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Dat TV, Binh V, Hoang TM, Tu VL, Luyen PD, Anh LTK. The effectiveness of telemedicine in the management of type 2 diabetes: A systematic review. SAGE Open Med 2024; 12:20503121241271846. [PMID: 39263639 PMCID: PMC11388326 DOI: 10.1177/20503121241271846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 07/03/2024] [Indexed: 09/13/2024] Open
Abstract
Background Type 2 diabetes, a lifestyle-related disease demanding daily self-management, is a significant health concern. In this context, the use of telemedicine as a management tool is a relatively new and promising approach. This study aims to contribute to the growing body of knowledge by identifying the effectiveness of telemedicine in managing type 2 diabetes through a systematic review approach. Methods Four databases were searched including PubMed, Virtual Health Library, Global Health Library, and Google Scholar on 27 July 2022. Additionally, a manual search was performed to identify any relevant articles that may have been missed. The quality of the included articles was rigorously assessed using the Study Quality Assessment Tools of the National Institute of Health. Results We analyzed data from 134 articles. All 134 studies were published between 2002 and 2022, including 103 controlled intervention trials, 13 cohort studies, 7 before-after (pre-post) studies with no control group, 1 initial trial, 1 case study, 1 pilot study, and 8 two-arm studies that did not report the study design. Accordingly, most studies show positive changes in glycemic index in every group using telemedicine. Overall, although the BMI and weight indices in the studies improved at the end of the course, the improvement values were considered insignificant. Conclusion Telemedicine may be a valuable solution for blood sugar management in patients with type 2 diabetes. However, the effectiveness of telemedicine in improving BMI and quality of life is unclear.
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Affiliation(s)
- Truong Van Dat
- Hanoi University of Public Health, Vietnam
- Ministry of Health, Hanoi, Vietnam
| | - Van Binh
- University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam
| | - Thai Minh Hoang
- University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam
| | - Vo Linh Tu
- University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam
| | - Pham Dinh Luyen
- University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam
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Terkes N, Bektas H, Balci MK. Effect of web-based education intervention on blood glucose control, self-care and quality of life in patients with type 2 diabetes: A single-blinded randomized controlled trial. Int J Nurs Pract 2024:e13298. [PMID: 39155430 DOI: 10.1111/ijn.13298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/12/2023] [Accepted: 08/04/2024] [Indexed: 08/20/2024]
Abstract
AIM This study aimed to assess the effects of web-based education on blood glucose control, self-care and quality of life in patients with type 2 diabetes. METHODS A single-blinded randomized controlled trial was conducted in accordance with the Consolidated Standards of Reporting Trials (CONSORT) checklist at a university hospital in Turkey. The study included 89 patients with type 2 diabetes who were randomly divided into an intervention group (44) and a control group (45). Participants in the intervention group participated in a 3-month web-based education programme. RESULTS The findings indicated that there were no significant differences in sociodemographic characteristics and illness features between the intervention and control groups, and both were homogeneous. A statistically significant decrease of 0.71 was observed in the HbA1c (%) level of the intervention group following web-based education. Following web-based education, there was a significant difference in body mass index (kg/m2) and waist circumferences (cm) between the intervention and control groups. The intervention group displayed significantly improved self-care and quality of life over the 3-month period (p < 0.05). CONCLUSION This study suggests that web-based education can enhance the self-care and quality of life of patients with type 2 diabetes.
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Affiliation(s)
- Nurten Terkes
- Bucak Health School, Department of Internal Medicine Nursing, Burdur Mehmet Akif Ersoy University, Burdur, Turkey
| | - Hicran Bektas
- Faculty of Nursing, Department of Internal Medicine Nursing, Akdeniz University, Antalya, Turkey
| | - Mustafa Kemal Balci
- Department of Endocrinology and Metabolism Disease, Akdeniz University Hospital, Antalya, Turkey
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Misra S, Aguilar-Salinas CA, Chikowore T, Konradsen F, Ma RCW, Mbau L, Mohan V, Morton RW, Nyirenda MJ, Tapela N, Franks PW. The case for precision medicine in the prevention, diagnosis, and treatment of cardiometabolic diseases in low-income and middle-income countries. Lancet Diabetes Endocrinol 2023; 11:836-847. [PMID: 37804857 DOI: 10.1016/s2213-8587(23)00164-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/08/2023] [Accepted: 06/01/2023] [Indexed: 10/09/2023]
Abstract
Cardiometabolic diseases are the leading preventable causes of death in most geographies. The causes, clinical presentations, and pathogenesis of cardiometabolic diseases vary greatly worldwide, as do the resources and strategies needed to prevent and treat them. Therefore, there is no single solution and health care should be optimised, if not to the individual (ie, personalised health care), then at least to population subgroups (ie, precision medicine). This optimisation should involve tailoring health care to individual disease characteristics according to ethnicity, biology, behaviour, environment, and subjective person-level characteristics. The capacity and availability of local resources and infrastructures should also be considered. Evidence needed for equitable precision medicine cannot be generated without adequate data from all target populations, and the idea that research done in high-income countries will transfer adequately to low-income and middle-income countries (LMICs) is problematic, as many migration studies and transethnic comparisons have shown. However, most data for precision medicine research are derived from people of European ancestry living in high-income countries. In this Series paper, we discuss the case for precision medicine for cardiometabolic diseases in LMICs, the barriers and enablers, and key considerations for implementation. We focus on three propositions: first, failure to explore and implement precision medicine for cardiometabolic disease in LMICs will enhance global health disparities. Second, some LMICs might already be placed to implement cardiometabolic precision medicine under appropriate circumstances, owing to progress made in treating infectious diseases. Third, improvements in population health from precision medicine are most probably asymptotic; the greatest gains are more likely to be obtained in countries where health-care systems are less developed. We outline key recommendations for implementation of precision medicine approaches in LMICs.
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Affiliation(s)
- Shivani Misra
- Division of Metabolism, Digestion and Reproduction, Imperial College London, London, UK; Department of Diabetes and Endocrinology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Carlos A Aguilar-Salinas
- Dirección de Nutricion, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico; Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, México
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Flemming Konradsen
- Novo Nordisk Foundation, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | | | - Viswanathan Mohan
- Madras Diabetes Research Foundation, ICMR Centre for Advanced Research in Diabetes, Chennai, India; Dr Mohan's Diabetes Specialties Centre, IDF Centre of Excellence in Diabetes Care, Chennai, India
| | | | - Moffat J Nyirenda
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; London School of Hygiene and Tropical Medicine, London, UK
| | - Neo Tapela
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; International Consortium for Health Outcomes Measurement, Oxford, UK
| | - Paul W Franks
- Novo Nordisk Foundation, Copenhagen, Denmark; Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Harvard T H Chan School of Public Health, Boston, MA, USA.
