IU CLEAR project - Health Information Map

HIMAP Health Information Map IU CLEAR Project Kristin Eilenberg, Project Leader 1@keilenberg #HIMAP #healthapps

School of Law & Ethics School of School of Informatics Medicine 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. 2@keilenberg #HIMAP #healthapps

What is Health 2.0? [video] 3@keilenberg #HIMAP #healthapps Ref: YouTube video - Health 2.0 response to The Machine is Us/ing Us

4@keilenberg #HIMAP #healthapps Ref: Geographies of the World’s Knowledge, Convoco 2011

5@keilenberg #HIMAP #healthapps

YouTube downloads 48 hours of video every 1 minute and more than 3 billion views/day 8@keilenberg #HIMAP #healthapps

8 in 10 internet users look online for health information Ref: Pew Research Center’s Internet & American Life Project and the 9@keilenberg #HIMAP #healthapps California HealthCare Foundation, Feb 2011

Who is driving the health discussions? 10@keilenberg #HIMAP #healthapps Ref: NMIncite, 09/2011

Project Overview 13@keilenberg #HIMAP #healthapps

HIMAP Health 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 14@keilenberg #HIMAP #healthapps

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 15@keilenberg #HIMAP #healthapps

Assumptions 16@keilenberg #HIMAP #healthapps

Patient Stages of Disease Symptom Recognition Diagnosis Treatment Initiated Treatment Ongoing Survival/Remission Maintenance Re-occurrence 17@keilenberg #HIMAP #healthapps

Information Seeking, Use, and Creation Behaviors Purchase Seek Create Find content/Comment/Rate Share/Connect Use/Apply 18@keilenberg #HIMAP #healthapps

E-Rx/Pharmacy/PBM Prior Analytics Co Insurance Alerts Authorization Status Pharma De-identified Data Sets Research Claim De-identified Adjucated Claim information Data Sets Health Claim Drinking Type Contact info Medications Allergies behaviors Prescriber ID Insurance Procedures Immunizations Smoking history Employment Diagnoses Hospitalizations Other health Analytics Co Claims history historyClearinghouse De-identified & Provider Biometric data Laboratory Genetic Data Sets seen/referred results Information Insurance Co Hospital Electronic Health Record Analytics Co De-identified Data Sets 19@keilenberg #HIMAP #healthapps

Phone ID User, Password Health Geo- Preferences Age, Gender habits location and Interests Drinking behaviors User, Activities Contact Info Lab results Password Preferences Religious and beliefs Interests Networks Social IP Address Allergies Mobile Age, Gender Phone App Network Political Family Employment Activities views Medications Contact Info Networks Memberships Drinking Affiliations behaviors Biometric Procedures data Political views Religious beliefs Diagnoses User, Password User, Password Genetic info Age, Gender Genetic info Age, Gender Employment Lab results Contact Info Lab results Contact Info Preferences and Drinking Interests behaviors Hospitalization IP Address s Personal Hospitalizations IP Address Activities Online Religious beliefs Health Insurance Immunizations Health Insurance coverage Immunizations Network coverage Records Networks Political views Provider Allergies Provider seen/referred Allergies seen/referred Memberships Family Affiliations Medications Biometric data Medications Biometric data Procedures Diagnoses Procedures Diagnoses 20@keilenberg #HIMAP #healthapps

Basic FrameworkExample User, Genetic Password Age, info Gender Contact Lab results Info Hospitaliza IP Address tions Personal Immunizati Health Insurance ons coverage Records Provider Allergies seen/refer red Medication Biometric s data Procedures DiagnosesInternet User, Password User, Genetic info Age, Gender Preferences Password Phone ID and Age, Gender Interests Lab results Employment Contact Info Health habits Geo-location Preferences Drinking and Drinking Activities Contact Info behaviors Interests behaviors User, Hospitalizati Lab results IP Address Password ons Online Religious Preference s and Mobile Religious beliefs Networks Social IP Address Activities Health beliefs Interests Network Immunizatio Insurance Allergies Phone Age, Gender Family Employment ns Network Political coverage App Networks views Political Provider Activities views Allergies seen/referre Medications Contact Info Membership d Membership Drinking Family s Affiliations behaviors s Affiliations Networks Biometric Biometric Political Religious Medications Procedures data data views beliefs Procedures Diagnoses Diagnoses 21 @keilenberg #HIMAP #healthapps

