Initially considered the forte of research agencies and digital companies, data analytics is now a prerequisite capability across sectors, including healthcare. This key strategic asset has helped organizations become increasingly competitive and innovative.
According to a McKinsey survey, companies that leverage big data and analytics effectively boost their productivity and profitability by 5-6 percent, giving them a competitive edge over their peers who do not leverage analytics driven insights.
Why is Big Data Vital in Healthcare?
Despite the increasing excitement regarding the prospects of big data analytics in investments and healthcare, most healthcare organizations are still lagging in adoption. A recent survey by Dimensional Insight has revealed that about 56% of healthcare facilities and hospitals lack a long-term analytics plan and proper data governance.
The risks of inadequate data governance include records duplication, missed reimbursement opportunities, financial benchmarking challenges, and other operational hurdles. An effective strategy around big data can effectively fix these!
As patient care becomes more intertwined and complex, the lack of proper analytics makes it increasingly challenging to deliver safe and quality patient care while simultaneously achieving better outcomes at lower costs. Due to data inaccuracies and mismatches, many healthcare facilities experience data disparities between their accounting and clinical departments.
However, when implemented and used properly, big data can support improvements at healthcare organizations in the following ways:
Help ensure identification and delivery of care to complex patients
Reduce administrative and utilization costs for healthcare providers by at least a quarter
Limits human errors in medical services
Enables rapid innovation of population-specific healthcare solutions
The ABC of Big Data
Here’s an overview of the ABC of big data:
Artificial Intelligence (AI)
Everyone is turning to AI or is beginning to master machine learning. Organizations need algorithms. Some may not understand why but can’t bear missing out on a revolutionary trend.
Companies require data analysis technologies and methodologies to extract insights from their bulk data. You need data to run your business, but this simple fact is a continuous challenge.
Like well-organized IT assets and leading tech teams, customer focus is a vital consideration for any company. The customer must sit at the core of every business endeavor viewed from a data analytics lens.
Information is considered the new oil for healthcare organizations, but like crude oil it is often inaccessible and challenging to use in raw form. Data intelligence can help understand how business information is structured, where it is, its connection, and the actual quality of the data itself.
If you’ve reached this level of data analytics maturity, making investment decisions is more effortless. It would be best to consider the customer database as a company asset to provide a sound basis for decision-making regarding BI, AI, and tech investment.
The Potential for Big Data to Enhance Revenue Cycle Performance and Cash Flow
The health care industry is transitioning toward a focus on value of care rather than volume of care, and organizations are always looking for ways to boost healthcare delivery and results while optimizing their bottom line. Here are the practical ways that big data can improve your cash flow and financial performance:
Improved revenue cycle
Big data grants access to vital revenue indicators like denial rates, claim rejections, and net collection rates. Utilizing data in this way, you can identify areas that need improvement as well as areas to expand. Furthermore, the data can inform staff training and awareness on common billing errors.
Data analytics can help you note the areas your practice is falling short in. Once challenge areas have been identified, you can then partner with organizational leaders to create strategies to bridge the deficiencies.
Identifying areas that need improvement and having precise metrics to benchmark and measure them against can help you set practical goals across the organization.
Most of the evidence exemplifies the reliance on data analytics to enhance practice performance. Indicators like payer mix breakdown and service revenue offer a holistic view of your practice’s financial health. You can also evaluate if you’re meeting targets or achieving goals.
Identifying growth and expansion opportunities
Through data analytics, you can locate areas within your organization that are positioned for growth. For instance, by viewing encounters distribution data, you’ll identify the treatments or conditions common to your patient population which allows for data-driven decisions when making company expansion maneuvers.
Troubleshooting urgent issues
Big data and analytics can help you identify problems like No Response or Denied claims that require prompt attention in order to receive reimbursement. A robust data analytics solution can detect payment delays, their causes, and do so in a timely manner to allow for adjudication.
Part of provider billing practices require accessing accurate and centralized revenue data sources. Use of service-level datasets can help reduce the manual aspects of data collection, analysis, and entry, and will free up valuable time staff spend on aggregating clinical data.
How Big Data Aids Risk Scoring
This healthcare analytics subset requires organizations to quantify complex but vital measures for running the organization. Although healthcare organizations are keenly focused on improving health for each member under care, providers and payers alike are still slow in adopting risk scoring capabilities that offer a holistic portrayal of member health.
Popular risk scoring structures like Hierarchical Condition Codes (HCC) compute only a single risk score per member. The models tabulate members’ relative health based on physician diagnosis but don’t offer specific, actionable health improvement and disease prevention insights based on these scores.
However, the landscape is evolving with the emergence of advanced analytics and big data technologies. As new innovations challenge the status quo, they’re fueling risk scoring capabilities’ evolution towards offering specific, actionable insights. Instead of computing one risk score per member, calculations are starting to incorporate clinical conditions, behavioral health status, and social determinants of health to help you understand and address each member’s holistic needs.
Machine learning predictive analytics is also helping healthcare providers compute illness-specific risk sfactors to identify those patients with the highest chance of hospital admission. Those who adopted the methodology early are already reaping the rewards, reducing admissions and readmissions while diminishing member medical costs and improving the health of their patients.
Big Data Key Performance Indicators (KPIs)
KPIs should simplify how CFOs and executives monitor the strategic performance of their healthcare facilities – but that’s not always the case. You may be tempted to track every bit of data in your hands, which can distract you from reporting used to predict future performance and critical forecasting needs.
Refining your KPIs using big data lets you mine datasets for insights that will influence vital business decisions to enhance your performance and impact your bottom line.
Effective KPIs must be:
Quantifiable and well-defined
Thoroughly communicated within your healthcare facility
Crucial to your goals
Relevant to your line of business
Achieve Better Results Using the Clinify Health Approach
Clinify Health is focused on enabling providers to develop, deploy, and manage population health strategies specific to their patient populations through a technology and services offering with the goal of improving their ability to enter in to and succeed in alternative payment arrangements. As the leading value-based care enablement partner, Clinify empowers success through customized practice transformation and access to actionable business and clinical data.
Clinify Health’s approach covers vital areas like KPIs, patient stratification, billing, and 837 and 835 analyses. Contact us for more information or to request our demo.