CHIME Series: Creating Value Out Of Your Analytics Investment
We are continuing to focus on the insights from our College of Healthcare Information Management Executives (CHIME) survey. This week we’re exploring the response to one of the questions asked: Do you feel that you have realized the full ROI of your data warehouse and analytics investment? The results to this survey question were astounding with close to 100 percent (95.7 percent) of respondents stating they have not realized the full potential of their investments.
In this blog post, we outline the necessary steps to take to ensure a return on your analytics investment. With nearly every healthcare organization somewhere along the value journey, it’s important to keep in mind that each step should be tailored to meet specific business objectives. Here are three guidelines to start:
- Offer Self-Service Access to Business Users: Although an investment has been made many organizations struggle to fully adopt the platform due to IT bottlenecks in reporting and analysis. By empowering business users with the ability to perform their own analysis to identify the root cause 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.
- 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.
With these best practices, healthcare organizations can begin to realize the value of their analytics implementation. To learn more, download our white paper here. If you’d like to partner with us – go to: medeanalytics.com/company/contact.
CHIME Series: The Value of Having a Dedicated Data Analytics Team
This week, we continue to explore the results of our College of Healthcare Information Management Executives (CHIME) survey and the need for data-driven teams. Our survey asked the question: With the shift to value-based care, have you considered creating a department dedicated exclusively to analytics for the enterprise? The results show that many organizations already have (32 percent) or are considering creating an analytics department (43 percent), while the remaining (25 percent) of organizations have not considered creating an exclusive data analytics team.
As healthcare continues to move towards value-based care, more organizations will need to create teams that focus exclusively on data analysis. An elite data-driven team understands that analytics is more than a data warehouse, and can help organizations make sense of data using predictive models, analysis of gaps in care, quality measure calculations and payer expertise. Breaking down these data silos will shed light on actionable insights that can be delivered to key decision-makers. Below are three best practices to ensure data teams are making an impact throughout the organization:
- Find departmental business leader and champions - data champions are the driving force that will integrate insight into their daily, monthly and/or quarterly management processes.
- Build trust with data governance – it’s important to provide reliable data that business leaders and champions can use to empower physician and clinical teams to reach their goals. To ensure data trust, there needs to be proper governance, documentation and data mapping to help build trust and transparency throughout the organization.
- Develop a data driven culture - data literacy and data democratization is the foundation for creating a data-driven culture. A key component in creating this is tapping data analysts whose sole job is to gather data and analyze it in a meaningful way to generate results. An example of this is with Presbyterian Healthcare Services (PHS), who gave their analysts the appropriate training and mentoring to ensure they were developing a consultative skillset that met the needs of their diverse organization.
With this strategy, healthcare organizations can ensure that their data-driven teams aren’t just understanding the data for their purposes but distributing it across the organization for success. To learn more about setting up a data-driven team, read more here. To get a better understanding of how PHS developed and made the best use of their data, click here. If you’re looking for guidance and assistance, make sure to contact us: http://medeanalytics.com/company/contact
CHIME Series: Are You Making the Most of Your Analytics Investment?
This week we are continuing to share our College of Healthcare Information Management Executives (CHIME) survey results with you. The focus is specifically around the question: Do you feel that you have realized the full ROI of your data warehouse and analytics investments? The results were telling – with close to 100 percent responding “no.” The healthcare industry continues to view data and analytics as top priorities to driving change. We have outlined best practices and strategies to ensure healthcare organizations receive the full potential of their IT investments while making strides to maximize value through the improvement of quality care and reduction in costs.
In partnering with our clients, MedeAnalytics works to ensure that the large hospital investment – both from a cost and organizational perspective – is realized. The key to achieving an overall best-practice strategy is to not only take data to insight but also into action. Below are five steps healthcare organizations can do to get their analytics investment on track:
- Identify enterprise champions – They will be the point-people to turn data into change as they will lead the entire organization’s attitude on data governance. Establishing authority will create a trickledown effect ensuring value is tracked and achieved.
- Find value in existing data – 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 a data-driven culture – An 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.
- Outline and develop manageable goals – Instead of tackling all problems at once, start small. By setting a goal with real, manageable next steps, the organization can quickly perceive value in an enterprise initiative.
