Research in Social & Administrative Pharmacy最新文献

Objective: To investigate the association between patient-reported experiences with new medication discharge counselling and readmission to hospital or emergency department (ED) visits within 30 days of discharge.

Methods: A retrospective cross-sectional study of patient-reported experiences from 8715 patients who reported being prescribed a new medication at discharge from a public hospital. Completeness of medication counselling was assessed based on (i) explanation of medication purpose, (ii) explanation of medication side effects, (iii) patient involvement in decision to use medication, (iv) provision of contradictory information. Multilevel models were used to estimate self-reported 30-day readmission or ED visit related to care received using adjusted odds ratios (AORs).

Results: Patients who were explained medication purpose were half as likely to report a readmission (AOR 0.54, 95%CI 0.31-0.93) or ED visit (AOR 0.65, 95%CI 0.48-0.87) within 30 days of discharge. Conversely, those who reported receiving contradictory information were more likely to report a readmission (AOR 1.62, 95%CI 1.16-2.26) and ED visit (AOR 1.82, 95%CI 1.41-2.34).

Conclusion: Patients who reported receiving comprehensive counselling on new medications were less likely to report being readmitted or visiting an ED within 30 days of discharge.

Background: Pharmacists are increasingly involved in patient care. Pharmacy practice research helps them identify the most clinically meaningful interventions. However, the lack of a widely accepted controlled vocabulary in this field hinders the discovery of this literature.

Objective: To compare the performance of a machine learning model with manual literature searches in identifying potentially relevant publications on the clinical impact of pharmacist interventions. To describe the dataset that was built.

Methods: An automated PubMed search was performed weekly starting in November 2021. Titles and abstracts were retrieved and independently evaluated by two reviewers to select potentially relevant publications on the clinical impact of pharmacists. A Cohen's kappa score was calculated. Data was collected during an 11-month period to train a machine learning model. It was evaluated prospectively during a 5-month period (predictions were collected without being shown to the reviewers). The performance of the model was compared with manual searches (positive predictive value [PPV] and sensitivity).

Results: A transformers-based model was selected. During the prospective evaluation period, 114/1631 (7 %) publications met selection criteria. If the model had been used, 1273/1631 (78 %) would not have needed review. Only 3/114 (3 %) would have been incorrectly excluded. The model showed a PPV of 0.310 and a sensitivity of 0.974. The best manual search showed a PPV of 0.046 and a sensitivity of 0.711. On December 12, 2023, the dataset contained 8607 publications, of which 544 (6 %) met the criteria. The kappa between reviewers was 0.786. The dataset and the model were used to develop a website and a newsletter to share publications (https://impactpharmacy.net).

Conclusion: A machine learning model was developed and performs better than manual PubMed searches to identify potentially relevant publications. It represents a considerable workload reduction. This tool can assist pharmacists and other stakeholders in finding evidence that support pharmacists' interventions.

Pharmacists' roles have evolved substantially from traditional drug compounding and dispensing to encompass patient-centred clinical services. Pharmacist clinical reasoning, though fundamental to these new roles, generally remains implicit and understudied, particularly compared with that of other healthcare professionals, such as physicians. However, teaching and supervising the clinical services provided by pharmacists require a thorough understanding of the reasoning process involved. Several models describing pharmacist clinical reasoning have been developed, but they lack unified mapping. Here, we used an instrumental case study approach to develop a model of pharmacist clinical reasoning during medication review. Our model is adapted from a previously published modelling-using-typified-objects model of physician clinical reasoning in all its cognitive complexity. Our pharmacist model, validated after iterative development and expert consultation, aligns components of pharmacist clinical reasoning with those of physician clinical reasoning. The clinical case contains drug-related problems of variable clinical relevance, as well as numerous key elements (e.g., laboratory results, vital signs) necessary for conducting a medication review. The case serves both as the foundation for model development and as an illustrative step-by-step example within this article. Our model delineates the subprocesses of pharmacist clinical reasoning during medication review, offering a flexible, multipath structure that underscores the dynamic, nonlinear nature of the reasoning. The model might be able to clarify implicit cognitive processes, thus furthering the overarching objective of promoting reflective skill development among learners rather than relying solely on tacit knowledge gained through practice experience.

Introduction: In light of the expanding role of pharmacy in addressing global health challenges of Universal Health Coverage, advancing pharmacy practice to provide more effective pharmaceutical services has become imperative. This study aims to develop and validate a global goals-oriented pharmaceutical development framework to support and guide a systematic practice transformation that can widen access to better health for all.

