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Transcript of Medinfo2015 workshop-adherence mangement-patient_driven-publicized
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Effective Patient Adherence Management by Engaging Enabling
Technologies
MEDINFO 2015 Workshop Aug 22 Saturday 14:30 - 16:00
Pei-Yun Sabrina Hsueha, Marion Ball, Vimla L. Patelb, Fernando Sanchezc, Marcia Itod,e, Chohreh Partoviana, María V. Giussi Bordonig, Henry Chang
Addressing Patient Adherence Issues by Engaging Enabling Technologies
2
Senior Advisor, Research Industry Specialist, Healthcare Informatics, IBM Research
Professor Emerita, Johns Hopkins University Affiliate professor, Division of Health Sciences
Informatics, Johns Hopkins School of Medicine Member, Institute of Medicine Serve on the Board Of Regents of the National Library of
Medicine Past President, International Medical Informatics
Association ( IMIA) Board member of American Medical Informatics
Association (AMIA)
Fellow: American College of Medical Informatics (ACMI), Past Board member and Fellow of the Health Information
Management and Systems Society( HIMSS), American Health Information Management Association (AHIMA) Medical Library Association (MLA) and the College of Health Information Management Executives (CHIME), American Academy of Nursing (FAAN)
Marion J. Ball, Ed.D
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Pei-Yun (Sabrina) Hsueh, PhD
Wellness Analytics LeadGlobal Technology Outlook Healthcare Topic co-LeadHealthcare Informatics PIC co-Chair Computational Behavioral and Decision Science Group Health Informatics Research Dept. IBM T. J. Watson Research Center
• Research focus: Insight-driven Healthcare service design, Patient-generation info from wearables and biosensor devices/implants, Personalization analytics framework for lifestyle intervention, Patient engagement & Adherence risk mitigation
Opening Remark
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Source: Based on McGinnis et al, The Case for More Active Policy Attention to Health Promotion, Health Affairs, 2002.
Health Determinants Mismatches Today’s Spending“We need to invest in addressing all determinants of health…”
BIG DATAClinical + behavior
drivenWellness Management
reduce
expand
Slide credit: Henry Chang
CLINICAL
GENETIC
EXOGENOUS
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Credit: John Rogers, Univ. of Illinois
Effective Patient Adherence Management by Engaging Enabling Technologies
Ion ~1 A
Protein ~10 nm
Synapse ~1 m
Compartment ~10 m
Dendrite ~100 m
Neuron ~500 m
Microcircuit ~1 mm
Network ~5 mm
Brain Region ~1 cm
Brain Tissue ~5 cm
Whole Brain ~10 cm
Organism ~1 m
DEVICES
MOLECULES
Multiscale Multimodal Brain Systems Modeling
Clinical Inputs
SIMULATION+ ANALYTICS
Clinical Prediction
Clinical Data
PET
MRI
BEHAVIOR
Credit: James Kozloski, IBM
Addressing Patient Adherence Issues by Engaging Enabling TechnologiesIt’s Data. Big Data!
It’s also not just Big Data!
1240 PB
1800 PB
6800 PB(annual)
Clinical:Episodic; care pathways in controlled settings Genomic: Mostly static
data, but critical for personalized medicine
Exogenous data (behavioral, social, environmental)Social and behavioral phenotypes + Exposome informatics
Exogenous Data Growing Fast !
NOISY, LARGE VOLUME, UNCONTROLLED
Need minimum description & quality control
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Turning big data to actionable small data
1990 Empirical MedicineIntuitive
Medicine
Personalized Service
Personalized service (Individualized Calibration)
Knowledge-driven Guideline
Precision Medicine
Degree of personalization
Degree of
collaboration (data dim
ension) Data-Driven Evidence
Century of behavior change
Hypothesis Modeling
++
Hyper-PersonalizationN of 1 clinical trial
Addressing Patient Adherence Issues by Engaging Enabling Technologies
IBM Confidential12
Recap from MEDINFO 2013 PANEL: Personalized Healthcare: Issues and Challenges
The true benefit of consumer technologies and consumer health informatics is not in the quantity of data they provide, but in how they transform data into useful
information that can make a difference, and improve value and care.Review physician cognitive model and the need to understand consumers
challenge in physician-patient communication: the lack of social context -- “christmas problem”challenge in cross-culture communication
challenge in designing instructions for medication managementThe potential of using technologies (e.g., mobile text messaging) to increase
adherence
Addressing Patient Adherence Issues by Engaging Enabling Technologies
IBM Confidential13
Recap from MIE 2014 WORKSHOP: Gaps observed in the use of Patient-Generated Data in Personalized Service Design
• The lack of reliable means to capture granular patient-generated data in non-clinical settings (user’s daily life contexts)– Leads to unreliable detection of inflection points, habit formation cycles and assessments of
treatment efficacy. • Need for a framework to integrate analytical insights with feasible service models.
– Progress impeded by the lack of modular design and data standardization in existing healthcare systems
Customer/Patient
Adherence
Theme#1
Theme#2
Theme#3
Personalization for risk stratification
(from population to individual evidence)
Personalization for in-context recommendation (from disease-centric to
patient-centric)
Personalization for adherence risk
mitigation (from status-insensitive
to status-sensitive)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
MEDDIN 2015 Focus Area: Adherence risk mitigation
- Less than 50% of patients adhere to clinical recommendations- 20 to 30% of prescriptions are never filled - 194,500 deaths a year and an additional 125 billion (EU) - 69% of adverse event-related hospital admissions, $100-$290 billion annually (US) - $30 - $594 billion dollars annually (global)- UK, France and Belgium have started including pharmacists as a mean to gather
additional information on patient adherence
How to bring patients and clinicians into the loop for evidence-based conversation?
Addressing Patient Adherence Issues by Engaging Enabling Technologies
15
Key Challenges in Adherence Risk Mitigation Existing system’s lack of capabilities to account for case history has resulted in not
being able to differentiate urgent cases. Care coordinators have to handle all case exceptions equally; this is a costly
process given the sheer number of guideline violations per day.
