In the News
Stories and trends changing the healthcare landscape
Analytics for Population Health Management – Article 4 – July 2023
Expanding Data Sources for Identification of Risk – Population Health Re-Imagined
Healthcare organizations are increasingly using additional sources of data to augment their understanding and insights into the populations they serve, for a variety of purposes – from forecasting health outcomes and future use of services to development of strategies for outreach and engagement.
As good fortune would have it, the advent of electronic medical records and other home monitoring devices opens up new possibilities for incorporating relevant data about individuals under review within the health program evaluation framework.
Analytics for Population Health Management – Article 3 – May 2023
Accounting for Health Risk and Disease Prevalence
Population Health Management requires providers and program managers to maintain a delicate balance between taking a longer-term view of a target population (patient) experience and outcomes versus a short-term focus on individuals participating in a health management program and their near-term cost, utilization and outcomes. It is often difficult to see the forest for the trees, when too much of the analytic focus is centered around short-term experience, particularly when measured by cost and utilization results.
Analytics for Population Health Management – Article 2 – May 2023
Using a cost and utilization lens to evaluate and improve health care delivery
As interest in improving care management grows, it is important to establish which models of care are most effective. As described in our first article in this series on “Analytics for Population Health Management”, it has now been over ten years since the Institute for Healthcare Improvement (IHI) introduced the Triple Aim framework, which has served to ignite the realization that quality of care (done right) will not only improve patient experience, but also leads to improvements in overall population health and potential to reduce health care costs. The Triple Aim framework also served to highlight the unintended consequences of cost-cutting without an understanding of potential to put quality at risk. The IHI model represented the idea that evaluation of population health management programs and services should not simply look at cost drivers at the population level but must also take into consideration the drivers of individual level quality and outcomes. This article offers some perspective and suggestions for how to accomplish this.
Case Study – Leveraging Operational Data and Process Analytics for Efficient Delivery – March 2023
This case study outlines how to re-design a complex, high risk, end-to-end claims appeals intake to improve outcomes. The recommended re-design included metrics around timeliness and productivity, and Standard Operating Procedures (SOPs) to achieve a more streamlined and simplified organization and sustainable, improved performance. This goal was achieved through leveraging operational data and process analytics aimed at improving the effectiveness and efficiency of the medical claims appeals lifecycle.
Case Study – Managing with the Right Metrics – February 2023
Improving operational performance and delivery through identifying and measuring the key metrics, with a focus on aging and turnaround time, compliance, mitigating accreditation risk via new processes, reporting, and operational discipline.
Analytics for Population Health Management, Introduction to Series – January 2023
Maturing Analytics for Population Health Management
This is the first in a series of articles that will introduce an analytic capability and framework for translating health care data into actionable insights for population health management. Many healthcare organizations struggle to transform available data into viable solutions that improve patient care, while lowering cost of care at the same time. However, the growing emphasis on value-based healthcare has created the imperative for maturing analytics and unlocking insights needed to effectively manage population health and improve individual patient outcomes.
Primed Analytics Platform™ – November 2022
Primed Platform Supports Advanced Analytics
Expectations of health care analytics platforms have evolved considerably over the past several years. While this is true for well-established organizations, startups also need to come to the table with a matured analytic capability out of the gate to compete in today’s fast moving and ever-changing business environment.
Primed Analytics Platform – October, 2022
Evolving Health Care with Advanced Analytics Platforms
Expectations of health care analytics platforms have evolved considerably over the past several years for both start-ups and mature organizations. There is a growing need to accelerate the speed at which data is ready and available for business case development. Today’s fast moving, competitive environment calls for the ability to launch new initiatives quickly and be prepared to react proactively to rapidly changing market conditions.
Achieving Health Equity – August 2022
Achieving Health Equity – The focus has shifted to health payers and providers for solutions
U.S. public policy emphasis on Health Equity has been building for years. However, the COVID-19 pandemic and associated calls to action have now shifted attention to all parts of the health care system for potential solutions. The pandemic had a significant impact on the U.S. health and human services landscape, and inequities within the health care system propelled to the spotlight.
Lack of diversity in clinical trials isn’t just a recruiting problem—it’s a data problem
Leveraging the right data infrastructure and analytics can greatly improve healthcare processes. For example, though clinical trials have several obstacles to overcoming a lack of diversity, modernizing the data infrastructure and analytics is one of the most impactful improvements for such aspects as identifying the right patients to recruit. Modernizing also accommodates other improvements, such as:
- Identification of health inequity
- Root causes of disparity
As clinical trials are required to improve and pivot, so too is the way of wrangling the underlying diverse data streams and managing that data to present insights for better decision making in that recruitment process. DataWELL’s analytics and data platform are built for just that purpose, to support healthcare companies’ needs of:
- Speed of development
- Data management
- Leveraging one source of truth
- Timely data insights
“To achieve diversity goals in research requires a multifaceted approach that makes clinical trial participation easier and uses analytics to help identify the right patients to recruit for a clinical trial.” – Raj Indupuri (via MedCityNews.com)
(Links to a site external to Well Solutions Group)
