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BACKGROUND: Low medication literacy is prevalent among older adults and is associated with adverse drug events. The Medication Literacy Test for Older Adults (TELUMI) was developed and content validated in a previously published study. AIM: To evaluate the psychometric properties and provide norms for TELUMI scores. METHOD: This was a cross-sectional methodological study with older adults selected from the community and from two outpatient services. Descriptive item-analysis, exploratory factor analysis (EFA), item response theory (IRT), reliability, and validity analysis with schooling and health literacy were performed to test the psychometric properties of the TELUMI. The classification of the TELUMI scores was performed using percentile norms. RESULTS: A total of 344 participants, with a mean age of 68.7 years (standard deviation = 6.7), were included; most were female (66.6%), black/brown (61.8%), had low schooling level (60.2%) and low income (55.2%). The EFA pointed to the one-dimensional structure of TELUMI. A three-parameter logistic model was adopted for IRT. All items had an adequate difficulty index. One item had discrimination < 0.65, and three items had an unacceptable guessing index (< 0.35) and were excluded. The 29-item version of TELUMI had excellent internal consistency (KR20 = 0.89). There was a positive and strong association between TELUMI scores and health literacy and education level. The scores were classified as inadequate medication literacy (≤ 10.0 points), medium medication literacy (11-20 points), and adequate medication literacy (≥ 21 points). CONCLUSION: The results suggest that the 29-item version of TELUMI is psychometrically adequate for measuring medication literacy in older adults.
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BACKGROUND: Patient prioritization is a effective strategy to identify high risk patients for targeted Clinical Pharmacy Service (CPS) in hospital pharmacy. However, there is a paucity of patient prioritization tool to use in clinical practice. OBJECTIVES: Describe the development, content validation and standardization of an adult patient prioritization tool for hospital CPS named, PrioFarClinH. METHODS: The tool was developed using a stepwise design multi: Scoping Review to identify prioritization criteria/sub-criteria; Delphi technique to obtain consensus under the identified criteria/sub-criteria; Survey with pharmacists evaluating applicability of the criteria/sub-criteria obtained from Delphi; Definition of criteria/sub-criteria to be included in PrioFarClinH attribution of scores. Content validation was performed by a panel of experts evaluating relevance, feasibility, clarity and adequacy of the score. Content Validity Index (CVI) was calculated. Standardization occurred through a retrospective observational study carried out at 24 and 72 h and median of the patient's hospital stay. An intragroup norm was performed, determining percentile ranks of the instrument's total scores. Patients with a P90 score were classified with a high level of prioritization for CPS. RESULTS: PrioFarClinH is divided into three sections, with prioritization criteria for health issues; therapeutic classes; laboratory parameters. It comprises 51 criteria with specific scores with simple total calculation. None of the criteria presented CVI <0.78, maintaining the items from the initial version of PrioFarClinH. The scores were adjusted per suggestions from the panel of judges. Data were collected from 393 patients. The P90 percentile in the three hospitalization stages (24 h, 72 h, and median) was found, respectively, in the following scores: 18.0, 20.0, and 22.6. CONCLUSIONS: PrioFarClinH is a comprehensive tool to target and to prioritize adults patients most likely to benefit from CPS. Evidence for adequate content validity was provided. However, further validation of this tool is necessary to establish tool performance.
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BACKGROUND: Medication literacy reflects the specific literacy skills necessary to act on medication-related information. A comprehensive and clear conceptual model that reflects medication literacy is lacking. Conceptual models describe the components that represent a construct, allowing for its understanding and providing a rationale for its measurement. OBJECTIVES: To propose a conceptual model to support the development of an instrument to measure medication literacy. METHODS: This is a three-phase methodological study. A literature review was conducted to identify the components that should be part of the preliminary conceptual model. Subsequently, the importance of its components was judged on a Likert-5 scale. Then, the model was refined, and the dimensions and subdimensions of medication literacy were defined. RESULTS: Forty-five experts were included, with a mean age of 39.9 (SD = 10.5) years, most of them females (86.7%) and pharmacists (80%). All components of the preliminary conceptual model were considered important to extremely important by most experts. "Dosing information", "medication name", and "processing the information received about their medication and acting upon medication instructions" were the components considered most important. In the refinement phase, we identified that the construct has four dimensions - functional literacy, communicative literacy, critical literacy, and numeracy, which include the subdimensions to access, understand, evaluate, calculate, and communicate medication-related information. CONCLUSIONS: The conceptual model allowed identifying the components that represent medication literacy, which will support the development of an instrument for measuring the construct in Brazil.
Subject(s)
Health Literacy , Adult , Brazil , Communication , Female , Humans , Models, Theoretical , PharmacistsABSTRACT
BACKGROUND: Identifying patients at high risk of adverse medication-related outcomes for targeted clinical pharmacy services is essential in hospital pharmacy. Models and predictive tools to prioritize patients are available to the clinical pharmacy services for hospital use. OBJECTIVE: To describe and assess prognostic models and predictive tools used to identify inpatients at risk of adverse medication-related outcomes. METHODS: We searched in Medline, Lilacs, Cochrane, CINAHL, Embase, Scopus and Web of Science, databases of theses and dissertations, and the references of the selected studies. The screening was carried out by two independent researchers. Cross-sectional studies, prospective or retrospective cohort studies, and case-control studies were eligible for inclusion. The studies addressed the development or validation of predictive models and clinical prioritization tools based on expert opinion to identify inpatients at risk of adverse medication-related outcomes. RESULTS: 25 studies were included, 13 of which were prognostic prediction models, seven were instrument development using the consensus method, and five were validation. The outcome events were drug-related problems (9), adverse drug reactions (8), adverse drug events (6), and medication errors (2). Most studies targeted adult patients (14), eight had older adult patients, one had obstetric patients, and others had pediatric patients. External validation was performed after the development study in three studies. The predictive model with a low risk of bias was the Medicines Optimisation Assessment Tool. Limited details on the method of expert involvement and the number of experts were identified in four studies. CONCLUSION: The development of patient prioritization tools to optimize pharmacotherapy by clinical pharmacy services is a complex process. The predictive models and tools analyzed are limited in their development and validation process, hindering their effective use in prioritizing patients by the clinical pharmacy services. The development of additional prognostic prediction models for drug-related problems is a priority.
