If your data is an asset, shouldn’t you invest it?
While almost all healthcare providers and payers view their data as an asset, some see putting money into it as another expense that could strain already-tight budgets. But as healthcare providers and payers attempt to manage an ever-increasing volume of data, failure to invest in the people, processes, and technologies to support data management prevents the ability to turn data into value.
Data investments should support your mission, improve margins, and mitigate risk. How do you know when you’re investing enough? Here are 12 signs you may face when it’s time to reinvest in your greatest asset — your data — and advice on where to get started.
1. You lack timely information
Reports are finalized days (or weeks) after the data was needed to inform decision-making.
You’re intentional with your capital investments to make sure your portfolio has the right liquidity and is available when you need it. If you invest and manage your data as an asset, but it’s not accessible when you need it, it’s time to rebalance your portfolio.
As providers take on more risk through value based care, proactively managing patients and financial risk is increasingly critical. As payers continue to experience changing patient and provider behavior, quickly identifying the root cause for trends impacting their medical loss ratio is no longer a nice-to-have.
Investment advice: Assess your data pipelines to identify where data workflows are preventing near real-time information in your reports.
2. Your information is inconsistent
Different reports and dashboards show different figures and KPIs and are unable to be reconciled.
Data must be accessible as well as trustworthy. Perhaps the most common breach of trust, in healthcare especially, is when stakeholders find unexplainable inconsistencies between two different reports. It may be due to an error in the data sources, a misunderstood KPI definition, or even a simple typo in the code generating the report, but in each scenario, the result is the same — the end-user no longer trusts the data.
Investment advice: Build (or enhance) your data catalog to make sure it documents every data source, provides the data lineage to every report, and defines every KPI and report.
3. Your information is inaccurate
Errors were discovered in reports, either due to faulty report logic or inconsistent data entry.
Discrepancies between reports is just one data trust breaker. When you find an ant at the picnic, you know there are more. Likewise, when you find an error in your report, you can assume there are more you haven’t found. Whether the error was in the source data or somewhere in the analysis process, the result is untrustworthy data.
Investment advice: Define data quality rules and exception tests that identify inconsistent, missing, or irregular data in a data quality and observability solution.
4. You’re overly reliant on gut feelings
The scale and complexity of your organization has grown, and you don’t have the data to manage it.
Keeping a pulse on your operations was easier when you had one region, before your staff were remote, or with traditional fee-for-service contracts. As organizations grow and evolve more complex processes, a leader’s ability to rely on their gut feel is diminished. They need to become more reliant on data to truly make data-driven decisions.
Investment advice: Invest in a modern data platform suited to your new size to combine and manage data from all of your data sources and enable your teams to build analytics solutions.
5. You’re doing too much maintenance
Your report developers spend more of their time maintaining (e.g., fixing issues) than developing.
Report developers and data teams may be one of the most stretched support teams in healthcare. It’s an all-too-common story: a healthcare provider or payer wants to move quickly in launching a new, innovative product or solution, and the project is stalled until the data request can be fulfilled. We know firsthand that healthcare data teams are overwhelmed and understand the need to strategically schedule — and we know that unsustainable data architectures are often the culprit.
Investment advice: Assess your current reporting platform(s) and consider consolidating to a single, sustainable platform, which also enables self-service analytics.
6. You’re constantly troubleshooting
When there’s an urgent issue, your team doesn’t have data to quickly diagnose and quantify it.
Healthcare data is complex. With 30% of the world’s data volume generated in healthcare (and much of it transmitted by payer, providers, and third parties such as clearinghouses), there are countless risks in the data workflow for issue to occur. It might look like a claim denied by an AI due to a bug or an incorrectly configured benefit plan. The bottom line: when you notice the issue, you’re counting on your (overstretched) data team to quickly find the weak link and resolve it.
Investment advice: Establish an analytics center of excellence and expand your data team by democratizing analytics-enabled business users in each of your business units.
7. You’re excessively reliant on Excel
You have “standard reports” but most of the time they’re exported to be “sliced and diced” in Excel.
Microsoft Excel remains the most widely used analytics platform in the world. The reason: it’s available to every user and there are few skill set barriers to entry. Despite its popularity and usability, there are three main consequences: 1) it can only analyze about 1 million rows; 2) it stores a snapshot of the data; and 3) it doesn’t manage joining disparate sources well. Running your organization on Excel may be quick and easy, but isn’t sustainable.
Investment advice: Deploy a self-service analytics platform to your end-users as part of a broader data literacy (or data fluency) training program.
8. You rely too much on central IT
The only staff in your organization that can directly access data are those in IT.
Even with a self-service analytics platform, it’s useless without sufficient access to data. Because healthcare data is highly regulated, many organizations simply limit and restrict access to a small team of authorized users. Data privacy and data security shouldn’t be governed by a one-size-fits-one approach but can be thoughtfully tailored to balance security with business needs. Of course, it’s easier to put generic data access policies in place, but it’s much more effective to manage access with governance.
Investment advice: Formalize a data governance program that helps to balance risk and compliance with enabling your organization to use your data as an asset.
9. You’re not getting push reports
Reports are pulled to investigate an issue (after discovery) instead of pushed to alert of the issue.
The dashboard on your car shows a handful of KPIs: your speed, the oil temperature, and maybe your battery voltage. But when a sensor finds an issue, it alerts you to take action. While you may notice that your car is running hot on the dashboard (and hopefully before you smell smoke), isn’t it better to get an alert that something is wrong before you notice the symptoms and experience the consequences? Likewise, rather than monitor every KPI on a dashboard each morning, wouldn’t you prefer to be alerted beforehand?
Investment advice: Define and deploy exception reports which monitor financial and operational data in real-time and alert specific stakeholders to take action.
10. You’ve recently converted your system
You lost access to key reports and historic data and you question if the system is correctly configured.
System conversations pose one of the greatest risks to healthcare organizations. Some estimates suggest 20% of EHR implementations could be considered a failure, and more than 50% are underutilized. Payers face similar risks when migrating benefit administration and claim processing systems. Two of the greatest risks are: 1) bad data converted from the legacy system causes processing issues in the new system, and 2) the new system was configured with incorrect assumptions around data workflows.
Investment advice: Don’t start a system conversation, big or small, without first having a data strategy that outlines how data will be converted and how configuration will be tested.
11. You’ve gone through a merger or acquisition
After recent M&A activity, you’re running reports from two systems with different processes.
Just like merging teams is more complex than drafting a new org chart, merging data for a new region or a new business unit is more complex than just combining databases. This is exactly why leaders often rely on reports from multiple systems for months (or even years) post-close. Merging data requires normalizing and standardizing patients, providers, members, and hundreds of codes.
Investment advice: Deploy a data clean room to promote data sharing and collaboration (even pre-close) and invest in a master data management solution to standardize your data.
12. You’ve lost important talent
Your key analytics staff departed and you’re concerned the technology stack is unsustainable.
Data professionals have their own preferences on the types of tools and technologies they prefer. Whether due to comfort with the tool earned through years of experience or blind passion that a particular technology is best. Because data technology has evolved so quickly, many healthcare orgs have found their technology stack is now antiquated and unable to be supported by new staff who have been trained in more modern data platforms.
Investment advice: Assess your data technology stack to make sure the architecture is well-documented and it follows best practices for a modern data platform.
Protect and invest in your key assets
Just as every individual is in a unique financial position, with unique financial goals and unique risk tolerance, every organization is in a unique data position. The investment advice above is intended to serve as a general guideline to help you zero in on what will be most impactful to your organization.