• Personalized continuous feedback loop mechanism • Adherence monitoring on an
individual basis• Accommodate individual
differences in the way users behave
• Instant feedbacks on non-adherence• Detect changes in personal
activity model and identify problems
• Specify problem areas in physical activity segments and replay correct sequences
Collaborative Care
• Provide an evidence re-examination mechanism • Update the current personal activity
model in PWR according to latest behavioral changes
• Recommended services w.r.t. changes revealed in the monitoring context
Evidence Delivery
• Reuse evidence generated from population databases• Save time and cost in training• Learning from the coach-based (or
population-based) model.
Evidence Generation
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Will patient-generated data help?
• Parity of information access is important to effective engagement• The fact of creating, managing, and reporting data has the potential to
empower patients, to engage and “activate” them• “Patients who read their notes, collected personal health data, and
maintained a record became more aware of their conditions and behaviors => felt more in control of their care, and showed increased participation”
• Can address information gap and ensure continuity of care after discharge from hospital or between visits
• Leverage untapped patient experience for shared decision making
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Case Study: promoting physical activity in children• multitude of projects, e.g. Plischke et al, 2008, Stud Health
Technol Inform, cyberMarathon study, wearable sensor data feedback
• results:– change in BMI over a year in intervention group– +11.4% daily physical activity MET level
17
Credit: Michael Marschollek Prof. Dr. med Dr. Ing
(Director of Hanover Medical School, Peter L. Reichertz Institute for Medical Informatics)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
18
This analysis was performed using data from our program, supplemented with data from respected sources to estimate cost savings.
Analysis:
Results:
Compared to the control group, patients in the intervention group demonstrated 2x rehab completion, ¼ no-show rate at 3-month follow-up appointment, better exercise tolerance, & lower depression scores
Increased rehab completion rate reduces utilization → meaningful savingsEntity: HospitalPopulation: Commercial + Medicaid; Urban + RuralAverage age: 55n = 100English level: 6th gradeBenefit to hospital: Reduced 30-day readmissions for AMI, CABG, Stent, CHFCost savings: ~ $1,300 annual savings per member
Case Study: Promoting cardiac rehab program adherence through mobile text messaging
Credit: Bern Shen (CEO, HealthCrowd)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
What we are looking for at the individual level…….
Slide courtesy credit: Prof. Lange (UCI)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Stages of Change Model
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Source: Based on McGinnis et al, The Case for More Active Policy Attention to Health Promotion, Health Affairs, 2002.
Health Determinants Mismatches Today’s Spending“We need to invest in addressing all determinants of health…”
BIG DATAClinical + behavior
drivenWellness Management
reduce
expand
Slide credit: Henry Chang
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD, DSc, FRSC• Senior Research Scientist, The New York Academy of Medicine• Director, Center for Cognitive Studies in Medicine and Public health• Adjunct Professor, Biomedical Informatics. Columbia University, NY• Adjunct Professor, Public Health, Weill Cornell Medical Center, NY• Professor of Biomedical Informatics, Arizona State University
• Fellow of the Royal Society of Canada (Academy of Social Sciences)• Fellow, American College of Medical Informatics• Associate Editor, Journal of Biomedical Informative (JBI)• Editorial Boards of Journal of Artificial Intelligence in Medicine
(AIM), Advances in Health Science Education (AHSE), Topics in Cognitive Science.
• Past Vice-President (Member services), International Medical Informatics Association (IMIA)
• Past Vice-Chair, AMIA Scientific Program Committee• Past Editorial Boards: International Journal of Medical Informatics
(IJMI), Journal of Medical Decision Making (MDM)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Understanding People for Technology Support
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Knowledge Infrastructure Continuum
Knowledge
Generation– Scientific—Journals– Informal—Community
– Purpose—Real World ContextUtilization
Transmission– Through Technology– Face-to-face
Communication
– Mental Models—UsersRepresentation
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Impediment to Medication Adherence (2)
Implementation of medication administration instructions without understanding the nature of the users social context
Patel, V.L., Eisemon, T.O. & Arocha, J.F. (1988) Causal reasoning and treatment of diarrheal disease by mothers in Kenya. Social Science & Medicine, 27(11), 1277-1286.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Case 1: Oral Rehydration Therapy (ORT)
• Used in the treatment of dehydration in children with diarrhea
• Correct implementation involves preparation of sterile media (boil water) and the administration of a constant dosage at irregular intervals
• Patients are required to execute a complex procedure
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Pharmaceutical Instructions for ORTThe solution replaces body water and body salts lost during diarrhea. How to use this solution (for children up to 5-years old). Boil a tumbler of water up to mark (300ml). Add all powder from sachet to cool water. Stir.
Give two or three tumblers during the first 4 to 6 hours. Give 2 or 3 more tumblers over the next 18 to 24 hours. Give 2 more tumblers in the following 24 hours. Do not give more than 6 tumblers in 24 hours.
