How Covenant Health Utilized Analytics towards Population Health
Despite the initial administrative concerns, the healthcare industry is continuing its journey towards value to curb costs and improve patient outcomes. The U.S. healthcare spending, which in 2015 hit nearly $10,000 for every person in the country, is 29 percent higher than the next most expensive country, Luxembourg. With rising costs, the industry is looking towards innovative programs that tap healthcare organizations biggest resource: data.
Both Richard Boehler, MD, president and CEO, and Rebecca Williams, RN, care coordination manager at St. Joseph Hospital of Covenant Health (Covenant) connected with Bill Siwicki of Healthcare IT News to discuss how Covenant tapped their timely information to curb costs and improve quality of care for their employees. Here’s a recap of the key takeaways from the discussion:
- Adopted a population health program – To better track and manage the health of Covenant employees across three hospitals and affiliated facilities they looked to population health as a solution. By operating as a self-insured entity, Covenant saw this move as a necessity to improve health and control increasing expenses. The goal of the program was to enhance the well-being of employees, decrease costs and better understand the healthcare utilization patterns of employees and their dependents.
- Harnessed data analytics – Through data and analytics, they guided their population health management efforts. “The first thing we started thinking about was where the money was going; it must be avoidable ER use. We dug into the data, and nope, that wasn’t the case. Then we thought back injuries, so let’s dig in there and maybe we could create a comprehensive back program. But it wasn’t even our employees, it was their spouses, so that went out the window,” said Williams. Executives and caregivers learned that they had to prioritize their employees in terms of healthcare consumption.
- Making insights actionable – “You cannot take a population and put a stamp on it and say let’s do things this way; we had to look at prioritizing people and we worked with sophisticated analytics to see where our time would be best spent,” Williams explained. “The high utilizers were on dialysis or had an organ transplant or an acute burn, those were not things we could make an impact on. But that middle 70 percent is where we could make an impact. Keep people in the middle 70 percent from moving up to the highest spend category.”
Through Covenant’s efforts, they could identify cost drivers and opportunities for preventative care, enabling one of their three facilities, St. Joseph Hospital, to spend $2.5 million less in 2016 and a 12 percent per member per month improvement over all of 2015.
For more insights on how Covenant created a successful population health program, check out the full Healthcare IT News article or their case study here. If you’re interested in learning more on how our population health solution can help your organization – check out details here.
Best Practices for an Enterprise Analytics Strategy
The healthcare economy is changing rapidly – from increased consolidation to the rise of consumerism in care, healthcare organizations face a market that requires a holistic understanding of their enterprise (from clinical to claims data) to succeed. To stay competitive and deliver the best quality of care and value, providers should think like payers and payers like providers. As such, strengthening integrated care remains a hurdle for organizations to overcome as they seek to improve clinical quality, reduce operational costs and support care management. To achieve these goals, healthcare systems must be able to have access to data not just within their own organization, but from outside sources – which is often siloed.
A HFMA Health Care 2020 report on consolidation points out that to succeed in an increasingly competitive marketplace, healthcare organizations are investing in data analytics capabilities to help them understand their patient – and entire business – better. While investing in analytics is an integral key to success, an overall best-practice strategy must be developed to make data actionable. Here are five best practices that should be adopted to initiate an analytics strategy:
- Identify enterprise champions – To ensure buy-in from key internal stakeholders, leadership and process changes must occur. Change to the entire organization’s attitude on data governance must come from the top and trickle down to the bottom.
- Find value in existing data – As new payment models are adopted, healthcare providers need to design a technical infrastructure that can integrate payer, health system and medical group data within an enterprise healthcare delivery system to create value. Organizations should leverage their core data set and claims data, but also pull in existing ancillary data to have a better understanding of their organization.
- Create data-driven culture – Establishing an enterprise analytics department ensures that the entire business is standardizing and handling data consistently, but also encourages the new analytics department to champion a holistic approach towards data management. Champions should include representatives across all departments, from clinical to claims teams.
- Outline and developing manageable goals – Instead of tackling all problems at once, start small. Is the organization focusing on obtaining a streamline, single view of their entire business? By setting a goal with real, manageable next steps, all stakeholders can quickly perceive value in an enterprise initiative.
- Train, train, train – Repeated trainings and regular communications across the enterprise ensure long-term initiative success. By holding teams accountable, while empowering them with resources to succeed, data sharing efforts across the enterprise are bound to improve.
Changing goals and evolving organizational structures require players in the healthcare industry to pivot quickly. Whether it’s to meet increasing consumer demands or to better align on value-based initiatives, organizations will need to rely even more on data to achieve their goals. When organizations embrace analytics, and have a go-to data analytics strategy, the procurement and actionable next steps will come naturally.
To learn more on how to take action with your data, check out our latest whitepaper here. If you are interested in ways we can help you on your analytics journey, learn more about our enterprise analytics options.
