rfid in anaesthetic triangle

Adventures with RFID in the Anaesthetic Triangle

Bryan Houliston

AURA laboratory, School of Computing and Mathematical Sciences, Auckland University of Technology

[email protected]

Aura Laboratory

Outline

• Anaesthesia for busy people

• Monitoring anaesthesia– Approaches and problems

• Automated monitoring with RFID– Masters: RF+IDAS– PhD: AMoA

• Future work

• Conclusion

Introduction > Anaesthesia > Monitoring > RF+IDAS > AMoA > Conclusion

ACIS 2008 2RFID in the Anaesthetic Triangle

Anaesthesia for Busy People• “Extreme approximation of death”

(Euliano , 2004)

– Amnesia + Analgesia + Relaxation

• Stage 1 - Induction– injections, gases, intubation

• Stage 2 - Maintenance– monitoring vital signs, fluids

• Stage 3 - Emergence– extubation, injections



The Anaesthetic Triangle



Anaesthetic Activities



• Patient care 16%– Drug prep, admin– Gas, Airway– IV

• Recording 9%

• Computer 8%

• Equipment 7%

• Other 4%

• Observing 31%– Monitors– Patient

• Conversing 25%– Surgeon– Trainee

(Based on observation of 150 general anaesthetics at Auckland City Hospital, 2008)

Why Monitor Anaesthesia ?• “Every complication has the potential to

cause lasting harm... Therefore, deviations from the norm must be recognized and managed promptly”

(Aitkenhead , 2007)

– 1 error every 133 cases = 5 / day (Webster, 2001)

– 1% cause serious harm, death = 18 / year

• What is ‘the norm’ ?

• How do we recognise deviations ?



Monitoring Anaesthesia

• Self reporting – Anaesthetic record– Distraction from patient care– Inaccurate, ‘normalised’ (Aitkenhead , 2007)

• Manual observation (Weinger , 1994)

– Intrusive, distraction, potential safety risk– Labour intensive, errors, subjective– Long periods of inactivity



Theatre Gets Busy



Monitoring Anaesthesia

• Self reporting – Anaesthetic record– Distraction from patient care– Inaccurate, ‘normalised’ (Aitkenhead , 2007)

• Manual observation (Weinger , 1994)

– Intrusive, distraction– Labour intensive, errors, subjective– Long periods of inactivity

– Theatre gets busy, views get blocked

• Supplement with automated monitoring ?



RFID for Monitoring Activity



• Fixed readers vs Mobile readers– Activity at location Activity by person

• Activity detection vs Event detection– Duration captured No duration

• Coarse grained vs Fine grained– Moving around Body movement

• Specified rules vs Machine learning

– Detect known Discover patterns

RFID Monitoring Applications



Perioperative Progress



Anaesthetic Training



Masters: Requirements

• Replace barcodes on syringes in IDAS(Merry, 2001)

• Consistent labels (FDA, 2004)

• Can’t change IDAS code

• Minimal extra cables• No interference with medical

equipment (van der Togt, 2008)

• Hygiene



Design

• 13.56MHz HF rather than UHF– Shorter range– Less interference from metal, liquids– Proposed for pharma tagging

• Fixed reader less intrusive than mobile

• On drug trolley– Cables out of the way– Away from electronic medical devices– Less hygiene concern than at patient



Tagging Syringes



RF+IDAS• Reader under syringe

tray, 1 read / second

• Tags under label, linked with barcode

• Tag not detected = syringe picked up = send barcode through virtual serial port



