Pain Management in Primary Care: A Randomized Controlled Trial of a Computerized Decision Support Tool.

BACKGROUND: Primary care providers manage most patients with chronic pain. Pain is a complex problem, particularly in underserved populations. A technology-enabled, point-of-care decision support tool may improve pain management outcomes. METHODS: We created an electronic health record (EHR)-based decision support tool, the Pain Management Support System-Primary Care (PMSS-PC), and studied the tool-plus-education in 6 Federally Qualified Health Center practices using a randomized, wait-list controlled design. The PMSS-PC generated "best practice alerts," gave clinicians access to a pain assessment template, psychological distress and substance use measures, guidelines for drug and non-drug therapies, and facilitated referrals. Practices were randomly assigned to early vs delayed (after 6 months) implementation of the intervention, including technical support and 6 webinars. The primary outcome was change in worst pain intensity scores after 6 months, assessed on the Brief Pain Inventory-Short Form. Changes in outcomes were compared between the practices using linear multilevel modeling. The EHR provided clinician data on PMSS-PC utilization. RESULTS: The 256 patients in the early implementation practices had significantly improved worst pain (standardized effect size [ES] = -.32) compared with the 272 patients in the delayed implementation practices (ES = -.11). There was very low clinician uptake of the intervention in both conditions. CONCLUSIONS: Early implementation of the PMSS-PC improved worst pain, but this effect cannot be attributed to clinician use of the tool. Further PMSS-PC development is not indicated, but practice-level interventions can improve pain, and studies are needed to identify the determinants of change.

Effect of an Electronic Health Record "Nudge" on Opioid Prescribing and Electronic Health Record Keystrokes in Ambulatory Care.

BACKGROUND: Multiple policy initiatives encourage more cautious prescribing of opioids in light of their risks. Electronic health record (EHR) redesign can influence prescriber choices, but some redesigns add to workload. OBJECTIVE: To estimate the effect of an EHR prescribing redesign on both opioid prescribing choices and keystrokes. DESIGN: Quality improvement quasi-experiment, analyzed as interrupted time series. PARTICIPANTS: Adult patients of an academic multispecialty practice and a federally qualified health center (FQHC) who received new prescriptions for short-acting opioids, and their providers. INTERVENTION: In the redesign, new prescriptions of short-acting opioids defaulted to the CDC-recommended minimum for opioid-naïve patients, with no alerts or hard stops, such that 9 keystrokes were required for a guideline-concordant prescription and 24 for a non-concordant prescription. MAIN MEASURES: Proportion of guideline-concordant prescriptions, defined as new prescriptions with a 3-day supply or less, calculated per 2-week period. Number of mouse clicks and keystrokes needed to place prescriptions. KEY RESULTS: Across the 2 sites, 22,113 patients received a new short-acting opioid prescription from 821 providers. Before the intervention, both settings showed secular trends toward smaller-quantity prescriptions. At the academic practice, the intervention was associated with an immediate increase in guideline-concordant prescriptions from an average of 12% to 31% of all prescriptions. At the FQHC, about 44% of prescriptions were concordant at the time of the intervention, which was not associated with an additional significant increase. However, total keystrokes needed to place the concordant prescriptions decreased 62.7% from 3552 in the 6 months before the intervention to 1323 in the 6 months afterwards. CONCLUSIONS: Autocompleting prescription forms with guideline-recommended values was associated with a large increase in guideline concordance in an organization where baseline concordance was low, but not in an organization where it was already high. The redesign markedly reduced the number of keystrokes needed to place orders, with important implications for EHR-related stress. TRIAL REGISTRATION: www.ClinicalTrials.gov protocol 1710018646.

Implementation of Electronic Decision Support for Diabetic Care in a Student-Run Clinic.

