Learn More About Healthcare Analytics Software
What is Healthcare Analytics Software?
Healthcare analytics software, sometimes called healthcare business intelligence software, helps organizations such as hospitals and clinics turn their operational and clinical data into actionable insights. These products ingest data from various sources and systems, allowing decision makers to identify ways to improve patient outcomes, deliver more efficient care, reduce costs, optimize revenue, and assess current compliance. Healthcare analytics software ranges in functionality, with more advanced tools utilizing machine learning and predictive analytics to identify patterns, target high-risk individuals and populations for outreach, and reallocate resources as needed.
Every department in a healthcare organization can benefit from using this software. For example, a hospital’s billing department can use healthcare analytics to determine the likelihood of claim denials before submission, giving them a chance to correct any errors. An emergency room can identify patterns in overcrowding, allowing them to staff accordingly during those days and times. Clinical teams can use data trends to monitor chronic disease patients for timely outreach when they need symptom management support or identify which psychiatric patients are at high risk for a crisis.
What are the Common Features of Healthcare Analytics Software?
The following are some core features within healthcare analytics software that can help providers and administrators turn their healthcare data into actionable insights :
Data management: Healthcare analytics software enables healthcare providers to organize large datasets, connecting multiple data sources into one central repository. This has numerous benefits, including better patient care, smarter decision-making, and improved metrics across departments. Importantly, these specialized analytics platforms ensure data access is restricted to the appropriate users.
Data modeling and blending: Healthcare analytics software promotes interoperability between different healthcare systems, taking disparate data sets and uncovering trends and connections. By employing advanced analytics, this software helps stakeholders make important decisions that impact clinical outcomes, revenue forecasting, and administrative procedures. As hospital systems navigate extensive regulatory frameworks, data modeling and blending bring together seemingly unrelated data and uncover weak points in a healthcare organization’s overall compliance strategy.
Data visualization: Data visualization tools such as real-time dashboards, charts, and graphs help users hone in on the data that matters most. These tools can be further customized to display progress towards specific initiatives or monitor key performance indicators (KPIs) across departments. Reports can be generated and shared as needed, with automation features allowing regular reports to populate based on time or milestone triggers.
Self service: Regardless of role or IT experience, self-service analytics allow any type of user to access the data insights they need at any time without support. This can be particularly handy for administrative staff such as scheduling, billing and claims, and triage staff, who may need access to analytics to make informed decisions under urgent timing.
What are the Benefits of Healthcare Analytics Software?
The following are the benefits of healthcare analytics software:
Better outcomes: Analytics allows healthcare providers to tailor their approach to each patient, promoting stronger health outcomes. Healthcare analytics software can take historical data trends and apply them to present decisions, leading to smarter use of resources and more effective care coordination. An analytics platform can assess geographic region, income level, risk factors, and existing conditions to determine strategic community outreach for care. Every data point can play into clinical decision making.
Improved revenue: By reducing the likelihood of claim denials, healthcare analytics platforms can promote higher reimbursement rates from insurance companies and improve patient collection rates. These solutions can also identify areas of supply overspending and operational deficiencies that are contributing to budget shortfalls.
Improved productivity and decision making: Healthcare analytics removes a lot of guesswork for healthcare staff, automating certain processes and empowering staff to solve problems more efficiently. These platforms can reduce errors, streamline care delivery, and generate more stable revenue.
Who Uses Healthcare Analytics Software?
Clinicians: Clinicians use healthcare analytics software to monitor population outcomes, determine appropriate, individualized treatment for patients, identify which patients are most likely to not adhere to treatment, and identify benchmarks for standardized treatment plans. They can also use this data to help reduce patient readmission, target specific populations that are overusing emergency services, and track vaccination efforts.
Administrators: Administrators across scheduling, billing, and health information teams use healthcare analytics software to stay compliant, reduce errors in workflow, and optimize patient retention and revenue collection.
Marketers: Though not as common, marketing teams in healthcare organizations and companies can utilize healthcare analytics data to identify target groups for email and text engagement outreach, medical sales strategy, and community health initiatives.
What are the Alternatives to Healthcare Analytics Software?
While healthcare analytics software has multiple use cases, healthcare organizations may opt to use specialized analytics platforms that focus on one business function:
Healthcare compliance software: Healthcare compliance software utilizes analytics to monitor ongoing progress against compliance programs and reduce the likelihood of fraud and abuse. This may include tracking the percentage of staff who have specific certifications or the number of HIPAA violations recorded over a certain period.
Healthcare supply chain software: Healthcare supply chain software uses analytics to improve efficiency in inventory and overall vendor spend. Hospital staff can use this software to identify the appropriate cadence for medical inventory restocking based on current patient trends and employ workflows to automate the ordering process.
Clinical decision support software: Clinical decision support software applies data analytics to EHRs to help healthcare providers make evidence-based decisions at the point of care. These solutions can provide information on treatment protocols, prompt questions on medication adherence, and provide tailored recommendations for health behavior changes.
