Physicians' experience adopting the electronic transfer of care communication tool: barriers and opportunities

Effectiveness of an Electronic Communication Tool on Transitions in Care From the Intensive Care Unit: Protocol for a Cluster-Specific Pre-Post Trial

BACKGROUND

Transitions in care are vulnerable periods in health care that can expose patients to preventable errors due to incomplete or delayed communication between health care providers. Transitioning critically ill patients from intensive care units (ICUs) to other patient care units (PCUs) is particularly risky, due to the high acuity of the patients and the diversity of health care providers involved in their care. Instituting structured documentation to standardize written communication between health care providers during transitions has been identified as a promising means to reduce communication breakdowns. We developed an evidence-informed, computer-enabled, ICU-specific structured tool-an electronic transfer (e-transfer) tool-to facilitate and standardize the composition of written transfer summaries in the ICUs of one Canadian city. The tool consisted of 10 primary sections with a user interface combination of structured, automated, and free-text fields.

OBJECTIVE

Our overarching goal is to evaluate whether implementation of our e-transfer tool will improve the completeness and timeliness of transfer summaries and streamline communications between health care providers during high-risk transitions.

METHODS

This study is a cluster-specific pre-post trial, with randomized and staggered implementation of the e-transfer tool in four hospitals in Calgary, Alberta. Hospitals (ie, clusters) were allocated randomly to cross over every 2 months from control (ie, dictation only) to intervention (ie, e-transfer tool). Implementation at each site was facilitated with user education, point-of-care support, and audit and feedback. We will compare transfer summaries randomly sampled over 6 months postimplementation to summaries randomly sampled over 6 months preimplementation. The primary outcome will be a binary composite measure of the timeliness and completeness of transfer summaries. Secondary measures will include overall completeness, timeliness, and provider ratings of transfer summaries; hospital and ICU lengths of stay; and post-ICU patient outcomes, including ICU readmission, adverse events, cardiac arrest, rapid response team activation, and mortality. We will use descriptive statistics (ie, medians and means) to describe demographic characteristics. The primary outcome will be compared within each hospital pre- and postimplementation using separate logistic regression models for each hospital, with adjustment for patient characteristics.

RESULTS

Participating hospitals were cluster randomized to the intervention between July 2018 and January 2019. Preliminary extraction of ICU patient admission lists was completed in September 2019. We anticipate that evaluation data collection will be completed by early 2021, with first results ready for publication in spring or summer 2021.

CONCLUSIONS

This study will report the impact of implementing an evidence-informed, computer-enabled, ICU-specific structured transfer tool on communication and preventable medical errors among patients transferred from the ICU to other hospital care units.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03590002; https://www.clinicaltrials.gov/ct2/show/NCT03590002.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18675.

Promoting Relational Agent for Health Behavior Change in Low and Middle - Income Countries (LMICs): Issues and Approaches

The use of contemporary technologies in healthcare systems to improve quality of care and to promote behavioral healthcare outcomes are prevalent in high-income countries. However, low and middle-income countries (LMICs) are not receiving the same advantages of technology, which may be due to inadequate technological infrastructure and financial resources, lack of interest among policy makers and healthcare service providers, lack of skills and capacity among healthcare professionals in using technology based interventions, and resistance of the public to the use of technologies for healthcare or health promotion activities. Technology-based interventions offer considerable promise to develop entirely new models of healthcare both within and outside of formal systems of care and offer the opportunity to have a large public health impact. Such technology-based interventions could be used to address targeted global health problems in LMICs, including the chronic non-communicable diseases (NCDs) - a growing health system burden in LMICs. Major preventable behavioral risk factors of chronic NCDs are increasing in LMICs, and innovative interventions are essential to address these risk factors. Computer-based or mobile-based virtual coaches or Relational Agents (RAs) are increasingly being explored for counseling patients to change their health behavior in high-income countries; however, the use of RAs in LMICs has not been studied. In this paper, we summarize the growing application of RA technology in behavior change interventions in high-income countries and describe the potential of its use in LMICs. Finally, we review the potential barriers and challenges in promoting RAs in LMICs.

