Medical Specialty Referrals from a Student Health Service

Abstract

During a 10-week period, 51 referrals resulted from 3171 visits to the Student Health Service, a referral rate of 1.6%. Specialties receiving the most frequent referrals were orthopedics (31%), ophthalmology (16%), general surgery (10%), and gynecology (10%). Data from this study suggest that specialty referrals occur infrequently in the Student Health Service. It would appear that this low referral rate, along with a relatively small student population, would not justify provision of in-house specialty consultation in the Student Health Service.

“The Prognosis of Inflammatory Bowel Disease,” DAVID J. SALES AND JOSEPH B. KIRSNER. The complications of ulcerative colitis generally develop during the first two years of disease. The mortality is higher than expected and the highest likelihood of colectomy also occurs early in the disease. Mortality in Crohn's disease is greater than expected, especially in males. For both conditions, the overall mortality has decreased steadily, and currently is less than 5%. Ulcerative colitis is curable with proctocolectomy and lieostomy. In Crohn's disease, intestinal resection and reanastomosis is followed by recurrence in the majority of patients. The recurrence rate after proctocolectomy and lieostomy for Crohn's disease of the colon also is considerable, ranging from 20% to 35%. In ulcerative colitis, the more colon involved, the more frequent and more serious are the complications. In Crohn's disease, the anatomic pattern of disease tends to predict the type and extent of complications. Both ulcerative colitis and Crohn's disease appear to follow a more severe course in children and adolescents with “inflammatory bowel disease.” Patients with either ulcerative colitis or Crohn's disease are at increased risk for the later development of cancer. In ulcerative colitis, the excess risk is limited to colorectal cancer. Patients with Crohn's disease have increased cancer rates for both the small and large bowel. Finally, most patients with these diseases are able to maintain normal occupations and enjoy reasonably stable social and economic situations. The successful adaptation of patients with inflammatory bowel disease is influenced by a hopeful, optimistic personality and by an encouraging, supportive physician.     

Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain

We develop results for the use of Lasso and post‐Lasso methods to form first‐stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p. Our results apply even when p is much larger than the sample size, n. We show that the IV estimator based on using Lasso or post‐Lasso in the first stage is root‐n consistent and asymptotically normal when the first stage is approximately sparse, that is, when the conditional expectation of the endogenous variables given the instruments can be well‐approximated by a relatively small set of variables whose identities may be unknown. We also show that the estimator is semiparametrically efficient when the structural error is homoscedastic. Notably, our results allow for imperfect model selection, and do not rely upon the unrealistic “beta‐min” conditions that are widely used to establish validity of inference following model selection (see also Belloni, Chernozhukov, and Hansen (2011b)). In simulation experiments, the Lasso‐based IV estimator with a data‐driven penalty performs well compared to recently advocated many‐instrument robust procedures. In an empirical example dealing with the effect of judicial eminent domain decisions on economic outcomes, the Lasso‐based IV estimator outperforms an intuitive benchmark. Optimal instruments are conditional expectations. In developing the IV results, we establish a series of new results for Lasso and post‐Lasso estimators of nonparametric conditional expectation functions which are of independent theoretical and practical interest. We construct a modification of Lasso designed to deal with non‐Gaussian, heteroscedastic disturbances that uses a data‐weighted ℓ₁‐penalty function. By innovatively using moderate deviation theory for self‐normalized sums, we provide convergence rates for the resulting Lasso and post‐Lasso estimators that are as sharp as the corresponding rates in the homoscedastic Gaussian case under the condition that logp = o(n^1/3). We also provide a data‐driven method for choosing the penalty level that must be specified in obtaining Lasso and post‐Lasso estimates and establish its asymptotic validity under non‐Gaussian, heteroscedastic disturbances.     

The forecasting performance of mortality models

Mortality projections are of special interest in many applications. For example, they are essential in life insurances to determine the annual contributions of their members as well as for population predictions. Due to their importance, there exists a huge variety of mortality forecasting models from which to seek the best approach. In the demographic literature, statements about the quality of the various models are mostly based on empirical ex-post examinations of mortality data for very few populations. On the basis of such a small number of observations, it is impossible to precisely estimate statistical forecasting measures. We use Monte Carlo (MC) methods here to generate time trajectories of mortality tables, which form a more comprehensive basis for estimating the root-mean-square error (RMSE) of different mortality forecasts.     

Long‐Term Risk: An Operator Approach

We create an analytical structure that reveals the long‐run risk‐return relationship for nonlinear continuous‐time Markov environments. We do so by studying an eigenvalue problem associated with a positive eigenfunction for a conveniently chosen family of valuation operators. The members of this family are indexed by the elapsed time between payoff and valuation dates, and they are necessarily related via a mathematical structure called a semigroup. We represent the semigroup using a positive process with three components: an exponential term constructed from the eigenvalue, a martingale, and a transient eigenfunction term. The eigenvalue encodes the risk adjustment, the martingale alters the probability measure to capture long‐run approximation, and the eigenfunction gives the long‐run dependence on the Markov state. We discuss sufficient conditions for the existence and uniqueness of the relevant eigenvalue and eigenfunction. By showing how changes in the stochastic growth components of cash flows induce changes in the corresponding eigenvalues and eigenfunctions, we reveal a long‐run risk‐return trade‐off.     

