PATIENTS AND METHODS: A retrospective cohort study was conducted at a tertiary care hospital in Malaysia from 1st January to 21st May 2019. Seventy admissions for COPD exacerbation involving 58 patients were analyzed.
RESULTS: The majority of the patients were male (89.8%), had a mean age of 71.95 ± 7.24 years and a median smoking history of 40 (IQR = 25) pack-years, 84.5% were in GOLD group D and 91.4% had a mMRC grading of 2 or greater. Approximately 60.3% had upper or lower respiratory tract infection as the cause of exacerbation; one in five patients had uncompensated hypercapnic respiratory failure at presentation, and 27.6% needed mechanical ventilatory support. Approximately 43.1% of patients had a history of exacerbation that required hospitalisation in the past year. The mean blood eosinophil concentration was 0.38 ± 0.46 x109 cells/L. The 30-day readmission rate was 20.3%, revisit rate to the emergency room within 30 days after discharge was 3.4%, and in-hospital mortality rate was 1.7%. Among all characteristics, a higher baseline mMRC grade (p = 0.038) and history of exacerbation in the past 1 year (p < 0.001) were statistically associated with 30-day readmission.
CONCLUSION: The 30-day readmission rate for COPD exacerbation in a Malaysian tertiary hospital is similar to the rates in high-income countries. Exacerbation in the previous year and a higher baseline mMRC grading were significant risk factors for 30-day readmission in patients with COPD. Strategies of COPD management should concentrate on improvement of symptoms control by optimisation of pharmacotherapy, and early initiation of pulmonary rehabilitation, and structured integrated care programs to reduce readmission rates.
METHODS: We recruited eligible adults from the Klang Asthma Cohort registry in primary care for a 3-month mixed-method study plus a 2-month extended observation. We collected baseline data on socio-demography, health literacy and asthma control level. The outcomes of the intervention were assessed at 1- and 3-month: i) adoption (app download and usage), ii) adherence (app usage), iii) retention (app usage in the observation period), iv) health outcomes (e.g., severe asthma attacks) and v) process outcomes (e.g., ownership and use of action plans). At 1-month, participants were purposively sampled for in-depth interviews, which were audio-recorded, transcribed verbatim, and analysed deductively.
RESULTS: We recruited 48 participants; 35 participants (23 Female; median age = 43 years; median HLS score = 28) completed the 3 months study. Of these, 14 participants (10 Female; median age = 48 years; median HLS score = 28) provided interviews. Thirty-seven (77%) participants adopted the app (downloaded and used it in the first month of the study). The main factor reported as influencing adoption was the ease of using the app. A total of 950 app usage were captured during the 3-month feasibility study. App usage increased gradually, peaking at month 2 (355 total log-ins) accounting for 78% of users. In month 5, 51.4% of the participants used the app at least once. The main factors influencing continued use included adherence features (e.g., prompts and reminders), familiarity with app function and support from family members.
CONCLUSIONS: An asthma self-management app intervention was acceptable for adults with limited health literacy and it was feasible to collect the desired outcomes at different time points during the study. A future trial is warranted to estimate the clinical and cost-effectiveness of the intervention and to explore implementation strategies.
METHODS: A systematic search was conducted through Pubmed, CINAHL, EMBASE and Cochrane Central Register of Controlled Trials. Additional articles were located through cross-checking of the references list and bibliography citations of the included studies and previous review papers. We included intervention studies with controlled or baseline comparison groups that were conducted in primary care practices or the community, targeted at adult populations (randomized controlled trials, non-randomized trials with controlled groups and pre- and post-intervention studies). The interventions were targeted either at individuals, communities, health care professionals or the health-care system. The main outcome of interest was the relative risk (RR) of screening uptake rates due to the intervention.
RESULTS: We included 21 studies in the meta-analysis. The risk of bias for randomization was low to medium in the randomized controlled trials, except for one, and high in the non-randomized trials. Two analyses were performed; optimistic (using the highest effect sizes) and pessimistic (using the lowest effect sizes). Overall, interventions were shown to increase the uptake of screening for CVD risk factors (RR 1.443; 95% CI 1.264 to 1.648 for pessimistic analysis and RR 1.680; 95% CI 1.420 to 1.988 for optimistic analysis). Effective interventions that increased screening participation included: use of physician reminders (RR ranged between 1.392; 95% CI 1.192 to 1.625, and 1.471; 95% CI 1.304 to 1.660), use of dedicated personnel (RR ranged between 1.510; 95% CI 1.014 to 2.247, and 2.536; 95% CI 1.297 to 4.960) and provision of financial incentives for screening (RR 1.462; 95% CI 1.068 to 2.000). Meta-regression analysis showed that the effect of CVD risk factors screening uptake was not associated with study design, types of population nor types of interventions.
CONCLUSIONS: Interventions using physician reminders, using dedicated personnel to deliver screening, and provision of financial incentives were found to be effective in increasing CVD risk factors screening uptake.