Barriers for Hospital-Based Nurse Practitioners Utilizing Clinical Decision Support Systems: A Systematic Review

Standardizing and optimizing nutrition evaluation frequency of enterally fed patients in an ambulatory pediatric gastroenterology practice: A single-center study

BACKGROUND

Nutrition monitoring is essential in feeding tube-dependent patients receiving home enteral nutrition (HEN). We identified lack of consistency in dietitian evaluations for our pediatric patients receiving HEN. Consequently, after establishing an institutional standard for nutrition reassessment intervals, we underwent a quality improvement (QI) initiative to improve rates of adherence to standard frequency of dietitian consults and referrals among patients receiving HEN.

METHODS

A prospective QI initiative from April 2021 to December 2021 was performed using multiple plan-do-study-act (PDSA) cycles. Interventions included (1) a reminder placard, (2) the display of feeding tube status and date of the last dietitian note in the electronic health record (EHR) clinic schedule dashboard, and (3) an autotext smart element to the EHR default clinic note template. The goal was to enable clinicians to quickly identify the need for nutrition evaluation with either a same-day dietitian consult or a referral to nutrition clinic.

RESULTS

Among 111 HEN patients with >6 months since last nutrition encounter, the dietitian referral/consult rate prior to any interventions was 58%. The placard (PDSA 1) was abandoned before obtaining reportable data because of sampling bias and clinic workflow inefficiencies. The clinic schedule dashboard modification (PDSA 2) improved the dietitian referral/consult rate to 66%. Subsequently, the clinic note smart element (PDSA 3) increased the rate to 77%. An 8-week postintervention check revealed a compliance rate of 78%.

CONCLUSION

Implementation of minimally interruptive EHR enhancements showed a sustained increase in dietitian referrals and consults for patients receiving HEN, which may improve nutrition outcomes.

Barriers and facilitators to implementing a nursing clinical decision support system in a tertiary hospital setting: A qualitative study using the FITT framework

OBJECTIVE

Clinical decision support systems (CDSSs) have been increasingly introduced to health care settings; however, their adoption is far from ideal. Guided by the FITT framework, this study aims to explore barriers and facilitators to the implementation of a CDSS from the perspective of nurses.

METHODS

A qualitative study with 200 h of participatory observation and 21 semi structured interviews was conducted from February to August 2021 in four medical-surgical wards in a 2000-bed tertiary hospital in Shanghai, China. The field notes were typed and the audio-recorded interviews were transcribed to texts verbatim and were coded with a four-step approach. We used the FITT framework to interpret our findings based on the technology, individual and task attributes and the fit between them.

RESULTS

A total of twelve categories were identified, which were integrated into two themes: barriers and facilitators to system implementation. All categories but one can be mapped to the three attributes of the FITT framework: technology, individual and task. We assumed that management has a vital role to play in the following areas: addressing user resistance, improving system usability, setting standards on practice and, finally, building connectivity between nurses and the technical staff to improve the fit between the technology, individual and task attribute and thus promote system implementation.

CONCLUSION

Barriers and facilitators to CDSS implementation include system-related, user-related and organizational factors which can largely be fit io the FITT framework. There is potential to extend the FITT framework to represent management intervention on inter-disciplinary collaboration. Future empirical studies on facilitating strategies from the management to improve user experience and willingness of CDSS adoption are needed.

Status of AI-Enabled Clinical Decision Support Systems Implementations in China

BACKGROUND

AI-enabled Clinical Decision Support Systems (AI + CDSSs) were heralded to contribute greatly to the advancement of health care services. There is an increased availability of monetary funds and technical expertise invested in projects and proposals targeting the building and implementation of such systems. Therefore, understanding the actual system implementation status in clinical practice is imperative.

OBJECTIVES

The aim of the study is to understand (1) the current situation of AI + CDSSs clinical implementations in Chinese hospitals and (2) concerns regarding AI + CDSSs current and future implementations.

METHODS

We investigated 160 tertiary hospitals from six provinces and province-level cities. Descriptive analysis, two-sided Fisher exact test, and Mann-Whitney U-test were utilized for analysis.

RESULTS

Thirty-eight of the surveyed hospitals (23.75%) had implemented AI + CDSSs. There were statistical differences on grade, scales, and medical volume between the two groups of hospitals (implemented vs. not-implemented AI + CDSSs, p <0.05). On the 5-point Likert scale, 81.58% (31/38) of respondents rated their overall satisfaction with the systems as "just neutral" to "satisfied." The three most common concerns were system functions improvement and integration into the clinical process, data quality and availability, and methodological bias.