Springing into Spring: Health IT Trends to Look For
After a long, cold, winter, the melting snow and warmer weather means spring is finally here. The health IT industry has been busy this past winter with the HIMSS17 conference and the stalling of the GOP health care bill, to name a few. At HIMSS, healthcare leaders were busy discussing machine learning, analytics and population health and sharing new technologies aimed at improving patient care. After the GOP healthcare bill was pulled amid widespread reports that they did not have enough votes to pass it, Republicans say repealing the ACA is back on the agenda, adding to the uncertainty that has faced the industry under the new administration. To kick off the new season, here are a few of the trends that we are keeping an eye out for:
- Precision Medicine – Despite concerns regarding the overall effectiveness of interoperability and big data, a survey by NEJM Catalyst Insights Report found that precision medicine data will have a major influence on the industry in the coming years. This new approach to treatment will be used to eliminate medication errors, improve care, treat disease and help provide feedback for physicians.
- Leveraging Big Data to Solve Population Health Issues - The future of healthcare lies in data but its application is constantly shifting. With the data generated from EHRs and wearables, organizations are faced with growing amounts of useful insight, that in many cases will go unleveraged due to silos or a lack of analytics tools. Throughout the winter, we saw how communities are leveraging data to tackle the opioid crisis, pathologists are using it to detect breast cancer and providers are using it to reduce waste. We will be keeping an eye out to see how organizations will continue to leverage big data to draw insights and uncover new tools.
Finding success in the changing healthcare landscape: Q&A on MedeAnalytics’ Consulting Services
With uncertainty surrounding the ACA and the new administration, payers and providers alike are facing many challenges. Payers are bracing themselves for the 20 million people who could become uninsured, 20 percent of providers remain unfamiliar with the requirements set in place by MACRA and 35 percent of providers are still not getting paid via alternative payment models. These challenges, in addition to any potential roadblocks from new policies, mean that the industry needs to have a strong understanding of where they stand in their journey to value and the potential risk they can feasibly take on. To understand this, healthcare organizations need a strategic partner that can provide best-in-class analytics and guidance on how to make the most of their analytics investment. MedeAnalytics’ consulting team helps clients across the nation better leverage their data and turn cost-saving opportunities into realities.
In this week’s blog post, we explored the current client landscape with Karen Mitchell, Group Vice President of Consulting Services. This Q&A highlights how MedeAnalytics’ consulting services are helping clients overcome their challenges to remain successful in the competitive healthcare landscape, along with her predictions and hopes for the industry throughout 2017.
1. What are some of the common challenges that healthcare organizations come to you with, especially with the uncertainty around the ACA?
Due to rising costs, the continued transition to value-based care and new CMS regulations, financial risks are greater today than they ever have been. Provider organizations are looking for insight into how they can accurately and appropriately bill to decrease denials, improve payment accuracy and ultimately increase revenue and cut costs. Our consulting services can help organizations better identify ways to manage their financial risk so they don’t inadvertently miss revenue opportunities or receive less reimbursement than contracts stipulate.
Payers are facing similar issues due to variations in the cost of services from hospital to hospital. For example, knee and hip replacements are very common operations in the U.S. with about 1 million done each year. In most cases, health plans are not incentivizing members to go to hospitals with lower costs and higher quality outcomes, putting millions of dollars on the line in potential losses from high-cost, lower-performance hospitals. We can help payers identify high-performing hospitals and collaborate on strategies that encourage members to use these top providers, all of which can generate major savings for all.
Analytics Are Nothing Without Action
Although the investment in health IT innovations continue to rise, with 56 percent of providers investing in IT this year, there still remains a disconnect on how to best leverage the data and insights that organizations have at their disposal. With a new healthcare economy focused on value, provider consolidation, consumers and changing reimbursement models, healthcare organizations need a holistic, enterprise-wide view of their business. They also need valuable data insights to tap into cost savings opportunities.
In this week's post, we continue to offer best practices that healthcare organizations can utilize to make the most of their analytics’ investments and turn those insights into action. Here are three key strategies that can make a significant impact on an organization’s financial health:
- Offer Self-Service Access to Business Users: In many cases, organizations have invested in creating an enterprise data warehouse, but the adoption of the platform is often delayed due to IT bottlenecks in reporting and analysis. By empowering business users with the ability to perform their own analysis to identify the root causes of trends, the speed from insight to action will increase.
Find New Value in Existing Claims and Billing Data: Most data warehouses focus on aggregating clinical data from EMRs, but many healthcare organizations fail to recognize the potential in claims and billing data. Most data models are built on this type of data, so their value should not be underestimated. Organizations should also recognize that most risk models and clinical measures, including CMS quality measures and HEDIS measures, are based largely on this data. By using this insight, organizations can better prepare for the changing risk models and clinical measures.
Learn to Work with Payer Data: As new payment models blur the lines between providers and payers, leveraging payer data has never been so important. By creating a data infrastructure and training your staff to manage and analyze payer data, organizations can develop analytics for utilization measures and per member per month (PMPM) cost. These insights can help support new business models and uncover nuances to create added value across the enterprise.
To obtain more strategies, check out our latest whitepaper, Harnessing Enterprise Data Analytics for the New Healthcare Economy, here. Learn more about integrated analytics for the healthcare enterprise here.