DEVELOPING A METHOD FOR IDENTIFYING AND REDUCING FUNCTIONAL DISCREPANCIES OF INFORMATION SYSTEMS

Currently more than half of Electronic Health Record (EHR) projects fail. Most of these failures are not due to flawed technology, but rather due to the lack of systematic considerations of human issues. Among the barriers for EHR adoption, function mismatching among users, activities, and systems is a major area that has not been systematically addressed from a human-centered perspective. A theoretical framework called Functional Framework was developed for identifying and reducing functional discrepancies among users, activities, and systems. The Functional Framework is composed of three models – the User Model, the Designer Model, and the Activity Model. The User Model was developed by conducting a survey (N = 32) that identified the functions needed and desired from the user’s perspective. The Designer Model was developed by conducting a systemic review of an Electronic Dental Record (EDR) and its functions. The Activity Model was developed using an ethnographic method called shadowing where EDR users (5 dentists, 5 dental assistants, 5 administrative personnel) were followed quietly and observed for their activities. These three models were combined to form a unified model. From the unified model the work domain ontology was developed by asking users to rate the functions (a total of 190 functions) in the unified model along the dimensions of frequency and criticality in a survey. The functional discrepancies, as indicated by the regions of the Venn diagrams formed by the three models, were consistent with the survey results, especially with user satisfaction. The survey for the Functional Framework indicated the preference of one system over the other (R=0.895). The results of this project showed that the Functional Framework provides a systematic method for identifying, evaluating, and reducing functional discrepancies among users, systems, and activities. Limitations and generalizability of the Functional Framework were discussed.

AN EVALUATION OF THE CONSISTENCY OF IMRT PATIENT-SPECIFIC QA TECHNIQUES

To ensure the integrity of an intensity modulated radiation therapy (IMRT) treatment, each plan must be validated through a measurement-based quality assurance (QA) procedure, known as patient specific IMRT QA. Many methods of measurement and analysis have evolved for this QA. There is not a standard among clinical institutions, and many devices and action levels are used. Since the acceptance criteria determines if the dosimetric tools’ output passes the patient plan, it is important to see how these parameters influence the performance of the QA device. While analyzing the results of IMRT QA, it is important to understand the variability in the measurements. Due to the different form factors of the many QA methods, this reproducibility can be device dependent. These questions of patient-specific IMRT QA reproducibility and performance were investigated across five dosimeter systems: a helical diode array, radiographic film, ion chamber, diode array (AP field-by-field, AP composite, and rotational composite), and an in-house designed multiple ion chamber phantom. The reproducibility was gauged for each device by comparing the coefficients of variation (CV) across six patient plans. The performance of each device was determined by comparing each one’s ability to accurately label a plan as acceptable or unacceptable compared to a gold standard. All methods demonstrated a CV of less than 4%. Film proved to have the highest variability in QA measurement, likely due to the high level of user involvement in the readout and analysis. This is further shown by how the setup contributed more variation than the readout and analysis for all of the methods, except film. When evaluated for ability to correctly label acceptable and unacceptable plans, two distinct performance groups emerged with the helical diode array, AP composite diode array, film, and ion chamber in the better group; and the rotational composite and AP field-by-field diode array in the poorer group. Additionally, optimal threshold cutoffs were determined for each of the dosimetry systems. These findings, combined with practical considerations for factors such as labor and cost, can aid a clinic in its choice of an effective and safe patient-specific IMRT QA implementation.

Attitudes of Parents at risk of inheriting Li-Fraumeni Syndrome towards predictive genetic testing in their minor-aged children.

Li-Fraumeni Syndrome (LFS) is a hereditary cancer syndrome which predisposes individuals to cancer beginning in childhood. These risks are spread across a lifetime, from early childhood to adulthood. Mutations in the p53 tumor suppressor gene are known to cause the majority of cases of LFS. The risk for early onset cancer in individuals with Li-Fraumeni Syndrome is high. Studies have shown that individuals with LFS have a 90% lifetime cancer risk. Children under 18 have up to a 15% chance of cancer development. Effectiveness of cancer screening and management in individuals with Li-Fraumeni Syndrome is unclear. Screening for LFS-associated cancers has not been shown to reduce mortality. Due to the lack of effective screening techniques for childhood cancers, institutions vary with regard to their policies on testing children for LFS. There are currently no national guidelines regarding predictive testing of children who are at risk of inheriting LFS. No studies have looked at parental attitudes towards predictive p53 genetic testing in their children. This was a cross-sectional pilot study aimed at describing these attitudes. We identified individuals whose children were at risk for inheriting p53 genetic mutations. These individuals were provided with surveys which included validated measures addressing attitudes and beliefs towards genetic testing. The questionnaire included qualitative and quantitative measures. Six individuals completed and returned the questionnaire with a response rate of 28.57%. In general, respondents agreed that parents should have the opportunity to obtain p53 genetic testing for their child. Parents vary in regard to their attitudes towards who should be involved in the decision making process and at what time and under what considerations testing should occur. Testing motivations cited most important by respondents included family history, planning for the future and health management. Concern for insurance genetic discrimination was cited as the most important “con” to genetic testing. Although limited by a poor response rate, this study can give health care practitioners insight into testing attitudes and beliefs of families considering pediatric genetic testing.

The Houston Academy of Medicine--Texas Medical Center Library management information system.

A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.

Controlled Software Evaluation Methodology: Case Simulation and Cognitive User Analysis

Software for use with patient records is challenging to design and difficult to evaluate because of the tremendous variability of patient circumstances. A method was devised by the authors to overcome a number of difficulties. The method evaluates and compares objectively various software products for use in emergency departments and compares software to conventional methods like dictation and templated chart forms. The technique utilizes oral case simulation and video recording for analysis. The methodology and experiences of executing a study using this case simulation are discussed in this presentation.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.