Value-based reimbursement software: Value-based reimbursement solutions can exist as software, service, or a hybrid of both; the latter allows healthcare software vendors to equip healthcare organizations with the analytics and expertise necessary to revamp existing reimbursement models. By deploying value-based reimbursement strategies, hospitals and health care practices can better and more accurately compensate for the services rendered to a patient.
Software Related to Healthcare Analytics Software
Related solutions that can be used together with healthcare analytics software include:
EHR software: EHRs offer a tremendous amount of healthcare data for analytics platforms to utilize. Hospital systems can identify trends in prescriptions, diagnoses, demographic groups, and hospital asset usage, among numerous other data points. An analytics platform without a connected EHR would be useless to a hospital system.
Medical practice management software: Medical practices, from small clinics to large hospital systems, can glean operational insights from their medical practice management software. They can assess how often appointments are scheduled and canceled by specific populations, the average length of time it takes patients to pay off bills, or how frequently specific procedures are performed.
Patient experience software: Patient experience software is managed with various software products aimed at patient engagement, case management, and relationship management. These solutions can work with healthcare analytics platforms to determine appropriate patient care strategies, improve patient safety and wellbeing, or even improve social media reputation for medical practices.
Population health management software: Population health management depends upon data analytics to improve community health outcomes. Analytics enables healthcare providers to target individuals for outreach, monitor year-over-year progress for chronically ill communities, and improve value-based reimbursement by ensuring better health outcomes.
Healthcare learning management systems (LMS): Continued education is important for hospital staff to remain compliant with ever-changing healthcare regulations. Healthcare LMS tools make it easier for healthcare staff to receive and track the appropriate accreditations or certifications. Integration with a healthcare analytics platform allows administrators to monitor staff compliance with specific training requirements.
Revenue cycle management software: Revenue cycle management relies on data analytics to ensure KPIs are met and that historical trends allow for proactive response to revenue cycle performance. A dedicated analytics platform can help benchmark revenue cycle performance against competitors and identify which specific portions of the process are performing well versus others.
Challenges with Healthcare Analytics Software
Software solutions can come with their own set of challenges.
Complexity: Depending on the scale of the healthcare organization, finding the right healthcare analytics platform and implementing it can be daunting. The need to integrate with all existing systems while ensuring the analytics platform can scale and be used by various staff at various levels of IT expertise can lead to an ever-growing list of requirements when searching for the right solution.
Data security: Healthcare analytics software ingests a staggering amount of sensitive health data. A data breach could be costly to healthcare providers and potentially dangerous for patients. A good analytics platform will enable appropriate data management standards to ensure sensitive data is not compromised and that all information is securely stored and backed up.
Lack of APIs: Interoperability remains one of the biggest challenges for the healthcare industry. A healthcare analytics platform that can’t utilize APIs will have less data access compared to platforms that support APIs. This can impact population health initiatives, patient medical record access, and even healthcare software development.
How to Buy Healthcare Analytics Software
Requirements Gathering (RFI/RFP) for Healthcare Analytics Software
If a healthcare organization is just starting out and looking to purchase its first healthcare analytics platform, or maybe an organization needs to update a legacy system--wherever it is in its buying process, G2.com can help select the best healthcare analytics platform.
Given the broad use cases for healthcare analytics, an organization should identify the strongest areas for improvement as it begins identifying potential vendors. The organization should consider factors such as staff size, patient needs, and compliance concerns. Depending on these factors and many others, different healthcare analytics platforms will have varying success.
Compare Healthcare Analytics Software Products
Create a long list
From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison, after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.
Create a short list
From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, organizations can produce a matrix to compare the features and pricing of the various solutions.
Conduct demos
To ensure the comparison is thorough, the user should demo each solution on the short list with the same use case and datasets. This will allow the organizations to evaluate like for like and see how each vendor stacks up against the competition. The organization should also identify specific reports that are frequently needed and see how the product’s data visualization tools work. Determine the quality of tech support that each vendor provides in the event that staff require additional support and onboarding. Understanding the data migration and deletion process at the start and end of a contract is also important.
Selection of Healthcare Analytics Software
Choose a selection team
Before getting started, it's crucial to create a winning team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of organization members with the right interest, skills, and time to participate in this process. It’s important to include team members across various roles, including health information management, IT, administrative, and clinical staff. All these roles will interact with a healthcare analytics platform differently, so it’s important to select a system that works for everyone. In smaller organizations, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities.
Negotiation
Once the selection team has narrowed down their software picks, it’s time to discuss customization options, pricing, and the type of support needed from the vendor. It’s always important to address pricing options, even when they are listed on a vendor’s website. Many software vendors will provide discounts and custom pricing options based on what the buyer is looking to purchase.
Final decision
After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. The buyer can be confident that the selection was correct if the tool is well used and received. If not, it might be time to go back to the drawing board.
