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• W2024652180 abstract "Self-monitoring of blood glucose is widely accepted by patients today, but its usefulness to clinicians has been seriously limited by our inability to interpret the patient-generated data. It is difficult or impossible to make optimal use of hand-kept diaries, no matter how compulsively kept. Patterns elude us, summaries are inaccurate, and large blocks of data are almost entirely ignored. To remedy these problems, data source automation—the automatic recording of data at their site of origin—is being applied to diabetes. Meters will measure blood glucose and memorize the result, date, and time of day. One system even allows the patient to record insulin dosage, exercise, and diet. The advantage of these systems lies in their potential for data management. Recognition of patterns of blood glucose concentration, easy longitudinal comparison of data, and aggregation of large data bases are all facilitated by computerized manipulation of the stored data. In-hospital use of glucose meters can have better documented quality control. It is possible to communicate data to physicians by telephone modem. Effective use of these systems, though, requires convenient software; and their acceptance in actual clinical practice must be demonstrated. But data management capabilities, as they are refined and brought into common use, could significantly improve diabetic management." @default.
• W2024652180 created "2016-06-24" @default.
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• W2024652180 date "1989-07-01" @default.
• W2024652180 modified "2023-10-18" @default.
• W2024652180 title "Data Source Automation: New Technology for the Management of Patient-generated Test Results" @default.
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• W2024652180 doi "https://doi.org/10.1111/j.1464-5491.1989.tb01192.x" @default.
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