Quality of care for uninsured type 2 diabetic patients in a financial assistance medical home model

The medically uninsured population in the United States is 16% or 42 million people and consists of a significant number of Type 2 diabetic patients which is the predominant form of diabetes with 798,000 new cases diagnosed each year. There is limited health services research on uninsured populations concerning health system measures or specific disease conditions. ^ The purpose of this investigation was to determine the impact a newly implemented health care program had on the quality of care provided to patients with Type 2 diabetes. The primary study objective was to compare the quality of care while controlling for utilization, and health status of patients in the new program to their status during the previous financial assistance program. The research design was a retrospective matched-pairs design. The study population consisted of 225 patients who received medical care during 1996 and 1997 at the University Health System in San Antonio, Texas. ^ Six quality of care measures individually failed to demonstrate a statistically significant difference when compared between the two periods. However, an index measure reflecting the number of patients who received all six of the quality of care measures demonstrated a statistically significant increase in 1997 (p-value < 0.05). In 1996, 8 patients (2.6%) received all six medical management components. In 1997, 38 patients (16.8%) received all six medical management components. Four regression models were analyzed; two out of the four models demonstrated inconsistent results based on the program membership variable. ^ It is concluded that there has been a small effect of the Carelink program demonstrated by an increase from 8 to 38 patients receiving all quality of care components for Type 2 diabetics at the UHS. It is recommended that additional research be conducted in order to evaluate the quality of care provided to Type 2 diabetic patients. ^

A constellation of factors associated with premature births among African American women

A cohort, cross-sectional, historical study design was used to study factors related to spontaneous premature birth outcomes among African American women. The cohort consisted of 4,294 mothers drawn from the 1988 National Maternal and Infant Health Survey conducted by the National Center for Health Statistics. The objectives of the study were: (1) to examine the distribution of gestational ages of African American infants for selected variables reported for their families and (2) to describe risk factors associated with birth at 20–31 weeks of gestational age and at 32–36 weeks of gestational age. Risk factors examined include maternal age, maternal marital status, maternal living arrangements, maternal education, maternal work status, household income, gestational bleeding, month prenatal began, adequacy of prenatal care, parity, previous viable preterm birth, and behavioral factors of attitude toward pregnancy, smoking, drug, and alcohol use during pregnancy. Frequency distributions, cross tabulations, stratified analysis, and logistic regression analysis were used. ^ Risk factors associated with a 50 percent or more increase in preterm birth were cocaine use, low maternal education, teenaged mother, prenatal care deficits or overuse, and bleeding during the second half of pregnancy. The other risk factors of not living with the baby's father, smoking cigarettes and having a mistimed pregnancy carried statistically significance but lower strength of association. ^ Health care services, educational systems, and community organizations can develop and evaluate comprehensive health education and information campaigns that address preventable risk factors during pregnancy. Although preterm birth cannot always be prevented, preconception care can help identify and modify maternal risk and promote optimum health before conception. Quality care should include continued risk assessment, health promotion, and interventions. ^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

The Emergency Department: Rising wait times, costs, and possible remedies

Emergency Departments (EDs) and Emergency Rooms (ERs) are designed to manage trauma, respond to disasters, and serve as the initial care for those with serious illnesses. However, because of many factors, the ED has become the doorway to the hospital and a “catch-all net” for patients including those with non-urgent needs. This increase in the population in the ED has lead to an increase in wait times for patients. It has been well documented that there has been a constant and consistent rise in the number of patients that frequent the ED (National Center for Health Statistics, 2002); the wait time for patients in the ED has increased (Pitts, Niska, Xu, & Burt, 2008); and the cost of the treatment in the ER has risen (Everett Clinic, 2008). Because the ED was designed to treat patients who need quick diagnoses and may be in potential life-threatening circumstances, management of time can be the ultimate enemy. If a system was implemented to decrease wait times in the ED, decrease the use of ED resources, and decrease costs endured by patients seeking care, better outcomes for patients and patient satisfaction could be achieved. The goal of this research was to explore potential changes and/or alternatives to relieve the burden endured by the ED. In order to explore these options, data was collected by conducting one-on-one interviews with seven physicians closely tied to a Level 1 ED (Emergency Room physicians, Trauma Surgeons and Primary Care physicians). A qualitative analysis was performed on the responses of one-on-one interviews with the aforementioned physicians. The interviews were standardized, open-ended questions that probe what makes an effective ED, possible solutions to improving patient care in the ED, potential remedies for the mounting problems that plague the ED, and the feasibility of bringing Primary Care Physicians to the ED to decrease the wait times experienced by the patient. From the responses, it is clear that there needs to be more research in this area, several areas need to be addressed, and a variety of solutions could be implemented. The most viable option seems to be making the ED its own entity (similar to the clinic or hospital) that includes urgent clinics as a part of the system, in which triage and better staffing would be the most integral part of its success.^

