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BackgroundPatients often wait to have urgent or emergency surgery. The number of operating rooms (ORs) needed to minimize waiting time while optimizing resources can be determined using queuing theory and computer simulation. We developed a computer program using Monte Carlo simulation to determine the number of ORs needed to minimize patient wait times while optimizing resources.MethodsWe used patient arrival data and surgical procedure length from our institution, a tertiary-care academic medical center that serves a large diverse population. With ~4800 patients/year requiring non-elective surgery, and mean procedure length 185 min (median 150 min) we determined the number of ORs needed during the day and evening (0600-2200) and during the night (2200-0600) that resulted in acceptable wait times.ResultsSimulation of 4 ORs at day/evening and 3 ORs at night resulted in median wait time = 0 min (mean = 19 min) for emergency cases requiring surgery within 2 h, with wait time at the 95th percentile = 109 min. Median wait time for urgent cases needing surgery within 8-12 h was 34 min (mean = 136 min), with wait time at the 95th percentile = 474 min. The effect of changes in surgical length and volume on wait times was determined with sensitivity analysis.ConclusionsMonte Carlo simulation can guide decisions on how to balance resources for elective and non-elective surgical procedures.

BackgroundThis study used case reports to review the role of systemic chemotherapy in oligometastatic colorectal cancer (CRC) and to suggest ways to integrate clinical research findings into the interdisciplinary management of this potentially curable subset of patients.MethodsThis educational review discusses the role of chemotherapy in the management of oligometastatic metastatic CRC.ResultsIn initially resectable oligometastatic CRC, the goal of chemotherapy is to eradicate micrometastatic disease. Perioperative 5-fluorouracil and oxaliplatin together with surgical resection can result in 5-year survival rates as high as 57 %. With the development of increasingly successful chemotherapy regimens, attention is being paid to chemotherapy used to convert patients with initially unresectable metastasis to patients with a chance of surgical cure. The choice of chemotherapy regimen requires consideration of the goals for therapy and assessment of both tumor- and patient-specific factors.ConclusionThis report discusses the choice and timing of chemotherapy in patients with initially resectable and borderline resectable metastatic CRC. Coordinated multidisciplinary care of such patients can optimize survival outcomes and result in cure for patients with this otherwise lethal disease.

BackgroundPatients often wait to have urgent or emergency surgery. The number of operating rooms (ORs) needed to minimize waiting time while optimizing resources can be determined using queuing theory and computer simulation. We developed a computer program using Monte Carlo simulation to determine the number of ORs needed to minimize patient wait times while optimizing resources.MethodsWe used patient arrival data and surgical procedure length from our institution, a tertiary-care academic medical center that serves a large diverse population. With ~4800 patients/year requiring non-elective surgery, and mean procedure length 185 min (median 150 min) we determined the number of ORs needed during the day and evening (0600-2200) and during the night (2200-0600) that resulted in acceptable wait times.ResultsSimulation of 4 ORs at day/evening and 3 ORs at night resulted in median wait time = 0 min (mean = 19 min) for emergency cases requiring surgery within 2 h, with wait time at the 95th percentile = 109 min. Median wait time for urgent cases needing surgery within 8-12 h was 34 min (mean = 136 min), with wait time at the 95th percentile = 474 min. The effect of changes in surgical length and volume on wait times was determined with sensitivity analysis.ConclusionsMonte Carlo simulation can guide decisions on how to balance resources for elective and non-elective surgical procedures.

BackgroundThis study used case reports to review the role of systemic chemotherapy in oligometastatic colorectal cancer (CRC) and to suggest ways to integrate clinical research findings into the interdisciplinary management of this potentially curable subset of patients.MethodsThis educational review discusses the role of chemotherapy in the management of oligometastatic metastatic CRC.ResultsIn initially resectable oligometastatic CRC, the goal of chemotherapy is to eradicate micrometastatic disease. Perioperative 5-fluorouracil and oxaliplatin together with surgical resection can result in 5-year survival rates as high as 57 %. With the development of increasingly successful chemotherapy regimens, attention is being paid to chemotherapy used to convert patients with initially unresectable metastasis to patients with a chance of surgical cure. The choice of chemotherapy regimen requires consideration of the goals for therapy and assessment of both tumor- and patient-specific factors.ConclusionThis report discusses the choice and timing of chemotherapy in patients with initially resectable and borderline resectable metastatic CRC. Coordinated multidisciplinary care of such patients can optimize survival outcomes and result in cure for patients with this otherwise lethal disease.

