Periodic Reporting for period 1 - DemDX (Next generation clinical decision-support & education)
Reporting period: 2019-11-01 to 2020-02-29
The WHO estimates a shortfall of 4M doctors to acceptable levels of physician coverage. To bridge this gap, much of the initial assessment and diagnosis (triage) of patients is being shifted from physicians to other healthcare professionals such as nurses and advanced nurse practitioners. Whilst these healthcare professionals have significant clinical experience, they lack the extensive training and back-up support that doctors have traditionally been able to access.
Dem Dx aims to assist these nurses and other healthcare professionals through the provision of machine-learning optimised clinical decision support. Our tool guides users through the consultation they will have with a patient, following a doctor’s natural workflow from presenting complaint, through associated symptoms and signs to arrive at a differential diagnosis. The platform provides support to allied healthcare professionals as they take on increased clinical responsibility. The platform no only supports the upskilling of patients but also provides improved quality and efficiency of delivering care.
The objectives of the study are to determine the target market, pricing model, technical feasibility, commercial feasibility and scalability of the platform. Dem Dx will carryout detailed research and assess technical challenges in developing the platform.
Dem Dx aims to assist these nurses and other healthcare professionals through the provision of machine-learning optimised clinical decision support. Our tool guides users through the consultation they will have with a patient, following a doctor’s natural workflow from presenting complaint, through associated symptoms and signs to arrive at a differential diagnosis. The platform provides support to allied healthcare professionals as they take on increased clinical responsibility. The platform no only supports the upskilling of patients but also provides improved quality and efficiency of delivering care.
The objectives of the study are to determine the target market, pricing model, technical feasibility, commercial feasibility and scalability of the platform. Dem Dx will carryout detailed research and assess technical challenges in developing the platform.
The main actions of the project included carrying out a technical, commercial and financial feasibility assessments. The technical feasibility assessment included holding focus groups and meeting with key partners to understand key features needed on the platform, followed by initial technical and design developments by the Dem Dx team for review by the partners. The features identified offer an array of benefits including improved user experience, adapting to specific institutional needs and improving efficiency in triaging.
The commercial and financial feasibility study carried out by Dem Dx highlighted key market segments to target, along with features crucial to commercial feasibility for specific target groups. Interactions with partners, users and target institutions allowed for development of a clear go-to-market strategy, developments of a pricing model and future scalability.
During this study, Dem Dx discovered the need for a clinical diagnostic tool not only for improving clinical reasoning skills in the education market, but the applicability in the triaging setting. Clinical institutions emphasized the need for a clinical diagnostic reasoning tool to support task shifting and ups killing of nurses and allied healthcare professionals to take on more clinical responsibility and streamline triaging of patients.
Building on existing partner relationships, particularly in the ophthalmology sector, the primary objective obtained is to develop the machine learning clinical reasoning triaging platform to improve ophthalmic triaging. The need for an ophthalmic clinical reasoning triaging tool was well established to improve referrals for the community and to support nurses and allied healthcare professionals when delivering quality care and support task shifting to support the burdened healthcare system.
Dem Dx plans to expand further into the clinical institutional market by further developing the platform to support nurses and other allied healthcare professionals in the ophthalmology field.
The commercial and financial feasibility study carried out by Dem Dx highlighted key market segments to target, along with features crucial to commercial feasibility for specific target groups. Interactions with partners, users and target institutions allowed for development of a clear go-to-market strategy, developments of a pricing model and future scalability.
During this study, Dem Dx discovered the need for a clinical diagnostic tool not only for improving clinical reasoning skills in the education market, but the applicability in the triaging setting. Clinical institutions emphasized the need for a clinical diagnostic reasoning tool to support task shifting and ups killing of nurses and allied healthcare professionals to take on more clinical responsibility and streamline triaging of patients.
Building on existing partner relationships, particularly in the ophthalmology sector, the primary objective obtained is to develop the machine learning clinical reasoning triaging platform to improve ophthalmic triaging. The need for an ophthalmic clinical reasoning triaging tool was well established to improve referrals for the community and to support nurses and allied healthcare professionals when delivering quality care and support task shifting to support the burdened healthcare system.
Dem Dx plans to expand further into the clinical institutional market by further developing the platform to support nurses and other allied healthcare professionals in the ophthalmology field.
The Dem Dx triaging support platform is unlike any product available in the market. Current diagnostic platforms act a general reference tool for healthcare professionals but do not provide the capability of providing upskilling and triaging support. The Dem Dx platform provides clinical institutions with a novel tool to support their delivery of care.
The platform is developed using expert clinical knowledge and machine learning. The platform allows for quality healthcare to be accessed at all levels as it allows for consistent quality of care delivered. The scope of the platform is not limited to its use in large specialised clinics, but is also a useful tool in smaller regional and remote clinics. The platform can streamline referrals and ensure that the correct steps are taken when dealing with each medical case.
The platform is developed using expert clinical knowledge and machine learning. The platform allows for quality healthcare to be accessed at all levels as it allows for consistent quality of care delivered. The scope of the platform is not limited to its use in large specialised clinics, but is also a useful tool in smaller regional and remote clinics. The platform can streamline referrals and ensure that the correct steps are taken when dealing with each medical case.