As a new concept that emerged in the middle of 1990's, data mining can help researchers gain both novel and deep insights and can facilitate unprecedented understanding of large biomedical datasets. Data mining can uncover new biomedical and healthcare knowledge for clinical and administrative decision making as well as generate scientific hypotheses from large experimental data, clinical databases, and/or biomedical literature. This review first introduces data mining in general (e.g., the background, definition, and process of data mining), discusses the major differences between statistics and data mining and then speaks to the uniqueness of data mining in the biomedical and healthcare fields. A brief summarization of various data mining algorithms used for classification, clustering, and association as well as their respective advantages and drawbacks is also presented. Suggested guidelines on how to use data mining algorithms in each area of classification, clustering, and association are offered along with three examples of how data mining has been used in the healthcare industry. Given the successful application of data mining by health related organizations that has helped to predict health insurance fraud and under-diagnosed patients, and identify and classify at-risk people in terms of health with the goal of reducing healthcare cost, we introduce how data mining technologies (in each area of classification, clustering, and association) have been used for a multitude of purposes, including research in the biomedical and healthcare fields. A discussion of the technologies available to enable the prediction of healthcare costs (including length of hospital stay), disease diagnosis and prognosis, and the discovery of hidden biomedical and healthcare patterns from related databases is offered along with a discussion of the use of data mining to discover such relationships as those between health conditions and a disease, relationships among diseases, and relationships among drugs. The article concludes with a discussion of the problems that hamper the clinical use of data mining by health professionals.

Visit nonadherence, that is, "no shows," in psychiatry costs the US healthcare $100 billion every year. Nonadherent visits undermine healthcare quality improvement efforts and erode patients' health. Previous research has focused on patient demographics or on redundant scheduling, rather than on the actual structure of visit nonadherence. Drawing on a comprehensive literature review and a series of 3 studies, we identify 22 determinants that contribute to visit nonadherence. Significantly, 8 of these determinants seem to account for most of the variance in modeling visit nonadherence. This work lays the foundation to develop prognostic tools for reducing nonadherent visits in ambulatory care.

No abstract

Goal: Measures taken by healthcare organizations to address COVID-19 highlighted the long-standing lack of childcare infrastructure required to support healthcare workers. This study, designed to provide evidence to support operations at an academic medical center, looked at the influence that in-house and emergency childcare could have on the retention, recruitment, and productivity of healthcare workers. This study also outlined the implications that childcare, or its lack, has for healthcare organizations during and after the COVID-19 pandemic. Methods: We conducted a 35-question electronic employee survey (under institutional review board approval) during pandemic-induced public school closures, which included both quantitative and qualitative (write-in) questions. Principal Findings: The survey results showed that weekday on-site childcare was very or extremely important to more than half of survey respondents, the majority of whom were staff members (28%) or physicians (25%), followed by administrators (15%), researchers (12%), others (10%), nurses (5%), educators (2%), and residents (1%). Sixty percent of respondents reported that emergency on-site childcare was extremely important (34%) or very important (26%). Almost half (49%) reported that emergency childcare needs have disrupted their work in the past year, including canceling of clinics or surgical cases. Analysis of qualitative comments via a strategy based on coding and categorization showed that, when asked how childcare influences their work choices, employees responded that childcare availability has limited the hours or times they could work, that lack of childcare has prevented career growth, that they left a previous job or will leave their current job because of childcare needs, or that they stayed at a previous job or have remained in their current job longer because of the availability of childcare. Practical Applications: Although data from this mixed-methods study support findings in the literature that there is a need for in-house and emergency childcare, the data suggest that current employees at this academic medical center do not currently expect it, likely because such childcare is not generally available at most academic institutions. With increased rates of burnout and healthcare workers leaving the field since COVID-19, offering in-house and emergency childcare provides hospital systems with new opportunities to retain and recruit physicians, nurses, and staff, as well as to improve their well-being and productivity.