Healthcare analytics software: Top solutions for 2024
Overview: Healthcare analytics tools
Choosing the right healthcare analytics software provider takes research and time. There are most likely several questions your team is pondering before selecting a provider. If you’re just beginning your search, contemplating cost considerations, or narrowing your selection, there are a number of aspects to evaluate.
In this guide, we’ll take a look at healthcare analytics software basics and provide context to help answer your toughest questions. To give you an idea of where we’re headed, here’s a brief overview:
- What are healthcare analytics software tools?
- 5 reasons why your organization needs healthcare analytics tools
- Healthcare analytics software implementation challenges
- Healthcare analytics tools: build vs buy considerations
- Healthcare analytics software: top 5 solutions
Keep in mind that as the growing library of healthcare data expands, it’s crucial to select a scalable solution for your organization. As you read through these considerations, focus on choosing an analytics solution that will not only streamline your operations today but will launch your team into the future with increased opportunities for positive performance.
What are healthcare analytics software tools?
Healthcare analytics tools are irreplaceable software needed to extract insights from today’s massive healthcare dataset. As aggregated healthcare data expands, the tools used to analyze and predict data must also improve. If not, common healthcare problems will remain unsolved.
Contextualizing data takes a reliable software solution. Currently, disparate EHR systems and bespoke reporting create incoherent data. Data quality issues also make it difficult for teams to identify patterns and surface new insights.
That’s why a refined healthcare analytics platform is needed now more than ever to deliver better care through detailed dashboard reporting and reliable data distribution.
5 reasons why your organization needs healthcare analytics tools
Data analytics has extensive ripple effects on the healthcare industry at large. Within your own team, healthcare analytics tools can have direct impacts on operational and analytical capacities. Some of these positive consequences include:
- Controlled data quality. Standardized, aggregate data enables users to curate and enrich data into a high-quality, usable asset. As a result, analysts can spend less time hunting reports and concentrate on high-value tasks.
- Accessibility. With advanced analytic tools, your team can access data with ease. From there, you can take advantage of direct database access and improve your work with clean, standardized data.
- Insight distribution. Healthcare analytics tools enable you to share data where it’s needed most, spend more time on advanced queries, and less time on ad hoc reports.
- Workflow friction reduction. Analytics tools pass and surface insights easily across departments and systems. These systems complement existing infrastructure and expand your team’s existing capabilities.
- Results Interpretation. Once you’ve collected and organized your data, healthcare analytics tools like Arcadia Vista can help you interpret it.
These benefits create a positive snowball effect for propelling your organization towards improved and cost-effective outcomes. However, because healthcare analytics require detailed implementation procedures, your organization needs to choose a provider they can trust. Let's explore the implementation hurdles you must jump through in the next section.
Healthcare analytics software implementation challenges
When leveraged to its full capability, healthcare analytics can provide the above benefits and more, but insufficient implementation can cause serious damage. You need a provider that is familiar with common data analytics challenges to protect against the following negative outcomes:
- Provider burnout. Healthcare workers are already pressed for time and energy. With access to more EHR data, but short appointment times, providers are more likely to experience increased stress and leave the practice.
- Data volume. The sheer size of data from healthcare analytics can be overwhelming. Irregular data structures can hinder analyses and slow processes down. Not to mention, inaccurate medical information related to diagnoses, medical history, and medicines represent major roadblocks.
- Limited interoperability. It's common that even a highly intuitive healthcare analytics platform will not be compatible with other hospital systems or internal systems. That said, you need a provider that understands how to structure a complementary analytics system to easily share and update data without issues.
- Inconsistent data standards. Date formats, abbreviations, and units of measure can create inconsistencies within the existing healthcare dataset. A platform must take full advantage of new standards like the FHIR framework to proactively account for these issues.
- Security risks. Ransomware attacks and constantly evolving coding systems are risks your organization's analytics platform must account for. You need reliable software that keeps up with new data validation standards for strong protections.
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.
Healthcare analytics tools: Build vs buy considerations
Build vs. buy framework iterations can be found in product development across almost all major industries and fields, and it’s 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? Or do they take a chance on an outside solution, trusting a vendor to execute on their timeline, 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:
- Clarify: So you’ve discovered the status quo is no longer an option. What is the breaking point, and why now?
- Justify: You’re aware of a major hurdle that’s slowing down your team. Knowing that, what will solving it do for efficiency? Cost savings? Time recouped? The justification can be qualitative or quantitative, but it needs to make the intervention of new software or services worthwhile.
- Solidify: Gather evidence to support the need for new technology and research potential solutions. Comb through reviews on sites like KLAS and ask trusted peers outside your institution. Fact-find so that you can cost-compare and narrow down the best options.
- Consolidate: Armed with lots of information, you can narrow the field to the best contenders in this step. Side-by-side, break down the cost of building an in-house fix versus collaborating with another vendor, digging deep into what each course of action can offer.
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 vendors. In some cases, the two amounts are roughly equivalent.
However, it’s difficult to put a dollar amount on serving communities in need or reaching a population that’s otherwise disengaged. It’s easy, on the other hand, to measure the huge impact of preventive care, proactive outreach, and increased operating efficiency. With a more powerful business intelligence and healthcare data analytics resource at your disposal, there are few goals out of reach.
If you decide to go the vendor route, we’ve provided five top examples of healthcare analytics software that offer some of the best solutions on the market.
Healthcare analytics software: Top 5 solutions
As you comb through various resources to find the software analytics solution that works best for you, remember to reference your compiled reasons for selecting an analytics provider in the first place. What sort of problems are your team looking to solve? What was your breaking point, and how will vendor collaboration ameliorate your current status quo?
Naturally, each vendor will have different areas of specialization. Scroll through our list to discover which software solution is right for your team.
Arcadia
Arcadia is the leading cloud-based healthcare data platform built for analytics. Recognized five times by KLAS Research, Arcadia’s value-based services have connected 2,600 claims and EHRs while processing upwards of 170 million clinical patient records.
To provide a more holistic view of human health, Arcadia offers a comprehensive data platform to join disparate sets of data, awarded value-based care services, and a dedicated customer insights team to unlock your organization’s potential. Healthcare providers rely on Arcadia for financial optimization in both value-based care and FFS payment models alike. They also turn to Arcadia for STARS/HEDIS performance, care management insights, and risk adjustment accuracy.
SPSS
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.
Flatiron
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
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
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.
Healthcare analytics tools: Summary
There’s a wide selection of healthcare analytics vendors to choose from, each with various levels of expertise. Go with a solution that meets your unique needs — whether that solution involves vendor collaboration or in-house problem-solving.