Deploying machine learning with messy, real world data in low- and middle-income countries: Developing a global health use case.

The rapid emergence of machine learning in the form of large-scale computational statistics and accumulation of data offers global health implementing partners an opportunity to adopt, adapt, and apply these techniques and technologies to low- and middle-income country (LMIC) contexts where we work. These benefits reside just out of the reach of many implementing partners because they lack the experience and specific skills to use them. Yet the growth of available analytical systems and exponential growth of data require the global digital health community to become conversant in this technology to continue to make contributions to help fulfill our missions.

Understanding and valuing the broader health system benefits of Uganda's national Human Resources for Health Information System investment.

Background: To address the need for timely and comprehensive human resources for health (HRH) information, governments and organizations have been actively investing in electronic health information interventions, including in low-resource settings. The economics of human resources information systems (HRISs) in low-resource settings are not well understood, however, and warrant investigation and validation.

Case Description: This case study describes Uganda's Human Resources for Health Information System (HRHIS), implemented with support from the US Agency for International Development, and documents perceptions of its impact on the health labour market against the backdrop of the costs of implementation.

An informatics agenda for public health: summarized recommendations from the 2011 AMIA PHI Conference.

The AMIA Public Health Informatics 2011 Conference brought together members of the public health and health informatics communities to revisit the national agenda developed at the AMIA Spring Congress in 2001, assess the progress that has been made in the past decade, and develop recommendations to further guide the field. Participants met in five discussion tracks: technical framework; research and evaluation; ethics; education, professional training, and workforce development; and sustainability. Participants identified 62 recommendations, which clustered into three key themes related to the need to (1) enhance communication and information sharing within the public health informatics community, (2) improve the consistency of public health informatics through common public health terminologies, rigorous evaluation methodologies, and competency-based training, and (3) promote effective coordination and leadership that will champion and drive the field forward.