Research indicates that 67% of healthcare organizations cite the "inability to analyze data effectively" as their primary obstacle to improving patient outcomes. Analytics software presents a promising solution to this challenge, rising in effectiveness as an invaluable asset to teams across the care continuum.
However, the healthcare data analytics market is expanding at a Compound Annual Growth Rate (CAGR) of approximately 24%, meaning executives have a wide array of options to consider when selecting healthcare analytics tools for their organizations.
This article explores critical considerations that should guide your search for healthcare analytics software, including:
While enhancing care delivery is a critical output of effective healthcare data analytics, it’s not the only benefit. If you’re interested in understanding the full potential of analytics, watch our webinar: The value of data: How to optimize performance, grow provider networks, and improve patient care.
Healthcare analytics tools are software applications designed to aggregate vast amounts of healthcare data, identify relevant patterns and trends, extract actionable insights, and draw conclusions. These platforms enable health teams to understand, address, and even predict common challenges evident in their existing datasets.
Data analytics significantly impacts the broader healthcare industry. Within your own team, healthcare analytics tools directly influence operational and analytical capabilities, offering several positive outcomes:
These benefits create positive momentum, propelling your organization toward improved and cost-effective outcomes. However, given the detailed implementation procedures required for healthcare data analytics, choosing a trustworthy provider is paramount.
When leveraged to their full capability, analytics tools can provide the above benefits and more; however, insufficient implementation can limit the tools’ potential. Reliable healthcare analytics tools are well-equipped to mitigate implementation challenges and avoid or eliminate negative outcomes, including:
Keep these challenges in mind as you assess your organization's unique needs and goals. By being mindful of potential implementation pitfalls, you can plan an informed analytics route that accounts for risks ahead of time. Consider these points as you decide to build or buy your analytics solution.
Build vs. buy frameworks can be found in product development across almost all major industries and fields, and this topic is especially relevant in today’s healthcare analytics discussion.
It’s shorthand for a choice that stakeholders make time and time again: does a tech team dare build a system from the ground up in-house? Or do they take a chance on an outside solution, trusting a vendor to execute on their timeline and to their standards?
There are arguments in support of (and against) both approaches, but your organization can follow these steps to discern the best path for your use case:
In the end, this choice comes down to one paramount aspect — cost. It’s not straightforward either — you’ll spend money building from scratch, and you’ll certainly spend it contracting with a vendor. In some cases, the two amounts are roughly equivalent.
It’s challenging to assign a dollar value to serving communities in need or reaching a population that’s otherwise disengaged. On the other hand, it's easy to measure the significant impact of preventive care, proactive outreach, and increased operational efficiency. With a more powerful business intelligence and healthcare data analytics resource at your disposal, there are few goals out of reach.
The integration of artificial intelligence (AI) in healthcare tools is rapidly changing the way health organizations leverage data. AI-powered solutions offer advanced analytical capabilities, such as:
These applications can influence numerous aspects of care delivery, including early disease detection and personalized medicine. As AI models process vast amounts of patient data, they can identify patterns that may indicate the early onset of specific conditions. Analysis of genetic information, medical history, lifestyle factors, and other patient details can further tailor treatment plans to address health needs early and accurately.
Beyond care delivery, AI-enabled analytics tools also support overall operational efficiency by automating routine tasks and reducing administrative burden.
Arcadia is the leading cloud-based healthcare data platform built for analytics. Recognized five times by KLAS Research, Arcadia has connected approximately 2,600 claims and clinical data sources while processing clinical records for upwards of 170 million lives.
To provide a more holistic view of patient health and organizational performance, Arcadia offers comprehensive healthcare analytics tools encompassing:
With Arcadia, you can easily join disparate sets of data and work with a dedicated customer insights team to unlock your organization’s potential.
N1 Health is a predictive AI platform that combines data with predictive models to extract insights about adverse medical events, high costs of care, and barriers to seeking treatment. These insights empower health teams to engage and treat patients proactively, intervening before conditions or costs escalate.
The platform utilizes third-party and training data from over 30 different sources, and it has supplemented user data with more than 2,500 insights about individual patients.
Atropos Health translates clinical data into real-world evidence (RWE) reports, accelerating answers to clinical questions with information uploaded by health organizations, as well as the Atropos Evidence™ Network of approximately 200 million de-identified global patients’ records.
Atropos Health’s partnership with Arcadia enables providers to tap into evidence-generating technologies for better point-of-care decision-making.
IBM has been around for a while (since 1911 to be exact) and has obviously solidified its name in the information technology sector for years. SPSS Software is an analytical technology solution built by IBM to tackle healthcare workflow inefficiencies head-on.
The IBM SPSS solution is built with predictive, prescriptive, and descriptive-analytic capabilities. Its user-friendly platform makes scalable solutions readily available for users of every skill level, enabling your team to improve efficiency and minimize risk across all projects. With a recognizable tech footprint, the well-established company stretches across Asia, Europe, and North and South America.
On the other end of the spectrum, Flatiron has been on the market for a relatively shorter amount of time. However, they are making quite an impression on the healthcare sector by accelerating cancer research and improving quality care globally.
Flatiron’s vision to “reimagine the infrastructure of cancer care” relies on its ability to expand the possibilities for point-of-care solutions in oncology. The software’s integrated real-world evidence powers new approaches to evidence generation through a robust engaged care network ready to transform cancer care as a unified team.
Sisense seeks to go beyond business intelligence by providing your team with the ability to incorporate analytics across customer and employee workflows. Its highly customizable, AI-driven analytics cloud platform, Sisense Fusion, drives performance with infused insights.
Serving a variety of industries — healthcare, retail, manufacturing, finance, and more — Sisense’s analytics solutions are flexibly arranged to handle an assortment of projects. Specifically, its healthcare dashboards make it simple to extract actionable insights out of mountains of clinical data which can help your team minimize cost and achieve operational success.
Clarify Health provides “technology to power your path to value” for health plans and healthcare providers. The company’s enterprise analytics powers the business of better care by seeking to accomplish four objectives — winning the race to value, building the best networks, reducing medical spend, and accelerating value-based care transformation.
With a large data library and helpful customer support, Clarify Health’s user-friendly platform can make your data more accessible.
There is a wide selection of healthcare analytics vendors to choose from, each with various levels of expertise. Choose a solution that meets your unique needs — whether that solution involves vendor collaboration or in-house problem-solving.
Socially Determined
Socially Determined provides social determinants of health (SDoH) data to help health organizations identify social risks and close relevant gaps. This HITRUST-certified technology leverages a robust data supply chain to surface risks across seven domains: