Posts Tagged: data sharing

New Study: EHR Systems with Clinical Decision Support Tools Reduce Healthcare Costs

Posted October 8, 2020 by Beth Osborne & filed under Healthcare.

Every healthcare organization has similar objectives for data management. They want information to be accurate, accessible, portable, and interoperable. They’d also like to save money whenever possible. A new study on EHR systems and clinical support tools reveals they can.

However, integrating EHR systems and clinical support tools isn’t always easy. In this post, we’ll look at the study and its findings. Then discuss the challenges with data exchange between systems.

About the Study

The study, published in the U.S. National Library of Medicine, sought to understand the economic impact of clinical decision support (CDS) systems and EHRs. Researchers from the Mount Sinai School of Medicine (New York) and the University of Potsdam (Germany) analyzed 27 studies involving EHRs and CDS interventions.

After evaluation, the teams found 22 of the 27 reports showed a positive economic impact after CDS tool implementation. There were several categories of cost reduction:

Unnecessary lab work
Duplicate order entry
Reducing antibiotic prescriptions

While cutting expenses in these three categories is a win for healthcare organizations, the study’s not all good news. It supplements its findings with context around “malfunctions” that could arise and increase costs. Additionally, the researchers note that CDS tools have high up-front costs and maintenance fees.

If You Want to Save, Integration and Interoperability Are Necessary

In looking at the cons of integrating the two systems, the study focuses on the two challenges above and their potential to offset any financial gains.

Malfunctions

Integrations don’t always run smoothly, especially in healthcare. The APIs can be complex and must also follow any compliance guidelines. Sometimes a true integration isn’t even possible between disparate systems, so instead, interoperability is the workaround.

Of course, interoperability in healthcare is not perfect either. Data exchange between EHR systems and CDS tools could include several hiccups. One of the most serious but solvable is IT teams that lack bandwidth. For instance, if your healthcare system purchases a CDS tool and wants to use it in conjunction with an EHR, your IT team must work out the connection—integration or interoperability. It’s no secret that healthcare IT teams are running lean and dealing with many issues, only exasperated by COVID-19.

What’s the solution? Outsource the integration or data sharing to a provider that can deliver quickly, accurately, and compliantly.

Initial Costs and Maintenance Fees

With any health information system (HIS) procurement, there will be substantial upfront costs. To justify it, you need to understand its value. How can adding this HIS to your EHR system eventually save money and improve care?

With the right CDS tool, you can know, based on research, you can reduce costs in the areas defined above. Reducing these incidents can also lead to better health outcomes for patients, saving money for the entire healthcare ecosystem.

When evaluating tools, seek out those that will work with your EHR and has all the features you’d expect in a CDS. Do a trial run with a few platforms before making a final decision to ensure your investment will pay dividends.

EHR Systems and CDS Tools Should Work Together

Improving your EHR system is a high priority for most healthcare organizations. Augmenting it with other tools is a smart initiative to reduce costs and enhance care. While pairing EHR systems with CDS tools delivers benefits, consider how they will best work together and the sizable initial investment you’ll need to make.

Have questions about data sharing between your EHR and CDS? Explore our data sharing capabilities today!

Benefits of Interoperability for Healthcare Systems

Posted September 25, 2020 by Beth Osborne & filed under Healthcare.

Interoperability for healthcare systems is somewhat of a sore subject in the industry. Interoperability has been the Achilles heel in healthcare data for some time. There have been significant advances and attempts at reform, including the new interoperability rule. However, it’s still a struggle that adds unnecessary costs to the healthcare ecosystem and can negatively impact patient care.

When interoperability works, different platforms can communicate and exchange information. It removes the barriers driving these key benefits for all stakeholders.

Greater Productivity

The productivity of clinicians and providers is critical in their day to day. Ultimately, they want to spend more time with patients than with technology. But a recent study found this objective is unmet most of the time.

If interoperability is a challenge, productivity will be as well. Users need to be able to access information from disparate systems in a streamlined manner. They shouldn’t have to spend excess time, simply because the systems can’t communicate.

Reduced Costs

Hits to productivity also drive up costs. That’s one byproduct, but there are other ways the lack of interoperability adds to budgets. There are additional strains on IT teams that may lack the bandwidth or knowledge to share data across systems. This leads to delays in deploying new health information systems (HIS), so you’re paying for idle products. Further, digitization efforts are buoyed by interoperability, reducing the need for paper in the process.

Improved Patient Care

interoperability for healthcare systems patient care

Interoperability is key to improving patient care. With access to the right data at the right time, providers can make better decisions. This improvement isn’t possible with interoperability. Consider the advantages of using a decision support system. It needs data from multiple sources to be an effective tool. More information and context are vital to improving outcomes.

Better Public Health Data

Look no further than the COVID-19 data exchange woes to understand the importance of interoperability. Disparate systems and multiple streams of data are the roots of the problem. If there were standardization of interoperability across the system, this would be less of a problem. It would also provide all stakeholders with a transparent, accurate view of a public health crisis. Then the interpretation of said data could lead to better recommendations to the public.

Fewer Errors

Medical errors are costly, no matter where they occur. In cases of patient care, they can have significant consequences, simply because of unmade updates or issues with data entry. Any provider treating a patient should have access to their medical history without all the red tape and delays. It could seriously save lives.