IMPORTANT Always use as instructed unless otherwise directed by your doctor. Give slowly to prevent vomiting during treatment. Use clean spoon to give the solution to small babies. If baby is thirsty between drinks of the solution give plain boiled and cooled water. Begin normal feeding as soon as possible.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Procedural Representation of ORT InstructionsProcedures Sub- Procedures
1. How to prepare the solution 1.1 Fill tumbler with water
1.2 Boil water 1.3 Cool water
1.4 Add powder 1.5 Stir 2. How to administer the solution 2.1 Give 2-3 tumblers, first 4-6 hours
2.2 Give 2-3 more tumblers, next 18-24 hours 2.3 Give 2 or more tumblers, following 24 hours
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Results
Observations (in the wild) of Mothers in Kenya (Africa) and Montreal (Canada) while preparing medication
– Most of the participants correctly followed the instructions for preparation the ORT solutions
– Only 50% of the mothers were able to correctly administer the first stage of ORT
– Only those with graduate degree were able to correctly administer medication for all stages of therapy
Effective Patient Adherence Management by Engaging Enabling Technologies
Mean Level of Accuracy in Interpreting the ORT Procedure
Level of education
Mea
n A
ccur
acy
Graduate Degree All other levels0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Urban CanadianUrban KenyanRural Kenyan
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Problem Identification: Challenge
• Non-uniformity of instructions: Too complex for the most needy patient context, leading to lack of adherence
• Instructions insensitive to socio-cultural context: boiling a pre-determined amount of water, leading to adverse events in small babies
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Impediment to Medication Adherence (3)
Different (sometimes conflicting) mental models of medication administration for the patients, healthcare providers, and the designers of instructions
Patel, V.L., Eisemon, T.O. & Arocha, J.F. (1990) Comprehending instructions for using pharmaceutical products in rural Kenya. Instructional Science, 19, 71-84.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Case 2: Antipyretic Drops • Over-the-counter medicine used in
the treatment of the common fever• Correct implementation involves a
simple procedure and calculation but requires an appropriate medication plan for the child
• Mothers were asked to follow the instructions for youngest child in the family
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Pharmaceutical Instructions for Antipyretic DropsEACH 1 ml DOSE CONTAINS: 80 mg acetaminophenINDICATIONS: For fast and effective relief of children's fever and pain.DOSAGE: Administer single dose orally according to age as listed, 4 to
5 times daily, for maximum of 5 days. Age Maximum Single DoseUnder 2 years as directed by Physician2 to 3 years 2.0 ml (160 mg)4 to 5 years 3.0 ml (240 mg)6 to 8 years 4.0 ml (320 mg)9 to 10 years 5.0 ml (400 mg)11 to 12 years 6.0 ml (480 mg)
Consult a physician if the underlying condition requires use for more than five days. It is hazardous to exceed recommended dose unless advised by a physician.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Results– The majority of participants (77.7%) were
unable to correctly suggest therapy schedules for the administration of the proper amount of medication
– The participants consistently identified the frequency of administration recommended in the instructions as “too much”, since the suggested plan did not make intuitive sense
Effective Patient Adherence Management by Engaging Enabling Technologies
Dosage Accuracy for Antipyretic Drops
Accuracy
Perc
enta
ge
01020304050607080
Underdose
Correctdose
Slightoverdose
Extremeoverdose
English East AsianGreek
Effective Patient Adherence Management by Engaging Enabling Technologies
Usage Picture of Antipyretic Drops as Provided by a Primary Care Physician
Effective Patient Adherence Management by Engaging Enabling Technologies
Usage Picture of Antipyretic Drops as Provided by a Pharmacologist
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Think-Aloud Protocol Quotation #1
The doctor told us how much to give her, but I wouldn't give it to her five times a day. The maximum four and probably we might give it to her twice in the daytime and once before she went to bed. I wouldn't give it to her unless I thought she needed it. I have never given it five times a day to any of my children.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Think-Aloud Protocol Quotation #2
I would give him 3 milliliters using the pharmaceutical measuring spoon I have. I only give fever medicine when it is necessary. I don't believe in giving a lot of medicine to the children. I am really cautious when it comes to that, I only treat the fever when it needs it. If my son looks ok, then I don’t give anything
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Problem Identification: Challenge– Both under-dose and overdose of medication , leads
to the child not getting the best medical care– The frame of referent situation intended by the
instruction was with inaccurate understanding that it is shared by all readers (users), such that the identification of the appropriate representation will be facilitated
– The Medication instructions do not "make contact" with the subjective or intuitive models used by readers (patients) when interpreting them, and so they will fail to have their intended effects
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Thank You!
www.lodhia-patel.net
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Effective Patient Adherence Management by Engaging Enabling Technologies
Digital Medicine (Convergence of digital revolution and medicine)
• We have witnessed the impact of the digital revolution in other domains (banking, insurance, leisure, government,…)
• Although digital technology has greatly affected healthcare at the hospital or research centre level.
• The digital revolution has not yet reached medicine at the patient/citizen level
• THIS IS STARTING TO HAPPEN NOW !!!
Shaffer, D.W., Kigin, C.M., Kaput, J.J. & Gazelle, G.S. Stud. Health Technol. Inform. 80,195–204 (2002)
Effective Patient Adherence Management by Engaging Enabling Technologies
Participatory Health
Regina Holliday
The Society for Participatory Medicine defines participatory medicine as a movement in which networked patients shift from being mere passengers to responsible drivers of their health, and in which medical care providers encourage and value them as full partners.
Effective Patient Adherence Management by Engaging Enabling Technologies
History of Participatory Health
• September 2009 – California Healthcare Foundation Report: “Participatory Health: Online and Mobile Tools Help Chronically Ill Manage Their Care”
• “Partnership between patients and providers and trusted experts, one in which participation is enabled and enhanced by technology and information”
• “Patients are the most under-utilized resource, and they have the most at stake. They want to be involved and they can be involved. Their participation will lead to better medical outcomes at lower costs with dramatically higher patient/customer satisfaction”
Charles Safran MD
Effective Patient Adherence Management by Engaging Enabling Technologies
Patients areimpatient
Effective Patient Adherence Management by Engaging Enabling Technologies
Patient advocacy
• Gimme my damn data!
• The patient will see you now…
• Let patients help
• Nothing about me without me!
Effective Patient Adherence Management by Engaging Enabling Technologies
Effective Patient Adherence Management by Engaging Enabling Technologies
Effective Patient Adherence Management by Engaging Enabling Technologies
Interest from GovernmentsUS Australian
MyHealthRecord
People are managing their own health better.
