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Failure to complete recommended diagnostic tests may increase the risk of diagnostic errors.

Colorectal cancer is the most commonly occurring cancer in Germany, and the second and third most commonly diagnosed cancer in women and men, respectively. In this context, evidence-based guidelines positively impact the quality of treatment processes for cancer patients. However, evidence of their impact on real-world patient care remains unclear. To ensure the success of clinical guidelines, a fast and clear provision of knowledge at the point of care is [...]

The purpose of this study was to understand the ethical, legal, and social issues described by parents of children with known or suspected genetic conditions that cause intellectual and developmental disabilities regarding research use of their child's electronic health record (EHR).

Development of systematic approaches for understanding and assessing data quality is becoming increasingly important as the volume and utilization of health data steadily increases. In this study, a taxonomy of data defects was developed and utilized when automatically detecting defects to assess Medicaid data quality maintained by one of the states in the United States.

We propose a one-shot, privacy-preserving distributed algorithm to perform logistic regression (ODAL) across multiple clinical sites.

As the efficacy of artificial intelligence (AI) in improving aspects of healthcare delivery is increasingly becoming evident, it becomes likely that AI will be incorporated in routine clinical care in the near future. This promise has led to growing focus and investment in AI medical applications both from governmental organizations and technological companies. However, concern has been expressed about the ethical and regulatory aspects of the application of AI in [...]

Electronic consultations (e-consults) are clinician-to-clinician communications that may obviate face-to-face specialist visits. E-consult programs have spread within the US and internationally despite limited data on outcomes. We conducted a systematic review of the recent peer-reviewed literature on the effect of e-consults on access, cost, quality, and patient and clinician experience and identified the gaps in existing research on these outcomes.

Current machine learning models aiming to predict sepsis from electronic health records (EHR) do not account 20 for the heterogeneity of the condition despite its emerging importance in prognosis and treatment. This work demonstrates the added value of stratifying the types of organ dysfunction observed in patients who develop sepsis in the intensive care unit (ICU) in improving the ability to recognize patients at risk of sepsis from their EHR [...]

To (1) use an elastic net (EN) algorithm to derive a frailty measure from a national aged care eligibility assessment program; (2) compare the ability of EN-based and a traditional cumulative deficit (CD) based frailty measures to predict mortality and entry into permanent residential care; (3) assess if the predictive ability can be improved by using weighted frailty measures.

Memorial Sloan Kettering Cancer Center has more than a decade's experience creating online interfaces for obtaining data from patients as part of routine clinical care. We have developed a set of "golden rules" for design of these interfaces. Many relate to the knowledge imbalance between professional staff (whether medical or informatics) and patients, who are often old and sick and have limited knowledge of technology. Others relate to the clinical [...]