A content analysis of electronic health record (EHR) functionality to support tobacco treatment

Factors Associated With Tobacco Cessation Advice Recall and Quit Rates in Vascular Surgery Patients. A Single Center Study

OBJECTIVES

Smoking is an important modifiable risk factor in all vascular diseases and verbal advice from providers has been shown to increase rates of tobacco cessation. We sought to identify factors that will improve tobacco cessation and recall of receiving verbal cessation advice in vascular surgery patients at a single institution.

METHODS

The study is a retrospective cohort study. Patients seen in outpatient vascular surgery clinic who triggered a tobacco Best Practice Advisory (BPA) during their office visits over a 10-month period were contacted post-clinic and administered surveys detailing smoking status, cessation advice recall, and validated scales for nicotine dependence and willingness to quit smoking. This BPA is a "hard stop" that requires providers to document actions taken. Charts were reviewed for tobacco cessation documentation. Nine-digit zip-codes identified the area deprivation index, a measure of socioeconomic status. Univariate analysis was used to identify factors associated with cessation and advice recall.

RESULTS

One hundred out of 318 (31.4%) patients responded to the survey. Epic Slicer Dicer found 97 BPA responses. To dismiss the BPA, 89 providers (91.8%) selected "advised tobacco cessation" and "Unable to Advise" otherwise. Of the 318 patients, 115 (36.1%) had cessation intervention documented in their provider notes and 151 (47.5%) received written tobacco cessation advice. Of survey respondents, 70 recalled receiving verbal advice, 27 recalled receiving written advice, 28 reported receiving offers of medication/therapy for cessation. 55 patients reported having tobacco cessation plans, and among those 17 reported having quit tobacco. Recall of receiving written advice (P < .001) and recall of receiving medication/therapy (P = .008) were associated with recall of receiving verbal cessation advice.

CONCLUSIONS

Providing patients with tobacco cessation medication/therapy and written tobacco cessation education during office visits is associated with increased patients' recall of tobacco cessation advice. Vascular surgeons should continue to provide directed tobacco cessation advice.

Factors Associated with Smoking Cessation and the Receipt of Cessation Services in a Public, Safety-Net Primary Care System

BACKGROUND

Prevalence of smoking is high among patients receiving care in safety-net settings, and there is a need to better understand patient factors associated with smoking cessation and receipt of cessation services.

OBJECTIVE

To identify patient factors associated with smoking cessation attempts and receipt of cessation counseling and pharmacotherapy in a large safety-net health system.

DESIGN

We conducted a retrospective cohort analysis using EHR data in a safety-net system in San Francisco, CA.

PARTICIPANTS

We included 7384 adult current smokers who had at least three unique primary care encounters with documented smoking status between August 2019 and April 2022.

MAIN MEASURES

We assessed four outcomes using multivariate generalized estimating equation models: (1) any cessation attempt, indicating a transition in smoking status from "current smoker" to "former smoker"; (2) sustained cessation, defined as transition in smoking status from current smoker to former smokers for two or more consecutive visits; (3) receipt of smoking cessation counseling from healthcare providers; and (4) receipt of pharmacotherapy.

KEY RESULTS

Of 7384 current adult smokers, 17.6% had made any cessation attempt, and of those 66.5% had sustained cessation. Most patients (81.1%) received counseling and 41.8% received pharmacotherapy. Factors associated with lower odds of any cessation attempt included being aged 45-64, non-Hispanic black, and experiencing homelessness. The factor associated with lower odds of sustained cessation was being male. Factors associated with lower odds of receiving counseling were being insured by Medicaid or being uninsured. Factors associated with lower odds of receiving pharmacotherapy included speaking languages other than English, being male, and identifying as racial and ethnic minorities.

CONCLUSIONS

Health system interventions could close the gap in access to smoking cessation services for unhoused and racial/ethnic minority patients in safety-net settings, thereby increasing cessation among these populations.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics

BACKGROUND

Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias.

OBJECTIVE

This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I).

METHODS

We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption.

