Persisting workarounds in Electronic Health Record System use: types, risks and benefits

An Analysis of Incident Reports Related to Electronic Medication Management: How They Change Over Time

OBJECTIVE

Electronic medication management (EMM) systems have been shown to introduce new patient safety risks that were not possible, or unlikely to occur, with the use of paper charts. Our aim was to examine the factors that contribute to EMM-related incidents and how these incidents change over time with ongoing EMM use.

METHODS

Incidents reported at 3 hospitals between January 1, 2010, and December 31, 2019, were extracted using a keyword search and then screened to identify EMM-related reports. Data contained in EMM-related incident reports were then classified as unsafe acts made by users and the latent conditions contributing to each incident.

RESULTS

In our sample, 444 incident reports were determined to be EMM related. Commission errors were the most frequent unsafe act reported by users (n = 298), whereas workarounds were reported in only 13 reports. User latent conditions (n = 207) were described in the highest number of incident reports, followed by conditions related to the organization (n = 200) and EMM design (n = 184). Over time, user unfamiliarity with the system remained a key contributor to reported incidents. Although fewer articles to electronic transfer errors were reported over time, incident reports related to the transfer of information between different computerized systems increased as hospitals adopted more clinical information systems.

CONCLUSIONS

Electronic medication management-related incidents continue to occur years after EMM implementation and are driven by design, user, and organizational conditions. Although factors contribute to reported incidents in varying degrees over time, some factors are persistent and highlight the importance of continuously improving the EMM system and its use.

Challenges in reaching patients with severe mental illness for trials in general practice-a convergent mixed methods study based on the SOFIA pilot trial

BACKGROUND

Patients with severe mental illness (SMI) die prematurely due to undetected and inadequate treatment of somatic illnesses. The SOFIA pilot study was initiated to mend this gap in health inequity. However, reaching patients with SMI for intervention research has previously proven difficult. This study aimed to investigate the recruitment of patients with SMI for the SOFIA pilot study in 2021.

METHODS

We used a mixed-method convergent design. The qualitative material comprised 20 interviews with general practitioners (GPs) and staff, during patient recruitment. The quantitative data consisted of process data on baseline characteristics, GPs reported reasons for excluding a patient, reported reasons for patients declining participation, and registered data from a Danish population of patients with SMI. We used thematic analysis in the qualitative analysis and descriptive statistics for the quantitative analysis. Pillar integration was used for integrating the material.

RESULTS

Our findings show that selection bias occurred in the pilot study. We describe four main themes based on the integrated analysis that highlights selection issues: (1) poor data quality and inconsistency in defining severity definitions troubled identification and verification, (2) protecting the patient and maintaining practice efficiency, (3) being familiar with the patient was important for a successful recruitment, and (4) in hindsight, the GPs questioned whether the target population was reached.

CONCLUSIONS

In the light of theories of professions and street-level bureaucracy, we find that the main drivers of the patient selection bias occurring in the SOFIA pilot study were that 1) GPs and staff mended eligibility criteria to protect certain patients and/or to minimize workload and maintain efficiency in the practice 2) the data from the GP record systems and the digital assessment tool to assist recruitment was not optimal. Interventions targeting this patient group should carefully consider the recruitment strategy with a particular focus on professionals' discretionary practices and information technology pitfalls.

TRIAL REGISTRATION

The pilot trial protocol was registered on the 5th of November 2020. The registration number is NCT04618250 .

Fragmented care trajectories in municipal healthcare: Local sensemaking of digital documentation

Objective

Since the 1990s, almost all healthcare organisations have had electronic health records (EHR) to organise and manage treatment, care and work routines. This article aims to understand how healthcare professionals (HCPs) make sense of digital documentation practice.

Methods

Based on a case study design, field observations and semi-structured interviews were conducted in a Danish municipality. A systematic analysis based on Karl Weick's sensemaking theory was applied to investigate what cues HCPs extract from timetables in the EHR and how institutional logics frame the enactment of documentation practice.

