Modeling the trend of patient attendance in primary health centre using least square method

  • Peters Nwagor
  • Joyce Adaobi Okoro


The study used least square model to investigated the patient attendance in Model Primary Health Centres (MPHCs) in Rivers State. With the application  of nonlinear regression models, whose parameters were determined with the least-squares method. It was found that a logarithmic nonlinear model  proved the best fit for the source data and the parameters α=40.460 and β= 1.270 gave rise to the model as N(t)= (40.458)(1.265)t , revealing an annual  increase rate of 26.5%. The model had 26.02% mean error, reflecting 73.98% accurate fit. The model was used to forecast the patients attendance from  2015-2020. An estimate of 346 patient attendance annual increases aimed the research to recommend for government’s expansion of health care  infrastructures, more health personnel should be adequately trained to meet the manpower need of the health institutions and that there should be  public awareness to encourage rural dweller to readily access the Model Primary Health care’s because a healthy nation is a wealthy nation and further  studies in the area of factors militating against patients’ accessibility to MPHCs in Rivers State was advocated. 


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eISSN: 2971-6632