Coexisting principles and logics of elder care: Help to self‐help and consumer‐oriented service?

Healthy and active ageing has become an ideal in Western societies. In the Nordic countries, this ideal has been supported through a policy of help to self‐help in elder care since the 1980s. However, reforms inspired by New Public Management (NPM) have introduced a new policy principle of consumer‐oriented service that stresses the wishes and priorities of older people. We have studied how these two principles are applied by care workers in Denmark. Is one principle or logic replacing the other, or do they coexist? Do they create tensions between professional knowledge and the autonomy of older people? Using neo‐institutional theory and feminist care theory, we analysed the articulation of the two policy principles in interviews and their logics in observations in four local authorities. We conclude that help to self‐help is the dominant principle, that it is deeply entrenched in the identity of the professional care worker and that it coexists with consumer‐oriented service and without major tensions in the logics identified in their practices.     

Parenthood and Happiness: a Review of Folk Theories Versus Empirical Evidence

This paper reviews and compares folk theories and empirical evidence about the influence of parenthood on happiness and life satisfaction. The review of attitudes toward parenthood and childlessness reveals that people tend to believe that parenthood is central to a meaningful and fulfilling life, and that the lives of childless people are emptier, less rewarding, and lonelier, than the lives of parents. Most cross-sectional and longitudinal evidence suggest, however, that people are better off without having children. It is mainly children living at home that interfere with well-being, particularly among women, singles, lower socioeconomic strata, and people residing in less pronatalist societies??especially when these characteristics are combined. The discrepancy between beliefs and findings is discussed in relation to the various costs of parenting; the advantages of childlessness; adaptation and compensation among involuntarily childless persons; cognitive biases; and the possibility that parenthood confers rewards in terms of meaning rather than happiness.     

Can higher life expectancy induce more schooling and earlier retirement?

In this paper, we show that it may be optimal for individuals to educate more and retire earlier when life expectancy increases. This result reconciles the findings of Hazan (Econometrica 77:1829–1863, 2009) with theory. Further, the paper contributes to a better understanding of the conflicting empirical findings on the causal effect on income per capita from increased life expectancy.     

Historical Sociology and the Prism of Biography: Lillian Wineman and the Trade in Dakota Beadwork, 1893–1929

Qualitative Sociology - How can researchers learn about the social lives of people and cultures who leave little or no written record of their lives? This article introduces the idea that one...     

Threshold Autoregression with a Unit Root

This paper develops an asymptotic theory of inference for an unrestricted two‐regime threshold autoregressive (TAR) model with an autoregressive unit root. We find that the asymptotic null distribution of Wald tests for a threshold are nonstandard and different from the stationary case, and suggest basing inference on a bootstrap approximation. We also study the asymptotic null distributions of tests for an autoregressive unit root, and find that they are nonstandard and dependent on the presence of a threshold effect. We propose both asymptotic and bootstrap‐based tests. These tests and distribution theory allow for the joint consideration of nonlinearity (thresholds) and nonstationary (unit roots). Our limit theory is based on a new set of tools that combine unit root asymptotics with empirical process methods. We work with a particular two‐parameter empirical process that converges weakly to a two‐parameter Brownian motion. Our limit distributions involve stochastic integrals with respect to this two‐parameter process. This theory is entirely new and may find applications in other contexts. We illustrate the methods with an application to the U.S. monthly unemployment rate. We find strong evidence of a threshold effect. The point estimates suggest that the threshold effect is in the short‐run dynamics, rather than in the dominate root. While the conventional ADF test for a unit root is insignificant, our TAR unit root tests are arguably significant. The evidence is quite strong that the unemployment rate is not a unit root process, and there is considerable evidence that the series is a stationary TAR process.     

Artificial Intelligence and Generalized Qualitative-Response Models: An Empirical Test on Two Audit Decision-Making Domains

Machine learning methods are currently the object of considerable study by the artificial intelligence community. Research on machine learning carries implications for decision making in that it seeks computational methods that mimic input-output behaviors found in classes of decision-making examples. At the same time, research in statistics and econometrics has resulted in the development of qualitative-response models that can be applied to the same kind of problems addressed by machine-learning models—particularly those that involve a classification decision. This paper presents the theoretical structure of a generalized qualitative-response model and compares its performance to two seminal machine-learning models in two problem domains associated with audit decision making. The results suggest that the generalized qualitative-response model may be a useful alternative for certain problem domains.