Background and objectives Type 2 diabetes mellitus (T2DM) is a complex disease that can lead to complications. Electronic decision support in the electronic medical record (EMR) aids management. There is no study demonstrating the effectiveness of electronic decision support in assisting medical student providers in student-run free clinics. Methods There were 71 T2DM patients seen by medical students. Twenty-three encounters used a Diabetes Progress Note (DPN) that was created from consensus, opinion-based guidelines. Each note received a total composite score based on an eight-point scale for adherence to guidelines. Statistical comparisons between mean composite scores were performed using independent t-tests. Results The mean total composite score of DPN users was significantly greater than DPN non-users (5.35 vs. 4.23, p = 0.008), with a significant difference in the physical exam component (1.70 vs. 1.31, p = 0.002). Conclusions In this exploratory study, medical student providers at an attending-supervised, student-run free clinic that used electronic decision support during T2DM patient visits improved adherence to screening for diabetic complications and standard of care.

Correction to: Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.

Following publication of the original article [1], the authors reported that the article erroneously stated that Dr. Ancker was affiliated with the Tehran University of Medical Sciences. Dr. Ancker is not affiliated with that institution.

Enhancing Medical Student-Interpreter Collaboration in an Urban Free Clinic.

BACKGROUND AND OBJECTIVES: Cultural barriers and patient-provider language discordance exert deleterious effects on patient care. One solution has been the integration of medical interpreters into the care of patients with limited English proficiency. While medical schools and residency programs have started developing training programs on how to work with medical interpreters, no similar endeavor has been reported by student-run free clinics. METHODS: Over 1 year, 76 third-year medical students (MS3s) were enrolled in control and intervention groups, and evaluated by in-person interpreters during interpreted real-patient encounters. MS3s in the intervention group received a lesson- and reminder-based training program on how to work with in-person interpreters. RESULTS: MS3s who received the intervention were more likely to ask the patient one question at a time (odds ratio [OR] 3.54, P=.0079), listen to the interpreter without unnecessary interruption (OR 3.30, P=.022), and speak in short, simple sentences with pauses for interpretation (OR 3.08, P=.017). CONCLUSIONS: Our lesson- and reminder-based training program on provider-interpreter collaboration can improve the performance of MS3s within a select skill set with minimal cost and time investment.

Race and Ethnicity Do Not Clinically Associate with Quality of Life Among Patients with Chronic Severe Pain in a Federally Qualified Health Center.

Objective: Previous research suggests that race/ethnicity predicts health-related quality of life (HRQL) in chronic pain populations but has not examined this in community settings. This study evaluated this association in 522 community-dwelling patients with chronic pain treated at a Federally Qualified Health Center (FQHC). Design: Cross-sectional secondary analysis. Setting: Six practice sites of an FQHC in New York. Subjects: One hundred forty-two non-Hispanic blacks, 121 non-Hispanic whites, 219 Hispanics, and 40 classified as "other" with severe chronic pain. Methods: Patients with chronic severe pain (three or more months with worst pain ≥ 4/10 or T-score > 60.5 on the Patient-Reported Outcomes Measurement Information System pain interference tool) were interviewed as part of a clinical trial. Race/ethnicity and other potential predictors of HRQL were assessed. Results: Mean age was 53.0 years, and 70.1% were women; 62.8% earned less than $10,000 per year, and 22.8% were Spanish-speaking with low acculturation. Mean worst pain during the past week was 8.6/10, and 39.6% used opioids. In multivariate analyses, race/ethnicity was not significantly associated with mental HRQL. Hispanics had significantly lower physical HRQL than non-Hispanic whites or blacks, but this difference was not clinically meaningful (mean T-scores = 33.9 [Hispanics], 35.8 [non-Hispanic whites], and 35.6 [non-Hispanic blacks]). Mental HRQL was predicted by depression, anxiety, pain disability, income, and physical HRQL; physical HRQL was predicted by race/ethnicity, anxiety, pain disability, age, care satisfaction, and mental HRQL. Conclusions: Race/ethnicity does not explain important variation in HRQL reported by diverse patients with chronic pain. Psychological distress, pain disability, age, and socioeconomic status predicted this health outcome. Future studies may clarify modifiers of these associations to guide treatment in FQHC populations.

Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.

