Designing surveillance for noninfectious outcomes of medical care

Feeding back surveillance data to prevent hospital-acquired infections

We describe the Centers for Disease Control and Prevention's National Nosocomial Infections Surveillance system. Elements of the system critical for successful reduction of nosocomial infection rates include voluntary participation and confidentiality; standard definitions and protocols; identification of populations at high risk; site-specific, risk- adjusted infection rates comparable across institutions; adequate numbers of trained infection control professionals; dissemination of data to health-care providers; and a link between monitored rates and prevention efforts.

Requirements for infrastructure and essential activities of infection control and epidemiology in hospitals: A consensus panel report. Society for Healthcare Epidemiology of America

The scientific basis for claims of efficacy of nosocomial infection surveillance and control programs was established by the Study on the Efficacy of Nosocomial Infection Control project. Subsequent analyses have demonstrated nosocomial infection prevention and control programs to be not only clinically effective but also cost-effective. Although governmental and professional organizations have developed a wide variety of useful recommendations and guidelines for infection control, and apart from general guidance provided by the Joint Commission on Accreditation of Healthcare Organizations, there are surprisingly few recommendations on infrastructure and essential activities for infection control and epidemiology programs. In April 1996, the Society for Healthcare Epidemiology of America established a consensus panel to develop recommendations for optimal infrastructure and essential activities of infection control and epidemiology programs in hospitals. The following report represents the consensus panel's best assessment of needs for a healthy and effective hospital-based infection control and epidemiology program. The recommendations fall into eight categories: managing critical data and information; setting and recommending policies and procedures; compliance with regulations, guidelines, and accreditation requirements; employee health; direct intervention to prevent transmission of infectious diseases; education and training of healthcare workers; personnel resources; and nonpersonnel resources. The consensus panel used an evidence-based approach and categorized recommendations according to modifications of the scheme developed by the Clinical Affairs Committee of the Infectious Diseases Society of America and the Centers for Disease Control and Prevention's Hospital Infection Control Practices Advisory Committee.

Usefulness of intrinsic infection risk indexes as predictors of in-hospital death

OBJECTIVE

Comparison of two measures of intrinsic infection risk for predicting in-hospital mortality risks among subjects undergoing general surgery: the Study on the Efficacy of Nosocomial Infection Control (SENIC) index and the National Nosocomial Infection Surveillance (NNIS) index.

DESIGN

Prospective cohort study on 1483 patients admitted to the service of general surgery of a tertiary hospital. The main outcome measure was in-hospital death. Relative risks, crude and multiple-risk factor adjusted for by logistic regression analysis, and their 95% CIs were estimated.

RESULTS

During follow-up, 33 patients (2.2%) died. Both the SENIC and the NNIS indexes appeared related to in-hospital mortality risk in crude data. After several confounders (age, sex, severity of illness, American Society of Anesthesiologists score, serum creatinine, serum albumin, stay at the intensive care unit, length of operation, type of surgical wound, and preoperative stay) were controlled for, the SENIC index showed a borderline significant trend with mortality (p = 0.052), whereas the trend was significant for the NNIS index (p = 0.026). The NNIS index also showed a linear trend with both crude and adjusted for (SENIC index) risk of death. The SENIC index did not exhibit any linear trend with adjusted for (NNIS index) risk of surgical wound infection. To delineate whether the SENIC index added explanatory information to the NNIS index (or vice versa), we regressed the SENIC index on the NNIS index (and vice versa) and computed a set of residuals for both indexes. In logistic regression analyses, the residuals of NNIS index added meaningful information to the SENIC index, whereas the residuals of the SENIC index did not add any relevant information to the NNIS index. These results remained unchanged after controlling for several confounders.

CONCLUSIONS

Both the SENIC and the NNIS indexes are good predictors of in-hospital mortality risk. The NNIS index had greater capability for discriminating and predicting risk of dealth.