Cost Models with Prominent Outliers

Government reimbursement programs, such as Medicare and Medicaid, generally pay hospitals less than the cost of caring for the people enrolled in these programs. For many patient conditions, Medicare and Medicaid pay hospitals a fixed amount based upon average cost for a procedure or treatment with local conditions taken into consideration. In addition, while the hospital provides the services, it has little control over the cost of delivery of that service, which is determined more by physician orders. The physician is under no real obligation to control those costs as the physician bills separately for services that are independent of orders charged. However, some patients who are severely ill will cost considerably more than average. This has caused providers to lose money. In this study, we investigate the reimbursement policies and the assumptions that have been made to create these reimbursement policies.

The Relationship between Sleep Apnea and Cognitive Functioning

The brain is the most complicated and least studied area of Neuro Sceince. In recent times, it has been one of the fastest growing areas of study in the Medical Sciences. This is mostly due to computers and computational techniques that have emerged in the last 10-15 years. Cognitive Neuropsychology aims to understand how the structure and function of the brain relates to psychological processes. It places emphasis on studying the cognitive effects of brain injury or neurological illness with a view to inferring models of normal cognitive functioning. We investigate the relationship between sleep apnea and learning disorders. Sleep apnea is a neural disorder, where individuals find it difficult to sleep because they stop breathing. We want to see if patients with learning disabilities should be treated for sleep apnea.

Analyzing Problems of Childhood and Adolescence

The study presents the analysis of the results of a health survey that focuses on the health risk behaviors and attitudes in adolescents that result in teenage obesity. Predictive models are built and charts are plotted to map variations in childhood physical health with respect to their weight behavior and to compare the impact of each weight control plan. The analysis provides many useful observations and suggestions that can be helpful in developing child health policies. We also investigate another aspect of child health by examining the severity of immediate risk from disease versus the immediate risk from childhood vaccination by comparing mortality rates from the disease to the mortality rates from the vaccination. Results show that for some individuals, the risk from the vaccine can be higher than the risk from the disease. Therefore, individual risk should be taken into consideration rather than uniform risk across the population.

Healthcare Delivery in a Hospital Emergency Department

The outcome of interest in this study is the length of stay (LOS) at a Hospital Emergency Department (ED). The Length of stay depends on several independent clinical factors such as treatments, patient demographic characteristics, hospital, as well as physicians and nurses. The present study attempts to identify these variables by analyzing clinical data provided by electronic medical records (EMR) from an emergency department. Three analysis methodologies were identified as appropriate for this task. First, data mining techniques were applied, and then generalized linear models and Time series followed. In spite of the fact that Data Mining and Statistics share the same objective, which is to extract useful information from data, they perform independently of each other. In this case, we show how the two methodologies can be integrated with potential benefits. We applied decision trees to select important variables and used these variables as input in the other models.

Physician Prescribing Practices

The purpose of this project is to develop time series models to investigate prescribing practices and patient usage of medications with respect to the severity of the patient condition. The cost of medications is rising from year to year; some medications are prescribed more often compared to others even if they have similar properties. It would be of interest to pharmaceutical companies to know the reason for this. In this case, we predict the cost of medications, private insurance payments, Medicaid payments, Medicare payments, the quantity of medications, total payment and to study why the cost is rising in one medication compared to others. We investigate how much patients are spending on average for their prescriptions of medications, taking the inflation rate into account as a time-dependent regressor. Both forecasts, the one that incorporates the inflation rates and the one that does not are compared.

Utilization of the Emergency Department

The primary role of the Emergency Department (ED) is to treat the seriously injured and seriously sick patients. However, because of federal regulations requiring the ED to treat all who enter, EDs have become the providers of a large number of unscheduled, non-urgent care patients. The role of the ED has changed considerably in recent years to treat those without insurance, and without primary care physicians. The main purpose of this study is to investigate the use of the hospital ED for non-urgent care in relationship to socio-economic status and payer type. This study will identify the Socio-economic factors related to the utilization of the emergency department for health care. The study will identify for the purpose of shifting patients that use the Ed as primary care to a nearby clinic. The clinic is within a mile of the ED. It is a Nurse-managed health center that provides free care.

Outcomes Research in Gastrointestinal Treatment

This case study describes the use of SAS technology in streamlining cross-sectional and retrospective case-control studies in the exploration of the co-morbidity of depression and gastrointestinal disorders. Various studies in Europe and America have documented associations between irritable bowel syndrome and psychological conditions such as depression and anxiety disorders; however, these were observational studies. Because it is impossible to randomize symptoms, it is difficult to isolate patients with these co-morbidities for randomized trials. Therefore, studies will continue to use observational data. In this study, all steps are conducted electronically in a rapid development environment provided by SAS technology. In addition, it examines the potential rate of health-care utilization particularly for GI disorders among individuals with depressive symptoms and anxiety disorders. We find that the proportion of patients with gastrointestinal problems and psychological disorders is typically higher than the proportion of patients with only gastrointestinal problems.

Outcomes Research in Physical Therapy

This research investigates the outcomes of physical therapy by using data fusion methodology to develop a process for sequential episode grouping data in medicine. By using data fusion, data from different sources will be combined to review the use of physical therapy in orthopedic surgical procedures. The data that were used to develop sequential episode grouping consisted of insurance claims data from the Thomson Medstat MarketScan database. The data will be reviewed as a continuous time lapse for surgery date; that is, the utilization of physical therapy for a defined time period both before and after surgery will be used and studied. The methodology of this research will follow a series of preprocessing cleaning and sequential episode grouping, culminating in text mining and clustering the results to review. Through this research, it was found that the use of physical therapy for orthopedic issues is not common and was utilized in under 1% of the data sampled. Text mining was further utilized to examine the outcomes of physical rehabilitation in cardiopulmonary research. The functional independence measures score at discharge can be predicted to identify the potential benefits of physical rehabilitation on a patient by patient basis. By text mining and clustering comorbidity codes, the severity of those clusters were used in a prediction model to determine rehabilitation benefits. Other information such as preliminary functional independence scores and age (in relation to independence scores) were used in the prediction model to provide the prescribing physician a way to determine if a patient will benefit from rehabilitation after a cardiopulmonary event.

Analysis of Breast Cancer and Surgery as Treatment Options

In this case, we analyze breast cancer cases from the Thomson Medstat Market Scan® data using SAS and Enterprise Guide 4. First, we find breast cancer cases using ICD9 codes. We are interested in the age distribution, in the total charges of the entire treatment sequence and in the length of stay at the hospital during treatment. Then, we study two major surgery treatments: Mastectomy and Lumpectomy. For each one of them, we analyze the total charges and the length of stay. Then, we compare these two treatments in terms of total charges, length of stay and the association of the choice of treatment with age. Finally, we analyze other treatment options. The objective is to understand the methods used to obtain some useful information about breast cancer and also to explore how to use SAS and SAS Enterprise Guide 4 to examine specific healthcare problems.

Outcomes Research in Cardiovascular Procedures

In this case, the main objective is to examine information about patients with coronary artery disease who had invasive procedures (such as balloon angioplasty or stents), or coronary artery bypass surgery. We investigate the use of the drug- eluting stent as a treatment for coronary artery disease. The first section of this chapter is a brief background about coronary artery disease and different procedures that may be used as its treatment. Next, time series analysis as a statistical tool is discussed, and in the third section, the results of the time series analyses that are performed on the database are demonstrated. In this section, the effect of the drug-eluting stent as a new treatment on the demand of other procedures is discussed. The fourth section is about computing the risk of each procedure based on the claims database used. The last section includes the result, conclusion, and suggestions.