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By developing a number of measures distinguishing amount, type of content, and when and how that content is used, the current study revealed effective patterns of use that are associated with quality of life benefits during an eHealth intervention. Results generally suggest that the benefits depend on how a patient uses the system, far more than on sheer amount of exposure or even what type of content is chosen. The next generation of eHealth system should focus on providing new and varying content over time, but even more on encouraging intensity of use and long-term commitment to the system., The use of the Internet for health education has reached what many might consider a critical mass. According to the National Cancer Institute's Health Information National Trends Survey (Nelson et [...]

Legendary Ohio State University football coach Woody Hayes once quoted the great Michigan State University coach Duffy Daugherty as saying, 'There are three things that can happen when you pass [...]

Objective. To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources. Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods. A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection. For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results. Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions. A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. Key Words. Organizational change, Bayesian model, improvement, empirical evaluation, This paper describes the development of a short survey instrument and the creation of a companion Bayesian model that uses the survey data to predict the potential for successful implementation [...]

Health care practitioners were asked to identify and rank the obstacles that they are likely to encounter when trying to implement the total quality management (TQM) concept in their respective organizations. Health care professionals believed that the lack of proof that TQM could bring success was the greatest barrier to a successful TQM implementation. The study considered several factors that differentiated success from failure in innovation and improvement. Results of research work on innovations showed support for customer and quality mindedness. Future research work is recommended.

Systems thinking is a fundamental element of quality management and should be a fundamental element of health care reform. An implication of systems thinking is that one aim of health care should be to minimize the total costs of illness, not simply the direct medical expenditures. If we are to continue to improve health care over time, we should measure its impact on the total costs of illness to the patient, family, employer, and society. Thus a system of measurement is needed that quantifies total costs of illness and also suggests how these constituencies can collaborate to improve processes and reduce total costs. This article introduces the total costs of illness concept, contrasts it with societal costs of illness, describes a measurement system we developed to quantify it, and describes a case study examining the total costs of back injury illness to employers. We found that medical expenditures accounted for less than half of the total costs of illness, the average total costs of illness varied by over 350 percent among employers, and a simple metric (days off work) explained 62.5 percent of the variance in total costs of illness., Direct medical costs of an illness or injury comprise less than half of the total costs of that condition. The application of systems thinking to healthcare reform requires that other cost components be measured as well, including indirect costs to employers, patients, families and society. An industry/education research group developed a cost metric that analysed employer medical payouts, nonmedical payouts and lost opportunity costs to come up with total costs associated with back injury. The healthcare industry is encouraged to work with employers to ensure that improvement in the delivery of healthcare also reduces the total costs., 'Systems thinking' (Senge 1990) is one of the most important elements of quality management (QM). In fact, Deming (1989) identified systems thinking as one of the four sources of 'profound [...]

A study was done to evaluate the quality of psychiatric care using a Bayesian index. The Bayesian statistical methodology was patterned to predict a second panel's judgement quality and quality-related patient outcome, give an accurate measurement procedure and identify changes in patterns of emergency department practices. It was shown that the Bayesian quality index is valid and reliable in the determination of the quality of emergency psychiatric care., A primary purpose of emergency medical service systems is to ensure that the needs of the emergency victim are matched with the appropriate form of care, and to do so [...]