Risky Business: The Cost of Data Silos in Healthcare | Quisitive

More than ever, healthcare professionals rely on software to do their jobs. A lot of software. In a typical healthcare organization, staff might have dozens (or hundreds) of systems in use by different departments. Some common tier-1 applications include:

If copious amounts of technology made healthcare professionals’ work easier, faster, or improved patient care, the added administrative tasks would feel worth it.

Unfortunately, the data often sits in silos separated by system, purpose, or function. When this happens, providers are often left scrambling to collaborate, access meaningful tools, and efficiently serve patients. This lack of tech integration led a Forbes article to label data silos as “healthcare’s silent shame.” Ouch.

As the author explains:

For starters, most hospitals – even leading centers – are struggling to meaningfully organize the genetic and phenotypic data of their own patients in a fashion that can truly inform clinical decision-making.

For starters, most hospitals – even leading centers – are struggling to meaningfully organize the genetic and phenotypic data of their own patients in a fashion that can truly inform clinical decision-making.

How Data Silos Happened and Why They Matter

When HITECH (Health Information Technology for Economic and Clinical Health) became law in 2009, it required healthcare organizations to use electronic health records and achieve “Meaningful Use” goals. While this legislation helped advance the industry’s focus on data, it fell short of what we now see as vital – a requirement to standardize records so data could be shared among health systems.

As it happened, healthcare facilities began widely adopting electronic records before we saw the mess that dispersed data created. Thirteen years later, the repercussions of this oversight continue to plague the industry, including hospitals, where diverse teams of providers and support staff must access and understand vast amounts of digital information on a minute-by-minute basis.

Add these administrative requirements to an increasingly competitive market, and you get the current situation, one the Surgeon General has labeled a crisis due to worker burnout and resignation. Although it’s a complex issue exacerbated by the challenges of COVID-19, experts agree that administrative burdens play a large role in healthcare’s mass exodus.

Data silos contribute to the strain by creating glaring inefficiencies from both patient and provider perspectives, especially within hospital settings. Here’s how:

    1. Day-to-day operations

Hospital professionals must accurately evaluate and meet patient needs while effectively managing hospital resources. Triage, admission, and discharge decisions (patient flow) are hindered when staff can’t access the right data at the right time because everyone uses varying systems that don’t integrate. That is, the right foot does A while the left does B, leaving both at a standstill.

Entering notes and communication is the most significant pain point for hospital leaders.

When staff ack access to real-time information, like which and how many beds are occupied or available, patients can sit in waiting rooms for hours while beds sit empty or waiting to be cleaned. Other times, physicians may question whether to send a patient to the ICU or a general ward because they can’t access multiple medical records and medication lists.

And let’s not forget the elephant always in the room – the never-ending task of data entry, when doctors and nurses are forced to enter the same information into different systems over and over again. We recently conducted a private survey of 100 hospital leaders about healthcare technology concerns. Respondents listed difficulty entering notes and communication as their most significant software pain point.

Outdated or disjointed systems also strain supply management efforts. How can any team, especially healthcare professionals who work in a high-intensity environment, meet patient needs when they don’t have or can’t find essential medical supplies?

    2. The bottom line

The financial implications of data silos can’t be ignored. Hospitals need funds to operate, and run an effective healthcare facility requires balancing the budget and minimizing waste. When systems don’t integrate, the problems created by long wait times, excessive paperwork, and supply mismanagement make the cost of doing business go up.

Take supply struggles, for example. Physicians, nurses, and pharmacists may use different supply and materials management systems, some more sophisticated than others. While one team might use software to understand what and how much gets used, another may rely on a desktop spreadsheet, and another on post-it notes (it’s been known to happen).

The disparity and lack of confidence in systems can then lead to inventory hoarding, a sloppy but not unheard-of occasion in which staff shoves essential supplies in a cabinet or closet in case they run out at a crucial moment. This “just in case” method often negates the “just in time” ordering so many hospitals strive for. Obviously, such practices are neither sustainable nor cost-effective.

Further driving costs upward, many hospitals use software from different vendors, making it harder to manage costs and upgrades (e.g., one system gets replaced while another sits aging on a shelf).

Our recent surveys confirm the extent of supply frustration, as respondents listed differing ordering systems that don’t communicate across departments and lack of visibility for vendor discounts as the top complaints against supply management technology.

    3. Regulatory compliance

Healthcare professionals follow a lot of rules. While compliance obligations fall under a broad umbrella, most relate to patient safety and privacy.

In a hospital setting where different teams routinely compile and access electronic health records, maintaining patient privacy remains a top priority. It’s also a major cause of data silos and why sharing records between providers is so tricky.

Also, when the time comes for teams to prove compliance, they have to chase data from system to system, making the job time-consuming and unpleasant. This consistent tracking of outcomes will also prove useful for insights when planning continuous improvement protocols.

    4. Patient care

Despite the stress data silos put on other areas of healthcare, patient care bears the brunt. The fact is, disordered medical data stifles complete, timely care.

First, like providers, patients spend significant time repeatedly filling out identical paperwork, wondering why each process exists when surely the information must sit in a cloud somewhere.

Referrals become clunky and labor intensive, and patients stay frustrated with care that resembles a patchwork of providers at various venues – outpatient facilities, primary care practices, specialty clinics, and hospitals. And few of these sites communicate with the others.

