Healthcare organizations face mounting pressure from all sides to operate more efficiently in terms of cost and time. Balancing patient care with budgetary demands is an ongoing challenge. As Newsweek reports, approximately one-fourth of all healthcare spending is wasted in America — which amounts to between $760 billion and $935 billion annually. This waste can take many forms, including “administrative complexity,” “overtreatment” and “failure of care delivery.”
So, it’s no wonder healthcare systems are doing everything they can to reduce waste and increase efficiency while keeping an eye on optimizing patient outcomes. Deploying and adopting effective healthcare analytics technology is central to achieving these goals. As such, here are four key healthcare analytics best practices by which to abide.
Self-Service Analytics for Every Kind of User
User experience can ultimately make or break healthcare analytics adoption rates — that is, how much workers actually embrace the software available to them and incorporate their findings into routine decisions.
Accessibility, ease of use and level of customization are huge factors here, as many of the users of healthcare analytics will be clinicians and administrators without extensive data science backgrounds. As well as choosing the right tools to connect users to data insights, it’s also important to ensure they are fluent in utilizing the tools and interpreting the results confidently.
Evangelize Data from the Top Down
Another key component of raising analytics adoption rates within healthcare systems is building a culture that supports and encourages its usage. How leaders communicate about data is a leading factor here. As one expert notes in Becker’s Review, healthcare analytics initiatives have greater chances of success when executives are “visibly involved and support the project” because it encourages everyone else to do so as well.
Furthermore, making data a central talking point and clearly communicating data objectives helps get everyone on the same page. Offering continued learning and practice opportunities can also help employees make the most of the analytics tools available to them.
Identify Opportunities to Improve Internal Processes
A good place to start is by focusing on processes — both clinical and administrative — ripe for streamlining. Why? Because, as Healthcare IT News advises, these efforts generally have an immediate impact on operations and the bottom line in the sense that they “free up time and cost.” The ability to fine-tune everyday processes can have an outsized impact on the operating budget as well as the experiences of patients and staffers alike.
Using data analytics to immediately identify inefficiencies, bottlenecks and gaps is a great way to get a solid return on investment in analytics tools right away — and see speedy results.
Never Lose Sight of Improving Patient Outcomes
As important as improving internal processes can be — and as much of an effect they can ultimately have on the patient experience — the most impactful analytics use cases are the ones capable of directly improving patient outcomes.
Important key performance indicators (KPIs) to focus on include:
- Hospital readmission rates by condition
- Rates of death by condition
- Volume of antibiotics prescribed
- Follow-up appointment lengths
- Occurrences of diagnostic errors
- Hospital-acquired infection rates
- Amount of time spent per appointment
- Medical tests/treatment/appointment attendance rates
The aforementioned KPIs represent just a small sample of the measurable areas of patient care that can benefit from providers gaining the ability to analyze data to detect patterns, trends and outliers. Analytics tools can help healthcare orgs identify problem areas, set goals, measure progress and uncover new solutions.
Following healthcare analytics best practices will help systems get the most out of their analytics technology — ultimately boosting patient outcomes and streamlining operations.
