Electronic decision support for treatment of hospitalized smokers: A qualitative analysis of physicians' knowledge, attitudes, and practices

Clinical impacts of an integrated electronic health record-based smoking cessation intervention during hospitalisation

OBJECTIVE

To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system.

DESIGN

Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention.

SETTING

Kaiser Permanente Northern California, a large integrated health system with 4.2 million members.

PARTICIPANTS

Current smokers aged ≥18 hospitalised for any reason.

EXPOSURE

EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015).

MAIN OUTCOMES AND MEASURES

Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits.

RESULTS

The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%).

CONCLUSIONS

An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Identifying barriers and facilitators to successful implementation of computerized clinical decision support systems in hospitals: a NASSS framework-informed scoping review

BACKGROUND

Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim.

METHODS

Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework.

RESULTS

Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user's role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the "Technology," "Organization," and "Adopters" domains most frequently reported. No determinants were assigned to the "Embedding and Adaptation Over Time" domain.

CONCLUSIONS

This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals

Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals' acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants' profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure.

An Intervention to Promote Healthcare Transition Planning Among Pediatric Residents

PURPOSE

Poorly planned healthcare transition (HCT) from pediatric to adult-based care for adolescents and young adults with special healthcare needs (AYASHCN) is associated with increased morbidity and mortality. Most pediatricians and pediatric residents are not trained to assist AYASHCN with HCT planning. An electronic medical record-based Transition Planning Tool (TPT) was developed at a large children's hospital to guide provider-patient interactions around HCT planning. The purpose of this study was to evaluate an educational intervention to promote residents' use of the TPT.

METHODS

A multimodal (TPT training, demonstrations, use prompts, and case discussions) curriculum promoting the use of the TPT was developed and implemented within a one-month Adolescent Medicine Rotation. A prospective, nonrandomized, quasi-experimental design with Intervention and Historical Control groups was used. Forty-two residents received the intervention. Twenty-three Historical Control residents received minimal formal training in the TPT. Intervention Group residents completed prerotation/postrotation assessments measuring perceived importance of/comfort with HCT planning and self-reported HCT planning activities. TPT use was compared between the two groups.

RESULTS

Compared to the Historical Control Group, Intervention Group residents were significantly more likely to use the TPT (98% vs. 37%, p < .001) and had a higher mean number of uses (5.5 ± 3.0 vs. 2.6 ± 1.2, p < .001). Residents reported greater perceived importance of (p < .001) and engagement in (p < .001) transition planning activities after completing the intervention. Nearly all (91%) reported that their training increased their comfort in HCT planning.

CONCLUSIONS

A targeted intervention improved pediatric residents' use of the TPT and HCT planning activities.

Increased Reach and Effectiveness With a Low-Burden Point-of-Care Tobacco Treatment Program in Cancer Clinics

BACKGROUND

Tobacco cessation after a cancer diagnosis can extend patient survival by improving outcomes for primary cancer and preventing secondary cancers. However, smoking is often unaddressed in cancer care, highlighting the need for strategies to increase treatment reach and cessation. This study examined a low-burden, point-of-care tobacco treatment program (ELEVATE) featuring an electronic health record-enabled smoking module and decision support tools to increase the reach and effectiveness of evidence-based smoking cessation treatment.

METHODS

This study included adult outpatient tobacco smokers (n=13,651) in medical oncology, internal medicine, and surgical oncology clinics from a large midwestern healthcare system. We examined reach and effectiveness of ELEVATE with 2 comparisons: (1) preimplementation versus postimplementation of ELEVATE and (2) ELEVATE versus usual care. Data were evaluated during 2 time periods: preimplementation (January through May 2018) and postimplementation (June through December 2018), with smoking cessation assessed at the last follow-up outpatient encounter during the 6 months after these periods.

RESULTS

The proportion of current tobacco smokers receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (1.6%-27.9%; difference, 26.3%; relative risk, 16.9 [95% CI, 9.8-29.2]; P<.001). Compared with 27.9% treatment reach with ELEVATE in the postimplementation time period, reach within usual care clinics ranged from 11.8% to 12.0% during this same period. The proportion of tobacco smokers who subsequently achieved cessation increased significantly from pre-ELEVATE to post-ELEVATE (12.0% vs 17.2%; difference, 5.2%; relative risk, 1.3 [95% CI, 1.1-1.5]; P=.002). Compared with 17.2% smoking cessation with ELEVATE in the postimplementation time period, achievement of cessation within usual care clinics ranged from 8.2% to 9.9% during this same period.

