Survey reveals data analytics remains top challenge for health IT industry

For the second year in a row, the annual Health IT Industry Outlook Survey, designed to highlight industry trends and pain points, revealed that data analytics tops the list of challenges for health IT professionals (chief information officers, chief medical information officers, IT directors and consultants.) In fact, thirty-three percent of respondents identified data analytics and business intelligence as the hottest topic for 2016.

These results reflect that healthcare leaders are now recognizing the value in effective use of statistical data and trends to improve financial performance and patient outcomes. In addition, results show that they are influenced by enhanced data visualization capabilities advancing over the past few years. With greater ease in end-user understanding and proactive interpretation, actionable data insights tie into the success of population health management and value-based care initiatives promoted across the healthcare industry. Additionally, more accessible data, that is both reliable and comprehensive, allows providers to have timely evidence to support decisions for safer care.

Below is an overview of specific data challenges and implications revealed by the survey and suggestions for how they can be addressed.

Integrating dissimilar data sources

According to the survey, the most significant (33 percent) hurdle for healthcare organizations with data analytics programs is “correlating data from diverse and dissimilar sources.” The problem is that enterprise resource planning (ERP) systems commonly used by healthcare organizations to manage and interpret data are not sufficient for linking dissimilar sources of data. Though an ERP can manage operational staff data, it cannot store patient care information. As such, conducting a financial analysis of a patient care issue requires resourcefulness around dissimilar sources. The issue of dissimilar sources doesn’t solely impact financials though. On the clinical side, data from other providers is often not normalized, so something as simple as a blood pressure reading can be presented in varied data formats for interpretation.

Conducting a clinical or financial analysis efficiently and affordably requires a deeper understanding of the healthcare industry and cross-departmental operations and responsibilities. This can be difficult to attain with limited internal resources, especially for small community hospitals with limited staff. Third-party advisers, such as consultants with years of industry and operational experience across multiple facets of a healthcare organization, can step in to provide information, understanding and additional resources for interpreting disparate systems.

Lack of resources to sustain data analytics programs

Almost three-fourths of survey respondents indicated their data analytics programs are either under way but lack resources to complete requested initiatives, or their programs are young and need assistance to further develop.

No matter the size of the organization or budget, a healthcare organization would benefit by first determining program objectives and infrastructure before launching a data analytics program. Despite competing projects, time and resources must be dedicated to setting reasonable goals that are not too broad or too granular. By honing in on one or two specific, yet meaningful initiatives, organizations will achieve more realistic and measurable success. From those goals, a solid governance committee should be established to prioritize incoming requests, communicate with end users, gain leadership’s support and understanding of program progress and deliverables, and oversee program projects through completion.

Revenue cycle management barriers

Lastly, 40 percent of survey respondents indicated they see “inability or challenges with trending benchmarking data to identify areas of improvement” as the leading revenue cycle management (RCM) barrier for their healthcare organizations.  

Similar to the data analytics obstacle identified within the survey, this revenue cycle challenge requires combining data across disparate systems. Financial leaders of a community hospital, for example, would benefit by understanding care expenses and costs, charges going out the door, payment data from patient insurers and payment data from patient self-pay. They need to correlate this data from several different sources to understand how the organization’s payment outcomes affect patient care. Customized dashboards enable optimized workflow and processes, going beyond an initial few layer drill downs across revenue cycle performance. Analysts need to comprehend and extract data from across the board – including scheduling, acute billing, patient access, ERP, coding and ambulatory billing at a minimum.

Additionally, organizations tend to struggle with staying on top of their revenue cycle goals and management when transitioning EHR systems. It is important for RCM and IT leaders to stay aligned throughout the entire process, from system selection to go-live and optimization. Prior to implementation, it’s important for HIT professionals to take steps to  understand and prepare for how the system rollout will affect processes, like registration data quality assurance, remittance management and eligibility verification, and claims management workflow.

Revenue cycle management is much more than business office statistics. RCM truly starts at the time of scheduling appointments and continues all the way through billing insurance and patient responsibility, following through until an account balance is zero. By evaluating the data of the entire care story and integrating it into a meaningful overall picture, healthcare organizations can effectively change necessary behavior and processes to drive improvement.