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Zhang K, Huang Q, Wang Q, Li C, Zheng Q, Li Z, Xu D, Xie C, Zhang M, Lin R. Telemedicine in Improving Glycemic Control Among Children and Adolescents With Type 1 Diabetes Mellitus: Systematic Review and Meta-Analysis. J Med Internet Res 2024; 26:e51538. [PMID: 38981114 PMCID: PMC11267117 DOI: 10.2196/51538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 02/28/2024] [Accepted: 05/21/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Type 1 diabetes mellitus (T1DM) is the most common chronic autoimmune disease among children and adolescents. Telemedicine has been widely used in the field of chronic disease management and can benefit patients with T1DM. However, existing studies lack high-level evidence related to the effectiveness of telemedicine for glycemic control in children and adolescents with T1DM. OBJECTIVE This study aims to systematically review the evidence on the effectiveness of telemedicine interventions compared with usual care on glycemic control among children and adolescents with T1DM. METHODS In this systematic review and meta-analysis, we searched PubMed, Cochrane Library, Embase, Web of Science (all databases), and CINAHL Complete from database inception to May 2023. We included randomized controlled trials (RCTs) that evaluated the effectiveness of a telemedicine intervention on glycemic control in children and adolescents with T1DM. In total, 2 independent reviewers performed the study selection and data extraction. Study quality was assessed using the Cochrane Risk of Bias 2 tool. Our primary outcome was glycated hemoglobin (HbA1c) levels. Secondary outcomes were quality of life, self-monitoring of blood glucose, the incidence of hypoglycemia, and cost-effectiveness. A random-effects model was used for this meta-analysis. RESULTS Overall, 20 RCTs (1704 participants from 12 countries) were included in the meta-analysis. Only 5% (1/20) of the studies were at high risk of bias. Compared to usual care, telemedicine was found to reduce HbA1c levels by 0.22 (95% CI -0.33 to -0.10; P<.001; I2=35%). There was an improvement in self-monitoring of blood glucose (mean difference [MD] 0.54, 95% CI -0.72 to 1.80; P=.40; I2=67.8%) and the incidence of hypoglycemia (MD -0.15, 95% CI -0.57 to 0.27; P=.49; I2=70.7%), although this was not statistically significant. Moreover, telemedicine had no convincing effect on the Diabetes Quality of Life for Youth score (impact of diabetes: P=.59; worries about diabetes: P=.71; satisfaction with diabetes: P=.68), but there was a statistically significant improvement in non-youth-specific quality of life (MD -0.24, 95% CI -0.45 to -0.02; P=.04; I2=0%). Subgroup analyses revealed that the effect of telemedicine on HbA1c levels appeared to be greater in studies involving children (MD -0.41, 95% CI -0.62 to -0.20; P<.001), studies that lasted <6 months (MD -0.32, 95% CI -0.48 to -0.17; P<.001), studies where providers used smartphone apps to communicate with patients (MD -0.37, 95% CI -0.53 to -0.21; P<.001), and studies with medication dose adjustment (MD -0.25, 95% CI -0.37 to -0.12; P<.001). CONCLUSIONS Telemedicine can reduce HbA1c levels and improve quality of life in children and adolescents with T1DM. Telemedicine should be regarded as a useful supplement to usual care to control HbA1c levels and a potentially cost-effective mode. Meanwhile, researchers should develop higher-quality RCTs using large samples that focus on hard clinical outcomes, cost-effectiveness, and quality of life.
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Affiliation(s)
- Kun Zhang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qiyuan Huang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qiaosong Wang
- School of Nursing, Fujian Medical University, Fuzhou, China
- Department of Nursing, The First Affiliated Hospital of Fujian Medical University, Fujian Medical University, Fuzhou, China
| | - Chengyang Li
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qirong Zheng
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Zhuoyue Li
- Department of Infectious diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Dan Xu
- Foreign Language Department, Xuzhou Medical University, Xuzhou, China
| | - Cuiling Xie
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Mingqi Zhang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Rongjin Lin
- School of Nursing, Fujian Medical University, Fuzhou, China
- Department of Nursing, The First Affiliated Hospital of Fujian Medical University, Fujian Medical University, Fuzhou, China
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Palmer BA, Soltys K, Zimmerman MB, Norris AW, Tsalikian E, Tansey MJ, Pinnaro CT. Diabetes Device Downloading: Benefits and Barriers Among Youth With Type 1 Diabetes. J Diabetes Sci Technol 2023; 17:381-389. [PMID: 34809477 PMCID: PMC10012364 DOI: 10.1177/19322968211059537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The majority of youth with type 1 diabetes (T1D) fail to meet glycemic targets despite increasing continuous glucose monitoring (CGM) use. We therefore aimed to determine the proportion of caregivers who review recent glycemic trends ("retrospective review") and make ensuant insulin adjustments based on this data ("retroactive insulin adjustments"). We additionally considered that fear of hypoglycemia and frequency of severe hypoglycemia would be associated with performing retrospective review. METHODS We conducted a cross-sectional survey of caregivers of youth with T1D, collecting demographics, diabetes technology usage, patterns of glucose data review/insulin dose self-adjustment, and Hypoglycemia Fear Survey (HFS). RESULTS Nineteen percent of eligible caregivers (191/1003) responded. Performing retrospective review was associated with younger child age (12.2 versus 15.4, P = .0001) and CGM use (92% versus 73%, P = .004), but was not associated with a significant improvement in child's HbA1c (7.89 versus 8.04, P = .65). Retrospective reviewers had significantly higher HFS-behavior scores (31.9 versus 27.7, P = .0002), which remained significantly higher when adjusted for child's age and CGM use (P = .005). Linear regression identified a significant negative association between HbA1c (%) and number of retroactive insulin adjustments (0.24 percent lower mean HbA1c per additional adjustment made, P = .02). CONCLUSIONS Retrospective glucose data review is associated with improved HbA1c when coupled with data-driven retroactive insulin adjustments. Barriers to data downloading existed even in this cohort of predominantly CGM-using T1D families.
