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|Title:||Development of Screening Tools to Predict Medication-Related Problems Across the Continuum of Emergency Department Care: A Prospective, Multicenter Study.||Austin Authors:||Taylor, Simone E ;Mitri, Elise A ;Harding, Andrew M ;Taylor, David McD ;Weeks, Adrian;Abbott, Leonie;Lambros, Pani;Lawrence, Dona;Strumpman, Dana;Senturk-Raif, Reyhan;Louey, Stephen;Crisp, Hamish;Tomlinson, Emily;Manias, Elizabeth||Affiliation:||Pharmacy Department, Barwon Health, Geelong, VIC, Australia..
Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia..
Pharmacy Department, Western Health, Footscray, VIC, Australia..
Pharmacy Department, Northern Health, Epping, VIC, Australia..
Pharmacy Department, Eastern Health, Box Hill Hospital, Box Hill, VIC, Australia..
Pharmacy Department, Manly Hospital, Manly, NSW, Australia..
Pharmacy Department, Northern Beaches Hospital, Frenchs Forest, NSW, Australia..
Pharmacy Department, Prince of Wales Hospital, Randwick, NSW, Australia..
Pharmacy Department, Monash Health, Dandenong Hospital, Dandenong, VIC, Australia..
Pharmacy Department, Monash Health, Casey Hospital, Berwick, VIC, Australia..
Pharmacy Department, Launceston General Hospital, Launceston, TAS, Australia..
School of Nursing and Midwifery, Centre for Quality and Patient Safety Research, Institute for Health Transformation, Faculty of Health, Deakin University, Burwood, VIC, Australia..
Department of Critical Care, Melbourne Medical School, University of Melbourne, Parkville, VIC, Australia..
|Issue Date:||6-Jul-2022||Date:||2022||Publication information:||Frontiers in pharmacology 2022; 13: 865769||Abstract:||Background: Medication-related problems (MRPs) occur across the continuum of emergency department (ED) care: they may contribute to ED presentation, occur in the ED/short-stay unit (SSU), at hospital admission, or shortly after discharge to the community. This project aimed to determine predictors for MRPs across the continuum of ED care and incorporate these into screening tools (one for use at ED presentation and one at ED/SSU discharge), to identify patients at greatest risk, who could be targeted by ED pharmacists. Methods: A prospective, observational, multicenter study was undertaken in nine EDs, between July 2016 and August 2017. Blocks of ten consecutive adult patients presenting at pre-specified times were identified. Within 1 week of ED discharge, a pharmacist interviewed patients and undertook a medical record review to determine a medication history, patient understanding of treatment, risk factors for MRPs and to manage the MRPs. Logistic regression was undertaken to determine predictor variables. Multivariable regression beta coefficients were used to develop a scoring system for the two screening tools. Results: Of 1,238 patients meeting all inclusion criteria, 904 were recruited. Characteristics predicting MRPs related to ED presentation were: patient self-administers regular medications (OR = 7.95, 95%CI = 3.79-16.65), carer assists with medication administration (OR = 15.46, 95%CI = 6.52-36.67), or health-professional administers (OR = 5.01, 95%CI = 1.77-14.19); medication-related ED presentation (OR = 9.95, 95%CI = 4.92-20.10); age ≥80 years (OR = 3.63, 95%CI = 1.96-6.71), or age 65-79 years (OR = 2.01, 95%CI = 1.17-3.46); potential medication adherence issue (OR = 2.27, 95%CI = 1.38-3.73); medical specialist seen in past 6-months (OR = 2.02, 95%CI = 1.42-2.85); pharmaceutical benefit/pension/concession cardholder (OR = 1.89, 95%CI = 1.28-2.78); inpatient in previous 4-weeks (OR = 1.60, 95%CI = 1.02-2.52); being male (OR = 1.48, 95%CI = 1.05-2.10); and difficulties reading labels (OR = 0.63, 95%CI = 0.40-0.99). Characteristics predicting MRPs related to ED discharge were: potential medication adherence issue (OR = 6.80, 95%CI = 3.97-11.64); stay in ED > 8 h (OR = 3.23, 95%CI = 1.47-7.78); difficulties reading labels (OR = 2.33, 95%CI = 1.30-4.16); and medication regimen changed in ED (OR = 3.91, 95%CI = 2.43-6.30). For ED presentation, the model had a C-statistic of 0.84 (95% CI 0.81-0.86) (sensitivity = 80%, specificity = 70%). For ED discharge, the model had a C-statistic of 0.78 (95% CI 0.73-0.83) (sensitivity = 82%, specificity = 57%). Conclusion: Predictors of MRPs are readily available at the bedside and may be used to screen for patients at greatest risk upon ED presentation and upon ED/SSU discharge to the community. These screening tools now require external validation and implementation studies to evaluate the impact of using such tools on patient care outcomes.||URI:||https://ahro.austin.org.au/austinjspui/handle/1/30650||DOI:||10.3389/fphar.2022.865769||ORCID:||0000-0002-8986-9997
|Journal:||Frontiers in pharmacology||PubMed URL:||35873587||PubMed URL:||https://pubmed.ncbi.nlm.nih.gov/35873587/||ISSN:||1663-9812||Type:||Journal Article||Subjects:||emergency department
|Appears in Collections:||Journal articles|
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