OntoPharma: ontology based clinical decision support system to reduce medication prescribing errors

Background: Clinical decision support systems (CDSS) have been shown to reduce medication errors. However, they are underused because of different challenges. One approach to improve CDSS is to use ontologies instead of relational databases. The primary aim was to design and develop OntoPharma, an ontology based CDSS to reduce medication prescribing errors. Secondary aim was to implement OntoPharma in a hospital setting. Methods: A four-step process was proposed. (1) Defining the ontology domain. The ontology scope was the medication domain. An advisory board selected four use cases: maximum dosage alert, drug-drug interaction checker, renal failure adjustment, and drug allergy checker. (2) Implementing the ontology in a formal representation. The implementation was conducted by Medical Informatics specialists and Clinical Pharmacists using Protégé-OWL. (3) Developing an ontology-driven alert module. Computerised Physician Order Entry (CPOE) integration was performed through a REST API. SPARQL was used to query ontologies. (4) Implementing OntoPharma in a hospital setting. Alerts generated between July 2020/ November 2021 were analysed. Results: The three ontologies developed included 34,938 classes, 16,672 individuals and 82 properties. The domains addressed by ontologies were identification data of medicinal products, appropriateness drug data, and local concepts from CPOE. When a medication prescribing error is identified an alert is shown. OntoPharma generated 823 alerts in 1046 patients. 401 (48.7%) of them were accepted. Conclusions: OntoPharma is an ontology based CDSS implemented in clinical practice which generates alerts when a prescribing medication error is identified. To gain user acceptance OntoPharma has been designed and developed by a multidisciplinary team. Compared to CDSS based on relational databases, OntoPharma represents medication knowledge in a more intuitive, extensible and maintainable manner

Design and validation of a predictive model for 1-year hospital admission in HIV patients on antiretroviral treatment

Objectives To develop and validate a model for predicting the risk of hospital admission within 1 year in the HIV population under antiretroviral treatment.Methods We conducted a retrospective observational study. Patients receiving antiretroviral treatment for at least 1 year who were followed by the pharmacy service in a Spanish-speaking hospital between January 2008 and December 2012 were included. Demographics, and clinical and pharmacotherapy variables, were included in the model design. To find prognostic factors for hospital admission a multivariate logistic regression model was created after performing a univariate analysis. Model validity was determined by the shrinkage method and the model discrimination by Harrell's C-index.Results 442 patients were included in the study. The variables 'CD4 count 50 copies/mL)', 'number of previous admissions', and 'number of drugs different from antiretroviral treatment' were the independent predictors of risk of hospital admission. Probabilities predicted by the model showed an R-2=0.98 for the development sample and an R-2=0.86 for the validation sample. The Harrell's C index for the development and validation data were 0.82 (95% CI 0.77 to 0.87) and 0.80 (95% CI 0.73 to 0.88), respectively.Conclusions The model developed in this study may be useful in daily practice for identifying HIV patients at high risk of 1-year hospital admission

Traducción y adaptación transcultural al español del cuestionario ARMS para la medida de la adherencia en pacientes pluripatológicos.

Translate the ARMS scale into Spanish ensuring cross-cultural equivalence for measuring medication adherence in polypathological patients. Translation, cross-cultural adaptation and pilot testing. Secondary hospital. (i)Forward and blind-back translations followed by cross-cultural adaptation through qualitative methodology to ensure conceptual, semantic and content equivalence between the original scale and the Spanish version. (ii)Pilot testing in non-institutionalized polypathological patients to assess the instrument for clarity. The Spanish version of the ARMS scale has been obtained. Overall scores from translators involved in forward and blind-back translations were consistent with a low difficulty for assuring conceptual equivalence between both languages. Pilot testing (cognitive debriefing) in a sample of 40 non-institutionalized polypathological patients admitted to an internal medicine department of a secondary hospital showed an excellent clarity. The ARMS-e scale is a Spanish-adapted version of the ARMS scale, suitable for measuring adherence in polypathological patients. Its structure enables a multidimensional approach of the lack of adherence allowing the implementation of individualized interventions guided by the barriers detected in every patient

Selection of interventions aimed at improving medication adherence in patients with multimorbidity

[Objectives]: To select interventions aimed at improving medication adherence in patients with multimorbidity by means of a standardised methodology. [Methods]: A modified Delphi methodology was used to reach consensus. Interventions that had demonstrated their efficacy in improving medication adherence in patients with multimorbidity or in similar populations were identified from a literature search of several databases (PubMed, EMBASE, the Cochrane Library, Center for Reviews and Dissemination, and Web of Science). 11 experts in medication adherence and/or chronic disease scored the selected interventions for appropriateness according to three criteria: strength of the evidence that supported each intervention, usefulness in patients with multimorbidity, and feasibility of implementation in clinical practice. The final set of interventions was selected according to appropriateness and agreement based on the Delphi methodology. [Results]: 566 articles were retrieved in the literature search. Nine systematic reviews were included. 33 interventions were initially selected for evaluation by the panellists. Consensus after two Delphi rounds was reached on 16 interventions. Five interventions were categorized as educational, six as behavioural and five were related to other aspects of interest. [Conclusions]: The interventions selected following a comprehensive and standardized methodology, could be used to improve medication adherence in patients with multimorbidity

Selection of interventions aimed at improving medication adherence in patients with multimorbidity.

To select interventions aimed at improving medication adherence in patients with multimorbidity by means of a standardised methodology. A modified Delphi methodology was used to reach consensus. Interventions that had demonstrated their efficacy in improving medication adherence in patients with multimorbidity or in similar populations were identified from a literature search of several databases (PubMed, EMBASE, the Cochrane Library, Center for Reviews and Dissemination, and Web of Science). 11 experts in medication adherence and/or chronic disease scored the selected interventions for appropriateness according to three criteria: strength of the evidence that supported each intervention, usefulness in patients with multimorbidity, and feasibility of implementation in clinical practice. The final set of interventions was selected according to appropriateness and agreement based on the Delphi methodology. 566 articles were retrieved in the literature search. Nine systematic reviews were included. 33 interventions were initially selected for evaluation by the panellists. Consensus after two Delphi rounds was reached on 16 interventions. Five interventions were categorized as educational, six as behavioural and five were related to other aspects of interest. The interventions selected following a comprehensive and standardized methodology, could be used to improve medication adherence in patients with multimorbidity