Effective Patient Adherence Management by Engaging Enabling Technologies
IOM Workshop & Report 2013Partnering with Patients to Drive Shared Decisions, Better Value, and Care Improvement - Workshop Proceedings
Shared decision making
Effective Patient Adherence Management by Engaging Enabling TechnologiesHealth Informatics and Participatory health
I. Personal genome services (23andMe) II. Personal diagnostic testing III. Personal medical image managementIV. Personal sensing and monitoring (QS)V. Personal health records VI. Patient reading doctor’s notes (OpenNotes)VII. Patient initiating clinical trials (PLM)VIII. Patient reporting outcomes (PROMIS)IX. Patient sharing data (Social Media)X. Shared decision making
Collectingdata
Exchangingand using information
Participatoryhealth
Effective Patient Adherence Management by Engaging Enabling Technologies
Open Notes – Patients reading Doctor’s notes
Effective Patient Adherence Management by Engaging Enabling Technologies
Patient reported outcomes
• Health services and outcomes research
• Measuring quality of care from the patient perspective
NHS PROMs
NIH
Effective Patient Adherence Management by Engaging Enabling Technologies
Shared decision making
Effective Patient Adherence Management by Engaging Enabling Technologies
Visualising personal health risks profiles
(Univ. Missouri)(Juhan Sonin, MIT)
Effective Patient Adherence Management by Engaging Enabling TechnologiesTherapeutic affordances of social media
Merolli M, Gray K, Martin-Sanchez F. Developing a Framework to Generate Evidence of Health Outcomes From Social Media Use in Chronic Disease Management. Med 2.0, 2013. 2(2): e3.
1 2 3
Effective Patient Adherence Management by Engaging Enabling Technologies
White Paper
http://www.broadband.unimelb.edu.au
Activity Theory + Patient Activation
Effective Patient Adherence Management by Engaging Enabling Technologies
DeviceSample
Data
Where is it stored
Units
Location
Time
Body part (FMA)
Method
Name Model
Manufacturer
Technical Specs
Taxonomy
Body structureBody functionAround body
(based on WHO)
Who/Which part/Where/When?
What
How?
Processed
Raw
Minimum Information about a Self Monitoring Experiment (MISME)
Procedures
EXPERIMENT
Measurement
Effective Patient Adherence Management by Engaging Enabling Technologies
TensionsPatient advocatesClinicians’ resistance
to change
Effective Patient Adherence Management by Engaging Enabling Technologies
Australian Doctors the least open toward patients updating the information in their EHRs
Effective Patient Adherence Management by Engaging Enabling Technologies
MEDICINE PARTICIPATORY HEALTH
Provider-centric Patient or Consumer-centric
Curative Proactive
Passive role of the patient Active
Clinical decision making Shared decision making
Electronic medical record Patient Health Record
Adherence, compliance vs activationLiteracy vs ClarityResearch n=they vs n=me and n=we
Patient-generated data
Effective Patient Adherence Management by Engaging Enabling Technologies
AMA
• it must be recognised that as a design feature of the PCEHR, patient control means that the PCEHR cannot be relied on as a trusted source of key clinical information.
• The absence of specific remuneration for medical practitioner contribution to the PCEHR reinforces the need to ensure that using PCEHR functions does not impose any additional workflow requirements on them.
Consumer Health Forum, Consumer e-health Alliance
• The ‘personally controlled’ aspect of the eHealth record is what makes it such a powerful consumer resource.
• Patients and potential patients – health consumers – must be informed and engaged as the ultimate users of the PCEHR.
Submissions to Australian PCEHR Review - Nov 2013
Effective Patient Adherence Management by Engaging Enabling Technologies
Effective Patient Adherence Management by Engaging Enabling Technologies
Evolution
Shenkin B, Warner D. Giving the patient his medical record: a proposal to improve the system. NEJM, 1973
Effective Patient Adherence Management by Engaging Enabling Technologies
Benefits
• Better outcomes• Lower costs• Better patient experience• Motivation• Deepening understanding of their health• Self-improvement• Risk profiling• Prevention• Shift terciary secondary primary home care• Data donors for research
Effective Patient Adherence Management by Engaging Enabling Technologies
• Privacy• Security• Education• Cyberchondria• Equity• Regulation, accreditation• Role of the clinician• Infrastructure needs• Therapeutic gap (ethics)
Issues
Effective Patient Adherence Management by Engaging Enabling Technologies
Dr. Charles Safran, AMIA
Effective Patient Adherence Management by Engaging Enabling Technologies
© Copyright The University of Melbourne 2015
Thank you for your attention!
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
Addressing Patient Adherence Issues by Engaging Enabling Technologies
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Hungyang (Henry) Chang , PhD• Senior Research Staff member, Healthcare Informatics, IBM T.J. Watson Research center
• Program leader of WellVille initiatives for mobile health based improvements of community health
• Research lead of IBM Connected healthcare analytics for chronic disease management
• Program Director of IBM research collaborator in Taiwan for Health and Wellness (2010-2013), conducting technology development for chronic disease patient engagement via health literacy intelligence
• Research manager of business performance monitoring and management with technical responsibility to provide innovation leadership to IBM Websphere BPM suits and IBM internal supply chain visibility initiatives.
• IBM Innovate Awards for his works on model-based business transformation and B2B collaboration solution.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
77
Medical Service Providers Wellness Service Providers Exercise Service ProvidersDietary Service ProvidersService Device Providers
ServiceComponents
DiseaseMgnt.
DiseasePrevention
DiseaseTreatment
WellnessMgnt.
ExerciseMgnt.
DietaryMgnt.
Personalized CareElder CareServiceScenarios
ServiceProcesses
Dietary Recommendation
Exercise PlanDisease Mgnt.
Wellness Ecosystems– Research Framing
78
Addressing Patient Adherence Issues by Engaging Enabling Technologies
78
Diabetes Mellitus case manager service flow (Outpatient Clinic)
Healt
h Ed
ucatio
n Clin
ic(Ce
rtified
Dia
betes
Ed
ucator
)
Outpa
tient
Clinic
(Do
ctor)
Diabe
tes
Mellit
us Sha
red Ca
re Ne
twork
Healt
h Pro
motio
n Ma
nagem
ent
Cente
r(Ca
se ma
nager
)
Patie
ntHo
spital
Clinic
al Ch
emistr
y Lab
orator
y
Nutriti
on
Coun
seling
Cli
nicOutpatient Clinic Stage
Start
Appointments& Registration
Referral patients?
