Healthcare is an industry that evolves remarkably quickly. It is also one that will never run short of demand. While self-diagnosis is now more common than ever, people will always, sadly, get sick and need support.

With advances in modern healthcare always on the increase, data quality demands increase, too. Therefore, even the biggest medical or healthcare bodies can face considerable hurdles. Modern consumers’ expectations are changing.  With the rise and rise of telecare in 2020, commercial healthcare is facing new and exciting challenges.

Let's explore what these challenges might be and why cleaner data management may help.

Bottlenecking
Failure to Offer Self-Diagnosis
Failure to Collate Multiple Data Sources
Improper Decision Making
The Future of Data in Healthcare

Bottlenecking In Healthcare

As with any industry working with big data, poor efficiency can lead to bottlenecking in healthcare. Bottlenecking is anything that restricts the flow of patients into and through the clinic system. For example, incorrect or invalid patient records could slow down hospital procedures. Bottlenecking could be fatal for some patients, too, who are in dire need of care and support.

Bottlenecking can seem rife in the healthcare industries at times. That is, for at least a large portion of time, due to poor data management. Failure to integrate multiple data sources properly, for example, can lead to outdated information. Clean medical data is high-quality data, improving the flow of patients and them receiving the medical care they need.

‘Going digital’ and streamlining healthcare data is a clear way to prevent harmful bottlenecks. Data suggests that only around 7% of companies in the industry have gone ‘fully digital.’ This is around half of what you might expect, comparably, with other modern industries.

Therefore, healthcare must streamline and digitize its data for higher, cleaner quality. Otherwise, this could lead to heavy delays, poor feedback, and worse, health problems for patients.

Failure to Offer Self-Diagnosis

Self-diagnosis is very popular in the modern age. Google advised in 2019 that at least 7% of all search is related to healthcare. Given the COVID-19 pandemic of 2020, this could well be on the increase 12 months later.

However, it is key to keep in mind that an increasing number of people are looking online for healthcare support. In fact, there are up to a billion different healthcare queries posed through Google every day. That potentially supports the idea that people want to be able to diagnose themselves before consulting with professionals.

This is where some healthcare companies are potentially missing the mark. As mentioned, only 7% of companies in 2019 offered digital services. This involves carefully collating data. It requires precise record-keeping so that existing patients may be able to follow digital flows to find relevant answers.

Self-diagnosis in the post-pandemic age will be interesting to watch. US telehealth users are expected to peak at 81 million by 2022. As of 2017, this figure was only 30 million.

Technology is advancing. Healthcare companies may face increasing demand to offer users and patients at-home tools. Therefore, it’s never been more critical to ensure that the data they collate is clear and easy to understand.

dirty data in medica data

Failure to Collate Multiple Data Sources

Healthcare companies will likely communicate with multiple different sources. For example, the average US patient may have pharmacy records, multiple doctor records, and insurance data. Beyond this, there is data from any hospital visits.

There is also historical data. Data from older patients could begin with paper records. All told, this means that healthcare companies need to work with multiple data streams. Without an efficient data center, this could mean that they offer a low standard of service.

Collating and cleaning healthcare data means less administration time. Patients may be able to consult a doctor, for example, and claim medicine from a linked pharmacy. It is the same procedural that patients face when they see a doctor about an everyday complaint.

Doctors have records stemming from hospitals, pharmacies, and insurance companies. In the modern age, these sources may be increasing in number.

Therefore, healthcare companies need to stay on their toes. They must make sure that their records are accurate. They must also avoid duplicate details and that their systems can communicate with third parties.

 

cleaning medical data

Improper Decision Making

One of the biggest problems potentially arising from data mismanagement is poor decision making. It is safe to assume that accurate data helps to inform decisions. If a healthcare provider’s data is neither useful nor accurate, these decisions could be potentially disastrous.

Healthcare deals in big data. Research suggests that, in 2020, healthcare professionals handled more than 2,300 exabytes of medical data total. An exabyte, for perspective, is a billion gigabytes. That is, more or less enough data to fill four million laptop hard drives.

That is an incredible amount of data to handle. With birth rates increasing, there will be more data to generate, too. This is one reason why data for decision making must be clear and actionable. The more data there is, the more chance, arguably, there will be for confusion.

Decision making could impact one life or several. Depending on the scope of the healthcare provider in question, data mismanagement could prove fatal. Data handling in healthcare impacts mass medical advice, as well as direction consultations.

If healthcare providers continue to grow dependent on data, the need for careful management will also increase.

The Future of Data in Healthcare

US healthcare not only impacts a nation of millions, but it is also a huge business. It is thought that, by 2026, the healthcare industry in America will be worth around $5.7 trillion.

This will only exacerbate thanks to the rise of telecare, self-diagnosis, and wearable technology. Therefore, even the largest and most longest-standing medical providers must ensure their data is up to the highest quality and their data management systems are accurate.

How Can WinPure Help?

WinPure is already helping to support leading healthcare providers with their data quality. Brands and companies utilizing our platform include PruHealth, GE Healthcare, and Centura Health. By simplifying and cleaning data in healthcare, we can play a part in helping make treatment more efficient.

The demand for more convenient healthcare in the US is rising. To facilitate this demand, the buck arguably stops with the data management of healthcare providers.

If your healthcare firm is facing data management challenges, please take a tour of WinPure, or call our team for guidance.

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