Could the prevention of health care-associated infections increase hospital cost? The financial impact of health care-associated infections from a hospital management perspective.

BACKGROUND: The financial burden health care-associated infections (HAIs) have on patients, payers, and hospitals is not clear. Although patient safety is the highest priority, administrators require data to justify the expense of HAI reduction programs. METHODS: Chart review was performed to identify HAIs for patients discharged from Stanford Hospital. Using a t test, we tested whether patients with an HAI will have a different daily total hospital cost and length of stay than patients without an HAI. We calculated the change in hospital profit related to HAIs by comparing patients with and without an HAI in the same admit All-Patient Refined Diagnosis Related Group and complexity score. RESULTS: Between October 1, 2015 and September 30, 2018, there were 78,551 inpatient discharges and 1,541 HAIs identified. Daily total hospital cost and length of stay for patients with an HAI versus patients without an HAI was $6,433 ($6,251, $6,615) versus $6,604 ($6,557, $6,651) (P = .073), and 26.30 days (24.89, 27.71) versus 5.69 (5.64, 5.74) (P < .001). DISCUSSION: For each HAI eliminated, data suggests that hospital's cost and revenue would increase $25,008 and $1,518,682, respectively, by backfilling beds with new patients at a 4.62:1 ratio. The reduction of HAIs is profitable for hospitals. CONCLUSIONS: Data from this study suggest that the more HAIs you eliminate and the more capacity you build for the hospital, the higher the total hospital costs will go. This is an essential shift to the current paradigm that will allow for the accurate and continued funding of HAI reduction programs. Although hospital cost appears to increase as HAIs are reduced, hospital profits rise even more.

Using electronic medical records to increase the efficiency of catheter-associated urinary tract infection surveillance for National Health and Safety Network reporting.

BACKGROUND: Streamlining health care-associated infection surveillance is essential for health care facilities owing to the continuing increases in reporting requirements. METHODS: Stanford Hospital, a 583-bed adult tertiary care center, used their electronic medical record (EMR) to develop an electronic algorithm to reduce the time required to conduct catheter-associated urinary tract infection (CAUTI) surveillance in adults. The algorithm provides inclusion and exclusion criteria, using the National Healthcare Safety Network definitions, for patients with a CAUTI. The algorithm was validated by trained infection preventionists through complete chart review for a random sample of cultures collected during the study period, September 1, 2012, to February 28, 2013. RESULTS: During the study period, a total of 6,379 positive urine cultures were identified. The Stanford Hospital electronic CAUTI algorithm identified 6,101 of these positive cultures (95.64%) as not a CAUTI, 191 (2.99%) as a possible CAUTI requiring further validation, and 87 (1.36%) as a definite CAUTI. Overall, use of the algorithm reduced CAUTI surveillance requirements at Stanford Hospital by 97.01%. CONCLUSIONS: The electronic algorithm proved effective in increasing the efficiency of CAUTI surveillance. The data suggest that CAUTI surveillance using the National Healthcare Safety Network definitions can be fully automated.