Trends in all-cause mortality among adults with diagnosed type 2 diabetes in West Malaysia: 2010 - 2019.

AIMS: We determined 10-year all-cause mortality trends in diagnosed type 2 diabetes (T2D) population in West Malaysia, a middle-income country in the Western-Pacific region. METHODS: One million T2D people aged 40-79 registered in the National Diabetes Registry (2009-2018) were linked to death records (censored on 31 December 2019). Standardized absolute mortality rates and standardized mortality ratios (SMRs) were estimated relative to the Malaysian general population, and standardized to the 2019 registry population with respect to sex, age group, and disease duration. RESULTS: Overall all-cause standardized mortality rates were unchanged in both sexes. Rates increased in males aged 40-49 (annual average percent change [AAPC]: 2.46 % [95 % CI 0.42 %, 4.55 %]) and 50-59 (AAPC: 1.91 % [95 % CI 0.73 %, 3.10 %]), and females aged 40-49 (AAPC: 3.39 % [95 % CI 1.32 %, 5.50 %]). In both sexes, rates increased among those with 1) > 15 years disease duration, 2) prior cardiovascular disease, and 3) Bumiputera (Malay/native) ethnicity. The overall SMR was 1.83 (95 % CI 1.80, 1.86) for males and 1.85 (95 % CI 1.82, 1.89) for females, being higher in younger age groups and showed an increasing trend in those with either > 15 years disease duration or prior cardiovascular disease. CONCLUSIONS: Mortality trends worsened in certain T2D population in Malaysia.

Prevalence, predictors and reasons for COVID-19 vaccine hesitancy: Results of a global online survey.

Vaccine hesitancy has the potential to cripple efforts to end the COVID-19 pandemic. Policy makers need to be informed about the scale, nature and drivers of this problem, both domestically and globally, so that effective interventions can be designed. To this end, we conducted a statistical analysis of data from the CANDOUR survey (n = 15,536), which was carried out in 13 countries representing approximately half of the global population. Both pooled and country-level ordered regression models were estimated to identify predictors of vaccine hesitancy and reasons for not getting vaccinated. We found high levels of hesitancy, particularly in high-income countries. Factors driving moderate hesitancy differed from those driving extreme hesitancy. A lack of trust in health care providers was consistently the underlying driver of more extreme hesitancy. Predictors of moderate hesitancy varied across countries, though being younger and female was typically associated with greater hesitancy. While political ideology played a role in vaccine hesitancy in some countries, this effect was often moderated by income level, particularly in the US. Overall, the results suggest that different interventions such as mass-media campaigns and monetary incentives may be needed to target the moderately versus extremely hesitant. The lack of trust in health care professionals that drives extreme hesitancy may reflect deep societal mistrust in science and institutions and be challenging to overcome.

The COVID-19 pandemic and health-related quality of life across 13 high- and low-middle-income countries: A cross-sectional analysis.

BACKGROUND: Most research on the Coronavirus Disease 2019 (COVID-19) health burden has focused on confirmed cases and deaths, rather than consequences for the general population's health-related quality of life (HRQoL). It is also important to consider HRQoL to better understand the potential multifaceted implications of the COVID-19 pandemic in various international contexts. This study aimed to assess the association between the COVID-19 pandemic and changes in HRQoL in 13 diverse countries. METHODS AND FINDINGS: Adults (18+ years) were surveyed online (24 November to 17 December 2020) in 13 countries spanning 6 continents. Our cross-sectional study used descriptive and regression-based analyses (age adjusted and stratified by gender) to assess the association between the pandemic and changes in the general population's HRQoL, measured by the EQ-5D-5L instrument and its domains (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), and how overall health deterioration was associated with individual-level (socioeconomic, clinical, and experiences of COVID-19) and national-level (pandemic severity, government responsiveness, and effectiveness) factors. We also produced country-level quality-adjusted life years (QALYs) associated to COVID-19 pandemic-related morbidity. We found that overall health deteriorated, on average across countries, for more than one-third of the 15,480 participants, mostly in the anxiety/depression health domain, especially for younger people (<35 years old) and females/other gender. This translated overall into a 0.066 mean "loss" (95% CI: -0.075, -0.057; p-value < 0.001) in the EQ-5D-5L index, representing a reduction of 8% in overall HRQoL. QALYs lost associated with morbidity were 5 to 11 times greater than QALYs lost based on COVID-19 premature mortality. A limitation of the study is that participants were asked to complete the prepandemic health questionnaire retrospectively, meaning responses may be subject to recall bias. CONCLUSIONS: In this study, we observed that the COVID-19 pandemic was associated with a reduction in perceived HRQoL globally, especially with respect to the anxiety/depression health domain and among younger people. The COVID-19 health burden would therefore be substantially underestimated if based only on mortality. HRQoL measures are important to fully capture morbidity from the pandemic in the general population.

