A Provider-Facing Decision Support Tool for Prostate Cancer Screening in Primary Care: A Pilot Study.

OBJECTIVES: Our objective was to pilot test an electronic health record-embedded decision support tool to facilitate prostate-specific antigen (PSA) screening discussions in the primary care setting. METHODS: We pilot-tested a novel decision support tool that was used by 10 primary care physicians (PCPs) for 6 months, followed by a survey. The tool comprised (1) a risk-stratified algorithm, (2) a tool for facilitating shared decision-making (Simple Schema), (3) three best practice advisories (BPAs: <45, 45-75, and >75 years), and (4) a health maintenance module for scheduling automated reminders about PSA rescreening. RESULTS: All PCPs found the tool feasible, acceptable, and clear to use. Eight out of ten PCPs reported that the tool made PSA screening conversations somewhat or much easier. Before using the tool, 70% of PCPs felt confident in their ability to discuss PSA screening with their patient, and this improved to 100% after the tool was used by PCPs for 6 months. PCPs found the BPAs for eligible (45-75 years) and older men (>75 years) more useful than the BPA for younger men (<45 years). Among the 10 PCPs, 60% found the Simple Schema to be very useful, and 50% found the health maintenance module to be extremely or very useful. Most PCPs reported the components of the tool to be at least somewhat useful, with 10% finding them to be very burdensome. CONCLUSION: We demonstrated the feasibility and acceptability of the tool, which is notable given the marked low acceptance of existing tools. All PCPs reported that they would consider continuing to use the tool in their clinic and were likely or very likely to recommend the tool to a colleague.

Primary Care Physician Preferences Regarding Communication from Orthopaedic Surgeons.

BACKGROUND: Musculoskeletal consultations constitute a growing portion of primary care physician (PCP) referrals. Optimizing communication between PCPs and orthopaedists can potentially reduce time spent in the electronic medical record (EMR) as well as physician burnout. Little is known about the preferences of PCPs regarding communication from orthopaedic surgeons. Hence, the present study investigated, across a large health network, the preferences of PCPs regarding communication from orthopaedists. METHODS: A total of 175 PCPs across 15 practices within our health network were surveyed. These providers universally utilized Epic as their EMR platform. Five-point, labeled Likert scales were utilized to assess the PCP-perceived importance of communication from orthopaedists in specific clinical scenarios. PCPs were further asked to report their preferred method of communication in each scenario and their overall interest in communication from orthopaedists. Logistic regression analyses were performed to determine whether any PCP characteristics were associated with the preferred method of communication and the overall PCP interest in communication from orthopaedists. RESULTS: A total of 107 PCPs (61.1%) responded to the survey. PCPs most commonly rated communication from orthopaedists as highly important in the scenario of an orthopaedist needing information from the PCP. In this scenario, PCPs preferred to receive an Epic Staff Message. Scenarios involving a recommendation for surgery, hospitalization, or a major clinical change were also rated as highly important. In these scenarios, an Epic CC'd Chart rather than a Staff Message was preferred. Increased after-hours EMR use was associated with diminished odds of having a high interest in communication from orthopaedists (odds ratio, 0.65; 95% confidence interval, 0.48 to 0.88; p = 0.005). Ninety-three PCPs (86.9%) reported spending 1 to 1.5 hours or more per day in Epic after normal clinical hours, and 27 (25.2%) spent >3 hours per day. Forty-six PCPs (43.0%) reported experiencing ≥1 symptom of burnout. CONCLUSIONS: There were distinct preferences among PCPs regarding clinical communication from orthopaedic surgeons. There was also evidence of substantial burnout and after-hours work effort by PCPs. These results may help to optimize communication between PCPs and orthopaedists while reducing the amount of time that PCPs spend in the EMR.

Protocol for a randomized controlled trial of the Enhanced Smoking Cessation Approach to Promote Empowerment (ESCAPE) digitalized intervention to promote lung health in high-risk individuals who smoke.

Low dose computed tomography (LDCT) is an effective screening test to decrease lung cancer deaths. Lung cancer screening may be a teachable moment helping people who smoke to quit, which may result in increased benefit of screening. Innovative strategies are needed to engage high-risk individuals in learning about LDCT screening. More precise methods such as polygenic risk scores quantify genetic predisposition to tobacco use, and optimize lung health interventions. We present the ESCAPE (Enhanced Smoking Cessation Approach to Promote Empowerment) protocol. This study will test a smoking cessation intervention using personal stories and a lung cancer screening decision-aide compared to standard care (brief advice, referral to a quit line, and a lung cancer screening decision-aide), examine the relationship between a polygenic risk score and smoking abstinence, and describe perceptions about integration of genomic information into smoking cessation treatment. A randomized controlled trial followed by a sequential explanatory mixed methods approach will compare the efficacy of the interventions. Interviews will add insight into the use of genomic information and risk perceptions to tailor smoking cessation treatment. Two-hundred and fifty individuals will be recruited from primary care, community-based organizations, mailing lists and through social media. Data will be collected at baseline, 1, 3 and 6-months. The primary outcomes are 7-day point prevalence smoking abstinence and stage of lung cancer screening at 6-months. The results from this study will provide information to refine the ESCAPE intervention and facilitate integration of precision health into future lung health interventions. Clinical trial registration number: NCT0469129T.

