Disease-based modeling to predict fluid response in intensive care units.

OBJECTIVE: To compare general and disease-based modeling for fluid resuscitation and vasopressor use in intensive care units. METHODS: Retrospective cohort study involving 2944 adult medical and surgical intensive care unit (ICU) patients receiving fluid resuscitation. Within this cohort there were two disease-based groups, 802 patients with a diagnosis of pneumonia, and 143 patients with a diagnosis of pancreatitis. Fluid resuscitation either progressing to subsequent vasopressor administration or not was used as the primary outcome variable to compare general and disease-based modeling. RESULTS: Patients with pancreatitis, pneumonia and the general group all shared three common predictive features as core variables, arterial base excess, lactic acid and platelets. Patients with pneumonia also had non-invasive systolic blood pressure and white blood cells added to the core model, and pancreatitis patients additionally had temperature. Disease-based models had significantly higher values of AUC (p < 0.05) than the general group (0.82 ± 0.02 for pneumonia and 0.83 ± 0.03 for pancreatitis vs. 0.79 ± 0.02 for general patients). CONCLUSIONS: Disease-based predictive modeling reveals a different set of predictive variables compared to general modeling and improved performance. Our findings add support to the growing body of evidence advantaging disease specific predictive modeling.

Reducing unnecessary lab testing in the ICU with artificial intelligence.

OBJECTIVES: To reduce unnecessary lab testing by predicting when a proposed future lab test is likely to contribute information gain and thereby influence clinical management in patients with gastrointestinal bleeding. Recent studies have demonstrated that frequent laboratory testing does not necessarily relate to better outcomes. DESIGN: Data preprocessing, feature selection, and classification were performed and an artificial intelligence tool, fuzzy modeling, was used to identify lab tests that do not contribute an information gain. There were 11 input variables in total. Ten of these were derived from bedside monitor trends heart rate, oxygen saturation, respiratory rate, temperature, blood pressure, and urine collections, as well as infusion products and transfusions. The final input variable was a previous value from one of the eight lab tests being predicted: calcium, PTT, hematocrit, fibrinogen, lactate, platelets, INR and hemoglobin. The outcome for each test was a binary framework defining whether a test result contributed information gain or not. PATIENTS: Predictive modeling was applied to recognize unnecessary lab tests in a real world ICU database extract comprising 746 patients with gastrointestinal bleeding. MAIN RESULTS: Classification accuracy of necessary and unnecessary lab tests of greater than 80% was achieved for all eight lab tests. Sensitivity and specificity were satisfactory for all the outcomes. An average reduction of 50% of the lab tests was obtained. This is an improvement from previously reported similar studies with average performance 37% by [1-3]. CONCLUSIONS: Reducing frequent lab testing and the potential clinical and financial implications are an important issue in intensive care. In this work we present an artificial intelligence method to predict the benefit of proposed future laboratory tests. Using ICU data from 746 patients with gastrointestinal bleeding, and eleven measurements, we demonstrate high accuracy in predicting the likely information to be gained from proposed future lab testing for eight common GI related lab tests. Future work will explore applications of this approach to a range of underlying medical conditions and laboratory tests.

Performance decrements resulting from illness in the workplace: the effect of headaches.

OBJECTIVES: Studies on the impact of illness on work productivity are important to rationally allocate healthcare resources and to design programs to mitigate these effects. This investigation was conducted to develop and apply daily measures of illness episodes, and to collect subjective and objective data on work performance impacts. Medical bill reviewers completed daily responses to a questionnaire about headache manifestations, severity, and speed of work using interactive voice response (IVR). Of 134 eligible enrolled subjects, 117 (86%) provided at least 30 daily reports over 3 months. Their responses were matched to difficulty-adjusted objective measures: daily output, time on the system, and productivity. Respondents were clinically classified as migraineurs (n = 56), other headache disorders (n = 47), or having no headache disorder (n = 14). Each headache episode was classified as a migraine or nonmigraine headache based on reported manifestations. RESULTS: The three groups were similar in a variety of demographic factors, and mean subject-specific measures of speed, output, and productivity. In a multivariate model using general estimating equations, only episode severity (not type of headache or person-specific diagnosis) was found to be associated with a significant decrement in speed or productivity. The self-reported decrement in speed (approximately 20%) was much greater than the actual measured effect on productivity (approximately 8%). Intensive daily diary collection by IVR on symptoms and work performance is feasible. However, analysis of detailed daily objective productivity data can be complex, with significant unmeasured sources of variance. Severity may be a more important determinant of headache effect on work performance than specific diagnosis. Future studies on illness episodes and work performance should measure informal accommodations that may enable employees to compensate for episodic illnesses.

