Nauman Khan, Natalia Díaz Rodríguez,Ivan Porres and Johan Lilius (Åbo Akademi Univ., Finland)
Riitta Danielsson-Ojala, Hanna Pirinen, Lotta Kauhanen and Sanna Salanterä (University of Turku, Finland)
Sebu Björklund, Joachim Majors and Kimmo Rautanen
(MediaCity Content Testing Lab., Finland)
Tapio Salakoski, IlonaTuominen (University of Turku, Finland)
Presented at 6th International Workshop on Intelligent Environments Supporting Healthcare and Well-being WISHWell'14 within Ambient Intelligence (AmI'14), Eindhoven, The Netherlands. 11/11/14
Medical Related information reconciliation when a patient sees many providers or transfers between health facilities is challenging. Lack of updated and correct information is a key concern for patient safety during a health and illness trajectory [1]. Errors, near misses and adverse medication events are too common, particularly whne transfers between hospitals, nursing home and home are frequent, or engagement of multiple specialties is common [2]. Lack of effective informatics support can be harmful to a person’s health, leading to suffering, increased use of health care resources and increased costs.
As a case for interactive discussion, we have chosen information exchanges related to medication, prescription-based as well as over the counter drugs. This challenging chain of activities includes: (a) prescribing on paper or electronically by several medical specialists, (b) transcribing by sending and interpreting prescriptions in the pharmacy, (c) dispensing medication by brand name or generic substitution, (d) acquiring over the counter medication, (e) administering medication as a user, and (f) observing effects and side-effects. The risk of missing information leading to mistakes in the chain of activities in medication management is likely to increase as complex medication regimes become common due to demographic developments, co-morbidities or more personalized treatment. Potentials in patient activation and relevant informatics tools for medication reconciliation need further exploration.
Anne MOEN Institute for Health and Society, Faculty of Medicine, University of Oslo, NORWAY
Catherine CHRONAKI HL7 Foundation, Brussels, BELGIUM
Christian NØHR, Aalborg University, DENMARK
Line Helen LINSTAD Norwegian Center for eHealth Research, Tromsø, NORWAY
Petter HURLEN Akershus University Hospital, NORWAY
Many people rely on non-prescription drugs
therapy to treat common medical conditions. Health technology
can be a valid support to help people in selecting and choosing
an appropriate treatment.
Aim: This study examined how common people make their
decisions to select a non-prescription drug, evaluating
comprehensibility and satisfaction of a virtual tool that could
propose and sell different types of non-prescription drugs
therapy
As humans we are prone to making mistakes and getting things wrong, which is part of our everyday nature. However, in healthcare human errors can often lead to incidents, which can be sources of inconvenience or sometimes major consequences that can directly affect our patients.
Human factors theory plays an important role in understanding how human behavior contributes to such errors, through our interaction with colleagues, equipment, systems, and the working environment. The theory forms an integral part of aviation safety and has also found its feet in other industries, including healthcare.
This presentation was presented at the Saudi Health 2014 International Nursing Conference and introduced the basic concepts of human factors theory in nursing. Case studies were used as examples to draw on the factors that contribute to issues of care, which directly affect patients. Interventions of how to address common human factors to minimize risks were also discussed.
Medical Related information reconciliation when a patient sees many providers or transfers between health facilities is challenging. Lack of updated and correct information is a key concern for patient safety during a health and illness trajectory [1]. Errors, near misses and adverse medication events are too common, particularly whne transfers between hospitals, nursing home and home are frequent, or engagement of multiple specialties is common [2]. Lack of effective informatics support can be harmful to a person’s health, leading to suffering, increased use of health care resources and increased costs.
As a case for interactive discussion, we have chosen information exchanges related to medication, prescription-based as well as over the counter drugs. This challenging chain of activities includes: (a) prescribing on paper or electronically by several medical specialists, (b) transcribing by sending and interpreting prescriptions in the pharmacy, (c) dispensing medication by brand name or generic substitution, (d) acquiring over the counter medication, (e) administering medication as a user, and (f) observing effects and side-effects. The risk of missing information leading to mistakes in the chain of activities in medication management is likely to increase as complex medication regimes become common due to demographic developments, co-morbidities or more personalized treatment. Potentials in patient activation and relevant informatics tools for medication reconciliation need further exploration.
