9 data mistakes that amplify risk in value-based care

After years of anticipation, value-based care (VBC) and alternative payment models (APMs) are here — along with new risks for hospitals and health systems to navigate. When hospitals adopt VBC, they assume downside risk, which involves financial penalties if performance targets aren’t met. Transparency challenges can arise due to unclear value-based formulas and metrics, along with other risks like misalignment between providers and executives. Hospitals and health systems need accurate and timely data and data analytics to support behavioral changes and continuously improve their care delivery to ensure they receive compensation.

While existing dashboards in electronic health records (EHRs) help, ensuring seamless integration of data from various sources is crucial for real-time population monitoring. To have confidence when taking on the risks that come with VBC and APMs, hospitals and health systems are investing to build a modern data platform that allows for better data-sharing, care coordination, and innovation. If you’re among this group of forward-thinking industry leaders, take note of these 9 data gaps that could make the business of risk in VBC even riskier.

1. Lacking usable dashboards to continuously monitor your population and outcomes

Dashboards are supposed to simplify complexity, but they often can create information overload. When taking on risk, dashboards must strike the right balance — simplifying data while still providing enough information to monitor population trends and care outcomes. When done correctly, they play a critical role in reducing risk.

For example, one health system built dashboards in Tableau and analytics processed through Alteryx to identify an increase in high emergency department utilizers presenting with nonemergent diagnoses. Because many of these patients lacked insurance, the health system assumed the risk of caring for them, consistent with its mission as a public, safety-net health system. The dashboards helped tell the story of this specific patient population, including their complex behavioral and mental health needs along with a set of social determinants of health (SDOH) that increased their vulnerability. The health system used these dashboards to launch a population health initiative to continuously monitor this population and prioritize case management interventions to engage the patient in primary care, address their SDOH needs, and monitor their outcomes. As they track this population over time, they’ll be much better prepared to spot trends, understand their level of risk, and ensure their actions are leading to improvement.

2. Failing to monitor clearly defined KPI trends in a payer scorecard

A key indicator of readiness for managing payer relationships in a VBC model is the successful management of payer performance within a fee-for-service model. As providers face increased margin pressure and explore efforts to increase collections and revenue integrity with analytics, payers are also investing in analytics to make sure reimbursement is consistent with their contracts and policies.

The result is a zero-sum mindset that causes friction between payers and providers, rather than promoting a partnership with a shared vision (patient health) and mutual benefits (achieving their mission). Strained payer-provider relationships can be improved through transparently reviewing agreed-upon KPI trends together during recurring meetings with the payer.

Payer scorecards aren’t new — in fact, many EHRs include dashboards and reports with the standard metrics in a payer scorecard, such as percentage of first payments denied, average days to denial resolution, and percentage of accounts receivable greater than 90 days. But the standard dashboards often either aren’t used in payer meetings or aren’t effective.

To be effective, the dashboard should roll up the multiple insurance plans you have into one view, which may require integrating data using a platform like Informatica or Snowflake as well as a third-party dashboarding application like Tableau, Sigma, Qlik, or Power BI. Second, the KPIs in the dashboard must be standardized, meaning the payer also agrees with the KPI definition. The dashboard also should be benchmarked so you can show each payer their comparative performance. This will help to make sure the KPIs have targets that you, the provider, and the payer agree upon. Finally, the scorecard should show trended, historical data demonstrating how performance and the payer-provider partnership is improving.

3. Relying on data siloes for reporting instead of a modern data platform

Most hospitals and health systems have more than a hundred individual data sources with clinical information to help manage their population — in other words, data siloes. When clinicians and care coordinators rely on data siloes, they can’t see the complete profile of a patient’s clinical and SDOH needs. However, integrating these siloes with on-premise solutions can be expensive, with high hardware and software costs as well the expense for staff time dedicated to managing complex data integrations.

To prepare for value-based care, we advise hospitals and health systems to first deploy a scalable modern data platform like AMN Healthcare did with Snowflake to eliminate data siloes, which can dramatically reduce costs and help make meaningful improvements to patient care.

4. Caring for patients without continuous, real-time feedback loops to clinicians

The founder of the quality movement, W. Edwards Deming, said that “Quality is everyone’s responsibility.” This is perhaps most true in a healthcare setting, where the actions of every provider and healthcare worker can impact quality measures. And as the shift from fee-for-service to VBC continues, it will be even more important for hospitals and health systems to manage the quality measures through continuous quality improvement initiatives. In fact, your reimbursement may depend on it.

One method to master your VBC measures for maximum reimbursement is leveraging your data to provide real-time feedback to clinicians on patient outcomes and quality measures. Feedback loops are critical to reinforcing behavior. When a driver presses the gas pedal on a car, they see, hear, and feel that it achieves the outcome they expect. In the same way, it’s vital to help clinicians to see and confidently know the actions they’re taking are making improvements.