Healthcare expenditure in patients treated with venlafaxine or selective serotonin reuptake inhibitors for depression and anxiety.

We compared healthcare expenditure over a six-month period following initiation of therapy with either venlafaxine (immediate and extended-release) or a selective serotonin reuptake inhibitor (SSRI) in depressed patients with or without anxiety. Patients beginning treatment for a new depressive episode were identified retrospectively using the administrative data of the MEDSTAT MarketScan database for the period 1994-1999. Before beginning therapy, patients prescribed venlafaxine had more non-mental illnesses (0.85 vs 0.76; p<0.01) and hospitalisations for mental illness (0.53 vs 0.29; p<0.05) than patients prescribed SSRIs. In the six months after initiating treatment, venlafaxine was associated with lower hospitalisation expenditure for non-mental illness ($177 vs $526; p<0.01) than SSRIs, although total healthcare expenditure was not significantly different. Venlafaxine was associated with a 50% decrease in the odds of hospitalisation for non-mental illness compared with SSRIs, with significantly lower inpatient expenditure.

Health care use and at-work productivity among employees with mental disorders.

This study examines the differential medical care use and work productivity of employees with and without anxiety and with other mental disorders at a large national firm. A unique aspect of this study is that we integrate medical claims and employer-provided, objective productivity data for the same employees. We find extensive mental health comorbidities among anxious employees. Although medical care use differs considerably among employees having no, one, or several treated mental disorders, in most cases their annual average absenteeism and average at-work productivity performance do not differ. Differences among subgroups are observed for job tenure and maternity claims. We discuss these long-term average productivity findings in relation to other literature encompassing shorter time periods.

Lost human capital from early-onset chronic depression.

OBJECTIVE: Chronic depression starts at an early age for many individuals and could affect their accumulation of "human capital" (i.e., education, higher amounts of which can broaden occupational choice and increase earnings potential). The authors examined the impact, by gender, of early- (before age 22) versus late-onset major depressive disorder on educational attainment. They also determined whether the efficacy and sustainability of antidepressant treatments and psychosocial outcomes vary by age at onset and quantified the impact of early- versus late-onset, as well as never-occurring, major depressive disorder on expected lifetime earnings. METHOD: The authors used logistic and multivariate regression methods to analyze data from a three-phase, multicenter, double-blind, randomized trial that compared sertraline and imipramine treatment of 531 patients with chronic depression aged 30 years and older. These data were integrated with U.S. Census Bureau data on 1995 earnings by age, educational attainment, and gender. RESULTS: Early-onset major depressive disorder adversely affected the educational attainment of women but not of men. No significant difference in treatment responsiveness by age at onset was observed after 12 weeks of acute treatment or, for subjects rated as having responded, after 76 weeks of maintenance treatment. A randomly selected 21-year-old woman with early-onset major depressive disorder in 1995 could expect future annual earnings that were 12%-18% lower than those of a randomly selected 21-year-old woman whose onset of major depressive disorder occurred after age 21 or not at all. CONCLUSIONS: Early-onset major depressive disorder causes substantial human capital loss, particularly for women. Detection and effective treatment of early-onset major depressive disorder may have substantial economic benefits.

Loss of work productivity due to illness and medical treatment.

We examined the effects on work productivity of treatment with antihistamines in a retrospective study using linked health claims data and daily work output records for a sample of nearly 6000 claims processors at a large insurance company, between 1993 and 1995. We explained the variation in work output depending on the subjects' demographic characteristics, their jobs, and whether they were treated with "sedating" versus "nonsedating" antihistamines for nasal allergies. Differences of up to 13% in productivity were found after the subjects took sedating or nonsedating antihistamines. The observed effect suggests substantial indirect economic costs, which up to now have been largely overlooked because work productivity has proved difficult to measure objectively.

The economic burden of anxiety disorders in the 1990s.

