OBJECTIVE: To examine ethnic differences in participation in medical check-ups among the elderly.
DESIGN: A nationally representative data set was employed. Multiple logistic regressions were utilised to examine the relationship between ethnicity and the likelihood of undergoing medical check-ups. The regressions were stratified by age, income, marital status, gender, household location, insurance access and health status. These variables were also controlled for in the regressions (including stratified regressions).
PARTICIPANTS: The respondents were required to be residents of Malaysia and not be institutionalised. Overall, 30,806 individuals were selected to be interviewed, but only 28,650 were actually interviewed, equivalent to a 93% response rate. Of those, only 2248 were used in the analyses, because 26,402 were others or below aged 60.
MAIN MEASURES: The dependent variable was participation in a medical check-up. The main independent variables were the three major ethnic groups in Malaysia (Malay, Chinese, Indian).
KEY RESULTS: Among the elderly aged 70-79 years, Chinese (aOR 1.89; 95% CI 1.28, 2.81) and Indians (aOR 2.39; 95% CI 1.20, 4.74) were more likely to undergo medical check-ups than Malays. Among the elderly with monthly incomes of ≤ RM999, Chinese (aOR 1.44; 95% CI 1.12, 1.85) and Indians (aOR 1.50; 95% CI 0.99, 2.28) were more likely to undergo medical check-ups than Malays. Indian males were more likely to undergo medical check-ups than Malay males (aOR 2.32; 95% CI 1.15, 4.67). Chinese with hypercholesterolaemia (aOR 1.45; 95% CI 1.07, 1.98) and hypertension (aOR 1.32; 95% CI 1.02, 1.72) were more likely to undergo medical check-ups than Malays.
CONCLUSIONS: There were ethnic differences in participation in medical check-ups among the elderly. These ethnic differences varied across age, income, marital status, gender, household location, insurance access and health status.
METHODS: A systematic search was conducted in four databases from inception until April 30, 2021 as well as search of citation of included articles. Studies that reported patients' and/or their caregivers' attitude towards deprescribing quantitatively were included. All studies were independently screened, reviewed, and data extracted in duplicates. Patients and caregivers willingness to deprescribe their regular medication was pooled using random effects meta-analysis of proportions.
RESULTS: Twenty-nine unique studies involving 11,049 participants were included. All studies focused on the attitude of the patients towards deprescribing, and 7 studies included caregivers' perspective. Overall, 87.6% (95% CI: 83.3 to 91.4%) patients were willing to deprescribe their medication, based upon the doctors' suggestions. This was lower among caregivers, with only 74.8% (49.8% to 93.8%) willing to deprescribe their care recipients' medications. Patients' or caregivers' willingness to deprescribe were not influenced by study location, study population, or the number of medications they took.
DISCUSSION: Most patients and their caregivers were willing to deprescribe their medications, whenever possible and thus should be offered a trial of deprescribing. Nevertheless, as these tools have a poor predictive ability, patients and their caregivers should be engaged during the deprescribing process to ensure that the values and opinions are heard, which would ultimately improve patient safety. In terms of limitation, as not all studies may published the methods and results of measurement they used, this may impact the methodological quality and thus our findings. OPEN SCIENCE FRAMEWORK REGISTRATION: https:// osf.io/fhg94.
OBJECTIVE: This study aims to evaluate the effects of remote telemonitoring with team-based management on people with uncontrolled type 2 diabetes.
DESIGN: This was a pragmatic 52-week cluster-randomized controlled study among 11 primary care government practices in Malaysia.
PARTICIPANTS: People with type 2 diabetes aged 18 and above, who had hemoglobin A1c ≥ 7.5% but less than 11.0% within the past 3 months and resided in the state of Selangor.
INTERVENTION: The intervention group received home gluco-telemonitors and transmitted glucose data to a care team who could adjust therapy accordingly. The team also facilitated self-management by supporting participants to improve medication adherence, and encourage healthier lifestyle and use of resources to reduce risk factors. Usual care group received routine healthcare service.
MAIN MEASURE: The primary outcome was the change in HbA1c at 24 weeks and 52 weeks. Secondary outcomes included change in fasting plasma glucose, blood pressure, lipid levels, health-related quality of life, and diabetes self-efficacy.
RESULTS: A total of 240 participants were recruited in this study. The telemonitoring group reported larger improvements in glycemic control compared with control at the end of study (week 24, - 0.05%; 95% CI - 0.10 to 0.00%) and at follow-up (week 52, - 0.03%; - 0.07 to 0.02%, p = 0.226). Similarly, no differences in other secondary outcomes were observed, including the number of adverse events and health-related quality of life.
CONCLUSION: This study indicates that there is limited benefit of replacing telemedicine with the current practice of self-monitoring of blood glucose. Further innovative methods to improve patient engagement in diabetes care are needed.
TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02466880.