Variations in Quality Calculations Among EHR, HIE Data and the Impact on Reimbursement

A recent study found federal, state, and commercial programs that rely on quality measurement as part of reimbursement could promote improved quality measurements by increasing clinical data sharing.  

“Accurate and robust quality measurement is critical to the future of value-based care,” wrote the authors of the study. “Having incomplete information when calculating quality measures can cause inaccuracies in reported patient outcomes.” 

To better understand the study design and findings, we spoke with John D’Amore, cofounder, board member, and strategic advisor for Diameter Health, and Laura McCrary, EdD, president and CEO of KONZA. They explain the differences in how ambulatory quality calculations vary when using data from a single electronic health record versus longitudinal data from a health information exchange operating as a multisource registry for quality measurement, and how these measurements are critical to the future of value-based care. 

Why did you conduct this research? 

A number of studies show that data incompleteness and lack of data exchange between systems may impair clinical care, patient safety, and secondary research. For example, a 2016 study by Northeastern University, Harvard Medical School, and Harvard Pilgrim Health Care Institute shows that outpatient behavioral care data for more than half of patients with depression and bipolar disorder were missing from the EHR of a large multispecialty medical practice in Massachusetts.

A 2015 study by Weill Cornell Medical College and Medical Group Management Association estimated the cost of quality reporting for general internists, family physicians, cardiologists, and orthopedists at $15.4 billion annually. Much of this cost stems from time spent documenting care through varying workflows to make quality calculation possible. 

And in a 2018 review of academic articles on the impact of HIEs, researchers at Indiana University and the Center for Biomedical Informatics concluded that 68.3% of more than 63 individual analyses show HIEs improve patient care while reducing costs. 

Can you talk briefly about the study? Did the study findings surprise you?

We wanted to examine how ambulatory quality calculations vary when using data from a single electronic health record (EHR) versus longitudinal data from a health information exchange (HIE) operating as a multisource registry for quality measurement. 

The results demonstrate that quality measures based on single-site EHR data may be limited by incomplete information. Effective data sharing significantly changes quality calculations, which affect health care reimbursement, patient safety, and care quality.  

Our study also finds that data sharing provides depth to measures routinely used in value-based payment models. Therefore, programs that incorporate longitudinal data are more likely to result in more accurate quality measurement.  

What can health care professionals take away from this study? 

We see three policy implications to our research demonstrating that individual EHRs often have incomplete data for ambulatory quality measurement. First, our findings indicate that ambulatory quality programs that encourage data sharing may improve quality calculation for practices and health systems. Refocusing quality programs on data sharing reinforces the value of data interoperability and recognizes ambulatory care as a “team sport-” where multiple practitioners are integral in providing quality care to a patient.

Second, harmonized quality reporting methods can provide more consistency in quality measurement. While some facilities saw measure discrepancy rates exceed 20% in this research, others were below 5%. Until widespread interoperability is achieved, longitudinal calculation or EHR-based episodic quality measurement may provide more comparable performance rates.

Finally, effective data sharing provides an alternative infrastructure for measure calculation. This has the potential to reduce administrative burden, cost, and frustration associated with measure calculation. Longitudinal data aggregation using standards, such as those promoted by the Office of the National Coordinator for Health Information Technology and the National Committee for Quality Assurance, can provide a foundation for this transition.

Do you and your co-investigators intend to expand upon this research?

We never say never. However, having established the efficacy of clinical data sharing using rigorous research methods, we intend to continue to advocate for interoperability through data standards in the health care ecosystem, where we can best enable improved patient care and clinician satisfaction. 

Is there anything else pertaining to your research and findings that you would like to add?

We want to recognize our co-authors who participated with us: Jody Denson, Chun Li, Christopher J Vitale, Priyaranjan Tokachichu, Dean F Sittig, Allison B McCoy, and Adam Wright. Without their contributions, this research would not have been possible. 

About Mr D’Amore

Mr D’Amore is cofounder, board member, and strategic advisor for Diameter Health, a health data optimization solutions provider that transforms raw patient information into the highest quantity and quality of interoperable data for health care organizations. He has more than a decade of experience providing informatics and strategic insight to health care organizations. Prior to Diameter Health, he was vice president at Eclipsys (now Allscripts) overseeing enterprise performance management solutions. Mr D’Amore published on best practices in population health and presented at national forums on how information technology can improve medical outcomes.  

His research background is extensive and includes publication in the American Medical Informatics Association (AMIA), Applied Clinical Informatics, Journal of the American Medical Informatics Association (JAMIA), and American Journal of Public Health. He has also been technical advisor and editor to organizations (ONC, NCQA, HL7) influencing clinical data exchange and use nationally. He holds a biochemistry degree from Harvard University and a graduate degree in clinical informatics from the University of Texas, School of Biomedical Informatics.

About Dr McCrary

Dr McCrary is president and CEO of KONZA, a non-profit organization that operates a nationwide health information exchange (HIE). KONZA is committed to empowering health care providers, patients, health plans, and our technology partners to organize health care data into information that will drive health care transformation. She completed Post-Doctoral work at University of Kansas and received a Doctorate of Education from Kansas State University. Dr McCrary is an adjunct professor at Rockhurst University-Helzberg School of Management teaching courses in Health Information Technology and Quality. Finally, she has served as co-chair of the Advisory Board for the Sequoia Project/Carequality and on the Governance Group for the National Syndromic Surveillance Program. 

Reference:

D'Amore JD, McCrary LK, Denson J, et al. Clinical data sharing improves quality measurement and patient safety. J Am Med Inform Assoc. 2021;28(7):1534-1542. doi:10.1093/jamia/ocab039