Methods: A mixed methods approach was used to conduct a series of exploration, development, and consensus phases. The exploratory stage included desk research focused on innovative pharmaceutical provision globally. Focus groups with 14 international pharmacists were held, selected via convenience sampling, to obtain primary data on perceptions of the proposed global FIP "Development Goals" framework. The consultation stage was followed by a modified nominal group technique (mNGT) with 61 global pharmacy leaders from 35 countries across six WHO regions, selected through purposive sampling, to further develop the content of the framework's first iteration. Lastly, an online two-round modified Delphi approach with 28 global pharmacy leaders, also selected via purposive sampling, was used to ensure the credibility and content validity of the outputs, generating consensus on the final framework matrix.

Results: The exploratory stage produced a draft set of 13 unvalidated FIP Practice Development Goals (DGs) Framework (v0). Initial analysis of the mNGT showed complex intersections between the proposed set of goals, necessitating further modifications by embedding the previously published global Pharmaceutical Workforce Development Goals framework. This resulted in an amended FIP DGs Framework (v1) with 21 DGs. The evidence-led adjustment and distinctive format of the global consensus stage helped generate the validated, systematic FIP DGs Framework (final version), comprising 21 discrete global development goals ready for policy deployment.

Conclusion: A systematic goals-oriented development framework was developed to respond to pharmaceutical development needs and support a needs-based roadmap for a sustainable pharmacy practice transformation globally, regionally and nationally.

Unintended discrepancy in medications at the time of discharge from the hospital is associated with an increased incidence of adverse drug events, including readmission to hospital. Medication literacy is an essential part of health literacy and can reduce medication discrepancies. This prospective observational cohort study aimed to measure the medication literacy of patients at the time of discharge from the hospital when managed with usual care and after the introduction of a medication literacy improvement instrument. This study involved a baseline cohort receiving usual care and a post-intervention cohort aged 50-80 years with high health literacy. The 7 Things I Should Know About My Medications at the Time of Discharge from Hospital instrument, in short, The 7 Domains MedLit Instrument, was designed by the researchers in addition to three medication literacy measurement questionnaires. Medication literacy was measured at 30 h post-discharge. The impact on readmission to hospital was assessed at 30 days post-discharge. The 7 Domains MedLit Instrument was found to significantly increase the number of patients reporting increased counselling by a clinician at the time of discharge from the hospital (clinician, 59.3 % vs. 100.0 %, X² (1, n = 49) = 11.10, p < 0.01, physician, 28.6 % vs. 76.2, X² (1, n = 49) = 10.9, p < 0.01, pharmacist 25.0 % vs. 71.4 %, X² (1, n = 49) = 10.4, p < 0.01)). Significantly, more patients had increased knowledge on drug interactions or adverse drug reactions after using the instrument (26.1 % vs. 61.9 %, P = 0.032 and 30.4 % vs. 66.7 %, P = 0.033, respectively). The 7 Domains MedLit Instrument and the schooling years significantly correlated with the knowledge of drug interactions and adverse drug reactions. Less post-intervention participants visited an emergency department within 30 days post-discharge. The 7 Domains MedLit Instrument significantly improved the patients' medication literacy at the time of discharge from hospital.

Background: Opioid utilization and related harm have increased in recent decades, notably in Australia, the United States, Canada, and some European countries. For people who are prescribed opioids, pharmacies offer an accessible, regular point-of-contact, providing a unique opportunity to address opioid prescription drugs risks.

Objective: This project aimed to develop consensus-based, best practice statements for improving the safer use of prescription opioids through community pharmacy settings.

Methods: The e-Delphi technique is used to obtain consensus from experts about issues where conclusive evidence is lacking, using multiple rounds of online participation. The investigator group identified an international group of potential participants with relevant expertise who were invited to the study, and asked to identify other experts for invitation. The e-Delphi process comprised three online rounds, involving (1) statement idea generation, (2) developing statement consensus, and (3) confirming and ranking statements.

Results: A diverse group of 42 experts (76 % female, 6 countries) participated, comprising pharmacists (n = 24, 57 %), medical doctors of differing specialties (n = 12, 29 %), and/or researchers (n = 28, 67 %), with a mean of 15 years' professional experience (SD = 8.08). Eighty-five statements were initially developed in Round 1, and 78 were supported with amendments, with suggestions to merge and remove items in Round 2, resulting in 72 final statements which were all endorsed in Round 3. Items spanned seven themes: education, monitoring outcomes and risk, deprescribing and pain management, overdose education and naloxone, opioid agonist treatment, staff education, and overarching practices. Preferred terminology was determined in Round 2 and confirmed in Round 3.

Conclusions: Community pharmacies offer a unique opportunity to support the safer use of prescription opioids. These 72 best practice statements provide practical guidance on specific practices that pharmacists can undertake to support patients' safer use of prescription opioids and prevent or reduce harms from prescribed opioid use.

