InterSystems presentatie: Making sense of non-structured data in the medical world
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In deze presentatie leest u over de volgende onderwerpen: • Navigation through EPR • Mapping to UMLS High Level Concepts • Data Mining with DeepSee Advanced Analytics
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I have chosen three NANDA nursing diagnoses for this patient, with the first one being the priority. The three I choose are:
· Decreased Cardiac Output related to altered heart rate and ischemia as evidenced by ECG showing an ST elevation, elevated Troponin, and patient stating he has had chest pain for three days.
· Acute Pain related to tissue damage in the myocardium from inadequate blood supply as evidenced by elevated troponin labs and patient reporting chest pain that radiates to back for three days.
· Ineffective Health Maintenance related to deficient knowledge about self-care and treatment as evidenced by patient stating he eats fast food often and has had elevated blood pressure and cholesterol at past appointments, and patient admitting to smoking ½ pack of cigarettes daily despite family history of MI.
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This document discusses the role of the emergency department (ED) as a gatekeeper in transitions of care. It covers several key points:
1) The ED plays an important role in determining whether patients are observed, admitted, or discharged. Risk stratification tools help guide these decisions for conditions like chest pain.
2) The ED communicates patient acuity levels and makes recommendations about observation, medical-surgical floors, intensive care, etc. Information on condition, interventions, and risk scores are important to transmit.
3) Protocol-driven care that begins in the ED can continue on hospital floors, improving outcomes. Guidelines help with conditions like heart attacks and pneumonia.
4) The ED can help
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The document discusses how data can help patients and clinicians by analyzing large amounts of health data to identify who needs help, their medical conditions and preferences, and how to match needs with resources to improve access to care. It notes barriers include a lack of healthcare awareness of data tools, clinicians and consumers not trained to make decisions from big data, and issues with data accessibility, interoperability, and privacy. The presentation aims to explain how analyzing various health data sources can help target care across settings like hospitals, clinics, and homes.
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InterSystems presentatie: Making sense of non-structured data in the medical world
- 1. Making sense of non-structured data in the medical world Dirk Van Hyfte, MD, PhD Misha Bouzinier
- 2. What’s in? THE KEYS TO BREAKTHROUGH HEALTHCARE
- 3. What’s in? Some theory THE KEYS TO BREAKTHROUGH HEALTHCARE
- 4. What’s in? Some theory Examples THE KEYS TO BREAKTHROUGH HEALTHCARE
- 5. Traditional Knowledge Discovery: Top Down THE KEYS TO BREAKTHROUGH HEALTHCARE
- 6. iKnow Approach: Bottom up, Concept Level THE KEYS TO BREAKTHROUGH HEALTHCARE
- 7. Smart Indexing Two patients are suffering from congestive heart failure. Smart Indexing (concepts and relations): Two patients are suffering from congestive heart failure Smart Index relation detection concept detection Are suffering from Two patients Concep t Two patients Concep t Relation Congestive heart failure Are suffering from Congestive heart failure THE KEYS TO BREAKTHROUGH HEALTHCARE
- 8. Combine THE KEYS TO BREAKTHROUGH HEALTHCARE
- 9. Examples • Navigation through EPR • Mapping to UMLS High Level Concepts • Data Mining with DeepSee Advanced Analytics THE KEYS TO BREAKTHROUGH HEALTHCARE
- 10. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 11. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 12. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 13. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 14. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 15. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 16. Navigation through EPR THE KEYS TO BREAKTHROUGH HEALTHCARE
- 17. Navigation through EPR Population THE KEYS TO BREAKTHROUGH HEALTHCARE
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- 19. Mapping to UMLS HL Concepts THE KEYS TO BREAKTHROUGH HEALTHCARE
- 20. iKnow and Data Mining • Is the data really unstructured or does it in fact has a hidden structure? • iKnow helps to discover hidden structure of the data and subsequently present it in the standard relational form • Once the structure is imposed, DeepSee Advanced Analytical tools can be used to mine for the additional information 20 THE KEYS TO BREAKTHROUGH HEALTHCARE
- 21. Data Mining Demo Demo 21 THE KEYS TO BREAKTHROUGH HEALTHCARE