Outpatient Clinic
Diagnosis
Diabetes Mellitus?
CashierOPD
Dispensary
N
End
Meet DM Case
Criteria?Y
Collect Batch Case
Y
Health Education
Clinic
N
Transfer Case to Diabetes Mellitus Shared Care
Network by Batch System
Diabetes Mellitus
Shared Care Network
Education
Clinical Chemistry
Examination
Nutrition Counseling
Clinic
Physiology Examination
Clinical Chemistry
ExaminationReport
Physiology Examination
Report
Nutrition Health
Education
Referral Form
Y
N
Enrolled Case in Case
Management System
End
Diabetes Mellitus case manager service flow (Follow up)
Health
Edu
cation
Clinic
(Certifi
ed Dia
betes
Educat
or)
Outpa
tient
Clinic
(Docto
r)
Diabet
es Me
llitus
Shared
Care
Netwo
rk
Health
Pro
motio
n Ma
nagem
ent
Center
(Case m
anager
)
Patient
Hospi
talClin
ical
Chemis
try
Labora
tory
Nutriti
on Cou
nseling
Clin
ic
Follow up Stage
Start
Outpatient Clinic
Diagnosis
Cashier OPD Dispensary
End
Collect Batch Case
Health Education
Clinic
Transfer Case to Diabetes Mellitus Shared Care
Network by Batch System
Clinical Chemistry
Examination
Clinical Chemistry
ExaminationReport
Health Education
Clinic Referral
Care Plan Check
Appointments& Registration
Referral ? Y
N
N
Updat e Case
End
As-Is(in-site Hospital)
To-Be(IBM Mobile Health Pilot)
A DM Management Pilot for Newly Onset PatientsStart from Research Methodology to design innovated DM service procedure (2012-14)
Diabetes Mellitus case manager service flow (To-Be) (Follow up)
Heal
th
Educ
ation
Cl
inic
(Cer
tified
Di
abet
es
Educ
ator
)
Met
abol
ism
Out
patie
nt C
linic
(D
octo
r)
Diab
etes
M
ellit
us
Shar
ed C
are
Net
wor
k
Heal
th
Prom
otion
M
anag
emen
t Ce
nter
(Cas
e m
anag
er)
Patie
ntHo
spita
lGe
nera
l Dep
ertm
ent
Clin
ical
Che
mis
try
Labo
rato
ryHI
S(S
yste
m)
PHM
Clo
ud(S
yste
m)
Card
iolo
gyO
utpa
tient
Cl
inic
(D
octo
r)
Clin
ical
Supp
ort S
yste
m(S
yste
m)
Follow up Stage
Start
Outpatient For Ongoing
Management and Follow-Up
Cashier OPD Dispensary
Collect Batch Case
Health Education Clinic for Referral
Transfer Case to Diabetes Mellitus
Shared Care Network by Batch System
Clinical Chemistry
Examination
Clinical Chemistry
Examination
Report
Issue Referral for Outpatient
Clinic
Care Plan Check
Appointments& Registration
Should Patient
Be Referral
?
Y
N
N
Update Case
End
Invoke Data Integration
process
Request Clinical Support Report
Generate Clinical Support
Analytic Report
Provide Clinical Data
Analyze compiled
information
Clinical Support Report
Outpatient Clinic
Diagnosis
Consider Referral to Diabetes
Care Team or
Specialists
PHM Data Integration
CardiologyOutpatient Clinic for Referral
Outpatient Clinic
Diagnosis
Invoke PHM Integration
process
Update PHM Care Plan
Based on Care Plan issue notice
Receive Notification from PHM
Upload Glycemic and Blood Pressure Data to
PHM
Collect & Update PHM
Data
End
1 2
34
Hospital site IBM Cloud Platform
Effective Patient Adherence Management by Engaging Enabling Technologies
Lack of theoretical models has hampered wider use of patient-generated data in lifestyle interventions
Susceptibility
Severity
Benefits
Barriers
Demographics
Triggers/Cues
Self-efficacy
Likelihood of Adherence
Curated data provides significant opportunity for foundational behavioral analytics
Addressing Patient Adherence Issues by Engaging Enabling TechnologiesValue-add services in exercise management for weight loss (adherence/personalization)
●Evaluate the disease risk●Provide personal health
plan●Base on health screen
results and personal behavior
Health screening and personalized disease
risk assessment
/
Metabolism assessment and personalized effective
exercise plan design
●Real time heart rate monitoring
●Exercise plan guidance
●Heart rate data recording
Exercise plan execution
(Devices and environment)
●Plan execution, adherence tracking and management
Plan adherence and outcome
tracking
●Establish personal metabolism profile
●Provide personal effective exercise plan
●Base on personal resting & exercise metabolism assessments
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Group B & C show the difference “Active service intervention (on site coach)” shows the improvement of plan adherence
for +42%~51% “Active service intervention (on site coach)” shows the delay of adherence attrition for
average 7 weeks
• 0%• 20%• 40%• 60%• 80%
• 100%• 120%
• 1• 4• 7• 10• 13• 16• 19• 22• 25• 28
• Group B• Group C
• Linear regression of B• Linear regression of C
• C. Trend of average time spend % over time
• B. Trend of average complied exercise event % over time
• A. Trend of average exercise event % over time • D. Trend of average total calories burnt % over time
• E. Trend of average fat calories burnt % over time
• Slope C = -1.08
• Slope B = -1.34
• 50% drop = 23.1 weeks
• 50% drop = 18.7 weeks
• 1• 4• 7• 10• 13• 16• 19• 22• 25• 28• 0%
• 20%• 40%• 60%• 80%
• 100%• 120%
• 1• 4• 7• 10• 13• 16• 19• 22• 25• 28• 0%
• 20%• 40%• 60%• 80%
• 100%• 120%• 140%
• 1• 4• 7• 10• 13• 16• 19• 22• 25• 28• 0%
• 20%• 40%• 60%• 80%
• 100%• 120%• 140%
• 1• 4• 7• 10• 13• 16• 19• 22• 25• 28• 0%
• 20%• 40%• 60%• 80%
• 100%• 120%• 140%
• Slope C = -0.72
• Slope B = -1.51
• 50% drop = 34.8 weeks
• 50% drop = 16.6 weeks
• Slope C = -0.87
• Slope B = -1.04
• 50% drop = 28.8 weeks
• 50% drop = 24.0 weeks
• Slope C = -0.94
• Slope B = -1.25
• 50% drop = 26.5 weeks
• 50% drop = 20.1 weeks
• Slope C = -1.50
• Slope B = -1.61
• 50% drop = 16.7 weeks
• 50% drop = 15.5 weeks
• Delay 4.4 weeks
• Delay 4.8 weeks
• Delay 1.1 weeks
• Delay 18.3 weeks
• Delay 6.5 weeks
81
Significant improvement from active monitoring
Addressing Patient Adherence Issues by Engaging Enabling Technologies
How to leverage community data for actionable health Insight?