THE EFFECT OF PERSON-ENVIRONMENT FIT ON THE PSYCHOLOGICAL WELL-BEING OF PSYCHIATRIC AIDES WORKING IN A STATE HOSPITAL (COPING RESOURCES, SOCIAL SUPPORT, OCCUPATIONAL STRESS, LOCUS-OF-CONTROL)

This study addressed two purposes: (1) to determine the effect of person-environment fit on the psychological well-being of psychiatric aides and (2) to determine what role the coping resources of social support and control have on the above relationship. Two hundred and ten psychiatric aides working in a state hospital in Texas responded to a questionnaire pertaining to these issues.^ Person-environment fit, as a measure of occupational stress, was assessed through a modified version of the Work Environment Scale (WES). The WES subscales used in this study were: involvement, autonomy, job pressure, job clarity, and physical comfort. Psychological well-being was measured with the General Well-Being Schedule which was developed by the National Center for Health Statistics. Co-worker and supervisor support were measured through the WES and finally, control was assessed through Rotter's Locus of Control Scale.^ The results of this study were as follows: (1) all person-environment (p-e) dimensions appeared to have linear relationships with psychological well-being; (2) the p-e fit - well-being relationship did not appear to be confounded by demographic factors; (3) all p-e fit dimensions were significantly related to well-being except for autonomy; (4) p-e fit was more strongly related to well-being than the environmental measure alone; (5) supervisor support and non-work related support were found to have additive effects on the relationship between p-e fit and well-being, however no interaction or buffering effects were observed; (6) locus of control was found to have additive effects in the prediction of well-being and showed interactive effects with work pressure, involvement and physical comfort; and (7) the testing of the overall study model which included many of the components mentioned above yielded an R('2) = .27.^ Implications of these findings are discussed, future research suggested and applications proposed. ^

AN ANALYSIS OF THE GENERAL WELL-BEING OF BLACKS AND WHITES

The importance of race as a factor in mental health status has been a topic of controversy. This study reviews the history of research in this area and examines racial variances in the relationship between selected socio-demographic variables and general well-being. The study also examines the appropriateness of an additive versus an interactive statistical model for this investigation.^ The sample consists of 6,913 persons who completed the General Well-Being Schedules as administered in the detailed component of the first National Health and Nutrition Examination Survey (NHANES I) conducted by the National Center for Health Statistics between April, 1971 and October, 1975. The sampling design is a multistage, probability sample of clusters of persons in area based segments. Of the 6,913 persons, 873 are Black.^ Unlike other recent community based mental health studies, this study revealed significant differences between the general well-being of Blacks and Whites. Blacks continued to exhibit significantly lower levels of well-being even after adjustments were made for income, education, marital status, sex, age and place of residence. Statistical interaction was found between race and sex with Black females reporting lower levels of well-being than either Black or White males or their White female counterparts.^ The study includes a detailed review of the NHANES I sample design. It is shown that selected aspects of the design make it difficult to render appropriate national comparisons of Black-White differences. As a result conclusions pertaining to these differences based on NHANES I may be of questionable validity. ^