Association Between Electronic Health Record Time and Quality of Care Metrics in Primary Care.

Importance: Physicians across the US spend substantial time working in the electronic health record (EHR), with primary care physicians (PCPs) spending the most time. The association between EHR time and ambulatory care quality outcomes is unclear. Objective: To characterize measures of EHR use and ambulatory care quality performance among PCPs. Design, Setting, and Participants: A cross-sectional study of PCPs with longitudinal patient panels using a single EHR vendor was conducted at Brigham and Women's Hospital and Massachusetts General Hospital during calendar year 2021. Exposures: Independent variables included PCPs demographic and practice characteristics and EHR time measures (PCP-level mean of daily total EHR time, after-hours time, time from 5:30 pm to 7:00 am and time on weekends, and daily EHR time on notes, sending and receiving patient, staff, results, prescription, or system messages [in-basket], and clinical review). Main Outcomes and Measures: Outcome variables were ambulatory quality measures (year-end, PCP panel-level achievement of targets for hemoglobin A1c level control, lipid management, hypertension control, diabetes screening, and breast cancer screening). Results: The sample included 291 physicians (174 [59.8%] women). Median panel size was 829 (IQR, 476-1157) patients and mean (SD) clinical full-time equivalent was 0.54 (0.27). The PCPs spent a mean (SD) of 145.9 (64.6) daily minutes on the EHR. There were significant associations between EHR time and panel-level achievement of hemoglobin A1c control, hypertension control, and breast cancer screening targets. In adjusted analyses, each additional 15 minutes of total daily EHR time was associated with 0.58 (95% CI, 0.32-0.84) percentage point greater panel-level hemoglobin A1c control, 0.52 (95% CI, 0.33-0.71) percentage point greater hypertension control, and 0.28 (95% CI, 0.05-0.52) higher breast cancer screening rates. Each daily additional 15 minutes of in-basket time was associated with 2.26 (95% CI, 1.05-3.48) greater panel-wide hemoglobin A1c control, 1.65 (95% CI, 0.83-2.47) percentage point greater hypertension control, and 1.26 (95% CI, 0.51-2.02) percentage point higher breast cancer screening rates. Associations were largely concentrated among PCPs with 0.5 clinical full-time equivalent or less. There were no associations between EHR use metrics and diabetes screening or lipid management in patients with cardiovascular disease. Conclusions and Relevance: This cross-sectional study found an association between EHR time and some measures of ambulatory care quality. Although increased EHR time is associated with burnout, it may represent a level of thoroughness or communication that enhances certain outcomes. It may be useful for future studies to characterize payment models, workflows, and technologies that enable high-quality ambulatory care delivery while minimizing EHR burden.

Unscheduled Radiologic Examination Orders in the Electronic Health Record: A Novel Resource for Targeting Ambulatory Diagnostic Errors in Radiology.

PURPOSE: The aim of this study was to assess the prevalence of unscheduled radiologic examination orders in an electronic health record, and the proportion of unscheduled orders that are clinically necessary, by modality. METHODS: This retrospective study was conducted from January to October 2016 at an academic institution. All unscheduled radiologic examination orders were retrieved for seven modalities (CT, MR, ultrasound, obstetric ultrasound, bone densitometry, mammography, and fluoroscopy). After excluding duplicates, 100 randomly selected orders from each modality were assigned to two physician reviewers who classified their clinical necessity, with 10% overlap. Interannotator agreement was assessed using κ statistics, the percentage of clinically necessary unscheduled orders was compared, and χ2 analysis was used to assess differences by modality. RESULTS: A total 494,503 radiologic examination orders were placed during the study period. After exclusions, 33,546 unscheduled orders were identified, 7% of all radiologic examination orders. Among 700 reviewed unscheduled orders, agreement was substantial (κ = 0.63). Eighty-seven percent of bone densitometric examinations and sixty-five percent of mammographic studies were considered clinically necessary, primarily for follow-up management. The majority of orders in each modality were clinically necessary, except for CT, obstetric ultrasound, and fluoroscopy (P < .0001). CONCLUSIONS: Large numbers of radiologic examination orders remain unscheduled in the electronic health record. A substantial portion are clinically necessary, representing potential delays in executing documented provider care plans. Clinically unnecessary unscheduled orders may inadvertently be scheduled and performed. Identifying and performing clinically necessary unscheduled radiologic examination orders may help reduce diagnostic errors related to diagnosis and treatment delays and enhance patient safety, while eliminating clinically unnecessary unscheduled orders will help avoid unneeded testing.

An Electronic Health Record Order Entry-Enabled Educational Intervention Is Not Effective in Reducing STAT Inpatient Radiology Orders.

