How are you Tracking to Value-Based Care?
It’s no secret that today’s healthcare landscape is changing. As costs rise and reimbursement models change, healthcare organizations are continuing to track towards value instead of volume. With this transition comes the rising importance of quality, especially since payers and providers are now dependent on quality measures for reimbursement. According to CMS, these measures are meant to quantify healthcare processes, outcomes, patient perceptions and organizations’ structure associated with providing high-quality care. This journey requires a shift in mindset and new approaches to sharing information to enable quality improvements.
The first step in improving quality of care is the collaboration between payers and providers. Bruce Carver, associate vice president of payer services at MedeAnalytics, notes the importance of this collaboration in a recent interview with Becker’s Hospital Review, explaining that there are great opportunities between payers and providers, especially around data and best practices, to enhance value-based care, such as eliminating gaps in care and driving positive outcomes.
The second step is to use data as a guide to outline areas of opportunities. As payers and providers adopt technologies that enable value-based care, forward thinking organizations are collaborating on quality management programs that serve as the basis of their efforts. These programs must be designed to not only measure and monitor quality measures, but also lead data-driven conversations so payers and providers can collaboratively improve clinical outcomes for their patient populations. Through collaboration and the power of data, both payers and providers can leverage valuable information in the following ways:
- To measure and record an organization’s performance – Both payers and providers can benefit from understanding where their organization is succeeding in providing their members and patients with quality care. Among the many measures, HEDIS and CMS Star Ratings have the greatest impact as value-based care unfolds.
- To help avoid duplicative care – Today’s disconnected provider environment means that many providers operate in silos and do not have insight into care performed by other providers. Duplicative care is not only a waste of time for the patient, but it also negatively affects the healthcare organizations’ bottom line. By taking a holistic approach to a data strategy, organizations can better work together to avoid this.
- To better identify high-risk patients – Data, combined with population health tools and predictive analytics can identify high-risk patients immediately instead of waiting months for data to be generated. Identifying these types of patients early can allow organizations to step in to create personalized, automated interventions that lower healthcare costs and improve the overall health of the patient.
As healthcare industry continues to evolve, payers and providers must look toward a future defined by positive outcomes for their patient populations. The focus on quality and value will become more deeply ingrained. To meet these objectives, organizations must collaboratively design programs that enable them to meet or exceed quality measures and pay-for-performance expectations—today and for years to come.
To learn more about how to improve quality of care for your members in today’s changing healthcare ecosystem, access our whitepaper, Enabling Payer and Provider Collaboration in the Journey Toward Quality Care. To learn how MedeAnalytics can help you on this journey, learn about our quality management solution here.
Enterprise Analytics and Beyond: A Q&A with our Vice President of Healthcare Provider Solutions
In a previous blog, we explored the important approaches and best practices that the payer industry needs to keep in mind to succeed amidst a climate of uncertainty. For this week’s blog post, we are exploring top provider concerns in a conversation with John Hansel, our vice president of healthcare provider solutions. During a Q&A, John shared his perspectives on the challenges that lay ahead for providers and the continued importance of investing in Enterprise Analytics (EA) strategies in today’s rapidly changing healthcare environment.
1. Major healthcare industry transformations will happen in 2017 but what will remain constant? And how can an EA strategy help organizations prepare?
Collaboration between payers and providers will be important regardless of any potential repeal and replace of the Affordable Care Act (ACA). Since the ACA passage, providers have assumed more risk which has led them to acquiring or establishing health plans to help manage and ease the financial burden. In fact, PriceWaterhouse Coopers estimates that 50 percent of health systems have applied or intend to apply for an insurance license. With healthcare organizations establishing their own health plans, they will need to continue to invest in robust analytics to properly manage insight. This collaboration creates more data as information flows in from payers, providers and patients. More data means more information to sift through, making it even more challenging to turn that information into action. The investment in analytics will thus remain a top priority as the technology can offer providers a holistic view of financial, clinical and operational data that fuel cost-saving decisions. This holistic approach to data will help providers better manage the risk they are taking on and gauge areas for improvement whether it be gaps in care or medication adherence.
2. To succeed with an EA strategy, healthcare organizations need to integrate analytics and data into everyone’s day-to-day. How is this done?
There are many challenges that arise when establishing any type of analytics strategy – from a lack of leadership, proper IT support and the associated cost. Some of this is out of our control. However, there are proactive approaches that can be taken to ensure a seamless EA strategy:
- Train and educate the clinical leadership – Healthcare organizations need to invest in their people and training. For example, clinicians often don’t have the background or bandwidth to tackle analytical insights without guidance and support. As such, clinical leaders would benefit from educational courses, workflow conversations and other prep to ensure that they can direct their clinical teams in a data-driven manner.
- Establish realistic goals – Training and education investments are doomed to fail if a provider executive doesn’t establish realistic goals. To ensure that data-driven leadership and approaches become part of a clinical staff’s day-to-day, set realistic goals and timelines. And be patient – this will be an iterative approach vs. a one and done.
