Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

Exploring the use of pharmaceutical patient assistance programs as an option to improve access to and affordability of prescription drugs

Background. Pharmaceutical-sponsored patient assistance programs (PAPs) are charity programs that provide free or reduced-priced medications to eligible patients. PAPs have the potential to improve prescription drug accessibility for patients but currently there is limited information about their use and effectiveness. ^ Objectives and methods. This dissertation described the use of PAPs in the U.S. through the conduct of two studies: (1) a systematic review of primary studies of PAPs from commercially-published and “grey” literature sources; and (2) a retrospective, cross-sectional study of cancer patients' use of PAPs at a tertiary care cancer outpatient center. ^ Results. (1) The systematic review identified 33 studies: 15 evaluated the impact of PAP enrollment assistance programs on patient healthcare outcomes; 7 assessed institutional costs of providing enrollment assistance; 7 surveyed stakeholders; 4 examined other aspects. Standardized mean differences calculated for disease indicator outcomes (most of which were single group, pre-posttest designs) showed significant decreases in glycemic and lipid control, and inconsistent results for blood pressure. Grey literature abstracts reported insufficient statistics for calculations. Study heterogeneity made weighted summary estimates inappropriate. Economic analyses indicated positive financial benefits to institutions providing enrollment assistance (cost) compared to the wholesale value of the medications provided (benefit); analyses did not value health outcomes. Mean quality of reporting scores were higher for observational studies in commercially-published articles versus full text, grey literature reports. (2) The cross-sectional study found that PAP outpatients were significantly more likely to be uninsured, indigent, and < 65 years old than non-PAP patients. Nearly all non-PAP and PAP prescriptions were for non-cancer conditions, either for co-morbidities (e.g., hypertension) or the management of treatment side effects (e.g., pain). Oral chemotherapies from PAPs were significantly more likely to be for breast versus other cancers, and be a newer, targeted versus traditional chemotherapy.^ Conclusions. In outpatient settings, PAP enrollment assistance plus additional medication services (e.g., counseling, reminders, and free samples) is associated with improved disease indicators for patients. Healthcare institutions, including cancer centers, can offset financial losses from uncompensated drug costs and recoup costs invested in enrollment assistance programs by procuring free PAP medications. Cancer patients who are indigent and uninsured may be able to access more outpatient medications for their supportive care needs through PAPs, than for cancer treatment options like oral chemotherapies. Because of the selective availability of drugs through PAPs, there may be more options for newer, oral, targeted chemotherapies for the treatment breast cancer versus other for other cancers.^

The use of social media to communicate child health information to low-income parents: A formative study

The Internet, and specifically web 2.0 social media applications, offers an innovative method for communicating child health information to low-income parents. The main objective of this study was to use qualitative data to determine the value of using social media to reach low-income parents with child health information. A qualitative formative evaluation employing focus groups was used to determine the value of using social media for dissemination of child health information. Inclusion criteria included: (1) a parent with a child that attends a school in a designated Central Texas school district; and (2) English-speaking. The students who attend these schools are generally economically disadvantaged and are predominately Hispanic. The classic analysis strategy was used for data analysis. Focus group participants (n=19) were female (95%); White (53%), Hispanic (42%) or African American (5%); and received government assistance (63%). Most had access to the Internet (74%) and were likely to have low health literacy (53%). The most preferred source of child health information was the family pediatrician or general practitioner. Many participants were familiar with social media applications and had profiles on popular social networking sites, but used them infrequently. Objections to social media sites as sources of child health information included lack of credibility and parent time. Social media has excellent potential for reaching low-income parents when used as part of a multi-channel communication campaign. Further research should focus on the most effective type and format of messages that can promote behavior change in this population, such as story-telling. ^

The New Futuro College Plan: Facilitating College Access

Built on a free, bilingual, "high-touch, high-tech" platform, New Futuro has created a robust community of Latino students and parents, non-profit organizations, education institutions, government agencies, and corporations to connect those that need help with those that provide it. One of the resources developed by New Futuro is a proprietary 10-Steps College Plan that provides structured information targeted to Latino students and families to help them prepare, apply and pay for college.

The Effect of Proximity, Explicitness, and Representation of Basic Science Information on Student Clinical Problem-Solving

Problem: Medical and veterinary students memorize facts but then have difficulty applying those facts in clinical problem solving. Cognitive engineering research suggests that the inability of medical and veterinary students to infer concepts from facts may be due in part to specific features of how information is represented and organized in educational materials. First, physical separation of pieces of information may increase the cognitive load on the student. Second, information that is necessary but not explicitly stated may also contribute to the student’s cognitive load. Finally, the types of representations – textual or graphical – may also support or hinder the student’s learning process. This may explain why students have difficulty applying biomedical facts in clinical problem solving. Purpose: To test the hypothesis that three specific aspects of expository text – the patial distance between the facts needed to infer a rule, the explicitness of information, and the format of representation – affected the ability of students to solve clinical problems. Setting: The study was conducted in the parasitology laboratory of a college of veterinary medicine in Texas. Sample: The study subjects were a convenience sample consisting of 132 second-year veterinary students who matriculated in 2007. The age of this class upon admission ranged from 20-52, and the gender makeup of this class consisted of approximately 75% females and 25% males. Results: No statistically significant difference in student ability to solve clinical problems was found when relevant facts were placed in proximity, nor when an explicit rule was stated. Further, no statistically significant difference in student ability to solve clinical problems was found when students were given different representations of material, including tables and concept maps. Findings: The findings from this study indicate that the three properties investigated – proximity, explicitness, and representation – had no statistically significant effect on student learning as it relates to clinical problem-solving ability. However, ad hoc observations as well as findings from other researchers suggest that the subjects were probably using rote learning techniques such as memorization, and therefore were not attempting to infer relationships from the factual material in the interventions, unless they were specifically prompted to look for patterns. A serendipitous finding unrelated to the study hypothesis was that those subjects who correctly answered questions regarding functional (non-morphologic) properties, such as mode of transmission and intermediate host, at the family taxonomic level were significantly more likely to correctly answer clinical case scenarios than were subjects who did not correctly answer questions regarding functional properties. These findings suggest a strong relationship (p < .001) between well-organized knowledge of taxonomic functional properties and clinical problem solving ability. Recommendations: Further study should be undertaken investigating the relationship between knowledge of functional taxonomic properties and clinical problem solving ability. In addition, the effect of prompting students to look for patterns in instructional material, followed by the effect of factors that affect cognitive load such as proximity, explicitness, and representation, should be explored.