A systematic review: Cost-effectiveness of continuous glucose monitoring compared to self-monitoring of blood glucose in type 1 diabetes.

Continuous glucose monitoring (CGM) is rapidly becoming a vital tool in the management of type 1 diabetes. Its use has been shown to improve glycaemic management and reduce the risk of hypoglycaemic events. The cost of CGM remains a barrier to its widespread application. We aimed to identify and synthesize evidence about the cost-effectiveness of utilizing CGM in patients with type 1 diabetes. Studies were identified from MEDLINE, Embase and Cochrane Library from January 2010 to February 2022. Those that assessed the cost-effectiveness of CGM compared to self-monitored blood glucose (SMBG) in patients with type 1 diabetes and reported lifetime incremental cost-effectiveness ratio (ICER) were included. Studies on critically ill or pregnant patients were excluded. Nineteen studies were identified. Most studies compared continuous subcutaneous insulin infusion and SMBG to a sensor-augmented pump (SAP). The estimated ICER range was [$18,734-$99,941] and the quality-adjusted life year (QALY) gain range was [0.76-2.99]. Use in patients with suboptimal management or greater hypoglycaemic risk revealed more homogenous results and lower ICERs. Limited studies assessed CGM in the context of multiple daily injections (MDI) (n = 4), MDI and SMBG versus SAP (n = 2) and three studies included hybrid closed-loop systems. Most studies (n = 17) concluded that CGM is a cost-effective tool. This systematic review suggests that CGM appears to be a cost-effective tool for individuals with type 1 diabetes. Cost-effectiveness is driven by reducing short- and long-term complications. Use in patients with suboptimal management or at risk of severe hypoglycaemia is most cost-effective.

Malaysian public preferences and decision making for COVID-19 vaccination: A discrete choice experiment.

Background: Low vaccine uptake has the potential to seriously undermine COVID-19 vaccination programs, as very high coverage levels are likely to be needed for virus suppression to return life to normal. We aimed to determine the influence of vaccine attributes (including access costs) on COVID-19 vaccination preferences among the Malaysian public to improve national uptake. Methods: An online Discrete Choice Experiment (DCE) was conducted on a representative sample of 2028 Malaysians. Respondents were asked to make vaccination decisions in a series of hypothetical scenarios. A nested, mixed logit model was used to estimate the preferences for vaccination over vaccine refusal and for how those preferences varied between different sub-populations. The attributes were the risk of developing severe side effects of the vaccine, vaccine effectiveness, vaccine content, vaccination schedule, and distance from home to vaccination centre. Findings: Reported public uptake of COVID-19 vaccination was primarily influenced by the risk of developing severe side effects (b = -1·747, 95% CI = -2·269, -1·225), vaccine effectiveness (b = 3·061, 95% CI = 2·628, 3·494) and its Halal status (b = 3·722, 95% CI = 3·152, 4·292). Other factors such as appointment timing and travel distance to the vaccination centre also had an effect on vaccine uptake. There was substantial heterogeneity in preferences between different populations, particularly for age groups, ethnicity, regions, and underlying health conditions. Interpretation: Perceived effectiveness and side effects are likely to affect COVID-19 vaccine uptake in Malaysia. Halal content is critical to Malays' vaccination choices. Reducing the physical distance to vaccination centres, particularly in rural areas where uptake is lower, is likely to improve uptake. Funding: Ministry of Health Research Grant from the Malaysian government [NIH/800-3/2/1 Jld.7(46), grant reference no: 57377 and warrant no: 91000776].

