Search PubMed⌕ Search

Biomedical subjects

Deanna J M Isaman

Publications and source records attributed to Deanna J M Isaman.

3 recordsLinked to original sources

A discrete-state discrete-time model using indirect observation.

This research was motivated by a desire to model the progression of a chronic disease through various disease stages when data are not available to directly estimate all the transition parameters in the model. This is a common occurrence when time and expense make it unfeasible to follow a single cohort to estimate all the transition parameters. One difficulty of developing a model of chronic disease progression from such data is that the available studies often do not include the transitions of interest. For example, in our model of diabetic nephropathy, many clinical studies did not differentiate between patients without nephropathy and those who had microalbuminuria (a pre-clinical stage of nephropathy). Another difficulty was a lack of data to directly estimate parameters of interest. We consider models which can accommodate such difficulties. In this paper we consider the problem of estimating parameters of a discrete-time Markov process when longitudinal data describing the entire process are not available. First, we present a likelihood approach to estimate parameters of a discrete-time Markov model. Next, we use simulation to investigate the finite-sample behaviour of our approach. Finally, we present two examples: a model of diabetic nephropathy and a model of cardiovascular disease in diabetes.

Albuminuria↗

A computer simulation model of diabetes progression, quality of life, and cost.

OBJECTIVE: To develop and validate a comprehensive computer simulation model to assess the impact of screening, prevention, and treatment strategies on type 2 diabetes and its complications, comorbidities, quality of life, and cost. RESEARCH DESIGN AND METHODS: The incidence of type 2 diabetes and its complications and comorbidities were derived from population-based epidemiologic studies and randomized, controlled clinical trials. Health utility scores were derived for patients with type 2 diabetes using the Quality of Well Being-Self-Administered. Direct medical costs were derived for managed care patients with type 2 diabetes using paid insurance claims. Monte Carlo techniques were used to implement a semi-Markov model. Performance of the model was assessed using baseline and 4- and 10-year follow-up data from the older-onset diabetic population studied in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR). RESULTS: Applying the model to the baseline WESDR population with type 2 diabetes, we predicted mortality to be 51% at 10 years. The prevalences of stroke and myocardial infarction were predicted to be 18 and 19% at 10 years. The prevalences of nonproliferative diabetic retinopathy, proliferative retinopathy, and macular edema were predicted to be 45, 16, and 18%, respectively; the prevalences of microalbuminuria, proteinuria, and end-stage renal disease were predicted to be 19, 39, and 3%, respectively; and the prevalences of clinical neuropathy and amputation were predicted to be 52 and 5%, respectively, at 10 years. Over 10 years, average undiscounted total direct medical costs were estimated to be USD $53,000 per person. Among survivors, the average utility score was estimated to be 0.56 at 10 years. CONCLUSIONS: Our computer simulation model accurately predicted survival and the cardiovascular, microvascular, and neuropathic complications observed in the WESDR cohort with type 2 diabetes over 10 years. The model can be used to predict the progression of diabetes and its complications, comorbidities, quality of life, and cost and to assess the relative effectiveness, cost-effectiveness, and cost-utility of alternative strategies for the prevention and treatment of type 2 diabetes.

Computer Simulation↗

Improving diabetes processes of care in managed care.

OBJECTIVE: To evaluate the impact of systematic patient evaluation and patient and provider feedback on the processes and intermediate outcomes of diabetes care in Independent Practice Association model internal medicine practices. RESEARCH DESIGN AND METHODS: Nine practices providing care to managed care patients were randomly assigned as intervention or comparison sites. Intervention-site subjects had Annual Diabetes Assessment Program (ADAP) assessments (HbA(1c), blood pressure, lipids, smoking, retinal photos, urine microalbumin, and foot examination) at years 1 and 2. Comparison-site subjects had ADAP assessments at year 2. At Intervention sites, year 1 ADAP results were reviewed with subjects, mailed to providers, and incorporated into electronic medical records with guideline-generated suggestions for treatment and follow-up. Medical records were evaluated for both groups for the year before both the year 1 and year 2 ADAP assessments. Processes and intermediate outcomes were compared using linear and logistic mixed hierarchical models. RESULTS: Of 284 eligible subjects, 103 of 173 (60%) at the Intervention sites and 71 of 111 (64%) at the comparison sites participated; 83 of 103 (81%) of the intervention-site subjects returned for follow-up at year 2. Performance of the six recommended assessments improved in intervention-site subjects at year 2 compared with year 1 (5.8 vs. 4.3, P = 0.0001) and compared with comparison-site subjects at year 2 (4.2, P = 0.014). No significant changes were noted in intermediate outcomes. CONCLUSIONS: The ADAP significantly improved processes of care but not intermediate outcomes. Additional interventions are needed to improve intermediate outcomes.

Aged↗