mHealth and global mental health: still waiting for the mH2 wedding?

BACKGROUND: Two phenomena have become increasingly visible over the past decade: the significant global burden of disease arising from mental illness and the rapid acceleration of mobile phone usage in poorer countries. Mental ill-health accounts for a significant proportion of global disability-adjusted life years (DALYs) and years lived with disability (YLDs), especially in poorer countries where a number of factors combine to exacerbate issues of undertreatment. Yet poorer countries have also witnessed significant investments in, and dramatic expansions of, mobile coverage and usage over the past decade. DEBATE: The conjunction of high levels of mental illness and high levels of mobile phone usage in poorer countries highlights the potential for "mH(2)" interventions--i.e. mHealth (mobile technology-based) mental health interventions--to tackle global mental health challenges. However, global mental health movements and initiatives have yet to engage fully with this potential, partly because of scepticism towards technological solutions in general and partly because existing mH(2) projects in mental health have often taken place in a fragmented, narrowly-focused, and small-scale manner. We argue for a deeper and more sustained engagement with mobile phone technology in the global mental health context, and outline the possible shape of an integrated mH(2) platform for the diagnosis, treatment, and monitoring of mental health. SUMMARY: Existing and developing mH(2) technologies represent an underutilised resource in global mental health. If development, evaluation, and implementation challenges are overcome, an integrated mH2 platform would make significant contributions to mental healthcare in multiple settings and contexts.

Emergency department crowding: prioritising quantified crowding measures using a Delphi study.

AimsEmergency department (ED) crowding has been associated with a number of negative health outcomes, including unnecessary deaths, increased waiting times and a decrease in care quality. Despite the seriousness of this issue, there is little agreement on appropriate crowding measures to assess crowding effects on ED operations. The objective of this study was to prioritise a list of quantified crowding measures that would assess the current state of a department.MethodsA three round Delphi study was conducted via email and an Internet based survey tool. The panel consisted of 40 professionals who had exposure to and expertise in crowding. Participants submitted quantified crowding measures which, through three rounds, were evaluated and ranked to assess participant agreement for inclusion.ResultsThe panel identified 27 measures of which eight (29.6%) reached consensus at the end of the study. These measures comprised: (1) ability of ambulances to offload; (2) patients who leave without being seen or treated; (3) time until triage; (4) ED occupancy rate; (5) patients' total length of stay in the ED; (6) time to see a physician; (7) ED boarding time; and (8) number of patients boarding in the ED.ConclusionsThis study resulted in the identification of eight quantified crowding measures, which present a comprehensive view of how crowding is affecting ED operations, and highlighted areas of concern. These quantified measures have the potential to make a considerable contribution to decision making by ED management and to provide a basis for learning across different departments.