Anne MOEN Institute for Health and Society, Faculty of Medicine, University of Oslo, NORWAY
Catherine CHRONAKI HL7 Foundation, Brussels, BELGIUM
Christian NØHR, Aalborg University, DENMARK
Line Helen LINSTAD Norwegian Center for eHealth Research, Tromsø, NORWAY
Petter HURLEN Akershus University Hospital, NORWAY
Many people rely on non-prescription drugs
therapy to treat common medical conditions. Health technology
can be a valid support to help people in selecting and choosing
an appropriate treatment.
Aim: This study examined how common people make their
decisions to select a non-prescription drug, evaluating
comprehensibility and satisfaction of a virtual tool that could
propose and sell different types of non-prescription drugs
therapy
As humans we are prone to making mistakes and getting things wrong, which is part of our everyday nature. However, in healthcare human errors can often lead to incidents, which can be sources of inconvenience or sometimes major consequences that can directly affect our patients.
Human factors theory plays an important role in understanding how human behavior contributes to such errors, through our interaction with colleagues, equipment, systems, and the working environment. The theory forms an integral part of aviation safety and has also found its feet in other industries, including healthcare.
This presentation was presented at the Saudi Health 2014 International Nursing Conference and introduced the basic concepts of human factors theory in nursing. Case studies were used as examples to draw on the factors that contribute to issues of care, which directly affect patients. Interventions of how to address common human factors to minimize risks were also discussed.
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Matching EHR Tool to Task: Making it Easier to CareJeffery Belden
Presentation at I-PrACTISE Conference at U Wisconsin. Shared graphical display of home & office BP to improve collaborative decision making for better BP control. How sharing the EHR display between doctor and patient affects their interactions.
Producing "Inspired EHRs: Designing for Clinicians" online at inspiredEHRs.org, designed for health IT development teams.
Purpose of the Call:
Women's College Hospital is an academic ambulatory hospital. The speaker will share their hospital’s journey as they sought to implement best practices for medication reconciliation from other settings customized for the ambulatory environment.
Read more and watch the webinar recording: http://bit.ly/1sxHIUP
SHI2019 Immersion and Perspective Taking in Healthcare Technology: Supporting...Renée Schulz
Presentation for the paper at SHI2019/ EHiN2019 in Oslo.
Full paper: https://www.researchgate.net/publication/337324074_Immersion_and_Perspective_Taking_in_Healthcare_Technology_Supporting_Healthcare_Professionals_with_Daily_Tasks_and_Clinical_Procedures
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Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representation learning where learned features are in low dimension, evolve through time, and are influenced by actions of an agent. As the representation learned captures the variation in the environment generated by agents, this kind of representation is particularly suitable for robotics and control scenarios. In particular, the low dimension helps to overcome the curse of dimensionality, provides easier interpretation and utilization by humans and can help improve performance and speed in policy learning algorithms such as reinforcement learning.
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Tobacco Use: Immediate effects include increased heart rate, while long-term risks encompass cancer and heart disease.
Drug Use: Risks vary depending on the drug type, including health and psychological implications.
Prevention Strategies: Education, healthy coping mechanisms, community support, and policies are vital in preventing substance use.
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Seeking Help for Addiction: Recognizing signs, available treatments, support systems, and resources are essential for recovery.
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Resources: Provide contact information and links for further support.
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Smart Dosing: A mobile application for tracking the medication tray-filling and dispensation processes in hospital wards
1. Smart Dosing: A mobile application for tracking the medication tray-filling and dispensation processes in hospital wards
NaumanKhan, Natalia DíazRodríguez,Ivan Porresand Johan Lilius(ÅboAkademiUniv., Finland)
RiittaDanielsson-Ojala, Hanna Pirinen, LottaKauhanenand SannaSalanterä(University of Turku, Finland)
SebuBjörklund, Joachim Majors and KimmoRautanen
(MediaCityContent Testing Lab., Finland)
TapioSalakoski, IlonaTuominen(University of Turku, Finland)
6th International Workshop on Intelligent Environments Supporting Healthcare and Well-being WISHWell'14 within Ambient Intelligence (AmI'14), Eindhoven, The Netherlands. 11/11/14
2. Contents
•Introduction
•Problem: Medication dispensation in hospital wards
•Pilot test: field work at hospital wards
•Eye-tracking, stress response
•Medication dispensing process evaluation
•Building Smart Dosingtablet application
•UI usability evaluation
•Conclusions and Future Work
3. Introduction
•Medication dispensation in hospital wards today:
•Painstaking, tedious and meticulous work
•Mistake-prone, time-consuming
•DB non centralized: find equivalent medications, correspondences, secondary effects, etc.
