OBJECTIVE: To assess the effect of a service containing self-management support delivered by community pharmacists to patients with asthma.
METHODS: A systematic search was performed in the following databases from inception to January 2017: PubMed, Embase, Cochrane Library's Central Register of Controlled Trials, CINAHL (Cumulative Index to Nursing and Allied Health Literature) Plus, International Pharmaceutical Abstracts, and PsycInfo. Original studies were selected if they met the following criteria: (a) provided by community pharmacists; (b) the intervention service included the essential components of asthma self-management; (c) included a usual care group; and (d) measured control/severity of asthma symptoms, health-related quality of life (HRQOL), or medication adherence.
RESULTS: Of the 639 articles screened, 12 studies involving 2,121 asthma patients were included. Six studies were randomized trials, and the other 6 were nonrandomized trials. Patients with asthma who received a self-management support service by community pharmacists had better symptom control/lower severity compared with those receiving usual care (standardized mean difference [SMD] = 0.46; 95% CI = 0.09-0.82) with high heterogeneity (I2=82.6%; P = 0.000). The overall improvement in HRQOL and medication adherence among patients in the asthma self-management support group was greater than for those in the usual care group with SMD of 0.23 (95% CI = 0.12-0.34) and 0.44 (95% CI = 0.27-0.61), respectively. Evidence of heterogeneity was not observed in these 2 outcomes.
CONCLUSIONS: Self-management support service provided by community pharmacists can help improve symptom control, quality of life, and medication adherence in patients with asthma.
DISCLOSURES: This study received financial support from Naresuan University's Faculty of Pharmaceutical Sciences Research Fund. Two authors, Saini and Krass, have studies that were included in this review. However, they were not involved in the processes that could bias outcomes of the present study, that is, quality assessment and meta-analysis. The remaining authors have declared no conflicts of interest.
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: To assess the effects of mobile phone text messaging in patients with established arterial occlusive events on adherence to treatment, fatal and non-fatal cardiovascular events, and adverse effects.
SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, the Conference Proceedings Citation Index - Science on Web of Science on 7 November 2016, and two clinical trial registers on 12 November 2016. We contacted authors of included studies for missing information and searched reference lists of relevant papers. We applied no language or date restrictions.
SELECTION CRITERIA: We included randomised trials with at least 50% of the participants with established arterial occlusive events. We included trials investigating interventions using short message service (SMS) or multimedia messaging service (MMS) with the aim to improve adherence to medication for the secondary prevention of cardiovascular events. Eligible comparators were no intervention or other modes of communication.
DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. In addition, we attempted to contact all authors on how the SMS were developed.
MAIN RESULTS: We included seven trials (reported in 13 reports) with 1310 participants randomised. Follow-up ranged from one month to 12 months. Due to heterogeneity in the methods, population and outcome measures, we were unable to conduct meta-analysis on these studies. All seven studies reported on adherence, but using different methods and scales. Six out of seven trials showed a beneficial effect of mobile phone text messaging for medication adherence. Dale 2015a, reported significantly greater medication adherence score in the intervention group (Mean Difference (MD) 0.58, 95% confidence interval (CI) 0.19 to 0.97; 123 participants randomised) at six months. Khonsari 2015 reported less adherence in the control group (Relative Risk (RR) 4.09, 95% CI 1.82 to 9.18; 62 participants randomised) at eight weeks. Pandey 2014 (34 participants randomised) assessed medication adherence through self-reported logs with 90% adherence in the intervention group compared to 70% in the control group at 12 months. Park 2014a (90 participants randomised) reported a greater increase of the medication adherence score in the control group, but also measured adherence with an event monitoring system for a number of medications with adherence levels ranging from 84.1% adherence to 86.2% in the intervention group and 79.7% to 85.7% in the control group at 30 days. Quilici 2013, reported reduced odds of non-adherence in the intervention group (Odds Ratio (OR) 0.43, 95% CI 0.22 to 0.86, 521 participants randomised) at 30 days. Fang 2016, reported that participants given SMS alone had reduced odds of being non-adherent compared to telephone reminders (OR 0.40 95% CI 0.18 to 0.63; 280 patients randomised). Kamal 2015 reported higher levels of adherence in the intervention arm (adjusted MD 0.54, 95% CI 0.22 to 0.85; 200 participants randomised). Khonsari 2015 was the only study to report fatal cardiovascular events and only reported two events, both in the control arm. No study reported on the other primary outcomes. No study reported repetitive thumb injury or road traffic crashes or other adverse events that were related to the intervention.Four authors replied to our questionnaire on SMS development. No study reported examining causes of non-adherence or provided SMS tailored to individual patient characteristics.The included studies were small, heterogeneous and included participants recruited directly after acute events. All studies were assessed as having high risk of bias across at least one domain. Most of the studies came from high-income countries, with two studies conducted in an upper middle-income country (China, Malaysia), and one study from a lower middle-income country (Pakistan). The quality of the evidence was found to be very low. There was no obvious conflicts of interest from authors, although only two declared their funding.
AUTHORS' CONCLUSIONS: While the results of this systematic review are promising, there is insufficient evidence to draw conclusions on the effectiveness of text message-based interventions for adherence to medications for secondary prevention of CVD. Sufficiently powered, high-quality randomised trials are needed, particularly in low- and middle-income countries.
AIM: This study aimed to evaluate the feasibility of implementing medication reviews with follow-up for older adults in community pharmacies and examined potential outcomes on medication use.
METHOD: A pilot randomised controlled trial was conducted with 4 cluster-randomised community pharmacies to assess the feasibility of the intervention. Two community pharmacies served as intervention and control groups. Both groups recruited older adults over 60 who were followed over 6 months. The translated Medication use Questionnaire (MedUseQ) was administered at baseline and 6 months for both groups. The outcomes were to assess the feasibility of conducting medication review with follow-up and the probable medication use outcomes from the intervention.
RESULTS: The intervention and control groups comprised 14 and 13 older adults. A total of 35 recommendations were made by pharmacists in the intervention group and 8 in the control group. MedUseQ was easily administered, providing some evidence the feasibility of the intervention. However, there were feasibility challenges such as a lack of pharmacists, collaborative practice, difficulties with the tool language, time constraints, and limited funds. Questionnaire results provided a signal of improvement in medication administration, adherence, and polypharmacy among intervention participants. The incidence of drug related problems was significantly higher in the control group (median = 1) after 6 months, U = 15, z = - 2.98, p = 0.01.
CONCLUSION: Medication review with follow-up is potentialy practical in community pharmacies, but there are feasibility issues. While these challenges can be addressed, it is essential to study larger sample sizes to establish more robust evidence regarding outcomes.
CLINICAL TRIAL REGISTRY: ClinicalTrials.Gov NCT05297461.
METHODS: Patients initiating cART between 2006 and 2013 were included. TI was defined as stopping cART for >1 day. Treatment failure was defined as confirmed virological, immunological or clinical failure. Time to treatment failure during cART was analysed using Cox regression, not including periods off treatment. Covariables with P < 0.10 in univariable analyses were included in multivariable analyses, where P < 0.05 was considered statistically significant.
RESULTS: Of 4549 patients from 13 countries in Asia, 3176 (69.8%) were male and the median age was 34 years. A total of 111 (2.4%) had TIs due to AEs and 135 (3.0%) had TIs for other reasons. Median interruption times were 22 days for AE and 148 days for non-AE TIs. In multivariable analyses, interruptions >30 days were associated with failure (31-180 days HR = 2.66, 95%CI (1.70-4.16); 181-365 days HR = 6.22, 95%CI (3.26-11.86); and >365 days HR = 9.10, 95% CI (4.27-19.38), all P < 0.001, compared to 0-14 days). Reasons for previous TI were not statistically significant (P = 0.158).
CONCLUSIONS: Duration of interruptions of more than 30 days was the key factor associated with large increases in subsequent risk of treatment failure. If TI is unavoidable, its duration should be minimised to reduce the risk of failure after treatment resumption.
OBJECTIVE: To investigate the impact of customized CMI (C-CMI) on health-related quality of life (HRQoL) among type 2 diabetes mellitus (T2DM) patients in Qatar.
METHODS: This was a randomized controlled intervention study, in which the intervention group patients received C-CMI and the control group patients received usual care. HRQoL was measured using the EQ-5D-5L questionnaire and EQ visual analog scale (EQ-VAS) at three intervals [i.e. baseline, after 3 months and 6 months].
RESULTS: The EQ-5D-5L index value for the intervention group exhibited sustained improvement from baseline to the third visit. There was a statistically significant difference between groups in the HRQoL utility value (represented as EQ index) at 6 months (0.939 vs. 0.796; p = 0.019). Similarly, the intervention group compared with the control group had significantly greater EQ-VAS at 6 months (90% vs. 80%; p = 0.003).
CONCLUSIONS: The impact of C-CMI on health outcomes of T2DM patients in Qatar reported improvement in HRQoL indicators among the intervention patients. The study built a platform for health policymakers and regulatory agencies to consider the provision of C-CMI in multiple languages.
METHODS: A randomized controlled trial was conducted from December 2014 to April 2015. The home blood pressure monitoring group used an automatic blood pressure device along with standard hypertension outpatient care. Patients were seen at baseline and after 2 months. Medication adherence was measured using a novel validated Medication Adherence Scale (MAS) questionnaire. Office blood pressure and MAS were recorded at both visits. The primary outcomes included evaluation of mean office blood pressure and MAS within groups and between groups at baseline and after 2 months.
RESULTS: Mean changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) and MAS differed significantly within groups. The home blood pressure monitoring group showed greater mean changes (SBP 17.6 mm Hg, DBP 9.5 mm Hg, MAS 1.5 vs. SBP 14.3 mm Hg, DBP 6.4 mm Hg, MAS 1.3), while between group comparisons showed no significant differences across all variables. The adjusted mean difference for mean SBP was 4.74 (95% confidence interval [CI], -0.65 to 10.13 mm Hg; P=0.084), mean DBP was 1.41 (95% CI, -2.01 to 4.82 mm Hg; P=0.415), and mean MAS was 0.05 (95% CI, -0.29 to 0.40 mm Hg; P=0.768).
CONCLUSION: Short-term home blood pressure monitoring significantly reduced office blood pressure and improved medication adherence, albeit similarly to standard care.
Methods: A multi-center cross sectional study was conducted for a month in out-patient wards of hospitals in Khobar, Dammam, Makkah, and Madinah, Saudi Arabia. Patients were randomly selected from a registered patient pools at hospitals and the item-subject ratio was kept at 1:20. The tool was assessed for factorial, construct, convergent, known group and predictive validities as well as, reliability and internal consistency of scale were also evaluated. Sensitivity, specificity, and accuracy were also evaluated. Data were analyzed using SPSS v24 and MedCalc v19.2. The study was approved by concerned ethics committees (IRB-129-25/6/1439) and (IRB-2019-05-002).
Results: A total of 282 responses were received. The values for normed fit index (NFI), comparative fit index (CFI), Tucker Lewis index (TLI) and incremental fit index (IFI) were 0.960, 0.979, 0.954 and 0.980. All values were >0.95. The value for root mean square error of approximation (RMSEA) was 0.059, i.e., <0.06. Hence, factorial validity was established. The average factor loading of the scale was 0.725, i.e., >0.7, that established convergent validity. Known group validity was established by obtaining significant p-value <0.05, for the associations based on hypotheses. Cronbach's α was 0.865, i.e., >0.7. Predictive validity was established by evaluating odds ratios (OR) of demographic factors with adherence score using logistic regression. Sensitivity was 78.16%, specificity was 76.85% and, accuracy of the tool was 77.66%, i.e., >70%.
Conclusion: The Arabic version of GMAS achieved all required statistical parameters and was validated in Saudi patients with chronic diseases.
Purpose: To determine the level of adherence to opioid analgesics in patients with cancer pain and to identify factors that may influence the adherence.
Patient and Methods: This was a cross-sectional study conducted from March to June 2018 at two tertiary care hospitals in Malaysia. Study instruments consisted of a set of validated questionnaires; the Medication Compliance Questionnaire, Brief Pain Inventory and Pain Opioid Analgesic Beliefs─Cancer scale.
Results: A total of 134 patients participated in this study. The patients' adherence scores ranged from 52-100%. Factors with a moderate, statistically significant negative correlation with adherence were negative effect beliefs (rs= -0.53, p<0.001), pain endurance beliefs (rs = -0.49, p<0.001) and the use of aqueous morphine (rs = -0.26, p=0.002). A multiple linear regression model on these predictors resulted in a final model which accounted for 47.0% of the total variance in adherence (R2 = 0.47, F (7, 126) = 15.75, p<0.001). After controlling for other variables, negative effect beliefs were the strongest contributor to the model (β = -0.39, p<0.001) and uniquely explained 12.3% of the total variance.
Conclusion: The overall adherence to opioid analgesics among Malaysian patients with cancer pain was good. Negative effects beliefs regarding cancer pain and opioids strongly predicted adherence.
METHODS: This prospective study was conducted among the caregivers of 443 child TB patients registered during the study. Caregivers of children were queried using a structured questionnaire consisting of sociodemographic and socio-economic factors and the role of healthcare workers during the treatment course. Risk factors for non-adherence were estimated using a logistic regression model.
RESULTS: In multivariate analysis, the independent variables that had a statistically significant positive association with non-adherence were male sex (adjusted odds ratio [AOR] 5.870 [95% confidence interval {CI} 1.99 to 17.29]), age ≥45 y (AOR 5.627 [95% CI 1.88 to 16.82]), caregivers with no formal education (AOR 3.905 [95% CI 1.29 to 11.79]), financial barriers (AOR 30.297 [95% CI 6.13 to 149.54]), insufficient counselling by healthcare workers (AOR 5.319 [95% CI 1.62 to 17.42]), insufficient counselling by health professionals (AOR 4.117 [95% CI 1.05 to 16.05]) and unfriendly attitude and poor support from healthcare professionals (AOR 11.150 [95% CI 1.91 to 65.10]).
CONCLUSIONS: Treatment adherence in the present study was 86% using the Morisky Green Levine Medication Adherence Scale and 90.7% using the visual analogue scale tool. Predictors of non-adherence need to be a focus and caregivers should be given complete knowledge about the importance of adherence to TB treatment.