Results

The analysis uncovered three themes: making sense of planning, making sense of tasks and making sense of documentation. The themes illustrate that HCPs make sense of the digital documentation practice as a dominant managerial tool designed to control resources and work routines. This sensemaking leads to a task-oriented practice which centres on delivering fragmented tasks according to a timetable.

Conclusion

HCPs mitigate fragmentation by responding to a care professional logic, where they document to share information and carry out invisible work outside of timetables and scheduled tasks. However, HCPs are focused on solving specific tasks by the minute with the possible consequence that continuity and their overview of the service user's care and treatment disappear. In conclusion, the EHR system eliminates a holistic view of care trajectories, leaving it up to HCPs to collaborate in an effort to obtain continuity for the service user.

Transition to a new nursing information system embedded with clinical decision support: a mixed-method study using the HOT-fit framework

BACKGROUND

Nursing information systems embedded with standardized nursing language and clinical decision support have been increasingly introduced in health care settings. User experience is key to the adoption of health information technologies. Despite extensive research into the user experience with nursing information systems, few studies have focused on the interaction between user, technology and organizational attributes during its implementation. Guided by the human, organization and technology-fit framework, this study aimed to investigate nurses' perceptions and experiences with transition to a new nursing information system (Care Direct) 2 years after its first introduction.

METHODS

This is a mixed-method study using an embedded design. An online survey was launched to collect nurses' self-reported use of the new system, perceived system effectiveness and experience of participation in system optimization. Twenty-two semi structured interviews were conducted with twenty nurses with clinical or administrative roles. The quantitative and qualitative data were merged using the Pillar Integration Process.

RESULTS

The average score of system use behavior was 3.76 ± 0.79. Regarding perceived system effectiveness, the score of each dimension ranged 3.07-3.34 out of 5. Despite large variations in approaches to participating in system optimization, nurses had generally positive experiences with management and technical support. Eight main categories emerged from the integrated findings, which were further condensed into three themes: perceptions on system content, structure, and functionality; perceptions on interdisciplinary and cross-level cooperation; and embracing and accepting the change.

CONCLUSIONS

Effective collaboration between clinicians, administrators and technical staff is required during system promotion to enhance system usability and user experience. Clear communication of organizational missions to staff and support from top management is needed to smooth the system implementation process and achieve broader system adoption.

Stakeholder perspectives of system-related errors: Types, contributing factors, and consequences

BACKGROUND

Despite growing evidence of the benefits of electronic medication management systems (EMMS), research has also identified a range of new safety risks linked with their use. There is limited qualitative research focusing on system-related errors that result from use of EMMS. The aim of this study was to explore in-depth stakeholders' perceptions and experiences of system-related errors.

METHODS

Semi-structured interviews were conducted with EMMS users and other relevant staff (e.g. supporting roles in EMMS) across a local health district in Sydney, Australia. Analysis was conducted iteratively using a general inductive approach, and then mapped to Reason's accident causation model, where codes were categorized as 1) unsafe acts (i.e. what error occurred), 2) latent conditions (i.e. what factors contributed to errors), and 3) consequences resulting from the error.

RESULTS

Twenty-five participants were interviewed between September 2020 and May 2021. Participants most frequently described omission errors (e.g. failure to check for duplicate orders) as unsafe acts, although commission errors and workarounds were also reported. Poor EMMS design was reported to be a significant workplace factor contributing to system-related errors, however participants also described user factors, such as an overreliance on the system, and organizational factors, such as system downtime, as contributing to errors. Reported consequences of system-related errors included medication errors, but also impacts to the EMMS and on workers.

CONCLUSIONS

EMMS design is a significant contributor to system-related errors, but this research showed that user and organizational factors are also at play. As these factors are not independent, minimizing system-related errors requires a multi-faceted approach, where mitigation strategies target not only the EMMS, but also the context in which the system has been implemented.