Issues



• Couldn’t get tags that are– Right colours– Small size– Affordable

• Read range shorter than expected– 1 reader per syringe tray

PhD: Requirements• Monitor tasks to support observation

– Drug preparation, admin– Updating anaesthetic

record– Sitting down

• Can’t tag syringes

• Can ‘equip’ anaesthetists



Mobile Reader Approach ?• Don’t wear gloves much

• Battery life < 2 hours

• Short range– Tagging all syringes



Fixed Reader Approach

• Each activity associated with a location

Activity Reader located Observed activity

Preparing drugs Drug trolley Drug Prep IV

Updating manual anaesthetic record

Clipboard on workstation

Recording

Sitting at rest Chair -

Injection – neck Head of table Drug Admin IV

Injection – wrist Arm of table Drug Admin IV

Injection – IV line IV stand Drug Admin IV



Readers• Tracient UHF Padl

• Wireless– Battery powered for

7 – 8 hours– Bluetooth connection to PC

• Low power, RF emissions– No interference with

infusion pump



Trolley, Clipboard, Chair



Operating Table and IV



Tagging the Anaesthetist• Tags worn on dominant hand

– Must be comfortable to wear– Must read from different angles, distances



Wristbands• ver 1 - tag on

outside of wrist

• ver 2 – hanging tag

• ver 3 – 3 tags around wrist

• ver 4 - 4 tags along wrist

• + tag on back of scrubs



Results



False -ve

False +veTheory

Location mismatch?

Action mismatch?

Issues



• Readers around table– Interference from metal– Knocked around

• Wristband– Easier to remove – handwashing, transfer

• Location – Activity mapping– Activities that change location– Activities with no location– Locations with multiple activities

Multiple Activities per LocationReader location Activities to monitor Other activities

Drug trolley Drug Prep IV Cleaning Up

Clipboard on anaesthetic workstation

Recording Using ComputerDrug Admin GasEquipment Related

Chair Sitting ?

Head of table Drug Admin IV Line PlacementPositioning PatientAirway Procedure

Arm of table Drug Admin IV Line PlacementPositioning Patient

IV stand Drug Admin IV IV Setup/Adjustment



Telling Activities Apart• Planning to try three approaches

1. Learn RFID sequences for observed activities



Learn RFID Sequences


• Match on common element - Time

• Simple, but– Device times must be kept synchronised– How many sequences required?

Drug Prep IV 9:27:33 9:27:40

Drug Prep IV 9:30:03 9:31:00

Line Placement 9:31:03 9:32:53

09:28:13 Trolley E2003411B80201115620213109:30:38 Trolley E2003411B80201115620213209:30:39 Trolley E2003411B80201115620213209:30:41 Trolley E2003411B80201115620213209:30:48 Trolley E2003411B80201115620213009:30:49 Trolley E2003411B80201115620213209:30:53 Trolley E2003411B80201115620213109:30:53 Trolley E2003411B80201115620213209:30:55 Trolley E2003411B80201115620213109:30:56 Trolley E2003411B80201115620213209:30:58 Trolley E2003411B80201115620213209:30:58 Trolley E2003411B80201115620209309:30:58 Trolley E2003411B80201115620213009:30:59 Trolley E2003411B80201115620213109:31:01 Trolley E2003411B80201115620213109:31:02 Trolley E2003411B802011156202093


Telling Activities Apart• Planning to try three approaches

1. Learn RFID sequences for observed activities

2. Characterise observed activities, and apply to RFID sequences



Characterising Activity• Duration

– Median 17s

– Median 42s




• Stage of procedure





• Preceding activities





• Preceding activities

• Location

• More initial effort, but – Fewer samples– Quicker to apply in real time



Telling Activities Apart• Considering three approaches

1. Learn RFID sequences from observed activities

2. Characterise observed activities, and apply to RFID data

3. Mine RFID data for common sequences, and compare to observed activities



Future Work• Refine activity characterisation

– Type 2 fuzzy sets (Hagras, 2008)

• More RFID data– Cleaning - SMURF (Jeffery, 2008)

– Test fuzzy set functions– Hand position, movement ?– Mining – PERUSE (Minnen, 2007)



Future Work• Alternative reader locations

– Active RFID, triangulation by signal strength

• Object tagging in simulation (Patterson, 2005)

• Benefit realisation– Synthesizing ‘the norm’– Detecting deviations in real time



Conclusion• There is RFID technology suitable for

automated anaesthesia monitoring – Wireless readers, good battery life– Negligible risk of interference, distraction

• But technical and economic challenges remain– Accurate activity detection– Regulation / standards– Cost / safety



ReferencesAgarwal, S., Joshi, A., Finin, T., Yesha, Y., & Ganous, T. (2007). A Pervasive Computing System for the

Operating Room of the Future. Mobile Netw Appl(12), 215-228.

