MONITORING OF STRESS IN HEALTHCARE CARE PROFESSIONALS IN COMPLEX ENVIRONMENTS

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MONITORING OF STRESS IN HEALTHCARE CARE PROFESSIONALS IN COMPLEX ENVIRONMENTS

  1. 1. MONITORING OF STRESS IN HEALTHCARE CARE PROFESSIONALS IN COMPLEX ENVIRONMENTS Preliminary results Deepak Agrawal, KK Biswas*, Renu Saini, Yamuna Prasad* Department of Neurosurgery, JPNA Trauma Centre, AIIMS & *Department of Computer Science, IIT, New Delhi
  2. 2. Background Healthcare care professionals like doctors & nurses are expected to have the highest level stress in complex environments like Emergency rooms , OT’s & Intensive care units
  3. 3. Stress Dependent Factors O Pre-existing stress levels, O Pre-existing knowledge, O Personal & professional relationship with peers & subordinates, O Experience in the specific environment
  4. 4. AIM To use wearable biosensor(s) and attempt to measure the stress in the complex environments at the individual level
  5. 5. Methodology Selection of wearable sensors Data acquisition Complexity modeling
  6. 6. Biosensor O A biosensor is an analytical device which is used to determine the presence and concentration of a specific substance in a biological analyte
  7. 7. What is wearable biosensor ? Object that can be worn on body. O Watch O Jacket O Ring
  8. 8. Selected Biosensor We have selected sunnto T6d watches, that is; O Comfortable, O Have desirable physiological parameter, O Inter Beat Interval O Heart Rate O Temperature O Calories O Easy to wear and take off.
  9. 9. Methodology
  10. 10. STEP -1 STEP- 2
  11. 11. Step 3 O Event Marking O Patient entering Resuscitation bay O Patient requiring intubation (patient desaturating) O Cardiac/respiratory arrest
  12. 12. On Line Data Collection
  13. 13. Step 4-Modulation of Data Complexity modeling using Support Vector Machines O Linear O Gaussian Kernels
  14. 14. OBSERVATIONS O 1642 Hours of data collected over 6 months O 37 doctors O 52 nurses
  15. 15. Results O Variation in all the parameter (Energy, IBI, Heart rate, and Temp) across the normal or abnormal data. O We are able to quantify stress levels at a individual level with 100% accuracy
  16. 16. Result O Different stress level found between individual doctors/nurses for a single event corroborated the fact that in- experienced doctors/nurses may have high stress dealing with in the event as compare to the experienced doctors/nurses.
  17. 17. Results O Stress level is different at different times & this is independent of individual stress levels O This implies that doctor /nurse are more highly stress during specific shift(s) (night).
  18. 18. New Observations O 100% stress level detection in the hospital set up during the medical procedure at the individual level.
  19. 19. Innovations O Pre-existing stress levels can be measured by the variation in normal attributes due to factors such as O Lack of sleep, O Non-related work stress etc.
  20. 20. Application Potential O Long Term Duty roster should be prepared according to the predetermined stress levels using our modeling so that a team posted in the ED at any point of time has a balanced mix of health care professionals of different stress level. O Immediate This systematic research will useful to assess stress level of healthcare worker in the complex environment in emergency department.
  21. 21. Application Potential O Repeated Stress testing O Baseline and at regular intervals O Could be surrogate marker for assimilation of knowledge & experience in an individual.
  22. 22. Future Prospect This approach will help to reduce medical error that focuses on the emergence, detection and management of error within a complex cognitive system.
  23. 23. Acknowledgements O Project funded by Cognitive Task Force, Department of Science & Technology, Govt of India. O Data Capture done with help of Dr Bhoi, Department of Emergency Medicine, JPNATC, AIIMS, New Delhi O Data analysis & Modelling done in Department of Computer Science, IIT, Delhi
  24. 24. THANK YOU

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