National Academies Press: OpenBook

A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration (2011)

Chapter: 5 Case Study of a Strategic-Investment Decision

« Previous: 4 Case Study of a Targeting Decision
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

5
Case Study of a Strategic-Investment Decision

This chapter describes a case study that uses the committee’s framework to characterize the public-health consequences associated with two medical devices under current and enhanced postmarket-surveillance programs. The decision of whether to implement the enhanced postmarket-surveillance system is an example of a strategic-investment decision. The case study was selected because it is relevant to a scenario provided to the committee by the Food and Drug Administration (FDA) and there was relevant expertise on the committee. The data used were gleaned from publicly available Web sites or publications or were provided by FDA. The committee did not conduct exhaustive literature searches or reviews, and all information is illustrative. The case study simply provides an illustration of how the committee’s framework might be used for a strategic-investment decision.

FRAMING THE ISSUE: MEDICAL DEVICES AND POSTMARKET SURVEILLANCE

The FDA Center for Devices and Radiological Health regulates an estimated 220,000 devices, reviews around 3,500-4,000 new products each year, and monitors some 1,000 product recalls each year. Items as varied as tongue depressors, tubing, and pacemakers are under the purview of this FDA center. At the approval stage, medical devices are labeled as Class I, II, or III on the basis of the control needed to ensure the safety and effectiveness of the devices; Class III products are life-supporting and life-sustaining devices. For recalls, the order of severity is reversed. Class I recalls involve dangerous or defective products that predictably could cause serious health problems or death, such as a defective artificial heart valve; Class II recalls involve products that could cause temporary health problems; and Class III recalls involve products that are

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

unlikely to cause any adverse health effect. In 2009, FDA reported that there were 160 Class I recalls, over 500 Class II recalls, and 172 Class III recalls (FDA 2010a). Not all the recalled products were in clinical use, so the recalls may have prevented additional future exposures.

Many recalls of implanted medical devices are based partly on postmarket surveillance data. A universal, one-size-fits-all system for medical-device reporting and postmarket surveillance has not yet reached the level of success that FDA would like. The existing FDA medical-device reporting systems—Manufacturer and User Facility Device Experience (MAUDE) and Medical Device Reporting (MDR)—contain a great deal of information that cannot be reliably analyzed, and the agency is studying new approaches to postmarket surveillance under the Sentinel Initiative.

Under MDR requirements, manufacturers of medical devices are required to report deaths and serious injuries caused by malfunctions of medical devices to FDA. User facilities are required to report serious injuries associated with medical devices to their manufacturers and to report deaths to both the manufacturers and FDA (FDA 2009a). Data from 1991 through 1996 are in the MDR database, and data from various sources from 1991 to the present are in the MAUDE database (manufacturer and user-facility reports since 1996 are included in MAUDE) (FDA 2010b). Although the systems include useful information on the number and types of adverse events associated with medical devices, they do not include clear information on the number of people who use the devices, and that makes it difficult to estimate the rate of such adverse events and therefore difficult to detect changes in the rate.

Medical-device registries have some appeal, but it is probably not possible to implement them for all medical implants that are in general clinical use. There is a device registry in place for ventricular assist devices (VADs): INTERMACS® (Interagency Registry for Mechanically Assisted Circulatory Support) is a national registry for patients who are receiving mechanical circulatory-support device therapy to treat advanced heart failure. This registry was devised as a joint effort of the National Heart, Lung, and Blood Institute, the Centers for Medicare and Medicaid Services, and FDA and was formed to analyze clinical outcomes, device durability, adverse-event rates, and costs. Analysis of the data collected is expected to facilitate improved patient evaluation and management and aid in better device design and development. Registry results are also expected to influence future research and system design and facilitate appropriate regulation of VAD implants. About 85% of all VAD implants are enrolled in the registry (D.C. Naftel, University of Alabama at Birmingham, personal. commun., March 7, 2011).

DECISION CONTEXT FOR THE CASE STUDY

This case study focuses on medical implants that make direct contact with tissues other than the skin. They constitute a pool of about 20,000 medical im-

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

plants designed for various periods of use (months to years) and are manufactured by domestic and foreign companies. A paracorporeal infusion pump is defined as a medical implant for this study, and transdermal patches worn on the skin are not. The rationale for a focus on medical implants is partly the postmarket-surveillance scenario identified by FDA (see Appendix C) and partly the fact that patient compliance does not have to be considered as a factor in estimating the effects (the patient is by definition compliant with a medical implant because it can be modified only with surgery).

The strategic-investment decision considered here is whether FDA keeps the reporting system as it is or invests in enhanced postmarket surveillance of two specific medical devices—artificial knees and VADs. The former is an established technology that is used extensively across the country and has a long history of clinical use in a large patient population. The latter is an emerging technology in limited use and, as noted above, the subject of a comprehensive registry (INTERMACS).

There are many ways that an enhanced postmarket-surveillance system could be designed, but the goal should be to find types and patterns of unexpected adverse events. Such patterns may point to problems in design, implantation processes, clinical interventions, or manufacturing variances; early detection of such problems should lead to improvements. The information gathered in a postmarket-surveillance system would be of value not only to FDA but to the medical-device industry and to individual patients. FDA's New Molecular Entity Postmarketing Safety Evaluation Pilot Program to evaluate accumulated information within some specified period after a drug is approved for marketing is an example of such a reporting system (FDA 2009b). Systems currently under development include FDA’s Sentinel Initiative and MDEpiNet programs, which are intended to provide new surveillance capabilities for device-related adverse events (FDA 2011a,b). Better information on the effects of medical implants on individual patients—in particular, insights from patient social networks as noted below—could also be useful for patients and physicians engaged in shared decision-making (Charles et al. 1997).