- Empower self-service - Putting the tools in the hands of business decision makers can ensure real-time decisions are being made towards important organizational goals. There are various tools and interfaces that business leaders can be trained on that are geared with business end-users in mind. This ensures that insights are getting delivered and implemented throughout the healthcare organization and not in an IT-bottleneck.
With or Without ACA, Payers Should Continue to Invest in Analytics Capabilities
With the turn of the new year and the new presidential administration, the potential repeal and replace of the Affordable Care Act (ACA) has dominated headlines and payers have been left in a state of uncertainty on several major issues. From the 20 million people that could become uninsured, to the removal of the individual mandate and corresponding spike in premiums, health plans are bracing themselves for unknown market instabilities.
However, payers should not lose sight of what they can control today: how to leverage data in a healthcare economy that is defined by value over volume. We connected with Bruce Carver, associate vice president of payer services, to shed light on how critical it is for payers to have a strong data-driven strategy in 2017 to prepare them for forthcoming regulatory changes.
Payers play a unique role in healthcare as they can offer providers access to robust data on their member population. That data, however, is not actionable without proper analytics that can identify potential cost savings via patient care gaps and high cost populations. In 2017, here are three evergreen cost saving areas to focus on:
- The individual market – trend where risk existed over the last three years to understand what you can take on from a cost perspective in the future. This retrospective analysis will allow payers to make strategic decisions on how to approach and cater to specific member populations, like those suffering from chronic diseases.
- Gaps in care – identify gaps in care that are driving down value, work more closely with providers and outline strategies that can start to drive down the bad debt caused by these gaps. Collaboration with providers is the only road to quality to create a holistic patient record. Start collecting information on everything from claims and demographics to clinical data generated by the electronic health records of multiple providers.
- High costs –establish a trajectory of where you are spending the most and use your data to analyze where that spend may be in the future and to course-correct throughout the year. No regulatory mandate will ever change the fact that payer organizations need to have a strong understanding of their profits and losses. Is there an at-risk patient population that needs more interventional resources now before they progress to a chronic condition? Are some of your high cost groups associated with medication adherence issues? These are just some questions to ask and address when examining spend vs. value.
How Health Systems Can Achieve ROI in Analytics Investments
The journey to value-based care is filled with challenges, especially as it relates to measuring quality metrics. This challenge can be difficult to overcome without the right tools and skillsets but analytics can be an invaluable asset to help track and benchmark progress towards value. In fact, this is already becoming a widely-adopted tool, with the healthcare analytics market expecting to reach $42.8 billion by 2024. In this week’s blog post, we’ll outline the necessary steps healthcare organizations can take to ensure return on investment (ROI) with analytics. With nearly every healthcare organization somewhere along the value journey, it’s important to keep in mind that each step should be catered to help meet specific business objectives. Here are three guidelines to start:
1. Lead with Business Use Case, Not Technology
A successful analytics project begins by identifying key stakeholders and understanding their needs for reporting and analysis. Think of the following question when getting started: what business problems are we trying to solve and how can enterprise analytics create value? Analytics programs need to be built with problems at the center.
2. Achieve Quick Wins
Starting small is key. Sifting through and analyzing data can be a large and daunting task, so it’s important to remain focused at the start of your project and then expand. Focus on one or two small use cases such as medication adherence or hospital readmissions. Once those initiatives are deployed, set realistic metrics and timeframes to properly measure progress. If progress is being made, make sure to continue driving the initiative and look for additional growth opportunities.
3. Create a Data-Drive Culture
Healthcare organizations typically work in siloes, especially as it relates to analytics. Each department has various levels of competency and integration of analytics tools. Establishing a dedicated analytics department that is separate from others instills its importance and creates a data-driven culture. Through centralizing analytics, the healthcare organization can spread expertise across the organization, standardize analytical platforms and create governance for consistent calculations and metrics.
To learn more on how to make the most of your analytics investment, 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.
Case Study: How St. Joseph Hospital Achieved 12% Savings with Population Health Data
Due to rising healthcare costs and the shift to value-based care, many organizations are now looking to improve quality and reduce costs. In our recent case study, we highlight how St. Joseph Hospital, part of Covenant Health, was able to leverage our population health solution and consulting services to adopt an innovative approach to population health within its workforce, reducing per member per month (PMPM) costs by 12 percent and saving nearly $2.5 million in 2016.
Prior to MedeAnalytics, St. Joseph Hospital was unable to draw insights from its data. The health system wanted a solution that would allow them to reduce costs, while also improving the health and wellness of their employees.
Through our partnership, St. Joseph Hospital was able to identify which employee patient groups were at risk for chronic conditions and high-cost care. For example, they discovered that a high percentage of pharmacy spending came from specialty drugs and were able to save at least $100,000 with generic drug substitutions. The partnership also allowed the hospital to achieve the following:
- Reduce one employee’s $700 monthly prescription costs to $9
- Build a foundation for population health initiatives
- Devise a focused plan design around data insights
These accomplishments have established a building block for the healthcare organization to continue its march towards value-based care. “We see this as an important stepping stone towards our goal of having at least 50 percent of our payments being tied to value-based models by 2018,” says Richard Boehler, MD and CEO of St. Joseph Hospital.