BackgroundThe relationship between procedural relative value units (RVUs) for surgical procedures and other measures of surgeon effort are poorly characterized. We hypothesized that RVUs would poorly correlate with quantifiable metrics of surgeon effort.MethodsUsing the 2010 American College of Surgeons - National Surgical Quality Improvement Program (NSQIP) database, we selected 11 primary current procedural terminology codes associated with high volume surgical procedures. We then identified all patients with a single reported procedural RVU who underwent nonemergent, inpatient general surgical operations. We used linear regression to correlate length of stay (LOS), operative time, overall morbidity, frequency of serious adverse events (SAEs), and mortality with RVUs. We used multivariable logistic regression using all preoperative NSQIP variables to determine other significant predictors of our outcome measures.ResultsAmong 14,481 patients, RVUs poorly correlated with individual LOS (R(2) = 0.05), operative time (R(2) = 0.10), and mortality (R(2) = 0.35). There was a moderate correlation between RVUs and SAEs (R(2) = 0.79) and RVUs and overall morbidity (R(2) = 0.75). However, among low- to mid-level RVU procedures (11-35) there was a poor correlation between SAEs (R(2) = 0.15), overall morbidity (R(2) = 0.05), and RVUs. On multivariable analysis, RVUs were significant predictors of operative time, LOS, and SAEs (odds ratio 1.06, 95% confidence interval: 1.05-1.07), but RVUs were not a significant predictor of mortality (odds ratio 1.02, 95% confidence interval: 0.99-1.05).ConclusionsFor common, index general surgery procedures, the current RVU assignments poorly correlate with certain metrics of surgeon work, while moderately correlating with others. Given the increasing emphasis on measuring and tracking surgeon productivity, more objective measures of surgeon work and productivity should be

This case report describes the radical subtotal palliative resection of a massive recurrent desmoid tumor encompassing the abdomen, pelvis, and groin in a child who was 13 years old at the time of initial resection. Given the extensive distribution of the tumor en bloc resection, which is the standard treatment of desmoid tumors, would have meant performing a hemipelvectomy and repair of a large abdominal wall defect, likely with skin grafts and mesh. The patient’s personal goals however were to alleviate the pain and limited mobility that would allow her to re-attend high school and appear normal to her peers. Therefore, palliative surgery was pursued and currently the patient is 5 years out from her last surgery doing well. We believe that the option of surgical palliation in this case was warranted and should be an option for similar cases in the future.

This case report describes the radical subtotal palliative resection of a massive recurrent desmoid tumor encompassing the abdomen, pelvis, and groin in a child who was 13 years old at the time of initial resection. Given the extensive distribution of the tumor en bloc resection, which is the standard treatment of desmoid tumors, would have meant performing a hemipelvectomy and repair of a large abdominal wall defect, likely with skin grafts and mesh. The patient’s personal goals however were to alleviate the pain and limited mobility that would allow her to re-attend high school and appear normal to her peers. Therefore, palliative surgery was pursued and currently the patient is 5 years out from her last surgery doing well. We believe that the option of surgical palliation in this case was warranted and should be an option for similar cases in the future.

Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both "what" and "when/where," need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on "what" is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.

The objective of this research is to formally define a spatio-temporal conceptual model that captures data semantics required for temporal and geospatial applications. We show how the proposed model provides a metaphor that bridges the semantic gap between the real world and its spatio-temporal representation in information systems. Our multi-methodological research approach includes: (i) formally defining a spatio-temporal semantic model called ST USM (Spatio-Temporal Unifying Semantic Model); (ii) evaluating the proposed model using a case study and a laboratory study; and (iii) demonstrating practicality of our proposed model using a proof-of-concept prototype system. We describe a spatio-temporal conceptual modeling approach--applicable to any conventional conceptual model--that incorporates sequenced and nonsequenced space/time semantics. We have applied our annotation-based approach to the Unifying Semantic Model (USM)--a conventional conceptual model--to propose ST USM. ST USM is an upward-compatible, snapshot reducible, annotation-based spatio-temporal conceptual model that can comprehensively capture semantics related to space and time without adding any new spatio-temporal constructs. We provide formal semantics of ST USM via a mapping to conventional USM and constraints (expressed in first-order logic), from which the logical schema can be derived. To evaluate the proposed model, we conducted a case study at the US Geological Survey that helped us assess the extent to which the proposed formalism helps capture all the spatio-temporal data semantics for an application. We show that ST USM is ontologically expressive and leads to schemas that completely capture the requisite spatio-temporal semantics. We conducted a laboratory study and found that an annotation-based approach to capturing the spatio-temporal semantics does not adversely impact the schema comprehension as compared with conventional conceptual models (e.g., USM). This implies that annotations