The committee defined the enhanced surveillance system for this case study as one that would require manufacturers and hospitals—which are more able to determine the number of medical implants—to report both numbers and rates of device-related deaths and unexpected adverse effects and to report marked changes in adverse-effect rates. With modern information-technology capabilities, it may be feasible now to develop systems to flag and report effect-rate changes. The enhanced system would also include direct and indirect efforts to gain more information directly from patients by, for example, using social networks for rapid patient feedback on quality of life and health issues related to the implants. Finally, the hypothesized postmarket-surveillance system would include not only additional data collection and tracking but analysis of adverse-event data and, when appropriate, would incorporate lessons from the surveillance data into patient-selection guidelines and recommendations for postimplantation care.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

CHARACTERIZING THE PUBLIC-HEALTH CONSEQUENCES

This section summarizes the use of the risk attributes to characterize the public-health consequences associated with the current postmarket surveillance and the hypothetical enhanced surveillance of artificial knees and VADs. The committee estimated the values for each of the risk attributes in the current system by using scientific literature and subjective judgments based on available information (given its limitations). For the enhanced system, the values were developed on the basis of several overarching assumptions: that enhanced surveillance would lead to better understanding of the risks and the risk factors associated with each device and that action would be taken according to that information, as appropriate, to improve patient outcomes through improved patient selection and postimplantation care and follow up. The committee also assumed that better tracking of adverse events improves the ability to prevent adverse effects, to detect them if they occur, and perhaps to mitigate them. Table 5-1 summarizes the comparison.

Several challenges that are unique to evaluation of postmarket surveillance of implanted medical devices arose in this case study. First was the issue of data availability and the current state of information-tracking and reporting responsibilities. Although the most important and most useful information to have is information on rates of unexpected adverse events, those data are not collected or reported. When a person who has an implant (or more than one implant) dies, the death is reported, but the death may or may not be related to the implant. The lack of available data leads to substantial uncertainty in the estimates of the number of adverse health effects associated with the devices, as shown in Table 5-1. Second was the difficulty of developing estimates of the effects under an enhanced postmarket-surveillance system without a detailed definition of what that system would look like. Many ways of designing such a system could be envisioned, and for this case study the committee assumed only that improved information on adverse-event rates would somehow be obtained.

Artificial Knees

Artificial knees provide increased mobility and decreased pain and are generally implanted in adult patients with relatively good health. The mortality risk due to the knee replacement is primarily in the 90-day postoperative period. In terms of quality of life, people can resume hobbies or work activities that were restricted because of pain. Moss et al. (1991) contains 1988 data on selected medical-device implants in the United States, including artificial joints and heart valves. Data are provided on type of implant, number of each implant type (such as two artificial joints), socioeconomic characteristics, and reasons for implantation. Additional information on artificial knees can be found in AAOS (2009) and Palmer and Cross (2010).

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

TABLE 5-1 Risk Attributes for Strategic-Investment Decision for Medical Devices

Attribute

Metric

Decision Options

Artificial Knees

Ventricular Assist Devices

Current System

Enhanced System

Current System

Enhanced System

Exposed population

Number who use the product or resource in a year

5 million

(2-8 million)

5 million

(2-8 million)

3,000

(1,000-5,000)

3,000a

(1,000-5,000)

 

Populations of concern

Most of the exposed population are elderly; women are twice as likely as men to receive implants; other populations with higher than average exposure are people suffering from arthritis

The exposed population consists entirely of people with advanced heart failure; men are 4 times as likely as women to require the implants

Mortality

Number of deaths per year

6,000

(3,000-150,000)

Reduce the uncertainty (the range) by about 85%; for example, the range might be 4,000-26,000

300

(200-400)

Reduce the uncertainty (the range) by about 35%; for example, the range might be 220-350

Morbidity

Number experiencing severe adverse health effects per year

80,000

(15,000-130,000)

Reduce the uncertainty (the range) by about 30%; for example, the range might be 20,000-100,000

410

(240-510)

Reduce the uncertainty (the range) by about 40%; for example, the range might be 300-460.

 

Number experiencing less severe adverse health effects per year

1.25 million

(1-1.5 million)

No change

1,500

(1,000-2,500)

No change

 

Number per year experiencing adverse health effects that affects only quality of life

No estimates developed

Personal controllability

For operative and 90-day postoperative risks

100% of patients have the ability to avoid or reduce the risks associated with implantation of an artificial knee

Less than 40% of patients have the ability to avoid or reduce the risks of VAD implantation.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

 

For risks associated with living with the implants

5-10% of problems with implanted artificial knees can be reduced or managed through personal action by patients

10-20% of problems with implanted artificial knees can be reduced or managed through personal action by patients

Less than 5% of patients have the ability to control or reduce the risks associated with an implanted VAD after surgery

Ability to detect adverse health effects

Ability of informed institution to detect population-level effects associated with product being evaluated

10-25% of adverse health effects caused by artificial knees could be detected and successfully attributed

25-75% of adverse health effects caused by artificial knees could be detected and successfully attributed

About 90% of adverse effects caused by VADs would be detected and correctly attributed

