Posts Tagged: big data

Data Management Pain Points in Healthcare

Posted March 17, 2021 by Beth Osborne & filed under Healthcare.

To say data management is challenging in healthcare is an understatement. Many challenges persist for all healthcare data stakeholders. Regulations create compliance requirements, and a disconnect in interoperability makes data sharing burdensome. These data management pain points can add up and may have your organization looking for ways to alleviate them. As pioneers in data management, we’ve learned a lot over the years and want to provide you with some pain-free solutions.

What Are the Most Agonizing Data Management Pain Points?

There are aches and pains all through the ecosystem that touch compliance, interoperability, aggregation, insights, and more.

Compliance Conundrums

Healthcare data requires special care and compliance with HIPAA and other laws. It’s a pain point because it can hinder some areas like interoperability. But the biggest pain is risk and threats. Healthcare is a favorite target of hackers. Healthcare cybersecurity is integral to compliance. That means that any organization that accesses it must have protocols in place along with regular auditing and a strong security posture.

The Interoperability Pain Point

Without integration of systems, fragmentation is a threat to healthcare data and interoperability. That’s just talking about the internal needs. Sharing data with payers, other providers, public health, and consumers isn’t standardized. Regulators are attempting to remediate this, but the fact that the U.S. health system is so fragmented itself doesn’t help. Until streamlining protocols and practices blanket the entire industry, this will continue to be a pain point.

Data Aggregation Is Painful

For providers and payers especially, data aggregation can be difficult. With multiple sources of data, combining it all for analysis, sharing, or other activities is often held up by a lack of IT resource bandwidth. Aggregating data enables you to learn more because there’s more context. From a predictive lens, healthcare organizations and patients would benefit from this analysis. There are ways to do this via APIs and analytics engines. This healthcare big data could significantly improve outcomes.

Moving Data Is Laborious

Just moving data is sometimes an arduous task. Organizations often need to convert data from one health information system (HIS) to another. Others want to retire legacy systems and archive data they still have to retain.

Not having enough resources causes this healthcare data point. Internal expertise on how to migrate data accurately can also be challenging. There are healthcare data pros like InfoWerks that can help you with this heavy lift.

What Are Your Healthcare Data Pain Points?

Your data should be improving operations, not hindering you. However, data can only be helpful when it’s accessible, portable, and interoperable. We’re experts at all three and make data management pain-free. Contact our team today to discuss your healthcare data pain points.

What Are Your 2020 Healthcare Data Resolutions?

Posted January 30, 2020 by Beth Osborne & filed under Healthcare.

Data is one of the most valuable assets a healthcare organization has. However, you may be facing lots of challenges with data quality, accessibility, portability, and interoperability. These roadblocks may have you thinking about 2020 data resolutions. How will you bridge the gap and ensure your data is working for you?

What Do You Want to Do with Your Data in 2020?

Having a big data strategy and goals associated with your data, you may be unsure of how to meet these. Healthcare data is complicated! This complexity is made more so if you aren’t consistent across your platforms.

When data isn’t formatted or structured in a uniform fashion, it’s much harder to ensure it’s portable and interoperable. Analyzing the data can be difficult, as well. It’s a good idea to put some data governance rules in place to eliminate these issues.

Healthcare data is also highly regulated. It’s a valuable target for cybercriminals, so you need to have cybersecurity policies in place to ensure compliance. You don’t want to be in the headlines for a data breach. Your data should be secure at all times, regardless if it’s in transit or at rest.

You may also be dealing with a massive amount of data in your software systems, some of which aren’t active anymore. This could be negatively impacting the performance of your EHR or pharmacy software. While you likely need to keep this data to adhere to medical record retention laws, there are alternatives, such as data archiving.

A New Frontier for Healthcare Data

We’ve been in the healthcare data industry for over 23 years, completing over 27,000 data projects. In 2020, our focus is on helping the healthcare ecosystem streamline processes, reduce costs, and remain compliant.

