Biomedical subjects

Peter J Fos

Publications and source records attributed to Peter J Fos.

6 recordsLinked to original sources

PubMed2005

Relationship of cataract symptoms of preoperative patients and vision-related quality of life.

BACKGROUND: This study was conducted in an attempt to describe the status of cataract symptoms of preoperative cataract patients, as well as to determine the relationship between cataract symptom and vision-related quality of life measures. RESEARCH DESIGN: A cross-sectional study design was used. Study subjects were selected using non-probabilistic methods. The study sample consisted of 132 patients scheduled for cataract surgery in one eye. Information was obtained from study subjects by conducting face-to-face interviews. PARTICIPANTS: Study subjects were adult cataract patients at Samsung and Kunyang General Hospitals in Seoul, Korea, and Tulane University Hospital and Clinics in New Orleans, Louisiana, United States of America. MEASUREMENTS: Degree to which study subjects were "bothered" by cataract symptoms was measured by using the 5-item Cataract Symptom Scores (CSS). The number of symptoms, highest scored symptom among the five, number of symptoms extremely bothering, and the mean of cataract symptom score were created based on the CSS measure. Vision-related quality of life was assessed by using the Visual Function 14 Items (VF-14) and Global Measure of Vision (GMV) for trouble and satisfaction. RESULTS: The symptoms "blurry vision" and "worsening of vision" were most frequently reported. The symptom "colors looking different" was rarely reported among preoperative cataract patients. The degree to which study subjects were bothered by "blurry vision" and "seeing glare, halo, or rings" was highly associated with visual function, visual trouble, and visual satisfaction. Multiple regression analysis revealed that the newly developed cataract symptom-related scales, as well as total amount of degree to which study subjects were "bothered" by symptoms were highly related to vision-related quality of life measures. These relationships were persistent after controlling for major socio-demographic variables. CONCLUSIONS: The results indicate that cataract symptoms are highly associated with vision-related quality of life. The results also suggest that the number of symptoms, highest scored symptom among the five, number of symptoms extremely bothering, and the mean cataract symptom scores should be considered an important cataract symptom-related scale when analyzing quality of life, including cataract symptom.

Aged↗

PubMed2003

Combining the performance strengths of the logistic regression and neural network models: a medical outcomes approach.

The assessment of medical outcomes is important in the effort to contain costs, streamline patient management, and codify medical practices. As such, it is necessary to develop predictive models that will make accurate predictions of these outcomes. The neural network methodology has often been shown to perform as well, if not better, than the logistic regression methodology in terms of sample predictive performance. However, the logistic regression method is capable of providing an explanation regarding the relationship(s) between variables. This explanation is often crucial to understanding the clinical underpinnings of the disease process. Given the respective strengths of the methodologies in question, the combined use of a statistical (i.e., logistic regression) and machine learning (i.e., neural network) technology in the classification of medical outcomes is warranted under appropriate conditions. The study discusses these conditions and describes an approach for combining the strengths of the models.

Artificial Intelligence↗

PubMed2003

Health-related quality of life of cataract patients: cross-cultural comparisons of utility and psychometric measures.

BACKGROUND: This study was conducted to assess the presence and/or absence of cross-cultural differences or similarities between Korean and United States cataract patients. A systematic assessment was performed using utility and psychometric measures in the study population. RESEARCH DESIGN: A cross-sectional study design was used to examine the comparison of preoperative outcomes measures in cataract patients in Korea and the United States. Study subjects were selected using non-probabilistic methods and included 132 patients scheduled for cataract surgery in one eye. PARTICIPANTS: Subjects were adult cataract patients at Samsung and Kunyang General Hospital in Seoul, Korea, and Tulane University Hospital and Clinics in New Orleans, Louisiana. MEASUREMENTS: Preoperative utility was assessed using the verbal rating scale and standard reference gamble techniques. Current preoperative health status was assessed using the SF-36 and VF-14 surveys. Current preoperative Snellen visual acuity was used as a clinical measure of vision status. RESULTS: Korean patients were more likely to be younger (p = 0.001), less educated (p = 0.001), and to have worse Snellen visual acuity (p = 0.002) than United States patients. Multivariate analysis of variance (MANOVA) revealed that in contrast to Korean patients, United States patients were assessed to have higher scoring in general health, vitality, VF-14, and verbal rating for visual health. This higher scoring trend persisted after controlling for age, gender, education and Snellen visual acuity. The difference in health-related quality of life (HRQOL) between the two countries was quite clear, especially in the older age and highly educated group. CONCLUSIONS: Subjects in Korea and the United States were significantly different in quality of life, functional status and clinical outcomes. Subjects in the United States had more favorable health outcomes than those in Korea. These differences may be caused by multiple factors, including country-specific differences in economic status, health care system, cultural value system, and health policy. Cross-cultural differences should be considered when making international comparisons of quality of life.