Ability to mitigate adverse health effects

Probability that an informed institution will be able to reduce or mitigate any adverse health effects associated with the specific product being evaluated if such a problem is known to exist

80%

90%

80%

90%

aIf the sole VAD on the market is recalled, there would be no more implants.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Exposed population

The committee used data from several sources to estimate the number of people who are currently living with at least one artificial knee. Because artificial knees carry perioperative risks and some continuing risks associated with living with the device, the committee considered data on the annual number of implants and on the total number of people who live with implants as relevant. Recent data indicate that about 581,000 knee replacements are performed each year (AAOS 2009). By 1988, the total number of people who had knee implants in the United States was 521,000 (Moss et al. 1991); however, no recent data were available on the total number of people living with implants. The committee assumed that artificial knees are in use for about 20 years and that some patients die of causes unrelated to the implants and some require revisions. The committee made a direct judgment that the number of people receiving or living with one or two artificial knees in a given year is about 5 million but could range from 2 million to 8 million. In the terminology of Chapter 2, 5 million is the best estimate of the size of the exposed population, 2 million is the low estimate (defined as about equal to the 5th percentile of a probability distribution of the exposed population), and 8 million is the high estimate (defined as about equal to the 95th percentile).

For the enhanced surveillance system, the committee estimated that there would be no change in the size of the exposed population. Those who currently have knee replacements retain those implants and remain part of the population exposed to the long-term risks associated with the devices. Although new information from the enhanced system might lead to changes in guidance on patient selection for implant operations, the committee concluded that the enhanced system would be unlikely to change the aggregate numbers receiving knee replacements.

Knee-replacement recipients are mainly older adults who have mobility limitations, but they also include teenagers who have arthritis. Roughly twice as many women receive knee replacements as men (among Medicare-funded operations), according to data from Katz et al. (1996). The committee assumed that the sex ratio would not change in the enhanced surveillance system.

Mortality and Morbidity

Most deaths of knee-replacement patients occur in the 90-day postoperative period, although infections or other adverse effects can occur in the later years of living with the device. Complications that may arise after total knee-replacement surgery include blood clots, infection, patellofemoral complications, neurovascular complications, fractures around the prosthetic, loosening of the prosthetic, and excess scar tissue that can cause restriction of knee movement. Most of the adverse effects occur in no more than 1% of patients; patellofemoral complications are the most common reason for reoperation. Loosen-

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

ing has the highest incidence (5-10% of patients 0-15 years after initial surgery). There have been improvements in devices, and those with more recent implants may face lower risks than those living with older implants.

There are a variety of mortality estimates in the literature (see Table 5-2 for selected values), from which the committee estimated 0.5% 90-day postoperative mortality rate.

For mortality under the current system, the committee calculated estimates as follows:

  • Low Estimate. The low estimate is the product of 90-day postoperative mortality rate (0.5%) and the number of operations performed each year (600,000), which yields 3,000 deaths each year.

  • Best Estimate. The best estimate is 2 times the low estimate and includes both the 90-day postoperative deaths and an assumption that an equivalent number of device-related deaths occurs in the population living with artificial knees.

TABLE 5-2 Mortality Estimates

Description

Value

Reference

Overall mortality rate

<1%

Palmer and Cross 2010

In-hospital 30-day mortality rate

0.12%

UAMS 2010

30-day mortality rates

0.41-0.73%

Taylor et al. 1997

 

0.36%

Gill et al. 2003

 

0.21%

Parvizi et al. 2001

90-day mortality rate

0.46%

Gill et al. 2003

90-day postoperative mortality rate after first surgery; rate derived from Medicare claims

0.7%

Mahomed et al. 2005

90-day postoperative mortality after revision surgery; rate derived from Medicare claims

1.1%

Mahomed et al. 2005

Cumulative survival rate at 5.5 years

97.1%

Paxton et al. 2010

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
  • High Estimate. For the high estimate, the committee estimated the number of artificial-knee recipients in the United States who would die in a year and attributed all those deaths to the implants. In the general U.S. population, eight of 1,000 people die each year from any cause; older people have higher death rates, ranging from about 9 per 1,000 for people 55-64 years old to 50 per 1,000 for people 75-84 years old (NCHS 2010). Because artificial-knee recipients are typically older adults, the committee used an estimate of a 3% annual death rate in the exposed population of 5 million, for an estimated 150,000 deaths per year. The high estimate accounts for the fact that a large exposed population of 5 million who live with the devices presents the potential for a large number of people to die from some sort of implant-related complications.

Potential severe adverse effects of artificial knees include the perioperative risk of serious complications and the potential for adverse effects after implantation that may lead to the need for surgical intervention, such as patellofemoral complications, arterial thrombosis, and loosening. Mahomed et al. (2005) found the following 90-day postoperative complications associated with knee replacements among Medicare claims: 4.7% readmissions, 1.8% wound infection, 1.4% pneumonia, 1% myocardial infarction, and 0.5% pulmonary embolism. In a 7-year study of 39,286 primary total knee arthroplasties, Paxton et al. (2010) found that 1.7% were revised by the date of the study, 0.7% were revised because of infection, and 0.3% were revised because of instability.

