Cloud Based Data Analytics for Hospitals

Description:

Introduction

Cloud computing allows users to store data and use software through the Internet without managing physical hardware. Hospitals can access medical records, databases, and applications anytime and from anywhere. Cloud systems are flexible and scalable, so hospitals can increase or reduce resources based on patient needs. With cloud-based data analytics for hospitals, healthcare organizations analyze large volumes of data in real time, improve clinical decisions, and enhance patient care. Doctors and administrators use online tools to track trends, manage resources, and improve service quality. Overall, cloud-based analytics supports faster operations, better data accuracy, cost efficiency, and improved healthcare delivery.

Objective of the Study

• To identify why hospitals adopt cloud-based data analytics solutions.
• To examine the extent and areas of cloud analytics use in hospitals.
• To analyze the impact of cloud analytics on faster and better decision-making.
• To study the challenges hospitals face while adopting cloud analytics.
• To evaluate how cloud analytics improves hospital efficiency and service quality.

Research Design

Research design provides a clear plan for collecting and analyzing data. This study follows a descriptive research design to present a true picture of how hospitals use cloud-based data analytics. Descriptive research uses surveys and fact-finding methods to understand existing practices. The study also follows an ex post facto approach, where the researcher does not control any variables but observes current situations. Simple statistical tools such as averages and percentages were used to ensure objective and clear analysis.

Mode of Data Collection

The researcher used a survey method to study the relationship between cloud-based data analytics and hospital operations. The researcher designed a structured questionnaire to understand how hospitals adopt cloud systems, the benefits they experience, and the problems they face. This method helped the researcher collect direct responses from hospital professionals.

Population and Sample Size

The target population included hospital owners, managers, and decision-makers involved in cloud-related decisions. The study used purposive sampling to select knowledgeable respondents. A total of 50 respondents were chosen based on the study objectives.

Data Collections Methods

Primary data was collected through a questionnaire containing 15 multiple-choice questions.

• Generic questions covered hospital size, location, and awareness of cloud solutions.
• Objective-based questions focused on benefits, challenges, and decision-making factors.

Data Analysis Techniques

The researcher analyzed data using tables, percentages, bar charts, and pie charts to identify patterns, trends, and operational impacts.