Background: The prevalence of direct-to-consumer (DTC) advertising for prescription drugs has led to concerns about how consumers interpret the medical information conveyed in these ads. One strategy for improving lay understanding of medical information involves incorporating quantitative information about a treatment's potential benefits and risks.

Objective: This literature review investigates laypersons' interpretations of statistical concepts, expanding on past reviews and including terms that may be used in DTC prescription drug advertising.

Methods: We searched six databases for articles published from January 2000 to October 2021. Articles were included if they were in English and examined general or lay audiences' comprehension of quantitative or statistical concepts, without limiting the context of the studies to medical situations.

Results: We identified 25 eligible articles. The evidence suggests that likelihood ratios, odds ratios, probabilities, numbers needed to treat/harm, and confidence intervals hinder comprehension of quantitative information. The results are mixed for information presented as frequencies, percentages, absolute risk reduction, and relative risk reduction. The mixed findings could be due to numeracy, framing as risks or benefits, and operationalization of the outcomes. We found no studies examining interpretations of minimum, maximum, central tendency, power, statistical significance, or hazard ratio.

Conclusion: Studies spanning several decades have examined how laypeople interpret statistical concepts. While a few terms are consistently studied, many questions still remain on how to make risk information more understandable to lay audiences, particularly those with low numeracy.

Background: Prescribing by pharmacists is an increasingly common practice worldwide. In Brazil regulation of this practice began in 2013, and the practice remains unexplored as a research topic.

Objective: We aimed to explore and gain insights into pharmacist prescribing practices in Brazil and assessing pharmacist's perceptions of their training and preparedness to prescribe medications.

Methods: A cross-sectional survey was conducted between October 2022 and March 2023 via convenience sampling. Data were collected using an online questionnaire covering sociodemographic issues, academic training, prescribing practices, and perceptions regarding the provision of pharmacist prescribing in ambulatory care. Exploratory descriptive analysis and Poisson regression were performed to estimate the associations between pharmacist characteristics and their practices in prescribing medicines.

Results: Among the 305 valid responses, 58.7% of the outpatient pharmacists stated that they had not prescribed any medication in the previous three years. Over-the-counter medication prescriptions were most common (42.0%). Only 4.6% of respondents had prescribed prescription-only medicines provided through collaborative agreement, with 2.6% reporting that they had adjusted doses, and 2.3% played a role in prescription renewal. Pharmacists living in Northeast regions tended to be more active prescribers (PR = 1.42; 95%CI 1.03-2.18), whereas those in primary healthcare (PR = 0.61; 95%CI 0.39-0.96) and self-declared Black pharmacists (PR = 0.30; 95%CI 0.10-0.97) prescribed less. Respondents strongly believed in the pharmacist's role as a prescriber, although they remained ambivalent regarding their responsibility for patient outcomes. Progress barriers include infrastructure gaps and strained relationships with physicians.

Conclusions: This study suggests that pharmacists in Brazil predominantly prescribe over-the-counter medications, and variations in setting, region, and race can influence prescribing by pharmacist in ambulatory care.

Background: Tuberculosis (TB) treatment interruption poses risks of antimicrobial resistance, potentially leading to treatment failure and mortality. Addressing the risk of early treatment interruption is crucial in tuberculosis care and management to improve treatment outcomes and curb disease transmission.

Objectives: This study aimed to identify risk factors of TB treatment interruption and construct a predictive scoring model that enables objective risk stratification for better prediction of treatment interruption.

Methods: A multicentre retrospective cohort study was conducted at public health clinics in Sarawak, Malaysia over 11 months from March 2022 to January 2023, involving adult patients aged ≥18 years with drug-susceptible TB diagnosed between 2018 and 2021. Cumulative missed doses or discontinuation of TB medications for ≥2 weeks, either consecutive or non-consecutive, was considered as treatment interruption. The model was developed and internally validated using the split-sample method. Multiple logistic regression analysed 18 pre-defined variables to identify the predictors of TB treatment interruption. The Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUC) were employed to evaluate model performance.

Results: Of 2953 cases, two-thirds (1969) were assigned to the derivation cohort, and one-third (984) formed the validation cohort. Positive predictors included smoking, previously treated cases, and adverse drug reactions, while concurrent diabetes was protective. Based on the validation dataset, the model demonstrated good calibration (P = 0.143) with acceptable discriminative ability (AUC = 0.775). A cutoff score of 2.5 out of 11 achieved a sensitivity of 81 % and a specificity of 64.4 %. Risk stratification into low (0-2), medium (3-5), and high-risk (≥6) categories showed ascending interruption rates of 5.3 %, 18.1 %, and 41.3 %, respectively (P < 0.001).

Conclusion: The predictive scoring model aids in risk assessment for TB treatment interruption, enabling focused monitoring and personalized intervention plans for higher-risk groups in the early treatment phase.