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Affiliation(s)
- Benjamin A. Palmer
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | - Karissa Soltys
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | | | - Andrew W. Norris
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
| | - Eva Tsalikian
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | - Michael J. Tansey
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
| | - Catherina T. Pinnaro
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
- Catherina T. Pinnaro, MD, MS, Division of
Endocrinology and Diabetes, Stead Family Department of Pediatrics, The
University of Iowa, 216 MRC, 501 Newton Road, Iowa City, IA 52242, USA.
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Zafra‐Tanaka JH, Beran D, Bernabe‐Ortiz A. Health system responses for type 1 diabetes: A scoping review. Diabet Med 2022; 39:e14805. [PMID: 35124856 PMCID: PMC9306957 DOI: 10.1111/dme.14805] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 02/03/2022] [Indexed: 11/29/2022]
Abstract
AIMS The focus of health system interventions for noncommunicable diseases and diabetes focus mainly on primary health care responses. However, existing interventions are not necessarily adapted for the complex management of type 1 diabetes (T1DM). We aimed to identify and describe health system interventions which have been developed to improve the management of T1DM globally. METHODS We conducted a scoping review by searching MEDLINE, Embase, and Global Health using OVID for peer-review articles published in either English, Spanish, Portuguese or French in the last 10 years. We classified the intervention strategies according to the Effective Practice and Organization of Care (EPOC) taxonomy for health system interventions and the World Health Organization (WHO) health system building blocks. RESULTS This review identified 159 health system interventions to improve T1DM management. Over half of the studies focused only on children or adolescents with type 1 diabetes. Only a small fraction of the studies were conducted in low-and-middle income countries (LMICs). According to the EPOC taxonomy, the most frequently studied category was delivery arrangement interventions, while implementation strategies and financial arrangements were less frequently studied. Also, governance arrangements domains were not studied. The most common combination of intervention strategies included self-management with either telemedicine, use of information and smart home technologies. CONCLUSIONS There is a need to expand potential interventions to other EPOC strategies to assess their potential effect on health outcomes in people with T1DM, as well as to involve more LMIC settings as the impact may be greater in these settings.
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Affiliation(s)
- Jessica H. Zafra‐Tanaka
- CRONICAS Center of Excellence in Chronic DiseasesUniversidad Peruana Cayetano HerediaLimaPeru
- Division of Tropical and Humanitarian MedicineUniversity of Geneva and Geneva University HospitalsGenevaSwitzerland
| | - David Beran
- Division of Tropical and Humanitarian MedicineUniversity of Geneva and Geneva University HospitalsGenevaSwitzerland
| | - Antonio Bernabe‐Ortiz
- CRONICAS Center of Excellence in Chronic DiseasesUniversidad Peruana Cayetano HerediaLimaPeru
- Universidad Científica del SurLimaPeru
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Meneghetti L, Dassau E, Doyle FJ, Del Favero S. Machine Learning-Based Anomaly Detection Algorithms to Alert Patients Using Sensor Augmented Pump of Infusion Site Failures. J Diabetes Sci Technol 2022; 16:641-648. [PMID: 33686873 PMCID: PMC9294564 DOI: 10.1177/1932296821997854] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Personal insulin pumps have shown to be effective in improving the quality of therapy for people with type 1 diabetes (T1D). However, the safety of this technology is limited by the possible infusion site failures, which are linked with hyperglycemia and ketoacidosis. Thanks to the large availability of collected data provided by modern therapeutic technologies, machine learning algorithms have the potential to provide new way to identify failures early and avert adverse events. METHODS A clinical dataset (N = 20) is used to evaluate a novel method for detecting real-time infusion site failures using unsupervised anomaly detection algorithms, previously proposed and developed on in-silico data. An adapted feature engineering procedure is introduced to make the method able to operate in the absence of a closed-loop (CL) system and meal announcements. RESULTS In the optimal configuration, we obtained a performance of 0.75 Sensitivity (15 out of 20 total failures detected) and 0.08 FP/day, outperforming previously proposed literature algorithms. The algorithm was able to anticipate the replacement of the malfunctioning infusion sets by ~2 h on average. CONCLUSIONS On the considered dataset, the proposed algorithm showed the potential to improve the safety of patients treated with sensor-augmented pump systems.
