ABSTRACT
The ultimate purpose of diabetes care is achieving the outcomes that patients regard as important throughout the life course. Despite advances in pharmaceuticals, nutraceuticals, psychoeducational programs, information technologies, and digital health, the levels of treatment target achievement in people with diabetes mellitus (DM) have remained suboptimal. This clinical care of people with DM is highly challenging, complex, costly, and confounded for patients, physicians, and healthcare systems. One key underlying problem is clinical inertia in general and therapeutic inertia (TI) in particular. TI refers to healthcare providers’ failure to modify therapy appropriately when treatment goals are not met. TI therefore relates to the prescribing decisions made by healthcare professionals, such as doctors, nurses, and pharmacists. The known causes of TI include factors at the level of the physician (50%), patient (30%), and health system (20%). Although TI is often multifactorial, the literature suggests that 28% of strategies are targeted at multiple levels of causes, 38% at the patient level, 26% at the healthcare professional level, and only 8% at the healthcare system level. The most effective interventions against TI are shorter intervals until revisit appointments and empowering nurses, diabetes educators, and pharmacists to review treatments and modify prescriptions.
ABSTRACT
Purpose@#This study aims to explore the expectations and acceptability of a smart nursing home model among Chinese older adults and their family members based on a scoping review that defines the concept of smart nursing homes. @*Methods@#A qualitative case study was employed for this research. Semi-structured, in-depth interviews and focus group discussions were conducted on WeChat. Participants were purposively sampled through snowball sampling in Hainan and Dalian, China. A total of 28 older adults aged 60–75 and six adult children were interviewed until data saturation was achieved, followed by a thematic analysis. @*Results@#The expectations of smart nursing homes include: 1) quality of care supported by governments and societies; 2) smart technology applications; 3) the presence of a skilled healthcare professional team; 4) access to and scope of basic medical services; and 5) integration of medical services. The acceptability of smart nursing homes included factors such as stakeholders’ perceived efficaciousness, usability, and collateral damages of using smart technologies, and the coping process of adoption was influenced by factors such as age, economic status, health status, education, and openness to smart technologies among older adults. @*Conclusions@#Chinese older adults and their family members have a positive perception of the smart nursing home model. The qualitative evidence regarding their expectations and acceptability of smart nursing homes contributes valuable insights for a wide range of stakeholders involved in the planning and implementation of smart nursing homes.
ABSTRACT
<p><b>INTRODUCTION</b>We assessed the predictors of poor glycaemic control among older patients with type 2 diabetes mellitus (T2DM) in Malaysia.</p><p><b>METHODS</b>This cross-sectional study used the data of 21,336 patients aged ≥ 60 years with T2DM from the Adult Diabetes Control and Management Registry 2008-2009.</p><p><b>RESULTS</b>Predictors of poor glycaemic control were: age groups 60-69 years (odds ratio [OR] 1.96, 95% confidence interval [CI] 1.66-2.33) and 70-79 years (OR 1.43, 95% CI 1.20-1.71); Malay (OR 1.53, 95% CI 1.41-1.66) and Indian (OR 1.32, 95% CI 1.19-1.46) ethnicities; T2DM durations of 5-10 years (OR 1.46, 95% CI 1.35-1.58) and > 10 years (OR 1.75, 95% CI 1.59-1.91); the use of oral antidiabetic agents only (OR 5.86, 95% CI 3.32-10.34), insulin only (OR 17.93, 95% CI 9.91-32.43), and oral antidiabetic agents and insulin (OR 29.42, 95% CI 16.47-52.53); and elevated blood pressure (OR 1.10, 95% CI 1.01-1.20), low-density lipoprotein cholesterol (OR 1.48, 95% CI 1.38-1.59) and triglycerides (OR 1.61, 95% CI 1.51-1.73). Hypertension (OR 0.71, 95% CI 0.64-0.80), hypertension and dyslipidaemia (OR 0.68, 95% CI 0.61-0.75), pre-obesity (OR 0.89, 95% CI 0.82-0.98) and obesity (OR 0.76, 95% CI 0.70-0.84) were less likely to be associated with poor glycaemic control.</p><p><b>CONCLUSION</b>Young-old and middle-old age groups (i.e. < 80 years), Malay and Indian ethnicities, longer T2DM duration, the use of pharmacological agents, and elevated blood pressure and lipid levels were associated with poor glycaemic control. The presence of comorbidities, pre-obesity and obesity were less likely to be associated with poor glycaemic control.</p>