ProliferationExample User, Genetic Password Age, info Gender Contact Lab results Info Hospitaliza IP Address tions Personal Immunizati Health Insurance ons coverage Records Health habits Phone ID Geo-location User, Password Provider Genetic info Allergies Age, Gender seen/refer Drinking red behaviors Phone ID User, User, User, Employment Medication Lab results Preferences Password Lab results Contact Info Biometric Password Health habits Geo-location and Age, Gender Preferences Password Preferences s data Preference Drinking User, Religious and Age, Gender Interests Interests and Interests behaviors Procedures Diagnoses Genetic info Password s and Age, Gender Interests Mobile beliefs Phone ID Drinking behaviors User, Hospitalizati Lab results Activities Contact Info Activities onsContact Info Online IP Address Lab results Employment Allergies Contact Info Phone Health habits Age, Gender Geo-location Preference Password Religious Activities Religious beliefs Preferences and Drinking App Drinking s and behaviorsInterests Mobile beliefs Social Health Interests behaviors Lab results Political User, PasswordNetworks Networks IP Address Social Immunizatio IP Address Insurance Hospitalizati Activities IP Address Preference Allergies views Phone Age, Gen Network ns Network coverage ons Online Medications s and Contact Info Mobile Religious beliefs User, Network Networks Genetic info User, PasswordPolitical views Gender Age, Activities Religious beliefs Networks Interests App Family Preferences Family Interests Password and Employment Age, Gender Allergies Employment Provider seen/referre Immunizatio Health User, Procedures Allergies Health habits Insurance Phone ID Biometric Phone data Geo-location Medications Activities Age, Gender Political views Contact Info Employment d ns Activities Contact Info Lab results Family Membership PreferencesAffiliations and s Drinking Contact Info Network Genetic info Password Age, Gender Political coverage Diagnoses Drinking behaviors App Health habits Phone ID PoliticalNetworks Geo-location Membership Drinking Biometric behaviors Networks Activities User, s Affiliations Membership behaviors Drinking Medications Interests data views Lab results views Biometric Employment Provider Medications Procedures Password Contact Info Drinking s Affiliations behaviors Lab results Contact Info data Political Religious Hospitalizati AllergiesAddressPreferences Preference seen/referre behaviors Procedures Diagnoses IP Drinking Religious Diagnoses User, views beliefs Networks Social Political views Religious beliefs IP Address ons Activities Online Religious beliefs and InterestsFamily Membership behaviors s Affiliations d s and Interests Mobile Lab results beliefs Networks Preference Biometric Religious Password Procedures Network Immunizatio Health Hospitalizati Medications ons Insurance Online Biometric Allergies data IP Address Phone s anddata Age, Gender Diagnoses Interests Mobile beliefs Religious Family Employment ns Network Political coverage Activities Procedures Health Diagnoses beliefs App Allergies Political Phone Age, Ge Networks Activities Allergies Immunizatio views ns Provider seen/referre Network Insurance Medicationscoverage views Contact Info App Political Membership Drinking d Activities Membership Political views s Affiliations behaviors Family Networks Networks Medications Contact Info s Affiliations views Political Religious Biometric Allergies Provider Procedures seen/referre Biometric data 22@keilenberg #HIMAP #healthapps views beliefs Medications Procedures Diagnoses data Family Membership s Affiliations d Diagnoses Procedures Networks Biometric data

E-Rx/Pharmacy/PBM Prior Analytics Co Insurance Alerts Authorization Status Pharma De-identified Data Sets Research Claim De-identified Adjucated Claim information Data Sets Health Claim Drinking Type Contact info Medications Allergies behaviors Prescriber ID Insurance Procedures Immunizations Smoking history Employment Diagnoses Hospitalizations Other health Analytics Co Claims history historyClearinghouse De-identified & Provider Biometric data Laboratory Genetic Data Sets seen/referred results Information Insurance Co Hospital Electronic Health Record Analytics Co De-identified Data Sets 23@keilenberg #HIMAP #healthapps