Aged↗

PubMedDate not supplied

Data mining a diabetic data warehouse.

Diabetes is a major health problem in the United States. There is a long history of diabetic registries and databases with systematically collected patient information. We examine one such diabetic data warehouse, showing a method of applying data mining techniques, and some of the data issues, analysis problems, and results. The diabetic data warehouse is from a large integrated health care system in the New Orleans area with 30,383 diabetic patients. Methods for translating a complex relational database with time series and sequencing information to a flat file suitable for data mining are challenging. We discuss two variables in detail, a comorbidity index and the HgbA1c, a measure of glycemic control related to outcomes. We used the classification tree approach in Classification and Regression Trees (CART) with a binary target variable of HgbA1c >9.5 and 10 predictors: age, sex, emergency department visits, office visits, comorbidity index, dyslipidemia, hypertension, cardiovascular disease, retinopathy, end-stage renal disease. Unexpectedly, the most important variable associated with bad glycemic control is younger age, not the comorbiditity index or whether patients have related diseases. If we want to target diabetics with bad HgbA1c values, the odds of finding them is 3.2 times as high in those <65 years of age than those older. Data mining can discover novel associations that are useful to clinicians and administrators [corrected].

Adult↗

PubMedDate not supplied

Combining the benefits of decision science and financial analysis in public health management: a county-specific budgeting and planning model.

State public health agencies are charged with providing and overseeing the management of basic public health services on a population-wide basis. These activities have a re-emphasized focus as a result of the events of September 11, 2001, the subsequent anthrax events, and the continuing importance placed on bioterrorism preparedness, West Nile virus, and emerging infectious diseases (eg, monkeypox, SARS). This has added to the tension that exists in budgeting and planning, given the diverse constituencies that are served in each state. State health agencies must be prepared to allocate finite resources in a more formal manner to be able to provide basic public health services on a routine basis, as well as during outbreaks. This article describes the use of an analytical approach to assist financial analysis that is used for budgeting and planning in a state health agency. The combined benefits of decision science and financial analysis are needed to adequately and appropriately plan and budget to meet the diverse needs of the populations within a state. Health and financial indicators are incorporated into a decision model, based on multicriteria decision theory, that has been employed to acquire information about counties and public health programs areas within a county, that reflect the impact of planning and budgeting efforts. This information can be used to allocate resources, to distribute funds for health care services, and to guide public health finance policy formulation and implementation.

Budgets↗

PubMedDate not supplied

The role of quality improvement in disease management: a statewide tuberculosis control success story.

This study describes Mississippi's statewide latent tuberculosis infection (LTBI) control management efforts to improve treatment outcomes using scientific quality improvement tools. LTBI medication completion rates were observed by month and by nine administrative health districts for a 12-month period. Analysis of variance (ANOVA) was conducted to see if there was any significant change between preintervention and postintervention in medication completion rates. Regression analysis was performed to test the linearity of change across the monthly rates. A change from a rate of 79.7 percent to 90.5 percent completion of the LTBI medication regimen was observed after the quality improvement intervention was instituted. During the quality improvement intervention, the mean reached 96.5 percent completion, followed by a slight decline at the end of the intervention to 90.5 percent. The analysis revealed that the mean LTBI medication completion rate across the nine administrative health districts was significantly increased and variability was decreased across all administrative health districts, with minor exceptions. A quality improvement team approach was shown to be effective in disease management by increasing LTBI medication completion. New baseline expectations can be established when quality improvement initiatives are implemented. This success can be linked, in part, to the use of scientific methods, precise and valid data, persuasive and clear goal setting, appropriate feedback, and ongoing monitoring.

Analysis of Variance↗