Post-discharge surveillance (PDS) for surgical site infections: a good method is more important than a long duration.

Post-discharge surveillance (PDS) for surgical site infections (SSIs) normally lasts 30 days, or one year after implant surgery, causing delayed feedback to healthcare professionals. We investigated the effect of shortened PDS durations on SSI incidence to determine whether shorter PDS durations are justified. We also studied the impact of two national PDS methods (those mandatory since 2009 ('mandatory') and other methods acceptable before 2009 ('other')) on SSI incidence. From Dutch surveillance (PREZIES) data (1999-2008), four implant-free surgeries (breast amputation, Caesarean section, laparoscopic cholecystectomy and colectomy) and two implant surgeries (knee replacement and total hip replacement) were selected. We studied the impact of PDS duration and method on SSI incidences by survival and Cox regression analyses. We included 105,607 operations. Shortened PDS duration for implant surgery from one year to 90 days resulted in 6­14% of all SSIs being missed. For implant-free procedures, PDS reduction from 30 to 21 days caused similar levels of missed SSIs. In contrast, up to 62% of SSIs (for cholecystectomy) were missed if other instead of mandatory PDS methods were used. Inferior methods of PDS, rather than shortened PDS durations, may lead to greater underestimation of SSI incidence. Our data validate international recommendations to limit the maximum PDS duration (for implant surgeries) to 90 days for surveillance purposes, as this provides robust insight into trends.

MRSA carriage in healthcare personnel in contact with farm animals.

In The Netherlands it has been shown that people in contact with pigs have a higher risk of meticillin-resistant Staphylococcus aureus (MRSA) carriage than the general population. Isolates of closely related spa types, corresponding to multilocus sequence type (MLST) ST398, were found in pig farmers, pig veterinarians and pigs. The objective of this study was to investigate whether contact with pigs and veal calves or other livestock is a risk factor for MRSA carriage in Dutch healthcare workers (HCWs). HCWs at four general hospitals and one university hospital were asked to fill in questionnaires covering contact with animals and to take MRSA cultures of their throat and nares. Cultures of HCWs in contact with livestock were processed with samples from HCWs with no contact with livestock as controls. Seventy-seven of 1721 HCWs (4.4%) reported direct or indirect contact with pigs and/or veal calves and 145 reported contact with other livestock animals. The MRSA carriage rate in the group in contact with pigs and veal calves was 1.7% and in the control group was 0.15%. No carriers were found among HCWs in contact with other livestock. An estimated 3% of hospital staff working in Dutch hospitals serving rural populations belong to a high risk group for MRSA carriage according to the Dutch guidelines. Although MRSA carriage in HCWs in contact with livestock is 10-fold higher than in other HCWs, the difference is not statistically significant.

A data mart for operations analysis.

In this article we describe the evolution and architecture of a data mart developed to address the modeling and analysis needs of healthcare operations analysts. More specifically, the data mart is used in projects relating to demand analysis, forecasting, capacity planning, and service system design for a healthcare system consisting of a large tertiary care hospital and a smaller community hospital. The primary focus of the mart is on the detailed movement of inpatients through each hospital, although most component data tables include outpatient information such as emergency center visits, surgical cases, cardiac catheterization cases, and short-stay visits. We show that the data mart goes well beyond consolidating data from different sources by including a number of complex, precalculated fields, data structures, and function libraries that are specific to the needs of operations analysts. We discuss several outstanding and challenging design issues that should be of interest to the data warehouse vendor community.

Tactical staff scheduling analysis for hospital ancillary units.

Hospital ancillary units face difficult staffing problems due to demand variability by time of day and day of week. For such problems, tour scheduling models play an important role in minimizing labor cost while meeting the staffing needs and personnel scheduling constraints of the unit. We describe an approach called tactical scheduling analysis for addressing such problems. The components of such an analysis are detailed and several actual scheduling analysis projects are presented in order to give a sense of the different types of problems faced by ancillary units and how we as engineers try to solve these problems.

Patient-scheduling methodologies.

Inpatient admissions, surgical scheduling, and outpatient scheduling are three of the most important patient-scheduling functions in the hospital. In this paper, the key elements of state-of-the-art scheduling systems are discussed, along with a rationale for their importance. Our purpose is to show how well-designed patient-scheduling systems can contribute to the improvement of hospital operations.

A heuristic approach to nurse scheduling in hospital units with non-stationary, urgent demand, and a fixed staff size.

We present a practical approach to personnel scheduling problems arising in hospital units with demand that is of an urgent nature, cannot be backlogged, and is highly dependent on the time of day. A simple rounding heuristic is combined with a simulated annealing algorithm to obtain near-optimal solutions to large linear integer programming models of these personnel scheduling problems in a reasonable amount of time on a personal computer. The models are designed to complement the current state-of-the-art of commercially available hospital staff scheduling systems.