•Mainly manually
•IT can help!
Pilot test observing nurses daily tasks in
2 university hospital wards in Finland:
•Cancer patients (21 beds and 14
nurses)
•Plastic surgery ward (16 beds and 12
nurses)
4. •Hospital medical errors (Finland): Up to 1700 lives claimed yearly. Medicine dispensing related-tasks: major cause
•Last years, 340,000 (medical errors and patient safety) incidents in hospital districts
•Many manual and computerized tasks -> can lead to potential oversights and errors.
Motivation
5. Use pilot test findings [1] to implement a tablet application that:
a.Saves time
b.Reduces proneness to errors
c.Reduces the nurses’ stress
[1]NataliaDíazRodríguez,JohanLilius,RiittaDanielsson-Ojala,HannaPirinen, LottaKauhanen,SannaSalanterä,JoachimMajors,SebuBjörlund,KimmoRautanen,TapioSalakoski,IlonaTuominen,CanITHealth-CareApplicationsImprovetheMedicationTray-FillingProcessAtHospitalWards?AnExploratoryStudyUsingEye-TrackingandStressResponse.In:AugustoVenâncioNeto,JoséNeumandeSouza(Eds.),16thIEEEInternationalConferenceonE-healthNetworking,Application&Services(HealthCom),Brazil,347–352,2014.
Main aim?
6. Problem: Medication dispensation in hospital wards
●Today: multiphase process:
retrieving, preparing, administering,
documenting and monitoring.
●Medication errors in all
phases. Highest occurrence:
preparing the tray with pills.
9. Medication adherence or pill reminders
●Life Capsule
●MediSafe
●Epocrates
●Smart TV Medicine Tracker
●e-pill
●Wedjat
●Healthcare@Home(H@H)
●and other medication dispensers, e.g. for Alzheimer patients
However, no application designed for nurses
(all designed for patients use)
10. Pilot test: field work at hospital wards
●Mixed data gathering methods:
•TobiiEye Tracking glasses
•Stress sensor Affectiva: Electrodermalactivity (EDA, i.e., galvanic skin response).
●Video
●Data gathering within user centreddesign (to achieve usability in interactive system development)
●QUESTION:
Can some subtasks be made more effective?
11. Medication dispensing process evaluation
Answer: YES!
According to pilot [1]
•23 registered nurses interviewed
•13 sub-tasks (some optional)
[1] Natalia DíazRodríguez, Johan Lilius, RiittaDanielsson-Ojala, Hanna Pirinen, LottaKauhanen, SannaSalanterä, Joachim Majors, SebuBjörlund, KimmoRautanen, TapioSalakoski, IlonaTuominen,Can IT Health-Care Applications Improve the Medication Tray-Filling Process At Hospital Wards? An Exploratory Study Using Eye-Tracking and Stress Response. In: Augusto VenâncioNeto, José Neumande Souza (Eds.),16th IEEE International Conference on E-health Networking, Application & Services (HealthCom), Brazil, 347–352, 2014.
12. Medication dispensing process evaluation
1) Print and cut out the patients’ medicine paper list. These print-outs,contain the patient’s treatments, dosage and administration timing information (this pre-step was not considered during the eye-tracking recording process).
2) Clean work space area and hands.
3) Unlock medicine cabinets (narcotics have extra security keys in separate cabinet).
4) Organize different colour medicine cups to be filled according to time period of the day (morning, noon, evening, night).
5) Search for medicine in cabinet.
6) Keep track of where on the patient’s medicine paper list the nurse is, which medicine has been filled and which is next.
7) Fill colour cups with medicine.
8) Halve medicine pill.
9) Look up medicine equivalences in Pharmaca Fennica medical components catalogue.
10) Look up medicine on web page if not found in Pharmaca Fennica.
11) Double check medicine paper list with the amount of medicine filled in cups.
12) Put medicine cups and patient medicine paper list on tray.
13) Write information on syringe/medicine package/paper list.