The comparative mortality of an elite group in the long run of history: an observational analysis of politicians from 11 countries.

This study aims to compare the mortality rate and life expectancy of politicians with those of the age and gender-matched general populations. This was an observational analysis of mortality rates of politicians (i.e. members of national parliaments with available data on dates of birth, death and election, gender, and life tables) in 11 developed countries. Politicians were followed from date of first election until either death or the last available year with life table data. Relative mortality differences were estimated using standardised mortality ratios (SMRs). Absolute inequalities were quantified as the difference in survival by deducting a population's remaining life expectancy from politicians' remaining life expectancy at age 45, estimated using Gompertz parametric proportional hazards models. We included 57,561 politicians (with follow-up ranging from 1816-2016 for France to 1949-2017 for Germany). In almost all countries politicians had similar rates of mortality to the general population in the early part of the twentieth century. Relative mortality and survival differences (favouring politicians) increased considerably over the course of the twentieth century, with recent SMRs ranging from 0.45 (95%CI 0.41-0.50) in Italy to 0.82 (95%CI 0.69-0.95) in New Zealand. The peak life expectancy gaps ranged from 4.4 (95% CI, 3.5-5.4) years in the Netherlands to 7.8 (95% CI, 7.2-8.4) years in the US. Our results show large relative and absolute inequalities favouring politicians in every country. In some countries, such as the US, relative inequalities are at the greatest level in over 150 years.

Eliciting risk preferences that predict risky health behavior: A comparison of two approaches.

Information on attitudes to risk could increase understanding of and explain risky health behaviors. We investigate two approaches to eliciting risk preferences in the health domain, a novel "indirect" lottery elicitation approach with health states as outcomes and a "direct" approach where respondents are asked directly about their willingness to take risks. We compare the ability of the two approaches to predict health-related risky behaviors in a general adult population. We also investigate a potential framing effect in the indirect lottery elicitation approach. We find that risk preferences elicited using the direct approach can better predict health-related risky behavior than those elicited using the indirect approach. Moreover, a seemingly innocuous change to the framing of the lottery question results in significantly different risk preference estimates, and conflicting conclusions about the ability of the indicators to predict risky health behaviors.

The Value of Genomic Testing: A Contingent Valuation Across Six Child- and Adult-Onset Genetic Conditions.

OBJECTIVES: The aim of this study was to elicit the willingness-to-pay (WTP) for genomic testing, using contingent valuation, among people with lived experience of genetic conditions in Australia. METHODS: Parents of children with suspected mitochondrial disorders, epileptic encephalopathy, leukodystrophy, or malformations of cortical development completed a dynamic triple-bounded dichotomous choice (DC) contingent valuation. Adult patients or parents of children with suspected genetic kidney disease or complex neurological and neurodegenerative conditions completed a payment card (PC) contingent valuation. DC data were analyzed using a multilevel interval regression and a multilevel probit model. PC data were analyzed using a Heckman selection model. RESULTS: In total, 360 individuals participated in the contingent valuation (CV), with 141 (39%) and 219 (61%) completing the DC and PC questions, respectively. The mean WTP for genomic testing was estimated at AU$2830 (95% confidence interval [CI] 2236-3424) based on the DC data and AU$1914 (95% CI 1532-2296) based on the PC data. The mean WTP across the six cohorts ranged from AU$1879 (genetic kidney disease) to AU$4554 (leukodystrophy). CONCLUSIONS: Genomic testing is highly valued by people experiencing rare genetic conditions. Our findings can inform cost-benefit analyses and the prioritization of genomics into mainstream clinical care. While our WTP estimates for adult-onset genetic conditions aligned with estimates derived from discrete choice experiments (DCEs), for childhood-onset conditions our estimates were significantly lower. Research is urgently required to directly compare, and critically evaluate, the performance of CV and DCE methods.

Is There Broad-Based Support in High-Income Countries for COVID-19 Vaccine Donation? Evidence from Seven Countries.

