Most health systems suffer from data clutter and efficiency problems. As a result, analysts spend most of their time searching for data, not performing high value work. There are three steps that can help you address your data management issues: 1) find all your dispersed analysts in the organization, 2) assess your analytics risks and challenges, 3) champion the creation of an EDW as the foundation for clinical data management.
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Patient-reported outcomes (PROs), defined as “any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else,” are the future of healthcare.
In addition to helping people like 80-year-old-Ruth continue to live interpedently, PROs—interchangeable with the term patient-generated health data (PGHD)—have several benefits:
- Effectively supplement existing clinical data, filling in gaps in information and providing a more comprehensive picture of ongoing patient health.
- Provide important information about how patients are doing between medical visits.
- Gather information on an ongoing basis—rather than just one point in time—and provide information relevant to preventive and chronic care management.
The new technologies that enable PROs and PGHD (e.g., sensors that detect whether Ruth takes food out of her refrigerator on a regular basis), generate important data outside of patients’ traditional care environments, sharing it with care teams to expand the depth, breadth, and continuity of information available to improve healthcare and outcomes.
Gaining an understanding of the way other people think and operate allows you to more effectively communicate with them — and ultimately — get them to do what is best. In this webinar Gretchen and Tom will discuss the Four Tendencies, apply them to specific healthcare scenarios, and delve into Health Catalyst’s own unique applications of the Four Tendencies with its employee base.
By attending this webinar you will gain:
- Knowledge of the four tendencies: the upholder, the questioner, the obliger, and the rebel
- An understanding of how these tendencies can affect behavior in a healthcare setting
- Practical tips for working with superiors, colleagues, and patients that fall into different tendencies
- Insight into why people choose to act and why they don’t act
The results of applying Gretchen’s model can help you to make better decisions, be less stressed and generally be more effective in your work, but first you must know your own tendency. Click here to take a free tendency quiz prior to joining us.
A Health Catalyst Overview: Learn How a Data First Strategy Can Drive Increased Outcomes Improvements
In this webinar you will learn how healthcare payers and providers are taking advantage of aggregated data and analytics across their networks to identify broad trends and patterns as well as individual personal health profiles provided by combined Health Catalyst solutions and services. Together we will flip up the hood of Health Catalyst offerings so you can understand the strategic interplay between solutions and professional services that have been key to driving more than 155 documented financial, operational, and clinical outcomes improvements.
Without the pressure of a one-on-one meeting, you can join a crowd of your peers to ‘kick the tires’ on Health Catalyst solutions as Jared Crapo—a sought after healthcare strategist—talks about combining interoperability and analytics data, and the unique capabilities of the Health Catalyst DOS platform. Learn about the unique engineering approach that now combines the features of data warehousing, clinical data repositories, and health information exchanges in a single, common-sense technology platform that turns data into actionable assets used for all types of outcomes improvements.
Even if you aren’t in the market for Health Catalyst solutions and services, by attending this webinar you will be able to:
- Think with more clarity through your approach to overcoming the current market challenges.
- Reconsider the strategy you are employing to build cross-organizational awareness and build support to put a data-first plan at the center of your plan.
- Define actions you can take today to assess your gaps, understand your options, and accelerate your progress to drive outcomes improvements.
Join us and you won’t be disappointed. Jared is one of those types of thinkers that many pay big money to listen to and we are fortunate to have 60 minutes with him to think deeply about moving healthcare forward, one patient at a time. We hope you can join us.
With one of every four deaths in the U.S. being attributed to cancer, it is the second leading cause of death, surpassed only by heart disease. There are more deaths from lung cancer than from any other type of cancer accounting for more than 155,000 deaths annually.
While new lung cancer screening guidelines were available, few providers were compliant with the guidelines, or fully understood the complex reimbursement requirements, particularly the patient characteristics that qualify a patient to be eligible for low-dose computed tomography (LDCT) screening and the documentation required for reimbursement.
Mission Health, based in Asheville, North Carolina, is the state’s sixth largest health system with six hospitals and numerous outpatient and surgery centers. The organization wanted to increase the number of patients screened for lung cancer to catch the disease at an earlier, more treatable phase. Mission established a care process model improvement team, enhanced its screening program, and utilized its analytics platform to extract and integrate data from various source systems to evaluate the impact of LDCT screening and outcomes for its patients. Results from the enhanced program include:
- 71 percent relative increase in LDCT screening for people at increased risk for lung cancer.
- 56 people with lung cancer identified through early screening.
- 4.3 percent relative increase in people being diagnosed at early stage I or II lung cancer.
- 21.2 percent relative reduction in people diagnosed with late stage III or IV lung cancer.
A global pandemic, heart failure (HF) affects at least 26 million people worldwide, and its prevalence only continues to increase. Within the U.S. alone, 5.7 million adults live with HF, carrying a cost of nearly $30.7 billion each year. At 55 percent, HF represents the most common cause of Medicare readmissions, and HF accounts for 42 percent of total admissions for Medicare patients.
Readmissions for HF carry a heavy cost for patients and health systems, in addition to reimbursement penalties from CMS. This makes properly assessing the risk for readmission for patients with HF a top priority. MultiCare Health System leveraged artificial intelligence and machine learning to improve the accuracy of readmission risk predictions for patients with HF. Providing a more accurate risk score in a timely fashion gives care teams more time to intervene effectively and prevent avoidable readmissions.
- 85 percent estimated accuracy for heart failure readmission risk predictor. (LACE accuracy around 62 percent)
- Three-fold increase in the number of HF readmission risk-predictions made each day.