Modern healthcare produces a staggering amount of heterogeneous data. Data analytics in healthcare helps to spin this data into valuable insights for better decision making. The benefits can range from improving diagnosis accuracy to reducing cost of healthcare processes. The global data analytics healthcare market is set to reach a figure of $96.90 billion growing at a CAGR of 15.3% . We will learn how data analytics is transforming healthcare shortly. Before that, let’s understand the common source of data in the healthcare processes.
Common Data Points for Data Analytics in Healthcare
Electronic Health Records (EHR)
EHRs are the goldmine of patient data consisting of demographics, patient history, lab reports, imaging reports, and vital signs. They help to identify a pattern in a patient’s ailments and also segregate patients demographically based on age, location, gender etc.
Administrative Systems
Administrative systems within healthcare play a crucial role in providing valuable data for healthcare analytics. These systems, including appointment scheduling systems that monitor patient appointments, cancellations, and no-shows, billing and coding systems that record diagnoses, procedures, and charges, and pharmacy records tracking medication dispensing and refills, serve as essential data points for analyzing operational efficiency, financial performance, and patient care quality within healthcare organizations.
Clinical Support Systems
Clinical support systems are integral data sources for healthcare analytics, offering valuable insights for improving patient care and operational efficiency. These systems include Computerized Physician Order Entry (CPOE), which logs physician orders for medications, tests, and procedures, Decision Support Systems (DSS) that offer clinical recommendations guided by patient data and evidence-based guidelines, and Telehealth platforms that gather data from remote patient monitoring and virtual consultations. Leveraging data from these clinical support systems enables healthcare providers to enhance decision-making, optimize treatment plans, and deliver more personalized care to patients.
Medical Devices and Wearables
Medical devices and wearables play a crucial role in providing valuable data for healthcare analytics. These devices, including physiological monitors that monitor vital signs such as heart rate, blood pressure, and oxygen saturation, imaging equipment that produces images like X-rays, MRIs, and CT scans, as well as glucometers and fitness trackers that capture data on blood sugar levels, activity levels, and sleep patterns, serve as essential sources of information for analyzing patient health, tracking progress, and enhancing personalized healthcare interventions.
Facility Management System
Facility Management Systems provide valuable data for healthcare analytics, encompassing building automation systems that monitor energy consumption, temperature control, and equipment usage, as well as security systems that oversee access control and security incidents. In addition to these systems, other data sources such as patient satisfaction surveys offering insights into patient experience and care quality, and social media sentiment analysis reflecting public perceptions of the healthcare facility, contribute to a comprehensive dataset for analyzing operational efficiency, patient satisfaction, and overall performance within healthcare facilities.
How Data Analytics is Transforming Healthcare
Data analytics offers visualization and has the potential to enhance patient access to services while reducing costs. Following are the primary applications of data analytics in the healthcare sector:
1. Clinical decision support
Utilizing data analytics in healthcare enhances diagnostic accuracy and treatment effectiveness by providing evidence-based decision support for clinical teams. Rather than depending solely on intuition or judgment, professionals benefit from data-driven insights that expedite the diagnostic process and ensure optimal patient care. In the face of workforce shortages and heavy workloads, data analytics plays a crucial role in identifying possible diagnoses and effective treatments, with features like point-of-care generative AI swiftly analyzing extensive datasets to uncover valuable insights, including rare medical conditions.
2. Operational efficiency
Enhancing operational efficiency is a key application of data analytics in healthcare. Data analytics excels at simultaneously tracking the various components within a healthcare network. Hospitals require available beds for incoming patients and a sufficiently robust staff to manage patient volumes effectively. By utilizing an analytics platform, healthcare systems can streamline hospital operations, optimizing resource allocation and improving overall efficiency.
3. Financial management
In healthcare, financial management is a critical application of data analytics. Given the narrow operating margins, financial efficiency holds heightened significance in the industry. Data analytics plays a pivotal role in providing insights into program costs and revenue generation. By leveraging an analytics platform, organizations gain a comprehensive view of their performance, enabling streamlined billing processes, optimized insurance claims management, and enhanced financial planning capabilities.
4. Population health management
Utilizing data analytics in healthcare for population health management is crucial for addressing public health challenges. Data plays a vital role in measuring and monitoring complex public health issues, making it a critical tool in this domain. Advanced data platforms integrate census data and non-clinical sources to enrich healthcare organizations’ datasets with real-world information. By incorporating insights into social determinants of health (SDoH), such as food insecurity and transportation barriers, healthcare systems can uncover innovative and holistic interventions that extend beyond traditional hospital settings.
5. Treatment personalization
In healthcare, data analytics plays a pivotal role in personalizing treatments for patients. Healthcare organizations utilize data to stratify patients, pinpointing those with chronic illnesses or at risk of developing them. Moreover, data serves as a crucial tool for enhancing diagnostic accuracy. An article in the JCO Clinical Cancer Informatics journal illustrates how advanced data models can recommend specific drugs and treatment paths tailored to an individual patient’s disease profile. By merging healthcare providers’ expertise with data-driven insights, organizations blend human empathy with digital discoveries to deliver personalized and effective care.
6. Manage supply chain costs
Optimizing supply chain costs in healthcare is a vital application of data analytics. Hospitals manage extensive supply chains where timely deliveries are crucial for patient care. Data analytics plays a pivotal role in enhancing supply chain efficiency by monitoring key metrics, ensuring timely deliveries, and ultimately saving lives while reducing costs. By leveraging data-driven insights, healthcare facilities can streamline their supply chain operations, improve resource allocation, and enhance overall operational efficiency.
7. Enhance security and prevents fraud
Strengthening security and combating fraud in healthcare is a critical application of data analytics. Hospital databases are prime targets for cybercriminals, posing risks of revenue loss and compromising patient confidentiality. Data analytics plays a crucial role in safeguarding healthcare systems by analyzing network traffic patterns and detecting anomalies indicative of potential cyber threats. By proactively monitoring and identifying suspicious online activities, data analytics helps prevent fraud, protect sensitive patient information, and fortify the security infrastructure of healthcare organizations.
Conclusion
Data analytics in healthcare is accelerating different healthcare workflows by improving the efficiency with accurate information. Doctors are able to look beyond what deflects the natural eye and make important treatment decisions. The loopholes in various healthcare systems are exposed through appropriate data visualization tools leaving scope for improving speed or cost. Asset tracking and management is enhanced with proper inventory management driven by data leading to a decline in wastage or delay in supply. Analytics helps to put the ear closer to the beneficiaries of the healthcare system and improve their experience.
