The healthcare sector breathes new life into patients every day the world over. Aiding this noble endeavor is healthcare data that acts like oxygen to a healthcare facility and the industry at large. And there’s plenty of help coming from it too, seeing that this sector constitutes 30% of the overall data generated globally by industries across niches. The CAGR for healthcare data is expected to be at 36% in 2025, more than any other sector.
The catch is that managing this data with all its complexities can be a true challenge unless there is accurate and timely medical data entry involved. The amount of Big Data that the industry can look forward to cannot be managed with conventional approaches. It will involve innovation on the side of stakeholders in the industry and regulatory authorities at all levels. Your healthcare facility should also adopt these innovative approaches toward your clinical data management, or you risk not just losing to the competition but also to patient care expectations.
Continue reading this blog to uncover the true significance of medical data and the challenges the industry faces today and the ones to come in the future. You will also learn the solutions you should adopt to mitigate or eliminate risks and the advantages of opting for external healthcare data entry service providers for it.
Why Healthcare Data Matters
Wrongful diagnosis is the third leading cause of death in the US, being the reason behind 10% of all deaths in the country annually. Incorrect patient data is behind many wrongful diagnoses, and it starts with the wrongful recording of patient data during coding. These deaths can be avoided with an accurate medical data recording system that considers a patient’s data from various sources, including personal wearable devices/health monitors. Data collected about the workload and stress levels of the medical staff at the facility, the status of important equipment used for diagnoses, and other pertinent data helps improve diagnostics. This way, patients can receive the right treatment and avoid deaths, while your facility can avoid litigations.
Greater Market Edge
A healthcare facility is also a business that needs to stay ahead of its competition to make the profits it needs to function and sustain. Healthcare data plays a large role in this as it provides concerned stakeholders with the insight they need into their business’s operations and personnel. With accurate medical data entry, stakeholders can determine how much to expand the beds per rising demand.
Data obtained from competition research will tell you what moves the competition is making to gain a better market share and how you can counter it. It can tell you what the needs of the market are by detailing the prevalent diseases and medical conditions, along with their intensity. This lets you formulate a better marketing strategy that brings more patients to your doorstep.
Better Predictions and Business Decisions
The healthcare sector is a tumultuous one with constantly changing dynamics. These include market, regulatory, and prevalent health adversities. Your facility must be ready to render the necessary treatment for possible outbreaks within a short period if necessary, and your facility must have everything in place for it. It is through clinical data abstraction and other data analysis methods that you can predict such happenstances and get everything in order.
For example, if you know from the analysis of different data you’ve gathered that this year’s flu season will be more intense, you can add more beds and hire temporary staff to handle the situation. This is better than not being prepared and having an influx of patients that you can’t manage, leading to a bad brand image and treatment outcomes. With accurate data analysis, you can also make quick decisions as the risks will be more clearly visible.
The medical industry is one of the biggest adopters and benefactors of the Artificial Intelligence revolution, with every aspect of it being affected. And you cannot develop an AI without large volumes of accurate data. Pharmaceutical manufacturing, inventory, and supply chain can be better managed with an AI model developed using the large quantities of data generated by the same.
Medical research institutes can gain better insights into possible cures and the many diseases/ pathogens they are working on. Hospitals and clinics can better diagnose and treat patients while simultaneously coding patient data more efficiently. The institute’s administration can offload a large amount of workload to the system so that they can focus on their core administrative tasks.
Some are even using AI to deliver medicines to rural areas autonomously, and surgeons are trying to perform remote surgeries through AI assistance. The list of advantages your facility will experience from AI is long, and accurate medical data entry is behind it all.
Medical billing data being accurate is what leads to a lack of insurance claim rejections. Data is also behind stocking the pharmacy right and avoiding losses from excessive, unwanted inventory. These are just a couple of examples of medical data helping with cost management. Managing a healthcare facility’s finances becomes a lot less of a hassle if you have its accurate financial data in hand, along with other associated data.
This advantage is enhanced if you outsource healthcare data entry services to a competent agency. With their large number of professionals handling all types of medical data reducing costs due to economies of scale and possible currency exchange advantages, you can save a lot of money that you can, in turn, use to improve your facility.
Setting Regulatory Standards
Regulatory boards that set the rules and standards for the healthcare industry depend on accurate healthcare data to do that task. For instance, they take a look at how a medication has performed on test patients to determine if it should be approved for mass-market use or not.
They also take feedback data after approval to ensure that it is not having adverse effects, and if so, they can determine whether to continue that product or take it off the market. You should have quality data in your database to deliver to these agencies so that they can make informed decisions about all things healthcare.
Efficient Database Management
With large data quantities come difficulty in managing your database. Add to that sporadic input data that may contain many errors, and you have a recipe for disaster. The effects of poor database management are multifold, not least of which is doctors’ inability to retrieve the data they need for treatment when it matters.
Proper medical data entry ensures that the data in the storage is ordered and placed under the right categories. Thus, when someone wants to retrieve it, they can get it immediately by heading to the right data category. It also removes problems like duplication and data bloating, preventing more errors from occurring and saving you from investing in unnecessary IT infrastructure.
The Challenges Associated with Clinical Data
To gain the full set of benefits of medical data, you need to overcome some challenges that could derail your efforts. They are listed below.
Shifting Compliance Requirements
All medical data that is generated and recorded have to go by every applicable standard and remain compliant with all applicable regional and international laws of the field. For example, all Electronic Health Records (EHR) should follow HIPAA, or face legal consequences otherwise. Every piece of patient information in it should be stored securely due to the strict privacy requirements.
The real issue with compliance arises when the standards and laws change, especially overnight. It makes medical data entry that much more difficult and leads to confusion that could result in unwanted consequences to both patients and healthcare facilities. You need to be vigilant about the standards all the time to prevent untoward occurrences.
Complex Data Analysis
It’s not always that one can simply use medical data from a facility’s database directly. They may require more complex analytical functions to make full use of their potential. A simple example is recorded patient test results over a period. That data should be analyzed to determine the correct condition of that person’s health, as directly going through all that data could be impractical.
But complex data analysis is a resource-intensive process that takes two of your most valuable resources of yours in large volumes to complete: money and time. This is a problem in critical care situations as there may not be enough time for the analysis.
Speeding it up can ruin the accuracy of results, which is another outcome to be avoided. Processes like clinical data abstraction can remove the intricate details necessary for providing proper treatment while giving a quick overview of the data.
Varying Clinical Trial Parameters
Clinical trial data should be accurate to the letter as beneficiaries of that treatment are staking their lives on it as well as the business behind it. There is a lot of modeling and simulation involved here, requiring set standards and procedures. However, new approaches are adaptive, meaning the standards and protocols of all aspects of the trial change.
The data from the preceding stage becomes the lighthouse for how the next stage occurs. Such variations in trials, especially mid-study changes, can wreak havoc on medical data consistency, particularly wrt compliance. If you’re involved in one, you should have contingency plans in place to recheck recorded data and mitigate unwanted outcomes.
The best care can be provided to patients only if you have the best medical data by your side. And with the growth of technology, medical data will only become more prevalent, voluminous, significant, and challenging to manage. By performing accurate, cost-effective, and timely medical data entry, you can help resolve many of the issues that prevent you from running your healthcare facility at its best and prepare for even the most challenges of health-related adversities.