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: 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.
Driving Enterprise-Wide Change by Breaking Down Data Silos and Creating a Data-Driven Culture
This year’s Big Data & Healthcare Analytics Forum brought together payers, providers, government and academia decision-makers who shared their successes and lessons learned from their transition to value-based care. Of the many thought leaders who participated in the discussion, our client, Soyal Momin, Vice President of Data & Analytics at Presbyterian Healthcare Services (PHS), presented his abstract, “Eliminating Data Silos and Driving ROI.”
As a large integrated healthcare system consisting of eight hospitals, a statewide health plan and a growing multi-specialty medical group, PHS found it increasingly challenging to oversee its entire business from one integrated view. After investing in an enterprise data warehouse (EDW), PHS continued utilizing several reporting tools from different vendors for each of its business lines that created data silos. For PHS to thrive under the value-based care model, the organization knew they needed to balance their costs, utilization, quality, risk and outcomes. During Soyal’s presentation, he outlined how through their partnership with MedeAnalytics they could strategically differentiate themselves and add value within their integrated data analytics model. To achieve this success, PHS focused on three distinct categories:
- Creating Value for Key Stakeholders – Creating an integrated, enterprise approach, extends meaningful, actionable insights across PHS and to their business users so they’re able to access content, business rules, benchmarks, best-practice analysis and views.
- Integrating Payer and Provider Analytics – Through an enterprise approach to analytics, PHS has an integrated overview into their provider groups and health plan. The insights are extended across financial, operational and clinical areas throughout the provider-side of the organization. For the health plan, they can analyze payer data for cost and utilization.
- Promoting a Data-Driven Culture – Data literacy and data democratization is the foundation for creating a data-driven culture. A key component in creating this was tapping data analysts whose sole job is to gather data and analyze it in a meaningful way to generate results. PHS gave their analysts the appropriate training and mentoring to ensure they were developing a consultative skillset that met the needs of their diverse organization.
PHS has 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.
Data Democratization at the Heart of Health Datapalooza 2017
The 8th Annual Health Datapalooza conference in Washington D.C. brought together a variety of data advocates who focused on how to harness the power of big data and put it into the hands of the people who benefit from it most: patients and providers. As part of the two-day event, one of our clients – Ian Morris, Clinical Data Interoperability Project Manager for the State of Mississippi, Division of Medicaid – presented as part of a panel titled “Health Systems Reaching Out to Patients and Providers.” During his presentation, Morris shared Medicaid’s experience of modernizing their Medicaid infrastructure and empowering real-time data sharing across all of Mississippi. In addition, Morris outlined lessons learned around interoperability and the roadmap for Medicaid’s interoperability efforts in years to come.
After the conference came to an end, we connected with Morris to discuss his experience at the event and other key takeaways. Morris shares his highlights below.
1. As a first-time attendee and presenter at Health Datapalooza, what intrigued you most about the event?
It was refreshing to hear the patient perspective. A lot of the time when you attend conferences that focus on data and analytics, you don’t get the rich patient narrative. However, Health Datapalooza took the imperative to put democratization of health data at the heart of the event. Empowering the physician and patient to take control of the data is what we’re all striving for, and that’s where organizations like Medicaid fit into the narrative. You need to understand the value of data first, and that’s where we – people such as interoperability managers – come into play. We translate that value, and once it’s understood by the provider, it can be shared externally with the patient.
2. What was a best practice that you learned from your peers and what do you hope to see at next year’s conference?
There were many presentations at the event that delved into the importance of collaborating between multiple state systems (i.e. bridging the broader health and human services, mental health and advocacy groups together) all for the greater good – improving patient outcomes via better data sharing. Such intricate collaboration efforts made me think of the initiatives Medicaid plans to embark on in the future. If there is one take away, it’s that statewide collaboration is key to better data sharing practices. My hope for next year’s conference is to have more speaking panels that touch upon just this, especially as it relates to interoperability efforts overall.
3. Other post-conference highlights that you’d like to share?
Health Datapalooza was full of energetic and enthusiastic data leaders. From patient advocates, to vendors to hands-on project managers, conference attendees and speakers embraced each other’s lessons and shared challenges of their own. Serving as a microcosm of what we’re all striving for in healthcare, Health Datapalooza reminds us that the sharing and analysis of data has a purpose – and that is ultimately to improve patient outcomes.
To read more about how Mississippi Division of Medicaid became the first Medicaid Agency to exchange clinical data summaries with their providers, read their story here. To learn more about how to act on your data and ensure quality, cost-effective care for Medicaid beneficiaries, visit our Provider Access solution here.