On the basis of that information, the committee’s low estimate of the number of severe adverse health effects is 2.5% of the 600,000 implants per year (that is, about half the rate of readmissions among Medicare claims). The best estimate of 80,000 severe adverse effects is based on an assumption that about 5% of all patients who receive an implant in a year will have one of the severe complications identified by Mahomed et al. and about 1% of those living with an artificial knee will experience a severe adverse effect associated with that implant. Each of the potential severe adverse effects described generally occurs in less than 1% of the exposed population except loosening, which is expected to occur in 5-10% of patients from 0-15 years after surgery. The high estimate is that such effects would occur in 2% of the exposed population combined with the 5% of the population who receive an implant and suffer a severe complication.

For less severe effects, the committee assumed that the effects would include nerve injury and less serious infections that could be treated with antibiotics. The best estimate is 25% of the exposed population of 5 million, the low estimate is 20% of the exposed population, and the high estimate is 30% of the exposed population.

The committee did not attempt to estimate the number of patients who experience adverse health effects important enough to affect their quality of life but not important enough to require medical attention or otherwise meet the definition of “less severe adverse effects.” Although some such effects may occur, estimating them is exceptionally difficult in this case because knee replace-

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

ments are associated with increases in quality of life, such as greater mobility and less pain; this greatly confounds any attempt to monitor or estimate adverse effects on quality of life that do not require some medical attention.

As described above, the hypothetical enhanced postmarket-surveillance approach defined for this case study focuses on gaining better information on the number and rates of adverse events through enhanced reporting requirements and direct and indirect patient outreach. The committee also assumes that the information collected through the enhanced surveillance would enable the medical community to take actions—to improve patient-selection criteria and to develop improved monitoring and follow-up of higher-risk patients. For example, there might be guidance on getting more x-ray examinations and clinical inspections of knees in higher-risk patients before and after implantation that would allow earlier detection and correction or avoidance of current or future life-threatening problems.

Those two features lead to two effects. First, improved information on adverse-event rates will reduce the uncertainty in the annual number of those adverse events (for example, the difference between the high and low estimates shown in Table 5-1 would be smaller with the enhanced surveillance than with the current system). It is not possible, however, to specify exactly how the high and low estimates would change, only that the difference between them would be smaller. For the annual number of deaths, for example, the current estimate is that 3,000-150,000 people die each year because of an artificial-knee implant. With better information, that range might be reduced by about 85%. But the end points of the estimated range could be 4,000-26,000, 5,000-27,000, or some other range; there is no credible way to estimate the precise end points of the range. Accordingly, Table 5-1 contains a brief description of the expected reduction in the uncertainty in the numbers of deaths and other adverse effects associated with the enhanced surveillance system and an example of what a new range could be (that is, what a more accurate estimate would look like).

Second, the assumption that the enhanced postmarket-surveillance system would enable medical providers to improve patient selection, monitoring, and follow-up suggests that the overall rates and annual numbers of deaths and severe adverse effects will be reduced over time as the improvements take effect. Because artificial knees have been in use for many years, much of the potential improvement in patient selection and monitoring may have already been attained, so the committee estimated negligible change in the number of adverse effects that would occur because of the added surveillance of the implants, at least in the short term.

Personal Controllability

The primary methods by which people can eliminate or reduce their own personal risk of death or serious 90-day postoperative adverse effects are by declining to have the knee replacement and by careful selection of hospitals and

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

physicians with low adverse-effect rates. Medical informed consent requires that patients be informed of the risks associated with a proposed treatment or procedure, so it is reasonable to assume that they make the choice to undergo knee replacement willingly and with knowledge of the risks that they face from the surgery. Artifical knees are not a life-saving technology, so the committee assumed that all patients who receive an implant in a given year have the ability to control their risks (that is, could choose not to have the implant). Enhanced postmarket surveillance would not change that aspect of personal controllability.

For patients who already have an artificial knee, the ability to control the risks associated with that implant are substantially less. People have no ability to reduce the chances of device failure; they have limited ability to reduce the consequences of such failures through basic health maintenance and appropriate postoperative physical therapy and by seeking prompt medical attention if problems develop. However, it may be difficult for a patient to detect a problem or to associate adverse health effects with the implant when they do not directly involve the knee implant itself, such as bloodborne infections that result from a dental treatment and effects on ligaments or muscles in other parts of the body. The committee estimated that 5-10% of the problems that arise with existing implants could be managed or reduced by individual actions by the patient. The hypothesized enhanced postmarket-surveillance system is designed to provide more and better information to the patient population and to the medical community and includes an assumption of increased use of social media to reach those patient populations. The committee estimates that the resulting increase in patient awareness of the various problems that can occur and steps that they can take to minimize the problems will lead to an increase in the controllability of the effects.

Ability to Detect Adverse Health Effects

Artificial knees that have been implanted more than a few years are examined when a patient chooses to return to an orthopedist; examinations are recommended every 2-3 years. However, the patient may not detect some problems or might not see an orthopedist about a possible problem even if walking becomes more difficult. Problems with knee replacements can lead to other problems (such as in ligaments or muscles in other parts of the body) that may not be readily recognized as being linked to the knees by patients or physicians. On the basis of the required reporting data for medical implants, it appears that only the device manufacturers would have sufficient data to identify systematic or population-level adverse effects, and they rely on adverse-event reporting from the facilities. Given the relatively long chain of reporting with multiple opportunities to miss signals, the committee judged that relatively few systematic problems would be detected—perhaps 10-25%.

