In rare disease physician targeting, a major challenge is how to identify physicians who are treating diagnosed or underdiagnosed rare diseases patients. Rare diseases have extremely low incidence rate. For a specified rare disease, only a small number of patients are affected and a fractional of physicians are involved. The existing targeting methodologies, such as segmentation and profiling, are developed under mass market assumption. They are not suitable for rare disease market where the target classes are extremely imbalanced. The authors propose a graphical model approach to predict targets by jointly modeling physician and patient features from different data spaces and utilizing the extra relational information. Through an empirical example with medical claim and prescription data, the proposed approach demonstrates better accuracy in finding target physicians. The graph representation also provides visual interpretability of relationship among physicians and patients. The model can be extended to incorporate more complex dependency structures. This article contributes to the literature of exploring the benefit of utilizing relational dependencies among entities in healthcare industry.
"When you are told your child has congenital heart disease it is scary, overwhelming and can sometimes cause you to feel isolated from loved ones that don't understand the emotional stress a diagnosis with so many unknowns can cause," Parman said. Facing the fear "alongside someone who's already walked that path gives both parties a sense of strength and encouragement," she said.
The Supreme Court is considering making a rare apology to former leprosy patients for the past practice of trying them outside standard courtrooms for fear of infection, sources close to the matter said Thursday. The top court aims to finalize its plan at a meeting of all 15 justices of the bench and apologize publicly in a report to be released soon, according to the sources. The envisioned move, however, would have no bearing on individual cases, and is not expected to pave the way for any retrials. Under Japan law, trials can be held outside court buildings if the Supreme Court finds it necessary. Such special courts were convened in 95 cases between 1948 and 1972 at isolated sanatoriums and other facilities for leprosy patients, according to the Supreme Court.
To provide insight into patient-level disease dynamics from data collected at irregular time intervals, this work extends applications of semi-parametric clustering for temporal mining. In the semi-parametric clustering framework, Markovian models provide useful parametric assumptions for modeling temporal dynamics, and a non-parametric method isused to cluster the temporal abstractions instead operating on the original data. Our contribution extends abstraction to continuous-time Markov models and the clustering componentto the non-parametric Bayesian setting, which does not require the number of clusters to be indicated a priori.