RESULTS

The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden.

CONCLUSIONS

EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

System-Level Quality Improvement Initiatives for Tobacco Use in a Safety-Net Health System During the COVID-19 Pandemic

Introduction:

The shift from in-person care to telemedicine made it challenging to provide guideline-recommended tobacco cessation care during the COVID-19 pandemic. We described quality improvement (QI) initiatives for tobacco cessation during the COVID-19 pandemic, focusing on African American/Black patients with high smoking rates.

Methods:

The QI initiatives took place in the San Francisco Health Network, a network of 13 safety-net clinics in San Francisco, California between February 2020 and February 2022. We conducted direct patient outreach by telephone and increased staff capacity to increase cessation care delivery. We examined trends in tobacco screening, provider counseling, and best practice for cessation care (ie, the proportion of patients receiving at least 1 smoking cessation service during a clinical encounter).

Results:

In-person visits at the onset of the pandemic was 20% in April 2020 and increased to 67% by February 2022. During this time, tobacco screening increased from 29% to 74%. From March 2020 to March 2021, 34% more patients received provider counseling by telephone than in-person. The trend reversed from April 2021 to February 2022, where 23% more patients received counseling in-person than by telehealth. Best practice care increased by 23% from June 2020 to February 2022: 24% for African American/Black patients and 23% for other patients.

Conclusions:

Telehealth adaptations to the EHR, targeted outreach to patients, and a multi-disciplinary medical team may be associated with increases in cessation care delivery during the COVID-19 pandemic.

Concordance Between Electronic Health Record and Tumor Registry Documentation of Smoking Status Among Patients With Cancer

PURPOSE

Patients with cancer who use tobacco experience reduced treatment effectiveness, increased risk of recurrence and mortality, and diminished quality of life. Accurate tobacco use documentation for patients with cancer is necessary for appropriate clinical decision making and cancer outcomes research. Our aim was to assess agreement between electronic health record (EHR) smoking status data and cancer registry data.

MATERIALS AND METHODS

We identified all patients with cancer seen at University of Florida Health from 2015 to 2018. Structured EHR smoking status was compared with the tumor registry smoking status for each patient. Sensitivity, specificity, positive predictive values, negative predictive values, and Kappa statistics were calculated. We used logistic regression to determine if patient characteristics were associated with odds of agreement in smoking status between EHR and registry data.

RESULTS

We analyzed 11,110 patient records. EHR smoking status was documented for nearly all (98%) patients. Overall kappa (0.78; 95% CI, 0.77 to 0.79) indicated moderate agreement between the registry and EHR. The sensitivity was 0.82 (95% CI, 0.81 to 0.84), and the specificity was 0.97 (95% CI, 0.96 to 0.97). The logistic regression results indicated that agreement was more likely among patients who were older and female and if the EHR documentation occurred closer to the date of cancer diagnosis.

CONCLUSION

Although documentation of smoking status for patients with cancer is standard practice, we only found moderate agreement between EHR and tumor registry data. Interventions and research using EHR data should prioritize ensuring the validity of smoking status data. Multilevel strategies are needed to achieve consistent and accurate documentation of smoking status in cancer care.

Co-creating opportunities to incorporate cessation for electronic nicotine delivery systems in family medicine - a qualitative program evaluation

Background

The number of Americans who use tobacco has decreased in the twenty-first century, but electronic nicotine delivery systems (ENDS) have increased the complexity of treating tobacco dependence. The experiences of 18 family medicine practices were explored and opportunities to improve ENDS cessation were co-created in this study.

Methods

Eighteen family medicine practices were enrolled into an implementation project to incorporate ENDS cessation into their practice. The participants’ experiences were explored throughout the project using an iterative qualitative approach. The research team provided technical assistance. Semi-structured group interviews and focus groups were held with participants at the beginning, middle, and end of the project to explore participants’ experiences. The collective knowledge and experiences of participants, expert consultants and the research team were fused together to co-create opportunities to improve ENDS cessation.

