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Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health
medRxiv - Endocrinology Pub Date : 2021-05-08 , DOI: 10.1101/2021.05.04.21256647 Johannes O. Ferstad , Jacqueline J. Vallon , Daniel Jun , Angela Gu , Anastasiya Vitko , Dianelys P. Morales , Jeannine Leverenz , Ming Yeh Lee , Brianna Leverenz , Christos Vasilakis , Esli Osmanlliu , Priya Prahalad , David M Maahs , Ramesh Johari , David Scheinker
medRxiv - Endocrinology Pub Date : 2021-05-08 , DOI: 10.1101/2021.05.04.21256647 Johannes O. Ferstad , Jacqueline J. Vallon , Daniel Jun , Angela Gu , Anastasiya Vitko , Dianelys P. Morales , Jeannine Leverenz , Ming Yeh Lee , Brianna Leverenz , Christos Vasilakis , Esli Osmanlliu , Priya Prahalad , David M Maahs , Ramesh Johari , David Scheinker
Objective: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review. Research Design and Methods: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review. Results: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2 +/- 0.20 to 1.3 +/- 0.24 minutes per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n=58) have associated 8.8 percentage points (pp) (95% CI = 0.6-16.9pp) greater time-in-range (70-180 mg/dL) glucoses compared to 25 control patients who did not qualify at twelve months after T1D onset. Conclusions: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range.
中文翻译:
通过持续的血糖监测和算法优先级对1型糖尿病的人群水平管理:精准的健康满足人群的健康需求
目的:利用远程医疗和通过连续血糖监测仪(CGM)数据审查对病人进行远程监测,开发并扩展具有算法功能的患者优先级,以改善拥有固定资源的儿科门诊1型糖尿病(T1D)的人群水平管理。研究设计和方法:我们使用CGM调整了T1D患者的共识血糖目标,以识别可解释的临床标准,以优先考虑患者的每周供应商审查。建立该标准是为了管理每周检查的患者数量,并确定最需要提供者联系的患者。我们开发了一个交互式仪表板来显示与优先检查的患者相关的CGM数据。结果:新标准和交互式仪表板的引入使远程和异步查看患者数据并与患者联系的糖尿病团队成员的平均时间减少了60%,从每分钟3.2 +/- 0.20到1.3 +/- 0.24分钟每周一次的病人。给定固定的资源进行审核,这相当于每周门诊量估计增加了147%。符合条件并接受远程复查(n = 58)的患者与25个对照组相比,在范围内的时间范围内(70-180 mg / dL)葡萄糖的关联时间长了8.8个百分点(pp)(95%CI = 0.6-16.9pp) T1D发作后十二个月不合格的患者。结论:通过算法启用的CGM对T1D患者进行优先级排序以进行异步远程审查,可以减少每位患者花费的提供者时间,并且可以缩短治疗时间。
更新日期:2021-05-09
中文翻译:
通过持续的血糖监测和算法优先级对1型糖尿病的人群水平管理:精准的健康满足人群的健康需求
目的:利用远程医疗和通过连续血糖监测仪(CGM)数据审查对病人进行远程监测,开发并扩展具有算法功能的患者优先级,以改善拥有固定资源的儿科门诊1型糖尿病(T1D)的人群水平管理。研究设计和方法:我们使用CGM调整了T1D患者的共识血糖目标,以识别可解释的临床标准,以优先考虑患者的每周供应商审查。建立该标准是为了管理每周检查的患者数量,并确定最需要提供者联系的患者。我们开发了一个交互式仪表板来显示与优先检查的患者相关的CGM数据。结果:新标准和交互式仪表板的引入使远程和异步查看患者数据并与患者联系的糖尿病团队成员的平均时间减少了60%,从每分钟3.2 +/- 0.20到1.3 +/- 0.24分钟每周一次的病人。给定固定的资源进行审核,这相当于每周门诊量估计增加了147%。符合条件并接受远程复查(n = 58)的患者与25个对照组相比,在范围内的时间范围内(70-180 mg / dL)葡萄糖的关联时间长了8.8个百分点(pp)(95%CI = 0.6-16.9pp) T1D发作后十二个月不合格的患者。结论:通过算法启用的CGM对T1D患者进行优先级排序以进行异步远程审查,可以减少每位患者花费的提供者时间,并且可以缩短治疗时间。