OBJECTIVE: Assess whether introducing order priorities with defined performance expectations in the electronic health record (EHR) reduces immediate inpatient radiology orders. MATERIALS AND METHODS: This Institutional Review Board-approved, retrospective study was performed at a 776-bed academic hospital conducting 164,000+ inpatient radiology examinations annually. Study period was January 2, 2017, to July 23, 2017; 14 weeks pre- and postimplementation of an education-only intervention including replacing urgent and as soon as possible priorities with imaging within next 6, 12, or 24 hours; imaging in the morning; and required for discharge priorities. STAT routine, timed, today order priorities remained unchanged. Institution-wide training immediately pre- and postimplementation was provided through two waves of e-mail and electronic tip sheets. Primary outcome measure was total STAT studies ordered of total radiology studies ordered per week (STAT rate). Secondary outcomes were non-STAT, non-routine (non-SR) order rate, and routine order rate. Paired t test and statistical process control (SPC) analysis were performed. RESULTS: STAT rate pre- (22.5%, 7,150 STAT of 31,765 total; weeks 1-14) and postintervention (23.4%, 7,481 STAT of 32,034 total; weeks 16-29) remained unchanged (P = .37). SPC demonstrated no special cause variation. Postintervention non-SR rate increased 3-fold (2.7%, 859 non-SR of 31,765 total pre-intervention versus 8.2%, 2,615 non-SR of 32,034 total postintervention; 8.2%/2.7% = 3.0; P < .0001). There was an 8.8% relative reduction in routine rate postintervention (73.9%, 23,471 routine of 31,765 total pre-intervention; 67.4%, 21,579 routine of 32,034 total postintervention; (73.9% - 67.4%)/73.9% × 100 = 8.8%; P < .0001). CONCLUSION: Implementing ordering priorities with defined performance expectations in the EHR reduced routine but did not reduce STAT inpatient radiology orders. More stringent interventions may be needed to reduce unnecessary STAT inpatient radiology ordering to improve use of limited imaging resources.

Perceptions of Oncologists About Sharing Clinic Notes with Patients.

In a large survey (n = 809) conducted to understand how oncologists differ from nononcologists regarding routinely sharing visit notes with patients, oncologists were less likely to agree patient safety would improve (p = .03) or that patients would be offended after reading notes (p = .01); however, they agreed with nononcologists that sharing notes would lead to less candid documentation (69% vs. 73%; p = .39). Oncologists share a high level of worry about the impact of sharing notes on documentation practices, a concern that will need to be addressed as the practice of sharing visit notes expands to cancer care.

Changes in the quality of care during progress from stage 1 to stage 2 of Meaningful Use.

Background: The Centers for Medicare and Medicaid Services (CMS) canceled Meaningful Use (MU), replacing it with Advancing Care Information, which preserves many MU elements. Therefore, transitioning from MU stage 1 to MU stage 2 has important implications for the new policy, yet the quality of care provided by physicians transitioning from MU1 to MU2 is unknown. Methods: Retrospective longitudinal evaluation of the quality of care delivered by outpatient physicians at an academic medical center in the transition between MU1 and MU2. Results: Between MU1 and MU2, 4 measures improved: hypertension control (35% vs 40%), influenza immunization (63% vs 68%), tobacco use assessment/counseling (86% vs 96%), and diabetes control (93% vs 96%; P all <.01). One worsened: senior weight screening/follow-up (54% vs 49%; P < .01). Two were unchanged: chlamydia screening and adult weight screening/follow-up. Conclusion: In this single-site study, when clinicians progressed from MU1 to MU2, 4 quality measures improved, 2 were unchanged, and 1 worsened. Analysis of national data should guide policy decisions about the content of MU's successor.

Journal club: Requiring clinical justification to override repeat imaging decision support: impact on CT use.

OBJECTIVE: The purpose of this study was to determine the impact of requiring clinical justification to override decision support alerts on repeat use of CT. SUBJECTS AND METHODS: This before and after intervention study was conducted at a 793-bed tertiary hospital with computerized physician order entry and clinical decision support systems. When a CT order is placed, decision support alerts the orderer if the patient's same body part has undergone CT within the past 90 days. The study cohort included all 28,420 CT orders triggering a repeat alert in 2010. The intervention required clinical justification, selected from a predetermined menu, to override repeat CT decision support alerts to place a CT order; otherwise the order could not be placed and was dropped. The primary outcome, dropped repeat CT orders, was analyzed using three methods: chi-square tests to compare proportions dropped before and after intervention; multiple logistic regression tests to control for orderer, care setting, and patient factors; and statistical process control for temporal trends. RESULTS: The repeat CT order drop rate had an absolute increase of 1.4%; 6.1% (682/11,230) before to 7.5% (1290/17,190) after intervention, which was a 23% relative change (7.5 - 6.1)/6.1 × 100 = 23%; p < 0.0001). Orders were dropped more often after intervention (odds ratio, 1.3; 95% CI, 1.1-1.4; p < 0.0001). Statistical control analysis supported the association between the increase in the drop rate with intervention rather than underlying trends. CONCLUSION: Adding a requirement for clinical justification to override alerts modestly but significantly improves the impact of repeat CT decision support (23% relative change), with the overall effect of preventing one in 13 repeat CT orders.