Results

Nine opportunities to improve ENDS cessation were identified in three larger categories. The first category was leading change. This included: creating a vision for change to establish buy-in from key stakeholders and educate health care professionals to improve their confidence to address ENDS. The second category was creating processes. This included: establishing criteria for screening and quality improvement for ENDS cessation; being specific when asking about ENDS; creating electronic health record systems to support incorporating ENDS cessation; using chart audits if electronic health records cannot support incorporating ENDS into tobacco cessation; and assigning roles and responsibilities to members of the clinical care team. The third category was assisting patients who use ENDS. This included: educating patients and their parents/caregivers about ENDS and their potential harms, avoiding dual use, and developing a plan to quit.

Conclusions

This study highlights challenges and opportunities for incorporating ENDS cessation into family medicine. The opportunities outlined here provide a practical approach which is rooted in the experiences of family physicians and their clinical care teams working to improve how they address ENDS and based on peer reviewed literature and expert input. Improving how ENDS are addressed in family medicine will require more than clinical expertise. It will also require leadership skills and the ability to create process improvements.

Trial registration

Not applicable

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01520-x.

Implementation of Ask-Advise-Connect in a safety net healthcare system: quitline treatment engagement and smoking cessation outcomes

Ask-Advise-Connect (AAC) was designed to link smokers in primary care settings with evidence-based tobacco treatment delivered via state quitlines. AAC involves training medical staff to Ask about smoking status, Advise smokers to quit, and offer to immediately Connect smokers with quitlines through an automated link within the electronic health record. We evaluated the efficacy of AAC in facilitating treatment engagement and smoking abstinence in a 34 month implementation trial conducted in a large, safety-net health care system. AAC was implemented from April 2013 through February 2016 in 13 community clinics that provided care to low-income, predominantly racial/ethnic minority smokers. Licensed vocational nurses were trained to implement AAC as part of standard care. Outcomes included (a) treatment engagement (i.e., proportion of identified smokers that enrolled in treatment) and (b) self-reported and biochemically confirmed abstinence at 6 months. Smoking status was recorded for 218,915 unique patients, and 40,888 reported current smoking. The proportion of all identified smokers who enrolled in treatment was 11.8%. Self-reported abstinence at 6 months was 16.6%, and biochemically confirmed abstinence was 4.5%. AAC was successfully implemented as part of standard care. Treatment engagement was high compared with rates of engagement for more traditional referral-based approaches reported in the literature. Although self-reported abstinence was in line with other quitline-delivered treatment studies, biochemically confirmed abstinence, which is not routinely captured in quitline studies, was dramatically lower. This discrepancy challenges the adequacy of self-report for large, population-based studies. A more detailed and comprehensive investigation is warranted.

Closed-Loop Electronic Referral From Primary Care Clinics to a State Tobacco Cessation Quitline: Effects Using Real-World Implementation Training

INTRODUCTION

Patients who use tobacco are too rarely connected with tobacco use treatment during healthcare visits. Electronic health record enhancements may increase such referrals in primary care settings. This project used the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to assess the implementation of a healthcare system change carried out in an externally valid manner (executed by the healthcare system).

METHODS

The healthcare system used their standard, computer-based training approach to implement the electronic health record and clinic workflow changes for electronic referral in 30 primary care clinics that previously used faxed quitline referral. Electronic health record data captured rates of assessment of readiness to quit and quitline referral 4 months before implementation and 8 months (May-December 2017) after implementation. Data, analyzed from October 2018 to June 2019, also reflected intervention reach, adoption, and maintenance.

RESULTS

For reach and effectiveness, from before to after implementation for electronic referral, among adult patients who smoked, assessment of readiness to quit increased from 24.8% (2,126 of 8,569) to 93.2% (11,163 of 11,977), quitline referrals increased from 1.7% (143 of 8,569) to 11.3% (1,351 of 11,977), and 3.6% were connected with the quitline after implementation. For representativeness of reach, electronic referral rates were especially high for women, African Americans, and Medicaid patients. For adoption, 52.6% of staff who roomed at least 1 patient who smoked referred to the quitline. For maintenance, electronic referral rates fell by approximately 60% over 8 months but remained higher than pre-implementation rates.

