Developing an Interactive Computer Interface for Elderly Patients

A1) The Decision Aid: Making a Decision about Colon Cancer Screening, a decision aid designed forpatients aged 75 and older, was developed and tested in paper form between December 2005 and December 2007. Six versions, targeted by age group and gender, were created and tested at the Cecil G Sheps Center for Health Services Research in conjunction with the Lineberger Comprehensive Cancer Center. A2) Decision to Convert to Computer: The decision to convert this existing decision aid to a computer-based format was based on a two-fold reasoning structure. First, with the oldest of the Baby Boomers reaching their 60’s, computer programming with emphasis on the older users is becoming more important. Several theories of likelihood of technology use for health education cite as two of the constructs perceived usefulness and perceived ease of use. As the population of older computer users transitions into one with more computer experience, the likelihood of use of computer-based tools will increase. Secondly, a computer-based system can tailor information more specifically per patient with less possibility for error. Beyond the six different versions based on age group and gender, algorithmic programs imbedded in the interface can be utilized to tailor information to much more specific variables, resulting in a large number of slightly different versions that would be impracticable on paper. A3) Development of the Interface: Theories of computer interface development, health education, and concerns regarding age-related decline in fine motor control and visual acuity informed our design of this computer interface. We utilized Adobe’s Flash CS3 to realize our design.Master of Public Healt

Development of a Practical Model for Targeting Patient Decision Support Interventions to Promote Colorectal Cancer Screening in Vulnerable Populations

We sought to develop a practical model for predicting probability of colorectal cancer (CRC) screening completion in a diverse safety-net population and a subsequent framework for targeting screening promotion interventions. Data used to construct the models was prospectively collected from a CRC screening intervention. Models were cross-validated by randomly splitting the data into training and validation samples. The predicted probabilities of screening completion from the final model were trichotomized into framework groups and cross-validated by defining cut-points in the training sample, applying them to the validation sample, and comparing across samples for homogeneity. The final model included demographic and simple psychosocial measures and predicted screening behavior adequately (AUROC=0.63). The framework groups (cut-points 0.62 (low), 0.74 (medium), and 1.0 (high)) were homogeneous across the two samples. The model and framework may be useful for designing and delivering targeted interventions to promote CRC screening. Future research should validate the framework groups

Resident Physicians' Life Expectancy Estimates and Colon Cancer Screening Recommendations in Elderly Patients

Colon cancer screening recommendations for patients aged 75 years and older should account for variation in older adults’ health states, life expectancies, and potential to benefit from screening

Comparing 3 Techniques for Eliciting Patient Values for Decision Making About Prostate-Specific Antigen Screening: A Randomized Controlled Trial

Good decision making about prostate-specific antigen (PSA) screening involves men considering how they value the different potential outcomes. The effects of different methods of helping men consider such values, however, is not clear

Development and Assessment of Algorithms for Delivering Tailored or Targeted Patient Decision Support in Two Disease Models

Thesis (Ph.D.)--University of Washington, 2013Patient decision support refers to the provision of appropriate information to a patient about his or her health conditions to aid in the goal of informed medical decision-making. Medical decisions in which there are multiple valid options in which the risks and benefits differ, deemed "preference-sensitive" decisions, necessitate shared decision-making and patient decision support. Tailoring and targeting can be used to adapt the content or the amount of information delivered to the patient. Tailored or targeted health information for patient decision support has long been shown to be more effective than generic information at modifying health behaviors. To increase adoption in clinical care, one goal in developing targeting frameworks is to choose theory constructs and personal characteristics measured by a few data items that are simple to collect. Thus, in developing parsimonious algorithms, it is important to understand the relationships between socio-demographic characteristics and theories of health behavior. Finally, to ensure acceptance of algorithms in patient decision support, it is critical to understand patient perceptions of such algorithms, particularly what additional factors are important in decision-making. This dissertation addresses these needs in two parts: Part 1) development of algorithms to guide content and intensity of patient decision support in the context of colorectal cancer screening, and Part 2) assessment of patient perceptions of the use of algorithms to guide patient decision support in the context of heart disease prevention. In the Part 1 of this dissertation, I conducted two studies that consider health beliefs, demographics, and patient behavior in the context of colorectal cancer screening behavior. The first study sought to understand the relationship between socio-demographic characteristics and constructs of the health belief model in the context of colorectal cancer screening behavior in a racially, ethnically, and linguistically diverse population. The second study sought to develop a practical regression model to predict the probability of completing colorectal cancer screening and, from this model, a framework for targeting patient decision support materials based on level of probability of completing CRC screening. In Part 2 of this dissertation, I conducted one study to assess the use of an algorithm in patient decision support for heart disease prevention therapy. This study was a qualitative analysis of interviews conducted after a discrete choice experiment (DCE) for heart disease prevention. I sought to understand new factors that were influencing heart disease prevention therapy choices and perception of DCE-based "values concordant" choice results. In the first part of the dissertation, I observed several key differences across racial/ethnic and language groups in terms of health beliefs about CRC and CRC screening. These differences were largely dependent upon primary spoken language, which may approximate level of acculturation. Non-English speaking Hispanics typically reported lower perceived susceptibility to CRC than non-Hispanic Whites, and higher perception of several barriers to CRC screening (prior testing experience, preparation for the test, need for sedation). Non-English speaking Asians also reported lower perceived susceptibility than non-Hispanic Whites, but lower perception of several barriers to CRC screening (need for additional testing, fear of results of the test, concern about complications from the test, need for sedation, anxiety about the procedure). These results may suggest topic areas that could be highlighted in CRC screening promotion interventions that are targeted at specific racial/ethnic and language groups. In the second study, I developed a simple model for predicting CRC screening completion. From that model I developed an intervention framework that may be useful for targeting the amount of information to patients based on how likely they are to complete screening. In the final study, I found several new factors that were influencing heart disease prevention decisions: medication avoidance/naturalness, competing demands, and familiarity. Participants were receptive to the DCE-based "values concordant" choice, even if they did not ultimately agree with it. The results of this dissertation may be informative to patient decision support researchers considering methods for targeting or tailoring decision support intervention for CRC screening or heart disease prevention. Future research should confirm the differences in health beliefs about CRC that we observed across racial/ethnic and language groups. Additionally, the targeting framework that we developed for CRC screening promotion interventions should be evaluated. Finally, future work in DCE for heart disease prevention therapy decision-making should incorporate the new attributes

Beyond Informed Consent: Educating the Patient

The informed consent doctrine was conceived as a basis for allowing patients to meaningfully participate in the decision-making process. It has evolved into a formal, legal document that reflects a desire by physicians and surgeons to have patients execute “waivers of liability.” In the process it has lost its educational value by shifting the emphasis to obtaining a “preoperative release” from an exchange of information upon which a patient can make important decisions about their healthcare choices. This is unfortunate because, in the process, both patients and physicians have suffered. Patients have become alienated from the informed consent process and, paradoxically, physicians and surgeons may have created more liability exposure through this alienation. We propose that by returning to an educational model, the patients will develop a greater sense of control, become more compliant, and potentially experience improved healthcare outcomes. There may also develop an alliance between the patient and the physician or surgeon, such that the seeds of an antagonistic or litigious relationship will not be planted before treatment begins. Liability reduction, therefore, may more likely arise from the educational model