Managing big data is critical to the health of any organization and its patients, but these initiatives can be a drain on time and resources. One way to increase efficiency, measure progress, and improve performance is through the use of analytics.
By aggregating and analyzing clinical, financial and operational data, analytical reports and dashboards inform decision making and help improve outcomes. At its best, analytics make data more meaningful and provide vital insights about organizational performance.
After utilizing dashboards and running reports to confirm productivity goals were met, interest shifted toward clinical operations. Testing data accuracy became a priority to see what areas could be tracked better, especially Comprehensive Primary Care (CPC) measures.
Once care gaps were spotted, we targeted several areas where analytics could assist in achieving greater clinical intelligence for the entire organization. However, we first had to address a few barriers to ensure our analytics strategy would work for us and not against us.
Initial analytics challenges
Putting analytics at the forefront of our efforts showed how care teams were behaving as individuals, rather than as an organization. For example, there was debate surrounding how relative value units (RVUs) should be assigned and how physicians get credited. Different protocols caused data to get lost in the mix. Incentivizing physicians to follow the same process, rather than the easiest method of payment, was an initial struggle, but transforming RVU assignment methods became an eye-opening experience for the entire staff.
We also found gaps in workflow and referral loops. At times, clinicians would have conversations about a patient, but wouldn’t document correctly. Areas such as substance use, fall risk assessment, and depression screening lacked a continuity of care due to these inconsistencies.
Utilizing analytics for improved efficiency
Making internal changes to properly implement analytics started with Kalispell staff being honest with themselves and conducting self-evaluation as a clinic and as a team of providers. After identifying areas for clinical improvement to close gaps in care, we put new processes in place that were based on proper documentation and transforming clinical workflows.
One great example is how we reduced the number of CPC measures being tracked from 14 to two (blood pressure and A1Cs) and then focused on improving efficiency by aligning three levels of care: Physicians, care coordinators, and nurses.
Past data showed that there were gaps in patients receiving correct, timely referrals. Because of this, we decided to empower care coordinators so referrals would become automatic without the need for doctor involvement.
For example, a diabetic protocol was implemented so that if a patient meets certain measures, they automatically receive a diabetic referral. The documentation behind these efforts, powered by analytical reporting, made it easier to track patients down and get them in for visits as needed. This also helped streamline care coordination and improve staff communication.
After being alarmed by the previous numbers and seeing initial success with a new analytical approach, our staff was inspired to get their hands around other organizational issues by dedicating the right individuals and teams to each initiative. Using data transparency garnered more trust with our physicians and organization as a whole.
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