Kurt E. Schnier

Risk Factors for 30-Day Hospital Readmission among General Surgery Patients

BACKGROUND Hospital readmission within 30 days of an index hospitalization is receiving increased scrutiny as a marker of poor-quality patient care. This study identifies factors associated with 30-day readmission after general surgery procedures. STUDY DESIGN Using standard National Surgical Quality Improvement Project protocol, preoperative, intraoperative, and postoperative outcomes were collected on patients undergoing inpatient general surgery procedures at a single academic center between 2009 and 2011. Data were merged with our institutional clinical data warehouse to identify unplanned 30-day readmissions. Demographics, comorbidities, type of procedure, postoperative complications, and ICD-9 coding data were reviewed for patients who were readmitted. Univariate and multivariate analysis was used to identify risk factors associated with 30-day readmission. RESULTS One thousand four hundred and forty-two general surgery patients were reviewed. One hundred and sixty-three (11.3%) were readmitted within 30 days of discharge. The most common reasons for readmission were gastrointestinal problem/complication (27.6%), surgical infection (22.1%), and failure to thrive/malnutrition (10.4%). Comorbidities associated with risk of readmission included disseminated cancer, dyspnea, and preoperative open wound (p < 0.05 for all variables). Surgical procedures associated with higher rates of readmission included pancreatectomy, colectomy, and liver resection. Postoperative occurrences leading to increased risk of readmission were blood transfusion, postoperative pulmonary complication, wound complication, sepsis/shock, urinary tract infection, and vascular complications. Multivariable analysis demonstrates that the most significant independent risk factor for readmission is the occurrence of any postoperative complication (odds ratio = 4.20; 95% CI, 2.89-6.13). CONCLUSIONS Risk factors for readmission after general surgery procedures are multifactorial, however, postoperative complications appear to drive readmissions in surgical patients. Taking appropriate steps to minimize postoperative complications will decrease postoperative readmissions.

The Fishery Performance Indicators: A Management Tool for Triple Bottom Line Outcomes

Pursuit of the triple bottom line of economic, community and ecological sustainability has increased the complexity of fishery management; fisheries assessments require new types of data and analysis to guide science-based policy in addition to traditional biological information and modeling. We introduce the Fishery Performance Indicators (FPIs), a broadly applicable and flexible tool for assessing performance in individual fisheries, and for establishing cross-sectional links between enabling conditions, management strategies and triple bottom line outcomes. Conceptually separating measures of performance, the FPIs use 68 individual outcome metrics—coded on a 1 to 5 scale based on expert assessment to facilitate application to data poor fisheries and sectors—that can be partitioned into sector-based or triple-bottom-line sustainability-based interpretative indicators. Variation among outcomes is explained with 54 similarly structured metrics of inputs, management approaches and enabling conditions. Using 61 initial fishery case studies drawn from industrial and developing countries around the world, we demonstrate the inferential importance of tracking economic and community outcomes, in addition to resource status.

Protecting Marine Biodiversity: A Comparison of Individual Habitat Quotas (IHQs) and Marine Protected Areas

Fisheries managers in the United States are required to identify and mitigate the adverse impacts of fishing activity on essential fish habitat (EFH). There are additional concerns that the viability of noncommercial species, animals that are habitat dependent and/or are themselves constituents of fishery habitat may still be threatened. We consider a cap-and-trade system for habitat conservation, individual habitat quotas for fisheries, to achieve habitat conservation and species protection goals cost effectively. Individual quotas of habitat impact units (HIUs) would be distributed to fishers with an aggregate quota set to maintain a target habitat “stock” of EFH conservation. Using a dynamic, spatially explicit fishery simulation model we explore the efficiency and cost effectiveness of an IHQ policy versus alternative marine protected area (MPA) configurations, at reducing the risk of extinguishing a habitat dependent species of unknown spatial distribution. Our findings indicate that an IHQ policy with a conservatively established habitat target is better suited to the protection of non-target species than a rotating or fixed MPA policy.

Dynamic Random Utility Modeling: A Monte Carlo Analysis

Applied studies of commercial fishing have largely ignored the intertemporal aspects of repeated site choices. For many fisheries, fishermen might choose a dynamically optimal cruise trajectory rather than myopic day-to-day strategies and a model that ignores these considerations will likely lead to biased parameter estimates and poor policy guidance. A dynamic random utility model is developed that utilizes the same information as static site-choice models but is entrenched in the principles of dynamic optimization. Using Monte Carlo analysis, we evaluate the performance of this estimator as compared to the static model for a variety of simulated fishery types.