BACKGROUND: Many high-income countries (HICs) have now vaccinated a substantial proportion of their population against COVID-19. Many low-income countries (LICs) may need to wait until at least 2022 before even the most vulnerable 20% of their populations are vaccinated. Beyond ethical considerations, some redistribution of doses would reduce the risk of the emergence and spread of new variants and benefit the economy, both globally and in donor countries. However, the willingness of HIC governments to donate vaccine doses is likely to depend on public support. While previous work has indicated strong average levels of public support in HIC for donation, little is known about how broad-based this support is. OBJECTIVE: To investigate the extent to which support for donation holds across both pre-specified and exploratory subgroups. METHODS: From 24 November-28 December 2020 we conducted an online survey of 8209 members of the general public in seven HIC (Australia, Canada, France, Italy, Spain, UK and USA). We conducted tests of proportions and used Bayesian ordinal logistic regression models to assess the extent of support for donation across population subgroups. RESULTS: We found broad-based support for donations in terms of age, gender, socio-economic status and political ideology. We found no strong evidence that support for donations was higher among those with greater income or a university education. Support for donation among those on the political right and centre was lower than on the left, but 51% (95% confidence interval 48-53%) of respondents who identified with the right supported some level of donation. Those in the more altruistic half of the sample (as captured by willingness to donate money to a good cause) were more likely to support donation than those who were not, but around half of the less altruistic group supported some level of donation. CONCLUSION: There is broad-based support for policymakers in HICs to donate some of their countries' COVID-19 vaccine doses for distribution to LICs.

Citizens from 13 countries share similar preferences for COVID-19 vaccine allocation priorities.

How does the public want a COVID-19 vaccine to be allocated? We conducted a conjoint experiment asking 15,536 adults in 13 countries to evaluate 248,576 profiles of potential vaccine recipients who varied randomly on five attributes. Our sample includes diverse countries from all continents. The results suggest that in addition to giving priority to health workers and to those at high risk, the public favors giving priority to a broad range of key workers and to those with lower income. These preferences are similar across respondents of different education levels, incomes, and political ideologies, as well as across most surveyed countries. The public favored COVID-19 vaccines being allocated solely via government programs but were highly polarized in some developed countries on whether taking a vaccine should be mandatory. There is a consensus among the public on many aspects of COVID-19 vaccination, which needs to be taken into account when developing and communicating rollout strategies.

Meal-time glycaemia in adults with type 1 diabetes using multiple daily injections vs insulin pump therapy following carbohydrate-counting education and bolus calculator provision.

AIMS: To compare meal-time glycaemia in adults with type 1 diabetes mellitus (T1D) managed with multiple daily injections (MDI) vs. insulin pump therapy (IPT), using self-monitoring blood glucose (SMBG), following diabetes education. METHODS: Adults with T1D received carbohydrate-counting education and a bolus calculator: MDI (Roche Aviva Expert) and IPT (pump bolus calculator). All then wore 3-weeks of masked-CGM (Enlite, Medtronic). Meal-times were assessed by two approaches: 1) Set time-blocks (breakfast 06:00-10:00hrs; lunch 11:00-15:00hrs; dinner 17:00-21:00hrs) and 2) Bolus-calculator carbohydrate entries signalling meal commencement. Post-meal masked-CGM time-in-range (TIR) 3.9-10.0 mmol/L was the primary outcome. RESULTS: MDI(n = 61) and IPT (n = 59) participants were equivalent in age, sex, diabetes duration and HbA1c. Median (IQR) education time provided did not differ (MDI: 1.1 h (0.75, 1.5) vs. IPT: 1.1 h (1.0, 2.0); p = 0.86). Overall, daytime (06:00-24:00hrs), lunch and dinner TIR did not differ for MDI vs. IPT participants but was greater for breakfast with IPT in both analyses with a mean difference of 12.8%, (95 CI 4.8, 20.9); p = 0.002 (time-block analysis). CONCLUSION: After diabetes education, MDI and IPT use were associated with similar day-time glycemia, though IPT users had significantly greater TIR during the breakfast period. With education, meal-time glucose levels are comparable with use of MDI vs. pumps.

