Food inspection forecasting to optimize inspections with analytics

According to the CDC, 1 in 6 Americans develops a food borne illness annually, which results in over 3,000 deaths per year. The estimated economic impact of these illnesses are up to $77 billion per year and as few as 2.9% of those who become sick seek medical care and most do not report their illness.

There are over 15,000 food establishments across the City of Chicago that are subject to sanitation inspections by the Chicago Department of Public Health (CDPH) with 36 sanitarians responsible for inspecting these establishments. The CDPH has systematically collected the results of nearly 100,000 sanitation inspections posted on the City’s Open Data Portal; meanwhile, other City departments have collected data on 311 complaints business characteristics, and other information also posted on the portal.

With this information, the City of Chicago’s Department of Innovation and Technology (DoIT), in collaboration with an insurance company, and the CDPH, together developed advanced analytics to forecast food establishments that are most likely to have critical violations, which are most likely to contribute to food borne illness, so that they may be inspected first. The code is written in the free and open source statistical modeling software.

The result is that food establishments with critical violations are more likely to be discovered earlier by the CDPH sanitarians. Food establishments with critical violations were discovered over one week earlier during a two-month evaluation. The formulation of these new strategies fit within the constructs of existing rules and regulations that add order for the allocation of inspectors to prioritized food establishments.