Aitkenhead, A. R., Smith, G., & Rowbotham, D. J. (Eds.). (2007). Textbook of Anaesthesia (Fifth ed.): Elsevier Limited.

Bacheldor, B. (2008). PinnacleHealth Pushes Ahead with RFID. Retrieved 1 September, 2008, from www.rifdjournal.com

Boginski, V., Mun, I. K., Wu, Y., Mason, K. P., & Zhang, C. (2007). Simulation and Analysis of Hospital Operations and Resource Utilization Using RFID Data. Paper presented at the International Conference on RFID, Grapevine, Texas.

Bravo, J., Hervas, R., Fuentes, C., Chavira, G., & Nava, S. W. (2008). Tagging for Nursing Care. Paper presented at the Second International Conference on Pervasive Computing Technologies for Healthcare, Tampere, Finland.



References



Euliano, T. Y., & Gravenstein, J. S. (2004). Essential Anaesthesia From Science to Practice. Cambridge, UK: Cambridge University Press.

FDA. (2004). 2002N-0204: Bar Code Label Requirements for Human Drug Products and Biological Products; Final Rule. Retrieved October 21, 2004, from www.fda.gov

Fishkin, K. P., Consolvo, S., Rode, J., Ross, B., Smith, I., & Souter, K. (2004). Ubiquitous Computing Support for Skills Assessment in Medical School. Paper presented at Third International Workshop on Ubiquitous Computing for Pervasive Healthcare Applications, Nottingham, England

Hagras, H. (2008). Type-2 Fuzzy Logic Controllers: A Way Forward for Fuzzy Systems in Real World Environments. Paper presented at the IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6.

Houliston, B. (2005). Integrating RFID Technology into a Drug Administration System. Paper presented at the Health Informatics NZ Conference, August 2-5, Auckland, New Zealand.

ReferencesJeffery, S. R., Franklin, M. J., & Garofalakis, M. (2008). An adaptive RFID middleware for supporting

metaphysical data independence. The VLDB Journal, 17, 265-289.

Khoussainova, N., Balazinska, M., & Suciu, D. (2007). Probabilistic RFID Data Management: University of Washington, Seattle.

Merry, A., Webster, C., & Mathew, D. (2001). A New, Safety-Oriented, Integrated Drug Administration and Automated Anesthesia Record System. Anesthesia & Analgesia, 93, 385-390.

Minnen, D., Starner, T., Essa, I., & Isbell, C. (2006). Discovering Characteristic Actions from On-Body Sensor Data. Paper presented at the International Symposium on Wearable Computing, Montreux, Switzerland.

Patterson, D. J., Fox, D., Kautz, H., & Philipose, M. (2005). Fine-Grained Activity Recognition by Aggregating Abstract Object Usage. Paper presented at the Ninth International Symposium on Wearable Computers, October 18-21, Osaka, Japan.



References Symonds, J., Parry, D., & Briggs, J. (2007). An RFID-based System for Assisted

Living: Challenges and Solutions. Studies in Health Technology and Informatics, 127, 127-138.

van der Togt, R., van Lieshout, E. J., Hensbroek, R., Beinat, E., Binnekade, J. M., & Bakker, P. J. M. (2008). Electromagnetic Interference From Radio Frequency Identification Inducing Potentially Hazardous Incidents in Critical Care Medical Equipment. Journal of the American Medical Association, 299(24), 2884-2890.

Webster, C., Merry, A., Larsson, L., McGraths, K. A., & Weller, J. (2001). The Frequency and Nature of Drug Administration Error During Anaesthesia. Anaesthesia and Intensive Care, 29(5), 494-500.

Weinger, M. B., Herndon, O. W., Zornow, M. H., Paulus, M. P., Gaba, D. M., & Dallen, L. T. (1994). An Objective Methodology for Task Analysis and Workload Assessment in Anaesthesia Providers. Anesthesiology, 80(1), 77-92.



Acknowledgements• Tracient Technologies

– For providing RFID readers

• Anaesthetists at ACH– For their professionalism and forbearance

• Dave Parry, Alan Merry– For their guidance and supervision

Aura LaboratoryACIS 2008 45RFID in the Anaesthetic Triangle


Questions?

Aura LaboratoryACIS 2008 46RFID in the Anaesthetic Triangle
