The United States has the highest overall and per-capital healthcare spending of any developed country, overspending by approximately $600 billion. Big data and the use of business intelligence in healthcare have the potential to change this outcome. It is estimated that healthcare business intelligence could reduce annual healthcare costs by $300 to $450 billion—effectively halving the overspend.
Healthcare BI won't address every excess expenditure in the system, but it can significantly reduce costs while simultaneously improving patient care.
There are many benefits of utilizing embedded business intelligence tools in clinical healthcare, ranging from solo practices to hospital networks.
Here, we'll discuss features to look for in a healthcare BI tool. We'll also address the questions a healthcare BI tool can answer.
When selecting a business intelligence solution for healthcare, organizations must consider all users and other factors.
Is This Specific High-Cost/High-Risk Treatment Worth Pursuing?
The ability to assess the likely effectiveness of different treatments is critical when considering high-cost or high-risk treatments. Recommending specific high-cost/high-risk treatments shouldn't be left to personal medical provider judgment.
Healthcare business intelligence ensures that the decision isn't based solely on subjective judgment by providing evidence on the effectiveness and risks of specific treatments in specific situations.
Should Providers Recommend New Treatments to Patients?
One of the most challenging treatment decisions that providers make is whether to recommend newer treatments. Of course, the decision will always be situationally specific to both the treatment and patient. The aggregate data that business intelligence tools analyze can aid in two ways.
Where Can the Organization Improve Revenues Without Sacrificing Patient Care?
Identifying high-value treatments and overlooked treatments show where an organization can maintain or increase revenues. Pairing that financial data with treatment outcomes ensures that revenues are never pursued at the expense of patient care, but are improved in concert with maintaining and improving patient care.
Where Are Labor Inefficiencies Among Medical Providers?
Accurately determining what cases each level of medical provider can treat makes better use of all providers' time, including doctors, physician assistants, and nurses. This reduces labor inefficiencies and costs.
Reducing labor costs in this way may simultaneously improve patient care, as appointments are scheduled with the appropriate level provider. The savings that an organization sees is often substantial considering how high labor costs are in the field.
The role of big data in healthcare will only increase, and all organizations should be adopting solutions.
To learn more about how healthcare business intelligence can help your organization both now and in the future, contact us. ↓