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Affiliation(s)
- Lorenzo Meneghetti
- Department of Information Engineering,
University of Padua, Padua, Italy
| | - Eyal Dassau
- Harvard John A. Paulson School of
Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Francis J. Doyle
- Harvard John A. Paulson School of
Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Simone Del Favero
- Department of Information Engineering,
University of Padua, Padua, Italy
- Simone Del Favero, PhD, Department of
Information Engineering, University of Padova, Via Gradenigo 6/b, Padova (PD)
35131, Italy.
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5
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Maahs DM, Addala A, Shalitin S. Diabetes Technology and Therapy in the Pediatric Age Group. Diabetes Technol Ther 2022; 24:S107-S128. [PMID: 35475702 DOI: 10.1089/dia.2022.2507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- David M Maahs
- Department of Pediatrics, Division of Endocrinology and Diabetes, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
- Department of Health Research and Policy (Epidemiology), Stanford University, Stanford, CA
| | - Ananta Addala
- Department of Pediatrics, Division of Endocrinology and Diabetes, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
| | - Shlomit Shalitin
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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6
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Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes. Nat Med 2020; 26:1380-1384. [DOI: 10.1038/s41591-020-1045-7] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 08/03/2020] [Indexed: 01/29/2023]
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Abstract
BACKGROUND Advances in pump technology have increased the popularity of this treatment modality among patients with type 1 diabetes and recently also among patients with type 2 diabetes. AREAS OF UNCERTAINTY Four decades after the incorporation of the insulin pump in clinical use, questions regarding its efficacy, occurrence rate of short-term complications as hypoglycemia and diabetes ketoacidosis, timing of pump initiation, and selected populations for use remain unanswered. DATA SOURCES A review of the literature was performed using the PubMed database to identify all articles published up till December 2018, with the search terms including insulin pump therapy/continuous subcutaneous insulin delivery. The Cochrane database was searched for meta-analysis evaluating controlled randomized trials. Consensuses guidelines published by the International Society for Pediatric and Adolescent Diabetes, American Diabetes Association, and Advanced Technologies and Treatments for Diabetes year books were additionally reviewed for relevant cited articles. THERAPEUTIC ADVANCES Insulin pump therapy offers flexible management of diabetes. It enables adjustment of basal insulin to daily requirements and circadian needs, offers more precise treatment for meals and physical activity, and, when integrated with continuous glucose monitoring, allows glucose responsive insulin delivery. The ability to download and transmit data for analysis allow for treatment optimization. Newer pumps are simple to operate and increase user experience. Studies support the efficacy of pump therapy in improving glycemic control and reducing the occurrence of hypoglycemia without increasing episodes of diabetes ketoacidosis. They also improve quality of life. Recent evidence suggests a role for pump therapy in reducing microvascular and macrovascular diabetes-related complications. CONCLUSIONS Insulin pump therapy appears to be effective and safe in people with T1D regardless of age. Future advancements will include incorporation of closed loop and various decision support systems to aid and improve metabolic control and quality of life.
