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Utilization of ambulatory care studies: testing the assumptions

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Abstract

A linear regression procedure is usually used to estimate the effect of a set of predictors on utilization of ambulatory health care. The implicit assumptions embedded in the linear regression model have never been examined. Here, with utilization data of a sample of 48292 patients from the file of the Québec National Health Plan, four implicit hypotheses embedded in the linear regression model are tested: (1) the transition from the state of utilization to the state of no utilization, and vice-versa, depends on the level of the transition rates, (2) the effect of independent variables depends on the transitions being predicted from or to the state of utilization, (3) the transition is time dependent, and (4) the system of transitions from one state to another is not at equilibrium. The analysis shows that the first three hypotheses cannot be rejected. Thus, the use of the familiar linear regression procedure in this study to estimate the effect of a set of factors on utilization would have yielded biased estimates.

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Béland, F. Utilization of ambulatory care studies: testing the assumptions. Qual Quant 25, 137–150 (1991). https://doi.org/10.1007/BF00145702

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