Identifying complex patients in family medicine for potential benefit from a case manager: a short questionnaire derived from the INTERMED Self-Assessment (IMSA) questionnaire

Abstract

Abstract Purpose To investigate how useful the Intermed-Self Assessment (IMSA) questionnaire and its components were for identifying which patient candidates would benefit most from case management (CM) in general practice. Methods The study was carried out in a group family medicine practice in Lausanne comprising seven GPs and four medical assistants, from February to April 2019. All the patients attending the practice between February and April 2019 were invited to complete the IMSA questionnaire. Additionally, their GPs were asked for their opinions on the potential benefits of each patient being assigned a case manager. Each IMSA item’s value has been assessed as a predictor of GPs’ opinions by using multivariate logistic models. A score including items retained as predictor was built. Results Three hundred and thirty one patients participated in the study (participation rate: 62%). Three items from the 20 item IMSA were sufficient to predict GPs’ opinions about whether their patients could be expected to benefit if assigned a case manager. Those items addressed the patient’s existing chronic diseases (item1), quality of life in relation to existing diseases (item 3), and their social situation (item 9). Using these three items as a score, a cut-off at 4 gave a sensitivity of 70% (ability to correctly identify patients who could benefit from a CM) and specificity of 73% (ability to correctly identify patients who should not benefit from a CM) and concerned about one patient in two. Conclusion Identifying complex patients suitable for case management remains a challenge for primary care professionals. This paper describes a novel approach using a structured process of combining the results of standardized tools such as the one defined in this study, and the experience of the primary care team.

Keywords

• Case management
• Intermed-SA tool
• Complex patients
• Family medicine