OBJECTIVES: This study aimed to determine the incidence of unintentional discrepancies (medication errors), types of medication errors with its potential severity of patient harm and acceptance rate of pharmaceutical care interventions.
METHODS: A four-month cross-sectional study was conducted in the general medical wards of a tertiary hospital. All newly admitted patients with at least one prescription medication were recruited via purposive sampling. Medication history assessments were done by clinical pharmacists within 24 hours or as soon as possible after admission. Pharmacist-acquired medication histories were then compared with in-patient medication charts to detect discrepancies. Verification of the discrepancies, interventions, and assessment of the potential severity of patient harm resulting from medication errors were collaboratively carried out with the treating doctors.
RESULTS: There were 990 medication discrepancies detected among 390 patients recruited in this study. One hundred and thirty-five (13.6%) medication errors were detected in 93 (23.8%) patients (1.45 errors per patient). These were mostly contributed by medication omissions (79.3%), followed by dosing errors (9.6%). Among these errors, 88.2% were considered "significant" or "serious" but none were "life-threatening." Most (83%) of the pharmaceutical interventions were accepted by the doctors.
CONCLUSION: Medication history assessment by pharmacists proved vital in detecting medication errors, mostly medication omissions. Majority of the errors intervened by pharmacists were accepted by the doctors which prevented potential significant or serious patient harm.
METHODS: Articles published from 2012 to 2021 were searched through seven databases. Studies that established the relationship for risk factors of TB treatment interruption among adult Asian were included. Relevant articles were screened, extracted and appraised using Joanna Briggs Institute's checklists for cohort, case-control and cross-sectional study designs by three reviewers. Meta-analysis was performed using the random effect model in Review Manager software. The pooled prevalence and predictors of treatment interruption were expressed in ORs with 95% CIs; heterogeneity was assessed using the I2 statistic. The publication bias was visually inspected using the funnel plot.
RESULTS: Fifty eligible studies (658 304 participants) from 17 Asian countries were included. The overall pooled prevalence of treatment interruption was 17% (95% CI 16% to 18%), the highest in Southern Asia (22% (95% CI 16% to 29%)), followed by Eastern Asia (18% (95% CI 16% to 20%)) and South East Asia (16% (95% CI 4% to 28%)). Seven predictors were identified to increase the risk of treatment interruption, namely, male gender (OR 1.38 (95% CI 1.26 to 1.51)), employment (OR 1.43 (95% CI 1.11 to 1.84)), alcohol intake (OR 2.24 (95% CI 1.58 to 3.18)), smoking (OR 2.74 (95% CI 1.98 to 3.78)), HIV-positive (OR 1.50 (95% CI 1.15 to 1.96)), adverse drug reactions (OR 2.01 (95% CI 1.20 to 3.34)) and previously treated cases (OR 1.77 (95% CI 1.39 to 2.26)). All predictors demonstrated substantial heterogeneity except employment and HIV status with no publication bias.
CONCLUSION: The identification of predictors for TB treatment interruption enables strategised planning and collective intervention to be targeted at the high-risk groups to strengthen TB care and control in the Asia region.
METHODS: We conducted a retrospective cohort study by retrieving 4 years (2018-2021) of TB patients' records at 10 public health clinics in Sarawak, Malaysia. Adult patients (≥18 years) with drug-susceptible TB were selected. Treatment interruption was defined as ≥2 weeks of cumulative interruption during treatment. The Chi-square test, Mann-Whitney U test, Kaplan-Meier and Cox proportional hazards regression were used to analyse the data, with p
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
METHODS: A pre-post intervention study was conducted at medical wards in a public tertiary hospital. During the intervention phase, a structured bedside dispensing process was delineated and conveyed to the doctors, nurses, and pharmacists. Regular verbal reminders were given to the doctors to prioritize discharge patients by producing the prescriptions once discharge decisions had been made and nurses to hand the prescriptions to ward pharmacists and not patients. Throughout the study, ward pharmacists were involved in medication reconciliation via screening of discharge prescriptions and reusing POMs, performed pharmaceutical interventions for any medication errors detected, and provided bedside dispensing with discharge counseling. Comparisons were made between bedside versus counter-dispensing at pre-post intervention phases using the chi-square test.
RESULTS: A total of 1097 and 817 discharge prescriptions were dispensed in the pre-intervention and post-intervention phases, respectively. The bedside dispensing rate increased by 13.5% following remedial actions (p