Improving care for hypertension and diabetes in india by addition of clinical decision support system and task shifting in the national NCD program: I-TREC model of care.
Improving care for hypertension and diabetes in india by addition of clinical decision support system and task shifting in the national NCD program: I-TREC model of care.
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DOI：
10.1186/s12913-022-08025-y
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发表时间：
2022-05-23
影响因子：
2.8
通讯作者：
Tandon, Nikhil
中科院分区：
文献类型：
--
作者：
Jindal, Devraj;Sharma, Hanspria;Gupta, Yashdeep;Ajay, Vamadevan S.;Roy, Ambuj;Sharma, Rakshit;Ali, Mumtaj;Jarhyan, Prashant;Gupta, Priti;Venkateshmurthy, Nikhil Srinivasapura;Ali, Mohammed K.;Narayan, K. M. Venkat;Prabhakaran, Dorairaj;Weber, Mary Beth;Mohan, Sailesh;Patel, Shivani A.;Tandon, Nikhil
关键词：
高血压和糖尿病日益加重的负担是印度卫生系统面临的主要公共卫生挑战之一。临床决策支持系统（CDSS），协助定制的循证管理方法结合从更专业的任务转移到不太专业的供应商可以一起提高计划的影响。我们寻求将技术“CDSS”和战略“任务转移”纳入印度政府（GoI）综合初级卫生保健（CPHC）倡议下的非传染性疾病（NCD）系统，以增强该计划的影响力，以解决印度日益增长的高血压和糖尿病负担。我们开发了一种护理模式“I-TREC”，完全校准，以便在印度旁遮普纳加尔区沙希德·巴加特·辛格（SBS）的一个街区的所有设施类型（初级卫生中心、社区卫生中心和地区医院）的当前卫生系统中实施。我们开展了学术-社区合作，将CDSS与任务转移相结合，纳入GoI CPHC-NCD系统，这是一个帮助医疗保健提供者记录患者信息以进行常规NCD护理的平台。学术合作伙伴开发了临床算法，修订了临床工作流程，并与政府和技术合作伙伴进行了迭代合作和咨询，以将CDSS纳入现有系统。支持CDSS的GoI CPHC-NCD系统为高血压和糖尿病提供循证建议;基于阈值的提示，以确保跨卫生设施的转诊机制;集成患者数据库，并通过工作流程管理和仪表板警报进行护理协调。为了实现有效的实施，对患者工作流程进行了修改，技术使用的支点从医生转移到护士。I-TREC护理模式旨在在全国范围内适用，目前正在印度旁遮普邦的一个街区进行试点。I-TREC的经验教训将为其他公共卫生专家提供路线图，以整合和调整他们在国家一级的干预措施。CTRI/2020/01/022723。在线版本包含补充材料，可通过10.1186/s12913-022-08025-y获得。
The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology “CDSS” and a strategy “Task-shifting” within the Government of India’s (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program’s impact to address the growing burden of hypertension and diabetes in India. We developed a model of care “I-TREC” entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system. The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse. Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level. CTRI/2020/01/022723. The online version contains supplementary material available at 10.1186/s12913-022-08025-y.
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影响因子：
2.9
作者：
Jha, Dilip;Gupta, Priti;Prabhakaran, Dorairaj
通讯作者：
Prabhakaran, Dorairaj
影响因子：
39
作者：
Geldsetzer, Pascal;Manne-Goehler, Jennifer;Atun, Rifat
通讯作者：
Atun, Rifat
影响因子：
3.7
作者：
Jindal, Devraj;Roy, Ambuj;Tandon, Nikhil
通讯作者：
Tandon, Nikhil
DOI：
10.1016/s2214-109x(20)30449-6
发表时间：
2021-03
期刊：
The Lancet. Global health
影响因子：
--
作者：
Maria JL;Anand TN;Dona B;Prinu J;Prabhakaran D;Jeemon P
通讯作者：
Jeemon P
影响因子：
37.8
作者：
Prabhakaran, Dorairaj;Jha, Dilip;Patel, Vikram
通讯作者：
Patel, Vikram