Click here to learn more about author Jon Pilkington.
According to Grandview Research, the global healthcare Data Analytics market will grow to $42.8 billion by 2024, as healthcare companies increasingly use data for financial applications, and to improve operational and administrative processes. The industry’s reliance on Data Analytics is also being driven by the increased use of electronic health records (EHRs) as well as the digitization of financial records and insurance claims processing.
While the use cases for data in healthcare are endless, in this post, we’ll take a look at how analytics outcomes can specifically impact administrative and financial offices in healthcare organizations of all types and sizes.
Healthcare administrators are increasingly tasked with making faster, better financial decisions – from managing cash flow and cutting costs, to identifying gaps in the revenue cycle and pinpointing opportunities for increased profitability. And they need to be able to find, access, prepare and blend data from all of the sources at their disposal – including EHR systems, 835/837 insurance claim remittances, billing statements, insurance denial forms and reimbursement system reports – for a 360-degree view of financial operations. Only then will they be able to make more informed financial decisions and effectively improve the revenue lifecycle.
Although it sounds like a simple task to grab information from disparate sources and combine it into one large database or spreadsheet for analysis, the reality is that Data Quality and access are the biggest pain points faced by finance administrators today. Data that provides the best analytical value has traditionally been locked away in multi-structured or unstructured documents, such as text reports, web pages, PDFs, JSON, and log files. The only way for data users to access this information has been to manually rekey and reconcile the data, which are time-intensive and error-prone processes. Additionally, in many instances, an organization’s source data is diverse, and rarely presents itself in a form that is accessible or in the format needed to perform analytics.
What does this mean for the business? Important financial decisions are often based on incomplete, inaccurate or outdated data. Not only does this impact a healthcare company’s patient care, financial processes and bottom line, but it can also affect claims coding and HIPAA compliance. Violation of HIPAA compliance, in particular, comes at a heavy price, with fines ranging from $50,000 to $1.5 million.
The good news is that most of the common problems faced by healthcare financial management professionals can be addressed, and in many cases completely solved, by implementing data preparation software.
This transforming technology automates data retrieval and preparation processes, enabling administrators to easily access, manipulate, enrich and combine disparate data from virtually any source – and then quickly prepare it for analysis in visualization, analytics, and cognitive tools in a fraction of the time that it takes using spreadsheets and other manually-intensive measures. And included governance features – such as data masking, data retention, data lineage, and role-based permissions – are applied throughout data access, preparation and analytics processes to keep patient data safe, and healthcare organizations’ compliant with industry and federal regulations.
When empowered with the ability to rapidly and easily access, combine, prep, analyze and transform data into actionable intelligence, tasks ranging from 835/837 remittance file reconciliation, to scrubbing patient and provider data, can be streamlined and automated, significantly improving revenue cycle efficiency. Most importantly, finance professionals can make faster, more informed decisions and improve operational processes – both of which deliver unrivaled business value that improves patient care and the bottom line.