Thank you for taking time to read my letter and explore the knowledge center we've created for Reading Health System. Below, I've selected resources I believe will resonate with your organization. I hope they will provide you with useful insights and perspectives as you think about how enterprise data warehousing and analytics can transform your organization. Lastly, I’d like to challenge every healthcare system in the country by asking a simple question: “What transformative data driven success stories will you be adding in the next 12 months?”
How to Reduce Heart Failure Readmission Rates: One Hospital’s Story
An estimated 24 percent of patients who are discharged with heart failure (HF) are readmitted to the hospital within 30 days. Learn how this healthcare organization engaged physicians and multidisciplinary teams to improve their outcomes. Deploying evidence best practices—medication reconciliation, follow-up appointments, follow-up phone calls and teach back—they reduced and sustained their 30-day HF readmission rates by 29 percent, and their 90-day HF readmissions by 14 percent. They have seen their process measures increase significantly: 120 percent increase in follow-up appointments; 78 percent increase in pharmacist medication reconciliation; 87 percent increase in follow-up phone calls; 84 percent increase in teach-back interventions.
Population Health Analytics: Improving Care One Patient at a Time
Population Health Analytics is about more than just identifying a group of patients. It involves helping physicians care for their patients as individuals, improving their own practice through evidence-based best practices, and enacting cultural change that results in better outcomes for entire populations. Population Health Analytics—with the capability to look at one patient at a time and one physician at a time—will enable providers and organizations to answer three important questions: 1) What best practices should I be doing with this population? 2) How well am I following these best practices with this population? And 3) How can I change to create better outcomes for this population?
In addition to addressing these population health questions, please join Tom Burton, Co-Founder and Senior Vice President of Product Development, Health Catalyst, as he discusses Population Health Analytics and presents the Three Systems Model of Care Delivery. Tom will share Health Catalyst’s experiences and learning’s and why each system is essential to create long-term change and transform healthcare.
Attendees of the webinar will:
Learn about the Three Systems Model of Care Delivery required for effective Population Health Analytics. Understand the issues that must be addressed at each stage in order to optimize care delivery.
Discover the role analytics play in enabling physicians to deliver better care to their patients leading to improved outcomes for an entire population of the patients.
In the future, healthcare executives with a solid Population Health Analytics system will be better prepared to deliver better outcomes and more efficient care. Both will be key for succeeding with payment models based on risk, value, and performance.
Launching an EDW to Rapidly Reduce Waste in Asthma Care
See how one children’s hospital used its enterprise data warehouse and related analysis tools to uncover a faulty order set in an EHR that was resulting in too many chest xrays. End result? A 49% reduction in x-rays ordered in the first six months. And the numbers just keep getting better.
My Wake-Up Call: How Data Saves Lives
Have you ever had one of those “wake up moments” where you literally learn a lesson that impacts and changes the trajectory of your life? Read this personal story by Dr. Bryan Oshiro of his “wake up” call where he learned the importance of data to save lives. He learned this first-hand when he saw rows of babies on ventilators in the neonatal unit and realized that they had all been electively delivered before 39 weeks. But he didn’t have the data compiled to make a compelling case to his physicians to stop elective pre-39 week deliveries. Working with his technology team, he gathered the data, analyzed it, and successfully engaged his physician team in a quality improvement project to reduce these elective deliveries.
Texas Children's Hospital Significantly Reduces Reporting Costs Using a Clinical Data Warehouse
Clinical data can be difficult to extract from an EMR, particularly when you want to combine it with other data and use it in a timely manner. But when Texas Children’s Hospital adopted an enterprise data warehouse, they found they were able to extract the data and create near real-time reports that came with an added bonus: a 67% cost savings.
Healthcare Revenue Cycle: How to Improve Data Timeliness and Reduce Manual Work
With cash flows declining, margins tightening and bad debt increasing, it’s more important than ever for healthcare organizations to maintain their bottom line. Efficient, effective revenue cycle management that ensures timely payment is one key to an organization’s financial health. Learn how this healthcare system: a) improved their data timeliness, b) realized an estimated $380K in annual operational savings, and c) reduced manual work.
How to Increase Professional Billing Charge Capture with Healthcare Analytics
The demand on hospital coders continues to rise – and even more so with the ICD-10 rollout. At the same time, health systems want to make sure professional billing charge captures are accurate. Learn how North Memorial Health System leveraged their hospital enterprise data warehouse – and the Health Catalyst Professional Billing Module – to: a) increase the number of provider notes with sufficient clinical data for billing, b) increase their monthly net income and c) improve their hospital coding staff productivity by 25%.
Automating the Executive Healthcare Dashboard: Spend Less Time Collecting and Validating KPI Data
Healthcare executives rely increasingly on executive healthcare dashboards to provide a snapshot of their organization’s performance measured against established monthly and yearly key process indicator (KPI) targets. However, collecting and aggregating the needed data to create the dashboard can be a very time-intensive process and many organizations are using Excel spreadsheets to “cobble together” these dashboards from a variety of sources. Learn how this organization is leveraging a healthcare enterprise data warehouse (EDW) and analytics technology to automate and improve the dashboarding process.