ProliferationExample User, Genetic Password Age, info Gender Contact Lab results Info Hospitaliza IP Address tions Personal Immunizati Health Insurance ons coverage Records Health habits Phone ID Geo-location User, Password Provider Genetic info Allergies Age, Gender seen/refer Drinking red behaviors Phone ID User, User, User, Employment Medication Lab results Preferences Password Lab results Contact Info Biometric Password Health habits Geo-location and Age, Gender Preferences Password Preferences s data Preference Drinking User, Religious and Age, Gender Interests Interests and Interests behaviors Procedures Diagnoses Genetic info Password s and Age, Gender Interests Mobile beliefs Phone ID Drinking behaviors User, Hospitalizati Lab results Activities Contact Info Activities onsContact Info Online IP Address Lab results Employment Allergies Contact Info Phone Health habits Age, Gender Geo-location Preference Password Religious Activities Religious beliefs Preferences and Drinking App Drinking s and behaviorsInterests Mobile beliefs Social Health Interests behaviors Lab results Political User, PasswordNetworks Networks IP Address Social Immunizatio IP Address Insurance Hospitalizati Activities IP Address Preference Allergies views Phone Age, Gen Network ns Network coverage ons Online Medications s and Contact Info Mobile Religious beliefs User, Network Networks Genetic info User, PasswordPolitical views Gender Age, Activities Religious beliefs Networks Interests App Family Preferences Family Interests Password and Employment Age, Gender Allergies Employment Provider seen/referre Immunizatio Health User, Procedures Allergies Health habits Insurance Phone ID Biometric Phone data Geo-location Medications Activities Age, Gender Political views Contact Info Employment d ns Activities Contact Info Lab results Family Membership PreferencesAffiliations and s Drinking Contact Info Network Genetic info Password Age, Gender Political coverage Diagnoses Drinking behaviors App Health habits Phone ID PoliticalNetworks Geo-location Membership Drinking Biometric behaviors Networks Activities User, s Affiliations Membership behaviors Drinking Medications Interests data views Lab results views Biometric Employment Provider Medications Procedures Password Contact Info Drinking s Affiliations behaviors Lab results Contact Info data Political Religious Hospitalizati AllergiesAddressPreferences Preference seen/referre behaviors Procedures Diagnoses IP Drinking Religious Diagnoses User, views beliefs Networks Social Political views Religious beliefs IP Address ons Activities Online Religious beliefs and InterestsFamily Membership behaviors s Affiliations d s and Interests Mobile Lab results beliefs Networks Preference Biometric Religious Password Procedures Network Immunizatio Health Hospitalizati Medications ons Insurance Online Biometric Allergies data IP Address Phone s anddata Age, Gender Diagnoses Interests Mobile beliefs Religious Family Employment ns Network Political coverage Activities Procedures Health Diagnoses beliefs App Allergies Political Phone Age, Ge Networks Activities Allergies Immunizatio views ns Provider seen/referre Network Insurance Medicationscoverage views Contact Info App Political Membership Drinking d Activities Membership Political views s Affiliations behaviors Family Networks Networks Medications Contact Info s Affiliations views Political Religious Biometric Allergies Provider Procedures seen/referre Biometric data 24@keilenberg #HIMAP #healthapps views beliefs Medications Procedures Diagnoses data Family Membership s Affiliations d Diagnoses Procedures Networks Biometric data

