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The Importance of Decoding Health Data to Every Organization

To the observant onlooker, data is everywhere. From spending habits to hospital visits, humans are walking treasure troves of information. As technology…

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This article was originally published by HIT Consultant
4 Areas Where Big Data is Transforming Healthcare Right Now
Joel Landau, Chairman and Founder of The Allure Group

To the observant onlooker, data is everywhere. From spending habits to hospital visits, humans are walking treasure troves of information. As technology has exponentially improved in the last 20 years, so has the collection of data. In 2010, a mere two zettabytes of data were created, captured, copied, or consumed. In 2020, estimates put that number at 79 zettabytes. 

Data collection goes hand-in-hand with the revolution of the Information Age — since the 1970s, unprecedented digital access to the details of everyday life has transformed the way we understand the world. Rather than relying on gut instincts and trial-and-error processes, experts can gather robust data and make more informed conclusions. 

Scientists can now chart changes to ecosystems in real time, doctors can predict their patients’ likelihood of developing certain conditions, and marketing execs can determine the success of an ad campaign before it is even launched. Such data-driven decisions are capable of reducing costs, improving daily experiences, and saving lives

From Collection to Analysis

Businesses often let data amass without devising a plan to use it, which translates into a massive lost opportunity. In 2020, a survey of 1,500 businesses revealed that 68 percent of data sits unused, collecting metaphorical dust. Seagate Technology, the data storage company that released the report, said barriers to data usage included the proliferation of data silos and the inability to break down collected data into actionable statistics.

That’s why it’s important for every organization to prioritize data analysis. The collection is only the first stop in a lengthier journey to effectively harness any available information related to the quotidian operations, client services, and long-term plans of a business. Leaders, especially those in the healthcare industry, would benefit from incorporating data-driven decisions into all their policies and practices going forward. 

Getting to that point requires supporting employees who are well-versed in data analytics and providing them access to key analytic programs. It may also include hiring a data scientist solely dedicated to decoding information that will improve an organization. 

Those ready to embrace data-driven decision-making should consider the following questions. Doing so can narrow the scope of a data project and result in more specific answers to pressing organizational concerns. 

What Issue(s) Can Data Illuminate?

A good leader knows their organization inside-out. They can tell when morale is low, a sector is underperforming, or an outside issue is slowing down business. One’s intuition on such matters can be a great springboard for targeting data but do not be surprised if it’s disproved in the end. Focus on one concern at a time, set a timeline for getting answers, and be willing to accept the unexpected.

Let’s imagine a doctor’s office in a working-class community where patients’ non-adherence to treatments is a common concern. Having providers ask patients outright why they are not taking prescribed medicine has yet to yield clear answers. Instead, the medical team decides to ask themselves: What factors might contribute to non-adherence in this situation?

They come up with a few ideas. Maybe the cost of prescriptions is too high, people don’t have time to visit the pharmacy between work shifts, or patients feel unsupported after their initial appointment. To determine an effective strategy to combat non-adherence, they’ll need to conduct a bit of research. 

How Can Such Data Be Collected and Processed? 

The office hires a data scientist to gather data on prescription costs, pharmacy hours,  average work shifts in the area, and patient’s perception of their care. Such information can be brought to light through a number of tools, like software programs, census and labor data, and anonymous surveys.

After doing so, the data scientist discovers that non-adherence most often occurs in zip codes furthest from the only pharmacy in town. The surveys reveal that many patients in the area don’t have regular access to transportation and are unaware of any delivery system available at the pharmacy. She presents her findings to the team.

Hundreds of companies provide similar analyses within the healthcare field, which offers data-driven solutions for pharmaceutical supply chains. These companies can extract a unifying narrative from large data sets, allowing their scientists to return to medical professionals with valuable insights about their staff, users, and operational capacity.

What Changes Might Result from Data Analysis?

More likely than not, data analysis will help identify areas of improvement within an organization. If so, it’s time for further action. In the case of the doctor’s office, the team may choose to send free delivery vouchers to all their patients, no questions asked. Then the data scientist can continue to track adherence rates and report back whether the vouchers made a significant difference. 

When embarking on a data project, decide what funds and resources should be allocated to it. That way, once the results are in, there is a way forward. Identifying a concern by using data is only useful if a solution is also identified and implemented.

The Potential of a Data-Driven World

As mentioned above, only one-third of data is currently leveraged by businesses around the globe. The remaining unleveraged data amounts to revenue loss, missed opportunities, and operational blind spots. 

The last thing to keep in mind as businesses make greater plans for data collection and analysis is privacy measures. Improving outcomes based on data cannot take precedence over privacy. In the healthcare sector, this primarily applies to patient data. Conduct due diligence when acquiring data-combing software, be transparent about research with staff and clients, and make sure to adhere to local and national policies. 

Data has the potential to streamline business practices and eliminate common setbacks. In the modern world, the raw information within our reach shows no signs of slowing down and effective business leaders know how to grasp it. 


About Joel Landau

Joel Landau, founder and chairman of The Allure Group, a network of six New York City-based nursing homes

data analytics


medicine


prescription
pharmaceutical

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