Database searches and spreadsheets are not analytics
Updated: 5 days ago
If you rely on spreadsheets, SQL, or your data team to generate pharmacy plan reports, you are wasting time and overhead. With over 50 fields and hundreds of thousands of lines in a standard pharmacy claims file, traditional pharmacy reporting is tedious and slow. The output may provide a summary view of different facets of the Rx plan, but the time required to manually cull this complex data often leaves little time to identify actionable insights for the plan sponsor.
In contrast, true data analytics aggregates and displays pharmacy claims so that the client can make highly informed plan decisions. Data analytics dissects plan utilization, pricing details, and trends into nuggets of actionable information without time-consuming manual calculations. Traditional reporting provides a claims summarily. Data analytics provides suggestions and highlights opportunities to affect change.
“Without arduous spreadsheets and SQL queries, data analytics provides a consolidated, consistent, and frequent method for brokers and plan sponsors to understand exactly how their pharmacy dollars are being spent.” Kenneth Wener, COO Prescription Care Management.
By aggregating plan information in one place, data analytics provides a more efficient way to manage claims and eligibility data from multiple vendors.
Wener explains, “For brokers, a robust analytics tool can automatically import claims files from multiple PBMs and insurers into one place so you can see a comprehensive view of pharmacy plan spend.”
Data analytics is a single process that replaces endless database searches and complex spreadsheets. With all of your pharmacy plan details in one place, it is much easier to sort, filter, and organize metrics. Consolidated data also allows true visibility of plan trends from multiple angles (e.g. pharmacy, participant, physician, claim, etc.) so you can contain costs more effectively.
Consolidated claims and eligibility data provides unparalleled reporting with action items built in. Instead of compiling reports by cutting and pasting charts, graphs, and metrics from multiple formats, data analytics inherently allows the creation of standard, easy-to-understand reports.
In turn, consistent reporting allows for increased customization. Instead of spending time reformatting and branding, you can present clear, concise data and easily pinpoint issues. Consistent reporting dramatically reduces the amount of time spent altering templates to fit a specific client’s needs, while speeding up the sales, renewal, and repricing processes so you can focus more time on providing actionable solutions.
Requesting database searches to update spreadsheets is time consuming and limits the number of client reports you can provide.
With data analytics, the ability to derive value from your data is almost instantaneous; as consistent and customizable reports are just a click away. Reports can be generated as frequently as needed without contacting the data team or allocating time to manually organize data. Additionally, data analytics provides actionable insights by quickly identifying trends or outliers such as new high cost drugs or increased plan vs. participant spend. Instead of remaining static in a warehouse, aggregated plan data can be manipulated to troubleshoot immediate pharmacy issues and provide a much deeper level of granularity than is available in a spreadsheet.
“In an age of rapid technological growth, brokers, third-party administrators, and plan sponsors are lagging behind. Antiquated processes and cumbersome tools don’t allow brokers and plan sponsors to quickly meet cost containment needs,” Wener explains. “Many employers can’t wait an entire year to review plan costs. Waiting is just too costly.”
SQL and spreadsheets are not today’s analytics. It’s time to re-evaluate how you utilize pharmacy data. Get more consolidated information, consistent reporting, and frequent troubleshooting by employing an intelligent pharmacy analytics platform.
Explore PCM’s analytics tool here.