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Konnyu KJ, Yogasingam S, Lépine J, Sullivan K, Alabousi M, Edwards A, Hillmer M, Karunananthan S, Lavis JN, Linklater S, Manns BJ, Moher D, Mortazhejri S, Nazarali S, Paprica PA, Ramsay T, Ryan PM, Sargious P, Shojania KG, Straus SE, Tonelli M, Tricco A, Vachon B, Yu CH, Zahradnik M, Trikalinos TA, Grimshaw JM, Ivers N. Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes. Cochrane Database Syst Rev 2023; 5:CD014513. [PMID: 37254718 PMCID: PMC10233616 DOI: 10.1002/14651858.cd014513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
BACKGROUND There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors. Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted. Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three. Combinations of the three most effective QI strategies were estimated to lead to the below effects: - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%; - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg; - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.
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Affiliation(s)
- Kristin J Konnyu
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sharlini Yogasingam
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Johanie Lépine
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Katrina Sullivan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Alun Edwards
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Michael Hillmer
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
| | - Sathya Karunananthan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Canada
| | - John N Lavis
- McMaster Health Forum, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Stefanie Linklater
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Braden J Manns
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sameh Mortazhejri
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Samir Nazarali
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada
| | - P Alison Paprica
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Timothy Ramsay
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Peter Sargious
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Kaveh G Shojania
- University of Toronto Centre for Patient Safety, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sharon E Straus
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
| | - Marcello Tonelli
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - Andrea Tricco
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
- Epidemiology Division and Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Queen's Collaboration for Health Care Quality: A JBI Centre of Excellence, Queen's University, Kingston, Canada
| | - Brigitte Vachon
- School of Rehabilitation, Occupational Therapy Program, University of Montreal, Montreal, Canada
| | - Catherine Hy Yu
- Department of Medicine, St. Michael's Hospital, Toronto, Canada
| | - Michael Zahradnik
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Thomas A Trikalinos
- Departments of Health Services, Policy, and Practice and Biostatistics, Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Jeremy M Grimshaw
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Noah Ivers
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
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Lim LL, Lau ESH, Cheung JTK, Chan SP, Ji L, Lim S, Sirinvaravong S, Unnikrishnan AG, Luk AOY, Cortese V, Durocher A, Chan JCN. Real-world usage of sulphonylureas in Asian patients with type 2 diabetes using the Joint Asia Diabetes Evaluation (JADE) register. Diabetes Obes Metab 2023; 25:208-221. [PMID: 36082513 PMCID: PMC10087907 DOI: 10.1111/dom.14865] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 08/24/2022] [Accepted: 09/04/2022] [Indexed: 12/14/2022]
Abstract
AIMS To explore the patterns of use of oral glucose-lowering drugs (OGLDs) in Asian patients with type 2 diabetes (T2D), focusing on sulphonylureas (SUs), and to describe patient profiles according to treatment regimen. METHODS We conducted a cross-sectional analysis of data from adults with T2D from 11 Asian countries/regions with structured assessment enrolled in the prospective Joint Asia Diabetes Evaluation (JADE) register between November 2007 and December 2019. Patients receiving insulin and/or injectable glucagon-like peptide-1 receptor agonists were excluded. RESULTS Amongst 62 512 patients (mean ± standard deviation age: 57.3 ± 11.8 years; 53.6% men), 54 783 (87.6%) were treated with OGLDs at enrolment. Most received one (37.5%) or two (44.2%) OGLDs. In the entire cohort, 59.4% of treated patients received SU-based therapy with variations amongst countries/regions. Overall, 79.5% of SU regimens were based on SUs plus metformin, and 22.1% on SUs plus dipeptidyl peptidase-4 inhibitors. Among SU users, gliclazide was most commonly prescribed (46.7%), followed by glimepiride (40.0%) and glibenclamide (8.1%). More gliclazide users entered the cohort with glycated haemoglobin levels <53 mmol/mol (7%) than non-gliclazide SU users (odds ratio [OR] 1.09, 95% CI 1.02-1.17), with less frequent self-reported hypoglycaemia in the 3 months before registration (OR 0.81, 95% CI 0.72-0.92; adjusted for sociodemographic factors, cardiometabolic risk factors, complications, use of other OGLDs, country/region and year of registration). CONCLUSION In Asia, SUs are a popular OGLD class, often combined with metformin. Good glycaemic control and safety profiles associated with the use of SUs, including gliclazide, support their position as a key treatment option in patients with T2D.
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Affiliation(s)
- Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
- Asia Diabetes Foundation, Shatin, Hong Kong, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
- Asia Diabetes Foundation, Shatin, Hong Kong, China
| | - Johnny T K Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
| | - Siew Pheng Chan
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking, China
| | - Soo Lim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea
| | - Sirinart Sirinvaravong
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - A G Unnikrishnan
- Department of Endocrinology, Chellaram Diabetes Institute, Pune, India
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
- Asia Diabetes Foundation, Shatin, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Viviana Cortese
- Global Medical and Patient Affairs, Servier Affaires Médicales, Suresnes, France
| | - Alexandra Durocher
- Global Medical and Patient Affairs, Servier Affaires Médicales, Suresnes, France
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China
- Asia Diabetes Foundation, Shatin, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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Khunti K, Aroda VR, Aschner P, Chan JCN, Del Prato S, Hambling CE, Harris S, Lamptey R, McKee M, Tandon N, Valabhji J, Seidu S. The impact of the COVID-19 pandemic on diabetes services: planning for a global recovery. Lancet Diabetes Endocrinol 2022; 10:890-900. [PMID: 36356612 PMCID: PMC9640202 DOI: 10.1016/s2213-8587(22)00278-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 09/01/2022] [Accepted: 09/30/2022] [Indexed: 11/09/2022]
Abstract
The COVID-19 pandemic has disproportionately affected certain groups, such as older people (ie, >65 years), minority ethnic populations, and people with specific chronic conditions including diabetes, cardiovascular disease, kidney disease, and some respiratory diseases. There is now evidence of not only direct but also indirect adverse effects of COVID-19 in people with diabetes. Recurrent lockdowns and public health measures throughout the pandemic have restricted access to routine diabetes care, limiting new diagnoses, and affecting self-management, routine follow-ups, and access to medications, as well as affecting lifestyle behaviours and emotional wellbeing globally. Pre-pandemic studies have shown that short-term delays in delivery of routine care, even by 12 months, are associated with adverse effects on risk factor control and worse microvascular, macrovascular, and mortality outcomes in people with diabetes. Disruptions within the short-to-medium term due to natural disasters also result in worse diabetes outcomes. However, the true magnitude of the indirect effects of the COVID-19 pandemic on long-term outcomes and mortality in people with diabetes is still unclear. Disasters tend to exacerbate existing health disparities; as we recover ambulatory diabetes services in the aftermath of the pandemic, there is an opportunity to prioritise those with the greatest need, and to target resources and interventions aimed at improving outcomes and reducing inequality.
