Karim Keshavjee

31 Seguidores

I have over 25 years of experience designing, developing and implementing Electronic Health Records/Electronic Medical Records and helping clinicians use them effectively. I am currently working on architecting a scalable and sustainable technology system that will help us prevent diabetes cost-effectively. Diabetes prevention is feasible, but is not cost-effective. I believe an engineered solution could change things dramatically. In previous projects, I have architected and evaluated two clinical decision support tools using randomized controlled trials with McMaster University through their COMPETE studies. I am interested in applying research findings to...

emr ehr patient engagement data science diabetes usability big data standardization governance ieee infoclin. patient empowerment mobile apps bluestar reference architecture clinical practice data cleansing predictive analytics analytics data discipline prescribing decision-support cdss hospital coordinated care aco managed care architecture high needs patient care high cost utaut user interface structured data entry web-based form emr template multi-morbidity healthcare conference mhealth apps health prescription ui ux health information exchange snomed hl7 interoperability cpcssn napcrg research ehealth

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Karim Keshavjee

Apresentações

Canada's rank in OECD studies 20100610

Pitfalls and realities of working with Big Data

EMR NG

Sleepless in Arthritis Oct 2015_AF_KK (1)

Panel on the future of Electronic Health Records

Evaluation of Diabetes mhealth apps 2017

Evaluation of a Multi-EMR web-based Form

IT for bending the healthcare cost curve

What we can learn from Amazon for Clinical Decision Support

The cost of data quality in EMRs

Health Apps by Design: A reference architecture

Canada’s innovation agenda apr 13, 2017

Documentos

CHT Virtual FHT (Published)

Governance microbubble poster v4

Gostaram

Deploying deep learning models with Docker and Kubernetes

There Is A 90% Probability That Your Son Is Pregnant: Predicting the Future of Predictive Analytics in Healthcare