CONCLUSIONS

A low-burden, point-of-care tobacco treatment strategy increased tobacco treatment and cessation, thereby improving access to and the impact of evidence-based cessation treatment. Using implementation strategies to embed tobacco treatment in every healthcare encounter promises to engage more smokers in evidence-based treatment and facilitate smoking cessation, thereby improving care cancer for patients who smoke.

How can hospitals change practice to better implement smoking cessation interventions? A systematic review

Smoking cessation reduces the risk of death, improves recovery, and reduces the risk of hospital readmission. Evidence and policy support hospital admission as an ideal time to deliver smoking-cessation interventions. However, this is not well implemented in practice. In this systematic review, the authors summarize the literature on smoking-cessation implementation strategies and evaluate their success to guide the implementation of best-practice smoking interventions into hospital settings. The CINAHL Complete, Embase, MEDLINE Complete, and PsycInfo databases were searched using terms associated with the following topics: smoking cessation, hospitals, and implementation. In total, 14,287 original records were identified and screened, resulting in 63 eligible articles from 56 studies. Data were extracted on the study characteristics, implementation strategies, and implementation outcomes. Implementation outcomes were guided by Proctor and colleagues' framework and included acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability. The findings demonstrate that studies predominantly focused on the training of staff to achieve implementation. Brief implementation approaches using a small number of implementation strategies were less successful and poorly sustained compared with well resourced and multicomponent approaches. Although brief implementation approaches may be viewed as advantageous because they are less resource-intensive, their capacity to change practice in a sustained way lacks evidence. Attempts to change clinician behavior or introduce new models of care are challenging in a short time frame, and implementation efforts should be designed for long-term success. There is a need to embrace strategic, well planned implementation approaches to embed smoking-cessation interventions into hospitals and to reap and sustain the benefits for people who smoke.

Pediatric Resident Training in Tobacco Control and the Electronic Health Record

Given the dangers posed by tobacco use and tobacco smoke exposure, pediatricians should address tobacco use and exposure with patients and parents at every opportunity, but this is not consistently done in practice. One reason may be that many medical residents do not receive education on how to address tobacco use and tobacco smoke exposure with patients and their parents. In a 2012 survey of U.S. pediatric program directors, 65% of programs reported covering tobacco control in their curricula, but most training programs focused on tobacco's health effects and not intervention strategies for clinical practice. Since that survey, electronic health records have been implemented broadly nationwide and utilized to address tobacco smoke exposure. Investigators surveyed U.S. program directors in 2018 and residents in 2019 to explore the ways in which the residents learn about tobacco use and tobacco smoke exposure, components and use of the electronic record specific to tobacco use and tobacco smoke exposure, and perceived resident effectiveness in this area. All the program directors and 85% of the residents valued training, but 21% of the residents reported receiving none. Moreover, a minority of the residents assessed themselves as effective at counseling parents (19%) or adolescents (23%), and their perceived effectiveness was related to small group learning and active learning workshops, modalities that were infrequently implemented in training. Respondents also reported infrequent use of electronic health record prompts regarding tobacco and the absence of prompts about critical issues (e.g., addressing tobacco smoke exposure in vehicles or other settings or offering treatment or referrals to parents who smoke). This paper provides recommendations about augmenting pediatric resident training in simple ways.

[Systematic identification of smokers and tobacco smoking management in the general hospital]

INTRODUCTION

The prevalence of daily smoking in France was 24 % in 2019 and tobacco control remains a major public health issue. A hospital stay provides an opportunity for smoking cessation intervention. Identification and management of smokers during a hospital stay may be variously integrated into electronic health records (EHR).

STATE OF THE ART

Smoking status identification, which have included pre-filled forms, check-box, reminders, icons, is heterogeneous. Specific modules in EHR have been implemented for smoking cessation management such as counselling sessions, tobacco cessation prescriptions, smoking cessation guidelines and long-term follow-up. EHR-based intervention to identify and manage smokers with a long-term follow-up for at least one month after hospital discharge has shown an increase in smoking abstinence at 6-12 months.

OUTLOOK

Due to the lower quality of free data about smoking status, systematic identification with check-box, reminders or icons in EHR may be more appropriate. Integration of functionalities such as help for prescription, reminders and follow-up of patients would make tobacco cessation management easier for health professionals.

CONCLUSION

EHR interventions to identify smokers and manage smoking cessation during hospital stays are an opportunity to increase smoking cessation.