Data is an invaluable resource that informs nearly every choice we make, but poor data quality can have devastating effects on the decision-making process and financial outcomes. When it comes to health and patient care in particular, the stakes are at their highest. New research from Sage Growth Partners commissioned by InterSystems, involving C-level leaders from top healthcare organisations, reveals just how critically and financially important harmonised data is, and how investing in higher quality data can yield better benefits and decision-making for patient care.
Hospitals and healthcare organisations (HCOs) currently face a number of bad data challenges, from a growing number of disparate data sources to erroneous and siloed data in fragmented repositories. These inefficient practices can impose a significant financial burden. Research shows that 43% of IT staff time is spent on data extraction and harmonisation. Cutting that time in half alone could save an HCO upwards of nearly US$1.6M in three years.
The report suggests that implementing what has come to be known as a smart data fabric can unify and democratise information, ultimately improving the finances, management and operations of a health system. A smart data fabric can embed a wide range of analytic capabilities, including business intelligence, natural language processing and machine learning to make it easier and faster for HCOs to process and share more accurate data. By implementing a smart data fabric and true interoperability standard across an entire health enterprise, HCOs could save upwards of US$42.1 million over the course of three years.
“Every clinical and operational decision in healthcare is driven by data,” said Alex MacLeod, Director of Healthcare Commercial Initiatives at InterSystems. “Implementing solutions such as a smart data fabric can improve the quality of the data, enhance interoperability and dramatically increase cost savings for HCOs. There is a pressing need for easy access to data from a single source of truth to put actionable insights back into the hands of administrators and clinicians and improve patient care.”
The report looks at the cost of manual data input, duplicate and inaccurate testing, and errors during transition of care as some of the impacts of poor data quality. It also considers the costs of shadow IT systems – hardware, software or other programs not supported by a central IT department – and finds these currently consume 40% of the total IT capital budget. Reducing them by half could save the typical HCO a total of US$10 million over three years.
“The financial burden of bad data cannot be ignored,” said Stephanie Kovalick, Chief Strategy Officer of Sage Growth Partners. “The annual cost of poor data quality in the U.S. across all industries tracks upwards of US$3.1 trillion. According to Gartner, this burden can be as much as US$12.9 million for an organisation due to data management challenges. With the escalating cost of healthcare in the US, health systems must start to pay more attention here. Investing in a smart data fabric is key to significantly reducing costs and saving clinicians valuable time spent otherwise on chasing and cleansing data to ensure the best possible outcomes.”
For more detailed information, read the recent market report “Bad Data, Bad Analytics, Bad Decisions.” And watch the recent LinkedIn Live as Stephanie Kovalick discusses the survey findings and what they mean for the industry in greater detail. You can download the full white paper here.
About Sage Growth Partners
Sage Growth Partners accelerates commercial success for B2B, B2B2C and B2C healthcare organisations through a singular focus on growth. The company helps its clients thrive amid the complexities of a rapidly changing marketplace with deep domain expertise and an integrated application of research, strategy and marketing. Founded in 2005, Sage Growth Partners is located in Baltimore, MD, and serves clients such as the National Minority Health Association, Philips Healthcare, U.S. Renal Care, Quest Diagnostics, Livongo, Olive and iN2L.