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Abstract
Background The Socio-Technical Model of Health Information Technology (STMHIT) (figure 1) is important to consider in improvement science as it supports the understanding of how technology facilitates the design and development of complex adaptive healthcare systems and supports the implementation of usability-based informatics applications such as accurate documentation in Electronic Health Records (EHRs), dashboards and clinical reminders.
Objectives The aim of the Quality Improvement (QI) project was to ensure that 100% of patients over 65 received the Institute for Healthcare Improvement’s Age-Friendly Health Systems 4Ms care: What Matters, Medications, Mentation, and Mobility by December 2022 (figure 2). The STMHIT was used to align the workflow to technology and ensure uptake of 4Ms care and accurate recording of performance.
Methods The project started with leadership creation of the documentation fields in the EHR and education for 3,300 providers to provide age-friendly care. The next PDSA was an EHR best practice alert that resulted in a 20% increase in 4Ms deliver (figure 3). A dashboard was created to provide feedback to the providers on performance to enhance uptake (figure 4).
Results Uptake of the 4Ms as a set reached 11.8% in May, 2022 (figure 5)/Iterative focus groups revealed that one barrier to obtaining the goal of 4Ms care was documentation omission. PDSA cycles to improve documentation included education, tip sheets, and videos on documenting the 4Ms, and coaching providers to perform chart reviews to learn why the documentation omissions were occurring. Feedback revealed that a deeper understanding of the usability and usefulness of the interface specific to documentation alignment with user workflow was needed.
Socio-technical model of health information technology
Institute for healthcare improvement age-friendly health systems 4Ms
Improvement in 4Ms update due to best practice alert
Technology enhanced dashboards to monitor progress capabilities
Proportion statistical process control analysis (p Chart) for the weekly proportion of eligible patients meeting “4M” criteria from 2020-2022 (n=324,245). Data points (dark blue dots and line) represent the proportion of eligible patients meeting criteria. The light blue line represents the overall average proportion. The red dashed lines show the upper and lower control limits, which are 3 sigma deviations (approximately 2.67 standard deviations) above and below the overall average proportion line (light blue line). The analysis was split with new overall averages (light blue lines) and control limits (red dashed lines) calculated when sustained non-random variations (sustained special cause signals meeting Shift or Trend criteria via IHI detection rules) were observed to assess for new performance characteristics following each split
Conclusions The QI case study revealed the importance of understanding human-computer interaction and considering the user-technology interface in improvement strategies. Research is in process that expands the STMHIT to explore the documentation interface with the current workflow to evaluate implementation usability, document efficiency, satisfaction, and usefulness.