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9
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Nimri R, Dassau E, Segall T, Muller I, Bratina N, Kordonouri O, Bello R, Biester T, Dovc K, Tenenbaum A, Brener A, Šimunović M, Sakka SD, Nevo Shenker M, Passone CG, Rutigliano I, Tinti D, Bonura C, Caiulo S, Ruszala A, Piccini B, Giri D, Stein R, Rabbone I, Bruzzi P, Omladič JŠ, Steele C, Beccuti G, Yackobovitch-Gavan M, Battelino T, Danne T, Atlas E, Phillip M. Adjusting insulin doses in patients with type 1 diabetes who use insulin pump and continuous glucose monitoring: Variations among countries and physicians. Diabetes Obes Metab 2018; 20:2458-2466. [PMID: 29885025 DOI: 10.1111/dom.13408] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Revised: 05/27/2018] [Accepted: 06/05/2018] [Indexed: 12/14/2022]
Abstract
AIMS To evaluate physicians' adjustments of insulin pump settings based on continuous glucose monitoring (CGM) for patients with type 1 diabetes and to compare these to automated insulin dose adjustments. METHODS A total of 26 physicians from 16 centres in Europe, Israel and South America participated in the study. All were asked to adjust insulin dosing based on insulin pump, CGM and glucometer downloads of 15 patients (mean age 16.2 ± 4.3 years, six female, mean glycated haemoglobin 8.3 ± 0.9% [66.8 ± 7.3 mmol/mol]) gathered over a 3-week period. Recommendations were compared for the relative changes in the basal, carbohydrate to insulin ratio (CR) and correction factor (CF) plans among physicians and among centres and also between the physicians and an automated algorithm, the Advisor Pro (DreaMed Diabetes Ltd, Petah Tikva, Israel). Study endpoints were the percentage of comparison points for which there was full agreement on the trend of insulin dose adjustments (same trend), partial agreement (increase/decrease vs no change) and full disagreement (opposite trend). RESULTS The percentages for full agreement between physicians on the trend of insulin adjustments of the basal, CR and CF plans were 41 ± 9%, 45 ± 11% and 45.5 ± 13%, and for complete disagreement they were 12 ± 7%, 9.5 ± 7% and 10 ± 8%, respectively. Significantly similar results were found between the physicians and the automated algorithm. The algorithm magnitude of insulin dose change was at least equal to or less than that proposed by the physicians. CONCLUSIONS Physicians provide different insulin dose recommendations based on the same datasets. The automated advice of the Advisor Pro did not differ significantly from the advice given by the physicians in the direction or magnitude of the insulin dosing.
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Affiliation(s)
- Revital Nimri
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
| | | | - Ido Muller
- DreaMed Diabetes Ltd, Petah Tikva, Israel
| | - Natasa Bratina
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, Ljubljana, Slovenia
| | - Olga Kordonouri
- Diabetes Centre for Children and Adolescents, Auf der Bult, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Rachel Bello
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Torben Biester
- Diabetes Centre for Children and Adolescents, Auf der Bult, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, Ljubljana, Slovenia
| | - Ariel Tenenbaum
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Avivit Brener
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Marko Šimunović
- Department of Pediatrics, University Hospital Centre Split, Split, Croatia
| | - Sophia D Sakka
- Department of Endocrinology and Diabetes, Evelina London Children's Hospital, London, UK
| | - Michal Nevo Shenker
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | | | - Irene Rutigliano
- Pediatrics IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Davide Tinti
- Centre of Pediatric Diabetes, Department of Pediatrics, University of Turin, Turin, Italy
| | - Clara Bonura
- San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Silvana Caiulo
- San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Anna Ruszala
- Department of Pediatric and Adolescent Endocrinology, Institute of Pediatrics, Jagiellonian University Medical College, Krakow, Poland
| | - Barbara Piccini
- Diabetology Unit, Meyer Children's Hospital, Florence, Italy
| | - Dinesh Giri
- Department of Paediatric Endocrinology and Diabetes, Bristol Royal Hospital for Children, Bristol, UK
| | - Ronnie Stein
- Paediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Sourasky Medical Centre, Tel Aviv, Israel
| | - Ivana Rabbone
- Centre of Pediatric Diabetes, Department of Pediatrics, University of Turin, Turin, Italy
| | - Patrizia Bruzzi
- Departments of Medical and Surgical Sciences of Mothers, Children and Adults, Azienda Ospedaliero-Univeristaria of Modena Policlinico, Paediatric Unit, Modena, Italy
| | - Jasna Šuput Omladič
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, Ljubljana, Slovenia
| | - Caroline Steele
- Paediatric Endocrinology and Diabetes, Leeds Children's Hospital, Leeds, UK
| | - Guglielmo Beccuti
- Division of Endocrinology, Diabetes and Metabolism, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Michal Yackobovitch-Gavan
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Thomas Danne
- Diabetes Centre for Children and Adolescents, Auf der Bult, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Eran Atlas
- DreaMed Diabetes Ltd, Petah Tikva, Israel
| | - Moshe Phillip
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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10
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Gandrud L, Altan A, Buzinec P, Hemphill J, Chatterton J, Kelley T, Vojta D. Intensive remote monitoring versus conventional care in type 1 diabetes: A randomized controlled trial. Pediatr Diabetes 2018; 19:1086-1093. [PMID: 29464831 DOI: 10.1111/pedi.12654] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 12/22/2017] [Accepted: 01/24/2018] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE While frequent contact with diabetes care providers may improve glycemic control among patients with type 1 diabetes (T1D), in-person visits are labor-intensive and costly. This study was conducted to assess the impact of an intensive remote therapy (IRT) intervention for pediatric patients with T1D. METHODS Pediatric patients with T1D were randomized to IRT or conventional care (CC) for 6 months. Both cohorts continued routine quarterly clinic visits and uploaded device data; for the IRT cohort, data were reviewed and patients were contacted if regimen adjustments were indicated. Glycated hemoglobin (HbA1c) change from baseline was assessed at 6 and 9 months. Diabetes-related quality of life (QoL), healthcare services utilization, and hypoglycemic events were also tracked. RESULTS Among 117 enrollees (60 IRT, 57 CC), mean (SD) 6-month %HbA1c change for IRT vs CC was -0.34 (0.85) (-3.7 mmol/mol) vs -0.05 (0.74) (-0.5 mmol/mol) overall (P = .071); -0.15 (0.67) (1.6 mmol/mol) vs -0.02 (0.66) (0.2 mmol/mol) for ages 8 to 12 (P = .541); and -0.50 (0.95) (-5.5 mmol/mol) vs -0.06 (0.80) (-0.7 mmol/mol) for ages 13 to 17 (P = .056). Diabetes-related QoL increased by 6.5 and 1.3 points for IRT and CC, respectively (P = .062). Three months after intervention cessation, %HbA1c changed minimally among treated children aged 8 to 12 but increased by 0.22 (0.89) (2.4 mmol/mol) among those aged 13 to 17. CONCLUSIONS IRT substantially affected diabetes metrics and improved QoL among pediatric patients with T1D. Adolescents experienced a stronger treatment effect, but had difficulty in sustaining improved control after intervention cessation.