While we’re known for our data conversions, we do so much more!

Data archiving: Move legacy data to our searchable, web-based tool
Data analytics: Get insights on acquisitions and your own operations
Data transfers: Share PHI with patients and third parties securely
Data aggregation: Combine multiple data sources
Data interoperability: Ensure your data is accessible across platforms

These are just a few of the data projects we can facilitate. Whatever your data resolutions are for the coming year, we’ve got the solutions you need, customizable to your situation. Connect with us today to learn more.

Do You Have a Healthcare Big Data Strategy?

Posted December 19, 2019 by Beth Osborne & filed under Healthcare.

In the age of data, healthcare organizations are facing many challenges. First, there’s the sheer quantity of data. Then there are concerns about how to aggregate it and analyze it. These quandaries are further complicated by security and compliance regulations. Having a healthcare big data strategy is a prudent move by any organization. Even if you currently have one, it may be time to revisit it.

What Is Healthcare Big Data?

Healthcare big data refers to the vast amounts of information created by the digitization of all aspects of the industry. That data is then consolidated and analyzed with technological tools.

Healthcare has become exponentially more complex as we live longer, which is a shift in treatment models. Data makes this possible. Healthcare data analytics can improve prevention, diagnosis, and treatment.

Why Is Healthcare Big Data Important?

Much of its value comes down to reducing costs. The U.S. spends more than twice on health care per person than is peers. It’s not because the U.S. has more sick people. Rather these inflated costs are mostly due to drug costs, clinician salaries, hospital administration, and increasing medical services fees.

Data can help reign in costs, and healthcare systems have more incentive to use insights to facilitate better care. That’s because of the shift from fee for service to pay for outcomes.

Big data has multiple real-world applications in healthcare, including:

Understanding peak times to staff better
Helping prevent opioid abuse
Enhancing patient engagement
Research projects for cancer and other diseases
Using predictive analytics
Reducing fraud
Enhancing data security
Practicing telemedicine
Integrating medical imaging for more precise diagnoses
Preventing unnecessary ER visits

Investing in Big Data Initiatives and Tools

In a recent survey by Deloitte Insights, the healthcare industry has become highly invested in big data unlocking value. The survey found that 70% of respondents have a defined analytics strategy, compared with only 40% in 2015. The survey also revealed that health systems are willing to invest in data scientists, visualization designers, and data architects.

Healthcare Big Data Strategy: Becoming Data First

For any organization that wants to leverage their data, they must build a roadmap to being data first. Data analytics should become the backbone of healthcare. Employing new tools such as machine learning and artificial intelligence will be necessary as well. These tools help you manage data and provide you with a fundamental analysis plan that can then turn into actionable insights.

What’s Driving the Big Data Revolution?

The biggest driver for embracing big data in healthcare is to improve patient care and outcomes. This objective includes population health management. Interpreting a large amount of healthcare data has the potential to spot population health trends, which can help healthcare systems shape their response to emerging risks.

How Can You Develop or Improve Your Strategy?

Having a big data strategy is critical to reaping the benefits that data brings. While this is an evolving concept, there are still some fundamental things you can put in place for better data management.

Data aggregation: you probably have data from multiple sources, including EHRs and other systems. To be data first, you need a single hub to combine all data sources.
Interoperability: are your systems able to communicate with one another? If not, then this could impede your ability to learn from your data.
AI and machine learning tools: while data scientists are exceptional at interpretation, they can’t do the volume of analysis like these technology resources can.
Real-time information: looking back at data to predict is one part of your strategy, but you also need to have the ability to have access to real-time data for in the moment decisions.
Business intelligence opportunities: use your data to fuel better decision-making regarding your operations, patient engagement, and more.
Security and privacy measures: your data strategy must include how you’ll keep data safe from breaches and compliant with HIPAA.

Big data in healthcare has the capability to boost patient outcomes, streamline workflows, and improve operations. Need a big data strategy or have big data challenges? Chat with our experts to see how we can help.