With the hundreds of data sources in a typical hospital or health system, this can be difficult. Tools like Informatica can help to integrate data quickly, as New York Health + Hospitals experienced by empowering 50,000 healthcare professionals with trusted data and analytics.

5. Lacking the ability to ingest shared data from partners and monitor attributed lives

When you take on a downside risk arrangement to manage a population, you can’t do it alone. While you may be attributed to the patient life, you’ll be relying on data from other providers, clinics, hospitals, pharmacies, insurers, laboratories, and community partners to manage your population.

Without the tools to ingest data from partners and see a complete clinical profile of your population, you potentially assume unknown risks you’re not aware of without the information you need to manage the risk. This requires a very thoughtful data strategy and a robust data governance program. Even though the inability to access data from your partners is a risk, ingesting data without a clear plan to manage the security risk — and potentially introducing data that may not be consistent with your organization’s data standards — is also risky. Participating in a healthy information exchange can help promote these standards, and we advise clients to prepare by building a modern data platform such as a combination of Informatica and Snowflake that can ingest and manage data and scale with your needs.

6. Modeling complex APM payment performance and cashflow scenarios in the wrong tool 

Modeling fee-for-service contracts is complex enough with the need to account for different base weights and rates by facility, bundled services, and complex outlier provisions. Your health system has likely invested in robust contract modeling solutions to both estimate potential reimbursement scenarios and validate that payers are reimbursing claims consistent with contract terms. And even through all of this effort, you still may uncover special cases that require refining your contract models — that’s why it’s important to find a platform that’s nimble enough for your team to modify as needed.

When transitioning from the well-understood fee-for-service model to a less-understood VBC model, which has more variables and downside risk, hospitals and health systems shouldn’t rely on overly rigid modeling tools. The payers you’re negotiating with have teams of actuaries and years of actuarial experience modeling risk through their underwriting process. When entering into risk-based contracts with them, hospitals and health systems CFOs should work with their CIO or chief data officer (CDO) colleagues to level the playing field with a modern data platform and technologies to model risk-based contracts.

7. Relying on “pull” reports instead of “push” alerts for data-driven decisions

As we saw during the COVID-19 pandemic, timely data is correlated with timely decision-making. In response to the pandemic, many health systems launched new dashboards with real-time (or near real-time) data to quickly respond to the rapidly changing operational situation. In each department, teams of clinicians and leaders would ask for the most current reports to find the handful of key data points to inform their decision-making. This system won’t be efficient enough going forward.

You shouldn’t need to pull data reports from your tools; your tools should automatically send you the information you need to make decisions when you need it. To be prepared for a risk-based world, hospitals and health systems will need push alerts to provide care for patients, manage attributed lives, and mitigate risk. In a VBC environment, operations will make you or break you and will require you to proactively manage patient care, based on data, as highlighted in these four tips to manage the switch.

8. Lacking interoperability tools to share real-time data and seamlessly coordinate care

When taking on risk for attributed lives, you need to be able to support all other providers and community partners who deliver care and services for your population. And one of the best ways you can support them is through securely providing the clinical patient data they need, when and where they need it.

In the wake of the widely publicized Change Healthcare ransomware attacks, many hospitals and health systems are reevaluating their data security and data-sharing policies, which is appropriate given that protecting sensitive patient data requires a collaborative, organizationwide strategy.

But as the shift to VBC continues, simply avoiding data-sharing isn’t a viable long-term option. It’ll be necessary for hospitals and health systems to have the interoperability tools to share data and provide timely access. For example, a modern data platform such as Snowflake provides a flexible and secure method to confidently and quickly share data with partner organizations as demonstrated by the Colorado Community Managed Care Network. As interoperability standards like Fast Healthcare Interoperability Resources become more widely adopted, and as your partners gain the ability to receive data, the expectation (and opportunity) to share real-time data that helps to seamlessly coordinate care will grow.

9. Having data governance gaps that cause poor or inconsistent data quality

You can fix every other data mistake on this list, but it would all be for nought if your data was incomplete or inaccurate. The transition to VBC will illuminate the divide between two types of healthcare organizations — those that invest in and protect their data as a strategic asset and those that disregard it as just another technology cost.

When 30% of the world’s data volume is being generated by the healthcare industry, but only 57% of a healthcare organization’s data is used in key decision-making, it seems there must be a problem. Perhaps it’s because just 20% of healthcare organization executives fully trust their data.

Getting started

There’s an imperative on the horizon for all hospitals and health systems to formalize a robust data governance program. The program should be designed to educate your people, enhance your data management processes, and deploy data governance technologies to improve data quality and advance your readiness for taking on risk.