Development of a decision tree for the pharmacy-led consultation of elderly patients with haematological malignancies

Abstract

Introduction Elderly patients with haematological malignancies are a population at risk of iatrogenic for whom these activities could optimize therapeutic management. However, the limitation of human resources requires optimization of the process in order to improve the efficiency of pharmaceutical activities. The objective was to build a decision tree to optimize the pharmaceutical consultation in these population within a multidisciplinary team in haematology. Method Pharmaceutical consultations were proposed to elderly subjects with haematological malignancies followed up in a haematology day hospitalization at the University Hospital of Limoges. Risk factors for prescribing risky drugs in this population were determined by logistic regression models. A decision tree was constructed based on these results and by agreement between pharmacist, geriatrician and hematologist. Results Female gender (aOR[CI95%] = 1.71 [1.14–2.57]), polypharmacy (aOR[CI95%] = 1.89 [1.14–3.13]), hyper-polypharmacy (aOR[CI95%] = 5.73 [3.03–10.84]) and moderate cholinergic load (aOR[CI95%] = 2.15 [1.04–4.45]) were risk factors for the prescription of inappropriate medicine. Female gender (aOR[CI95%] = 1.55 [1.02–2.35]) and hyper-polypharmacy (aOR[CI95%] = 6.19 [1–1.28]) were risk factors for prescribing anticholinergic drugs or anticoagulants; in contrast, frailty status was a protective factor for prescribing anticholinergics (aOR[CI95%] = 0.51 [0.33–0.81]). Prioritization of pharmaceutical consultations is based on frailty status, prescription of a target drug and polypharmacy. Discussion Pharmaceutical consultations during the day hospitalization of elderly subjects with hematological diseases allow to propose therapeutic optimizations. The prioritization proposed in our study would increase the efficiency of pharmaceutical activities in order to improve quality and safety throughout the care pathway of these patients.