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Affiliation(s)
- Kamlesh Khunti
- Diabetes Research Centre, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK; NIHR Applied Research Collaboration East Midlands, Leicester, UK.
| | | | - Pablo Aschner
- Asociación Colombiana de Diabetes, Bogotá, Colombia; Oficina de Investigaciones, Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Stefano Del Prato
- Diabetology Divisions, Pisa University Hospital, University of Pisa, Pisa, Italy
| | | | - Stewart Harris
- Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Roberta Lamptey
- Department of Family Medicine, Korle Bu Teaching Hospital, Accra, Ghana; Department of Community Health, University of Ghana Medical School, Accra, Ghana
| | - Martin McKee
- Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK
| | - Nikhil Tandon
- Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India
| | - Jonathan Valabhji
- Division of Metabolism, Digestion and Reproduction, Imperial College London, London, UK; NHS England, London, UK; NHS Improvement, London, UK; Department of Diabetes and Endocrinology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Samuel Seidu
- Diabetes Research Centre, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK; NIHR Applied Research Collaboration East Midlands, Leicester, UK
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7
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Investigation of the Effect of Web-Based Education on Self-Care Management and Family Support in Women With Type 2 Diabetes. J Nurse Pract 2022. [DOI: 10.1016/j.nurpra.2022.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Mikkonen K, Yamakawa M, Tomietto M, Tuomikoski A, Utsumi M, Jarva E, Kääriäinen M, Oikarinen A. Randomised controlled trials addressing how the clinical application of information and communication technology impacts the quality of patient care—A systematic review and meta‐analysis. J Clin Nurs 2022. [DOI: 10.1111/jocn.16448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/04/2022] [Accepted: 06/23/2022] [Indexed: 11/27/2022]
Affiliation(s)
- Kristina Mikkonen
- Research Unit of Health Sciences and Technology University of Oulu Oulu Finland
- The Finnish Centre for Evidence‐Based Health Care: A JOANNA Briggs Institute Centre of Excellence Helsinki Finland
- Medical Research Center Oulu Oulu University Hospital and University of Oulu Oulu Finland
| | - Miyae Yamakawa
- Department of Evidence‐Based Clinical Nursing Division of Health Sciences Graduate School of Medicine Osaka University Asakayama General Hospital Osaka Japan
| | - Marco Tomietto
- Department of Nursing, Midwifery and Healthcare Faculty of Health and Life Sciences Northumbria University Newcastle upon Tyne UK
- Research Unit of Nursing Science and Health Management University of Oulu Oulu Finland
| | - Anna‐Maria Tuomikoski
- The Finnish Centre for Evidence‐Based Health Care: A JOANNA Briggs Institute Centre of Excellence Helsinki Finland
- Oulu University Hospital Oulu Finland
| | - Momoe Utsumi
- Department of Evidence‐Based Clinical Nursing Division of Health Sciences Graduate School of Medicine Osaka University Asakayama General Hospital Osaka Japan
| | - Erika Jarva
- Research Unit of Health Sciences and Technology University of Oulu Oulu Finland
- The Finnish Centre for Evidence‐Based Health Care: A JOANNA Briggs Institute Centre of Excellence Helsinki Finland
| | - Maria Kääriäinen
- Research Unit of Health Sciences and Technology University of Oulu Oulu Finland
- The Finnish Centre for Evidence‐Based Health Care: A JOANNA Briggs Institute Centre of Excellence Helsinki Finland
- Medical Research Center Oulu Oulu University Hospital and University of Oulu Oulu Finland
| | - Anne Oikarinen
- Research Unit of Health Sciences and Technology University of Oulu Oulu Finland
- The Finnish Centre for Evidence‐Based Health Care: A JOANNA Briggs Institute Centre of Excellence Helsinki Finland
- Medical Research Center Oulu Oulu University Hospital and University of Oulu Oulu Finland
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9
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Hategeka C, Adu P, Desloge A, Marten R, Shao R, Tian M, Wei T, Kruk ME. Implementation research on noncommunicable disease prevention and control interventions in low- and middle-income countries: A systematic review. PLoS Med 2022; 19:e1004055. [PMID: 35877677 PMCID: PMC9359585 DOI: 10.1371/journal.pmed.1004055] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 08/08/2022] [Accepted: 06/21/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND While the evidence for the clinical effectiveness of most noncommunicable disease (NCD) prevention and treatment interventions is well established, care delivery models and means of scaling these up in a variety of resource-constrained health systems are not. The objective of this review was to synthesize evidence on the current state of implementation research on priority NCD prevention and control interventions provided by health systems in low- and middle-income countries (LMICs). METHODS AND FINDINGS On January 20, 2021, we searched MEDLINE and EMBASE databases from 1990 through 2020 to identify implementation research studies that focused on the World Health Organization (WHO) priority NCD prevention and control interventions targeting cardiovascular disease, cancer, diabetes, and chronic respiratory disease and provided within health systems in LMICs. Any empirical and peer-reviewed studies that focused on these interventions and reported implementation outcomes were eligible for inclusion. Given the focus on this review and the heterogeneity in aims and methodologies of included studies, risk of bias assessment to understand how effect size may have been compromised by bias is not applicable. We instead commented on the distribution of research designs and discussed about stronger/weaker designs. We synthesized extracted data using descriptive statistics and following the review protocol registered in PROSPERO (CRD42021252969). Of 9,683 potential studies and 7,419 unique records screened for inclusion, 222 eligible studies evaluated 265 priority NCD prevention and control interventions implemented in 62 countries (6% in low-income countries and 90% in middle-income countries). The number of studies published has been increasing over time. Nearly 40% of all the studies were on cervical cancer. With regards to intervention type, screening accounted for 49%, treatment for 39%, while prevention for 12% (with 80% of the latter focusing on prevention of the NCD behavior risk factors). Feasibility (38%) was the most studied implementation outcome followed by adoption (23%); few studies addressed sustainability. The implementation strategies were not specified well enough. Most studies used quantitative methods (86%). The weakest study design, preexperimental, and the strongest study design, experimental, were respectively employed in 25% and 24% of included studies. Approximately 72% of studies reported funding, with international funding being the predominant source. The majority of studies were proof of concept or pilot (88%) and targeted the micro level of health system (79%). Less than 5% of studies report using implementation research framework. CONCLUSIONS Despite growth in implementation research on NCDs in LMICs, we found major gaps in the science. Future studies should prioritize implementation at scale, target higher levels health systems (meso and macro levels), and test sustainability of NCD programs. They should employ designs with stronger internal validity, be more conceptually driven, and use mixed methods to understand mechanisms. To maximize impact of the research under limited resources, adding implementation science outcomes to effectiveness research and regional collaborations are promising.