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Affiliation(s)
| | | | | | | | | | - Tina Kelley
- UnitedHealth Group Research & Development, Minnetonka, Minnesota
| | - Deneen Vojta
- UnitedHealth Group Research & Development, Minnetonka, Minnesota
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Tao D, Wang T, Wang T, Liu S, Qu X. Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials. J Am Med Inform Assoc 2018; 24:1014-1023. [PMID: 28340030 DOI: 10.1093/jamia/ocx014] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 02/09/2017] [Indexed: 12/23/2022] Open
Abstract
Objective To reveal the effects of consumer-oriented health information technologies (CHITs) on patient outcomes in diabetes management over time through systematic review and meta-analysis. Methods We searched 5 electronic databases (from database inception to July 2016) for studies that reported on randomized controlled trials examining the effects of CHITs on glycemic control and other patient outcomes in diabetes management. Data were analyzed using either meta-analysis or a narrative synthesis approach. Results Eighty randomized controlled trial studies, representing 87 individual trials, were identified and included for analysis. Overall, the meta-analysis showed that the use of CHITs resulted in significant improvement in glycemic control compared to usual care (standardized mean difference = -0.31%, 95% confidence interval -0.38 to -0.23, P < .001) in patients with diabetes. Specifically, improvement in glycemic control was significant at intervention durations of 3, 6, 8, 9, 12, 15, 30, and 60 months, while no significant differences were found at other time points reported. The narrative synthesis provided mixed effects of CHITs on other clinical, psychosocial, behavioral, and knowledge outcomes. Conclusions The use of CHITs appears to be more effective than usual care in improving glycemic control for patients with diabetes. However, their effectiveness did not remain consistent over time and in other patient outcomes. Further efforts are required to examine long-term effects of CHITs and to explore factors that can moderate the effects over time.
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Affiliation(s)
- Da Tao
- Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
| | - Tieyan Wang
- School of Management, Xi'an Polytechnic University, Xi'an, China
| | - Tieshan Wang
- School of Management, Xi'an Polytechnic University, Xi'an, China
| | - Shuang Liu
- Marine Human Factors Engineering Lab, China Institute of Marine Technology and Economy, Beijing, China
| | - Xingda Qu
- Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
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Petrovski G, Zivkovic M. Impact of Facebook on Glucose Control in Type 1 Diabetes: A Three-Year Cohort Study. JMIR Diabetes 2017; 2:e9. [PMID: 30291064 PMCID: PMC6238860 DOI: 10.2196/diabetes.7693] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 04/22/2017] [Accepted: 04/24/2017] [Indexed: 11/13/2022] Open
Abstract
Background As the world is changing, traditional health care services should be adapted for the new era of technology and the Internet. One of the possible ways for communication between health care providers and patients is social media. There are several benefits of social media in health: increased interactions with others; more available and shared information; increased accessibility; social or emotional support. Objective The aim of this study was to evaluate the results of Facebook and CareLink software as a possible Internet tool to improve diabetes control in type 1 diabetes patients using a sensor augmented pump. Methods A total of 67 adolescents with type 1 diabetes and in the age range of 14-23 years were randomized in 2 groups: (1) Traditional group and (2) Internet group. In the traditional group, 34 patients were treated using standard medical protocol with regular clinic visits, where data were uploaded at the clinic and interventions (pump settings-basal bolus insulin and education) were delivered to the patient. In the Internet group, 33 patients were treated using Facebook and CareLink software (Medtronic Diabetes) on a monthly basis, where the data were uploaded by the patient at home and interventions (same as traditional group) were delivered via Facebook (written reports and chats). Both the traditional and Internet group had regular visits every 3 months with standard medical protocol. Glycosylated hemoglobin (HbA1c) was obtained before and every 3 months during the study for a 3-year-period. Results The improvement in glucose control was found in both groups: 7.9% (SD 1.4) [62.8 mmol/mol (SD 12.9)] to 6.9% (SD 1.2) [51.9 mmol/mol (SD 10.8)] in the traditional group, and 7.8% (SD 1.8) [61.7 mmol/mol (SD 17.2)] to 6.7% (SD 1.8) [49.7 mmol/mol (SD 17.3)] in the Internet group). Significant improvement of HbA1c (P<.05) was found in favor of the Internet group. Conclusions Social media such as Facebook as a tool can assist in standard medical care to improve glucose control in a long term period in adolescents with type 1 diabetes using insulin pump therapy.