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
María Victoria Giussi
- MD, Buenos Aires University
- Family Physician
- Medical Resident at Health Informatics Department from Hospital Italiano de Buenos Aires.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Personal Health Record at HIBA
2001HIS- EHR
2007PHR
2012 PHR- UCD
• Web based & “in house” developed tools
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Some numbers
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
What makes our PHR important in Engaging Patients to their Healthcare?
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Our Strategy to achieve an Effective Patient Adherence is…
Knowing what patients really need
The integration with the EHR
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
We focus on:• Collect information about expectations and perceptions of both
physicians and patients in order to improve the tool
• Incorporate features based on real patient needs
• Encourage the active role of patients in the design and functionality of the PHR
• Knowing the impact of new technologies in the daily workflow of the physicians
• Empowering the patients to manage their health information
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
User Centered Design
Focus Groups Interviews in waiting room
Workshops
Analizing our data base
Effective management of patient suggestions
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Patients are the owners of their Health Data
- Entry Health Data
- Access to their Health Data
- Give access at their EHR to the Healthcare Professionals
- Share the access to their PHR with other people
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Active role in their Healthcare
• Engage in the design of the PHR
- Rediseño Centrado en el Usuario de un Portal Personal de Salud. Goldenberg J, et al. CBIS 2012
Menu without UCD Menu after UCD
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• PERSONALIZED HEALTH INFORMATION from MedlinePlus
• INFOBUTTONS
- Implementación de Arquitectura Orientada a Servicios (SOA) en un proyecto de E-Salud. Gómez A, et al. INFOLAC 2008.
- Integrating personalized health information from MedlinePlus in a patient portal . Borbolla et al. Stud Health Technol Inform. 2014;205:348-52.PMID: 25160204
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Desktop
Tablets
Smartphones
Portal Personal de Salud del Hospital Italiano. Evaluación del uso de su versión “Mobile” Gómez A, et al. INFOLAC 2014
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Desktop
Tablets
Smartphones
Portal Personal de Salud del Hospital Italiano. Evaluación del uso de su versión “Mobile” Gómez A, et al. INFOLAC 2014
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Web Message Service
- Diseño y evolución de un sistema de mensajería electrónico entre médicos y pacientes del HIBA . Giussi MV, et al. CBIS 2014.- Understandig how physicians respod messages sent by their patients. Almerares A, et al. CBIS 2014 - ¿Qué opinan los médicos acerca de la comunicación electrónica con sus pacientes? Khorsadnia B, et al. CBIS 2014
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Suggestions for improvement through the Helpdesk
• Solve some problems with the use of the PHR
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Administrative Consultations
• Schedule an appointment with physician
• View study results from the EHR and upload results
• Consult physicians directory
• Update vital signs
• View and manage prescriptions
• View all referrals
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Remote Consultations
• Digital literacy of the Elderly
• Improving conditions of life for the Elderly through the use of ICT: Active Assisted Living programme (AAL)
• Improvements for the PHR Mobile App
• Integration of patient health data generated by wearables and external devices to the EHR trough PHR
• Medication Reconciliation by patients
• Accuracy of the Problem List
• Health Forums
• Patient Access to progress notes
• Health Assets GIS Mapping
Working on…
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Data generated per patient (per life)
Genomics6 Terabytes
Exogenous Data (Behavior, environment, etc)1.100 Terabytes
Extracted from IBM Watson for Oncology.
