This document is based on the MIT Sloan Management Review case study on data and analytics at Intermountain Healthcare titled “When Health Care Gets a Healthy Dose of Data”. The document should be viewed as a summary of the attributes that played a role in advancing data and analytics at Intermountain.

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Introduction
This document is based on the MIT Sloan Management Review case study on data and analytics at
Intermountain Healthcare titled “When Health Care Gets a Healthy Dose of Data”. The document
should be viewed as a summary of the attributes that played a role in advancing data and analytics
at Intermountain.
The case study is available at:
http://sloanreview.mit.edu/case-study/when-healthcare-gets-a-healthy-dose-of-data/
Culture
Intermountains’ embrace of data can be traced back to its pioneering days in healthcare analytics
with one of the first EHR (Electronic Health Records) systems in the United States. At the time, 1968,
the system provided doctors with diagnostic advice and treatment guidance and was also effective
in helping doctors identify the causes of adverse drug reactions.
In 1985, Intermountain extended the system to all of its hospitals. This provided administrators with
an opportunity to put data-driven decision making at the forefront of the organization - laying the
foundation for later data driven initiatives.
Data integrity
For organisations looking to advance their analytical maturity, data integrity efforts are critical if
analytics is to eventually pervade the organisation – providing enterprise wide insight and input to
strategic decision making. In an effort to build trust in its data initiatives, Intermountain spent years
creating a common language for data across departments and hospitals. As cited in the case study:
“… once you’ve got bad data, it takes months to recover that level of trust. The single most important
thing is the integrity of the data.” Intermountains’ data integrity efforts included regular meetings
with practicing clinicians to hammer out definitions that ultimately enabled, for the first time, direct
comparison of hospitals and departments on a wide range of metrics.
Stakeholder engagement
In fostering a data driven culture and to support data integrity, Intermountain encouraged
stakeholder engagement by allowing physicians to question the integrity of the data. This resulted in
physicians being more comfortable with the data while still being able to challenge it if necessary.
This blending of the strengths of technology with the strengths of people is key for buy-in and
support for future initiatives.
Team driven behavioural change
Intermountain created a collaborative, team-driven process to encourage behavioural change by
applying gentle peer pressure, extolling doctors or teams that have excellent results and
encouraging others to take the same steps.
Measurement
As organisations advance in analytical maturity, data is embedded in organisational processes as a
basis for measurement and decision making. Intermountain has done this with their care initiatives

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in their cardiovascular clinical care unit by first running baseline data and comparing this to post
implementation data as the basis for identifying improvement.
Analytical competence
Intermountain has built data teams that consist of three people: a data manager who makes sure
data is being collected correctly, a data analyst to flag important trends, and a data architect who
pulls together data from various sources inside and outside Intermountain. Such teams help to
embed analytics within the organisation by providing stakeholders with the analytical support they
need.
Driving policy
An attribute of organisational maturity in analytics is the transition from a tactical to strategic use of
data. An example of such a transition can be seen at the Intermountain cardiovascular practice,
where it has expanded its use of analytics to support patient care not only through decision making
but also at the policy level – for example, deciding that it should have only four of its hospitals
perform cardiovascular operations.
Supply chain
Intermountains’ supply chain focus is a good example of analytics permeating the organisation.
Where initially analytics was seeded in its core business with the EHR system, Intermountain has
sought to address procurement issues, specifically the issue of doctors’ being unaware of their
supply costs or how to reduce them, by increasing price transparency and information sharing.
In its first year, for example, the supply chain initiative cut $25 million from operating costs in its
Surgical Services Clinical Program alone. Impressively it aims to cut costs by $400 million by 2018.
Such success engrains analytics within the organisation and can serve as the basis for winning over
areas of the organisation more sceptical of the benefits.
In Summary
With its long history of using data, blending people and technology, collaborative culture,
transparent data practices, incremental improvement and embedding analytics in processes across
the organisation, Intermountain has created a solid foundation for leveraging analytics as a strategic
resource. Although not without challenges, such efforts have placed Intermountain in a strong
position to exploit ever rising data driven opportunities – an enviable position.