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From Hong Kong Diabetes Register to JADE Program to RAMP-DM for Data-Driven Actions

Chan JCN, Lim LL, Luk AOY, Ozaki R, Kong APS, Ma RCW, et al.

Diabetes Care, 2019 11;42(11):2022-2031.
PMID: 31530658 DOI: 10.2337/dci19-0003

In 1995, the Hong Kong Diabetes Register (HKDR) was established by a doctor-nurse team at a university-affiliated, publicly funded, hospital-based diabetes center using a structured protocol for gathering data to stratify risk, triage care, empower patients, and individualize treatment. This research-driven quality improvement program has motivated the introduction of a territory-wide diabetes risk assessment and management program provided by 18 hospital-based diabetes centers since 2000. By linking the data-rich HKDR to the territory-wide electronic medical record, risk equations were developed and validated to predict clinical outcomes. In 2007, the HKDR protocol was digitalized to establish the web-based Joint Asia Diabetes Evaluation (JADE) Program complete with risk levels and algorithms for issuance of personalized reports to reduce clinical inertia and empower self-management. Through this technologically assisted, integrated diabetes care program, we have generated big data to track secular trends, identify unmet needs, and verify interventions in a naturalistic environment. In 2009, the JADE Program was adapted to form the Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) in the publicly funded primary care clinics, which reduced all major events by 30-60% in patients without complications. Meanwhile, a JADE-assisted assessment and empowerment program provided by a university-affiliated, self-funded, nurse-coordinated diabetes center, aimed at complementing medical care in the community, also reduced all major events by 30-50% in patients with different risk levels. By combining universal health coverage, public-private partnerships, and data-driven integrated care, the Hong Kong experience provides a possible solution than can be adapted elsewhere to make quality diabetes care accessible, affordable, and sustainable.
Metabolic, immunological and clinical characteristics in newly diagnosed Asian diabetes patients aged 12-40 years

Pan CY, So WY, Khalid BA, Mohan V, Thai AC, Zimmet P, et al.

Diabet Med, 2004 Sep;21(9):1007-13.
PMID: 15317606 DOI: 10.1111/j.1464-5491.2004.01287.x

AIM: To describe the clinical, biochemical and immunological characteristics of young-onset diabetes in Asia.
METHODS: Clinical, biochemical and immunological variables were assessed in 919 newly diagnosed (duration less than 12 months) young onset Asian diabetic patients aged between 12 and 40 years. The subjects constituted 57% Chinese, 29% Indians and 14% Malays, recruited from diabetes centres in China, Hong Kong, India, Malaysia and Singapore.
RESULTS: The mean age (+/- sd) was 31.6 +/- 7.2 years, with the majority (66%) in the 31-40 years age group. Mean body mass index (BMI) (+/- sd) was 25.3 +/- 5.0 kg/m2 with 47% exceeding the suggested Asian cut-off point for obesity (BMI > or = 25). Ethnic difference in clinical characteristics included BMI, blood pressure, mode of treatment and degree of insulin resistance. Most patients had a clinical presentation of Type 2 diabetes. About 10% had a classical combination of ketotic presentation, presence of autoimmune-markers and documented insulin deficiency indicative of Type 1 diabetes. Forty-eight percent were receiving oral hypoglycaemic agents (OHAs) while 31% were on diet only, 18% were receiving insulin and 2% were on a combination of insulin and OHA.
CONCLUSION: Young onset diabetes patients in Asia represent a heterogeneous group in terms of their clinical and biochemical characteristics and classical Type 1 diabetes is relatively uncommon. The 5-year follow up study will determine the progress of these patients and help to clarify the natural history.
Fulltext Aspects of Multicomponent Integrated Care Promote Sustained Improvement in Surrogate Clinical Outcomes: A Systematic Review and Meta-analysis

Lim LL, Lau ESH, Kong APS, Davies MJ, Levitt NS, Eliasson B, et al.

Diabetes Care, 2018 06;41(6):1312-1320.
PMID: 29784698 DOI: 10.2337/dc17-2010

OBJECTIVE: The implementation of the Chronic Care Model (CCM) improves health care quality. We examined the sustained effectiveness of multicomponent integrated care in type 2 diabetes.

RESEARCH DESIGN AND METHODS: We searched PubMed and Ovid MEDLINE (January 2000-August 2016) and identified randomized controlled trials comprising two or more quality improvement strategies from two or more domains (health system, health care providers, or patients) lasting ≥12 months with one or more clinical outcomes. Two reviewers extracted data and appraised the reporting quality.

RESULTS: In a meta-analysis of 181 trials (N = 135,112), random-effects modeling revealed pooled mean differences in HbA1c of -0.28% (95% CI -0.35 to -0.21) (-3.1 mmol/mol [-3.9 to -2.3]), in systolic blood pressure (SBP) of -2.3 mmHg (-3.1 to -1.4), in diastolic blood pressure (DBP) of -1.1 mmHg (-1.5 to -0.6), and in LDL cholesterol (LDL-C) of -0.14 mmol/L (-0.21 to -0.07), with greater effects in patients with LDL-C ≥3.4 mmol/L (-0.31 vs. -0.10 mmol/L for <3.4 mmol/L; Pdifference = 0.013), studies from Asia (HbA1c -0.51% vs. -0.23% for North America [-5.5 vs. -2.5 mmol/mol]; Pdifference = 0.046), and studies lasting >12 months (SBP -3.4 vs. -1.4 mmHg, Pdifference = 0.034; DBP -1.7 vs. -0.7 mmHg, Pdifference = 0.047; LDL-C -0.21 vs. -0.07 mmol/L for 12-month studies, Pdifference = 0.049). Patients with median age <60 years had greater HbA1c reduction (-0.35% vs. -0.18% for ≥60 years [-3.8 vs. -2.0 mmol/mol]; Pdifference = 0.029). Team change, patient education/self-management, and improved patient-provider communication had the largest effect sizes (0.28-0.36% [3.0-3.9 mmol/mol]).

CONCLUSIONS: Despite the small effect size of multicomponent integrated care (in part attenuated by good background care), team-based care with better information flow may improve patient-provider communication and self-management in patients who are young, with suboptimal control, and in low-resource settings.
Fulltext 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

Lim LL, Lau ESH, Ozaki R, Chung H, Fu AWC, Chan W, et al.

PLoS Med, 2020 10;17(10):e1003367.
PMID: 33007052 DOI: 10.1371/journal.pmed.1003367

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.
Fulltext Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4

Ma RC, Hu C, Tam CH, Zhang R, Kwan P, Leung TF, et al.

Diabetologia, 2013 Jun;56(6):1291-305.
PMID: 23532257 DOI: 10.1007/s00125-013-2874-4

AIMS/HYPOTHESIS: Most genetic variants identified for type 2 diabetes have been discovered in European populations. We performed genome-wide association studies (GWAS) in a Chinese population with the aim of identifying novel variants for type 2 diabetes in Asians.
METHODS: We performed a meta-analysis of three GWAS comprising 684 patients with type 2 diabetes and 955 controls of Southern Han Chinese descent. We followed up the top signals in two independent Southern Han Chinese cohorts (totalling 10,383 cases and 6,974 controls), and performed in silico replication in multiple populations.
RESULTS: We identified CDKN2A/B and four novel type 2 diabetes association signals with p
The Lancet Commission on diabetes: using data to transform diabetes care and patient lives

Chan JCN, Lim LL, Wareham NJ, Shaw JE, Orchard TJ, Zhang P, et al.

Lancet, 2021 Dec 19;396(10267):2019-2082.
PMID: 33189186 DOI: 10.1016/S0140-6736(20)32374-6