Objectives: To evaluate characteristics of the medication complexity, risk factors associated with high medication complexity and their clinical consequences in patients with advanced chronic conditions.
Methods: A 10-month cross-sectional study was performed in an acute-hospital care Geriatric Unit. Patients with advanced chronic conditions were identified by the NECPAL test.
Background: Potentially inappropriate medications (PIMs) are common in palliative care patients, but no specific tools have been used to determine these PIMs.
Objective: To evaluate the prevalence of PIMs according to specific tool 'STOPP-Frail', related factors with its existence and clinical consequences.
Methods: This is a post hoc analysis from a 10-month prospective cross-sectional study.
Aim: To evaluate the anticholinergic burden (ACB), the risk factors associated with its onset and the clinical consequences for patients with advanced chronic conditions.
Methods: A 10-month cross-sectional study was carried out in an acute hospital care geriatric unit. Patients with advanced chronic conditions were identified by the NECessity of PALliative care (NECPAL) test.
Patients with multiple disorders and on multiple medication are often associated with clinical complexity, defined as a situation of uncertainty conditioned by difficulties in establishing a situational diagnosis and decision-making. The patient-centred care approach in this population group seems to be one of the best therapeutic options. In this context, the preparation of an individualised therapeutic plan is the most relevant practical element, where the pharmacological plan maintains an important role.
View Article and Find Full Text PDFClinical Decision Support Systems (CDSS) are computerized tools designed to help healthcare professionals to make clinical and therapeutic decisions, with the objective of improving patient care. Prescription-targeted CDSS have the highest impact in improving patient safety. Although there are different designs and functionalities, all these systems will combine clinical knowledge and patient information in a smart manner, in order to improve the prescription process.
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