Health Information Map

Welcome to the IU Health Information Mapping Project (HIMAP)

The goal of this project is to:

• 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, and
• To better understand what health information is created, where it is created, and how it is used.

The methods that were used were:

• 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; and
• 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.

Phase I: Where data comes from

Phase I of HIMAP included the identification of both healthcare practices/settings and online websites that collect healthcare data. Once the entities were identified, data element information was collected through publicly available sources and telephone interviews with individuals that were familiar with the data elements that are collected by the entity.

Summary of Phase I -

• Initial data set included over 160 data elements. To improve the representation of the data that was collected via the visualization, elements were batched and organized by similar types and themes of data types. This effort resulted in the creation of 42 primary data elements.
• The categorization of the data elements was determined by the choice that the end user had in providing the data. For example, if the end user was required to provide the data element, then this is equivalent to ‘Routinely Collected’; if the data element was optional or collected/mined via free text , this this is equivalent to ‘Potentially Collected’; if the data element was not present, then this is equivalent to ‘Not Usually Collected’.

Phase II: Where it goes

Phase II of HIMAP focused on mapping the flow of the data from one entity to the next.

Summary of Phase II -

• Many entities were not concerned about providing which information they collect (Phase I), but were very sensitive about sharing how they moved and shared health data elements (Phase II). In most cases, interviewees for Phase II asked to remain anonymous.
• This phase required several interviews with each entity as there is a general lack of knowledge at both healthcare and online entities regarding what happens to health data beyond the point of data collection.
• Most organizations have not built up data analytics capabilities and are not accessing or using the health data elements that they collect beyond the point of data collection.
• For non-health oriented online entities, health data elements are not tagged or recognized any differently than other data elements.

Phase III: Patient Journey (includes Journey Graph and Journey in 3D)

The intent of Phase III of HIMAP is to build a graphical depiction and comparison of health data creation, dissemination, and movement by the years of 2002 (historical), 2012 (current), and 2022 (prediction based on trends).

Summary of Phase III -

• This part of the project required multiple visualizations.
• • Patient Journey: the individual actions and movement of health data by year
  • Journey Graph: the data from the Patient Journey layered on top of each other so that the differences by year can be easily seen
  • Journey in 3D: the data from the Patient Journey reflecting the connections by entity
• With the adoption and use of social media tools and technology advancements, there has been a significant increase in the possible dissemination of health data between 2002 and 2012. With millions of mobile applications available, the social media entities referenced in this research represent only a fraction of the potential connections and flows for health data.
• There is a true separation between health data generated as part of patient care and the health data generated by patients on their own.
• It is expected that the rate of adoption of smart phones, social media, and data analytics will only increase over the next few years.
• There are several entities that were not included in Phases I or II, but may became key health data intermediaries by 2022.