BACKGROUND: Although alert fatigue is blamed for high override rates in contemporary clinical decision support systems, the concept of alert fatigue is poorly defined. We tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time. METHODS: Retrospective cohort study using electronic health record data (both drug alerts and clinical practice reminders) from January 2010 through June 2013 from 112 ambulatory primary care clinicians. The cognitive overload hypotheses were that alert acceptance would be lower with higher workload (number of encounters, number of patients), higher work complexity (patient comorbidity, alerts per encounter), and more alerts low in informational value (repeated alerts for the same patient in the same year). The desensitization hypothesis was that, for newly deployed alerts, acceptance rates would decline after an initial peak. RESULTS: On average, one-quarter of drug alerts received by a primary care clinician, and one-third of clinical reminders, were repeats for the same patient within the same year. Alert acceptance was associated with work complexity and repeated alerts, but not with the amount of work. Likelihood of reminder acceptance dropped by 30% for each additional reminder received per encounter, and by 10% for each five percentage point increase in proportion of repeated reminders. The newly deployed reminders did not show a pattern of declining response rates over time, which would have been consistent with desensitization. Interestingly, nurse practitioners were 4 times as likely to accept drug alerts as physicians. CONCLUSIONS: Clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert. Reducing within-patient repeats may be a promising target for reducing alert overrides and alert fatigue.

Skin Disease in the Uninsured: Diagnoses, Management Decisions, and Referral Outcomes of an Urban Free Clinic.

An understanding of the burden of skin disease in the uninsured population is needed to address the unique barriers they face to access dermatologic care. We conducted a retrospective chart review of patients seen for skin conditions over three years at the New York City (NYC) Free Clinic, a weekly primary care clinic operated by the NYU School of Medicine and the Institute for Family Health. Main outcomes of this study were descriptive analyses of demographic characteristics, diagnoses, management strategies, and referral outcomes, as well as key factors influencing referral to a dermatologist and referral attendance. Diagnosis was a significant predictor of referral (p<.000). The referral attendance rate was 52.5%. Patients older than 50 years were more likely to attend their appointments than younger patients (p=.025). Gender, wait time, and travel distance had no significant association with non-attendance. While demand for dermatologic care by uninsured patients in NYC is high, referral non-attendance remains a substantial barrier to care.

Associations between healthcare quality and use of electronic health record functions in ambulatory care.

OBJECTIVES: Contemporary electronic health records (EHRs) offer a wide variety of features, creating opportunities to influence healthcare quality in different ways. This study was designed to assess the relationship between physician use of individual EHR functions and healthcare quality. MATERIALS AND METHODS: Sixty-five providers eligible for "meaningful use" were included. Data were abstracted from office visit records during the study timeframe (183 095 visits with 61 977 patients). Three EHR functions were considered potential predictors: acceptance of best practice alerts, use of order sets, and viewing panel-level reports. Eighteen clinical quality measures from the "meaningful use" program were abstracted. RESULTS: Use of condition-specific best-practice alerts and order sets was associated with better scores on clinical quality measures capturing processes in diabetes, cancer screening, tobacco cessation, and pneumonia vaccination. For example, providers above the median in use of tobacco-related alerts had higher performance on tobacco cessation intervention metrics (median 80.6% vs. 66.7%; P < .001), and providers above the median in use of diabetes order sets had higher quality on diabetes low density lipoprotein (LDL) testing (68.2% vs. 59.5%; P == .001). Post hoc examination of the results showed that the positive associations were with measures of healthcare processes (such as rates of LDL testing), whereas there were no positive associations with measures of healthcare outcomes (such as LDL levels). DISCUSSION: Among primary care providers in the ambulatory setting using a single EHR, intensive use of certain EHR functions was associated with increased adherence to recommended care as measured by performance on electronically reported "meaningful use" quality measures. This study is relevant to current policy as it uses quality metrics constructed by contemporary certified EHR technology, and quantitative EHR use metrics rather than self-reported use. CONCLUSION: In the early stages of the "meaningful use" program, use of specific EHR functions was associated with higher performance on healthcare process metrics.

How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use.

BACKGROUND: Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features. OBJECTIVE: To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time. METHODS: Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use. RESULTS: Data were analyzed for 112 physicians and nurse practitioners, consisting of 430,803 encounters with 99,649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency. CONCLUSIONS: Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.