Model based health change monitoring in pre surgical patients
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Model based health change monitoring in pre-surgical patients. Jan 21, 2014. Petros Endale May 18, 1985 B.Sc in computer science(2006) M.Sc Telemedicine and e-health(2014 ) Primary Advisor Prof Gunar H. Background. 12,000 annual elective surgery at UNN

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Model based health change monitoring in pre-surgical patients

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Model based health change monitoring in pre surgical patients

Model based health change monitoring in pre-surgical patients

Jan 21, 2014


Model based health change monitoring in pre surgical patients

PetrosEndaleMay 18, 1985B.Sc in computer science(2006)M.Sc Telemedicine and e-health(2014)Primary Advisor Prof Gunar H.


Background

Background

  • 12,000 annual elective surgery at UNN

  • Population settlement of Northern Norway

  • The overall risk of surgery is low in healthy individuals. Preoperative tests usually lead to false-positive results, unnecessary costs, and a potential delay of surgery. Preoperative tests should not be performed unless there is a clear clinical indication.


Surgery cancellation

Surgery cancellation

2001-2002(a Hospital in UK)


E team surgery msc project

e-Team Surgery…MSc Project

  • Exploring if moving the pre-surgical planning out of hospitals and to patients at home through electronic collaboration will improve the quality of care for patients scheduled for surgery

  • Developing system for monitoring health changes in pre-surgical patients. The focus will be on the patient model


Model based health change monitoring in pre surgical patients

GPs

Surgeons

Anesthesiologist

How can we identify serious changes in the patients health remotely?

Patients


Challenges

Challenges

  • Due to the vast scope of pre-operative assessment, the clinical domain knowledge potentially relevant for assessment is virtually limitless

    • a comprehensive list of co morbidities, full history of previous surgery, medication, family history, allergies, previous experiences of clinical adverse events

  • Data availability


Preop

Preop


Detect deviations

Detect deviations

  • Questionnaire(baseline data) + Objective physiological parameters

  • Rule Engine(based on guidelines and expert opinion)

  • Notification, Recommendation and status

  • The Health professional decision and action

  • The patient status aproved by the HP or in agreement with the previous model is taken as the new model.


Model based health change monitoring in pre surgical patients

Risk scores

Patient status

Inference Engine

Self Assessment

Status

Models

Rules

Guidelines


Models

Models

  • Model can be seen as a simplified high-level description of a specific patient in XML form.

  • The model can inform patients and physicians about the status of the patient, and deviation from expected/normal


Model based health change monitoring in pre surgical patients

HealthNet

Server

Patient

XML

Rule

Database


Model based health change monitoring in pre surgical patients

  • Questionnaire answers and physiological data coming from the patient

  • The rule engine and the reasoner compare it with previous models and determines the current state of the patient

  • The current state along with the decision of the health professional will be saved as the new model

  • Anonimze and save the model the model for future similar cases(case based reasoning)


Future work

Future work

  • If significant number of Models and their related decisions are collected then automatic statically population model can be developed.


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