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Affiliation(s)
- Celestin Hategeka
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Prince Adu
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Allissa Desloge
- School of Public Health, University of Illinois Chicago, Chicago, Illinois, United States of America
| | - Robert Marten
- Alliance for Health Policy and Systems Research, WHO, Geneva, Switzerland
| | | | - Maoyi Tian
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
- School of Public Health, Harbin Medical University, Harbin, China
| | - Ting Wei
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Margaret E. Kruk
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
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10
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Chan JCN, Lim LL, Wareham NJ, Shaw JE, Orchard TJ, Zhang P, Lau ESH, Eliasson B, Kong APS, Ezzati M, Aguilar-Salinas CA, McGill M, Levitt NS, Ning G, So WY, Adams J, Bracco P, Forouhi NG, Gregory GA, Guo J, Hua X, Klatman EL, Magliano DJ, Ng BP, Ogilvie D, Panter J, Pavkov M, Shao H, Unwin N, White M, Wou C, Ma RCW, Schmidt MI, Ramachandran A, Seino Y, Bennett PH, Oldenburg B, Gagliardino JJ, Luk AOY, Clarke PM, Ogle GD, Davies MJ, Holman RR, Gregg EW. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet 2021; 396:2019-2082. [PMID: 33189186 DOI: 10.1016/s0140-6736(20)32374-6] [Citation(s) in RCA: 303] [Impact Index Per Article: 101.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 07/06/2020] [Accepted: 11/05/2020] [Indexed: 01/19/2023]
Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China.
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Life Sciences, La Trobe University, Melbourne, VIC, Australia
| | - Trevor J Orchard
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Ping Zhang
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Eric S H Lau
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Björn Eliasson
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Endocrinology and Metabolism, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alice P S Kong
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Medical Research Council Centre for Environment and Health, Imperial College London, London, UK; WHO Collaborating Centre on NCD Surveillance and Epidemiology, Imperial College London, London, UK
| | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Margaret McGill
- Diabetes Centre, Royal Prince Alfred Hospital, University of Sydney, Sydney, NSW, Australia
| | - Naomi S Levitt
- Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Medicine and Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Guang Ning
- Shanghai Clinical Center for Endocrine and Metabolic Disease, Department of Endocrinology, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, China; Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jean Adams
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Paula Bracco
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Gabriel A Gregory
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Jingchuan Guo
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Xinyang Hua
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Emma L Klatman
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia
| | - Dianna J Magliano
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Boon-Peng Ng
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; College of Nursing and Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL, USA
| | - David Ogilvie
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jenna Panter
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Meda Pavkov
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hui Shao
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Nigel Unwin
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Martin White
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Constance Wou
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Maria I Schmidt
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ambady Ramachandran
- India Diabetes Research Foundation and Dr A Ramachandran's Diabetes Hospitals, Chennai, India
| | - Yutaka Seino
- Center for Diabetes, Endocrinology and Metabolism, Kansai Electric Power Hospital, Osaka, Japan; Yutaka Seino Distinguished Center for Diabetes Research, Kansai Electric Power Medical Research Institute, Kobe, Japan
| | - Peter H Bennett
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Brian Oldenburg
- Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre on Implementation Research for Prevention and Control of NCDs, University of Melbourne, Melbourne, VIC, Australia
| | - Juan José Gagliardino
- Centro de Endocrinología Experimental y Aplicada, UNLP-CONICET-CICPBA, Facultad de Ciencias Médicas, Universidad Nacional de La Plata, La Plata, Argentina
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Philip M Clarke
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Graham D Ogle
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Rury R Holman
- Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Edward W Gregg
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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Effects of Mobile Phone-based Telemedicine Management in Patients with Type 2 Diabetes Mellitus: A Randomized Clinical Trial. Am J Med Sci 2021; 363:224-231. [PMID: 34534510 DOI: 10.1016/j.amjms.2021.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 05/19/2021] [Accepted: 09/10/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND This study aims to explore the effect of mobile phone-based telemedicine management of glycemic control of type 2 diabetes mellitus (T2DM). METHODS Patients with T2DM were followed up in Chongqing Jiulongpo District Yuzhoulu Community Health Center, and randomly divided into the telemedicine group (n=47) and the control group (n=50). The control group received regularly routine intervention. The telemedicine management group used the mobile phone to manage their health condition remotely. RESULTS Both groups had similar baseline characteristics. After a follow-up period of 12 months intervention, the weight, body mass index, waist circumference, systolic blood pressure, body fat percentage, body fat mass, body water and muscle mass, fasting blood glucose, glycosylated hemoglobin, total costs of diabetes treatment for 1 month and the quality-of-life score were significantly improved in the telemedicine group (P<0.05). And compared with the control group, body fat composition, fasting blood glucose, glycosylated hemoglobin and the cost of change shows a significant improvement (P<0.05). Positive correlation was detected between fasting blood glucose and body composition parameters, such as body fat percentage, lean body mass and body fat mass in the telemedicine group (r=0.56, P<0.05; r=0.37, P<0.05; r=0.56, P<0.05). CONCLUSIONS Compared with conventional intervention, the mobile phone-based telemedicine management can help patients with diabetes to improve glycemic level and quality of life.
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12
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Jia W, Zhang P, Zhu D, Duolikun N, Li H, Bao Y, Li X. Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): A cluster randomized trial. PLoS Med 2021; 18:e1003754. [PMID: 34547030 PMCID: PMC8454951 DOI: 10.1371/journal.pmed.1003754] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 08/04/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Glycemic control remains suboptimal in developing countries due to critical system deficiencies. An innovative mobile health (mHealth)-enabled hierarchical diabetes management intervention was introduced and evaluated in China with the purpose of achieving better control of type 2 diabetes in primary care. METHODS AND FINDINGS A community-based cluster randomized controlled trial was conducted among registered patients with type 2 diabetes in primary care from June 2017 to July 2019. A total of 19,601 participants were recruited from 864 communities (clusters) across 25 provinces in China, and 19,546 completed baseline assessment. Moreover, 576 communities (13,037 participants) were centrally randomized to the intervention and 288 communities (6,509 participants) to usual care. The intervention was centered on a tiered care team-delivered mHealth-mediated service package, initiated by monthly blood glucose monitoring at each structured clinic visit. Capacity building and quarterly performance review strategies upheld the quality of delivered primary care. The primary outcome was control of glycated hemoglobin (HbA1c; <7.0%), assessed at baseline and 12 months. The secondary outcomes include the individual/combined control rates of blood glucose, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C); changes in levels of HbA1c, BP, LDL-C, fasting blood glucose (FBG), and body weight; and episodes of hypoglycemia. Data were analyzed using intention-to-treat (ITT) generalized estimating equation (GEE) models, accounting for clustering and baseline values of the analyzed outcomes. After 1-year follow-up, 17,554 participants (89.8%) completed the end-of-study (EOS) assessment, with 45.1% of them from economically developed areas, 49.9% from urban areas, 60.5 (standard deviation [SD] 8.4) years of age, 41.2% male, 6.0 years of median diabetes duration, HbA1c level of 7.87% (SD 1.92%), and 37.3% with HbA1c <7.0% at baseline. Compared with usual care, the intervention led to an absolute improvement in the HbA1c control rate of 7.0% (95% confidence interval [CI] 4.0% to 10.0%) and a relative improvement of 18.6% (relative risk [RR] 1.186, 95% CI 1.105 to 1.267) and an absolute improvement in the composite ABC control (HbA1c <7.0%, BP <140/80 mm Hg, and LDL-C <2.6 mmol/L) rate of 1.9% (95% CI 0.5 to 3.5) and a relative improvement of 21.8% (RR 1.218, 95% CI 1.062 to 1.395). No difference was found on hypoglycemia episode and weight gain between groups. Study limitations include noncentralized laboratory tests except for HbA1c, and caution should be exercised when extrapolating the findings to patients not registered in primary care system. CONCLUSIONS The mHealth-enabled hierarchical diabetes management intervention effectively improved diabetes control in primary care and has the potential to be transferred to other chronic conditions management in similar contexts. TRIAL REGISTRATION Chinese Clinical Trial Registry (ChiCTR) IOC-17011325.