Development of a life expectancy table for individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes; however, there is currently no published equivalent for individuals with type 1 diabetes. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes. METHODS: The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. The following six important risk factors were included in the life table: sex; age; current smoking status; BMI; eGFR; and HbA1c. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort. RESULTS: There was a substantial variation in life expectancy across patients with different risk factor levels. Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0-53.9 years). The variation in life expectancy was a function of the combination of risk factor values, with HbA1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. Individuals with the lowest level (20 kg/m2) and highest level of BMI (35 kg/m2) had a lower life expectancy compared with those with a BMI of 25 kg/m2. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors. CONCLUSIONS/INTERPRETATION: The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. The table allows for rapid communications of risk in an easily understood format between healthcare professionals, health economists, researchers, policy makers and patients. Particularly, it supports clinicians in their discussion with patients about the benefits of improving risk factors.

The effects of self-assessed health: Dealing with and understanding misclassification bias.

Self-assessed health (SAH) is often used in health econometric models as the key explanatory variable or as a control variable. However, there is evidence questioning its test-retest reliability, with up to 30% of individuals changing their response. Building on recent advances in the econometrics of misclassification, we develop a way to consistently estimate and account for misclassification in reported SAH by using data from a large representative longitudinal survey where SAH was elicited twice. From this we gain new insights into the nature of SAH misclassification and its potential for biasing health econometric estimates. The results from applying our approach to nonlinear models of long-term mortality and chronic morbidities reveal that there is substantial heterogeneity in misclassification patterns. We find that adjusting for misclassification is important for estimating the impact of SAH. For other explanatory variables of interest, we find significant but generally small changes to their estimates when SAH misclassification is ignored.

Population norms for quality adjusted life years for the United States of America, China, the United Kingdom and Australia.

Health economics uses quality adjusted life years (QALYs) to help healthcare decision makers. However, unlike life expectancy for which age- and sex-dependent national life tables are available, no general population norms exist to use as a benchmark against which to compare observed or modeled projections of QALYs in sub-populations or patients. We developed a 2-state Markov model to generate QALY population norms for the USA, UK, China and Australia. Annual age- and sex-specific probabilities of all-cause mortality were taken from life tables combined with general population country-specific age- and sex-specific health state utilities for the EQ-5D-3L (all countries); and SF-6D (Australia) multi-attribute utility instruments (MAUI). To validate our QALY benchmark model we found that the model closely predicted population life expectancies. Using EQ-5D-3L, undiscounted QALYs for males/females aged 18 years ranged 54.62/58.90 (USA), 55.55/60.21 (China), 57.11/60.16 (Australia), and 58.01/61.43 (UK) years. SF-6D benchmark QALYs for Australia were consistently lower than those generated from the EQ-5D-3L. The gap in undiscounted QALYs between the UK (highest) and the USA (lowest) was 2.53 QALYs in women and 3.39 QALYs in men aged 18 years. Our model's QALY population norms can be used for internal validation of future health economic models for the country-specific value sets for the instruments that we adopted, and when quantifying burden of disease in terms of QALYs lost due to illness compared to the general population. We have created a publicly available repository to continuously include QALY benchmarks that use country-specific value sets for other MAUIs and life expectancies.

Lessons from the pandemic on the value of research infrastructure.

The COVID-19 pandemic has shed a spotlight on the resilience of healthcare systems, and their ability to cope efficiently and effectively with unexpected crises. If we are to learn one economic lesson from the pandemic, arguably it is the perils of an overfocus on short-term allocative efficiency at the price of lack of capacity to deal with uncertain future challenges. In normal times, building spare capacity with 'option value' into health systems may seem inefficient, the costs potentially exceeding the benefits. Yet the fatal weakness of not doing so is that this can leave health systems highly constrained when dealing with unexpected, but ultimately inevitable, shocks-such as the COVID-19 pandemic. In this article, we argue that the pandemic has highlighted the potentially enormous option value of biomedical research infrastructure. We illustrate this with reference to COVID-19 response work supported by the United Kingdom National Institute for Health Research Oxford Biomedical Research Centre. As the world deals with the fallout from the most serious economic crisis since the Great Depression, pressure will soon come to review government expenditure, including research funding. Developing a framework to fully account for option value, and understanding the public appetite to pay for it, should allow us to be better prepared for the next emerging problem.

