Table of contents(18 chapters)
The Human Genome Project will revolutionize much of medicine and business. Genetic technologies will let pharmaceutical companies customize products, clinicians predict health outcomes, insurers estimate future health costs, and employers select disease-resistant workers to enhance productivity. However, there are significant costs. Genomic drugs will be expensive, genetically-based insurance underwriting may leave some uninsurable, and genetically-based worker selection may leave some unemployable. Legal protections enacted to date are incomplete, because controlling genetic technologies will require more than new legal rules. It will necessitate rethinking many aspects of medicine and business, including medical data ownership, pharmaceutical development, health insurance, and worker productivity.
We use a data set which contains information on a nationally representative sample of drug purchases in 1996 to investigate the relationship between the type of insurance individuals have for prescription drugs — private insurance, Medicaid, or uninsured — and both the type of drugs they purchase and the prices they pay for drugs. We find that uninsured persons use more generic drugs than privately insured persons but fewer generic drugs than Medicaid recipients. Overall, uninsured persons purchase drugs whose unit costs are 45% lower than the drugs purchased by privately insured persons and 43% lower than the drugs purchased by Medicaid recipients. Differences in unit costs across insurance types reflect differences in the market basket of drugs they purchase. To compare retail drug prices across insurance types we use standardized prices — the retail unit price of each drug relative to a benchmark price. We final that uninsured individuals pay standardized prices which are, on average, 16.5% higher than the standardized prices paid by privately insured persons, and 8.4% higher than the standardized prices paid by Medicaid recipients.
Although previous studies have attempted to isolate the effect of pharmaceutical spending on health outcomes, most have been limited by analysis of inherently heterogeneous inter-country data. This study focuses on one particular health outcome — infant mortality at the state level in the U.S. — and shows that its important determinants include: (1) pharmaceutical expenditures; (2) health economic infrastructure (e.g. number of practicing physicians, number of hospital beds); (3) socio-demographics (e.g. teenage birth rate, low-weight births, high school graduation rate, racial composition of state population); and (4) state-level economic aggregates (e.g. a disposable income, percent of population below the poverty line).
Drugs in the same therapeutic class differ in their therapeutic profile, metabolism, adverse effects, dosing schedules, delivery systems, and other features. In addition, such agents can provide backup if the initial drug sometimes fails in the development stage or in the market. The availability of a broad range of medicines enables physicians to treat with precision the individual needs of diverse patients and provides options when the first agent used is either ineffective or not tolerated. Some incremental innovations have been associated with overall cost savings. Competition among drugs in a therapeutic class drives prices down. Policies that limit research on incremental innovations may deny access to important therapies, reduce competition, and erode incentives for research.
The most significant predictor for health care utilization is the individual's health status. Other factors shown to affect Medicare recipient's use of health care services are income, education, insurance, age, smoking status, place of residence, and having an ongoing relationship with a physician. Less is known about the demographic and socioeconomic factors that affect prescription drug use. Analogously to medical utilization, health status had been determined to be a significant predictor for prescription drug use. Prescription drug insurance has also been shown to increase pharmacy utilization, but its impact on overall health care costs has yet to be determined.
The study considers annual health care utilization and costs associated with human immunodeficiency virus (HIV) infection and the autoimmune disease syndrome (AIDS) complex by applying the previously developed disease and disease combination-specific cost of illness methodology. This study documents changes in age-specific mortality rates indicating the decline in age groups “20–39”. We estimate annual economic losses resulting from twenty-four HIV/AIDS-related diseases among the U.S. population to be $18.2 billion. This estimate includes direct medical cost of almost $9.2 billion, 80% of which is compensated by Medicaid. We demonstrate that an add-on therapy with additional mean cost of $7,100 per person per year would be justifiable if it could reduce the risk of progression to AIDS by 19%.
The change from using clinical endpoints to surrogate marker endpoints in antiretroviral (ARV) trials for human immunodeficiency virus (HIV) disease, combined with the multiplicity of factors that may influence the effectiveness of ART in the community, requires the systematic integration of data through mathematical modeling in order for these data to be useful for most decision makers. Many issues must be considered in the construction of such models, but once constructed the models may be used to compare the expected value, epidemiological, and budget impacts of competing therapies and programs to help select the most cost effective approaches given local conditions.
We study changes in age-specific diabetes-related mortality and annual health care utilization. We find that half of the estimated 16% increase of diabetic mortality falls within employable age groups. We estimate that disease combination-specific increase in case fatality has resulted in premature diabetic mortality costing $3.2 billion annually. The estimated annual direct cost of treating high-risk diabetics reaches $36 billion, of which Medicare and Other Federal Programs compensate 54%. Respiratory conditions among diabetics comprise the same proportion of high-risk diabetics as do the disease combinations including coronary heart diseases. Treating of general diabetic conditions has become more efficient as indicated by the estimated declines in per unit health care costs.
The purpose of this study was to determine what factors influence patient willingness to pay (WTP) for a diabetes disease state management (DSM) program. Adult diabetics (N = 169) were surveyed by mail on the following: patient satisfaction with pharmacy services, healthcare utilization, perceived need for DSM, and sociodemographic factors. Patients were willing to pay on average $28.16 (SD = $31.12, median $30) for a one-hour consultation. Patients who were likely to pay more for a diabetes DSM had a greater perceived need for the service (p = 0.0016), had more emergency room visits (p = 0.0001), were more likely to be male (p = 0.0037), were more likely to be younger (p = 0.0340), and had higher incomes (p = 0.0007).