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Affiliation(s)
- Weiping Jia
- Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Department of Endocrinology, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China
- Chinese Diabetes Society, Beijing, China
- * E-mail:
| | - Puhong Zhang
- The George Institute for Global Health at Peking University Health Science Center, Beijing, China
- Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Dalong Zhu
- Chinese Diabetes Society, Beijing, China
- Department of Endocrinology, Drum Tower Hospital affiliated to Nanjing University Medical School, Nanjing, China
| | - Nadila Duolikun
- The George Institute for Global Health at Peking University Health Science Center, Beijing, China
| | - Hong Li
- Department of Endocrinology, Sir Run Run Shaw Hospital affiliated to School of Medicine, Zhejiang University, Hangzhou, China
| | - Yuqian Bao
- Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Department of Endocrinology, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China
| | - Xian Li
- The George Institute for Global Health at Peking University Health Science Center, Beijing, China
- Faculty of Medicine, University of New South Wales, Sydney, Australia
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13
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Lim LL, Lau ESH, Fu AWC, Ray S, Hung YJ, Tan ATB, Chamnan P, Sheu WHH, Chawla MS, Chia YC, Chuang LM, Nguyen DC, Sosale A, Saboo BD, Phadke U, Kesavadev J, Goh SY, Gera N, Huyen Vu TT, Ma RCW, Lau V, Luk AOY, Kong APS, Chan JCN. Effects of a Technology-Assisted Integrated Diabetes Care Program on Cardiometabolic Risk Factors Among Patients With Type 2 Diabetes in the Asia-Pacific Region: The JADE Program Randomized Clinical Trial. JAMA Netw Open 2021; 4:e217557. [PMID: 33929522 PMCID: PMC8087959 DOI: 10.1001/jamanetworkopen.2021.7557] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
IMPORTANCE Many health care systems lack the efficiency, preparedness, or resources needed to address the increasing number of patients with type 2 diabetes, especially in low- and middle-income countries. OBJECTIVE To examine the effects of a quality improvement intervention comprising information and communications technology and contact with nonphysician personnel on the care and cardiometabolic risk factors of patients with type 2 diabetes in 8 Asia-Pacific countries. DESIGN, SETTING, AND PARTICIPANTS This 12-month multinational open-label randomized clinical trial was conducted from June 28, 2012, to April 28, 2016, at 50 primary care or hospital-based diabetes centers in 8 Asia-Pacific countries (India, Indonesia, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam). Six countries were low and middle income, and 2 countries were high income. The study was conducted in 2 phases; phase 1 enrolled 7537 participants, and phase 2 enrolled 13 297 participants. Participants in both phases were randomized on a 1:1 ratio to intervention or control groups. Data were analyzed by intention to treat and per protocol from July 3, 2019, to July 21, 2020. INTERVENTIONS In both phases, the intervention group received 3 care components: a nurse-led Joint Asia Diabetes Evaluation (JADE) technology-guided structured evaluation, automated personalized reports to encourage patient empowerment, and 2 or more telephone or face-to-face contacts by nurses to increase patient engagement. In phase 1, the control group received the JADE technology-guided structured evaluation and automated personalized reports. In phase 2, the control group received the JADE technology-guided structured evaluation only. MAIN OUTCOMES AND MEASURES The primary outcome was the incidence of a composite of diabetes-associated end points, including cardiovascular disease, chronic kidney disease, visual impairment or eye surgery, lower extremity amputation or foot ulcers requiring hospitalization, all-site cancers, and death. The secondary outcomes were the attainment of 2 or more primary diabetes-associated targets (glycated hemoglobin A1c <7.0%, blood pressure <130/80 mm Hg, and low-density lipoprotein cholesterol <100 mg/dL) and/or 2 or more key performance indices (reduction in glycated hemoglobin A1c≥0.5%, reduction in systolic blood pressure ≥5 mm Hg, reduction in low-density lipoprotein cholesterol ≥19 mg/dL, and reduction in body weight ≥3.0%). RESULTS A total of 20 834 patients with type 2 diabetes were randomized in phases 1 and 2. In phase 1, 7537 participants (mean [SD] age, 60.0 [11.3] years; 3914 men [51.9%]; 4855 patients [64.4%] from low- and middle-income countries) were randomized, with 3732 patients allocated to the intervention group and 3805 patients allocated to the control group. In phase 2, 13 297 participants (mean [SD] age, 54.0 [11.1] years; 7754 men [58.3%]; 13 297 patients [100%] from low- and middle-income countries) were randomized, with 6645 patients allocated to the intervention group and 6652 patients allocated to the control group. In phase 1, compared with the control group, the intervention group had a similar risk of experiencing any of the primary outcomes (odds ratio [OR], 0.94; 95% CI, 0.74-1.21) but had an increased likelihood of attaining 2 or more primary targets (OR, 1.34; 95% CI, 1.21-1.49) and 2 or more key performance indices (OR, 1.18; 95% CI, 1.04-1.34). In phase 2, the intervention group also had a similar risk of experiencing any of the primary outcomes (OR, 1.02; 95% CI, 0.83-1.25) and had a greater likelihood of attaining 2 or more primary targets (OR, 1.25; 95% CI, 1.14-1.37) and 2 or more key performance indices (OR, 1.50; 95% CI, 1.33-1.68) compared with the control group. For attainment of 2 or more primary targets, larger effects were observed among patients in low- and middle-income countries (OR, 1.50; 95% CI, 1.29-1.74) compared with high-income countries (OR, 1.20; 95% CI, 1.03-1.39) (P = .04). CONCLUSIONS AND RELEVANCE In this 12-month clinical trial, the use of information and communications technology and nurses to empower and engage patients did not change the number of clinical events but did reduce cardiometabolic risk factors among patients with type 2 diabetes, especially those in low- and middle-income countries in the Asia-Pacific region. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01631084.
