Creating Data-Driven Healthcare Organizations
As healthcare organizations complete their Meaningful Use investments and EHR implementations, they are confronted with a new problem: What to do with the mountains of data that are being collected on a weekly, daily, and sometimes, hourly basis?
In an environment where quality metrics, patient experience, and value-based care live under a magnifying glass, hospitals, payers and medical groups are looking at how they can stretch their current resources to meet these new strategic goals. Often, utilizing data to solve these challenges becomes a top priority.
The maturity curve for most industries is often the same: Organizations want their data to tell them:
- “Where have I been” or DESCRIPTIVE Analytics
- “What will happen if I make certain decisions?” or PREDICTIVE Analytics
- “What should I do?” or PRESCRIPTIVE Analytics
To illustrate the example, consider Google Maps. If you are at home and want to get to the local movies on time:
A) You type two addresses (home and theater) and Google tells you it will take X number of miles and Y estimated minutes to get to the theater. This is DESCRIPTIVE.
B. Now, if you change the dropdown from “Leave right now”, and say “I want to leave at…” or “I want to arrive at…” then Google uses past history, current traffic, and some fancy algorithm to predict transit time and gives you a PREDICTIVE result for when you should leave.
C. Further imagine that Google could text you when it was time to leave, which route to take, and if you should walk/drive/transit/bike. This is an example of PRESCRIPTIVE analytics — technology is telling you what to do to achieve a certain outcome.
In the analytics industry, there is a concept of the Analytics Maturity Curve which is meant to illustrate how organizations move from DESCRIPTIVE to PREDICTIVE to PRESCRIPTIVE analytics. While this framework is helpful, rarely does it consider the path to get to DESCRIPTIVE analytics. As such, our team at Slalom has augmented the curve and illustrated it below, notice that we’ve added several points along the journey for an organization before they get to DESCRIPTIVE analytics.
We find the following is true in healthcare organizations when it comes to analytics maturity:
Many organizations are ready to gather insights from data and have a strong desire to do so!
Most organizations have some sort of analytics budget to take existing spreadsheets and reports and pull them together to start conveying information more easily.
Some organizations are ready to invest in technology to make their lives easier. Technology enables consistency, automation, and scale unachievable by other means.
Rarely do organizations want to make the investment to start tying their data to insights (or outcomes).
Payer and Provider leaders are asking more about people and governance, how to organize data, how to manage it, how to establish data definitions, and guidance on infrastructure. These are elements that need to be put in place before a client can progress up the (blue) maturity curve.
At Slalom, we are partnering with our clients to establish this analytics foundation and together help organizations move up this curve and move up quickly! By creating data-driven healthcare organizations, we believe patient care, provider experience, efficiencies, and patient volume can be positively impacted.
There are three questions that a healthcare organization should ask before proceeding up the analytics maturity curve:
● Do we have the right people, skillset and governance in place to manage data across our organization?
● How is our data being managed today, and do we require some form of data hygiene? Do we have processes in place support our investment?
● Is our technology infrastructure ready to support the analytics needs of our people today, and tomorrow?
Guiding your organization in tackling these three issues will set up your organization for success as you scale up your analytics capabilities on behalf of your patients, providers, and others within the healthcare ecosystem.
Often when we work with organizations, they look to us purely for technology, but we find that starting all 3 areas in some capacity, at the same time, gives us the ability to drive toward positive, sustainable outcomes for patients, organizations, and our clients. Much like growing a plant takes soil, water, and sunlight — and the absence of one of those three things doesn’t yield a sprout — so too organizations must work to put all three areas in place at the same time. Technology without process yields poor quality. Process without people and technology is slow and unwieldy. People are most impactful when supported by proper technology and process. All three areas of focus must be worked on together for success to allow an organization to become truly data-driven.
In follow-up articles, we will continue the data-driven healthcare organization series and take a detailed look at the three areas of People, Process, and Technology. As the technology landscape changes, new processes need to evolve, and new people need to be aligned to achieve the organization’s goals. Only with persistent attention on all three areas can an organization truly achieve the maturity they desire. We’ll look at how the Cloud accelerates the technological ability for your data. We’ll look at how processes and talent need to change in response to this new, diverse set of capability. And we’ll cover how to best organize the on-going care and feeding of this new capability for your organization. We are truly thrilled to partner with you on this journey. Let’s get started!
Credit to @gordon.strodel from Slalom Boston’s Data and Analytics Practice for his collaboration and ongoing contribution.
Slalom partners with healthcare, biotech and pharmaceutical leaders to strengthen their organizations, improve their systems, and help with some of their most strategic business challenges. Find out more about our people, our company and what we do.
Cabul Mehta is a solution principal in healthcare and life sciences with Slalom. His experience includes operational process improvements, data and analytics implementations, strategic transformations, and population health interventions. His clients include health systems, physician organizations, cancer institutes, academic medical centers and community hospital settings throughout the United States. His research interests span across multiple areas in the industry including shared savings programs and accountable care organizations, personalized medicine, medical technology innovation, data platforms and analytics, and enhancing the overall patient and caregiver experience.