- Train, train, train – Repeated trainings and regular communications ensure long-term success. By holding teams accountable, while empowering them with resources to succeed, data sharing efforts across the enterprise are bound to improve.
An investment in analytics is the first step toward becoming a data-driven healthcare organization; however, the real change comes from leadership and education. To learn more about analytics best practices, download our whitepaper here. For success stories, access our case studies here. If you’re looking for guidance on how to make the most of your analytics investment – make sure to contact us: http://medeanalytics.com/company/contact
CHIME Series: Are Self-Insured Providers the Future of Healthcare?
As healthcare’s future continues to be battled on The Hill, we recently conducted a College of Healthcare Information Management Executives (CHIME) survey that outlined several questions around the various data-challenges facing healthcare organizations in the transition to value. This week’s blog focuses on the survey question: With the shift to value-based care, has your health system considered becoming or adopting parts of an integrated healthcare system (i.e., becoming a provider and a payer)? The results show that more than half (61.7 percent) of respondents have considered moving towards this model. As the U.S. healthcare spend continues to rise, with average healthcare costs close to $10,000 and the national level equaling more than 3 trillion, the need to better manage expenses is a top priority. One way to do this is through the cohesion of payers and providers, along with the use of data analytics as a guiding light.
At MedeAnalytics, we’ve worked with two healthcare organizations who have created an integrated healthcare system and utilized their valuable data resources to create analytics platforms that break down barriers and lead to lower costs and higher quality care.
Covenant Health: Covenant Health (Covenant), a self-insured hospital, uses data analytics to adopt an innovative approach to population health to drive down costs and engage in preventative care initiatives. Using a data analytics approach they achieved the following:
- Identified healthcare utilization to improve care for employees and their families
- Designed benefit plans
- Reduced overall health spend
By drawing insights from population health data, they strategically identified at-risk patients and proactively managed their care. Covenant determined that employee healthcare costs were more than 10 percent higher than the general population. Overall, just 9 percent of the highest risk employees were found to be responsible for 40 percent of employee health plan costs. The insights found in the data enabled them to proactively manage their employee population to identify exactly where money was being spent.
Presbyterian Healthcare Services: Presbyterian Healthcare Services (PHS), is an integrated healthcare provider and payer organization, looking to improve quality and reduce costs. Using data analytics, they strategically differentiated themselves and have added value within their integrated model. To achieve their success, PHS focused on three distinct categories:
- Created Value for Key Stakeholders
- Integrated Payer and Provider Analytics
- Promoted a Data-Driven Culture
PHS achieved ROI in its clinical, operational and financial areas within their enterprise. Additionally, PHS recognized operational efficiencies by replacing seven analytics vendors with MedeAnalytics, reducing redundancies and achieving quick wins with business stakeholders. More so, PHS expects to save millions in 2017 by improving collection for Medicaid encounters and increasing business development revenue.
To learn more about Covenant’s success, check out their case study here. For insights on PHS’ journey with data analytics, click here. If you’re looking for ways to become an integrated system or want to learn more, reach out to us: http://medeanalytics.com/company/contact.
Why CFOs and CIOs Need to Collaborate at HFMA ANI
The upcoming HFMA ANI conference (June 25-27) in Orlando, FL, will bring together thought leaders in the healthcare finance space to connect, discuss and explore the opportunities ahead. This year’s show theme – collaborating for the future – is particularly timely since the healthcare industry continues to rapidly consolidate, and the fate of the Affordable Care Act still hangs in the balance. The Trump administration’s potential new healthcare bill increases the likelihood that there will be a rise in uninsured patients, high-deductible plans and a continued focus on cost-cutting and value-based reimbursement for healthcare providers.
The lack of clarity and fast-paced changes in the market places even more pressure on Chief Financial Officers (CFO), whom are already challenged with juggling the transition to value-based care while managing fee-for-service (FFS). In addition to these pressures, many CFO’s feel like their issues are often de-prioritized in the long list of tech projects led by Chief Information Officers (CIO), who are more focused on clinical initiatives. With so much technical effort and budgets directed toward clinical transformations and electronic medical record (EMR) installations over the past 10 years, the financial analytics tools required to thrive under payment reform have been neglected.