Case study: Standardizing healthcare data through terminology
IMO’s terminology-based approach to healthcare data standardization is helping Sharp HealthCare to unlock new value from patient information.
IMO’s terminology-based approach to healthcare data standardization is helping Sharp HealthCare to unlock new value from patient information.
Our latest white paper dives into electronic quality measurement and the challenges of moving from quality measurement to quality improvement.
In our latest eBook, we explore the hazards of incomplete and inconsistent data for health systems and how healthcare data normalization can help.
A recent article in Health Affairs explores five reasons why quality measurement is failing, and five steps to guide the US toward true quality care.
The COVID-19 pandemic exposed longstanding problems in public health. IMO’s Chief Strategy Officer, Dale Sanders, suggests ways to fix an ailing system.
IMO and Amazon Web Services (AWS) are working together to help AWS customers quickly and easily migrate healthcare data to a cloud native environment.
The COVID-19 pandemic has exposed a number of systemic problems hindering healthcare in the United States. Below, IMO’s Chief Medical Officer, Andrew S. Kanter, MD, discusses the impact of one such issue – the frequent failure to collect data that is fit for purposes beyond financial management.
Providers will soon see changes to Medicare’s Quality Payment Program, which will have impacts on their payment for many years to come. Learn more about the specifics below.
In a data-driven society, it’s no surprise that the amount of information generated in the healthcare sphere is vast. That’s both good and bad. While a greater volume of material can support more accurate decision-making, it’s only as valuable as it is useful. Our webinar takes a look at three types of organizations working to solve this problem.
An in depth look at how CORHIO, one of the nation’s largest health information exchanges, is partnering with IMO to address data quality challenges complicating their COVID-19 lab aggregation and surveillance efforts.
Investigate three use cases for patient data through the lens of three different types of healthcare organizations, exploring how data quality issues impact each scenario, and how properly normalized data can help in each instance.
You don’t have to work for a medical coding company to know that quality data is important – especially in healthcare. But patient information comes from a variety of sources, and it’s rarely all in the same format, or documented using the same clinical terminology. So, what does this mean? We’re glad you asked.