Chronic Disease or Injury

One of the key questions in health economics is what is the direction of causality: does poverty cause poor health outcomes; does low education cause poor health outcomes; does poor health result in lack of productivity; does poor health cause poor educational and income outcomes; and how is this all related to mental health if at all. We are used to breaking down data into fragments as researchers: an investigator who is predominantly focused on health outcomes will approach the problem with disease as the dependent variable and income as the conditioning variable. However, if we are interested in income inequality we will reverse the direction and income will be the dependent variable with health status as the conditioning variable.

The representation above allows us to visualize data as a function of multiple fragments. For example, if we want to understand how depression is related to income, one can look at the figure to observe that with lower income there is a higher likelihood of being depressed. With this simple illustration, we can see that establishing causal links can be very tricky, if not incredibly challenging.

Objective

Our primary goal is to move towards establishing a causal link between binge drinking, mental health, employment, and income. 

Patients who suffer from rare diseases can be hard to diagnose for prolonged periods of time. In the process, they are often subjected to tentative treatments for ailments they do not have, risking an escalation of their actual condition and side effects from therapies they do not need. An early and accurate detection of these cases would enable follow-ups for precise diagnoses, mitigating the costs of unnecessary care and improving patients’ outcomes. 

Objective

To identify sufferers of a rare and hard to diagnose diseases by detecting sequential patterns in historical medical claims. 

Firearm violence is an issue of public health concern leading to more than 30,000 deaths and 80,000 nonfatal injuries in the United States annually. To date, firearm-related studies among Veterans have focused primarily on suicide and attempted suicide. Herein, we examine firearm violence among VHA enrollees for all manners/ intents, including assault, unintentional, self-inflicted, undetermined and other firearm-related injury encounters in both the inpatient and outpatient settings. 

Prescription Drug Monitoring Programs (PDMPs) are operating in 49 states and several U.S. territories. Current methods for surveillance of prescription drug related behaviors, include the mean daily dosage of morphine milligram equivalent (MME) per patient, annual percentage of days with overlapping prescriptions per patient, and annual multiple provider episodes for multiple controlled substance prescription drugs per patient that are described elsewhere.1,2 This work builds on these efforts by extending longitudinal methods to prescription drug behavior surveillance in order to predict risks associated with prescription drug use. 

Objective

This study aims to show the application of longitudinal statistical and epidemiological methods for building a proactive prescription drug surveillance system for public health.