Anna Maria Meyer1, Giacomo Siri2, Ingrid Becker3, Thomas Betz4, August W Bödecker5, Jörg W Robertz5, Olaf Krause6, Thomas Benzing1,7, Alberto Pilotto8,9, Maria Cristina Polidori1,7. 1. Ageing Clinical Research, Department II of Internal Medicine and Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. 2. Scientific Directorate-Biostatistics, E.O. Galliera Hospital, Genova, Italy. 3. Institute of Medical Statistics and Computational Biology, University Hospital of Cologne, Cologne, Germany. 4. Institute for General Practice, Academic training practive, University Hospital of Cologne, Cologne, Germany. 5. Institute for General Practice, University Hospital of Cologne, Cologne, Germany. 6. Institute for General Practice, Hannover Medical School, Hannover, Germany. 7. CECAD, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. 8. Department Geriatric Care, Orthogeriatrics and Rehabilitation, E.O. Galliera Hospital, Genova, Italy. 9. Department of Interdisciplinary Medicine, University of Bari, Bari, Italy.
Abstract
BACKGROUND: Older patients' health problems in general practice (GP) can often not be assigned to a specific disease, requiring a paradigm shift to goal-oriented, personalised care for clinical decision making. PURPOSE: To investigate the predictive value of the comprehensive geriatric assessment (CGA)-based Multidimensional Prognostic Index (MPI) in a GP setting with respect to the main healthcare indicators during the 12 months following initial evaluation. METHODS: One hundred twenty-five consecutive patients aged 70 years and older were enrolled in a GP and followed up to one year. All patients underwent a CGA based on which the MPI was calculated and subdivided into three risk groups (MPI-1, 0-0.33 = low risk, MPI-2, 0.34-0.66 = moderate risk and MPI-3, 0.67-1, severe risk). Grade of Care (GC), hospitalization rate, mortality, nursing home admission, use of home care services, falls, number of general practitioner contacts (GPC), of geriatric resources (GR) and geriatric syndromes (GS) during the 12 months following initial evaluation were collected. RESULTS: The MPI was significantly associated with number of GS (P < .001), GR (P < .001), GC (P < .001) as well as with the average number of GPC per year (mean 10.4, P = .046). Interestingly, the clinical judgement of the general practitioner, in this case knowing his patients for 16 years on average, was associated with adverse outcomes to a similar extent than the prediction offered by the MPI (GP/adverse outcomes and MPI/adverse outcomes P < .001). CONCLUSION: The MPI is strongly associated with adverse outcomes in older GP patients and strongly predicts the number of GPC up to one year after initial evaluation. Considering the feasibility and the strong clinimetric properties of the MPI, its collection should be encouraged as early as possible to disclose risk conditions, implement tailored preventive strategies and improve cost-effectiveness of healthcare resources use.
BACKGROUND: Older patients' health problems in general practice (GP) can often not be assigned to a specific disease, requiring a paradigm shift to goal-oriented, personalised care for clinical decision making. PURPOSE: To investigate the predictive value of the comprehensive geriatric assessment (CGA)-based Multidimensional Prognostic Index (MPI) in a GP setting with respect to the main healthcare indicators during the 12 months following initial evaluation. METHODS: One hundred twenty-five consecutive patients aged 70 years and older were enrolled in a GP and followed up to one year. All patients underwent a CGA based on which the MPI was calculated and subdivided into three risk groups (MPI-1, 0-0.33 = low risk, MPI-2, 0.34-0.66 = moderate risk and MPI-3, 0.67-1, severe risk). Grade of Care (GC), hospitalization rate, mortality, nursing home admission, use of home care services, falls, number of general practitioner contacts (GPC), of geriatric resources (GR) and geriatric syndromes (GS) during the 12 months following initial evaluation were collected. RESULTS: The MPI was significantly associated with number of GS (P < .001), GR (P < .001), GC (P < .001) as well as with the average number of GPC per year (mean 10.4, P = .046). Interestingly, the clinical judgement of the general practitioner, in this case knowing his patients for 16 years on average, was associated with adverse outcomes to a similar extent than the prediction offered by the MPI (GP/adverse outcomes and MPI/adverse outcomes P < .001). CONCLUSION: The MPI is strongly associated with adverse outcomes in older GP patients and strongly predicts the number of GPC up to one year after initial evaluation. Considering the feasibility and the strong clinimetric properties of the MPI, its collection should be encouraged as early as possible to disclose risk conditions, implement tailored preventive strategies and improve cost-effectiveness of healthcare resources use.
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