Beyond 30 days: does limiting the duration of surgical site infection follow-up limit detection?

超过 30 天:限制手术部位感染随访时间是否会限制检测?

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Abstract

Concern over consistency and completeness of surgical site infection (SSI) surveillance has increased due to public reporting of hospital SSI rates and imminent non-payment rules for hospitals that do not meet national benchmarks. Already, hospitals no longer receive additional payment from the Centers for Medicare & Medicaid Services (CMS) for certain infections following coronary artery bypass graft (CABG) surgery, orthopedic procedures, and bariatric surgery. One major concern is incomplete and differential post-discharge surveillance. At present, substantial variation exists in how and whether hospitals identify SSI events after the hospitalization in which the surgery occurred. Parameters used for SSI surveillance such as the duration of the window of time that surveillance takes place following the surgical procedure can impact the completeness of surveillance data. Determination of the optimal surveillance time period involves balancing the potential increased case ascertainment associated with a longer follow-up period with the increased resources that would be required. Currently, the time window for identifying potentially preventable SSIs related to events at the time of surgery is not fully standardized. The Centers for Disease Control and Prevention (CDC) National Healthcare Surveillance Network (NHSN) requires a 365-day postoperative surveillance period for procedures involving implants and a 30-day period for non-implant procedures. In contrast, the National Surgical Quality Improvement Program (NSQIP) and the Society of Thoracic Surgeons (STS) systems employ 30-day post-operative surveillance regardless of implant. As consensus builds towards national quality measures for hospital-specific SSI rates, it will be important to assess the frequency of events beyond the 30-day post-surgical window that may quantify the value of various durations of surveillance, and ultimately inform the choice of specific outcome measures.

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