Automating Healthcare Quality Reporting

Clinical quality measures help healthcare providers, payers and patients understand, compare and track healthcare quality. But with hundreds of measures in use, collecting and reporting all the data can be a significant burden for providers and agencies. 

That’s why the industry is moving towards electronic clinical quality measures (eCQMs). eCQMs automate the process of collecting and reporting quality data. However, there are some challenges to work through to ensure that the data they are collecting is correct, complete and equivalent to the data reported using traditional methods. 

Why eCQMs?

Current eCQMs are electronic versions of clinical quality measures (CQMs) that have been used in healthcare for more than a decade. Most CQMs have traditionally required manual chart abstraction, in which clinicians go into the patient’s medical record, find the information required and enter it into a reporting program. 

The move towards electronic health records (EHRs) has enabled much of this process to be automated. eCQMs use electronic sources of information such as the EHR and laboratory information systems to populate quality data automatically. This significantly cuts down on the burden for data collection and reporting for clinicians. It also will improve reporting times for reporting agencies and payers. 

Faster, more accurate reporting is needed to support the move towards value-based payment models. In these models, reimbursement is based on the added value that a treatment or service provides to the patient (through better outcomes) or to the healthcare system (through improved efficiencies). The Centers for Medicare & Medicaid Services (CMS) now require facilities participating in the Hospital Inpatient Quality Reporting Program to submit data directly from EHRs, and other CMS quality programs are following suit.

The Downside of Electronic Reporting

The move to eCQMs has not been without its challenges. In many cases, quality measures calculated using eCQMs are not equivalent to those using manual chart abstraction. In addition, many healthcare providers and health IT vendors are not fully prepared for the change. Changes are needed in EHR software and in the ways that clinicians use EHRs to record patient data to ensure that eCQMs are valid, accurate and reliable measures of healthcare quality. 

One of the biggest challenges has been the diversity of EHR software platforms. Different vendors use different architecture and different ways of inputting, displaying and storing data. Many large hospital systems also customize their platforms. This lack of standardization makes automatic data extraction challenging for eCQM reporting. 

eCQMs will have difficulty finding the information they need if data are not recorded in the place the EHR vendor told it to “look” or in the right format. The eCQM also may not recognize if the data in the record is incomplete or nonsensical. Human readers, on the other hand, can easily flip through a record and identify the information they need, even if it is in the “wrong” place or entered in a non-standard format. Humans also are able to use professional judgment to interpret information, recognize erroneous data and reconcile discrepancies. eCQM algorithms are not yet sophisticated enough to match these human abilities. 

Moving to Full Implementation of eCQMs

More work is needed at all levels of the healthcare system to make full implementation of eCQMs a reality. Some steps that will help include:  

  • More standardization in EHR platforms between vendors.
  • Standardization among measure developers, agencies and payers in terms of the structure of quality measures and the format in which quality data are reported.
  • Additional training for clinicians to ensure that they are entering data correctly to facilitate automatic extraction. 

As systems become more standardized and clinicians get more comfortable with entering data into EHRs, eCQMs will make quality data reporting easier and more accurate. The ultimate goal is a quality measure reporting system that fits seamlessly into the workflow and systems at the provider level and provides timely, accurate and reliable information to agencies and payers. 

Battelle is working at all levels of the industry to help make this vision a reality. We are developing solutions to help CMS, the Department of Veterans Affairs (VA), the Department of Defense (DoD), and hospital systems track, report and improve healthcare quality. 


October 02, 2017
Battelle Insider
Estimated Read Time
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