Health Information FlowExample User, Genetic Password Age, info Gender Contact Lab results Info Hospitaliza IP Address tions Personal Immunizati Health Insurance ons coverage Records Health habits Phone ID Geo-location Provider Allergies seen/refer Drinking red behaviors Phone ID User, User, User, Lab results Preferences Password Medication Biometric Password Health habits Geo-location and Age, Gender Preferences Password s data Preference User, Religious and Age, Gender Interests Interests Procedures Diagnoses Genetic info Password s and Age, Gender Interests Mobile beliefs Phone ID Drinking behaviors User, Lab results Activities Contact Info Activities Contact Info Lab results Employment Allergies Contact Info Phone Health habits Age, Gender Geo-location Preference Password Religious Preferences and Interests Drinking behaviors App Lab results Drinking s and behaviorsInterests Mobile User, beliefsNetworks Social Networks IP Address Social IP Address Hospitalizati Medications Activities IP Address Political Preference Allergies views Contact Info Phone Password Religious Age, Gen Network User, Network User, Password ons Activities Online Religious beliefs s and Interests Mobile beliefs App Genetic info Age, Gender Networks Family Preferences Family Interests Password and Employment Age, Gender Employment Immunizatio Health User, Procedures Allergies Health habits Insurance Phone ID Biometric Phone data Geo-location Medications Activities Age, Gender Political views Contact Info Employment Activities Contact Info Lab results Preferences and Drinking ns Contact Info Network Genetic info Password Age, Gender Political coverage Diagnoses Drinking behaviors App Health habits Phone ID PoliticalNetworks Geo-location Membership Drinking behaviors Networks Activities User, Membership Drinking Interests views Lab results views Biometric s Affiliations behaviors Employment Provider Medications Procedures Password Contact Info s Affiliations behaviors Lab results Contact Info Drinking data Political Religious Hospitalizati AllergiesAddressPreferences Preference seen/referre behaviors IP Drinking Religious Diagnoses User, views beliefs Networks Social Political views Religious beliefs IP Address ons Activities Online Religious beliefs and InterestsFamily Membership behaviors s Affiliations d s and Interests Mobile Lab results beliefs Networks Preference Biometric Religious Password Procedures Network Immunizatio Health Hospitalizati Medications ons Insurance Online Biometric Allergies data IP Address Phone s anddata Age, Gender Diagnoses Interests Mobile beliefs Religious Family Employment ns Network Political coverage Activities Procedures Health Diagnoses beliefs App Allergies Political Phone Age, Ge Networks Activities Allergies Immunizatio views ns Provider seen/referre Network Insurance Medicationscoverage views Contact Info App Political Membership Drinking d Activities Membership Political views s Affiliations behaviors Family Networks Networks Medications Contact Info s Affiliations views Political Religious Biometric Allergies Provider Procedures seen/referre Biometric data 25@keilenberg #HIMAP #healthapps views beliefs Medications Procedures Diagnoses data Family Membership s Affiliations d Diagnoses Procedures Networks Biometric data

What data and where 26@keilenberg #HIMAP #healthapps

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. 27@keilenberg #HIMAP #healthapps

@keilenberg #HIMAP #healthapps

Other views of the data 33@keilenberg #HIMAP #healthapps

70 65 60 Private Clinic 1 WebMD Gmail 55 Insurance Company 50 Facebook PatientsLikeMe 45 WebMD Hospital 2 Health Manager 40 YouTube FaceBook - 35 Susan G. KomenYND Score 30 25 20 CVS 15 Google 10 Cancer.net 5 00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 -5 Sensitivity Score 34@keilenberg #HIMAP #healthapps

Project Next Steps 35@keilenberg #HIMAP #healthapps

What They Know, Wall Street Journal, December 30, 2010 36@keilenberg #HIMAP #healthapps

Example Data Flow For Discussion Purposes Only 37@keilenberg #HIMAP #healthapps

Proposed Project Overview 38@keilenberg #HIMAP #healthapps

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. 39@keilenberg #HIMAP #healthapps

Contact Information: Kristin Eilenberg IU CLEAR Project Leader, Health Information Map Founder and CEO, Lodestone Logic kristin@lodestonelogic.com @keilenberg this presentation is available at: http://db.tt/EMJBjCwi 40@keilenberg #HIMAP #healthapps

Questions? 41@keilenberg #HIMAP #healthapps

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IU CLEAR project - Health Information Map

by lodestonelogic on Nov 21, 2011

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IU CLEAR project - Health Information Map — Presentation Transcript