Health care organizations collect patient demographic data including race, ethnicity and language (REAL) to fulfill meaningful use attestation, meet federal accreditation requirements and adhere to CLAS standards (Culturally and Linguistically Appropriate Services). How organizations use this data, however, varies greatly. Many organizations are beginning to use the information with their clinical quality and safety improvement efforts. Those that collect and analyze this demographic data as part of a quality strategy know its power – the power to not only improve outcomes for a specific patient population, but for all patients. Others simply collect this information to meet the data collection requirements. They keep it wrapped up in a box (a.k.a. the EMR), unsure of what they’ll find if they open it up and examine it. Pandora’s box or treasure trove? It all depends on how you look at it.
Using patient demographic data to stratify specific quality outcomes measures can produce a treasure trove of improvement opportunities. It may not be a panacea, but paired with the tenets of health care quality improvement it becomes a powerful tool for health care systems. Imagine being able to focus your efforts on specific processes and procedures for a population of patients who, by using demographic data analysis, you know need it the most. Imagine seeing double-digit improvements that get the attention of your entire institution (and maybe win you some awards). Leading health care organizations have done just that including Harborview Medical Center in Seattle, Wash., Novant Health in Charlotte, N.C. and others.
However, many health care organizations view demographic data analysis like Pandora’s box. I recently had a call with a health system where our data analysis showed a disparity between patients according to race regarding a specific clinical outcome. This is not easy news to deliver or receive but it’s not surprising either. It’s well documented in the literature that these types of health disparities exist throughout the U.S. The good news is now that they know, using a data-informed strategy they can do something about it. And they made sure they were ready to react to this news by involving key stakeholders including their leadership and their Equity, Diversity and Inclusion Committee. I am confident this organization will be successful in resolving the identified disparity while improving care for all of their patients at the same time.
Patient demographic data collection and analysis starts with REAL, but leading organizations aren’t stopping there. Demographics such as veteran status, sexual orientation and gender identity are also being collected to improve access, services and quality of care as well as to tailor care to better meet the needs of patients. Outlined in a field guide called “Trends in Demographic Data Collection and Use in Healthcare: A Field Guide for Improving Care for Veterans,” Vizient is helping health care organizations understand the unique health care needs of veterans and the health disparities they face, along with four best practices for collecting data about veterans. Vizient is offering a public webinar on Tuesday, Nov. 6, 11 a.m. CST, titled “Improving Care for Veterans,” featuring Warrior Centric Health, contributors to the field guide. All are welcome to join us. Registration is open now.
The veteran’s health field guide is the first part of a series Vizient is producing, in partnership with MiH, focused on demographic data collection and use within health care systems. Next month, Vizient plans to publish a guide for serving LGBT patients.
So, Pandora’s box or treasure trove? I think the conclusion is clear. After all, how do you truly know the health status of your patient populations if you aren’t using the key information about them you collect?
