Are you aware that the healthcare data collected in the last few years is more than the total healthcare information generated throughout human history? Today, a single patient generates as much as 80 megabytes of data annually in EMR and imaging data. By 2025, it is believed that the yearly growth rate of healthcare data will go up by 36%.
Look at this growth rate; you will realize that it’s much faster compared to the number projected for other industries, like media and entertainment, manufacturing, or financial services. Following an explosive couple of years of contact tracing, virus testing, outbreak tracking, medical research, and remote work, one can assume that the healthcare industry produces more information than the organizations protecting it can handle.
This mind-boggling amount of data must be stored, analyzed, and processed for them to be functional. This is the main task of data collectors; unfortunately, modern technologies are struggling to handle such volumes of data. Forbes reports that almost 95% of businesses have problems managing data.
What role does data collection play in providing better quality patient care?
Data collection refers to gathering, analyzing, and leveraging this data for patient documentation. This allows patient-related information to be available immediately for use. Good-quality data is needed for superior patient care. Every individual must be able to access this information to manage his conditions better. Likewise, the entire care team must have access to the most recent patient data to provide the best possible treatment and care.
Well-informed decisions: Accurate and error-free medical data leads to superior decision-making. If one cannot access correct data, doctors and medical organizations cannot understand patient needs. Doctors, insurers, and caregivers must have quick access to secure data in order to save lives.
Use of artificial intelligence (AI): AI as part of healthcare has been there for years, and now, it can help in patient data collection. Leveraging AI helps providers in different aspects of patient care. AI solutions can process and store large chunks of data. The more data to analyze, the faster and more accurately it’s done by AI tools, which can then offer suggestions.
Cost cutting: According to a study by McKinsey, efficient healthcare data collection can save the American medical industry a whopping $300 billion annually! The importance of data accuracy in healthcare is greater where individual healthcare is concerned. For hospitals, detailed diagnosis and comprehensive treatment lead to better outcomes and reduced costs. When huge volumes of complex data are stored in one place, it reduces the number of repeat visits by patients to doctors and helps to avoid unnecessary readmissions.
Easier integration: Storage of healthcare data in a single system ensures that all healthcare participants cooperate to boost the quality of services. It eases the problems of data sharing without compromising data security. Earlier, all records used to be stored in one facility. An individual had to visit it physically to get access to it. This was secure, but it slowed down the treatment. Nowadays, healthcare providers have access to a patient’s entire medical history. They can come up with a better treatment plan much faster.
Outbreak prevention: Data accuracy can prevent epidemics even before these take place. Data analysis with sophisticated tools helps doctors and epidemiologists detect risk factors across locations and groups. A shared database ensures that preventive measures can be taken on time to save lives, especially for those populations that are at risk.
This tells you why data collection and analysis are vital for managing patient care, whether for public, personal, or governmental matters. Proper data collection and management can guarantee better patient engagement and superior treatment plans, and save the industry valuable resources.