In the enhanced surveillance system, the ability to detect a problem would improve. The hypothesized enhanced surveillance system focuses specifically

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

on obtaining better, more accurate estimates of the rates of adverse events, and changes in those rates—exactly the type of information needed by institutions to detect emerging risks. The enhanced system delivers more accurate rate information that allows identification of higher-risk patient populations and improved guidance in patient selection and monitoring, all of which increases the ability to detect systematic problems. For example, risks of long-term effects, such as unexpected toxicity from device materials, might be detectable by institutions in a surveillance system that could institute enhanced monitoring of at-risk patients. The committee estimated that with enhanced surveillance systems, the ability to detect problems would increase by a factor of 2-3 and estimated that 25-75% of such problems could be detected and successfully attributed.

Ability to Mitigate Adverse Health Effects

As noted in Chapter 1, medical devices are highly regulated FDA products. The Center for Devices and Radiological Health conducts premarket reviews and monitors the manufacturing processes and uses of its regulated products. Premarket and postmarket inspections of manufacturing facilities are conducted, and imports are reviewed to ensure compliance with FDA standards. If a systematic problem does occur with a device, institutions can (or can attempt to) examine all relevant implant patients once that problem is detected. The adverse effects can typically be mitigated for the individual patient, although such mitigation may on occasion involve a substantial medical intervention, including possible replacement of the implant. The primary challenge is to identify and examine the relevant patients—determining who has an implant that might be at risk and encouraging the person to visit an orthopedist. Some patients will have moved and be lost to follow-up; others may have changed health-care providers, and the new providers may or may not have sufficient information available to them to identify a patient as being at risk. The committee estimated that about 80% of all patients with a device with identified problems could be located and examined and have their problems corrected.

In the enhanced surveillance system, the probability that an institution can mitigate a problem is improved. Again, the improvement is likely to come from the fact that more accurate data on adverse events would lead to more accurate identification of at-risk patient groups, and more targeted outreach to those patients could occur. The committee estimated that in the enhanced surveillance system, the ability to mitigate adverse effects increases to about 90%.

Ventricular Assist Devices

VADs are medical devices implanted in patients who have advanced heart failure and are ineligible for heart transplantation. They are electromechanical systems designed to assume the work of a patient’s left ventricle, improve coronary arterial perfusion, and provide systemic blood flow to all tissues and or-

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

gans. They allow the generally bed-ridden patients to resume moderate activities.1 Many advances have been made over the years with VADs, and more information can be found in Carr et al. (2010).

This medical-device class was chosen for this case study because it is an emerging technology that recently received FDA approval and the number of VAD patients is relatively small. The technology is entering clinical use in stepwise fashion with careful clinical, industrial, and federal involvement. In many respects, this novel medical technology may serve as a model for the orderly introduction of other emerging high-risk technologies and for enhancing the value of postmarket-surveillance systems for FDA decision-makers.

Exposed Population

For this case study, the committee considered only people who have advanced heart failure, who are generally not eligible for cardiac transplantation, and who may have a permanent VAD implanted. About 20,000-30,000 people may be eligible for VADs, but their use is not yet widespread, so the actual number of people exposed is much smaller than the population of potential VAD recipients. Estimates of exposure were based on data from the INTERMACS registry, the increasing use of VADs, and expert judgment. In 2010, about 3,000 people were listed in the registry as having received a VAD. The number of people living with a VAD may be higher or lower. For example, the INTERMACS registry is not complete; it is estimated that it contains data on 85% of the patients who have implants, and it may contain people who had a VAD and later received a heart transplant or died. On the basis of those data, the committee estimated that 1,000-5,000 people are living with VADs, representing the low and high estimates, respectively. The best estimate is that about 3,000 people are living with the devices. As the use of VADs increases, the number of people living with them will also increase; the data above and in the table provide a snapshot of the current status. The enhanced surveillance system is not expected to change the number of people receiving VADs.

Of the 3,000 people, about 20% are women and 80% are men (INTERMACS 2010). In the enhanced surveillance system, the committee concluded, there would not be a change in the sex ratio.

Mortality and Morbidity

To estimate mortality attributable to VADs, the committee considered both perioperative mortality and mortality occurring while people were living with the devices. The perioperative mortality rate for this population is about 5%; of the roughly 1,050 patients who receive VADs each year, about 50 would

1

Although VADs are used for shorter periods in patients who are to undergo cardiac transplantation, that use is not considered here.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

be expected to die (Kirklin et al. 2010). The annual mortality rate for patients who have VADs is about 10%; of about 3,000 patients who have VADs, about 300 would be expected to die each year. Using expert judgment and the data described, the committee estimated that 200-400 people will die each year in connection with use of VADs. The best estimate of the number of deaths is 300 (10% of the 3,000 people who have VADs). The committee notes that a VAD is a life-saving medical device: the mortality rate is reported to be about 80% for heart-failure patients who do not get VADs (Terracciano et al. 2010). However, for the purposes of this case study, the committee emphasizes that we are not providing an estimate of the benefit of having VAD technology available but rather are focused on the benefits of conducting enhanced postmarket surveillance of those who receive VADs.

To estimate the number of severe adverse health effects, the committee reviewed data on replacement and disabling stroke rates in VAD patients; stroke is a relatively common effect that meets the definition of severe adverse effects provided in Chapter 2. In clinical-trial patients, 16% had a baseline history of stroke, and 46% were free from disabling stroke and reoperation 2 years after implantation of a VAD (Slaughter et al. 2009). The same trial data indicate that there is 0.13 stroke per patient-year within 2 years after receiving a continuous-flow VAD implant and a 0.22 stroke per patient-year for pulsatile-flow VAD. The trial data also showed that 10% of devices were replaced at 2 years (that is, a 5% probability per year).

Using the probabilities for disabling stroke and for replacement, the committee estimated that in the current system a median of 410 people experience severe adverse health effects annually:

  • 150 have to have VAD replacement within a year (5% of 3,000).

  • 260 have strokes that are debilitating after receiving a VAD (0.13 stroke per patient-year for the 2,000 patients assumed to be within 2 years of initial replacement).

Using a VAD replacement rate of 3% and a disabling stroke rate of 5%, the committee estimated the 5th percentile to be 240, and using a VAD replacement rate of 7% and a disabling stroke rate of 10%, the committee estimated the 95th percentile to be 510.

Less severe adverse health effects that could follow VAD implantation include effects that would follow hospital release, such as drive-line infection, arrhythmia, renal or hepatic effects, thrombosis, and faulty battery or connections. In the current system, the committee assumed that 50% of those living with VADs experienced such effects, or 1,500 people experiencing less severe adverse health effects each year. The 5th percentile was judged to be 1,000, and the 95th percentile was judged to be 2,500.

The committee did not estimate the number of people who might experience adverse effects on quality of life because of VADs. As suggested above, VAD implantation is used to extend and improve the quality of life of those in

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

advanced heart failure. Quality of life, for example, can improve from being bed-ridden to being capable of moderate exercise (Slaughter et al. 2009). Those benefits would obscure any adverse effects of the VAD that do not require medical treatment.

As described in the section on mortality and morbidity associated with artificial knees, the effects of improved postmarket surveillance of VAD patients would be to reduce the uncertainty about the rates and numbers of deaths and other adverse health effects and, if that information is acted on, potentially to reduce the number of such effects. As for artificial knees, there is no credible way to estimate the precise end points of the ranges of those numbers before implementing the surveillance program. Accordingly, Table 5-1 contains a brief description of the expected reduction in the uncertainty in the number of deaths and other adverse effects associated with the enhanced surveillance system rather than precise numbers. Because the current system of postmarket surveillance of VADs is already quite comprehensive and the patient population is small, the expected benefits of the enhanced system compared with the current system are smaller than in the case of artificial knees, for which the enhanced system is much more rigorous than the current one.

Personal Controllability

In contrast with artificial knees, VADs are life-saving medical implants used as a destination therapy for patients who have congestive heart failure and are ineligible for transplant. Those for whom the device is recommended are likely to see it as their option of last resort—the only opportunity to extend their lives and to improve their quality of life for the time that remains. Although they technically have the same option to decline surgery as do artificial-knee recipients, that is not likely to be viewed by most as a real option. No data are available on the percentage of patients who are offered a VAD and decline it; the committee estimated that less than 40% of patients in a situation where a VAD would be offered would consider it to be optional and could be considered to have the ability to control their personal risks.

For patients who already have a VAD, the ability to control the risks associated with the implant is substantially lower. People have no ability to reduce the chances of device failure, and VAD patients tend to be older and in poor health at the time of implant, further reducing their ability to exercise personal control over their VAD-related outcomes. The committee estimates that less than 5% of the problems that arise with existing implants could be managed or reduced by individual actions by the patient. Because of characteristics of the patient population, the hypothesized enhanced postmarket-surveillance system is not expected to change the personal controllability of postsurgical VAD risks.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Ability to Detect Adverse Health Effects

Medical professionals follow VAD patients closely, and the goal of the INTERMACS registry is to follow all VAD patients and identify signs of potential problems. Because of that close observation of VAD patients and the use of the INTERMACS registry, the committee concluded that the ability to detect systematic occurrence of adverse effects at the institutional level in either the current system or the enhanced system would be relatively high, that is, 90% or more of potential problems with a VAD would be detected and successfully attributed.

Ability to Mitigate Adverse Health Effects

As noted above, medical devices are highly regulated, and VADs are monitored carefully. However, VAD patients are generally in advanced heart failure and are more susceptible to surgical risks and to adverse events after implantation than are recipients of artificial knees. Although most complications of VADs do not require explant, some situations may require replacement or removal of a VAD, and that might not be possible in some cases because of the overall health of the patient. The committee assumed that in the current system there is an 80% chance that an institution will be able to mitigate any problems that are found that are directly related to the VAD. The committee assumed in the enhanced surveillance system that the probability is improved to 90% because problems may be able to be alleviated quicker with greater surveillance and quicker communication to clinicians.

USING THE RISK CHARACTERIZATION TO SUPPORT DECISION-MAKING

Table 5-1 highlights the public-health consequences associated with two devices under the current and enhanced postmarket-surveillance systems. The differences indicate the benefits of enhanced surveillance. Specifically, the direct public-health benefits of the hypothesized enhanced postmarket-surveillance system compared with the current one are (1) a reduction in the uncertainty about the number of adverse effects attributed to the devices because of better tracking and reporting of adverse effects and their causes, (2) an increase in the ability of informed institutions to detect systemic problems that may be occurring with the devices because of the increased reporting requirements, and (3) a slight increase in the ability to mitigate adverse effects, again arising from the requirement for better reporting and tracking of problems and the assumption that the resulting improvement in understanding will lead to

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

identification of ways to reduce adverse outcomes. For artificial knees, the enhanced surveillance system is also expected to increase the ability of individual patients to manage and reduce their own personal risks because of increased focus on patient outreach and information-sharing.

