The American journal of managed care
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Diabetic retinopathy (DR), the primary retinal vascular complication of diabetes mellitus, is a progressive disease and a major cause of impaired vision and blindness, especially among individuals who are of working age. Early detection and treatment of DR can prevent 50% to 70% of its associated blindness. However, fewer than half of all US adults with diabetes adhere to guideline-recommended eye-screening schedules. ⋯ These delays in diagnosis and treatment may result in visual impairment that is permanent and cannot be reversed. Although the direct medical costs of DR are substantial, the indirect costs of visual impairment with respect to loss of productivity, increased nursing home admissions, and decreased quality of life are far more copious. Greater adherence to eye screening guidelines among patients with diabetes is required to facilitate prompt diagnosis and early treatment of DR, and in doing so, reduce the resulting vision loss and economic burden associated with DR.
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Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financial data for population risk stratification. ⋯ The deep learning model outperforms the traditional risk models in prospective hospitalization prediction. Thus, deep learning may improve the ability of managed care organizations to perform predictive modeling of financial risk, in addition to improving the accuracy of risk stratification for population health management activities.
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To compare coverage of orphan and nonorphan drugs, to examine variation in orphan drug coverage across the largest US private plans, and to evaluate factors influencing coverage decisions. ⋯ Health plans restrict access to orphan drugs approximately one-third of the time, and restrictions vary considerably across plans. Plans more often add restrictions for orphan drugs that are indicated for diseases with a higher prevalence and that have higher annual costs.
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To determine the patient's perception of the role of an anesthesiologist and the patient's expectations of their anesthesiologist and their anesthesia care. ⋯ Because satisfaction is a fulfillment of one's expectations, understanding what the patient expects from their anesthesiologist is the initial step to improve satisfaction scores. The onus is on the anesthesiologist to educate the patient about their role, to set realistic expectations of the postoperative course, and to involve the patient in decisions regarding their anesthesia care.