The purpose of this study was to assess the relationship between quality of life (QOL) and willingness to pay (WTP) for in vitro fertilization (IVF) in patients undergoing treatment for infertility. Adult women (N = 86) in treatment for infertility completed a self-administered mail survey. The Short-Form 36 was used to measure QOL and the contingent valuation method was used to measure WTP. Mean WTP for IVF was $10,277 (SD = $13,210, median $8,000) and mean total QOL was 574.6 (SD = 145.7). There was no significant difference in QOL (p = 0.70) or WTP (p = 0.20) among patients in Stages 1, 2, and 3 of infertility treatment. QOL and WTP were negatively (r = −0.05), but not significantly (p = 0.65) correlated.
The loss of human capital as a result of diabetes from the perspective of the patient and the patient's family is important. Several studies have demonstrated that having diabetes potentially presents employability problems. The increasingly common efforts to measure patients' health-related quality of life may represent a good source of data to enhance our understanding of the impact of diabetes on productivity. Health-related quality of life (HrQoL) is a multidimensional concept that includes physical function, social function, role function, mental health and general health perceptions. Such measurements can make tangible to physicians and patients the benefits of using pharmaceutical innovations. However, studies have shown impairment in the HrQoL occurs most clearly in patients suffering late-stage complications. Since the late stages of disease usually occurs after retirement in type 2 patients (the most common form), the measure of their work productivity may not be relevant under the concept of human capital. Retired patients with physical impairment may require the informal care of working-age family members and friends, or formal care provided by paid caregivers. Thus, in addition to direct measures of work productivity, the impact of diabetes and its treatment may require the measurement of caregivers' productivity. A longer duration of life free from diabetic complications can be expected to result in improved patients' (and their caregivers') HrQoL and work productivity. Thus, we can better appreciate the value of pharmaceutical interventions when we recognize their effectiveness in avoiding or delaying the onset of diabetes complications.
This study reviews and examines the role of low energy in the relationship of depression to decreased work productivity. Three-month findings are presented from a naturalistic clinical study of depression treatment in 573 primary care patients. Low energy was the most frequently reported symptom, was more predictive of poorer work and social functioning than other aspects of depressive symptomatology, and its improvement was more strongly related to improved work productivity than was a decrease in the number of depressive symptoms. Findings suggest that depression interventions to raise energy level may also be most suitable in speeding a return to work productivity.
This paper examines the promises and pitfalls of integrated models of mental health care in primary care settings, and presents the findings of a successful pilot study of integrated care. There are a number of technological breakthroughs which could improve treatment outcomes. However, research indicates improved outcomes are likely only when changes include new practice patterns, patient education, and systematic monitoring of patient process and outcomes. A study in a health maintenance organization is presented based on a staged model of treatment and exemplifying these principles. We conclude that integrated models while technically feasible, are organizationally complex in actual practice.
Previous studies have indicated that individuals with depression have increased workplace absenteeism, leading to substantial costs to employers. However, depressed patients are also more likely to be cigarette smokers, and smoking is also associated with increased absenteeism. We evaluated the impact of depression and smoking status on workplace absenteeism in a study of airline reservation agents. Smoking was associated with absenteeism for all levels of depression, but depression increased absenteeism only among current smokers. These results suggest that part of the workplace burden associated with depression may be attributable to smoking.
Suicide ranks among the most tragic events in human life. It is important to demonstrate that suicide is the cause of substantial economic losses in a societal perspective and to develop preventive measures with a high population impact.Would individuals who commit suicide have had the same life expectancy and productivity as others in the population? This assumption can be challenged on the basis of available evidence on the long-term course of depression.The main effects in suicide prevention on a population basis can be expected if resources are used to: increase public awareness of treatment options, decrease stigmatization, and increase knowledge about the diagnosis and treatment of depression within the health care system.
This investigation focuses on patients hospitalized with congestive heart failure (CHF) to evaluate the effects of insurance status on resource utilization (costs and procedure intensity), and the process of inpatient care (length of stay). Data include hospital discharge claims from fourteen states across the U.S. for 88,000 primary and another 135,000 secondary CHF patients under age 65. Risk adjustment methods control for clinical, demographic, and risk selection factors in order to isolate the effects of insurance status on the variables of interest.Results indicate that insurance status significantly affects the type and intensity of care. Lengths of stay are shortest for privately managed patients and longest for patient in public programs. Nonetheless access to high intensity treatment procedures favors private payors, especially those covered by indemnity plans. Overall hospitalization and treatment costs are less sensitive to payor status than length of stay and appear to be driven by high intensity procedure utilization. The marginal effects of CHF are substantial, raising length of stay and treatment cost by up to 40% and reinforcing the insurance status effect on length of stay and utilization found in patients hospitalized with CHF as a primary diagnosis. Despite these process-of-care differences, no significant inpatient mortality/morbidity differences were ascertained in either the primary or secondary analyses.