KEY IMPETUS

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While Health technology has made important contributions to organizational efficiency, it has not been successful in areas where new knowledge creation at deeper clinical context is the driver of progress.

This limitation is due to the complexity of clinical paradigm where knowledge-driven activity is wide-ranging, interwoven, intangible, and involves many varied disciplines and sub-disciplines, any attempt to solve the complex clinical problems, and providing more cost-effective model of care in this paradigm must ultimately encompass this diverse range of complexity at this deeper level.

However, the fundamental issue is that the existing attempts repeatedly narrow their focus on observable operational level, leading to limiting solutions that are:

  • Silo and inflexible,
  • Fragmented and non-continuous,
  • Quality and rigor issue,
  • Unaffordability and exclusivity.

Furthermore, many attempts assumes that valuable clinical data from the deeper context already exists, and all that is needed is mapping, mining and making it accessible.

The central weakness of healthcare digitalisation arises at the ‘creating data’ stage at deep complex adaptive clinical context, and the missing ingredients to addressee the complexity of this domain with breadth and depth.

HOW HUSKI DIFFERENTIATES FROM TRADITIONAL APPROACH

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The diagram compares HUSKi with the traditional approaches using the four quadrants classification with an extended scientific dimension.

This illustrates why depite of continuous investment, healthcare discovery remains slow and frustrating. The traditional attempts repeatedly focus on observable operation and neglect the support for people's most demanding knowledge-driven activities that are abstract, intangible and exacerbated by their scientific requirements. HUSKi is designed to overcome the existing shortcomings to offer the next generation platform to support transformational improvement in healthcare.

DESIGN PATTERN

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HUSKi uses an AI powered methodological knowledge machine to scientifically and holistically harness the perspectives of:

Tthe abstract controllable to tap into clinical wisdom and address the complex needs from diverse clinical specialties and professional network communities,

the non-abstract (observable) controllable to leverage advance technologies to rapidly bridging clinical research with practice,

the non-controllable (unpredictable) to rapidly adapt to change, growth and evolutionary needs..

SIMPLIFIED SNAPSHOT OF HUSKI KNOWLEDGE CREATION LIFECYCLE

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The diagram illustrates a simplified version of HUSKi’s knowledge cycle. This process is characterised by the methodological platform securely supports for:

  • guided user-interface for scientific-based hypothesis design, and model generation,
  • selecting of research methods, including AI-powered randomized clinical trial,
  • adapting to clinical practice, and change needs,
  • prediction machine using Bayes’ theorem
  • continuous data analytics and feedback as defined to improve quality and rigor
  • AI-driven execution, transformation and load mechanism that breaks the traditional data-science limitation

Most importantly, HUSKI places its complete discovery cycle with the holistic ecosystem for universality, adaptablity and sustainability to make innovating clinical insight cost-effective and rewarding.

EXAMPLE OF HUSKI USE CASE

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Area Project outcome and date System Complexity
Neonatology Best identified method to wean babies off CPAP, reduced chronic lung disease (CLD) and length of stay with significant savings per baby of about $ 7,000. Established that CLD at high birth does not play an important role in onset of asthma. Winner ACT Health Innovative Care Model Quality Award 2011. Second study – Retinopathy treatment. High-response adaptive randomised trial with very complicated calculations based on time and the large number required in the forms.
Eye Surgery Identified factors influencing macular hole closure and retinal detachment repair, identified current treatment trends among surgeons nationally. Winner ACT Health Systems Support Quality Award 2014. Moderate to high-collection relatively simple but requirements in terms of identifying missing data and reporting of log books by supervisor and registrar. Includes desktop and mobile versions.
Fractures Reduced length of stay and readmissions. Provided clear evidence of the benefits from a territory-wide pressure injury prevention program on the rate of pressure injuries experienced in the hospital and community settings. Part of the winning team obtaining a rare Extra Achievement (EA) in the recent hospital accreditation. Very high-highly relational patient to many admissions, to many wound locations on body to many types of wound within a location to may assessments over days. Needed to invest new type of meta data to manage, imaging complex and large volume with area mapping and sub locations, photo storage is the next step.
Tissue viability/Pressure Injury Reduced length of stay and readmissions. Provided clear evidence of the benefits from a territory-wide pressure injury prevention program on the rate of pressure injuries experienced in the hospital and community settings. Part of the winning team obtaining a rare Extra Achievement (EA) in the recent hospital accreditation. Very high-highly relational patient to many admissions, to many wound locations on body to many types of wound within a location to may assessments over days. Needed to invest new type of meta data to manage, imaging complex and large volume with area mapping and sub locations, photo storage is the next step.
Orthopaedics Prediction of surgical prognosis. Remote decision support to aid surveillance post joint replacement. These features in addition to descriptive outcomes provide valuable cost-effectiveness solutions to the significant costs associated with life-long surveillance. High-long term surveillance & follow-up multiple joints, email management, patient login, ipad devices, decision support around patient management, bid data management, complicated reporting and data extraction.
Gastroenterology Identified key moderating factors in viral response to HCV treatment. Determined the role psychiatric morbidity in the clinical treatment of hepatitis. Moderate to high – long term surveillance with formulas used to determine risk and level of surveillance required, warning and patient management.
Respiratory Sleep & Medicine Determined the optimum time for compliance in a sleep apena program. Identified moderating factors that influence treatment outcome in a sleep program. Moderate – clear business requirements for the sleep program, asset management embedded in the system adds to the complexity.
Gynaecology Developed a screening tool for menstrual dysfunction that identifies signs to support earlier treatment and more streamlined care pathways. This tool has major implications in the identification and long-term treatment of women with endometriosis. Moderate complexity but user does not have clear requirements – keep changing or are inconsistent with information technology standards
Mental Health Determined a superior method of treating women with post-natal depression Low-simple randomised study

BENEFITS OF USING HUSKI

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  • Reduce intelligent database design time by 85-100%
  • Reduce application development and cost by 55-85%
  • Reduce time to build the adaptable clinical application by 55-95%
  • Fits any scale, and any budget
  • Achieves accurate result quickly
  • Generates high quality big data and data analytics seamlessly in real-time

REQUIREMENT FULFILMENTS

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