Increasing organ donation via changes in the default choice or allocation rule

This research utilizes a laboratory experiment to evaluate the effectiveness of alternative public policies targeted at increasing the rate of deceased donor organ donation. The experiment includes treatments across different default choices and organ allocation rules inspired by the donor registration systems applied in different countries. Our results indicate that the opt-out with priority rule system generates the largest increase in organ donation relative to an opt-in only program. However, sizeable gains are achievable using either a priority rule or opt-out program separately, with the opt-out rule generating approximately 80% of the benefits achieved under a priority rule program.

Angler Heterogeneity and the Species-Specific Demand for Marine Recreational Fishing

Abstract In this study we assess the ability of the Marine Recreational Fishery Statistics Survey (MRFSS) to support single-species recreation demand models. We use the 2000 MRFSS southeast intercept data combined with the economic add-on. We determine that the MRFSS data will support only a few species-specific recreation demand models. Considering species of management interest in the Southeast, we focus on dolphinfish, king mackerel, red snapper, and red drum. We examine single-species recreational fishing behavior using random utility models of demand. We explore mixed logit (i.e., random parameter logit) and finite mixture (i.e., latent class logit) models for dealing with angler heterogeneity. We compare these to the commonly used conditional and nested logit models in terms of the value of catching (and keeping) one additional fish. Mixed logit models illustrate that the value of catch can be highly heterogeneous and, in some cases, can include both positive and negative values. The finite mixture model generates value estimates that were sometimes strikingly different than conditional, nested, and mixed logit models. Preference heterogeneity is significant within the MRFSS data. We find evidence that single-species models outperform multiple-species models and recreational values differ. JEL Classification Codes: Q26, Q51

Optimizing the scale of markets for water quality trading

Applying market approaches to environmental regulations requires establishing a spatial scale for trading. Spatially large markets usually increase opportunities for abatement cost savings but increase the potential for pollution damages (hot spots), vice versa for spatially small markets. We develop a coupled hydrologic-economic modeling approach for application to point source emissions trading by a large number of sources and apply this approach to the wastewater treatment plants (WWTPs) within the watershed of the second largest estuary in the U.S. We consider two different administrative structures that govern the trade of emission permits: one-for-one trading (the number of permits required for each unit of emission is the same for every WWTP) and trading ratios (the number of permits required for each unit of emissions varies across WWTP). Results show that water quality regulators should allow trading to occur at the river basin scale as an appropriate first-step policy, as is being done in a limited number of cases via compliance associations. Larger spatial scales may be needed under conditions of increased abatement costs. The optimal scale of the market is generally the same regardless of whether one-for-one trading or trading ratios are employed.

Nonregulatory Approaches to the Environment: Coasean and Pigouvian Perspectives

This article introduces a symposium on decentralized approaches to environmental management. These approaches include voluntary contributions to public goods, bundling contributions with private goods, and bundling the use of the environment with private goods. The article compares and contrasts the Coasean property rights perspective on such arrangements with the Pigouvian perspective of public economic theory. It further evaluates the efficiency of such arrangements through the lens of the excludability and nonrivalry problems, which are common to both perspectives. We conclude that both perspectives provide important insights for a comparative analysis of nonregulatory and regulatory approaches.

Accounting for Spatial Heterogeneity and Autocorrelation in Spatial Discrete Choice Models: Implications for Behavioral Predictions

The random utility model (RUM) is commonly used in the land-use and fishery economics literature. This research investigates the affect that spatial heterogeneity and spatial autocorrelation have within the RUM framework using alternative specifications of the multinomial logit, multinomial probit, and spatial multinomial probit models. Using data on the spatial decisions of fishermen, the results illustrate that ignoring spatial heterogeneity in the unobservable portion of the RUM dramatically affects model performance and welfare estimates. Furthermore, accounting for spatial autocorrelation in addition to spatial heterogeneity increases the performance of the RUM. (JEL C35, Q22)

Individual Behavior and Bidding Heterogeneity in Sealed Bid Auctions Where the Number of Bidders is Unknown

This paper analyzes individual bidding data from a series of first price (FP) and second price (SP) sealed-bid auctions in which the number of bidders is unknown. In SP auctions we find a substantial amount of coincidence with theory. We observe systematic deviations from risk neutral bidding in FP auctions and show theoretically that these deviations are consistent with risk averse preferences. We find essentially no heterogeneity in bidding in SP auctions where risk preferences and the number of bidders do not affect the optimal bid, while in the FP auctions heterogeneity in bidding persists and increases with experience. We conclude that heterogeneity in bidding in FP auctions is consistent with heterogeneity in risk preferences, the attempt to count the number of bidders in the auction, and bidder specific noise. (JEL D44, C91)