Medicine and the Congressional Budget Office both emphasized the importance of patient registries in developing comparative effectiveness evidence. In the past year, the NIH and AHRQ have issued several new funding opportunities under the American Recovery and Reinvestment Act (ARRA) that specifically focus on registries. The FDA already uses registries in assessing the safety and effectiveness of approved drugs and devices. Since 2005, the FDA Center for Devices and Radiological Health (CDRH) has called for some 120 post-approval studies, many of which use new or existing registries to study the real-world effectiveness of specific devices in community practice.

Patient registries have received particular attention in recent years among rare disease stakeholders, including patient advocacy groups, professional associations, and government agencies. These stakeholders look to patient registries as an efficient, powerful tool for observing the course of a disease, understanding variations in symptoms, treatment, and outcomes, and assessing the effectiveness of existing treatments. Through organized and coordinated clinical investigation systems like patient registries, researchers can accumulate a sufficient number of patients with rare diseases to provide the statistical power needed to study the clinical history of treated and untreated forms of the disease. Registries can also provide basic information, such as data on incidence and treatment patterns, needed for clinical trials of new tests and treatments.

  Two types of registries that are particularly relevant for rare disease research are disease registries and product registries. Disease registries enroll and study patients who are diagnosed with a specific disease. In rare disease research, these registries are often used to gather information on the natural history of the disease or to understand current treatment patterns. Product registries enroll patients who use a particular product. These registries may be used to study the long-term outcomes of patients using a new therapy for a rare disease.  

As previously discussed, rare disease research poses a number of challenges. Patient registries offer several unique features that make them particularly well suited to overcoming these challenges. In terms of study design, the protocol for a patient registry can be more flexible than for a traditional clinical trial. For example, in a disease area where the prevalence and incidence are unknown, a target sample size may be set at the study outset and adjusted during the course of the study, depending on the initial findings. In areas where diagnosis is difficult or not definitive, a registry may be designed to include patients classified as confirmed or probable cases. The registry data may then be used to help identify the most effective means of diagnosis.  

Registry data sets may also be modified over time, as new treatments or procedures become available. This can be particularly important in a registry designed to follow a patient for long periods, such as decades, or even for the remainder of the patient's life. In these registries, it is possible that new treatments will emerge during a patient's lifetime, making it possible to observe both the untreated and treated courses of the disease. In addition, because registry study designs are purely observational, it may be easier, in some cases, to obtain approval to study vulnerable populations, such as children or cognitively disabled people.  

Patient recruitment can still be difficult with a patient registry. However, registries generally have much broader inclusion criteria than trials. A trial may exclude patients using alternative therapies, or patients already enrolled in another trial. These limitations can severely limit the number of eligible patients in an already small population. Rare disease registries, particularly those attempting to understand the course of the disease and treatment patterns, may choose to enroll patients who are already in another trial, or patients pursuing alternative treatments.

While patient registries offer many advantages for rare disease research, there are several limitations to their use. First, patient registries cannot replace the controlled trials used to establish efficacy for new products and to obtain regulatory approval. Second, patient registries, like all observational studies, must address the potential effects of confounding. Study design considerations can help to reduce confounding, while statistical techniques can attempt to account for its effect on the study results. A second complication to the use of patient registries is the significant variation across observational studies in terms of their research methods and data quality. Many methodological improvements have been made in recent years, and good practice principles exist. For example, the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement provides guidelines for reporting the results of observational studies that have been widely adopted by biomedical journals.

  The AHRQ handbook mentioned earlier describes good practices for patient registry design, operation, and evaluation.

In addition to methodological issues, patient registries, particularly those that collect data over long periods, face issues with patient retention. Over a decades-long study, patients may move, or patients or their providers may simply stop participating in the registry. Registries must find ways to sustain patient and provider interest over the life of the registry. Other issues that may face patient registries include managing change as new treatments or procedures become available and ensuring data quality and consistency.  

In addition to the general advantages of advancing rare disease research, patient registries offer specific benefits to manufacturers developing treatments for rare diseases, providers treating patients with these conditions, and the patients themselves. For a drug or device manufacturer developing a product for a rare disease, a registry can be useful in both the pre- and post-approval phases. In the pre-approval phase, a disease registry may be used to advance the understanding of the disease; for example, the registry could provide new insights into the course of the disease or disease sub types, or provide more information on the burden of the disease and its effect on patient quality of life. This information may be important to designing and operating successful clinical trials to test a potential treatment. From a marketing standpoint, a disease registry can help to identify treating physicians and centers with large numbers of patients and to establish distribution channels prior to the launch of a new product.  

