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| Naji, M. |
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| Motta, Antonella |
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| Petrov, R. H. | Madrid |
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| Azevedo, Nuno Monteiro |
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Caddick, Barbara
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
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article
Measuring the complexity of general practice consultations
Abstract
Background: The complexity of general practice consultations may be increasing and vary in different settings. Testing these hypotheses requires a measure of complexity.<br/><br/>Aim: To develop a valid measure of general practice consultation complexity applicable to routine medical records. <br/><br/>Design: Delphi study to select potential indicators of complexity followed by cross-sectional study to develop and validate a complexity measure. <br/><br/>Setting: English general practices. <br/><br/>Method: An online Delphi study over two rounds involved 32 general practitioners to identify potential indicators of consultation complexity. The cross-sectional study used an age-sex stratified random sample of 173,130 patients and 725,616 general practice face-to-face consultations from 2013/14 in the Clinical Practice Research Datalink. We explored independent relationships between each indicator and consultation duration using mixed effects regression models, and revalidated findings using data from 2017/18. We assessed the proportion of complex consultations in different age-sex groups.<br/><br/>Results: After two rounds, the Delphi panel endorsed 34 of 45 possible complexity indicators. In the cross-sectional study, after excluding factors because of low prevalence or confounding, 17 indicators were retained. Defining complexity as the presence of any of these factors, 308,370 consultations (42.5%) were complex. Mean duration of complex consultations was 10.49 minutes, compared to 9.64 minutes for non-complex consultations. The proportion of complex consultations was similar in men and women but increased with age.<br/> <br/>Conclusion: Our consultation complexity measure has face and construct validity. It may be useful for research, management and policy, informing decisions about the range of resources needed in different practices.