Other errors aren’t life and death but still impact providers. Errors in coding for medical billing are avoidable when data from EHRs or other patient-focused systems is shareable with billing platforms.

Enhanced Patient Experiences

The patient experience is extremely important for many reasons. Patients deserve to have access to their medical history so they can be more active in their own health. They also don’t want to fill out paper forms every time they visit you. Finally, they also should have continuity of care across all their providers. All these things are probable with interoperability, and they contribute to patient satisfaction.

Safeguarding Patient Data

At the core of HIPAA and the responsibility of healthcare providers to patients is that their data is secure and private. The main way interoperability does this is because it doesn’t require duplication of efforts of typing in patient information into multiple platforms. The fewer touches of data and paper involved, the more secure the process.

What Are Your Interoperability Challenges?

Interoperability for healthcare systems has a tangled web of challenges. You can’t fix all of them, but you can improve your internal interoperability relating to data sharing. Learn more about how we can help, so your organization and patients can enjoy the benefits.

Data Collection in Healthcare: Where Are We Now?

Posted September 23, 2020 by Beth Osborne & filed under Healthcare.

Healthcare was certainly not the first vertical to embrace big data. Now, it’s a critical part of operations. From decision support systems that help providers make more accurate care decisions to payers that aggregate claims data to understand drivers behind poor health, data touches every part of the ecosystem. However, that doesn’t mean data collection in healthcare is seamless and without issue.

Many challenges and opportunities exist in the collection of healthcare data. How can those in the field overcome the challenges and leverage the opportunities?

Why Is Data Collection in Healthcare Important?

Data is the fuel in any industry—it powers the present, deciphers the past, and can help predict the future. Healthcare is no different. Both providers, payers, and regulatory bodies understand the value of data. It can improve patient care, reduce costs, streamline processes, combat fraud, and lead to insights in a public health crisis.

Think of the role healthcare data is playing in COVID-19. The number of cases and deaths is helping predict what areas are more at risk. Contact tracing is revealing how the virus spreads. It’s an invaluable resource for all those on the front lines of the pandemic.

What Are the Opportunities in Healthcare Data Collection?

Beyond the criticality of data in for public health emergencies like the pandemic, there are, of course, thousands of other opportunities. Here are some of the ways healthcare big data is changing care.

Better Care

More data leads to better decisions for care. Analytics and modeling take data to a new realm of predictive opportunities. The more providers know about a disease, in general, the more informed they can be when working with patients on treatments.

Additionally, when providers with the same patient share data, they can improve continuity of care. They have a big picture of all the patient’s ailments, not just the ones they treat.

Wearables to Monitor and Diagnose

Wearable devices aren’t just for counting steps. Healthcare has become a boom for wearables to monitor conditions and diagnose. Data collection from them feeds into predictive modeling, and providers can use it to make a precise diagnosis of a disease or monitor a chronic condition like diabetes. Data like this can enhance treatment plans and log a patient’s progress.

Patient Access

Many providers now have portals for patients to access their health information. When patients are able to view this information, it helps them be more involved in their health. They may also be more likely to continue follow up visits and be more adherent to their medication regimen.

What Are the Challenges of Healthcare Big Data?

Healthcare data collection is complicated. Most of the challenges revolve around compliance, interoperability, poor data quality, and inefficient processes.

Compliance Concerns

All collection of PHI (protected healthcare information) must be compliant with HIPAA. In most scenarios, this requires data encryption at collection, transit, and rest. How you collect healthcare data, no matter why must follow regulatory guidelines. While HIPAA has been a law for over two decades, the digitation of the healthcare space is still an ongoing process. It’s imperative that you design collection processes that ensure security and privacy.

Interoperability: Data Sharing and Exchange Have Issues

Healthcare interoperability is one of the most significant challenges in the field. All patient data isn’t just in one system. There are EHRs, pharmacy software systems, decision support systems, and many other health information systems (HIS). What you collect in one platform may also need to be shareable to others. Aggregation efforts are often problematic. That’s because data sharing isn’t always a priority.

Beyond sharing between internal systems, you may also need to provide data to other providers, payers, or regulatory bodies. The new interoperability rule seeks to untangle all these problems, but it’s not going to be easy with complete standardization.

Poor Data Quality

Accuracy of healthcare data is another challenge. Inaccuracy happens for several reasons. Some common causes are patient data isn’t up to date, human errors, and miscoding. If you’re going to leverage data, it must be quality data. Otherwise, it’s useless. Every healthcare entity should establish and maintain data governance and quality rules.

Inefficient Collection Processes

Did you know that paper is still a big part of the healthcare ecosystem? Every day, patients walk into providers and fill out paperwork about their health history, insurance, and other PHI. The information on the paper then must go into a digital form, either by manual entry of some type of scanning. These processes are not practical, and they can be risky.

How Are You Handling Healthcare Data Collection?

You probably have processes in place, but you know there are gaps, keeping you from resolving challenges and tapping into opportunities. However, you don’t have to navigate this road alone. As healthcare data management experts, we have solutions to help you with data collection, sharing, conversions, analytics, and more.

Check out how we support all healthcare players with their data.