Big Data Analytics Capabilities and Performance of Private Hospitals in Nairobi City County, Kenya

Jeremiah Wakhungu Kelvin^1, and Mutuku Morrisson¹

¹Department of Management Science, School of Business, Economics and Tourism, Kenyatta University

Cite this paper:
Jeremiah Wakhungu Kelvin and Mutuku Morrisson. Big Data Analytics Capabilities and Performance of Private Hospitals in Nairobi City County, Kenya. Journal of Business and Management Sciences. 2023; 11(3):169-175. doi: 10.12691/jbms-11-3-1

Abstract

This study explored how big data analytics and performance of private hospitals is related. Private hospitals in Kenya is very vital in provision of healthcare services. Kenya has established itself as a medical hub in East African nations due to the number of quality affordable hospitals facilities it has impressed. Growth and rise in economy in the region has also contributed on private hospitals expansion to cater for the high demand quality affordable healthcare services. Big data analytics has transformed conventional ways of business operations through its advanced analytic technological tools. Big data analytics, the process of identifying patterns, correlations, and trends in massive amounts of unstructured data to assist in the data-driven decision-making not only gathers and analyze data but also provide insights by efficiently utilizing available talent resources, technology, and data through firm’s wide roles. While playing a vital role in enhancing healthcare and improving people's lives, most private hospitals have been experiencing performance bottlenecks. The general objective of the study was to establish the relationship of big data and performance of private hospitals in Nairobi County, Kenya. The specific objectives for the study were to establish how big data technology capability, service responsiveness, financial measures and services quality relates to performance of private hospitals. This study was guided by four theories namely, Adaptive Structuration Theory, Diffusion of Innovation Theory, Dynamic Capabilities Theory and Resource Based View. The study adopted descriptive research design. The target population for the study was 120 participants. A census survey was conducted, and all 120 staff members of private hospitals were required to participate. To gather primary data, both open-ended and closed-ended questionnaires were used. The study used the pick-and-drop approach to gather its data. While Cronbach's Alpha was used to assess reliability, content validity was used to assess the questionnaire's validity. Using SPSS Version 26, descriptive and inferential statistics were used to examine the quantitative data, while content analysis was used to study the qualitative data. Frequency distribution tables and percentages were used to display descriptive statistics. Regression and other inferential analysis were used to analyze the relationships between the independent and dependent variables. All ethical requirements, particularly secrecy, anonymity, permission, and avoiding prejudice, were followed. The study revealed that there was a strong significant correlation between big data capability and performance, a strong significant correlation between service responsiveness and performance, a strong significant correlation between financial measures and performance and a medium correlation between service quality and performance. The study concluded that big data analytics capabilities and performance of private hospitals was indeed related and this was attributed to patient satisfaction, high quality, and cost effective patient services. It was recommended that private hospitals should focus on financial measures and its KPIs, service quality delivery strategies and adoption of new technology that brings change to organizations through various organization investments. The researcher proposed conducting more research.

Keywords:
big data analytics technology service responsiveness financial measures service quality

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