We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

An accurate method of measuring primary care providers' tobacco counseling actions is needed for monitoring adherence to clinical practice guidelines. We compared three methods of measuring providers' tobacco counseling practices: electronic medical record (EMR) review, patient survey, and provider survey. We mailed a survey to 1,613 smokers seen by 114 Boston-area primary care providers during a 2-month period to assess what tobacco counseling actions had occurred at the visit (N = 766; 47% response rate). Smokers' reports were compared with the EMR and with their providers' self-reported usual tobacco counseling practices, derived from a provider survey (N = 110; 96% response rate). Patients reported receiving each counseling action more frequently than providers documented it in the EMR. Agreement between the patient survey and the EMR was poor for all 5A steps (kappa statistic = 0.01-0.22). Providers reported that they often or always performed each 5A action at a higher rate than indicated by EMR or patient report. However, providers who said they often or always performed individual 5A steps did not have consistently higher mean rates of EMR documentation or patient report than those who said they performed the 5A's less frequently. Little agreement was found among the three methods of measuring primary care providers' tobacco counseling actions. Implementing an EMR does not necessarily improve providers' documentation of tobacco interventions, but EMR adaptations that would standardize provider documentation of tobacco counseling might make the EMR a more reliable tool for monitoring providers' delivery of tobacco treatment services.

U.S. Public Health Service (USPHS) clinical guidelines for tobacco treatment recommend that providers routinely counsel smokers using a five-step algorithm (5A's): ask about tobacco use, advise smokers to quit, assess interest in quitting, assist with treatment, and arrange follow-up. A potential barrier to compliance is providers' concern that addressing smoking might alienate smokers, especially those not ready to quit. A survey was mailed to 1,985 patients seen at one of eight Boston-area primary care practices from January 1 to March 31, 2003, and identified as smokers by chart review. The survey assessed respondents' receipt of the 5A's at their visit and their satisfaction with the provider's tobacco treatment and with their overall health care. We used multivariable logistic regression models to assess the association between satisfaction with care and patient-reported receipt of each 5A step, adjusted for age, sex, education, race, health status, smoking intensity, readiness to quit, and length of relationship with provider. Of 1,160 respondents (58% response rate), 765 reported that they smoked at the time of the visit. They reported high levels of satisfaction with their tobacco-related care and overall care. Patient-reported receipt of each 5A step was significantly associated with greater patient satisfaction with tobacco-related care and with overall health care, even after adjusting for a smoker's readiness to quit smoking. Satisfaction with overall health care increased as counseling intensity increased. Patient reports of smoking cessation interventions delivered during primary care practice are associated with greater patient satisfaction with their health care, even among smokers not ready to quit. Providers can follow USPHS guidelines with smokers without fear of alienating those not yet considering quitting.

BackgroundAccurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date.ObjectiveTo determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation.Study Design and MethodsInference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009–5/2010) and intervention (5/2010–11/2010) periods.Results17 043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions.ConclusionProblem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement.Trial RegistrationClinicalTrials.gov: NCT01105923.

Background 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. Methods 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. Results 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). Conclusion This electronic health record–based intervention improved smoking status documentation and increased counseling assistance to smokers but not the prescription of cessation medication.

Background Examine the impact of a multi-faceted, clinical decision support (CDS)-enabled intervention on magnetic resonance imaging (MRI) use in adult primary care patients with low back pain. Methods After a baseline observation period, we implemented a CDS targeting lumbar-spine MRI use in primary care patients with low back pain through our computerized physician order entry (CPOE) as well as two accountability tools: 1) mandatory peer-to-peer consultation when test utility was uncertain and 2) quarterly practice pattern variation reports to providers. Our primary outcome measure was rate of lumbar-spine MRI use. Secondary measures included utilization of MRI of any body part, comparing to that of a concurrent national comparison, as well as proportion of lumbar-spine MRI performed in the study cohort that was adherent to evidence-based guideline. Chi-square, t-tests, and logistic regression were used to assess pre- and post-intervention differences. Results In the study cohort, pre-intervention, 5.3% of low back pain-related primary care visits resulted in lumbar-spine MRI compared to 3.7% of visits post-intervention (p<0.0001, Adjusted Odds Ratio 0.68). There was a 30.8% relative decrease (6.5% vs. 4.5%, p<0.0001, Adjusted Odds Ratio 0.67) in the use of MRI of any body part by the primary care providers in the study cohort. This difference was not detected in the control cohort (5.6% vs. 5.3%, p=0.712). In the study cohort, adherence to evidence-based guideline in the use of lumbar-spine MRI increased from 78% to 96% (p=0.0002). Conclusions CDS and associated accountability tools may reduce potentially inappropriate imaging in patients with low back pain.

Background and objectives CKD is associated with significant morbidity, mortality, and financial burden. Practice guidelines outlining CKD management exist, but there is limited application of these guidelines. Interventions to improve CKD guideline adherence have been limited. This study evaluated a new CKD checklist (a tool outlining management guidelines for CKD) to determine whether implementation in an academic primary care clinic improved adherence to guidelines.Design, setting, participants, & measurements During a 1-year period (August 2012-August 2013), a prospective study was conducted among 13 primary care providers (PCPs), four of whom were assigned to use a CKD checklist incorporated into the electronic medical record during visits with patients with CKD stages 1-4. All providers received education regarding CKD guidelines. The intervention and control groups consisted of 105 and 263 patients, respectively. Adherence to CKD management guidelines was measured.Results A random-effects logistic regression analysis was performed to account for intra-group correlation by PCP assignment and adjusted for age and CKD stage. CKD care improved among patients whose PCPs were assigned to the checklist intervention compared with controls. Patients in the CKD checklist group were more likely than controls to have appropriate annual laboratory testing for albuminuria (odds ratio [OR], 7.9; 95% confidence interval [95% CI], 3.6 to 17.2), phosphate (OR, 3.5; 95% CI, 1.5 to 8.3), and parathyroid hormone (OR, 8.1; 95% CI, 4.8 to 13.7) (P,0.001 in all cases). Patients in the CKD checklist group had higher rates of achieving a hemoglobin A1c target,7% (OR, 2.7; 95% CI, 1.4 to 5.1), use of an angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker (OR, 2.1; 95% CI, 1.0 to 4.2), documentation of avoidance of nonsteroidal anti-inflammatory drugs (OR, 41.7; 95% CI, 17.8 to 100.0), and vaccination for annual influenza (OR, 2.1; 95% CI, 1.1 to 4.0) and pneumococcus (OR, 4.7; 95% CI, 2.6 to 8.6) (P,0.001 in all cases).Conclusions Implementation of a CKD checklist significantly improved adherence to CKD management guidelines and delivery of CKD care.

Subjects saw or heard words in a list (e.g. limerick) and then took two successive tests. The first was a yes/no recognition test in which auditory/visual modality of test words was manipulated orthogonally to the study modality. The second test varied with experimental conditions: subjects produced words to either perceptual (fragment) cues (l- -e-ick) or conceptual cues (What name is given to a lighthearted five-line poem?), under either explicit or implicit retrieval instructions. The major findings were: (a) that regardless of the type of retrieval cue (perceptual or conceptual) the degree of dependency between recognition and cued recall was greater than that between recognition and implicit retrieval; and (b) that modality shifts adversely affected perceptually cued explicit and implicit retrieval, whereas they had no effect either on conceptually cued retrieval or on recognition. These results suggest that the memory system subserving, and the processes involved in, conceptual priming differ from those underlying recognition and perceptual priming.