Integrating mHealth at point of care in low- and middle-income settings: the system perspective

While the field represents a wide spectrum of products and services, many aspects of mHealth have great promise within resource-poor settings: there is an extensive range of cheap, widely available tools which can be used at the point of care delivery. However, there are a number of conditions which need to be met if such solutions are to be adequately integrated into existing health systems; we consider these from regulatory, technological and user perspectives. We explore the need for an appropriate legislative and regulatory framework, to avoid ‘work around’ solutions, which threaten patient confidentiality (such as the extensive use of instant messaging services to deliver sensitive clinical information and seek diagnostic and management advice). In addition, we will look at other confidentiality issues such as the need for applications to remove identifiable information (such as photos) from users’ devices. Integration is dependent upon multiple technological factors, and we illustrate these using examples such as products made available specifically for adoption in low- and middle-income countries. Issues such as usability of the application, signal loss, data volume utilization, need to enter passwords, and the availability of automated or in-app context-relevant clinical advice will be discussed. From a user perspective, there are three groups to consider: experts, front-line clinicians, and patients. Each will accept, to different degrees, the use of technology in care – often with cultural or regional variation – and this is central to integration and uptake. For clinicians, ease of integration into daily work flow is critical, as are familiarity and acceptability of other technology in the workplace. Front-line staff tend to work in areas with more challenges around cell phone signal coverage and data availability than ‘back-end’ experts, and the effect of this is discussed.

Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature

Background

eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality.

Objective

Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure.

Methods

We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles.

Results

Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1).

Conclusions

The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved.

Prospective economic evaluation of an electronic discharge communication tool: analysis of a randomised controlled trial

OBJECTIVE

To complete an economic evaluation within a randomised controlled trial (RCT) comparing the use of an electronic discharge communication tool (eDCT) compared with usual care.

SETTING

Patients being discharged from a single tertiary care centre's internal medicine Medical Teaching Units.

PARTICIPANTS

Between January 2012 and December 2013, 1399 patients were randomised to a discharge mechanism. Forty-five patients were excluded from the economic evaluation as they did not have data for the index hospitalisation cost; 1354 patients contributed to the economic evaluation.

INTERVENTION

eDCT generated at discharge containing structured content on reason for admission, details of the hospital stay, treatments received and follow-up care required. The control group was discharged via traditional dictation methods.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary economic outcome was the cost per quality-adjusted life year (QALY) gained. Secondary outcomes included the cost per death avoided and the cost per readmission avoided.

RESULTS

The average transcription cost was $C22.28 per patient, whereas the estimated cost of the eDCT was $C13.33 per patient. The cost per QALY gained was $C239 933 in the eDCT arm compared with usual care due to the very small gains in effectiveness and approximately $C800difference in resource utilisation costs. The bootstrap analyses resulted in eDCT being more effective and more costly in 29.2% of samples, less costly and more effective in 29.2% of samples, less effective and more costly in 23.9% of samples and finally, less costly and less effective in 17.7% of samples.

CONCLUSIONS

The eDCT reduced per patient costs of the generation of discharge summaries. The bootstrap estimates demonstrate considerable uncertainty supporting the finding of neutrality reported in the clinical component of the RCT. The immediate transcription cost savings and previously documented provider and patient satisfaction may increase the impetus for organisations to invest in such systems, provided they have a foundation of eHealth infrastructure and readiness.

TRIAL REGISTRATION NUMBER

NCT01402609.

Adoption of e-health technology by physicians: a scoping review

OBJECTIVE

The goal of this scoping review was to summarize the current literature identifying barriers and opportunities that facilitate adoption of e-health technology by physicians.

DESIGN

Scoping review.

SETTING

MEDLINE, EMBASE, and PsycINFO databases as provided by Ovid were searched from their inception to July 2015. Studies captured by the search strategy were screened by two reviewers and included if the focus was on barriers and facilitators of e-health technology adoption by physicians.

RESULTS

Full-text screening yielded 74 studies to be included in the scoping review. Within those studies, eleven themes were identified, including cost and liability issues, unwillingness to use e-health technology, and training and support.

CONCLUSION

Cost and liability issues, unwillingness to use e-health technology, and training and support were the most frequently mentioned barriers and facilitators to the adoption of e-health technology. Government-level payment incentives and privacy laws to protect health information may be the key to overcome cost and liability issues. The adoption of e-health technology may be facilitated by tailoring to the individual physician's knowledge of the e-health technology and the use of follow-up sessions for physicians and on-site experts to support their use of the e-health technology. To ensure the effective uptake of e-health technologies, physician perspectives need to be considered in creating an environment that enables the adoption of e-health strategies.