iu clear project - health information map
DESCRIPTION
Patients are generating massive amounts of specific and attributable health information through their use of the internet, social networks, and mobile phone applications. How is this data being generated, consumed, and archived? What are the opportunities to use this data to increase healthcare efficiencies and to improve patient outcomes?Indiana University Center for Law, Ethics, and Applied Research (CLEAR) focus is to enhance the ethical, lawful, and practical use of health information to facilitate treatment and research, improve health outcomes for patient, and facilitate accountability. One of CLEAR’s ongoing projects is the development of a holistic view and map of the digital health information that is generated on a daily basis within computerized healthcare systems, the internet and social media platforms, and through consumer purchases of health related products and services. This map, once completed, will be available in the public domain and will be used to educate patients, caregivers, healthcare providers, and legislators about the volume of digital health data that is produced and consumed by patients that is referenced and archived by private entities. The map will be used to stimulate relevant privacy discussions and encourage appropriate integration of these silos of data to generate patient-centric insights that will improve healthcare efficiencies and patient outcomes.TRANSCRIPT
@keilenberg #HIMAP #healthapps1
HIMAPHealth Information Map
IU CLEAR ProjectKristin Eilenberg, Project Leader
@keilenberg #HIMAP #healthapps2
School of Medicine
School of Informatics
School of Law & Ethics
The Indiana University Center for Law, Ethics, and Applied Research in Health Information’s purpose is: • To enhance the ethical, lawful, and practical use of health information to
facilitate treatment and research, improve health outcomes for patient, and facilitate accountability.
• To work with key constituencies including healthcare providers and payers, patients, ethicists, attorneys, and professional groups, regulators, and others to devise a more rational and more trustworthy approach to using personal data for health research, one that recognizes that more and more relevant data comes from the internet and other digital sources that are largely beyond the scope of the current health privacy laws.
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What is Health 2.0?
[video]
Ref: YouTube video - Health 2.0 response to The Machine is Us/ing Us
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Ref: Geographies of the World’s Knowledge, Convoco 2011
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YouTube downloads 48 hours of video every 1 minute and more
than 3 billion views/day
FaceBook has over 800 million active (users who have returned to the site in the last 30 days)
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8 in 10 internet users look online for health information
Ref: Pew Research Center’s Internet & American Life Project and the California HealthCare Foundation, Feb 2011
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Who is driving the health discussions?
Ref: NMIncite, 09/2011
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Project Overview
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HIMAPHealth Information Map
• Purpose– Develop a Health Information Map that will represent the
holistic and complicated view of all of the health information that is generated on a daily basis within computerized healthcare systems, the internet and social media platforms, and through consumer purchases of health related products and services
– To better understand what health information is created, where it is created, and how it is used
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Health Information Map
• How– Mobilize and partner with experts in the medical profession,
electronic health records, health information data transactions, internet search, social media platforms, patient communities, and mobile/tele-medicine systems
– Develop an activity based model and mapping of the healthcare information/data that is generated on a daily basis related to disease: initial symptoms, diagnosis, treatment, survival/recovery, and re-occurrence
– Document key content creators and users of the data, primary locations of where the data is generated, how the data is shared and merged with other data sources, who owns the data, how the data is stored, and the sensitivity or impact of the data
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Assumptions
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Patient Stages of Disease
Re-occurrence
Maintenance
Survival/Remission
Treatment Ongoing
Treatment Initiated
Diagnosis
Symptom Recognition
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Seek
Find
Use/ApplyShare/Connect
Create content/Comm
ent/Rate
Purchase
Information Seeking, Use, and Creation Behaviors
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Contact info
Insurance
Employment
Provider seen/referred Biometric data
Diagnoses
Procedures
Medications Allergies
Immunizations
Hospitalizations history
Laboratory results
Genetic Information
Other health history
Smoking history
Drinking behaviors
Hospital Electronic Health Record
Health Claim Type
Prescriber ID
Claims Clearinghouse
&Insurance Co
Insurance Alerts
Claim information Adjucated Claim
Prior Authorization
Status
E-Rx/Pharmacy/PBM
De-identified Data Sets
