Opportunistic electronic reminders. Improving performance of preventive care in general practice. A demonstration project for using the electronic health record to identify and treat tobacco users. A computerized aid to support smoking cessation treatment for hospital patients. An electronic health record-based intervention to improve tobacco treatment in primary care: a cluster-randomized controlled trial. Care coordination to increase referrals to smoking cessation telephone counseling: a demonstration project. A method for educating patients and documenting smoking status in an electronic medical record. Smoking as a vital sign: prompts to ask and assess increase cessation counseling. The feasibility of paper-based Tracking Codes and electronic medical record systems to monitor tobacco-use assessment and intervention in an Individual Practice Association (IPA) Model health maintenance organization (HMO). Tools to improve documentation of smoking status. Continuous quality improvement and electronic medical records. Provider feedback to improve 5A's tobacco cessation in primary care: a cluster randomized clinical trial. Effects of the tobacco use cessation automated clinical practice guideline.
Preventive care is an important role for general practitioners, yet opportunities for prevention are often missed.
                We provided an automatic electronic record preventive care reminder system for 12 preventive care activities for one 10 doctor practice. All patients who attended were randomised by the terminal digit of their record number.
                The control uptake of opportunistic prevention was low; ranging from 1.5% (tetanus immunisation) to 27% (influenza immunisation). The reminders increased this by significant but small amounts for four out of 12 activities (immunisation for tetanus and pneumococcus and recording of allergies and weight), insignificant increases for four (mumps, measles and rubella immunisation, recording of smoking, and taking of cervical smears and of blood pressure), and insignificantly decreased influenza immunisation, and screening for diabetes and hyperlipidaemia.
                Opportunistic electronic reminders have the potential to increase preventive care in general practice. While the majority of smokers visit a primary care physician each year, only a small proportion of them receive evidence-based tobacco dependence treatment. The electronic health record (EHR) provides an opportunity to prompt clinicians to deliver tobacco dependence treatment in primary care.
                Over 1 year, Dean Health Systems worked with the University of Wisconsin School of Medicine and Public Health to modify the existing Dean EHR system (Epic Systems Corp, Verona, Wisconsin) to improve identification and treatment of adult smokers visiting primary care clinics. Modifications included evidence-based prompts that helped guide medical assistants to identify smokers and clinicians to deliver a brief tobacco cessation intervention (medication and Wisconsin Tobacco Quit Line referral). Eighteen primary care clinics provided data 1 year before and 1 year after implementing the EHR modifications.
                A higher percentage of adult patients had their tobacco use status identified after EHR modification compared to pre-implementation (71.6% versus 78.4%, P < .001). During the post-implementation year, 6.3% of adult smokers were prescribed tobacco cessation medication, 2.5% of adult smokers had documentation of counseling, and 1.5% of adult smokers had counseling billed (pre-implementation data not available).
                This demonstration project showed that a large health care system can increase the delivery of tobacco dependence treatment interventions (increased identification of smokers and relatively high rates of delivering specific tobacco dependence clinical interventions) building on an existing EHR platform. The project demonstrated that brief, evidence-based tobacco dependence interventions can be incorporated into primary care, especially when the EHR is used to improve clinic workflow. Hospital-based interventions promote smoking cessation after discharge. Strategies to deliver these interventions are needed, especially now that providing smoking cessation advice or treatment, or both, to inpatient smokers is a publicly reported quality-of-care measure for US hospitals.
                To assess the effect of adding a tobacco order set to an existing computerized order-entry system used to admit Medicine patients to 1 hospital.
                Pre-post study.
                Proportion of admitted patients who had smoking status identified, a smoking counselor consulted, or nicotine replacement therapy (NRT) ordered during 4 months before and after the change. In 4 months after implementation, the order set was used with 76% of Medicine admissions, and a known smoking status was recorded for 81% of these patients. The intervention increased the proportion of admitted patients who were referred for smoking counseling (0.8 to 2.1%) and had NRT ordered (1.6 to 2.5%) (p < .0001 for both). Concomitantly, the hospital's performance on the smoking cessation quality measure improved.
                Adding a brief tobacco order set to an existing computerized order-entry system increased a hospital's provision of evidence-based tobacco treatment and helped to improve its performance on a publicly reported quality measure. It provides a model for US hospitals seeking to improve their quality of care for inpatients. To improve the documentation and treatment of tobacco use in primary care, we developed and implemented a 3-part electronic health record enhancement: (1)smoking status icons, (2) tobacco treatment reminders, and (3) a Tobacco Smart Form that facilitated the ordering of medication and fax and e-mail counseling referrals.
                We performed a cluster-randomized controlled trial of the enhancement in 26 primary care practices between December 19, 2006, and September 30, 2007. The primary outcome was the proportion of documented smokers who made contact with a smoking cessation counselor. Secondary outcomes included coded smoking status documentation and medication prescribing.