Impact of Comorbid Conditions on Healthcare Expenditure and Work-related Outcomes in Patients With Rheumatoid Arthritis.

OBJECTIVE: To evaluate the effect of comorbid conditions on direct healthcare expenditure and work-related outcomes in patients with rheumatoid arthritis (RA). METHODS: This is a retrospective analysis of the Medical Expenditure Panel Survey from 2006 to 2015 in 4967 adults with RA in the United States. Generalized linear models were used for healthcare expenditure and income, logistic models for employment status, and zero-inflated negative binomial models for absenteeism. Thirteen comorbid conditions were included as potential predictors of direct cost- and work-related outcomes. The models were adjusted for sociodemographic factors including sex, age, region, marital status, race/ethnicity, income, education, and smoking status. RESULTS: Patients with RA with heart failure (HF) had the highest incremental annual healthcare expenditure (US$8205, 95% CI $3683-$12,726) compared to those without the condition. Many comorbid conditions including hypertension (HTN), diabetes, depression, chronic obstructive pulmonary disease, cancer, stroke, and HF reduced the chance of patients with RA aged between 18-64 years being employed. Absenteeism of employed patients with RA was significantly affected by HTN, depression, disorders of the eye and adnexa, or stroke. On average, RA patients with HF earned US$15,833 (95% CI $4435-$27,231) per year less than RA patients without HF. CONCLUSION: Comorbid conditions in patients with RA were associated with higher annual healthcare expenditure, lower likelihood of employment, higher rates of absenteeism, and lower income. Despite its low prevalence, HF was associated with the highest incremental healthcare expenditure and the lowest likelihood of being employed compared to other common comorbid conditions.

Association of technologically assisted integrated care with clinical outcomes in type 2 diabetes in Hong Kong using the prospective JADE Program: A retrospective cohort analysis.

BACKGROUND: Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. METHODS AND FINDINGS: The web-based Joint Asia Diabetes Evaluation (JADE) platform provides a protocol to guide data collection for issuing a personalized JADE report including risk categories (1-4, low-high), 5-year probabilities of cardiovascular-renal events, and trends and targets of 4 risk factors with tailored decision support. The JADE program is a prospective cohort study implemented in a naturalistic environment where patients underwent nurse-led structured evaluation (blood/urine/eye/feet) in public and private outpatient clinics and diabetes centers in Hong Kong. We retrospectively analyzed the data of 16,624 Han Chinese patients with type 2 diabetes who were enrolled in 2007-2015. In the public setting, the non-JADE group (n = 3,587) underwent structured evaluation for risk factors and complications only, while the JADE (n = 9,601) group received a JADE report with group empowerment by nurses. In a community-based, nurse-led, university-affiliated diabetes center (UDC), the JADE-Personalized (JADE-P) group (n = 3,436) received a JADE report, personalized empowerment, and annual telephone reminder for reevaluation and engagement. The primary composite outcome was time to the first occurrence of cardiovascular-renal diseases, all-site cancer, and/or death, based on hospitalization data censored on 30 June 2017. During 94,311 person-years of follow-up in 2007-2017, 7,779 primary events occurred. Compared with the JADE group (136.22 cases per 1,000 patient-years [95% CI 132.35-140.18]), the non-JADE group had higher (145.32 [95% CI 138.68-152.20]; P = 0.020) while the JADE-P group had lower event rates (70.94 [95% CI 67.12-74.91]; P < 0.001). The adjusted hazard ratios (aHRs) for the primary composite outcome were 1.22 (95% CI 1.15-1.30) and 0.70 (95% CI 0.66-0.75), respectively, independent of risk profiles, education levels, drug usage, self-care, and comorbidities at baseline. We reported consistent results in propensity-score-matched analyses and after accounting for loss to follow-up. Potential limitations include its nonrandomized design that precludes causal inference, residual confounding, and participation bias. CONCLUSIONS: ICT-assisted integrated care was associated with a reduction in clinical events, including death in type 2 diabetes in public and private healthcare settings.