Perspectives from deductible plan enrollees: plan knowledge and anticipated care-seeking changes

<p>Abstract</p> <p>Background</p> <p>Consumer directed health care proposes that patients will engage as informed consumers of health care services by sharing in more of their medical costs, often through deductibles. We examined knowledge of deductible plan details among new enrollees, as well as anticipated care-seeking changes in response to the deductible.</p> <p>Methods</p> <p>In a large integrated delivery system with a range of deductible-based health plans which varied in services included or exempted from deductible, we conducted a mixed-method, cross-sectional telephone interview study.</p> <p>Results</p> <p>Among 458 adults newly enrolled in a deductible plan (71% response rate), 51% knew they had a deductible, 26% knew the deductible amount, and 6% knew which medical services were included or exempted from their deductible. After adjusting for respondent characteristics, those with more deductible-applicable services and those with lower self-reported health status were significantly more likely to know they had a deductible. Among those who knew of their deductible, half anticipated that it would cause them to delay or avoid medical care, including avoiding doctor's office visits and medical tests, even services that they believed were medically necessary. Many expressed concern about their costs, anticipating the inability to afford care and expressing the desire to change plans.</p> <p>Conclusion</p> <p>Early in their experience with a deductible, patients had limited awareness of the deductible and little knowledge of the details. Many who knew of the deductible reported that it would cause them to delay or avoid seeking care and were concerned about their healthcare costs.</p

Biological Earth observation with animal sensors.

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Priority setting in health care: Lessons from the experiences of eight countries

All health care systems face problems of justice and efficiency related to setting priorities for allocating a limited pool of resources to a population. Because many of the central issues are the same in all systems, the United States and other countries can learn from the successes and failures of countries that have explicitly addressed the question of health care priorities

What's law got to do with it Part 2: Legal strategies for healthier nutrition and obesity prevention

This article is the second in a two-part review of law's possible role in a regulatory approach to healthier nutrition and obesity prevention in Australia. As discussed in Part 1, law can intervene in support of obesity prevention at a variety of levels: by engaging with the health care system, by targeting individual behaviours, and by seeking to influence the broader, socio-economic and environmental factors that influence patterns of behaviour across the population. Part 1 argued that the most important opportunities for law lie in seeking to enhance the effectiveness of a population health approach

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Clinical Uncertainty and Healthcare Disparities

The Institute of Medicine Report, Unequal Treatment: Confronting Racial and Ethnic Disparities, affirms in its first finding: Racial and ethnic disparities in health care exist and, because they are associated with worse outcomes in many cases, are unacceptable. The mechanisms that generate racial and ethnic disparities in medical care operate at the levels of the health care system and the clinical encounter. Research demonstrates the role of health care system factors, including differences in insurance coverage and other determinants of healthcare access, in producing disparities. Research also shows, however, that even when insurance status and other measures of access are controlled for by statistical methods, racial and ethnic disparities persist. These disparities remain when researchers try by various methods to control for patients\u27 clinical characteristics. Disparities are especially well documented through comparisons between white patients and African Americans and Latinos, but they are believed to affect other minority groups. As a result, many members of minority racial and ethnic groups receive less or inferior care. The purpose of this Article is to explore how one factor we regard to be key-provider and patient uncertainty about clinical decisions--contributes to disparities arising from the doctor-patient encounter

Testing for Statistical Discrimination in Health Care

OBJECTIVE: To examine the extent to which doctors' rational reactions to clinical uncertainty (“statistical discrimination”) can explain racial differences in the diagnosis of depression, hypertension, and diabetes. DATA SOURCES: Main data are from the Medical Outcomes Study (MOS), a 1986 study conducted by RAND Corporation in three U.S. cities. The study compares the processes and outcomes of care for patients in different health care systems. Complementary data from National Health And Examination Survey III (NHANES III) and National Comorbidity Survey (NCS) are also used. STUDY DESIGN: Across three systems of care (staff health maintenance organizations, multispecialty groups, and solo practices), the MOS selected 523 health care clinicians. A representative cross-section (21,480) of patients was then chosen from a pool of adults who visited any of these providers during a 9-day period. DATA COLLECTION: We analyzed a subsample of the MOS data consisting of patients of white family physicians or internists (11,664 patients). We obtain variables reflecting patients' health conditions and severity, demographics, socioeconomic status, and insurance from the patients' screener interview (administered by MOS staff prior to the patient's encounter with the clinician). We used the reports made by the clinician after the visit to construct indicators of doctors' diagnoses. We obtained prevalence rates from NHANES III and NCS. FINDINGS: We find evidence consistent with statistical discrimination for diagnoses of hypertension, diabetes, and depression. In particular, we find that if clinicians act like Bayesians, plausible priors held by the physician about the prevalence of the disease across racial groups could account for racial differences in the diagnosis of hypertension and diabetes. In the case of depression, we find evidence that race affects decisions through differences in communication patterns between doctors and white and minority patients. CONCLUSIONS: To contend effectively with inequities in health care, it is necessary to understand the mechanisms behind the problem. Discrimination stemming from prejudice is of a very different character than discrimination stemming from the application of rules of conditional probability as a response to clinical uncertainty. While in the former case, doctors are not acting in the best interests of their patients, in the latter, they are doing the best they can, given the information available. If miscommunication is the culprit, then efforts should be aimed at reducing disparities in the ways in which doctors communicate with patients