Data Metrics for “No Pay” Events: How Accurate is it?

The first two parts of this four-part HC Topics Series: Infection Control and Patient Safety in an Era of Never Events reviewed the development of patient safety and infection control from inception to the current industry climate, and the evolving regulatory framework for reimbursement penalties regarding mandatory public reporting and “never events.”  This third installment will delve further into some of the data, specifically as it relates to reimbursement, and discuss both the benefits and limitations of selected endorsed data metrics for public safety, including concerns regarding validation and accuracy.

Of the many patient safety indicators introduced in the first part of this series, two that have received a significant amount of public attention are certain hospital acquired infections (HAI) and hospital acquired conditions (HAC). The latter, as discussed earlier in the series, is a set 14 conditions that are considered never events,1 and under the Hospital Inpatient Prospective Payment System (IPPS), are ineligible for a higher rate of reimbursement.2  The former can impact hospital finances in several ways.  Eligible hospitals that choose not to participate in the Hospital Inpatient Quality Reporting (IQR) program via public reporting of quality indicators to the National Healthcare Safety Network (NHSN), or hospitals that receive a failing score (i.e., less than 75%) on a validation survey are subject to a two percent reduction in their annual payment update (APU) provided by CMS.3  In addition, beginning in FY 2013, hospital value-based purchasing (VBP) programs will withhold one percent from each participating hospital’s base operating diagnosis-related group (DRG) payments, which will only be reimbursed if the hospital achieves an acceptable performance score.  This score is calculated based on multiple metrics involving clinical processes, patient experience and outcomes (including HAI and HAC rates), and each facility’s demonstrated improvement and level of achievement for these measures.4 Of note, the number of indicators utilized in hospital VBP reimbursement determination is slated to increase over the years, from the original 10 survey-based measures in 2005, to 59 measures in 2015.5  Low-performing hospitals will not receive a return on the one percent reduction to base operating expenses, while high-performing hospitals will receive the full reimbursement in addition to bonus payments from redistribution of monies from low-performing hospitals.6  In addition, in the recently released FY 2014 proposed rule, CMS recommended initiation of a “HAC Reduction Program”, a VBP program whereby low-performing hospitals, i.e., those with specified HAC rates in the highest quartile, will be penalized by a one percent reduction to their APU.7

With increasing amounts of reimbursement at risk based on hospital performance with regard to HAC and HAI reduction, concerns have been raised regarding the accuracy, validity, and redundancy of data being collected for reimbursement purposes.  Two never events that have received attention for this particular concern are Catheter Associated Urinary Tract Infections (CAUTI) and Central Line Associated Bloodstream Infections (CLABSI), since data on both conditions are measured in more than one way, and can thus doubly impact hospital finances.

HAIs, including CAUTI and CLABSI events, are determined based on application of national surveillance definitions of HAIs as published by the Centers for Disease Control and Prevention (CDC) and the National Healthcare Safety Network (NHSN).8 Users of these surveillance definitions are, ideally, highly trained to interpret and assign infection types to events based on clinical and microbiological indicators.  Despite the rigorous training, however, studies have shown that inter-rater reliability for applying these definitions is highly variable among professionals, and that external review is helpful in correcting discrepancies.9 One of the uses of the hospital IQR program, mentioned previously, is to identify these inconsistencies and adjust facility reimbursement if the rate of disagreement between the hospital and external reviewer(s) are high enough to warrant it.

Similar validation and accuracy problems have been identified with utilization of HACs, which also include CAUTI and CLABSI, as a measure of patient safety.  Unlike HAIs, HACs are determined solely based upon physician documentation of a condition or diagnosis in the medical record.10  One recent study found that in comparing hospital coder determination of a CAUTI versus an external physician abstractor, underreporting of CAUTI occurred in 35% of cases.11  In a 2012 HAC analysis prepared at the request of CMS, researchers found that 6% of CAUTI and 3% of CLABSI were not coded or not reported accurately.12