15. Optional vs Recurrent tasks
Always:
●Unlock the medicine cabinet
●Line up or organize cups for medicine
●Look at the patient medicine paper list
●Search for medicine
●Fill the cups with pills
●Finally line up cups on tray
Not so frequent tasks:
●Sanitize work space
●Print and cut out patient medicine paper list
●Halve medicine pill
●Look up medicine in Pharmaca Fennicaand on a computer
●Double check the list with filled medicine cups, and write info on medicine paper lists and/or syringes.
Tricks or knacks:
●Double checking lists, amounts and medication dosages, track tray slots, double checking the patient/medicine they are working on (e.g. using a tongue dispenser)
16. Most error-prone tasks
●When taking out medicine from its package (pushing pills out of the pill cart into a cup and taking pills out of the jar with a spoon/pliers)
●Putting right amount of medicine in the right coloured cup
17. Where do nurses spent more time?
4-22 min on the tray-filling process (depending on how many patients they dispense medicine to and if they need to look up in PharmacaFennica)
Most time consuming task:
●6 min 26 s (out of 22 min): searchingfor specific medicines. When not finding a specific medicine in the list (going to other PC’s DB) (about 45 % of the whole process time).
•2 min and 51 s: searching for medicine in PharmacaFennicaand looking it up on the PC.
●3 min 22 s: lookingat the patient medicine list(29% of the time), and double check names and quantities of each medicine.
●26 % of the time: dispensingmedicine into cups and putting medicine back into its place in the cabinet.
18. Where do nurses spent more time?
When not having to search equivalence medication catalogue:
●Searching for medicine
●Writing information on syringe packages and on specific medicine packages
●Opening medicine package, taking out the pills and placing them in cups
●Putting medicine package back to its place
●Organizing the coloured cup for the patients
●Halving the medicine pills
●Unlocking medicine cabinets
19. Dispensing process evaluation
Assessing the nurses’ feelings and mental stress:
PXLabSelf-Assessment-Manikin (SAM) Scale for valence in relation to visual stimuli, and a dominance and arousal scale, as a 5-, 7-, and 9-point scale.
Valence
Arousal
21. Pilot 1-Practical solutions
●Unlock medicine cabinet (if there is a locked room for medication dealing only)
●Having medicine packages stored to avoid opening drawers (more practical design cabinets).
●Medication room only for medication purposes (against interruptions)
●Bigger workspace
22. Pilot 1-Insights
●There is room to improve existing medication dispensation system (lower risks and time, increase patient safety).
●After identifying most tedious and time consuming tasks and giving insights to improve the process’ efficiency, we propose:
●A tablet-based wizard navigation model (step- by-step) to facilitate information gathering and searching times
•Examination gloves may hinder the use of a tablet?
32. •Chances of human errors during medicine dispensation tasks:
•Non centralized info.
•Tedious work, pen and paper
•Different nurses and shifts
•Lack of history tracking system
•We propose Smart Dosingto gather all relevant info. for more versatile tray filling & dispensingprocesses.
•Relatively low values in the questionnaire: some nurse requirements not met yet?
•Expenses for learning and deploying the system should pay back; not bring adverse effects*.
•In next(real lifesytemdeployment) pilot weexpect:
•Reducetime (double checking tray content and in general)
•Minimize errors
•Less tedious and meticulous tasks: reduce work load
(*) As in computerized physician order entry system which significantly increased mortality rates from 2.8% to 6.57% after implementation [9,12]
Conclusions and Future Work
33. Thank you for your attention!
MORE INFORMATION: Natalia Díaz, ndiaz@abo.fi
Riitta Danielsson-Ojala, rkdaoj@utu.fihttp://www.utu.fi/en/units/med/units/hoitotiede/research/projects/ikitik/Pages/home.aspx
http://tucs.fi/
34. Pilot 1
Conclusions and Future Work
IT-application would be beneficial if
●It would automatically recognize from the medicine list that the medicine is not available (and show its substitute directly instead).
●Having medicine DB built-in search function (where typing the name of the drug gives information on the spot).
Questions to address when designing an IT-application:
●How is the information presented? What draws the nurses attention? What visual strategy they follow to optimize the search process?
●Showing package look and pill look (speed up visual cabinet search)
FUTURE: Pilot test the mobile application