This study presents a novel approach to tracking changes in health service use in Kenya using geostatistics to compensate for imperfect data from a national health management information system (HMIS). The researchers analyzed monthly attendance records from 1,271 government-run and 402 faith-based outpatient facilities between 1996 and 2004. By employing a space-time geostatistical model, they were able to estimate robust time series of mean outpatient utilisation at both national and provincial levels. The results revealed a significant decline in outpatient use from 1996 to 2002, followed by a dramatic increase from 2003 onwards. This pattern was consistent across different causes of attendance and was observed in all six major provinces. The study highlights the potential of geostatistical methods to enhance the capacity of decision-makers to monitor nationwide patterns of service use and assess the impact of health policy changes.This study presents a novel approach to tracking changes in health service use in Kenya using geostatistics to compensate for imperfect data from a national health management information system (HMIS). The researchers analyzed monthly attendance records from 1,271 government-run and 402 faith-based outpatient facilities between 1996 and 2004. By employing a space-time geostatistical model, they were able to estimate robust time series of mean outpatient utilisation at both national and provincial levels. The results revealed a significant decline in outpatient use from 1996 to 2002, followed by a dramatic increase from 2003 onwards. This pattern was consistent across different causes of attendance and was observed in all six major provinces. The study highlights the potential of geostatistical methods to enhance the capacity of decision-makers to monitor nationwide patterns of service use and assess the impact of health policy changes.