Due to what may be construed as redundant reporting, hospitals are now waging a two-sided battle to first prevent HAIs from occurring, and also to educate providers and medical coders about the implications and interpretation of medical documentation. In one study, researchers found that in comparing CLABSI cases coded by infection prevention professionals with administrative billing data for a subset of almost 3000 patients, the former identified 42 cases of CLABSI, while the latter identified only 10; only 3 of the identified cases were agreed upon by both parties.13

Based on the multitude of discrepancies noted within the varying methods of identification of these two specific measures of patient safety, concerns abound regarding application of certain quality measures for hospital VBP.  With the increasing regulatory and reimbursement implications associated with public reporting of patient safety and quality measures, as well as the rapidly approaching commencement of hospital VBP, penalties associated with consumer perception of published data and reimbursement penalties have created a financial and business case for the prevention of HAIs/HACs.  The next, and last, installment in this four-part series will further discuss the impact these reporting programs have on the various stakeholders in the healthcare industry, as well as potential impact on the evolving U.S. healthcare delivery to create a more quality-centric industry.

“FY 2013 Final HAC List”, by Centers for Medicare and Medicaid Services, (Accessed 6/15/13)

Section 5001 of the Deficit Reduction Act of 2005, Public Law 109-171 (February 8, 2006), STAT 30

“Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and Long Term Care Hospital Prospective Payment System Changes and FY2011 Rates; Provider Agreements and Supplier Approvals; and Hospital Conditions of Participation for Rehabilitation and Respiratory Care Services; Medicaid Program: Accreditation for Providers of Inpatient Psychiatric Services; Final Rule”, by Centers for Medicare and Medicaid Services, Federal Register, Vol. 75, No. 157 (August 16, 2010), p. 50220-50231; “APU Recipients: Hospital Inpatient Quality Reporting Program”, by QualityNet, (Accessed 6/16/13)

“Percentage Payment Summary Report: Fiscal Year 2014”, by Mary Cox, Centers for Medicare and Medicaid Services, July 17, 2013, p. 3, 6-7, 46-49

“Hospital Inpatient Quality Reporting (IQR) Program”, by Mary Cox, Centers for Medicare and Medicaid Services, July 24, 2013, p. 27

Ibid, Mary Cox, July 17, 2013, p. 48-49

“Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long Term Care Hospital Prospective Payment System and Proposed Fiscal Year 2015 Rates; Quality Reporting Requirements for Specific Providers; Hospital Conditions of Participation; Medicare Program; FY 2015 Hospice Wage Index and Payment Rate Update; Hospice Quality Reporting Requirements; and Updates on Payment Reform; Proposed Rules”, by Centers for Medicare and Medicaid Services, Federal Register, Vol. 78, No. 91 (May 10, 2013), p. 27629

“CDC/NHSN Surveillance Definition of Healthcare-Associated Infection and Criteria for Specific Types of Infections in the Acute Care Setting”, Centers for Disease Control and Prevention, January 2013, p. 7-8, 45-46

“Statewide Validation of Hospital-Reported Central Line-Associated Bloodstream Infections: Oregon, 2009”, Oh et al. (May 2012), Infection Control and Hospital Epidemiology, Vol. 33, No. 5, p. 441-444

“Hospital-Acquired Conditions (Present on Admission Indicator): Coding”, Centers for Medicare and Medicaid Services, (Accessed July 24, 2013)

“Hospital-Acquired Catheter-Associated Urinary Tract Infection: Documentation and Coding Issues May Reduce Financial Impact of Medicare’s New Payment Policy”, by Meddings, Saint, and McMahon, (June 2010), Infection Control and Hospital Epidemiology, Vol. 31, No. 6, p. 631

“Accuracy of Coding in the Hospital-Acquired Conditions-Present on Admission Program: Final Report”, by Snow et al., RTI International, June 20, 2012, p. 23

“Accuracy of Hospital Administrative Data in Reporting Central Line-Associated Bloodstream Infections in Newborns”, by Patrick et al., Pediatrics (March 2013), Vol. 131, Supplement 1, p. S77

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