New Insights from Old Numbers: Artificial Intelligence Makes Sense of Health Ministry Data

By Casey Bishopp, Communications officer, IntraHealth InternationalSeptember 24, 2019Ministries of health have more data than ever before—and the amount of data is increasing at an exponential rate. But what good is all that information if it’s unwieldy or difficult to use? Over the course of nine weeks, IntraHealth International’s digital health team and staff from our Regional Health Integration to Enhance Services in Eastern Uganda (RHITES-E) project modeled a machine-learning approach to glean insights from the flood of health systems and population data available to the Ugandan ministry of health. What they found will help ministry officials make more strategic decisions about the support they allocate to health facilities—making questions around which facilities need what and when more clear-cut. “We collect vast amounts of data,” says Nicholas Matsiko, RHITES-E monitoring and evaluation manager.“This a big step in solving the data-rich-but-information-poor paradigm facing ministries of health.” Machine learning is an application of artificial intelligence that enables data systems to learn from experience without being directly programmed. When it’s applied in this way, machine learning helps clarify and summarize data, removing unhelpful variables from the data pool and highlighting those that are most informative.  After pu...
Source: IntraHealth International - Category: International Medicine & Public Health Authors: Tags: Digital Health Technology HRIS Human Resources Management Health Workforce & Systems Source Type: news