A Study on the Effectiveness and Efficiency of Public or Private Hospitals within Pakistan

Noman Islam; Muhammad Usman Raees; Darakshan Syed

doi:10.33317/ssurj.588

Authors

Noman Islam KIET
Muhammad Usman Raees
Darakshan Syed

DOI:

https://doi.org/10.33317/ssurj.588

Keywords:

survey, public hospitals, machine learning, , random forest algorithm, effectiveness, efficiency

Abstract

Hospitals play a very important role in human lives. People are in search of quality and timely healthcare facilities. This paper talks about the efficiency and effectiveness of healthcare services. One needs to identify the factors and mechanisms to enhance the performance of government and private hospitals. This study aims to find the important variables that were required to find the best solution for public and private hospitals in Pakistan. The major contributions of the paper are as follows. The paper first deliberates on the need for technical excellence as compared to interpersonal excellence for hospital management. It also performs a qualitative review of the literature on the important variables for determining the effectiveness and efficiencies of the hospital. Then, the paper presents a public survey about the effectiveness and efficiency of public and private hospitals using different questionnaires. These questionnaires were filled by the relatives of patients or patients themselves when they visited hospitals. On this dataset, the paper applies a machine learning algorithm i.e., random forest, to predict which hospital type is suitable for them while considering the variables. These variables include; the services of the hospital, admission process, treatment, doctor's behavior, timely treatment, and knowledge of the staff about SOPs. The data was split into 75 % training and 25 % testing dataset. Python’s Library SK-learn was used for implementation. The accuracy of the classifier on the test dataset is 96.91 %. The paper then determines the variables that are contributing the most to the measure of effectiveness and efficiencies of hospitals. The algorithm also ranks these features that can be used to improve a hospital's performance. It also provides a benchmark to the patients in the selection of hospitals for healthcare facilities.

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