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.

Can prospective usability evaluation predict data errors?

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance.

Illusory predictors: Generalizability of findings in cocaine treatment retention research.

Treatment retention is of paramount importance in cocaine treatment research as treatment completion rates are often 50% or less. Failure to retain cocaine patients in treatment has both significant research and clinical implications. In this paper we qualitatively and quantitatively demonstrate the inconsistency found across analyses of retention predictors in order to highlight the problem. First, a qualitative review of the published literature was undertaken to identify the frequency of predictors studied and their relations to treatment retention. Second, an empirical demonstration of predictor stability was conducted by testing a common set of variables across three similar 12-week cocaine clinical trials conducted by the same investigators in the same research clinic within a five-year period. Results of the literature review indicated inconsistently selected variables of convenience, widely varying statistical procedures, and discrepant findings of significance. Further, quantitative analyses resulted in discrepancies in variables identified as significant predictors of retention among the three studies. Potential sources of heterogeneity affecting the consistency of findings across studies and recommendations to improve the validity and generalizability of predictor findings in future studies are proposed.

The design and evaluation of a 2D dose verification system for intensity modulated radiotherapy

The usage of intensity modulated radiotherapy (IMRT) treatments necessitates a significant amount of patient-specific quality assurance (QA). This research has investigated the precision and accuracy of Kodak EDR2 film measurements for IMRT verifications, the use of comparisons between 2D dose calculations and measurements to improve treatment plan beam models, and the dosimetric impact of delivery errors. New measurement techniques and software were developed and used clinically at M. D. Anderson Cancer Center. The software implemented two new dose comparison parameters, the 2D normalized agreement test (NAT) and the scalar NAT index. A single-film calibration technique using multileaf collimator (MLC) delivery was developed. EDR2 film's optical density response was found to be sensitive to several factors: radiation time, length of time between exposure and processing, and phantom material. Precision of EDR2 film measurements was found to be better than 1%. For IMRT verification, EDR2 film measurements agreed with ion chamber results to 2%/2mm accuracy for single-beam fluence map verifications and to 5%/2mm for transverse plane measurements of complete plan dose distributions. The same system was used to quantitatively optimize the radiation field offset and MLC transmission beam modeling parameters for Varian MLCs. While scalar dose comparison metrics can work well for optimization purposes, the influence of external parameters on the dose discrepancies must be minimized. The ability of 2D verifications to detect delivery errors was tested with simulated data. The dosimetric characteristics of delivery errors were compared to patient-specific clinical IMRT verifications. For the clinical verifications, the NAT index and percent of pixels failing the gamma index were exponentially distributed and dependent upon the measurement phantom but not the treatment site. Delivery errors affecting all beams in the treatment plan were flagged by the NAT index, although delivery errors impacting only one beam could not be differentiated from routine clinical verification discrepancies. Clinical use of this system will flag outliers, allow physicists to examine their causes, and perhaps improve the level of agreement between radiation dose distribution measurements and calculations. The principles used to design and evaluate this system are extensible to future multidimensional dose measurements and comparisons. ^

An overview of China's one child policy and health consequences on society

In 1979, China implemented the one child policy to stifle the burden of the massive demographic growth cast on the future economic development and quality of living conditions. At the time, a quarter of the world's population resided in China and occupied only 7 percent of the world's arable land (The World Factbook, 2006). The government set the target total population to about 1.4 billion for the year 2010 and to significantly reduce the natural increase rate. First this overview paper will describe population demographics and economy of China's society. This paper will also investigate what the one child policy entails and how it is implemented. Furthermore, the consequences of the policy in regard to population growth, sex ratio, marital discrepancies, adverse health of mother and child, aging population, and pension coverage will be examined. Finally, future recommendations and an alternative policy will be postulated to increase the effectiveness of the policy and improve its effects on health. ^

Leukemia and occupational exposure to electromagnetic fields: An incident case-control study

The existence of an association between leukemia and electromagnetic fields (EMF) is still controversial. The results of epidemiologic studies of leukemia in occupational groups with exposure to EMF are inconsistent. Weak associations have been seen in a few studies. EMF assessment is lacking in precision. Reported dose-response relationships have been based on qualitative levels of exposure to EMF without regard to duration of employment or EMF intensity on the jobs. Furthermore, potential confounding factors in the associations were not often well controlled. The current study is an analysis of the data collected from an incident case-control study. The primary objective was to test the hypothesis that occupational exposure to EMF is associated with leukemia, including total leukemia (TL), myelogenous leukemia (MYELOG) and acute non-lymphoid leukemia (ANLL). Potential confounding factors: occupational exposure to benzene, age, smoking, alcohol consumption, and previous medical radiation exposures were controlled in multivariate logistic regression models. Dose-response relationships were estimated by cumulative occupational exposure to EMF, taking into account duration of employment and EMF intensity on the jobs. In order to overcome weaknesses of most previous studies, special efforts were made to improve the precision of EMF assessment. Two definitions of EMF were used and result discrepancies using the two definitions were observed. These difference raised a question as to whether the workers at jobs with low EMF exposure should be considered as non-exposed in future studies. In addition, the current study suggested use of lifetime cumulative EMF exposure estimates to determine dose-response relationship. The analyses of the current study suggest an association between ANLL and employment at selected jobs with high EMF exposure. The existence of an association between three types of leukemia and broader categories of occupational EMF exposure, is still undetermined. If an association does exist between occupational EMF exposure and leukemia, the results of the current study suggest that EMF might only be a potential factor in the promotion of leukemia, but not its initiation. ^

Spit & lies: Does social desirability predict smoking cessation success?

This study examines the role of socially desirable responding (SDR) on smoking cessation program success. SDR is the tendency for individuals to give responses that put themselves in what they perceive to be a socially desirable light. ^ This research is a secondary analysis of data from Project Cognition, a study designed to examine the associations between performance on cognitive assessments and subsequent relapse to smoking. Adult smokers (N=183) were recruited from the greater Houston area to participate in the smoking cessation study. In this portion of the research, participants' smoking status was assessed on their quit day (QD), one week after QD, and four weeks after QD. Primary outcome measures were self-reported relapse, true cessation determined by biological measure, discrepancies between self-reported smoking status and biological assessments of smoking, and dropping out. ^ Primary predictor measures were the Balanced Inventory of Desirable Responding (BIDR) and self-reported motivation to quit smoking. The BIDR is a 40-item questionnaire that assesses Self-deceptive Enhancement (SDE; the tendency to give self-reports that are honest but positively biased) and Impression Management (IM; deliberate self-presentation to an audience). Scores were used to create a dichotomous BIDR total score group variable, a dichotomous SDE group variable, and a dichotomous IM group variable. Participants at one standard deviation above the mean were in the "high" group, and scores below one standard deviation were in the "normal" group. In addition, age, race, and gender were analyzed as covariates. ^ The overall findings of this study suggest that in the general population BIDR informs participants' self-reports and the IM and SDR subscales inform participants' behavior. BIDR predicted self-reported relapse in the general population and trended toward indicating that a participant will claim smoking cessation success when biological measures indicate otherwise. SDE interacted with motivation to predict biologically verified cessation success. There was no main effect for BIDR, IM, or SDE predicting drop out; however, IM interacted with age to predict participants' likelihood of drop out. Used in conjunction, the BIDR, IM subscale, and SDR subscale can be used to more accurately tailor smoking cessation programs to the needs of individual participants.^