5.6 Barriers to data analytics in healthcare

Several challenges have been cited in the literature on the use of data analytics in healthcare.

Data accuracy

Healthcare data is assembled from various resources and sometimes is entered into relevant software and data platforms by staff that do not have expertise with medically accepted terminology or language (Chen et al., 2020b). Data may be an inaccurate representation of the patient journey, especially if relying on this entry data to retrieve patient information for a specific initiative.

Fragmented patient care

Several organisations have hybrid platforms to record patient data during their inpatient stay, including transition across sites (Chen et al., 2020b; Pastorino et al., 2019). Lack of integration of software used by departments within the same organisation can lead to fragmented data entry, miscommunication and fragmented care (Chen et al., 2020b; Tan et al., 2015). This also applies to multisite organisations that have not fully implemented an electronic health record across all sites, resulting in a combination of paper-based and electronic patient data documentation.

Data privacy and security

Due to fast advancements in IT and the vast amount of data available on the web, healthcare organisations must take all necessary steps to enhance security of patient data against possible cyber breach or malware (Chen et al., 2020b). Healthcare organisations must ensure patient and staff information is protected by using up-to-date antivirus tools, multifactor authentication and encryption of sensitive data (Reddy et al., 2022).

Cost

Data retrieval is costly, especially if it involves various interfaces, analysis and processing to present it in a meaningful way to potential users (Chen et al., 2020b). Factors affecting the cost of data analytics include the type, amount and quality of data, the objectives of data analytics, vendor pricing, time taken by content experts to analyse data and customise it to meet the objectives, and organisational adaptability and readiness for change (Pastorino et al., 2019).

Human resources

The availability of suitably trained data IT analysts to manage all aspects of data can be challenging for smaller and rural health organisations (Schaeffer et al., 2017). Lack of appropriate skills and capability can present a hindrance to successful implementation of data analytics if not accounted for in workforce planning (Schaeffer et al., 2017).