BACKGROUND: We assess the annual economic burden of anxiety disorders in the United States from a societal perspective. METHOD: Using data from the National Comorbidity Study, we applied multivariate regression techniques to calculate the costs associated with anxiety disorders, after adjusting for demographic characteristics and the presence of comorbid psychiatric conditions. Based on additional data, in part from a large managed care organization, we estimated a human capital model of the societal cost of anxiety disorders. RESULTS: We estimated the annual cost of anxiety disorders to be approximately $42.3 billion in 1990 in the United States, or $1542 per sufferer. This comprises $23.0 billion (or 54% of the total cost) in nonpsychiatric medical treatment costs, S13.3 billion (31%) in psychiatric treatment costs, $4.1 billion (10%) in indirect workplace costs, $1.2 billion (3%) in mortality costs, and $0.8 billion (2%) in prescription pharmaceutical costs. Of the $256 in workplace costs per anxious worker, 88% is attributable to lost productivity while at work as opposed to absenteeism. Posttraumatic stress disorder and panic disorder are the anxiety disorders found to have the highest rates of service use. Other than simple phobia, all anxiety disorders analyzed are associated with impairment in workplace performance. CONCLUSION: Anxiety disorders impose a substantial cost on society, much of which may be avoidable with more widespread awareness, recognition, and appropriate early intervention.

Cost effectiveness, quality-adjusted life-years and supportive care. Recombinant human erythropoietin as a treatment of cancer-associated anaemia.

OBJECTIVE: To measure the cost effectiveness of a supportive care intervention when the no-treatment option is unrealistic in an analysis of recombinant human erythropoietin (epoetin) treatment for anaemic patients with cancer undergoing chemotherapy. Further, to assess whether quality-adjusted life-years (QALYs) can provide the basis for an appropriate measure of the value of supportive care interventions. DESIGN: A modelling study drawing cost and effectiveness assumptions from a literature review and from 3 US clinical trials involving more than 4500 patients with cancer who were treated with chemotherapy, radiotherapy, epoetin and blood transfusions as needed under standard care for patients with cancer. MAIN OUTCOME MEASURES AND RESULTS: When compared with transfusions, epoetin is cost effective under varying assumptions, whether effectiveness is measured by haemoglobin level or quality of life. Specifically, under a base-case scenario, the effectiveness resulting from $US1 spent on standard care can be achieved with only $US0.81 of epoetin care. Due in part to the health-state dependence of the significance patients attach to incremental changes in their responses on the linear analogue scale, cost per QALY results are ambiguous in this supportive care context. CONCLUSIONS: Under a broad range of plausible assumptions, epoetin can be used cost effectively in the treatment of anaemic patients with cancer. Further, QALYs have limited applicability here because, as a short term supportive treatment, epoetin enhances the quality but not the length of life. Future research would benefit from the establishment of consistent values for quality-of-life changes across patients and health status, and the extension of the QALY framework to supportive care.

Workplace performance effects from chronic depression and its treatment.

Utilizing data from a clinical trial and an econometric model incorporating the impact of a medical intervention and regression to the mean, we present evidence supporting the hypotheses that for chronically depressed individuals: (i) the level of perceived at-work performance is negatively related to the severity of depressive status; and (ii) a reduction in depressive severity improves the patient's perceived work performance. Improvement in work performance is rapid, with about two-thirds of the change occurring already by week 4. Those patients having the greatest work improvement are those with both relatively low baseline work performance and the least severity of baseline depression.

Improvement in subjective work performance after treatment of chronic depression: some preliminary results. Chronic Depression Study Group.

We analyzed the relationship between depression and patient-assessed or clinician-rated work performance among chronically depressed patients followed for 12 weeks in a large clinical trial. The data were collected in a double-blind design comparing sertraline, a selective serotonin reuptake inhibitor, with imipramine, a tricyclic antidepressant, in 12 academic centers nationwide. Incorporating work-related questions from a portfolio of rating scales used to assess depression, we constructed several measures of work performance, assessed at baseline and at Week 12 of the clinical investigation, and examined how they changed with improvement in depressive symptoms. As depressive symptoms subsided following treatment, patients reported substantial improvement in our measures of work performance. Eighty-six percent of the cohort reported some improvement from base-line to Week 12. The extent of improvement in work performance correlates highly with improvement in the depressive symptoms measured on the Hamilton Rating Scale for Depression. Treatment of depression with antidepressant medications resulted in substantial improvement in subjective work performance among the patients studied.

The economic burden of depression in 1990.