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Affiliation(s)
- Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric S. H. Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
| | - Amy W. C. Fu
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
| | | | - Yi-Jen Hung
- Tri-Service General Hospital, Taipei, Taiwan
| | - Alexander T. B. Tan
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Now with Sunway Medical Centre, Selangor, Malaysia
| | | | | | | | - Yook-Chin Chia
- Department of Primary Care Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | | | | | | | | | | | | | - Su-Yen Goh
- Department of Endocrinology, Singapore General Hospital, Outram Road, Singapore
| | - Neeru Gera
- Max Healthcare Institute, New Delhi, India
| | - Thi Thanh Huyen Vu
- Department of Internal Medicine, Hanoi Medical University, Hanoi, Vietnam
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Vanessa Lau
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
| | - Andrea O. Y. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Alice P. S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
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14
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Flood D, Hane J, Dunn M, Brown SJ, Wagenaar BH, Rogers EA, Heisler M, Rohloff P, Chopra V. Health system interventions for adults with type 2 diabetes in low- and middle-income countries: A systematic review and meta-analysis. PLoS Med 2020; 17:e1003434. [PMID: 33180775 PMCID: PMC7660583 DOI: 10.1371/journal.pmed.1003434] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 10/19/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Effective health system interventions may help address the disproportionate burden of diabetes in low- and middle-income countries (LMICs). We assessed the impact of health system interventions to improve outcomes for adults with type 2 diabetes in LMICs. METHODS AND FINDINGS We searched Ovid MEDLINE, Cochrane Library, EMBASE, African Index Medicus, LILACS, and Global Index Medicus from inception of each database through February 24, 2020. We included randomized controlled trials (RCTs) of health system interventions targeting adults with type 2 diabetes in LMICs. Eligible studies reported at least 1 of the following outcomes: glycemic change, mortality, quality of life, or cost-effectiveness. We conducted a meta-analysis for the glycemic outcome of hemoglobin A1c (HbA1c). GRADE and Cochrane Effective Practice and Organisation of Care methods were used to assess risk of bias for the glycemic outcome and to prepare a summary of findings table. Of the 12,921 references identified in searches, we included 39 studies in the narrative review of which 19 were cluster RCTs and 20 were individual RCTs. The greatest number of studies were conducted in the East Asia and Pacific region (n = 20) followed by South Asia (n = 7). There were 21,080 total participants enrolled across included studies and 10,060 total participants in the meta-analysis of HbA1c when accounting for the design effect of cluster RCTs. Non-glycemic outcomes of mortality, health-related quality of life, and cost-effectiveness had sparse data availability that precluded quantitative pooling. In the meta-analysis of HbA1c from 35 of the included studies, the mean difference was -0.46% (95% CI -0.60% to -0.31%, I2 87.8%, p < 0.001) overall, -0.37% (95% CI -0.64% to -0.10%, I2 60.0%, n = 7, p = 0.020) in multicomponent clinic-based interventions, -0.87% (-1.20% to -0.53%, I2 91.0%, n = 13, p < 0.001) in pharmacist task-sharing studies, and -0.27% (-0.50% to -0.04%, I2 64.1%, n = 7, p = 0.010) in trials of diabetes education or support alone. Other types of interventions had few included studies. Eight studies were at low risk of bias for the summary assessment of glycemic control, 15 studies were at unclear risk, and 16 studies were at high risk. The certainty of evidence for glycemic control by subgroup was moderate for multicomponent clinic-based interventions but was low or very low for other intervention types. Limitations include the lack of consensus definitions for health system interventions, differences in the quality of underlying studies, and sparse data availability for non-glycemic outcomes. CONCLUSIONS In this meta-analysis, we found that health system interventions for type 2 diabetes may be effective in improving glycemic control in LMICs, but few studies are available from rural areas or low- or lower-middle-income countries. Multicomponent clinic-based interventions had the strongest evidence for glycemic benefit among intervention types. Further research is needed to assess non-glycemic outcomes and to study implementation in rural and low-income settings.
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Affiliation(s)
- David Flood
- Center for Research in Indigenous Health, Wuqu’ Kawoq, Tecpán, Guatemala
- Division of Hospital Medicine, Department of Internal Medicine, National Clinician Scholars Program, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jessica Hane
- Medicine-Pediatrics Residency Program, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Matthew Dunn
- School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Bradley H. Wagenaar
- Department of Global Health, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Elizabeth A. Rogers
- Division of General Internal Medicine, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Michele Heisler
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan United States of America
- Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan United States of America
| | - Peter Rohloff
- Center for Research in Indigenous Health, Wuqu’ Kawoq, Tecpán, Guatemala
| | - Vineet Chopra
- Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan United States of America
- Division of Hospital Medicine, Department of Medicine, University of Michigan, Ann Arbor, Michigan United States of America
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15
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Lim LL, Lau ESH, Ozaki R, Chung H, Fu AWC, Chan W, Kong APS, Ma RCW, So WY, Chow E, Cheung KKT, Yau T, Chow CC, Lau V, Yue R, Ng S, Zee B, Goggins W, Oldenburg B, Clarke PM, Lau M, Wong R, Tsang CC, Gregg EW, Wu H, Tong PCY, Ko GTC, Luk AOY, Chan JCN. 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. PLoS Med 2020; 17:e1003367. [PMID: 33007052 PMCID: PMC7531841 DOI: 10.1371/journal.pmed.1003367] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Accepted: 08/26/2020] [Indexed: 12/27/2022] Open
Abstract
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.
