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Comprehensive Support for Self Management of Medications by a Networked Robot for the Elderly
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Comprehensive Support for Self Management of Medications by a Networked Robot for the Elderly


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Priyesh Tiwari …

Priyesh Tiwari
National Institute of Health Innovation, University of Auckland
(Thursday, 2.30, Science 1)
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Quality use of medication by older people is becoming an important challenge with the demographic shift and increasing burden on our healthcare system. There is a significant emphasis on improving medication adherence as well as safety. We developed an automated dialogue system for residents of an Aged Care Facility (ACF) who were on multiple medications to help them manage their medications better. The dialogue was delivered spoken as well as via a written display over a touch screen mounted on a robot. Each session assisted the identified users in finding the right medication, and taking the right dose at the right time through the right route. It also included dialogues on side effects monitoring and other essential drug information. The data on the robot were exchanged wirelessly with a remote health record (called Robogen) in real time. The sessions were video logged, researcher notes and semi-structured interviews were conducted to elicit acceptance and usability information. Six participants interacted over a two-week period. Most users found the system easy to use and helpful and demonstrated evidence of task mastery by the 3rd or 4th sessions. We conclude that such a system can be used to enhance quality of use of medication by the elderly, but we need to better understand and address user behaviour while designing such system.

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  • 1. Comprehensive Support for Self Management of Medications By The Elderly Testing a Networked RobotPriyesh Tiwari, Jim Warren, Karen Day, Chandan Datta University of Auckland
  • 2. Background & Rationale• Ageing of populations• Multiple chronic condition and practice of polypharmacy in elderly• Medication errors and ADEs common cause of morbidity in elderly• Medication safety for elderly is a priority for National Quality Improvement Program
  • 3. Searching for solutions• Shrinking healthcare workforce and increasing cost of personal support• Simply pushing adherence may not necessarily be safe for very elderly – Need to address medication safety, monitor and report ADEs, build skills for quality use and improve communication between patients and their providers – Use of pillboxes and simple reminders therefore is limited• Standard desktops and mobile phones pose usability challenge for elderly• There is room for innovationHow could a social robot help?
  • 4. Earlier work: Action research Cycle 1 A qualitative study to Safety arrive at a theoretical framework* Empower- *Tiwari P, Warren J, Day K, ment Can a Robot Facilitate Medication Information Sharing in an Aged Care Collabor- Facility? : Health Informatics SocietyUsability of Australia ation
  • 5. Action Research Cycle 2 Established the usability of a automated dialogue system and a touch-screen interface mounted on a robotTiwari P, Warren J, Day K, MacDonald B, Jayawardena C, Kuo I, et al., editors. Feasibility study of a robotic medication assistant for the elderly. Australasian User Interface Conference; 2011; Perth: CRPIT.Tiwari P, Warren J, Day K. Empowering Older Patients to Engage in Self Care: Designing an Interactive Robotic Device. Proceedings of the 2011 Annual AMIA Symposium; Washington DC, (2011)
  • 6. AR cycle 3 - Modules testedMedication reminder Testing long term usability : Visiting residents of a retirementMedication education home once in a day over 2 weeks Average age of 6 83-92 yrs. (Mean 80.5 respondents years)Screening for side Gender distribution 3 Maleseffects 3 Females Meds organized as 3 Loose medications 2 Pill BoxMeasuring BP and 1 SachetsSPO2
  • 7. Dialogue deliveryBack & quit buttonsDialogue displayOptions Menuwith soft buttonsSpeakersDual dialogue output: Written as well as Spoken
  • 8. Testing a real prescription WEB SERVICESMEDICATION MANAGEMENT ROBOGEN MODULE Web based application on The system reads prescription secure server from web server in real time Stores prescription information Starts the dialogue sequence and customized information for according to schedule constructing dialoguesUsers respond by touching soft Logs fine grained data coming buttons on the screen from MMM Communicated with Robogen Medication use andin real time reading prescription Monitoring data displayed as information and sending user weekly reports. responses. CDA architecture intendsCan send text alert to caregiver interoperability in real time
  • 9. RobogenDashboard for Healthcare Providers
  • 10. Converting a prescription into a dialogueExample Prescription by a Physician Example Reminder dialogues –Mr. Joe Bloggs, 20.09.2011 21.09.2011Med: Furosemide 40 mg Tablets Qty: - 8.30 AM (Breakfast time dialogues)30 Please find the “sachet” that reads “Mr.Sig: Take 1 tablet every morning Joe Bloggs”, “Wednesday 21st Sachet September” and “Breakfast time”Med: Metoprolol 47.5 mg TabletsQty: 30 “Take out” “2” “Pills” “and swallowSig: Take 1 tablet every morning whole with a large glass of water” Bottle - 1.30 PM (Lunch time dialogues)Med: Poly-Tears eye drops Qty: 1 Please find the “bottle” that readsSig: Instill 2 drops 3 times a day in “Poly-tears”.each eye Box “Instill” “2” “drops” “into each eye”Med: Paracetamol 500 mg TabletsQty: 200 *inverted commas represent placeholders forSig: Take 2 tabs as needed upto 4 each unit of dialogue constructed fromtimes a day Robogen