CONCLUSIONS

Real-world implementation of an electronic health record-based electronic referral system markedly increased readiness to quit assessment and quitline referral rates in primary care patients. Future research should focus on implementation methods that produce more consistent implementation and better maintenance of electronic referral.

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.

Mining Electronic Health Records to Promote the Reach of Digital Interventions for Cancer Prevention Through Proactive Electronic Outreach: Protocol for the Mixed Methods OptiMine Study

BACKGROUND

Digital behavior change interventions have demonstrated effectiveness for smoking cessation and reducing alcohol intake, which ultimately reduce cancer risk. Leveraging electronic health records (EHR) to identify at-risk patients and increasing the reach of digital interventions through proactive electronic outreach provide a novel approach that may increase the number of individuals who engage with evidence-based treatment.

OBJECTIVE

This study aims to increase the reach of digital behavior change interventions by implementing a proactive electronic message system for smoking cessation and alcohol reduction among a large, at-risk population identified through an acute hospital EHR.

METHODS

This protocol describes a 3-phase, mixed-methods implementation study to assess the acceptability, feasibility, and reach of a proactive electronic message system to digital interventions using a hospital's EHR system to identify eligible patients. In Phase 1, we will conduct focus group discussions with patients and hospital staff to assess the overall acceptability of the electronic message system. In Phase 2, we will conduct a descriptive analysis of the patient population in the hospital EHR regarding target risk behaviors and other person-level characteristics to determine the project's feasibility and potential reach. In Phase 3, we will send proactive messages to patients identified as smokers or risky drinkers. Messages will encourage and provide access to behavior change mobile apps via an embedded link; the primary outcome will be the proportion of participants who click on the link to access information about the apps.

RESULTS

At the time of initial protocol submission, data collection was complete, but analysis had not begun. This study was funded by Cancer Research UK from April 2019 to March 2020. Health Research Authority approval was granted in June 2019.

CONCLUSIONS

Increasing the reach of digital behavior change interventions can improve population health by reducing the burden of preventable death and disease.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/23669.

[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.

Methods to improve the quality of smoking records in a primary care EMR database: exploring multiple imputation and pattern-matching algorithms

BACKGROUND

Primary care electronic medical record (EMR) data are emerging as a useful source for secondary uses, such as disease surveillance, health outcomes research, and practice improvement. These data capture clinical details about patients' health status, as well as behavioural risk factors, such as smoking. While the importance of documenting smoking status in a healthcare setting is recognized, the quality of smoking data captured in EMRs is variable. This study was designed to test methods aimed at improving the quality of patient smoking information in a primary care EMR database.

METHODS

EMR data from community primary care settings extracted by two regional practice-based research networks in Alberta, Canada were used. Patients with at least one encounter in the previous 2 years (2016-2018) and having hypertension according to a validated definition were included (n = 48,377). Multiple imputation was tested under two different assumptions for missing data (smoking status is missing at random and missing not-at-random). A third method tested a novel pattern matching algorithm developed to augment smoking information in the primary care EMR database. External validity was examined by comparing the proportions of smoking categories generated in each method with a general population survey.

RESULTS

Among those with hypertension, 40.8% (n = 19,743) had either no smoking information recorded or it was not interpretable and considered missing. Those with missing smoking data differed statistically by demographics, clinical features, and type of EMR system used in the clinic. Both multiple imputation methods produced fully complete smoking status information, with the proportion of current smokers estimated at 25.3% (data missing at random) and 12.5% (data missing not-at-random). The pattern-matching algorithm classified 18.2% of patients as current smokers, similar to the population-based survey (18.9%), but still resulted in missing smoking information for 23.6% of patients. The algorithm was estimated to be 93.8% accurate overall, but varied by smoking status category.

