Using Cognitive Load Theory to Improve Posthospitalization Follow-Up Visits

Advancing health information during interhospital transfer: An interrupted time series

INTRODUCTION

Although the transfer of patients between acute care hospitals (interhospital transfer, IHT) is common, health information exchange (HIE) during IHT remains inadequate, with fragmented communication and unreliable access to clinical information. This study aims to design, implement, and rigorously evaluate the implementation of a HIE platform to improve data access during IHT.

METHODS AND ANALYSIS

Study subjects include patients aged >18 transferred to the medical, cardiology, oncology, or intensive care unit (ICU) services at an 800-bed quaternary care hospital; and healthcare workers involved in their care. The first aim of this study is to optimize clinician workflow, data visualization, and interoperability through user-centered design sessions for HIE platform development. The second aim is to evaluate the impact of the intervention on clinician-reported medical errors among 500 pre- and 500 postintervention IHT patients using interrupted time series methodology, adjusting for confounding variables and temporal trends. The third aim is to evaluate intervention fidelity, use and perceived usability of the platform, and barriers and facilitators of implementation from interprofessional stakeholder input, using mixed-methods evaluation. The fourth aim is to consolidate key findings to create a toolkit for spread and sustainability.

ETHICS AND DISSEMINATION

We will track patient safety endpoints and clinician workflow burdens and ensure the protection of patient data throughout the study. We will disseminate our findings via the creation of a toolkit for spread and sustainability, partnering with our funder (AHRQ) for dissemination, and communicating our results via abstracts and publications.

Concepts and metrics of clinician attention: a scoping review protocol

INTRODUCTION

There is growing emphasis on the importance of both the cognitive and behavioural phenomenon of attention for clinicians engaged in patient care. Aspects of attention such as cognitive load, distraction and task switching have been studied in various settings with different methodologies. Using the protocol described here, we aim to systematically review the medical literature in order to map the concept of attention and to synthesise diverse concepts and methods under the broader category of research focused on 'attention'.

METHODS AND ANALYSIS

Following the methodology described by the Joanna Briggs Institute and Arksey and O'Malley, our scoping review conducts an iterative search of Cumulative Index of Nursing and Allied Health Literature (CINAHL), Medline (PubMed) and EMBASE (Ovid). An initial limited search based on key concepts and terminology will generate relevant articles which in turn will be mined for additional keywords and index terms to guide a formal literature search. Our multidisciplinary team will extract data into a matrix, including a small random sample of the same studies (to ensure concordance), and present the results in a descriptive narrative format.

ETHICS AND DISSEMINATION

As a secondary analysis, our study does not require ethics approval, and we will ensure that included studies have appropriate approval. We anticipate results will identify diverse ways of conceptualising clinician attention and will provide a foundation for developing additional metrics and study methods to optimise attention in the clinical environment. We will disseminate results through journals and conferences and coordinate with colleagues doing work in adjacent fields.

Impact of a problem-oriented view on clinical data retrieval

OBJECTIVE

The electronic health record (EHR) data deluge makes data retrieval more difficult, escalating cognitive load and exacerbating clinician burnout. New auto-summarization techniques are needed. The study goal was to determine if problem-oriented view (POV) auto-summaries improve data retrieval workflows. We hypothesized that POV users would perform tasks faster, make fewer errors, be more satisfied with EHR use, and experience less cognitive load as compared with users of the standard view (SV).

METHODS

Simple data retrieval tasks were performed in an EHR simulation environment. A randomized block design was used. In the control group (SV), subjects retrieved lab results and medications by navigating to corresponding sections of the electronic record. In the intervention group (POV), subjects clicked on the name of the problem and immediately saw lab results and medications relevant to that problem.

RESULTS

With POV, mean completion time was faster (173 seconds for POV vs 205 seconds for SV; P < .0001), the error rate was lower (3.4% for POV vs 7.7% for SV; P = .0010), user satisfaction was greater (System Usability Scale score 58.5 for POV vs 41.3 for SV; P < .0001), and cognitive task load was less (NASA Task Load Index score 0.72 for POV vs 0.99 for SV; P < .0001).

DISCUSSION

The study demonstrates that using a problem-based auto-summary has a positive impact on 4 aspects of EHR data retrieval, including cognitive load.

CONCLUSION

EHRs have brought on a data deluge, with increased cognitive load and physician burnout. To mitigate these increases, further development and implementation of auto-summarization functionality and the requisite knowledge base are needed.