  • 11. Methods• Video recording and analysis• Questionnaire analysis• Structured interview with grounded analysis of script• Field notes
  • 12. Results: Video analysisUser No. Total No. Of Success of Appropriatene Backtracking, Response to Medication Non-technical Interactions medication ss of dialogue getting stuck or side effects information errors intake (out of to actual needing help question accessed / observed at total no of activity demonstrated any point interactions) 1 9 9/9 8† day 1 1 1‡ 2 5 5/5 4§ day 1, 2,3 1 1 3 8 8/8 8 day 1 1 4 8 8/8 8 0 1 1║ 5 7 6*/7 7 0 1 6 8 6*/8 8 day 1 1 1¶*Had taken medications before our arrival ‡ Loose medication was found in the pillbox,†Error in capturing “before breakfast” medication ║We missed to record supplements,§Unclear instruction when to swallow pills ¶Prompted name of brand was different
  • 13. Ratings on a questionnaire1= Poor, 2 =Average, 3 = Good, 4 = Excellent USER No. 4 1 Ratings 2 3 3 4 2 5 6 1 1 2 3 4 5 6 7 8 9 Number of Interactions
  • 14. Structured Interview Yes No Not OtherQuestion Researcher Comments (Field notes) sureWas your prescription information on the 5 0 1 0 Participant on Sachets have many pills packaged together and find it difficult to remember and correlaterobot correct?Did you access educational details about 0 6 0 0 None of the participants remembered having accessed medication education module despite beingyour medications on the robot? demonstrated in the beginning and therefore unsurprisingly did not find it useful.Did the robot have correct educational 1 0 5 0 Most participants did not access the details despite being available as an option, hence unsure about it.information about your medications?Did the robot help you to remember your 0 6 0 0 When one is prepared to receive visitors and a robot, little chances that they will forget. Anyways, themedications participants were independent living people who were managing themselves without reminding.Did the robot ask you about the side 1 5 0 0 Despite being asked on multiple occasions participants did not remember it. Perhaps because we did noteffects of your medications? specify this was a side effect question.Did you find the side effect monitoring 1 0 5 0 Since most of the participants did not acknowledge remembering it they were not sure about itsquestions helpful? helpfulness, but the one who remembered it found it helpfulWould you like to change the number of 0 6 0 0 The participants thought this was an appropriately delivered contentsteps or instructions being given inmedication management module?
  • 15. Some comments• “I have enjoyed it immensely-cannot speak too highly of its wide applications, and am desirous of having one myself. For me a brief reminder would be sufficient, but I am not sure if Mrs. …. Living next doors would make much sense of it”.• “I thought it was quite well done- but I missed to find out more about the actual medications, that would have been helpful if I knew it was there”.• “Entering my name was hard on the robot as my hands are shaky”.• “My grandsons think its a hoot that grandmas doing robot research. I found it quite entertaining, and looked forward to the visit each morning”.
  • 16. Observations• Automated dialogues correctly displayed the medication information from Robogen and successfully logged participant activity back• Participants successfully completed the task on 5-9 days over two weeks• The satisfaction ratings after each session did not drop over the duration of trial
  • 17. Observations• The participants enjoyed interactions in general• The task performance time steadily improved showing task mastery after 3-4 sessions• The participants did not access the passive option of education about their medications• They did not find the side effect monitoring questions noticeable or intrusive• Appreciation of fun factor that transforms the monotony of a daily chore
  • 18. Discussion• Significance 1. Develops understanding & Deeper insights – Medication management is a variable and constantly changing task – Users personalise a prescription uniquely – It is difficult to navigate this complexity and maintain relevance for deploying automated assistance – Frail and challenged patients need longer handholding and may be unsuitable for such intervention• Significance 2: Demonstrates a method – It was possible to create a fine grained accurate dialogue to meet personal variations – It was possible to share the information both ways, in real time with a web server. This could in turn communicate with a PHR or EHR in future.
  • 19. Discussion• Limitations – The results of this research are limited by its small sample size – Presence of researcher and Hawthorne effect could make results difficult to generalise• Future work – Lessons learnt in this phase would inform refinement of module design – The next action research cycle examines longer-term use of the robot without as much direct supervision by the researchers
  • 20. Conclusion• It is possible to create a collaborative information sharing system Meting both patients and providers preferences• Older people can successfully navigate through a touch screen based system to assist them with a complex self-care task• It is possible to unobtrusively query clinically relevant symptoms and side effects, without raising patient’s anxiety• Merely providing an option to access drug information may not work for older people. Personalised dialogues may be more effective.