Clinical Data0.4 Terabytes
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Conclusion
Strategic Decision
Thinking, developing, testing and
implementing the tool
Evaluate use Measure Outcomes
Personal Health Record at HIBA
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Giussi María Victoria, [email protected]
Thank You
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Márcia Ito, MD, PhD • Formation– Medical Doctor – EPM-UNIFESP/Brazil – PhD in Electronic Engineering – USP/Brazil – Data processing technologist – Fatec-SP/Brazil
• Research Scientist at IBM Brazil Research Lab• Visitor Professor at Health Informatics Department of EPM-UNIFESP• Teacher at MBA in Health Management at FGV-SP• Coordinator of Health Computation Applied Special Interest Group of the
Brazilian Computer Society (SBC)• Co-chair of HL7 Brazil• Member of Special Committee in Health Informatics Standardization at
ABNT (ISO/TC-215) – Working Group 1 and 2• Master degree advisor at IPT-USP• College Professor at Fatec-SP
• Past Executive Secretary of the Brazilian Health Informatics Society (2012-2014)
• Past Vice-Coordinator of Health Computation Applied Special Interest Group of the Brazilian Computer Society (2012-2014)
• Past Coordinator of the Research Laboratory Sciences Service in Paula Souza Center (2007-2011)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
The title of Dr. Ito’s Presentation will be:
• A Collaborative System based on Chronic Patient Relationship Management Model as a form to engage patient adherence to his treatment
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Chronic diseases require the care of several healthcare professionals, in addition we need to increase the engagement of patient adherence to his treatment– We must understand the patient as a human being and not only
disease evolution of him – personalized care and patient centered care
– Increase the interaction between the patient and his care team – collaborative relationship and care coordination
– The electronic medical records of the patient were not meeting those needs. Creates a set of objectives to develop useful EHR. – Meaningful Use
Healthcare Current Scenario
Addressing Patient Adherence Issues by Engaging Enabling Technologies
• Care Coordination– decrease the fragmentation of care and improve the delivery of health services– Sucess programs:
• the relationship between the care coordinator and the patient was beyond medical service• the care coordinator knows the needs of the patient and connected to him personally• long lasting relationships and trust between the patient and the care team and among
members of the care team – The relationship between the coordinator and the patient is the key, because
the treatment involve change behavior and choices that made by the patient.• Meaningful use is using certified electronic health record (EHR)
technology to:– Use the information to engage patients and their families in their care– Improve quality, safety, efficiency, and reduce health disparities– Improve care coordination, and population and public health– Maintain privacy and security of patient health information
Healthcare Current Scenario
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Chronic Patient Management – CPRM (Chronic Patient Relationship Management) Model – Conceptual Approach
• A model that makes the appropriate coordinate patient care so that we can prevent the disease, its complications or deaths: – Everybody is responsible for theirs health
(prevention, treatment adherence, etc.)– Participate in their treatment decisions
(collaborative relationship between doctor and patient)
– adequate control of the disease, based on best practice (translational medicine and evidence-based medicine) and the psychosocial context of the patient.
– Monitoring, assessment and control of laboratory tests, physical and psychosocial status of the patient
– Patient and physician behavior change – Better quality of health and life
• For all these phases we will need new integrated technologies.
Adapted from IBM, 2006: Healthcare 2015: Win-win or lose-lose?
Font: Adapted from ITO, M., MARTINI, J. S. C., IOCHIDA, L. C. CPRM: A Chronic Patient's Management Model Based on the Concepts of Customer Relationship In: 2008 ACM SIGAPP - Symposium on Applied Computing, 2008, Fortaleza. 2008 ACM SIGAPP - Symposium on Applied Computing. , 2008.
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Concept Actual Model New Model
Focus Disease/illness Pacient
Strategy Disease Control in accordance with existing standards (epidemiologic studies)
Control of the health considering the person biological context and psychosocial (individual/personalized analytics)
Approach Use of medications and guidelines "standardized"
Interactivity, confidence, awareness, credibility and personalized guidance
Collection of information and orientation
Information and data scattered throughout the organization or between organizations
Get the information only in the health attendence
Integrated all the informations – personalized healthcare information
New ways to communicate with each other in any time
Relationship distrust and authoritarianism Partnership, collaborative
Indicators Results of tests and clinical assessments sporadic
Results of tests and clinical assessments frequent, satisfaction and adherence
Adapted from: ITO, M., MARTINI, J. S. C., IOCHIDA, L. C. CPRM: A Chronic Patient's Management Model Based on the Concepts of Customer Relationship In: 2008 ACM SIGAPP - Symposium on Applied Computing, 2008, Fortaleza. 2008 ACM SIGAPP - Symposium on Applied Computing. , 2008.
CPRM Model – Comparison between the new and the old
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Use Case 1: Define Care team
Care Coordinator(CC)
Choose the patient that will be in the program – elegibility analise
Define the care team
Patient(P)
CC
P1
F1 M1
D1
(TM1)
Care team(TM)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Care Coordinator(CC)
care monitors
Care team(TM) Patient
(P)
Care Coordinator(CC)
coordinate
CC
P1
F1 M1
D1
(TM1)
Use Case 2: Patient Monitoring and Care
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Use Case 3: Collaborative Network of Patient Care
CC
P1
F1 M1
D1
(TM1)
P2
D2 M2
F2
(TM2)
P3
(TM3)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Use Case 4: Collaborative Network of Care Coordination
CC
F1 M1
D1
(TM1)
D2 M2
F2
(TM2)
(TM3)
Institution 1
Instittuion 2
DF3
DF2
DF1
COd
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Adapted from: ITO, M., MARTINI, J. S. C., IOCHIDA, L. C. CPRM: A Chronic Patient's Management Model Based on the Concepts of Customer Relationship In: 2008 ACM SIGAPP - Symposium on Applied Computing, 2008, Fortaleza. 2008 ACM SIGAPP - Symposium on Applied Computing. , 2008.
Patient + caregivers
phone assistant
Patient Care team
Colaborative Network
Analytic Component
Collaborativecomponent
Care CoordinatorOperationalComponent
Health System:-
Government- Hospitals- Assurance- Health
Institutions- others...
Chronic Patient’s Relationship Central Service (CPRC)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Operational
Coordination Patient Care System
Adapted from: ITO, M., MARTINI, J. S. C., IOCHIDA, L. C. CPRM: A Chronic Patient's Management Model Based on the Concepts of Customer Relationship In: 2008 ACM SIGAPP - Symposium on Applied Computing, 2008, Fortaleza. 2008 ACM SIGAPP - Symposium on Applied Computing. , 2008.
Text Conversion System
AppsSocialNet
Virtual environment
Directinteraction
sensors ????
CPRM extended Model - Architecture
Genoma Map
Phone, Urgency and Emergency Alerts, Whatsapp...