                During the 9-month study period, 132 630 patients made 315 962 visits to study practices. Coded documentation of smoking status increased from 37% of patients to 54% (+17%) in intervention practices and from 35% of patients to 46% (+11%) in control practices (P < .001 for the difference in differences). Among the 9589 patients who were documented smokers at the start of the study, more patients in the intervention practices were recorded as nonsmokers by the end of the study (5.3% vs 1.9% in control practices; P < .001). Among 12 207 documented smokers, more patients in the intervention practices made contact with a cessation counselor (3.9% vs 0.3% in control practices; P < .001). Smokers in the intervention practices were no more likely to be prescribed smoking cessation medication (2% vs 2% in control practices; P = .40).
                This electronic health record-based intervention improved smoking status documentation and increased counseling assistance to smokers but not the prescription of cessation medication. To test the effectiveness of a care coordination program for telephone counseling in raising referral and treatment rates for smoking cessation.
                A demonstration project implementing a smoking cessation care coordination program offering telephone counseling and medication management to patients referred from primary care.
                The study was performed at 18 Veterans Health Administration (VA) sites in California. Participants were VA patients receiving primary care. We randomly allocated 10 of 18 sites to receive the Telephone Care Coordination Program, which included simple 2-click referral, proactive care coordination, medication management, and 5 follow-up telephone calls. Each patient received a 30- to 45-minute counseling session from the California Smokers' Helpline. Patients at control sites received usual care.
                During 10 months, we received 2965 referrals. We were unable to reach 1156 patients (39%), despite at least 3 attempts. We excluded 73 patients (3%), and 391 patients (13%) were not interested. We connected the remaining 1345 patients (45%) to the Helpline. At 6-month followup, 335 patients (11% of all referrals and 25% of participating patients) were abstinent. Providers at intervention sites reported referring many more patients to telephone counseling than providers at control sites (15.6 vs 0.7 in the prior month).
                The program generated a large number of referrals; almost half of the patients referred were connected with the Helpline. Long-term abstinence was excellent. These results suggest that managed care organizations may be able to improve tobacco control by implementing a similar system of care coordination. Published evidence demonstrates benefit from pharmacist smoking cessation interventions; however, there is limited research evaluating the impact of a template within an electronic medical record used at pharmacy disease state management visits.
                To determine the rates of smoking cessation and movement along the transtheoretical model of change after implementation of a template into existing pharmacy-related progress notes within the electronic medical record.
                Patients who were routinely followed by clinical pharmacists for anticoagulation and diabetes mellitus education at 3 clinics at the Medical University of South Carolina were included. At each visit, the pharmacist would document patient smoking information in a newly designed template within the existing progress note. In addition, pharmacists would educate patients on the benefits of smoking cessation and pharmacologic options that may be available to them. Data were collected between April 2007 and March 2008. Baseline demographic data and smoking cessation rates and products were compared using descriptive statistics. The McNemar chi(2) test was used to compare the groups of patients achieving smoking cessation pre- and postintervention.
                Of the 90 current smokers, 38 (42%) achieved smoking cessation postintervention. Movement along the transtheoretical model of change was also seen, with 52 (58%) patients progressing to at least the next stage. Thirty-four patients in the contemplation/preparation stage and 4 patients in the precontemplation stage moved to the action or maintenance stage by the end of the study period (p = 0.03). A variety of pharmacologic therapies were used in individuals who stopped smoking, although varenicline was most common. Thirty-nine percent of the patients used no medications to achieve cessation.
                Incorporating a smoking cessation template into existing progress notes and providing education during existing pharmacy referral visits is a simple and effective method to assist patients in achieving smoking cessation. Strategies to improve smoking cessation counseling in clinical settings are critical to supporting smokers' attempts to quit. This study evaluates the impact of adding 2 smoking-related vital sign questions in an electronic medical records system on identification, assessment, and counseling for patients who smoke: "Current smoker?" and "Plan to quit?"
                Baseline data and data after intervention were collected through record review of 899 randomly selected patient visits across 3 outpatient clinics.
                From before to after intervention, identification of smokers increased 18% (from 71% to 84%; P<.001), and assessment for a plan to quit increased 100% (from 25.5% to 51%; P<.005). Among all smokers, cessation counseling increased 26% (from 23.6% to 29.8%; P=.41). Significantly more smokers who received the assessment for a plan to quit received cessation counseling (46% vs. 14%, P<.001). Regression analysis showed that patients receiving an assessment for plan to quit were 80% more likely to receive cessation counseling (OR 0.209; 95% CI, 0.095-0.456).