CONCLUSION

While AI + CDSSs were not yet widespread in Chinese clinical settings, professionals recognize the potential benefits and challenges regarding in-hospital AI + CDSSs.

Development and Implementation of a Pediatric Nursing-Clinical Decision Support System for Hyperthermia: A Pre- and Post-test

This article describes the development process and application of the Pediatric Nursing-Clinical Decision Support System for Hyperthermia. Firstly, we formed the Pediatric Nursing-Knowledge Base for Hyperthermia, which combines publicly available clinical practice guidelines and nursing routines of hyperthermia management. Then, following the nursing process framework, the system was developed using clinical decision support technology. Finally, a pre- and post-test were adopted to examine the effectiveness, usability, and feasibility before (1st to 31st of August 2018) and after (1st to 31st of December 2019) using the system. Its effectiveness was examined by analysis of nursing records' quality, including completeness of nursing assessment, timeliness of nursing diagnosis, individualization of nursing interventions, and timeliness of nursing evaluation. Its usability and feasibility were assessed using the Clinical Nursing Information System Effectiveness Evaluation Scale. There was a significant difference between the two groups in effectiveness, usability, and feasibility. Although the system was developed specifically for our hospital workflow and processes, the Pediatric Nursing-Knowledge Base for Hyperthermia and workflow for hyperthermia management in this study can be used as a reference to other hospitals.

A Conceptual Framework to Study the Implementation of Clinical Decision Support Systems (BEAR): Literature Review and Concept Mapping

Background

The implementation of clinical decision support systems (CDSSs) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and those associated with technology acceptance. However, the literature regarding these subjects is fragmented and originates from two traditionally separate disciplines: implementation science and technology acceptance.

Objective

Our objective is to propose an integrated framework that bridges the gap between the behavioral change and technology acceptance aspects of the implementation of CDSSs.

Methods

We employed an iterative process to map constructs from four contributing frameworks—the Theoretical Domains Framework (TDF); the Consolidated Framework for Implementation Research (CFIR); the Human, Organization, and Technology-fit framework (HOT-fit); and the Unified Theory of Acceptance and Use of Technology (UTAUT)—and the findings of 10 literature reviews, identified through a systematic review of reviews approach.

Results

The resulting framework comprises 22 domains: agreement with the decision algorithm; attitudes; behavioral regulation; beliefs about capabilities; beliefs about consequences; contingencies; demographic characteristics; effort expectancy; emotions; environmental context and resources; goals; intentions; intervention characteristics; knowledge; memory, attention, and decision processes; patient–health professional relationship; patient’s preferences; performance expectancy; role and identity; skills, ability, and competence; social influences; and system quality. We demonstrate the use of the framework providing examples from two research projects.

Conclusions

We proposed BEAR (BEhavior and Acceptance fRamework), an integrated framework that bridges the gap between behavioral change and technology acceptance, thereby widening the view established by current models.

Clinical Decision Support and Implications for the Clinician Burnout Crisis

OBJECTIVES

This survey aimed to review aspects of clinical decision support (CDS) that contribute to burnout and identify key themes for improving the acceptability of CDS to clinicians, with the goal of decreasing said burnout.

METHODS

We performed a survey of relevant articles from 2018-2019 addressing CDS and aspects of clinician burnout from PubMed and Web of Science™. Themes were manually extracted from publications that met inclusion criteria.

RESULTS

Eighty-nine articles met inclusion criteria, including 12 review articles. Review articles were either prescriptive, describing how CDS should work, or analytic, describing how current CDS tools are deployed. The non-review articles largely demonstrated poor relevance and acceptability of current tools, and few studies showed benefits in terms of efficiency or patient outcomes from implemented CDS. Encouragingly, multiple studies highlighted steps that succeeded in improving both acceptability and relevance of CDS.

CONCLUSIONS

CDS can contribute to clinician frustration and burnout. Using the techniques of improving relevance, soliciting feedback, customization, measurement of outcomes and metrics, and iteration, the effects of CDS on burnout can be ameliorated.

Electronic Health Records and Use of Clinical Decision Support

In 2009, the Health Information Technology for Economic and Clinical Health (HITECH) Act was signed into law. Along with this initiative came the push for meaningful use of the electronic health record. Clinicians, information technology professionals, and informaticists must partner to create evidence-based clinical decision support models to guide patient care using tools such as structured computerized physician order entry, order sets, templates, alerts, and reminders. Clinical decision support should be used to improve the quality of patient care and compliance with regulatory standards, while inherently following a provider's workflow.