Patient Care Collaborative System
Posts
Patient Care Management
Patient Information
Care teamManagement
HospitalInformationsSystems
Clinic’sSystems
Health Government’s Systems
HealthInstitutionsSystems
Eletronic HealthRecord(EHR)
Personal HealthRecord(PHR)
Patient EletronicRecord(PER)
SpecializedMonitoring Systems
EducationalSystems
PrimaryMonitoringSystems
Health Promotion Systems
Analytical
Collaborative
Addressing Patient Adherence Issues by Engaging Enabling Technologies
1st Prototype – Patient Page
Addressing Patient Adherence Issues by Engaging Enabling Technologies
1st Prototype – Care Coordinator PageCare Coordinator Communities
Addressing Patient Adherence Issues by Engaging Enabling Technologies
1st Prototype – Care Coordinator Page
Addressing Patient Adherence Issues by Engaging Enabling Technologies
1st Prototype – Medical Page
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Preliminary Results – Medical PageDoctor Applications
Addressing Patient Adherence Issues by Engaging Enabling Technologies
1st Prototype – Medical Page
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Expected Results
• Improve the patient care coordination • Improve the data visualizations about the patient
useUsing that information to track key clinical conditions
Electronically capturing health information in a standardized format
Care team
Communicating that information for care coordination process
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Expected Results
• Know more about patient pathway and dynamic demand on the service structure
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Expected Results
• Initiating the reporting of clinical quality measures and public health information
Care team Infra structure
Initiating the reporting of clinical quality measures and public health information
Using information to engage patients and their families in their care
Electronically capturing health information in a standardized format
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Thank You
MerciGrazie
Gracias
Obrigado Danke
Japanese
English
French
Russian
German
Italian
Spanish
Brazilian PortugueseArabic
Traditional Chinese
Simplified Chinese
HindiTamil
ThaiKorean
Hebrew
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Agenda• 14:30-14:45 Opening Remark
– Dr. Marion Ball: Intro of the workshop – Dr. Pei-Yun Sabrina Hsueh: from big data to small data for including patients in
evidence-based conversation • 14:45-15:45 Presentations
– Dr. Vimla Patel: Understanding people for technology support– Dr. Fernando Martin Sanchez: Enabling technology and data standards for
patient-generated data – Dr. Henry Chang: Adherence management proof-of-concept using technology – Dr. Victoria Giussi: Personal Health Record at HIBA– Dr. Marcia Ito: Proposed chronic adherence management model
• 15:45-16:00 Workshop discussion/audience Q&A– Dr. Marion Ball as moderator
MEDINFO 2015 Workshop 14 Room 8Addressing Patient Adherence Issues by Engaging Enabling Technologies
Vimla L. Patel, PhD DSc
(New York Academy of Medicine, USA)
Pei-Yun Sabrina Hsueh, PhD (Organizer)
Review of gap analysis from big data to “small” patient-generated data
(IBM T.J. Watson Research, USA)
Fernando Martin Sanchez, PhD
(University of Melbourne, Australia.) Marion Ball, Ed.D (Moderator)
(Johns Hopkins University)
Henry Chang, PhD
(IBM T.J. Watson Research Center, USA)
Victoria Giussi, MD
(Hospital Italiano de Bueno Aires, Argentina)
Marcia Ito, MD PhD
(IBM Brazil Research Lab/University of Federal Sao Paulo)
Addressing Patient Adherence Issues by Engaging Enabling Technologies
More questions to think & Suggestions on next step? • Do provider beliefs and support of these technologies and approaches affect patient
usage?• Will patient interactive reported data improve provider and patient communications,
reduce risks and increase early interventions? • Can adherence to care plans for patients with chronic health conditions be increased
through technology-mediated techniques? • Can analytics based on patient characteristics and adherence behavior be used to identify
patients at risk for adverse health events, as well as identify “model” adherers who are more effective than the average patient at remaining healthy?
• Can dynamically configured software improve health outcomes for the patient and help control costs?
• How will real time patient reported data shift communications, culture, care processes and the patient – provider partnership?
• What are the minimal description of patient-generated data sources to make the insights relevant in the patient-physician conversation? Any difference in terms of specialty?
• What are the good frameworks of patient engagement to be used for this purpose?• Are there information governance initiatives we can start inserting ourselves into?
A follow-up workshop/panel with a more focused area wherein filling in the gap has been perceived as priority MEDINFO 2015
https://goo.gl/Aj88Zs
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Thank You
MerciGrazie
Gracias
Obrigado Danke
Japanese
English
French
Russian
German
Italian
Spanish
Brazilian PortugueseArabic
Traditional Chinese
Simplified Chinese
HindiTamil
ThaiKorean
Hebrew
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Addressing Patient Adherence Issues by Engaging Enabling Technologies
Summary on Workshop Theme (1)
• (1) Implications and lessons learned from the case studies -- especially the gaps you perceived as barriers of entry
• (2) Requirements for successful redesign of healthcare systems to accommodate patient-generated information (with a sub-goal of identifying the areas where such information can make most impacts).
• (3) Identify action items and initiate proposals for enabling evidence-based conversation with patients/physicians/providers in the loop
Addressing Patient Adherence Issues by Engaging Enabling Technologies
More questions to think & Suggestions on next step? • Do provider beliefs and support of these technologies and approaches affect patient
usage?• Will patient interactive reported data improve provider and patient communications,
reduce risks and increase early interventions? • Can adherence to care plans for patients with chronic health conditions be increased
through technology-mediated techniques? • Can analytics based on patient characteristics and adherence behavior be used to identify
patients at risk for adverse health events, as well as identify “model” adherers who are more effective than the average patient at remaining healthy?
• Can dynamically configured software improve health outcomes for the patient and help control costs?
• How will real time patient reported data shift communications, culture, care processes and the patient – provider partnership?
• What are the minimal description of patient-generated data sources to make the insights relevant in the patient-physician conversation? Any difference in terms of specialty?
• What are the good frameworks of patient engagement to be used for this purpose?• Are there information governance initiatives we can start inserting ourselves into?
A follow-up workshop/panel/tutorial MEDINFO 2015
https://goo.gl/Aj88Zs