CONCLUSION

Multiple imputation and algorithmic pattern-matching can be used to improve EMR data post-extraction but the recommended method depends on the purpose of secondary use (e.g. practice improvement or epidemiological analyses).

Electronic medical record documentation of tobacco cessation support at eight community safety-net clinics with a high prevalence of tobacco use

OBJECTIVES

The high prevalence of tobacco use at primary care safety-net clinics represents an opportunity to offer assistance with cessation. Documentation of smoking status, offering advice and medications, and referral to cessation services are important steps in supporting cessation attempts and are required elements by payors and accrediting agencies to demonstrate care quality. This study examines tobacco cessation support rates and patient characteristics using electronic medical record (EMR) data.

METHODS

This cross-sectional study engaged eight community health centers affiliated with a county hospital system in NE Ohio where adult tobacco use rates exceed 30%. EMR data from June 2014 through May 2016 were analysed to assess rates of tobacco cessation counselling, order of cessation medications, or both. The association of tobacco cessation support with patient characteristics and quit attempts was assessed using multivariable logistic regression models.

RESULTS

Among 21 702 current tobacco users, 74% had no intervention documented; 15.4% had counselling documented, 6.4% were prescribed tobacco cessation medication, and 4.2% had both documented. Males, those aged 18 to 34, and African Americans were more likely to have no documented intervention. Of current tobacco users with at least two visits, 5.6% had a quit attempt. Medication alone was associated with a greater likelihood of a quit attempt (AOR: 1.72 [95% CI: 1.36-2.17]) as well as counselling and medication combined (AOR: 1.95 [95% CI: 1.48-2.56]).

CONCLUSIONS

Tobacco cessation support was lacking for 74% of current smokers and was less likely in subgroups including males, younger adults, and African Americans. Ordering tobacco cessation medication combined with counselling nearly doubled the likelihood of a quit attempt.

Using Electronic Health Records To Generate Phenotypes For Research

Electronic health records contain patient-level data collected during and for clinical care. Data within the electronic health record include diagnostic billing codes, procedure codes, vital signs, laboratory test results, clinical imaging, and physician notes. With repeated clinic visits, these data are longitudinal, providing important information on disease development, progression, and response to treatment or intervention strategies. The near universal adoption of electronic health records nationally has the potential to provide population-scale real-world clinical data accessible for biomedical research, including genetic association studies. For this research potential to be realized, high-quality research-grade variables must be extracted from these clinical data warehouses. We describe here common and emerging electronic phenotyping approaches applied to electronic health records, as well as current limitations of both the approaches and the biases associated with these clinically collected data that impact their use in research. © 2018 by John Wiley & Sons, Inc.

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

BACKGROUND

We recently demonstrated the ability of a suite of tools embedded in an electronic medical record (EMR) to improve tobacco cessation treatment for adult smokers admitted to the hospital. A randomized controlled trial conducted by our group demonstrated the ability of an EMR-embedded tobacco use disorder treatment tool, the Electronic Support Tool and Orders for the Prevention of Smoking (E-STOPS), to increase the identification and treatment of smokers, but its uptake varied among 126 physicians randomized to the intervention arm. The purpose of this study was to identify facilitators and barriers to using E-STOPS.

METHODS

Semi-structured individual interviews from a purposive sample of 12 hospitalist attending physicians and nine internal medicine residents who were randomized to the E-STOPS intervention were analyzed thematically.

RESULTS

Three themes shaped E-STOPS use: the inpatient environment, prescriber attitudes and beliefs, and information needs. Overall, participants were pleased with E-STOPS, but had specific suggestions for improvements regarding the timing of the intervention, suppression logic, and additional decision support and training. A few had concerns about the clinical appropriateness of beginning treatment for tobacco dependence during a hospitalization and the proper role of the inpatient team in that treatment.

CONCLUSIONS

Tobacco dependence treatment for hospitalized smokers and facilitated by the EMR is generally acceptable to hospitalists and resident physicians. Improvements in provider training and feedback as well as the timing and content of the electronic tools may increase their utilization by inpatient physicians.