Vol. 2012 No. 1 (2012)

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Time-Series Forecasting Model for Measuring Adoption Rates in District Hospitals Systems: A Methodological Evaluation of South African Context,

Fani Nkosi, University of Zululand Sipho Mkhize, Graduate School of Business, UCT
DOI: 10.5281/zenodo.18942718
Published: September 27, 2012

Abstract

The adoption rates of new healthcare technologies in South African district hospitals are critical for improving patient outcomes and resource management. The study employed a time-series analysis using an ARIMA (AutoRegressive Integrated Moving Average) model. Data were collected through surveys and official records. Adoption rates of electronic health record systems showed a consistent upward trend, increasing by approximately 15% over the two-year period. The ARIMA model provided reliable forecasts for adoption trends in district hospitals, indicating potential improvements with sustained intervention strategies. Further research should explore longer-term projections and incorporate additional variables such as financial incentives to enhance technology uptake. ARIMA model, time-series forecasting, healthcare technology, South Africa, district hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.

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How to Cite

Fani Nkosi, Sipho Mkhize (2012). Time-Series Forecasting Model for Measuring Adoption Rates in District Hospitals Systems: A Methodological Evaluation of South African Context,. African Journal of Community and Environmental Health, Vol. 2012 No. 1 (2012). https://doi.org/10.5281/zenodo.18942718

Keywords

African healthcare systemsGeographic Information Systems (GIS)Methodological evaluationTime-series analysisDistrict hospitalsForecasting modelsResource management

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Vol. 2012 No. 1 (2012)
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African Journal of Community and Environmental Health

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