Predicting ‘anticipated benefit’ from an extended consultation to personalise care in multimorbidity: A development and internal validation study of a prioritisation algorithm in general practice

Background: Persons with multimorbidity may in particular gain from person-centred care as compared to the current protocolised chronic disease management in Dutch general practice. Given time constraints and limited resources, it is essential to prioritise those most in need of an assessment of person-centred chronic care needs. Aim: To develop and validate a prioritisation algorithm based on routine electronic medical record (EMR) data that distinguishes between multimorbid patients who would and those who would not benefit from an ‘extended person-centred consultation’ to assess person-centred chronic care needs, in the judgement of general practitioners (GPs). Design&setting: A mixed-methods study conducted in five general practices. Method: Mixed-methods comprising (i) multivariable logistic regression using EMR data to predict the GPs’ judgement on patients’ ‘anticipated benefit’ from an extended consultation, and (ii) a thematic analysis of a focus group exploring GPs’ clinical reasoning for this judgement. Internal validation was performed using 10-fold cross-validation. Results: 1032 patients were selected, of whom 357(34.1%) were judged to have anticipated benefit. The model’s cross-validated C-statistic was 0.72(95%-CI;0.70-0.75). Calibration was good. Presence of home visit(s), history of myocardial infarctions and cancer were associated with anticipated benefit. Thematic analysis revealed three dimensions feeding anticipated benefit: GPs’ cause for concern, patients’ mindset regarding their conditions and balance between received care/expected care needed. Conclusion: External validation of the algorithm and evaluation of ‘actual benefit’ of consultation is recommended before implementation. This algorithm may facilitate automated prioritisation, potentially avoiding the need for GPs to personally triage the whole multimorbid practice population.