MRC was predictive of patients' potential for ADEs and unplanned hospital readmission. MRC may be useful in identifying patients that would benefit from additional transitional care interventions. Results indicate that simplifying medication regimens may favorably impact postdischarge outcomes.

Even though research interest is typically greatest for questions pertaining to central tendency and, to a lesser degree, variability, knowledge about the nature of a measure or variable is impoverished when information about the shape of the frequency distribution is ignored. This paper makes the point that descriptive and inferential measures of non-normality should be a routine part of research reporting, along with graphic displays of the frequency distribution of important variables. This point is especially true for research involving measures with non-arbitrary metrics where the shape of the distribution is not affected by measurement artifacts.

Complex medication regimens at hospital admission are predictive of rehospitalizations for ADEs. This finding suggests that medication regimen complexity be considered as a target for interventions to decrease the risk for readmission.

Older adults often suffer from functional impairments that affect their ability to perform everyday tasks. To detect the onset and changes in abilities, healthcare professionals administer standardized assessments. Recently, technology has been utilized to complement these clinical assessments to gain a more objective and detailed view of functionality. In the clinic and at home, technology is able to provide more information about patient performance and reduce subjectivity in outcome measures. The timed up and go (TUG) test is one such assessment recently instrumented with technology in several studies, yielding promising results towards the future of automating clinical assessments. Potential benefits of technological TUG implementations include additional performance parameters, generated reports, and the ability to be self-administered in the home. In this paper, we provide an overview of the TUG test and technologies utilized for TUG instrumentation. We then critically review the technological advancements and follow up with an evaluation of the benefits and limitations of each approach. Finally, we analyze the gaps in the implementations and discuss challenges for future research towards automated, self-administered assessment in the home.