IU CLEAR project - Health Information Map

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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.

@keilenberg #HIMAP #healthapps3

What is Health 2.0?

[video]

Ref: YouTube video - Health 2.0 response to The Machine is Us/ing Us

@keilenberg #HIMAP #healthapps4

Ref: Geographies of the World’s Knowledge, Convoco 2011

@keilenberg #HIMAP #healthapps5

@keilenberg #HIMAP #healthapps6

@keilenberg #HIMAP #healthapps7

@keilenberg #HIMAP #healthapps8

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)

@keilenberg #HIMAP #healthapps9

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

@keilenberg #HIMAP #healthapps10

Who is driving the health discussions?

Ref: NMIncite, 09/2011

@keilenberg #HIMAP #healthapps11

@keilenberg #HIMAP #healthapps12

@keilenberg #HIMAP #healthapps13

Project Overview

@keilenberg #HIMAP #healthapps14

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

@keilenberg #HIMAP #healthapps15

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

@keilenberg #HIMAP #healthapps16

Assumptions

@keilenberg #HIMAP #healthapps17

Patient Stages of Disease

Re-occurrence

Maintenance

Survival/Remission

Treatment Ongoing

Treatment Initiated

Diagnosis

Symptom Recognition

@keilenberg #HIMAP #healthapps18

Seek

Find

Use/ApplyShare/Connect

Create content/Comm

ent/Rate

Purchase

Information Seeking, Use, and Creation Behaviors

@keilenberg #HIMAP #healthapps19

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 #healthapps20

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

@keilenberg #HIMAP #healthapps26

What data and where

@keilenberg #HIMAP #healthapps27

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.

@keilenberg #HIMAP #healthapps28

@keilenberg #HIMAP #healthapps

@keilenberg #HIMAP #healthapps30

@keilenberg #HIMAP #healthapps31

@keilenberg #HIMAP #healthapps32

@keilenberg #HIMAP #healthapps33

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

Google

YouTube

GmailWebMD

PatientsLikeMe

Facebook

FaceBook -Susan G. Komen

CVS

Cancer.net

WebMD Health ManagerHospital 2

Private Clinic 1

Insurance Company

Sensitivity Score

YND

Sco

re

@keilenberg #HIMAP #healthapps35

Project Next Steps

@keilenberg #HIMAP #healthapps36

What They Know, Wall Street Journal, December 30, 2010

@keilenberg #HIMAP #healthapps37

Example Data Flow For Discussion Purposes Only

@keilenberg #HIMAP #healthapps38

Proposed Project Overview

@keilenberg #HIMAP #healthapps39

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 Logickristin@lodestonelogic.com

@keilenberg

this presentation is available at:http://db.tt/EMJBjCwi

@keilenberg #HIMAP #healthapps41

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