                Physician-documented counseling rates are significantly higher when patients are asked about smoking and assessed for a plan to quit. Two questions that ask about smoking status and assess plans to quit may provide prompts to increase the likelihood that patients who smoke receive cessation counseling. Despite evidence of its effectiveness, tobacco cessation is not systematically addressed in routine healthcare settings. Its measurement is part of the problem. A pilot study was designed to develop and implement two different tobacco tracking systems in two independent primary care offices that participated in an IPA Model health maintenance organization in Portland, Oregon. The first clinic, which utilized a paper-based charting system, implemented CPT-like tracking codes to measure and report tobacco-cessation activities, which were eventually included in the managed-care organization's (MCO) claims database. The second clinic implemented an electronic tracking system based on its computerized electronic medical record (EMR) charting system. This paper describes the pilot study, including the processes involved in building provider acceptance for the new tracking systems in these two clinics, the barriers and successes encountered during implementation, and the resources expended by the clinics and by the MCO during the pilot. The findings from the 3-month implementation period were that documentation of tobacco-use status remained stable at 42-45% in the paper-based clinic and increased from 79% to 88% in the EMR clinic. This pilot study demonstrated that Tracking Codes are a feasible preventive-care tracking system in paper-based medical offices. However, high levels of effort and support are needed, and a critical mass of insurers and health plans would need to adopt Tracking Codes before widespread use could be expected. Results of the EMR-based tracking system are also reviewed and discussed. Despite the deleterious effects of smoking on the nation's health and evidence that smoking cessation advice by family practice physicians is cost-effective, self-sustaining office systems to identify smokers in primary care clinics have been difficult to establish. We worked on a continuous quality improvement project group, aided by an electronic medical record, to design a system to document and periodically update smoking status in a consistent place in the medical record.
                Using the continuous quality improvement plan-do-study-act cycle, a 7-member group worked with nursing staff to define roles, routines and responsibilities for medical assistants to screen for and document 1 of 4 categories of smoking status in the major problem list of the electronic medical record for at least 80% of patient appointments. Screening rate was tracked monthly by means of the electronic medical record and feedback was given to staff.
                The screening rate rose from 18.4% to 80.3% within 2 weeks after the system was implemented and was maintained for 19 months. An additional benefit was an increased rate of smoking cessation counseling documented by providers, from a baseline rate of 17.1% to 48.3%.
                A continuous quality improvement group process aided by an electronic medical record is useful to develop a self-sustaining office system to screen, document, and periodically update smoking status in a consistent place in the medical record. Although screening for and documenting smoking status are only the first step toward helping patients stop smoking, it is an important one. The electronic health record (EHR) may be an effective tool to help clinicians address tobacco use more consistently. To evaluate the impact of EHR-generated practice feedback on rates of referral to a state-level tobacco quitline, we conducted a cluster randomized clinical trial (feedback versus no feedback) within 19 primary care clinics in Oregon. Intervention clinics received provider-specific monthly feedback reports generated from EHR data. The reports rated provider performance in asking, advising, assessing, and assisting with tobacco cessation compared with a clinic average and an achievable benchmark of care. During 12 months of follow-up, EHR-documented rates of advising, assessing, and assisting were significantly improved in the intervention clinics compared with the control clinics (p<.001). A higher case-mix index and presence of a clinic champion were associated with higher rates of referral to a state-level quitline. EHR-generated provider feedback improved documentation of assistance with tobacco cessation. Connecting physician offices to a state-level quitline was feasible and well accepted. To evaluate the effects of the Tobacco Use Cessation (TUC) Automated Clinical Practice Guideline (ACPG) (a variation of the US Department of Health and Human Services Clinical Practice Guideline on Treating Tobacco Use and Dependence) on guideline adherence in a multisite health system.
                The study used a pre-post cross-sectional design. Paneled patients were enrolled from 6 clinics, including 2 control clinics (arm 1), 2 control clinics that received a check-in screen only (the check-in screen provided a simplified method for entering patient vital signs into the electronic medical record) (arm 2), and 2 clinics that received the TUC intervention (arm 3).
                Baseline data on physician compliance with the 5 As (ask, assess, advise, assist, and arrange) at the last office visit were collected via telephone surveys from patients in the 3 study arms. The TUC-ACPG was then introduced in the TUC intervention clinics as part of the existing electronic medical record. Approximately 2 weeks after the TUC intervention, postimplementation data were collected via telephone survey.
                In the TUC intervention arm, postimplementation adherence rates increased relative to baseline for all 5 points of the guideline, with the largest increases seen in the assess and arrange guideline points. Controlling for factors such as age, race, and relevant comorbidities, logistic regression analysis indicated that the time (preimplementation vs postimplementation)-x-TUC intervention arm interaction demonstrated a statistically significant increase in the assess guideline point.
                Although baseline adherence rates were already high, the introduction of the TUC-ACPG led to further increases in guideline adherence.
At least in the short term, documentation of tobacco status and increased referral to cessation counseling do appear to increase following the introduction of an expectation to use the EHR to record and treat patient tobacco use at medical visits. There is a need for additional research to further understand the effect of EHRs on smoking treatment in healthcare settings.