Reverse targeting of preventive care due to lack of health insurance

We analyzed patterns of receipt of preventive services among middle-aged women, with particular attention to health insurance coverage, based on data from the National Health Interview Survey. Lack of insurance was most prevalent among socioeconomically disadvantaged women at high risk for disease and was the strongest predictor of failure to receive screening tests. The relative risk of inadequate screening for uninsured compared with insured women was 1.60 (95% confidence interval [Cl], 1.40 to 1.83) for blood pressure checkups, 1.55 (95% Cl, 1.43 to 1.68) for cervical smears, 1.52 (95% Cl, 1.41 to 1.63) for glaucoma testing, and 1.42 (95% Cl, 1.33 to 1.51) for clinical breast examination. Controlling for demographic and health status variables did not diminish the effect of insurance coverage. We conclude that inadequate insurance coverage leads to "reverse targeting" of preventive care--that is, populations at highest risk are least likely to be screened. This compromises both the effectiveness and the cost-effectiveness of screening.     

Going bare: trends in health insurance coverage, 1989 through 1996.

OBJECTIVES: This study analyzed trends in health insurance coverage in the United States from 1989 through 1996. METHODS: Data from annual cross-sectional surveys by the US Census Bureau were analyzed. RESULTS: Between 1989 and 1996, the number of uninsured persons increased by 8.3 million (90% confidence interval [CI] = 7.7, 8.9 million). In 1996, 41.7 million (90% CI = 40.9, 42.5 million) lacked insurance. From 1989 to 1993, the proportion with Medicaid increased by 3.6 percentage points (90% CI = 3.1, 4.0), while the proportion with private insurance declined by 4.2 percentage points (90% CI = 3.7, 4.7). From 1993 to 1996 private coverage rates stabilized but did not reverse earlier declines. Consequently, the number uninsured continued to increase. The greatest increase in the population of uninsured [corrected] was among young adults aged 18 to 39 years; rates among children also rose steeply after 1992. While Blacks had the largest percentage increase, Hispanics accounted for 36.4% (90% CI = 32.3%, 40.5%) of the increase in the number uninsured. From 1989 to 1993, the majority of the increase was among poor families. Since then, middle-income families have incurred the largest increase. Northcentral and northeastern states had the largest increases in percent uninsured. CONCLUSIONS: Despite economic prosperity, the numbers and rates of the uninsured continued to rise. Principally affected were children and young adults, poor and middle income families, blacks, and Hispanics.     

The silence of the doctors fifty years after nuremberg

When Seiss-Inquart, Reich Commissar for the Occupied Netherlands Territories, wanted to draw the Dutch physicians into the orbit of activities of the German medical profession, he did not tell them ‘you must send your chronic patients to death factories’ or ‘you must give lethal injections at government request in your offices,’ but he couched his order in most careful and superficially acceptable terms… ‘It is the duty of the doctor, through advice and effort, conscientiously and to his best ability, to assist as helper the person entrusted to his care in the maintenance, improvement and re-establishment of his vitality, physical efficiency and health. The accomplishment of this duty is a public task.’     

Reasons Why Patients Remain Uninsured after Massachusetts’ Health Care Reform: A Survey of Patients at a Safety-Net Hospital

BACKGROUND  

Following the 2006 Massachusetts health care reform, an estimated 316,492 residents remain uninsured. However, there have been no published studies that examine why Massachusetts residents remain uninsured four years into health reform.     

Hope and hype: predicting the impact of electronic medical records

The current fascination with electronic medical records (EMRs) is not new. For decades, vendors have capitalized on this enthusiasm. But hospitals and clinics have ended up with little to show for their large outlays. Indeed, computing at a typical hospital has not gotten much beyond what was available twenty-five years ago. The RAND analysis continues the tradition of hope and hype. Unfortunately, behind their impressive predictions of savings lie a disturbing array of unproven assumptions, wishful thinking, and special effects.