Effects of Digital Health Technologies on the Operational Efficiency of Pharmaceutical Firms in Nairobi County

Abstract

The general objective of the study was to examine the effects of digital health technologies on operational efficiency in Kenya's pharmaceutical firms in Nairobi County. The study sought to address the following specific objectives: Firstly, to establish the effects of quality assessment technologies on operational efficiency in pharmaceutical firms in Nairobi County, secondly to analyze the effects of health information technologies on operational efficiency in pharmaceutical firms in Nairobi County, and finally, assess the effects of automation technologies in pharmacy operations on operational efficiency in pharmaceutical firms in Nairobi County. The study adopted a descriptive research design. The target population for this study was the pharmaceutical firms in Nairobi County. The sampling frame was retrieved from the records of the Pharmacy and Poisons Board with business operations in Nairobi County. Simple sampling technique was utilized in accessing 133 respondents from the selected pharmaceuticals. The study used primary data which was through a structured questionnaire and administered via Survey Monkey. Through SPSS Version 24.0, data analysis entailed descriptive and inferential statistics which entailed Pearson Correlation Coefficient and Simple Linear Regression. Data output was presented in the form of tables and figures. The study revealed that pharmacy utilizes technology to enhance patient information sharing (𝑀 = 3.80, 𝑆𝐷 = 0.95) implying that on average, the pharmaceutical sector is moderately inclined towards using technology for improving the sharing of patient information. The relatively low standard deviation indicates that the responses are relatively consistent, with limited variation in the perception of the pharmacy staff regarding the use of technology in this context. Linear regression analysis showed that that quality assessment technologies explain 60.9% of the variation in operational efficiency, which statistically and significantly influenced operational efficiency in pharmaceutical firms in Nairobi County (𝑅2 = .609, (105) = 13.089, 𝑝 < .05). ANOVA (F = 159.842, p < 0.001) shows quality assessment technologies significantly explain operational efficiency variation in pharmaceutical firms. With regard to the effect of health information technologies revealed that the pharmacy had invested in a management information system which has enabled the minimization of administrative costs (𝑀 = 3.70, 𝑆𝐷 = 0.94). This suggests that, on average, the pharmacy Perceives that the utilization of this system has led to a reduction in administrative costs. The relatively low standard deviation indicates that there is relatively little variation in the perception of the pharmacy staff regarding the cost-saving benefits of the management information system. Linear regression analysis showed that that health information technologies explain 68.2% of the variation in operational efficiency, which statistically and significantly influenced operational efficiency in pharmaceutical firms in Nairobi County (𝑅2 = .682, (105) = 17.936, 𝑝 < .05). ANOVA (F = 218.561, p < 0.001) shows health information technologies significantly explain operational efficiency variation in pharmaceutical firms. Regarding the effect of automation technologies the study revealed that decision support system (DSS) is employed across all the core functions in the pharmacy (𝑀 = 4.16, 𝑆𝐷 = 0.94). This indicates that, on average, the pharmacy heavily relies on automation technologies, specifically the DSS, to support decision-making in all its essential operations. The relatively low standard deviation suggests that there is limited variation in the perception of the pharmacy staff regarding the utilization of the DSS across different functions. Linear regression analysis showed that that automation technologies explain 53.9% of the variation in operational efficiency, which statistically and significantly influenced operational efficiency in pharmaceutical firms in Nairobi County (𝑅2 = .539, (105) = 9.707, 𝑝 < .05). ANOVA (F = 120.562, p < 0.001) shows automation technologies significantly explain operational efficiency variation in pharmaceutical firms. In conclusion, this study has brought to fore that there is positive impact of Quality Assessment Technologies (QATs) on operational efficiency in pharmaceutical firms. The findings emphasize the importance of common management systems, staff training, and quality control measures to improve efficiency and provide superior services. Health information technologies have the potential to enhance operational efficiency, but improvements in financial support and staff training are necessary. The implementation of information management systems positively influences pharmacist performance. Automation technologies significantly improve operational efficiency, reducing errors and costs while improving communication. Embracing automation in key processes can greatly benefit pharmaceutical firms and enhance patient outcomes. Overall, technology plays a valuable role in enhancing efficiency and quality in the pharmaceutical industry. The study thus for improving operational efficiency in pharmaceutical firms include staff training on quality assessment systems, implementing standardized processes, and utilizing technology software. Investment in emerging pharmacy management systems and continuous evaluation of communication systems are advised. Adoption of automation technologies, such as electronic record-keeping and decision support systems, is recommended. Further research should explore the impact of digital health technologies on patient outcomes, cost effectiveness, job satisfaction, and well-being of healthcare workers. Longitudinal studies can assess sustainability and inform strategies for effective use of these technologies in the pharmaceutical industry.