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Introduction: With widespread adoption of enhanced recovery protocols and a push toward shorter length of stay (LOS) following colon surgery, the extent to which complications have shifted to the post-discharge setting is unknown. The objectives of this study were to (1) characterize changes in LOS and post-discharge complications over time and (2) evaluate risk factors associated with post-discharge complications.Methods: Patients who underwent elective colon resection from 2012 to 2018 were identified from the ACS NSQIP Colectomy-Targeted Dataset. Changes in LOS and the proportion of post-discharge complications were evaluated over time, and predictors of post-discharge complications were assessed using multivariable logistic regression.Results: Of the 98,136 patients who underwent colon resection, median LOS decreased from 5 days in 2012 to 4 days in 2018. Overall, 30-day complication rate was 21.5%, which decreased during the study period (25.8 to 19.1%, p < 0.001). Of the 13 individual complications evaluated, 4 demonstrated a significant increase in the proportion of post-discharge events including overall SSI (55.8 to 63.3%, p = 0.002), superficial SSI (57.3 to 75.7%, p < 0.001), wound disruption (46.0 to 62.1%, p = 0.047), and UTI (41.5 to 62.7%, p < 0.001). Factors associated with the development of any post-discharge complication included female sex, ASA III/IV/V, dependent functional status, and higher BMI. Intraoperative factors included wound class, operation time, and approach.Conclusions: Although LOS and 30-day complications decreased over time, the proportion of events occurring post-discharge increased for several complications. We identified specific factors associated with post-discharge complications which emphasize the importance of a patient monitoring program to early identify and manage post-discharge complications. [ABSTRACT FROM AUTHOR]

We develop a class of new multivariate procedures for monitoring quality by detecting a change in the level of a multivariate process. Following the ideas of S.N. Roy, we first consider a linear combination statistic which results from projecting the multivariate observations onto a unit vector and then maximizing a selected univariate statistic over all directions. An application to a sheet metal assembly process is discussed in Section 3. Comparisons are made between one of our new procedures and other major multivariate quality monitoring schemes in Section 4. A small simulation study compares the average run lengths of the different procedures both when the process is in-control and after a shift has occurred. Some large sample properties are discussed in Section 5 and some computational details in Section 6. [Copyright &y& Elsevier]