March 29, 2018

Analysis of Waiting-Time Data in Health Services Research - download pdf or read online

By Boris Sobolev

ISBN-10: 0387764216

ISBN-13: 9780387764214

Why a few sufferers wait longer than others is still a massive query. This ebook is a reference for overall healthiness companies researchers trying to find statistical instruments with which to review ready instances. The e-book deals particular insurance of statistical recommendations and techniques for the research and interpretation of waiting-time facts. It presents research from overall healthiness prone study viewpoint, instead of operations administration, and includes a choice of examples.

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Additional resources for Analysis of Waiting-Time Data in Health Services Research

Sample text

If the censored observations are not accounted for, the estimated probabilities of receiving the service may be biased toward a higher rate, and the median and mean waiting time may be underestimated [104]. The methods of timeto-event analysis allow us to use incomplete information in a sample [66]. A fundamental assumption that makes use of these methods is that the distribution of censored time does not depend on the parameters governing waiting-times distribution. If, however, censoring were related to the mechanism governing admissions, this assumption would result in biased estimates of the probability of receiving the service within a certain time.

The registry records accounted for all patients referred to the department for assessment at the outpatient clinic who were afterward added to the wait list. Patients who received emergency treatment were excluded. 2. 2 Patient population We studied the records of patients for whom elective vascular surgery was indicated and planned. Patients were registered on the wait list after the consultation visit during which surgery was deemed necessary. 3. Characteristics of 9199 patients registered for elective isolated coronary artery bypass grafting in British Columbia, 1991–2000 Priority group; no.

Unlike the proportions that we discussed in the previous section, the event rates account for the amount of time that patients spend on wait lists, by adjusting the at-risk set at the beginning of consecutive weeks. Although accurately describing the instantaneous risk of an event, event-specific rates cannot be converted into the probabilities of events without the unrealistic and unverifiable assumption that time to primary event and time to competing event are independent [45]. Despite that it is always possible to calculate an average event rate over the study period, such an average rate may not be representative if the rate varies during the period.

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Analysis of Waiting-Time Data in Health Services Research by Boris Sobolev


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