As in all the case studies, the differences in public-health consequences between the current and enhanced surveillance is only one of several factors that would need to be considered in deciding whether to make an investment in enhanced surveillance. Other factors that might be relevant include the costs and feasibility of implementing and validating an enhanced system, the ability to use the newly acquired data from surveillance to make decisions, and the usefulness of the improved information to the patients themselves in providing better information on patient-specific risks and benefits associated with elective devices.

This case study looked at a relatively simple comparison of “invest” or “do not invest” in an enhanced postmarket-surveillance system, but it raised some additional factors that could be of interest for more complex strategic-investment decisions or other types of decisions related to medical devices. For example, if the decision were to determine which of a variety of surveillance approaches should be pursued, a similar evaluation could be conducted. Rather than characterizing only two options, however, each surveillance approach would have to be defined and evaluated separately. If the decision were to determine on which products a new enhanced surveillance system should focus (that is, a targeting decision for a strategic investment), it may be useful to consider factors beyond the direct public-health benefits of the enhanced surveillance relative to the current system. In particular, applying an enhanced surveillance system to a product for which relevant, high-fidelity data are already being collected by another organization (for example, the INTERMACS registry for VADs described above) could provide a unique opportunity to compare the findings of the new enhanced surveillance system each year with an independent established dataset. That would provide a method for continuous improvement of the FDA surveillance system.

Finally, the committee notes that during the development of this case study, several issues related to medical devices arose that would probably be relevant for other device-related decisions. They include the speed with which health outcomes can be improved if a problem is detected, potentially measured as time between detection and correction; sustained health benefits of a medical implant and the performance of alternatives to the implant, which would be of particular relevance if FDA were evaluating decisions that could change the availability of the implant for potential recipients; and time-dependent projections of levels of exposure and health effects, especially for new products or ones whose use is growing or shrinking.

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

REFERENCES

AAOS (American Academy of Orthopaedic Surgeons). 2009. Total Knee Replacement. American Academy of Orthopaedic Surgeons [online]. Available: http://orthoinfo.aaos.org/topic.cfm?topic=A00389 [accessed Oct. 26, 2010].

Carr, C.M., J. Jacob, S.J. Park, B.L. Karon, E.E. Williamson, and P.A. Araoz. 2010. CT of left ventricular assist devices. RadioGraphics 30(2):429–444.

Charles, C., A. Gafni, and T. Whelan. 1997. Shared decision-making in the medical encounter: What does it mean? (or it takes at least two to tango). Soc Sci Med. 44(5):681-692.

FDA (U.S. Food and Drug Administration). 2006. Guidance for Industry and FDA Staff: Postmarket Surveillance under Section 522 of the Federal Food, Drug and Cosmetic Act. Center for Devices and Radiological Health, U.S. Food and Drug Administration [online]. Available: http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm072517.htm [accessed Nov.8, 2010].

FDA (U.S. Food and Drug Administration). 2009a. Reporting Adverse Events (Medical Devices). U.S. Food and Drug Administration [online]. Available: http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/PostmarketRequirements/%20ReportingAdverseEvents/default.htm#link [accessed Nov. 8, 2010].

FDA (U.S. Food and Drug Administration). 2009b. New Molecular Entity Postmarketing Safety Evaluation Pilot Program Final Report. U.S. Food and Drug Administration [online]. Available: http://www.fda.gov/Drugs/DrugSafety/PostmarketDrugSafetyInformationforPatientsandProviders/ucm185252.htm [accessed Oct. 26, 2010].

FDA (U.S. Food and Drug Administration). 2010a. FDA 101: Product Recalls – From First Alert to Effectiveness Checks. U.S. Food and Drug Administration [online]. Available: http://www.fda.gov/ForConsumers/ConsumerUpdates/ucm049070.htm [accessed Oct. 22, 2010].

FDA (U.S. Food and Drug Administration). 2010b. Manufacturer and User Facility Device Experience Database (MAUDE). U.S. Food and Drug Administration [online]. Available: http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/PostmarketRequirements/ReportingAdverseEvents/ucm127891.html [accessed Nov. 8, 2010].

FDA (U.S. Food and Drug Administration). 2011a. FDA’s Sentinel Initiative. U.S. Department of Health and Human Services, Food and Drug Administration [online]. Available: http://www.fda.gov/Safety/FDAsSentinelInitiative/ucm2007250.htm [accessed Apr. 18, 2011].

FDA (U.S. Food and Drug Administration). 2011b. FDA-TRACK CDRH Office of Surveillance and Biometrics (OSB) Dashboard. U.S. Department of Health and Human Services, Food and Drug Administration [online]. Available: http://www.fda.gov/AboutFDA/Transparency/track/ucm203271.htm [accessed Apr. 18, 2011].

Gill, G.S., D. Mills, and A.B. Joshi. 2003. Mortality following primary total knee arthroplasty. J Bone Joint Surg. Am. 85-A(3):432-435.

INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support). 2010. Quarterly Statistics Report: Implant Dates March 1, 2006 – June 30, 2010. Interagency Registry for Mechanically Assisted Circulatory Support [online]. Available: http://www.uab.edu/ctsresearch/intermacs/Document%20Library/INTERMACS%20Federal%20Partners%20Quarterly%20Report%20June%202010%20website.pdf [accessed Nov. 4, 2010].

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×

Katz, B.P., D.A. Freund, D.A. Heck, R.S. Dittus, J.E. Paul, J. Wright, P. Coyte, E. Holleman, and G. Hawker. 1996. Demographic variation in the rate of knee replacement: A multi-year analysis. Health Serv. Res. 31(2):125-140.