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Affiliation(s)
- Goran Petrovski
- University Clinic of Endocrinology and Diabetes, Center for Insulin Pump and Sensor, University Ss. Cyril and Methodius, Skopje, The Former Yugoslav Republic Of Macedonia
| | - Marija Zivkovic
- University Clinic of Endocrinology and Diabetes, Center for Insulin Pump and Sensor, University Ss. Cyril and Methodius, Skopje, The Former Yugoslav Republic Of Macedonia
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13
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Abstract
The glycemic goals of pregnancy are very narrow to reduce excess risks for numerous maternal and fetal complications. Continuous glucose monitors (CGMs) may help women achieve glucose goals and reduce hypoglycemia. CGM use has been found to be safe and effective in pregnancies associated with diabetes. CGM use can accurately identify glycemic patterns among women with and without diabetes in pregnancy. The data on the effects of CGM use on maternal and fetal outcomes are conflicting. Using CGMs in conjunction with continuous subcutaneous insulin infusion therapy in pregnancies complicated by diabetes may improve outcomes. There are limitations of CGM use that affect patients in and outside of pregnancy, as well as specific barriers that only affect pregnant women. Of importance, CGM use does not replace standard clinical care, but may be used an adjunctive tool in pregnancy. CGM remote monitoring in pregnancy is an understudied field. In this study, we review the studies on CGM use in pregnancy.
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Affiliation(s)
- Sarit Polsky
- Barbara Davis Center for Diabetes, University of Colorado Denver , Aurora, Colorado
| | - Rachel Garcetti
- Barbara Davis Center for Diabetes, University of Colorado Denver , Aurora, Colorado
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14
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Lee SWH, Ooi L, Lai YK. Telemedicine for the Management of Glycemic Control and Clinical Outcomes of Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Studies. Front Pharmacol 2017; 8:330. [PMID: 28611672 PMCID: PMC5447671 DOI: 10.3389/fphar.2017.00330] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 05/16/2017] [Indexed: 12/31/2022] Open
Abstract
Importance: Telemedicine has been shown to be an efficient and effective means of providing care to patients with chronic disease especially in remote and undeserved regions, by improving access to care and reduce healthcare cost. However, the evidence surrounding its applicability in type 1 diabetes remains scarce and conflicting. Objective: To synthesize evidence and quantify the effectiveness of telemedicine interventions for the management of glycemic and clinical outcomes in type 1 diabetes patients, relative to comparator conditions. Data Sources: MEDLINE, EMBASE, Cochrane Library, Web of Science, PsycINFO, and CINAHL were searched for published articles since inception until December 2016. Study Selection: Original articles reporting the results of randomized controlled studies on the effectiveness of telemedicine in people with type 1 diabetes were included. Data Extraction and Synthesis: Two reviewers independently extracted data, assessed quality, and strength of evidence. Interventions were categorized based upon the telemedicine focus (monitoring, education, consultation, case-management, and peer mentoring). Main Outcome and Measure: Absolute change in glycosylated hemoglobin A1c (HbA1c) from baseline to follow-up assessment. Results: A total of 38 studies described in 41 articles were identified. Positive effects on glycemic control were noted with studies examining telemedicine, with a mean reduction of 0.18% at the end of intervention. Studies with longer duration (>6 months) who had recruited patients with a higher baseline HbA1c (≥9%) were associated with larger effects. Telemedicine interventions that involve individualized assessments, audit with feedback and skill building were also more effective in improving glycemic control. However, no benefits were observed on blood pressure, lipids, weight, quality of life, and adverse events. Conclusions and Relevance: There is insufficient evidence to support telemedicine use for glycemic control and other clinically relevant outcome among patients with type 1 diabetes.