BACKGROUND: We estimate in dollar terms the economic burden of depression in the United States on an annual basis. METHOD: Using a human capital approach, we develop prevalence-based estimates of three major cost-of-illness categories: (1) direct costs of medical, psychiatric, and pharmacologic care; (2) mortality costs arising from depression-related suicides; and (3) morbidity costs associated with depression in the workplace. With respect to the latter category, we extend traditional cost-of-illness research to include not only the costs arising from excess absenteeism of depressed workers, but also the reductions in their productive capacity while at work during episodes of the illness. RESULTS: We estimate that the annual costs of depression in the United States total approximately $43.7 billion. Of this total, $12.4 billion-28%-is attributable to direct costs, $7.5 billion-17%-comprises mortality costs, and $23.8 billion-55%-is derived from the two morbidity cost categories. CONCLUSION: Depression imposes significant annual costs on society. Because there are many important categories of cost that have yet to be estimated, the true burden of this illness may be even greater than is implied by our estimate. Future research on the total costs of depression may include attention to the comorbidity costs of this illness with a variety of other diseases, reductions in the quality of life experienced by sufferers, and added out-of-pocket costs resulting from the effects of this illness, including those related to household services. Finally, it may be useful to estimate the additional costs associated with expanding the definition of depression to include individuals who suffer from only some of the symptoms of this illness.

Depression: a neglected major illness.

BACKGROUND: To illustrate the burden depression imposes on society, we present estimates of the annual costs of depression--$44 billion--as well as the number of individuals it affects per year--almost 11 million. Although these estimates point to depression as a major illness, this study examines why it is not generally considered as such by the medical and public health communities or by society at large. METHOD: We develop a framework that compares depression with major illnesses such as coronary heart disease, cancer, and AIDS by highlighting salient characteristics of each illness. This comparative illness framework considers the costs, prevalence, distribution of sufferers, mortality, recognition, and treatability of each disease. This comparison underscores many of the similarities and differences among the illnesses examined. RESULTS: Because depression often is not properly recognized and begins to affect many people at a relatively early age, it exacts costs over a longer period of time and in a more subtle manner than other major illnesses. It also imposes a particularly heavy burden on employers in the form of higher workplace costs. CONCLUSION: We conclude that, because of the potential for successful treatment, increased attempts to reach untreated sufferers of depression appear to be warranted. Employers as a group have a particular incentive to invest in the recognition and treatment of this widespread problem, in order to reduce the substantial costs it imposes upon them each year.

Factors associated with clinical dental faculty research productivity.

The purpose of this study was to determine factors that are associated with increased individual research productivity among clinical faculty in 67 United States and Canadian schools of dentistry. Individual faculty research productivity was defined as the total number of articles in refereed journals and book chapters published during an academic career. The 328 respondents represented a response rate of 62.8 percent from a 25 percent stratified random sample of faculty who (1) had full-time appointments and held at least the D.M.D./D.D.S. or foreign equivalent, (2) taught in a clinical department of the dental schools, and (3) were not department chairpersons and did not hold administrative positions (assistant dean, associate dean, or dean) within the dental school. Respondents reported a mean of 9.9 years in full-time dental education, a mean of 10.8 publications, and a mean of 7.5 hours spent in research per week. Forward addition multiple regression analysis demonstrated that five predictor variables, from a total of 20 variables evaluated, accounted for 59.9 percent of the variance in individual faculty research productivity. These predictor variables were total dollar amount of past research funding, career age, training status, colleague utilization in conducting research, and conducting research from planned goals.

Assessing technology for rehabilitation. Three cases and three countries.

The rehabilitation field has not always been regarded as the most glamorous or commercially promising section of medical care. But changing attitudes and demographics in many industrial countries have led to increased recognition of opportunity to provide services for individuals with disabilities and those in need of chronic care. As hospitals are under increasing pressure to offer rehabilitation services, this article focuses on three different technologies developed in three different countries, Sweden, the United Kingdom, and the United States.

The process of evaluating medical technologies for third-party coverage.

A detailed review of records and documentation considered more than 100 technology evaluations performed in conjunction with coverage decisions by the Medicare program and by a major Blue Cross/blue Shield plan. Medicare evaluations were highly structured, synthesizing thorough literature reviews, recommendations from the National Institutes of Health and other governmental agencies, and information solicited from medical specialty societies and independent practitioners; however, the material supplied by nongovernmental sources seldom influenced the coverage recommendations. In contrast, the Blue plan's evaluations were based largely on presentations and discussions at advisory committee meetings, after receiving informational inputs that were more limited than those used in Medicare evaluations. The fraction of technologies recommended for coverage was slightly over 50% for each carrier. If information was strongly positive about either a technology's safety, its effectiveness, or both, then coverage was nearly always recommended. Still, the carriers differed significantly in the stage of development of the practices evaluated and in their willingness to make a coverage decision in the face of both safety and effectiveness data that were regarded as tentative. Because coverage decisions, and the speed with which they are conducted, may be crucial to the rate of a technology's diffusion--and possibly even to the rate of innovation--the authors conclude that it is important to understand clearly the process by which this type of technology assessment is performed.