The Current State of Validating the Accuracy of Clinical Data Reporting: Lessons to Be Learned from Quality and Process Improvement Scientists

Abstract

We believe that the current practice in HAI reporting of using estimation approaches rather than quality control approaches to data supply chain validation might be supportable for research. However, we believe that it should not be the standard recommended practice for program managers who need to ensure that their data supply chain produces data of sustainably reliable quality over time to ensure maximum protection of the public’s health. Therefore, we strongly recommend an immediate, synergistic alignment of the state-of-the-art validation acceptance-sampling methods and science currently used widely in industry with the needs and logistics of the tasks involved in collecting, sampling, evaluating, and reporting HAI data. We believe that the American public deserves to have its best technology and its “A Team” on the field in this effort and that involving the ASQ, its Healthcare Division, its quality scientists, and its intellectual capital resources could dramatically improve the HAI quality reporting system. Our people and our healthcare system deserve no less!

Using quality improvement to implement the CNS/AAN quality measure on rescue medication for seizures

“…Those numbers were loaded into proprietary statistical process control (SPC) charting templates, which allowed the team to study process changes over time, as well F I G U R E 3 Control chart for diazepam rescue medication prescriptions as distinguish between common cause and special cause variation. 26 For the purposes of the SPC charts, we utilized the American Society for Quality (ASQ) criteria 26 for adjusting the centerline and control limits and evaluated each of our outcomes in monthly intervals. Different rules exist that determine whether a centerline shift has occurred.…”

Distribution of Central Line-Associated Bloodstream Infections Determined From Washington State’s Annual Reporting Validation Program, 2009–2013

“…1 In other industries, quality sciences experts define validation as ensuring that processes reliably produce outcomes fitting their intended purpose. 2 For HAI reporting, this means ensuring that hospital infection surveillance programs continually produce accurate HAI data. However, maintaining surveillance validation activities beyond basic data quality checks can be resource intensive.…”

“…The Washington State Department of Health implemented an international quality sciences based protocol to central line-associated bloodstream infection (CLABSI) reporting validation in 2009. 2 This protocol uses acceptance sampling to ensure hospital HAI surveillance accuracy; it also estimates disease burden and distribution. Here, we report findings and resource needs from the initial years of applying this validation methodology.…”

“…Healthcare-associated infection (HAI) reports for public display, performance compensation, and prevention progress claims require credible validation of surveillance and reporting 1 . In other industries, quality sciences experts define validation as ensuring that processes reliably produce outcomes fitting their intended purpose 2 . For HAI reporting, this means ensuring that hospital infection surveillance programs continually produce accurate HAI data.…”

Beyond Infection: Device Utilization Ratio as a Performance Measure for Urinary Catheter Harm

“…A second limitation of the surveillance definition is the potential for underreporting of CAUTI events. Validation of reported CAUTI outcomes by CMS is also in progress, a process that has its own constraints, 27 but may result in improved compliance by hospitals reporting these to NHSN. The Healthcare Infection Control Practices Advisory Committee (HICPAC) acknowledges the limitations of surveillance definitions when evaluating clinical disease and recommends that reported data be systematically validated 28 .…”