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Affiliation(s)
- Shaun W H Lee
- School of Pharmacy, Monash University MalaysiaBandar Sunway, Malaysia
| | - Leanne Ooi
- School of Pharmacy, Monash University MalaysiaBandar Sunway, Malaysia
| | - Yin K Lai
- Faculty of Pharmacy, UCSI UniversityKuala Lumpur, Malaysia
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15
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Clements MA, Staggs VS. A Mobile App for Synchronizing Glucometer Data: Impact on Adherence and Glycemic Control Among Youths With Type 1 Diabetes in Routine Care. J Diabetes Sci Technol 2017; 11:461-467. [PMID: 28745097 PMCID: PMC5505434 DOI: 10.1177/1932296817691302] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Many individuals with type 1 diabetes (T1D) upload and review blood glucose data between clinic visits. Mobile phone applications that receive data from a "connected" glucometer and that support pattern management are available and have the capacity to make data upload and review less burdensome. Whether mobile apps can improve diabetes self-management among individuals with type 1 diabetes remains unknown. METHOD We analyzed retrospective data on 81 youths with T1D who were trained to use a glucometer-connected mobile app in their self-management. To assess the effect of glucometer synchronization ("sync") rate on hemoglobin A1c (HbA1c), mean blood glucose (mBG), and daily frequency of SMBG, we regressed those clinical outcomes on the frequency of glucometer syncs with the mobile app after controlling for other clinical care variables. RESULTS Median age was 14.0 (IQR 10.4-15.9) years, median duration of diabetes was 4.9 (2.7, 7.5) years, and median baseline HbA1c was 8.6% (7.9, 9.8). The sample was 49% male and 86% white. Youths with T1D synchronized glucometer data with the mobile app an average of 0.22 times per week (range 0-2.25). The glucometer sync rate did not have a statistically significant association with HbA1c or mean BG; in contrast, data sync frequency was associated with the frequency of self-monitoring of blood glucose (SMBG) such that each additional sync was associated with a 2.3-fold increase in SMBG frequency ( P < .01). CONCLUSION A glucometer-connected mobile app may increase an individual's engagement with other aspects of care (eg, SMBG frequency). Whether diabetes device-connected mobile apps can improve glycemic control remains to be determined.
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Affiliation(s)
- Mark A. Clements
- Children’s Mercy Hospital, Center for Children’s Healthy Lifestyles & Nutrition, University of Missouri–Kansas City, University of Kansas Medical Center, Kansas City, MO, USA
- Mark A. Clements, MD, PhD, CPI, FAAP, Children’s Mercy Hospital, Center for Children’s Healthy Lifestyles & Nutrition, University of Missouri–Kansas City, University of Kansas Medical Center, 2401 Gillham Rd, Kansas City, MO, 64108, USA.
| | - Vincent S. Staggs
- Children’s Mercy Hospital, University of Missouri–Kansas City, Health Services & Outcomes Research, Kansas City, MO, USA
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16
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Neinstein A, Wong J, Look H, Arbiter B, Quirk K, McCanne S, Sun Y, Blum M, Adi S. A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management. J Am Med Inform Assoc 2015; 23:324-32. [PMID: 26338218 PMCID: PMC4784555 DOI: 10.1093/jamia/ocv104] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Accepted: 05/27/2015] [Indexed: 01/22/2023] Open
Abstract
Objective Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. Materials and Methods An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. Results Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application (“app”), Blip, to visualize the data. Tidepool’s software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. Discussion By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. Conclusion The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool’s open source, cloud model for health data interoperability is applicable to other healthcare use cases.
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Affiliation(s)
- Aaron Neinstein
- Department of Medicine and Center for Digital Health Innovation, University of California, San Francisco, CA, USA
| | - Jenise Wong
- Department of Pediatrics and Madison Clinic for Pediatric Diabetes, University of California, San Francisco, CA, USA
| | | | | | | | | | - Yao Sun
- Department of Pediatrics, University of California, San Francisco, CA, USA
| | - Michael Blum
- Department of Medicine and Center for Digital Health Innovation, University of California, San Francisco, CA, USA
| | - Saleh Adi
- Department of Pediatrics and Madison Clinic for Pediatric Diabetes, University of California, San Francisco, CA, USA
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17
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Wong JC, Neinstein AB, Spindler M, Adi S. A Minority of Patients with Type 1 Diabetes Routinely Downloads and Retrospectively Reviews Device Data. Diabetes Technol Ther 2015; 17:555-62. [PMID: 26133226 PMCID: PMC4529086 DOI: 10.1089/dia.2014.0413] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND In type 1 diabetes (T1D), periodic review of blood glucose and insulin dosing should be performed, but it is not known how often patients review these data on their own. We describe the proportion of patients with T1D who routinely downloaded and reviewed their data at home. MATERIALS AND METHODS A cross-sectional survey of 155 adults and 185 caregivers of children with T1D at a single academic institution was performed. "Routine Downloaders" (downloaded four or more times in the past year) were also considered "Routine Reviewers" if they reviewed their data most of the time they downloaded from devices. Logistic regression was used to identify factors associated with being a Routine Reviewer. RESULTS Only 31% of adults and 56% of caregivers reported ever downloading data from one or more devices, whereas 20% and 40%, respectively, were considered Routine Downloaders. Only 12% of adults and 27% of caregivers were Routine Reviewers. Mean hemoglobin A1c was lower in Routine Reviewers compared with non-Routine Reviewers (7.2±1.0% vs. 8.1±1.6% [P=0.03] in adults and 7.8±1.4% vs. 8.6±1.7% [P=0.001] in children). In adjusted analysis of adults, the odds ratio of being a Routine Reviewer of one or more devices for every 10-year increase in age was 1.5 (95% confidence interval, 1.1, 2.1 [P=0.02]). For every 10 years since diabetes diagnosis, the odds ratio of being a Routine Reviewer was 1.7 (95% confidence interval, 1.2, 2.4 [P=0.01]). For caregivers, there were no statistically significant factors associated with being a Routine Reviewer. CONCLUSIONS A minority of T1D patients routinely downloads and reviews data from their devices on their own. Further research is needed to understand obstacles, provide better education and tools for self-review, and determine if patient self-review is associated with improved glycemic control.
