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      Systematic review of predictive risk models for adverse drug events in hospitalized patients : Predictive risk models for adverse drug events in hospitalized patients

      1 , 1 , 2 , 1
      British Journal of Clinical Pharmacology
      Wiley

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          Abstract

          <div class="section"> <a class="named-anchor" id="bcp13514-sec-0001"> <!-- named anchor --> </a> <h5 class="section-title" id="d3203125e221">Aim</h5> <p id="d3203125e223">An emerging approach to reducing hospital adverse drug events is the use of predictive risk scores. The aim of this systematic review was to critically appraise models developed for predicting adverse drug event risk in inpatients. </p> </div><div class="section"> <a class="named-anchor" id="bcp13514-sec-0002"> <!-- named anchor --> </a> <h5 class="section-title" id="d3203125e226">Methods</h5> <p id="d3203125e228">Embase, PubMed, CINAHL and Scopus databases were used to identify studies of predictive risk models for hospitalized adult inpatients. Studies had to have used multivariable logistic regression for model development, resulting in a score or rule with two or more variables, to predict the likelihood of inpatient adverse drug events. The Checklist for the critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) was used to critically appraise eligible studies. </p> </div><div class="section"> <a class="named-anchor" id="bcp13514-sec-0003"> <!-- named anchor --> </a> <h5 class="section-title" id="d3203125e231">Results</h5> <p id="d3203125e233">Eleven studies met the inclusion criteria and were included in the review. Ten described the development of a new model, whilst one study revalidated and updated an existing score. Studies used different definitions for outcome but were synonymous with or closely related to adverse drug events. Four studies undertook external validation, five internally validated and two studies did not validate their model. No studies evaluated impact of risk scores on patient outcomes. </p> </div><div class="section"> <a class="named-anchor" id="bcp13514-sec-0004"> <!-- named anchor --> </a> <h5 class="section-title" id="d3203125e236">Conclusion</h5> <p id="d3203125e238">Adverse drug event risk prediction is a complex endeavour but could help to improve patient safety and hospital resource management. Studies in this review had some limitations in their methods for model development, reporting and validation. Two studies, the BADRI and Trivalle's risk scores, used better model development and validation methods and reported reasonable performance, and so could be considered for further research. </p> </div>

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          Most cited references36

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          US pharmacists' effect as team members on patient care: systematic review and meta-analyses.

          One approach postulated to improve the provision of health care is effective utilization of team-based care including pharmacists. The objective of this study was to conduct a comprehensive systematic review with focused meta-analyses to examine the effects of pharmacist-provided direct patient care on therapeutic, safety, and humanistic outcomes. The following databases were searched from inception to January 2009: NLM PubMed; Ovid/MEDLINE; ABI/INFORM; Health Business Fulltext Elite; Academic Search Complete; International Pharmaceutical Abstracts; PsycINFO; Cochrane Database of Systematic Reviews; National Guideline Clearinghouse; Database of Abstracts of Reviews of Effects; ClinicalTrials.gov; LexisNexis Academic Universe; and Google Scholar. Studies selected included those reporting pharmacist-provided care, comparison groups, and patient-related outcomes. Of these, 56,573 citations were considered. Data were extracted by multidisciplinary study review teams. Variables examined included study characteristics, pharmacists' interventions/services, patient characteristics, and study outcomes. Data for meta-analyses were extracted from randomized controlled trials meeting meta-analysis criteria. A total of 298 studies were included. Favorable results were found in therapeutic and safety outcomes, and meta-analyses conducted for hemoglobin A1c, LDL cholesterol, blood pressure, and adverse drug events were significant (P < 0.05), favoring pharmacists' direct patient care over comparative services. Results for humanistic outcomes were favorable with variability. Medication adherence, patient knowledge, and quality of life-general health meta-analyses were significant (P < 0.05), favoring pharmacists' direct patient care. Pharmacist-provided direct patient care has favorable effects across various patient outcomes, health care settings, and disease states. Incorporating pharmacists as health care team members in direct patient care is a viable solution to help improve US health care.
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            Validation, updating and impact of clinical prediction rules: a review.

            To provide an overview of the research steps that need to follow the development of diagnostic or prognostic prediction rules. These steps include validity assessment, updating (if necessary), and impact assessment of clinical prediction rules. Narrative review covering methodological and empirical prediction studies from primary and secondary care. In general, three types of validation of previously developed prediction rules can be distinguished: temporal, geographical, and domain validations. In case of poor validation, the validation data can be used to update or adjust the previously developed prediction rule to the new circumstances. These update methods differ in extensiveness, with the easiest method a change in model intercept to the outcome occurrence at hand. Prediction rules -- with or without updating -- showing good performance in (various) validation studies may subsequently be subjected to an impact study, to demonstrate whether they change physicians' decisions, improve clinically relevant process parameters, patient outcome, or reduce costs. Finally, whether a prediction rule is implemented successfully in clinical practice depends on several potential barriers to the use of the rule. The development of a diagnostic or prognostic prediction rule is just a first step. We reviewed important aspects of the subsequent steps in prediction research.
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              Incidence of Adverse Drug Events and Potential Adverse Drug Events

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                Author and article information

                Journal
                British Journal of Clinical Pharmacology
                Br J Clin Pharmacol
                Wiley
                03065251
                May 2018
                May 2018
                February 22 2018
                : 84
                : 5
                : 846-864
                Affiliations
                [1 ]School of Pharmacy, Pharmacy Australia Centre of Excellence; The University of Queensland; Brisbane QLD 4102 Australia
                [2 ]Princess Alexandra Hospital; Metro South Health; 199 Ipswich Road, Woolloongabba Brisbane QLD 4102 Australia
                Article
                10.1111/bcp.13514
                5903258
                29337387
                968ab799-c61b-4674-ab46-83a58cfe7f53
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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