Human capital theory predicts that life expectancy will impact human capital attainment. We estimate this relationship using variation in life expectancy driven by Huntington disease, an inherited ...neurological disorder. We compare investments for individuals who have ex-ante identical risks of HD but differ in disease realization. Individuals with the HD mutation complete less education and job training. The elasticity of demand for college attendance with respect to life expectancy is around 1.0. We relate this to cross-country and over-time differences in education. We use smoking and cancer screening data to test the corollary that health capital responds to life expectancy. (JEL I11, I12, I20, I31, J24) PUBLICATION ABSTRACT
As the U.S. population ages, the burden of neurodegenerative disorders, including Alzheimer disease and Parkinson disease, will increase substantially. However, many of these patients and their ...families currently do not receive neurologic care. For example, a recent study found that over 40% of Medicare beneficiaries with an incident Parkinson disease diagnosis did not receive neurologist care early after diagnosis and those who did not were more likely to fracture a hip, be placed in a nursing home, and die. While geography, age, race, and sex likely contribute to these observed disparities in care and outcomes, a large barrier may be Medicare's reimbursement policies, which value procedures over care. With further reductions in Medicare reimbursement constantly on the horizon, the devaluing of clinical care will likely continue. Rather than guaranteeing access to care, Medicare's reimbursement policies may increasingly be an impediment to care.
Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of ...high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health.
Parkinson disease (PD) is now the world's fastest growing brain disease; however, the factors underlying this rise are unclear. The past 25 years has witnessed a vast expansion in our understanding ...of the genetics of PD, but few individuals with PD carry one of the major known genetic risk factors. Environmental factors, including individual (e.g., medications) and ambient (e.g., pollutants), may contribute to this rise. In this issue of the JCI, Sasane et al. examined the risk of PD associated with medications commonly used to treat benign prostatic hypertrophy. In contrast with previous studies, certain alpha.sub.1 receptor antagonists failed to lower PD risk. Rather, the commonly used comparator drug, tamsulosin, increased PD risk. This finding highlights the importance of selecting comparator groups to correctly identify risk factors. Future studies to address the rise of PD with emphasis on both individual as well as the understudied ambient environmental factors are warranted.
Remote health assessments that gather real-world data (RWD) outside clinic settings require a clear understanding of appropriate methods for data collection, quality assessment, analysis and ...interpretation. Here we examine the performance and limitations of smartphones in collecting RWD in the remote mPower observational study of Parkinson's disease (PD). Within the first 6 months of study commencement, 960 participants had enrolled and performed at least five self-administered active PD symptom assessments (speeded tapping, gait/balance, phonation or memory). Task performance, especially speeded tapping, was predictive of self-reported PD status (area under the receiver operating characteristic curve (AUC) = 0.8) and correlated with in-clinic evaluation of disease severity (r = 0.71; P < 1.8 × 10
) when compared with motor Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Although remote assessment requires careful consideration for accurate interpretation of RWD, our results support the use of smartphones and wearables in objective and personalized disease assessments.
Summary Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease ...analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. Methods We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability YLD and years of life lost YLL) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. Findings In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% 95% uncertainty interval 6·2–7·7 of global DALYs), tobacco smoking including second-hand smoke (6·3% 5·5–7·0), and household air pollution from solid fuels (4·3% 3·4–5·3). In 1990, the leading risks were childhood underweight (7·9% 6·8–9·4), household air pollution from solid fuels (HAP; 6·8% 5·5–8·0), and tobacco smoking including second-hand smoke (6·1% 5·4–6·8). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4–1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, Andean Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, most of Latin America, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. Interpretation Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children. Funding Bill & Melinda Gates Foundation.
The anatomy of health care in the United States Moses, 3rd, Hamilton; Matheson, David H M; Dorsey, E Ray ...
JAMA : the journal of the American Medical Association,
11/2013, Letnik:
310, Številka:
18
Journal Article
Recenzirano
Health care in the United States includes a vast array of complex interrelationships among those who receive, provide, and finance care. In this article, publicly available data were used to identify ...trends in health care, principally from 1980 to 2011, in the source and use of funds ("economic anatomy"), the people receiving and organizations providing care, and the resulting value created and health outcomes. In 2011, US health care employed 15.7% of the workforce, with expenditures of $2.7 trillion, doubling since 1980 as a percentage of US gross domestic product (GDP) to 17.9%. Yearly growth has decreased since 1970, especially since 2002, but, at 3% per year, exceeds any other industry and GDP overall. Government funding increased from 31.1% in 1980 to 42.3% in 2011. Despite the increases in resources devoted to health care, multiple health metrics, including life expectancy at birth and survival with many diseases, shows the United States trailing peer nations. The findings from this analysis contradict several common assumptions. Since 2000, (1) price (especially of hospital charges +4.2%/y, professional services 3.6%/y, drugs and devices +4.0%/y, and administrative costs +5.6%/y), not demand for services or aging of the population, produced 91% of cost increases; (2) personal out-of-pocket spending on insurance premiums and co-payments have declined from 23% to 11%; and (3) chronic illnesses account for 84% of costs overall among the entire population, not only of the elderly. Three factors have produced the most change: (1) consolidation, with fewer general hospitals and more single-specialty hospitals and physician groups, producing financial concentration in health systems, insurers, pharmacies, and benefit managers; (2) information technology, in which investment has occurred but value is elusive; and (3) the patient as consumer, whereby influence is sought outside traditional channels, using social media, informal networks, new public sources of information, and self-management software. These forces create tension among patient aims for choice, personal care, and attention; physician aims for professionalism and autonomy; and public and private payer aims for aggregate economic value across large populations. Measurements of cost and outcome (applied to groups) are supplanting individuals' preferences. Clinicians increasingly are expected to substitute social and economic goals for the needs of a single patient. These contradictory forces are difficult to reconcile, creating risk of growing instability and political tensions. A national conversation, guided by the best data and information, aimed at explicit understanding of choices, tradeoffs, and expectations, using broader definitions of health and value, is needed.
PDF
