Transforming Healthcare with Data Lakes and Warehouses
The demand for healthcare organizations to deliver relevant business insights has increased dramatically, as the industry morphs from fee-for-service to value-based payment models, and disease management to population health platforms. It’s a move from a one-size-fits-all intervention approach to utilizing data to create a spectrum within a patient population resulting in the ability to target interventions. Healthcare organizations have access to a vast amount of data that can be leveraged to get the right care to the right patient at the right time, resulting in improved health outcomes for the member, and business outcomes for the organization. A shift in the maturity and complexity of data storage and analytic tools has allowed organizations the flexibility needed to build insightful, impactful, and relevant patient and provider intervention strategies.
Having access to data is the key to profiling populations, resulting in relevant business insights. A data strategy determines the parameters in which data is stored and accessed within the organization, thus impacting the agility and flexibility for data analysis. A data lake is a concept that has potential to bring value to organizations that need access to tie together data points across the organization to understand their full patient profile and have the flexibility to dig in and sample to find where to take action. Data lakes are storage repositories for raw data. Since the data is raw and stored in its natural state, it is able to fulfill the needs of analysis without predetermined scope or limitations as they support and retain all data types and support all users. Even though the data is raw, it’s organized so that it can be accessed for the right type of analysis. While a data warehouse also stores data, it is suited for business reporting such as trending reports on predefined populations. Data in a warehouse are structured and in a fixed configuration. A data warehouse typically stores data from transactional systems, while a data lake would include all data.
A data strategy determines the parameters in which data is stored and accessed within the organization, thus impacting the agility and flexibility for data analysis
As the healthcare industry is transforming, many organizations are adopting a hybrid data strategy to data lakes and warehouses as they complement each other when your audience is mixed. For clinical teams analyzing populations tied to diagnosis, social determinants of health, or wherever the data takes them, a data lake strategy would offer the flexibility needed to identify populations and report outcomes. At the same time, in a highly regulated industry, your reporting path is well known and worn. For business users that have prescribed parameters, the utilization of a data warehouse with a set course allows them to press play with consistency and meet business needs.
The data lake allows users to ask “why?” with the curiosity and unrelenting persistence to develop targeted data driven strategies. The data warehouse has the maturity and direction of a CEO who understands the capacity and scope of his team, and asks targeted and direct questions. As healthcare regulations and trends continue to drive towards value based and population health methodologies, organizations will have the option to adopt the data strategy that meets their business needs.