Analytics Co
De-identified Data Sets
Analytics Co
De-identified Data Sets
Analytics Co
De-identified Data Sets
PharmaResearch
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User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referred
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefsPolitical views
Memberships Affiliations
Family
Networks
Activities
Preferences and Interests
Mobile Phone App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and Interests
Personal Health
Records
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referred
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
@keilenberg #HIMAP #healthapps21
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Basic FrameworkExample
Internet
Personal Health
Records
User, Password Age,
Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referr
ed
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
@keilenberg #HIMAP #healthapps22
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Personal Health
Records
User, Password Age,
Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referr
ed
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
ProliferationExample
@keilenberg #HIMAP #healthapps23
Contact info
Insurance
Employment
Provider seen/referred Biometric data
Diagnoses
Procedures
Medications Allergies
Immunizations
Hospitalizations history
Laboratory results
Genetic Information
Other health history
Smoking history
Drinking behaviors
Hospital Electronic Health Record
Health Claim Type
Prescriber ID
Claims Clearinghouse
&Insurance Co
Insurance Alerts
Claim information Adjucated Claim
Prior Authorization
Status
E-Rx/Pharmacy/PBM
De-identified Data Sets
Analytics Co
De-identified Data Sets
Analytics Co
De-identified Data Sets
Analytics Co
De-identified Data Sets
PharmaResearch
@keilenberg #HIMAP #healthapps24
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Personal Health
Records
User, Password Age,
Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referr
ed
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
ProliferationExample
@keilenberg #HIMAP #healthapps25
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
Social Network
User, Password
Age, Gender
Contact Info
IP Address
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships
Affiliations
Family
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
Mobile Phone
App
Phone ID
Geo-location
User, Password
Age, Gender
Contact Info
Biometric data
Diagnoses
Procedures
Medications
Allergies
Lab results
Health habits
Drinking behaviors
Religious beliefs
Political views
Networks
Activities
Preferences and
Interests
User, Password
Age, Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referre
d
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Online Health
Network
Employment
Drinking behaviors
Religious beliefs
Political views
Memberships AffiliationsFamily
Networks
Activities
Preferences and
Interests
Personal Health
Records
User, Password Age,
Gender
Contact Info
IP Address
Insurance coverage
Provider seen/referr
ed
Biometric data
DiagnosesProcedures
Medications
Allergies
Immunizations
Hospitalizations
Lab results
Genetic info
Health Information FlowExample
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What data and where
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Data Elements and Definitions• Data Elements
– 2 = Will have, required or mandatory data point for account creation and use– 1 = May have, end user decides if they are going to provide the data and/or
the data may be found by the Entity doing free-text or semantic mining of the data that the user generates through their use
– 0 = Not collected, not a data point collected
• Data Element Impact Scoring– 0= Low Impact, Even if the data element was revealed/released/known to
others it would not cause any harm to the person whether in the form of discrimination, embarrassment etc.
– 1 = High Impact, If the data attribute were revealed/released/known to others it could cause harm (or very likely cause harm) to the individual whether directly or indirectly.
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Other views of the data
@keilenberg #HIMAP #healthapps3410 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
YouTube
GmailWebMD
PatientsLikeMe
FaceBook -Susan G. Komen
CVS
Cancer.net
WebMD Health ManagerHospital 2
Private Clinic 1
Insurance Company
Sensitivity Score
YND
Sco
re
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Project Next Steps
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What They Know, Wall Street Journal, December 30, 2010
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Example Data Flow For Discussion Purposes Only
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Proposed Project Overview
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To work with key constituencies including healthcare providers and payers, patients, ethicists, attorneys, and professional groups, regulators, and
others to devise a more rational and more trustworthy approach to using personal data for health research, one that recognizes that
more and more relevant data comes from the internet and other digital sources that are largely beyond the scope of the
current health privacy laws.
@keilenberg #HIMAP #healthapps40
Contact Information:
Kristin EilenbergIU CLEAR Project Leader, Health Information Map
Founder and CEO, Lodestone [email protected]
@keilenberg
this presentation is available at:http://db.tt/EMJBjCwi
@keilenberg #HIMAP #healthapps41
Questions?