In the post-approval phase, a product registry might demonstrate the performance of a product in the real world, provide information on product use patterns, or meet a post-marketing study commitment. The FDA has noted that "through the creation of registries, a sponsor can evaluate safety signals identified from spontaneous case reports, literature reports, or other sources, and evaluate the factors that affect the risk of adverse outcomes such as dose, timing of exposure, or patient characteristics."

  Disease registries may also be useful in the post-approval phase, helping manufacturers better understand and separate the effects of the new treatment from the symptoms of the disease. A manufacturer with an existing disease registry may also consider adapting the registry into a product registry after the launch of a new treatment. This process could involve limiting enrollment of new patients to those using the approved treatment. Alternately, the registry could continue to enroll all patients with the disease, but collect additional data on patients using the new treatment.  

For providers, patient registries offer a tool for learning more about the progression and treatment of a rare disease. Both disease and product registries can help treating physicians connect with a community of their peers, where they can compare their patients' progress and trends to others and to the aggregate. These registries can help foster the formation of an international community of expert physicians who can collaboratively develop recommendations on the clinical management of patients. Evidence has shown that collective clinical experience can lead to the development of recommendations for evaluation and monitoring of patients with rare diseases. The analysis of registry data on treatment outcomes can facilitate the establishment of therapeutic goals for patients with rare diseases.

  This builds a foundation for a consensus and the foundation for a consensus- and evidence-based disease management approach. For example, the use of a patient registry contributed to developing treatment practices that have more than doubled the life span of an estimated 30,000 cystic fibrosis patients.

Patients with a rare disease may also benefit from participating in a patient registry. Registries can provide patients with valuable sources of information on their disease. For example, the registry may develop and distribute educational materials to patients. The registry may also use information collected at each visit to develop custom reports for patients; these reports could track the patient's progress over time on key indicators. Some patients may find satisfaction in participating in a project that will improve the understanding of their disease.   

Many patient registries for rare diseases are already in use. One of the most long-standing is the Cystic Fibrosis Patient Registry. This registry, managed by the Cystic Fibrosis Foundation, has collected information on cystic fibrosis patients in the United States for more than 40 years. The registry includes over 25,000 patients and has contributed significantly to improved care and longer life spans for cystic fibrosis patients.

 Another example is the Gaucher Registry, which was established by Genzyme in 1991. The goals of the registry are to improve the understanding of Gaucher disease, provide treating physicians with recommendations to optimize patient care, and to evaluate the long-term effectiveness of enzyme replacement therapy. The registry includes data on more than 4,500 patients, collected from participating providers in 56 countries. Several publications have resulted from the registry data.

  Registries also exist for many other conditions, including Fabry disease, Pompe disease, and congenital cytomegalovirus. No complete list of orphan disease registries exists today, except to the extent they are listed in 

. This may change, though, as interest in rare disease registries is growing. 

The current interest in rare disease patient registries will likely lead to the development of many more such registries. However, the development of each individual registry requires significant effort and resources. For some diseases, well-organized private foundations or manufacturers with an interest in product development or monitoring are capable of developing effective registries. To date, private foundations and manufacturers have generally developed registries independently, and, currently, there are no widely used models for collaboration or data sharing. However, private foundations are moving toward developing clearer rules for engagement with manufacturers. 

For many other diseases, there are few resources to support an independent registry. Some efforts are underway to develop linked networks of registries for rare diseases. For example, the NIH has put forth the idea of creating a federation of Internet-based registries for rare diseases. The goal of this effort is to reduce the costs of developing and running a registry. The idea was part of the discussion at a January 2010 conference on patient registries and rare diseases sponsored by the NIH's Office of Rare Diseases Research.

Another major issue for rare disease registries in the near future will likely be the collection and storage of biosamples. Much research is focused on the genetic origin of rare diseases, and researchers are increasingly interested in obtaining and storing biosamples from patients for future analysis. Storage of biosamples raises new legal, ethical, and logistical issues, particularly for global registries. These challenges will need to be addressed to support ongoing genetic research. 

Patient registries offer many advantages for rare disease research, due largely to their flexible design and ability to follow a broad group of patients for long periods. Given these advantages and the positive results of rare disease registries to date, it is likely that more rare disease registries will be developed in the near future. These registries may play an important role in improving understanding of rare diseases, developing guidelines for disease treatment and management, and providing information to support the development of new treatments. 

 MPH, Senior Research Associate at Outcome Science Inc, 201 Broadway, Cambridge, MA.

* To whom all correspondence should be addressed. 

 National Institutes of Health, Office of Rare Disease Research, "Rare Diseases and Related Terms," 

http://rarediseases.info.nih.gov/RareDiseaseList.aspx?PageID=1

 National Institutes of Health, National Human Genome Research Institute, "Rare Diseases Day 2010," 

 Denis Gill and Ronald Kurz, "Practical and Ethical Issues in Clinical Trials," 

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