Importance of data collection in healthcare
It’s mind boggling to think the amount of data produced in just the last few years surpasses the amount of data generated in our entire human history. For all this massive amount of data to be functional it needs to be processed, stored, and analyzed. That is the purpose of data collection. However, modern technologies have struggled to contend with the huge volumes of information, which has led to poor performance, lost revenues, and wasted time. According to Forbes, 95 percent of businesses have problems managing data and are looking for an effective solution.
Data collection in healthcare is the process of collecting, analyzing, and using the data for patient documentation and resources. This technology allows patient data to be immediately available system-wide and the collaborative efforts within any medical system can improve the accuracy of medical data collection.
Good quality patient data is essential to inform our clinical care and everyone should have access to information about their own healthcare to help manage their conditions. Your entire care team, whether in a clinic or hospital, needs to have access to the most current patient data collection about you and your healthcare history to inform your treatment, and to provide the best possible care.
Why is data important in healthcare?
Data collection is important because it allows providers to make more informed decisions about a patient's care. With applications designed for sharing patient data across channels, every care provider has all the information available to treat their patients. Continue reading to learn more about, why is data important in healthcare.
Market competitiveness
Community health is a complicated system that involves governments, hospitals, and third-party agencies like registries and health plans. Proper patient data collection may considerably improve the quality of services offered to patients and lead to improved market positions and greater revenues. To reach these results care providers need to use the latest data collection and analysis tools and specialized software offerings.
Well-informed decisions
The importance of accurate data in healthcare can’t be overstated and there are many reasons why doctors, patients, insurance plans, and other institutions need to keep their data collection in healthcare accurate. One of the main reasons is decision-making. What is patient information good for if providers and organizations can’t get the information they need to understand their patients’ needs? With the help of medical data collection tools, it is possible to quickly and effectively collect and evaluate patient data and results. Doctors, caregivers, insurance plans and more need to quickly exchange information securely, which can save lives and lead to better care.
Implementation of artificial intelligence (AI)
AI in healthcare has long since been introduced, and with its help, patient data collection can be more efficient and improve systems automatically. The AI technologies becoming ever present in everyday life are also being applied to healthcare. The use of AI has the potential to assist providers in many aspects of patient care and administrative processes. The importance of data collection in healthcare means saving lives and improving the quality of life, so companies and governments are doing their best to offer new solutions. Artificial intelligence has enough capacity to store, process, and analyze vast volumes of patient data. AI in healthcare can educate itself as it goes. The more data there is to learn from and analyze, the faster and more accurately AI tools can make suggestions. Even offering evidence from the data that supports a particular decision or suggestion.
Some software systems today have the ability to process a patient’s data across the healthcare system using proprietary medical algorithms and offer clinical decision support to the physician at the point of care. Using artificial intelligence in Healthcare like machine learning and natural language processing give care providers and health plans the ability to process the huge volumes of unstructured patient data that is inputted into EHR systems on a daily basis.
Reduction of costs
The importance of data collection in healthcare according to McKinsey’s study, published in the National Library of Medicine, reports efficient data collection in healthcare and analysis can save the U.S. medical industry $300 billion per year. The importance of accurate data in healthcare notably increases when individual healthcare is involved. For hospitals and other medical institutions, detailed and comprehensive diagnosis and treatment may lead not only to better results but also to lower costs.
For individuals, the importance of data collection in healthcare is also evident. The collection of complex patient data, and its storage in one place, can reduce the number of repeated visits to the doctor and help avoid unnecessary and costly readmissions.
Storage of all data in one place
There are still many companies and institutions which keep medical data collection in different storages. When patient data collection is kept in a particular system, all healthcare participants can cooperate and significantly improve the quality of provided services.
For example, HL7’s newest standard is Fast Healthcare Interoperability Resources (HL7 FHIR, pronounced HL7 “fire”). The goal of the FHIR data model, according to HL7, is to help ease the challenges of data sharing and interoperability by simplifying implementation without sacrificing information integrity. By having regulations define and require interoperability using the FHIR standard, we can expect a more unified and easier integration process across EHR applications and data collection systems over the next few years with HL7 “fire”.
Before the powerful database systems of today, records were kept inside a single facility that a person needed to visit and request their medical record. In a way it was good for privacy but could also be viewed as significantly slowing the healthcare industry’s development. When healthcare providers have access to a complete picture of a patient's health history, they can offer a thorough treatment plan. If the patient data is not shared between doctors, researchers, and hospitals, it holds back the development and can cost lives.
Outbreak prevention
One of the benefits of accurate data in healthcare is a chance to prevent epidemics before they happen. For example, a woman in California has unrelated symptoms that are treated separately. But with better tools that can analyse the data collection in healthcare, and offer suggestions, doctors may detect other people with the same unrelated symptoms in the area and prevent problems before they happen. With a shared database, doctors and epidemiologists may be able to notice risk factors and trends across different groups and locations. This can greatly help society and save lives, especially among at-risk populations.
Why are databases important in healthcare?
In the healthcare industry of today, staying current is extremely important. Using the latest products and information systems available doctors can collect needed patient data and chart concurrently at the point of care or shortly after. Fast and accurate database systems are critical to healthcare because they provide access to massive amounts of patient data information at the click of a mouse or the tap of a screen. The importance of accurate data in healthcare can mean the difference between life and death to that specific patient and to the larger collective of patients as a whole. Today, doctors at every moment of the care process need instant access to the most up to date and accurate patient information possible.
Healthcare data storage challenges
Some question the problems that arise in relation to the security of data collection in healthcare and these issues shouldn’t be dismissed. When deciding whether to implement a new data collection system or not, be sure to take these points into consideration.
Security of data
Protecting and keeping sensitive data secure has always been an important issue not only in the medical field. Companies have to face numerous laws and restrictions when it comes to data storage. For example, a stolen computer from an insurance company may result in a million-dollar fine. A good alternative for keeping data secure is turning to cloud-based storage since most if not all of the security issues are managed by the vendor.
Low data quality
One of the biggest challenges is the quality of patient data. Some database systems are far superior to others and costs vary greatly. Also consider the process of medical data collection itself. For example, handwritten and then scanned notes can be a relatively slow process and be prone to mistakes, creating low quality patient data.
Difficulties in collaboration
Doctors use different methods for entering patient data into their charts. Some use EHR systems, while others prefer traditional spreadsheets or even paper documents. Some physicians don’t allow others access to certain documents, and others grant access just to certain specialists. The way medical data is written also matters because not all doctors speak the same way. Every doctor has a unique style and vision. This makes it quite difficult to cooperate, especially virtually.
Final thoughts
The importance of data collection in healthcare cannot be understated because it helps professionals assess many different important factors. Whether used for personal, public, or governmental matters, data collection and analysis tools help to get a clearer picture of a patient’s health, manage information quickly, and share it with other providers. Effective collection and management of information can be a key to the engagement of patients, lead to better treatments and save the healthcare industry valuable resources.
For healthcare organizations looking to succeed in the transformation to value-based care delivery models, including the Medicare Advantage Program, ForeSee Medical is a specialized software platform for accurate Medicare risk adjustment. Through artificial intelligence like proprietary medical algorithms and natural language processing, ForeSee Medical optimizes HCC coding, empowering providers to positively influence health outcomes.