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Affiliation(s)
- Jenise C. Wong
- Division of Endocrinology, Department of Pediatrics and the Madison Clinic for Pediatric Diabetes, University of California San Francisco, San Francisco, California
| | - Aaron B. Neinstein
- Division of Endocrinology and Metabolism, Department of Medicine and Center for Digital Health Innovation, University of California San Francisco, San Francisco, California
| | - Matthew Spindler
- Division of Endocrinology, Department of Pediatrics and the Madison Clinic for Pediatric Diabetes, University of California San Francisco, San Francisco, California
| | - Saleh Adi
- Division of Endocrinology, Department of Pediatrics and the Madison Clinic for Pediatric Diabetes, University of California San Francisco, San Francisco, California
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18
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Balkhi AM, Reid AM, Westen SC, Olsen B, Janicke DM, Geffken GR. Telehealth interventions to reduce management complications in type 1 diabetes: A review. World J Diabetes 2015; 6:371-379. [PMID: 25897348 PMCID: PMC4398894 DOI: 10.4239/wjd.v6.i3.371] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2014] [Revised: 12/20/2014] [Accepted: 01/20/2015] [Indexed: 02/05/2023] Open
Abstract
Type 1 diabetes is a chronic illness with a high burden of care. While effective interventions and recommendations for diabetes care exist, the intensive nature of diabetes management makes compliance difficult. This is especially true in children and adolescents as they have unique psychosocial and diabetes needs. Despite the development of effective in-person interventions targeting improving self-management and ameliorating psychosocial difficulties there are still a number of barriers to implementing these interventions, namely time, cost, and access. Telehealth interventions allow for the dissemination of these interventions to a broader audience. Self-management and psychosocial telehealth interventions are reviewed with a special emphasis on mobile phone and internet based technology use. While efficacy has been demonstrated in a number of telehealth interventions with improved cost effectiveness over in-person interventions, many challenges remain including high participant attrition and difficulties with receiving reimbursement for services rendered. These and other challenges are discussed with recommendations for researchers and telehealth providers provided.
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19
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Bratina N, Shalitin S, Phillip M, Battelino T. Type 1 Diabetes in the Young: Organization of Two National Centers in Israel and Slovenia. Zdr Varst 2015; 54:139-45. [PMID: 27646921 PMCID: PMC4820167 DOI: 10.1515/sjph-2015-0021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 02/03/2015] [Indexed: 01/25/2023] Open
Abstract
Type 1 diabetes is a chronic autoimmune disease that affects mainly young people. In the last 50 years, a steady increase of the T1D incidence in the young is reported worldwide, with an average 4 % increase annually. In addition, the mean age at the diagnosis is decreasing. Studies show that good metabolic control is important not only for delaying the chronic complications of diabetes but also for improving the quality of life of patients and their families. Continuous education, together with modern technology, is crucial in achieving these goals. Longitudinal data on glycated hemoglobin (HbA1c), along with the data on severe hypoglycemia and severe diabetic ketoacidosis, can describe the quality of care in a defined population. Two national reference diabetes centres taking care of children, adolescents and young adults with diabetes in Israel and Slovenia are described.
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Affiliation(s)
- Nataša Bratina
- University Children's Hospital, Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, Bohoriceva 20, 1000 Ljubljana, Slovenia
| | - Shlomit Shalitin
- The Jesse Z. and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel,14 Kaplan Street, Petah Tikva 4920235, Israel
| | - Moshe Phillip
- The Jesse Z. and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel,14 Kaplan Street, Petah Tikva 4920235, Israel
| | - Tadej Battelino
- University Children's Hospital, Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, Bohoriceva 20, 1000 Ljubljana, Slovenia; University of Ljubljana, Faculty of Medicine, Vrazov trg 2, 1000 Ljubljana, Slovenia
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20
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