A recent survey conducted by the Healthcare Information and Management Systems Society (HIMSS) and healthcare data analytics company Arcadia aimed to assess the current state of healthcare analytics platforms. The survey polled 55 healthcare executives, clinical leaders, and health IT stakeholders to better understand data utilization within hospitals and health systems.
The survey findings revealed that less than 60 percent of health systems’ data is currently being used to inform intelligent business decisions. However, stakeholders emphasize the importance of data access in improving healthcare outcomes.
Access to high-quality data was identified as a crucial factor by approximately 93 percent of respondents. The quality of data across workflows and platforms was seen as vital to a healthcare organization’s performance. The findings also showed that organizations using Epic as their primary electronic health record (EHR) platform had a slightly lower agreement with the importance of data access compared to organizations using other EHR platforms such as Cerner.
The size of an organization also influenced analytics priorities. Larger organizations, with 15,000 or more employees, were more likely to implement clinical decision support (CDS) tools within the next 12 months compared to smaller organizations. Additionally, organizations with 7,500 or more employees were more inclined to implement decision-making tools for their provider networks.
Investing in analytics proved to be a common challenge across healthcare organizations. While around 82 percent of respondents reported satisfaction with their current analytics platform, 71 percent cited other strategic priorities as barriers to further investment in analytics platforms. Limited staff resources were also seen as a challenge by 58 percent of respondents.
Data accuracy was another area of concern. Approximately one-third of respondents reported that their data accuracy was less than 76 percent. However, there was a noticeable difference in data accuracy perceptions based on the role of the respondent within the organization, with executive leadership roles generally reporting higher data accuracy percentages compared to clinical or IT roles.
In terms of data utilization for business decision-making, on average, only 57 percent of an organization’s data was used for this purpose. Larger organizations and those within integrated delivery networks (IDNs) or multi-hospitals were more likely to report using their data for intelligent business decisions.
The survey also highlighted the varied implementation of artificial intelligence (AI) tools in healthcare organizations. Research conducted by the Center for Connected Medicine and KLAS revealed that two-thirds of respondents were already using AI within their organizations, with a higher prevalence among facilities with over 1,001 beds. Pre-built machine learning models were the most popular AI solutions, with a focus on health/disease management and prediction.
Overall, the survey findings shed light on the current state of healthcare analytics platforms, emphasizing the importance of data access, data accuracy, and data utilization for informed decision-making in healthcare organizations.
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