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

Devraj Jindal, Hanspria Sharma, Yashdeep Gupta, Vamadevan S Ajay, Ambuj Roy, Rakshit Sharma, Mumtaj Ali, Prashant Jarhyan, Priti Gupta, Nikhil Srinivasapura Venkateshmurthy, Mohammed K Ali, K M Venkat Narayan, Dorairaj Prabhakaran, Mary Beth Weber, Sailesh Mohan, Shivani A Patel, Nikhil Tandon, Devraj Jindal, Hanspria Sharma, Yashdeep Gupta, Vamadevan S Ajay, Ambuj Roy, Rakshit Sharma, Mumtaj Ali, Prashant Jarhyan, Priti Gupta, Nikhil Srinivasapura Venkateshmurthy, Mohammed K Ali, K M Venkat Narayan, Dorairaj Prabhakaran, Mary Beth Weber, Sailesh Mohan, Shivani A Patel, Nikhil Tandon

Abstract

Background: 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.

Methods: 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.

Discussion: 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.

Conclusion: 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.

Trial registration: CTRI/2020/01/022723.

Keywords: Ayushman Bharat Initiative; Care-coordinator; Clinical Decision Support System; Digital Health; Implementation science; Integration; NPCDCS; Non-Communicable diseases; Scale up; Task Shifting.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Integrated- Tracking, Referral, Electronic decision support, and Care coordination (I-TREC) Development Framework
Fig. 2
Fig. 2
Screenshots of Printouts of Prescription and CDSS recommendations
Fig. 3
Fig. 3
CDSS-enabled GoI CPHC-NCD System Architecture
Fig. 4
Fig. 4
CDSS-enabled GoI CPHC-NCD System Data Flow
Fig. 5
Fig. 5
Screenshot of the GoI CPHC-NCD (Health facility) System

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Source: PubMed

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