Estimates of life expectancy gains from reducing/eliminating major causes of death in the USA: An update analysis for population in 2001--2008

Evaluation of the impact of a disease on life expectancy is an important part of public health. Potential gains in life expectancy (PGLE) that can properly take into account the competing risks are an effective indicator for measuring the impact of the multiple causes of death. This study aimed to measure the PGLEs from reducing/eliminating the major causes of death in the USA from 2001 to 2008. To calculate the PGLEs due to the elimination of specific causes of death, the age-specific mortality rates for heart disease, malignant neoplasms, Alzheimer disease, kidney diseases and HIV/AIDS and life table constructing data were obtained from the National Center for Health Statistics, and the multiple decremental life tables were constructed. The PGLEs by elimination of heart disease, malignant neoplasms or HIV/AIDS continued decreasing from 2001 to 2008, but the PGLE by elimination of Alzheimer's disease or kidney diseases revealed increased trends. The PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of heart disease 2001–2008 were 0.336–0.299, 0.327–0.301, 0.344–0.295, 0.360–0.315, 0.349–0.317, 0.371–0.316,0.278–0.251, 0.272–0.255, and 0.282–0.246 respectively. Similarly, the PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of malignant neoplasms, Alzheimer's disease, kidney disease or HIV/AIDS 2001–2008 were also uncovered, respectively. Most diseases affect specific population, such as, HIV/AIDS tends to have a greater impact on people of working age, heart disease and malignant neoplasms have a greater impact on people over 65 years of age, but Alzheimer's disease and kidney diseases have a greater impact on people over 75 years of age. To measure the impact of these diseases on life expectancy in people of working age, partial multiple decremental life tables were constructed and the PGLEs were computed by partial or complete elimination of various causes of death during the working years. Thus, the results of the study outlined a picture of how each single disease could affect the life expectancy in age-, race-, or sex-specific population in USA. Therefore, the findings would not only assist to evaluate current public health improvements, but also provide useful information for future research and disease control programs.^

Development and evaluation of a video-based modeling strategy for the dissemination phase of a school health tobacco -use prevention program

Even the best school health education programs will be unsuccessful if they are not disseminated effectively in a manner that encourages classroom adoption and implementation. This study involved two components: (1) the development of a videotape intervention to be used in the dissemination phase of a 4-year, NCI-funded diffusion study and (2) the evaluation of that videotape intervention strategy in comparison with a print (information transfer) strategy. Conceptualization has been guided by Social Learning Theory, Diffusion Theory, and communication theory. Additionally, the PRECEDE Framework has been used. Seventh and 8th grade classroom teachers from Spring Branch Independent School District in west Houston participated in the evaluation of the videotape and print interventions using a 57-item preadoption survey instrument developed by the UT Center for Health Promotion Research and Development. Two-way ANOVA was used to study individual score differences for five outcome variables: Total Scale Score (comprised of 57 predisposing, enabling, and reinforcing items), Adoption Characteristics Subscale, Attitude Toward Innovation Subscale, Receptivity Toward Innovation, and Reinforcement Subscale. The aim of the study is to compare the effect upon score differences of video and print interventions alone and in combination. Seventy-three 7th and 8th grade classroom teachers completed the study providing baseline and post-intervention measures on factors related to the adoption and implementation of tobacco-use prevention programs. Two-way ANOVA, in relation to the study questions, found significant scoring differences for those exposed to the videotape intervention alone for both the Attitude Toward Innovation Subscale and the Receptivity to Adopt Subscale. No significant results were found to suggest that print alone influences favorable scoring differences between baseline and post-intervention testing. One interaction effect was found suggesting video and print combined are more effective for influencing favorable scoring differences for the Reinforcement for the Adoption Subscale.^ This research is unique in that it represents a newly emerging field in health promotion communications research with implications for Social Learning Theory, Diffusion Theory, and communication science that are applicable to the development of improved school health interventions. ^

Database resources of the National Center for Biotechnology Information

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap’99, Human–Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri­tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.