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Affiliation(s)
- Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric S. H. Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Harriet Chung
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Amy W. C. Fu
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Wendy Chan
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Alice P. S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Wing-Yee So
- Hospital Authority Head Office, Hong Kong SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Kitty K. T. Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Tiffany Yau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - C. C. Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Vanessa Lau
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Rebecca Yue
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Shek Ng
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Benny Zee
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - William Goggins
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Brian Oldenburg
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Philip M. Clarke
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Maggie Lau
- Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong SAR, China
| | - Rebecca Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - C. C. Tsang
- Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong SAR, China
| | - Edward W. Gregg
- School of Public Health, Imperial College London, London, United Kingdom
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Peter C. Y. Tong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Gary T. C. Ko
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Andrea O. Y. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- * E-mail:
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16
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Chan JCN, Lim LL, Luk AOY, Ozaki R, Kong APS, Ma RCW, So WY, Lo SV. From Hong Kong Diabetes Register to JADE Program to RAMP-DM for Data-Driven Actions. Diabetes Care 2019; 42:2022-2031. [PMID: 31530658 DOI: 10.2337/dci19-0003] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China.,Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hospital Authority, Hong Kong SAR, China
| | - Su-Vui Lo
- Hospital Authority, Hong Kong SAR, China
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17
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Abstract
The People's Republic of China (herein referred to as China) has witnessed one of the most dramatic rises in diabetes prevalence anywhere in the world. The latest epidemiological study suggests that approximately 11% of the population has diabetes, with a significant proportion remaining undiagnosed. Risk factors for diabetes in the Chinese population are similar to those in other populations, though gestational diabetes and young-onset diabetes is becoming increasingly common. Data on the prevalence of diabetic complications remain limited, though cardio-renal complications account for significant morbidity and mortality. Other diabetes-related comorbidities are becoming increasingly common, with cancer emerging as a major cause of mortality among individuals with diabetes. There are many challenges and obstacles that impede effective diabetes prevention and the delivery of care, though much progress has occurred over recent years. Lessons learnt from how China has responded to the challenges posed by the diabetes epidemic will be invaluable for other countries facing the many threats of diabetes and its complications.
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Affiliation(s)
- Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- Chinese University of Hong Kong and Shanghai Jiao Tong University (CUHK-SJTU) Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
- NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
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18
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Coughlin SS, Prochaska JJ, Williams LB, Besenyi GM, Heboyan V, Goggans DS, Yoo W, De Leo G. Patient web portals, disease management, and primary prevention. Risk Manag Healthc Policy 2017; 10:33-40. [PMID: 28435342 PMCID: PMC5391175 DOI: 10.2147/rmhp.s130431] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Efforts aimed at health care reform and continued advances in information technologies have prompted interest among providers and researchers in patient web portals. Patient web portals are password-protected online websites that offer the patients 24-hour access to personal health information from anywhere with an Internet connection. METHODS This article, which is based upon bibliographic searches in PubMed, reviews important developments in web portals for primary and secondary disease prevention, including patient web portals tethered to electronic medical records, disease-specific portals, health disparities, and health-related community web portals. RESULTS Although findings have not been uniformly positive, several studies of the effectiveness of health care system patient portals in chronic disease management have shown promising results with regard to patient outcomes. Patient web portals have also shown promising results in increasing adherence with screening recommendations. Racial and ethnic minorities, younger persons, and patients who are less educated or have lower health literacy have been found to be less likely to use patient portals. CONCLUSION Additional studies are needed of the utility and effectiveness of different elements of web portals for different patient populations. This should include additional diseases and health topics such as smoking cessation and weight management.
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Affiliation(s)
- Steven S Coughlin
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA
| | - Judith J Prochaska
- Department of Medicine, Stanford Prevention Research Center, Stanford University, Stanford, CA
| | - Lovoria B Williams
- Department of Biobehavioral Nursing, College of Nursing, Augusta University
| | - Gina M Besenyi
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA
| | - Vahé Heboyan
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA
| | | | - Wonsuk Yoo
- Institute of Public and Preventive Health, Augusta University, Augusta, GA, USA
| | - Gianluca De Leo
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA
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19
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Tutino GE, Yang WY, Li X, Li WH, Zhang YY, Guo XH, Luk AO, Yeung ROP, Yin JM, Ozaki R, So WY, Ma RCW, Ji LN, Kong APS, Weng JP, Ko GTC, Jia WP, Chan JCN. A multicentre demonstration project to evaluate the effectiveness and acceptability of the web-based Joint Asia Diabetes Evaluation (JADE) programme with or without nurse support in Chinese patients with Type 2 diabetes. Diabet Med 2017; 34:440-450. [PMID: 27278933 PMCID: PMC5324581 DOI: 10.1111/dme.13164] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/07/2016] [Indexed: 02/06/2023]
Abstract
AIMS To test the hypothesis that delivery of integrated care augmented by a web-based disease management programme and nurse coordinator would improve treatment target attainment and health-related behaviour. METHODS The web-based Joint Asia Diabetes Evaluation (JADE) and Diabetes Monitoring Database (DIAMOND) portals contain identical built-in protocols to integrate structured assessment, risk stratification, personalized reporting and decision support. The JADE portal contains an additional module to facilitate structured follow-up visits. Between January 2009 and September 2010, 3586 Chinese patients with Type 2 diabetes from six sites in China were randomized to DIAMOND (n = 1728) or JADE, plus nurse-coordinated follow-up visits (n = 1858) with comprehensive assessments at baseline and 12 months. The primary outcome was proportion of patients achieving ≥ 2 treatment targets (HbA1c < 53 mmol/mol (7%), blood pressure < 130/80 mmHg and LDL cholesterol < 2.6 mmol/l). RESULTS Of 3586 participants enrolled (mean age 57 years, 54% men, median disease duration 5 years), 2559 returned for repeat assessment after a median (interquartile range) follow-up of 12.5 (4.6) months. The proportion of participants attaining ≥ 2 treatment targets increased in both groups (JADE 40.6 to 50.0%; DIAMOND 38.2 to 50.8%) and there were similar absolute reductions in HbA1c [DIAMOND -8 mmol/mol vs JADE -7 mmol/mol (-0.69 vs -0.62%)] and LDL cholesterol (DIAMOND -0.32 mmol/l vs JADE -0.28 mmol/l), with no between-group difference. The JADE group was more likely to self-monitor blood glucose (50.5 vs 44.2%; P = 0.005) and had fewer defaulters (25.6 vs 32.0%; P < 0.001). CONCLUSIONS Integrated care augmented by information technology improved cardiometabolic control, with additional nurse contacts reducing the default rate and enhancing self-care. (Clinical trials registry no.: NCT01274364).