Effective diagnosis and treatment then take a hit because providers often get an incomplete picture of medical history, medications, and specialist care. All the while, patients spend extensive time in a hospital waiting room when all they want is relief. A unified data pool with even access across the system can significantly improve the continuity of care by allowing medical teams to collaborate and treat the whole patient.

The Solution: Unify Data Under a Single Platform

In good news, many hospitals understand the problems data silos create and are actively trying to improve the situation. As such, our survey found that 75% of respondents with EHR systems have established a budget for upgrades.

Here at Quisitive, we think having a single platform that houses multiple healthcare-ready solutions is the way forward. Here’s why:

When health systems and their end users collaborate with access to unified data, everyone wins. Hospital administration, providers, and support staff have one less chore to worry about. Weary patients receive much-needed relief as medical facilities more effortlessly move toward value-based care. Provider-patient relationships strengthen, and costs stabilize for everyone.

Quisitive knows healthcare

Our real-time health solution, MazikCare, helps accomplish all the above – giving healthcare professionals indispensable access to data via a single platform, empowering informed decisions and enhanced patient care. Built on Microsoft Dynamics 365 and the Microsoft Cloud for Healthcare, MazikCare provides a digital bridge between patients, providers, and payers, streamlining and unifying each patient record, cutting down on vendor bloat and enabling care providers to save time and resources. MazikCare is the only platform on the market ready for healthcare businesses from Day 1, offering reduced implementation time, lower total cost of ownership, and accelerated ROI.

Get in touch! Ready to transform your corporate budgeting, planning, reporting & corporate performance management? We can help! With over 30 years of experience helping companies implement and optimize corporate performance management software, our team of experts is here to help analyze your existing processes and recommend the right solution to meet your needs. Get in touch

Before your organization takes the leap of migrating your data warehouse or your data and analytics platform to the cloud, there are some key elements to consider. Having a good handle on your answers to these four questions will better prepare your team to make the move.

1. Why are you migrating your data and analytics platform to the cloud in the first place?  

While this might seem like an obvious question, your answer should cover two things: what is the compelling event or reason for your organization to consider migrating your data to the cloud, and what do you want to achieve once it’s there?

In my experience, the answer to that first piece is widely varied. It might be that your organization’s data center hardware is reaching its end of life, end of support, or even end of lease, prompting a decision of some sort to be made. Sometimes it’s that you have reached a point where you have simply run out of hours in the night to do your data processing using your aging infrastructure. You can’t add more grunt to your hardware, and you can’t add hours to the clock, so you’re left with either buying expensive on-premises hardware or moving to the cloud.

Maybe it’s because you want to get your data closer to your apps that are already living in the cloud. Or perhaps you want to use machine learning and artificial intelligence to do predictive analytics on your data. To do that you need to be in the cloud.

Whatever your reasons, know what’s pushing you there and understand your goal. Having a good grasp on both can help you better articulate your vision to any partners you might have in your migration.

2. Are you considering a lift and shift or a full transformation? 

Data migration isn’t always a cut and dried process. There are very legitimate pros and cons to either considering a lift and shift where you will have to try to retrofit improvements later or completing a fundamental redesign of your data, which means you’re starting from the ground up.

For example, a redesign will slow down your process initially, taking longer to get everything up and running. On the other hand, by simply moving what you have up into the cloud, you’re undoubtedly bringing along legacy issues that have been slowing you down. I liken the lift and shift method to packing up an old house and moving it into a new one. Most people find those final few boxes that they simply don’t have the heart to unpack, and that end up sitting in a basement or a garage. They’re probably filled with items that should never have made the move, but now that they have they’re just taking up space.

Whatever you decide, be clear on why you’re making that decision, understand the trade-offs, and go into the process with your eyes open.

3. Where is your IT organization from a skills perspective? 

A company migrating its data and analytics platform to the cloud for the first time might make some stark discoveries, including a skills gap within the organization. Skills that are required for managing on-prem data centers differ from doing data analysis in the cloud.

Before you make the move to migrate your data warehouse, take stock of your in-house skill sets. Are there maturity gaps? If so, what’s your plan to bridge any gaps that you might discover? Do you intend to train up? If that’s the case, what time frame are you looking at? Do you need to hire data scientists? If you do, think about what specific skills you require and bring in talent early on in your process, so they have context for your new data environment. Don’t want to reskill or hire? Find a partner that can augment your team with managed services.

Understanding your team’s capabilities and capacity prior to migration will help ease the transition once you start operating in the cloud.

4. What’s your timeline and where do you want to begin? 

Every journey starts with a first step, but many times organizations have no clue where to begin when it comes to migrating their datacenter to the cloud.

The best advice is to understand there are experts out there, like Quisitive, who have deep knowledge, great experience, and a proven methodology to help businesses like yours move your data and analytics platform to the cloud and get you where you need to go.

At Quisitive, we’ve developed a proven and prescriptive method for this very purpose: On-Ramp to Azure Data. It provides step-by-step guidance based on best practices and proven cloud adoption methodologies, tools, and resources, to migrate your data and analytics workloads to Azure. In a series of short sprints, it can rapidly move you from planning to use case execution in 30 days.

Data migration doesn’t need to be messy. By walking into the process with a clear vision, a strong plan, and the answers to these four important questions, your migration will roll out much more smoothly.

Click here to learn more about the On-Ramp to Azure Data program. 

Ready to transform your corporate budgeting, planning, reporting & corporate performance management? We can help!

With over 30 years of experience helping companies implement and optimize corporate performance management software, our team of experts is here to help analyze your existing processes and recommend the right solution to meet your needs.

Get in touch