Keefe Bartels, LLC. 2010. Smith & Nephew Oxinium Knee Replacement. Keefe Bartels, LLC [online]. Available: http://www.keefebartels.com/CM/HotTopicsandAlerts/Smith-Nephew.asp [accessed Nov. 8, 2010].

Kirklin, J.K., D.C. Naftel, R.L. Kormos, L.W. Stevenson, F.D. Pagani, M.A. Miller, K.L. Ulisney, J.T. Baldwin, and J.B. Young. 2010. Second INTERMACS annual report: More than 1,000 primary left ventricular assist device implants. J. Heart Lung Transplant. 29(1):1-10.

Mahomed, N.N., J. Barrett, J.N. Katz, J.A. Baron, J. Wright, and E. Losina. 2005. Epidemiology of total knee replacement in the United States, Medicare population. J Bone Joint Surg Am. 87(6):1222-1228.

Moss, A.J., S. Hamburger, R.M. Moore, Jr., L.L. Jeng, and L.J. Howie. 1991. Use of Selected Medical Device Implants in the United States, 1988. Advance Data No. 191. DHHS (PHS) 91-1250. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Health Statistics, Hyattsville, MD.

NCHS (National Center for Health Statistics). 2010. Deaths and Mortality. Centers for Disease Control, National Center for Health Statistics, Hyattsville, MD [online]. Available: http://www.cdc.gov/nchs/fastats/deaths.htm [accessed Nov. 8, 2010].

Palmer, S.H., and M.J. Cross. 2010. Total Knee Arthroplasty. eMedicine Orthopedic Surgery-Knee [online]. Available: http://emedicine.medscape.com/article/1250275-overview [accessed Oct. 26, 2010].

Parvizi, J., T.A. Sullivan, R.T. Trousdale, and D.G. Lewallen. 2001. Thirty-day mortality after total knee arthroplasty. J. Bone Joint Surg. Am. 83-A (8):1157-1161.

Paxton, E.W., R.S. Namba, G.B. Maletis, M. Khatod, E.J. Yue, M. Davies, R.B. Low Jr., R.W. Wyatt, M.C. Inacio, and T.T. Funahashi. 2010. A prospective study of 80,000 total joint and 5000 anterior cruciate ligament reconstruction procedures in a community-based registry in the United States. J. Bone Joint Surg. Am. Suppl 2:117-132.

Slaughter, M.S., J. Rogers, C.A. Milano, S.D. Russell, J.V. Conte, D. Feldman, B. Sun, A.J. Tatooles, R.M. Delgado III, J.W. Long, T.C. Wozniak, W. Ghumman, D.J. Farrar, and O.H. Frazier. 2009. Advanced heart failure treated with continuous-flow left ventricular assist device. N. Engl. J. Med. 361(23)2241-2251.

Taylor, H.D., D.A. Dennis, and H.S. Crane. 1997. Relationship between mortality rates and hospital patient volume for Medicare patients undergoing major orthopaedic surgery of the hip, knee, spine, and femur. J. Arthroplasty 12(3):235-242.

Terracciano, C.M., L.W. Miller, and M.H. Yacoub. 2010. Contemporary use of ventricular assist devices. Annu. Rev. Med. 61:255-270.

UAMS (University of Arkansas for Medical Sciences). 2010. Inpatient Mortality Rate for Knee Replacement. University of Arkansas for Medical Sciences [online]. Available: http://www.uamshealth.com/?id=1240&sid=1 [accessed Oct. 26, 2010].

Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 92
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 93
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 94
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 95
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 96
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 97
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 98
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 99
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 100
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 101
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 102
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 103
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 104
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 105
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 106
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 107
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 108
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 109
Suggested Citation:"5 Case Study of a Strategic-Investment Decision." National Research Council and Institute of Medicine. 2011. A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration. Washington, DC: The National Academies Press. doi: 10.17226/13156.
×
Page 110
Next: 6 Case Study of a Targeting Decision That Spans Food and Drug Administration Centers »
A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration Get This Book
×
Buy Paperback | $46.00 Buy Ebook | $36.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

With the responsibility to ensure the safety of food, drugs, and other products, the U.S. Food and Drug Administration (FDA) faces decisions that may have public-health consequences every day. Often the decisions must be made quickly and on the basis of incomplete information. FDA recognized that collecting and evaluating information on the risks posed by the regulated products in a systematic manner would aid in its decision-making process. Consequently, FDA and the Department of Health and Human Services (DHHS) asked the National Research Council (NRC) to develop a conceptual model that could evaluate products or product categories that FDA regulates and provide information on the potential health consequences associated with them.

A Risk-Characterization Framework for Decision-Making at the Food and Drug Administration describes the proposed risk-characterization framework that can be used to evaluate, compare, and communicate the public-health consequences of decisions concerning a wide variety of products. The framework presented in this report is intended to complement other risk-based approaches that are in use and under development at FDA, not replace them. It provides a common language for describing potential public-health consequences of decisions, is designed to have wide applicability among all FDA centers, and draws extensively on the well-vetted risk literature to define the relevant health dimensions for decision-making at the FDA. The report illustrates the use of that framework with several case studies, and provides conclusions and recommendations.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    Switch between the Original Pages, where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

    « Back Next »
  6. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  7. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  8. ×

    View our suggested citation for this chapter.

    « Back Next »
  9. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!