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Affiliation(s)
- G. E. Tutino
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - W. Y. Yang
- China‐Japan Friendship HospitalBeijingChina
| | - X. Li
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Asia Diabetes FoundationPrince of Wales HospitalHong Kong SARChina
| | - W. H. Li
- Peking Union HospitalBeijingChina
| | - Y. Y. Zhang
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Asia Diabetes FoundationPrince of Wales HospitalHong Kong SARChina
| | - X. H. Guo
- First HospitalPeking University HospitalBeijingChina
| | - A. O. Luk
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Asia Diabetes FoundationPrince of Wales HospitalHong Kong SARChina
| | - R. O. P. Yeung
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Asia Diabetes FoundationPrince of Wales HospitalHong Kong SARChina
| | - J. M. Yin
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Asia Diabetes FoundationPrince of Wales HospitalHong Kong SARChina
| | - R. Ozaki
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - W. Y. So
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - R. C. W. Ma
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - L. N. Ji
- Beijing People's HospitalBeijingChina
| | - A. P. S. Kong
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - J. P. Weng
- Third Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - G. T. C. Ko
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
| | - W. P. Jia
- Shanghai Sixth People's HospitalShanghaiChina
| | - J. C. N. Chan
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong KongPrince of Wales HospitalHong Kong SARChina
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20
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Coughlin SS, Carbone LD, Heboyan V, Williams LB, Hatzigeorgiou C, Rangachari P, De Leo G. Use of My Health eVet patient web portal among veterans seen for diabetes mellitus at a medical center in the southeastern United States. Mhealth 2017; 3:50. [PMID: 29354642 PMCID: PMC5762985 DOI: 10.21037/mhealth.2017.10.02] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 10/12/2017] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND An increasing number of studies have examined the use of information technology to improve diabetes care and patient self-management. The goal of the current study was to determine the number of veterans seen for diabetes at a large medical center in the southeastern region of the U.S. and to examine whether they had registered for VA's My HealtheVet patient web portal according to selected characteristics. METHODS Existing patient records were reviewed including My HealtheVet web portal registration by veterans treated for diabetes (ICD-10 code for type 2 diabetes) at the Charlie Norwood VAMC. Number of outpatient clinic patients seen for diabetes who had or had not registered for My HealtheVet were examined by age categories, sex, race, Hispanic ethnicity, and era of military service. RESULTS A total of 49,341 veterans receive care at the Charlie Norwood VAMC. Of those patients, 10,950 have been seen for diabetes. Of the 49,341 patients, 21,372 patients (43.3%) are using My HealtheVet and 10,465 patients (21.2%) have used secure messages. Of 10,950 diabetic patients, only 1,256 (11.5%) have registered for My HealtheVet. Women with diabetes were more likely to be registered for My HealtheVet than their male counterparts [13.92% vs. 11.24%; odds ratio (OR)=1.28; 95% confidence interval (CI): 1.05-1.55). Veterans with diabetes who served during WW II or the Korean War were less likely to use My HealtheVet than those who served during more recent eras (OR=0.33; 95% CI: 0.24-0.44). Use of the patient portal was highest among diabetic patients ages 51-55 years (15.6%). CONCLUSIONS A low percentage of Veterans with diabetes are active users of My HealtheVet. Studies are needed to identify My HealtheVet portal design features and veteran characteristics that will increase use of this patient portal which may improve diabetes care.
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Affiliation(s)
- Steven S. Coughlin
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA
- Charlie Norwood Veterans Affairs Medical Center, Augusta, GA, USA
| | - Laura D. Carbone
- Charlie Norwood Veterans Affairs Medical Center, Augusta, GA, USA
- Division of Rheumatology, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Vahé Heboyan
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA
| | - Lovoria B. Williams
- Department of Biobehavioral Nursing, College of Nursing, Augusta University, Augusta, GA, USA
| | - Christos Hatzigeorgiou
- Division of General Internal Medicine, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Pavani Rangachari
- Office of the Associate Dean for Practice and Community Health, College of Allied Health Sciences, Augusta University, Augusta, GA, USA
| | - Gianluca De Leo
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA
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Coughlin SS, Williams LB, Hatzigeorgiou C. A systematic review of studies of web portals for patients with diabetes mellitus. Mhealth 2017; 3:23. [PMID: 28736732 PMCID: PMC5505929 DOI: 10.21037/mhealth.2017.05.05] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Accepted: 05/26/2017] [Indexed: 11/06/2022] Open
Abstract
Patient web portals are password-protected online websites that offer patients 24-hour access to personal health information from anywhere with an Internet connection. Due to advances in health information technologies, there has been increasing interest among providers and researchers in patient web portals for use by patients with diabetes and other chronic conditions. This article, which is based upon bibliographic searches in PubMed, reviews web portals for patients with diabetes mellitus including patient web portals tethered to electronic medical records and web portals developed specifically for patients with diabetes. Twelve studies of the impact of patient web portals on the management of diabetes patients were identified. Three had a cross-sectional design, 1 employed mixed-methods, one had a matched-control design, 3 had a retrospective cohort design, and 5 were randomized controlled trials. Six (50%) of the studies examined web portals tethered to electronic medical records and the remainder were web portals developed specifically for diabetes patients. The results of this review suggest that secure messaging between adult diabetic patients and their clinician is associated with improved glycemic control. However, results from observational studies indicate that many diabetic patients do not take advantage of web portal features such as secure messaging, perhaps because of a lack of internet access or lack of experience in navigating web portal resources. Although results from randomized controlled trials provide stronger evidence of the efficacy of web portal use in improving glycemic control among diabetic patients, the number of trials is small and results from the trials have been mixed. Studies suggest that secure messaging between adult diabetic patients and their clinician is associated with improved glycemic control, but negative findings have also been reported. The number of randomized controlled trials that have examined the efficacy of web portal use in improving glycemic control among diabetic patients is still small. Additional research is needed to identify specific portal features that may impact quality of care or improve glycemic control.
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Affiliation(s)
- Steven S. Coughlin
- Department of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, Georgia
- Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
| | - Lovoria B. Williams
- Department of Biobehavioral Nursing, College of Nursing, Augusta University, Augusta, Georgia
| | - Christos Hatzigeorgiou
- Division of General Internal Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia
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Abstract
According to a 2010 national survey, 11 % of adults in China have diabetes, affecting 109.6 million individuals. The high prevalence of diabetes has been attributed to the aging of the population, the rapid adoption of energy-dense foods, and a reduction in physical activity. Collectively, these secular changes have created an obesogenic environment that can unmask diabetes in subjects with a genetic predisposition. The growing prevalence of maternal obesity, gestational diabetes, childhood obesity, and early-onset disease can lead to premature morbidity and mortality. Rising to meet these public health challenges, researchers in China have conducted randomized studies to demonstrate the benefits of lifestyle modification in preventing diabetes (the Da Qing Study), as well as that of team-based integrated care, using multiple strategies including peer support and information technology, in order to reduce hospitalizations, cardiovascular-renal complications, and premature deaths. With growing evidence supporting the benefits of these diabetes prevention and management programs, the next challenge is to use policies and systems to scale up the implementation of these programs through raising awareness, building capacity, and providing resources to reduce the human and socioeconomic burden of diabetes.
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Affiliation(s)
- Junmei Yin
- Department of Clinical Nutrition, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong
| | - Alice P S Kong
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, 9th floor, Lui Che Woo Clinical Science Building, Shatin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Juliana C N Chan
- Asia Diabetes Foundation, Prince of Wales Hospital, Shatin, Hong Kong.
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, 9th floor, Lui Che Woo Clinical Science Building, Shatin, Hong Kong.
- Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong.
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