Medical decision making : an international journal of the Society for Medical Decision Making
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Over the cancer disease trajectory, from diagnosis and treatment to remission or end of life, patients and their families face difficult decisions. The provision of information and support when most relevant can optimize cancer decision making and coping. An interactive health communication system (IHCS) offers the potential to bridge the communication gaps that occur among patients, family, and clinicians and to empower each to actively engage in cancer care and shared decision making. ⋯ Critical issues of IHCS implementation include 1) need for interventions that accommodate a variety of format preferences and technology comfort ranges; 2) IHCS user training, 3) clinician investment in IHCS promotion, and 4) IHCS integration with existing medical systems. In creating such comprehensive systems, development strategies need to be grounded in population needs with appropriate use of technology that serves the target users, including the patient/family, clinical team, and health care organization. Implementation strategies should address timing, personnel, and environmental factors to facilitate continued use and benefit from IHCS.
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Despite the huge cost of the program, the Centers for Medicare and Medicaid Services (CMS) has maintained a policy that cost-effectiveness is not considered in national coverage determinations (NCDs). ⋯ CMS is covering a number of interventions that do not appear to be cost-effective, suggesting that resources could be allocated more efficiently. Although the authors identified several instances where cost-effectiveness evidence was cited in NCDs, they found no clear evidence of an implicit threshold.
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Clinical decision rules can benefit clinicians, patients, and health systems, but they involve considerable up-front development costs and must be acceptable to the target audience. No existing instrument measures the acceptability of a rule. The current study validated such an instrument. ⋯ The OADRI is a simple, 12-item instrument that evaluates rule acceptability among clinicians. Potential uses include comparing multiple ''protorules'' during development, examining acceptability of a rule to a new audience prior to implementation, indicating barriers to rule use addressable by knowledge translation interventions, and potentially serving as a proxy measure for future rule use.
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To test the hypothesis that nearest-neighbor analysis adds to logistic regression in the early diagnosis of late-onset neonatal sepsis. ⋯ The authors propose nearest-neighbor analysis in addition to regression in the early diagnosis of subacute, potentially catastrophic illnesses such as neonatal sepsis, and they recommend it as an approach to the general problem of predicting a clinical event from a multivariable data set.
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Systematic reviews of healthcare disparities suggest that clinicians' diagnostic and therapeutic decision making varies by clinically irrelevant characteristics, such as patient race, and that this variation may contribute to healthcare disparities. However, there is little understanding of the particular features of the healthcare setting under which clinicians are most likely to be inappropriately influenced by these characteristics. This study delineates several hypotheses to stimulate future research in this area. ⋯ It is further hypothesized that certain characteristics of healthcare settings will result in higher levels of cognitive load experienced by providers (H3). Finally, it is hypothesized that minority patients will be disproportionately likely to be treated in healthcare settings in which providers experience greater levels of cognitive load (H4a), which will result in racial disparities due to lower levels of controlled processing by providers (H4b) and the influence of racial stereotypes (H4c). The study concludes with implications for research and practice that flow from this framework.