Clinician Ordering and Management Patterns of Urine Toxicology Results at a Cancer Center

CONTEXT

Opioid therapy is a cornerstone for treatment of cancer-related pain, but standardized management practices for patients with cancer and aberrant urine drug test (UDT) results are lacking.

OBJECTIVES

To identify the prevalence of UDT ordering (both screening and definitive testing) in the oncology setting and to examine clinician management practices for patients with cancer on opioid therapy with aberrant definitive UDT results.

METHODS

We conducted a retrospective chart review of patients with cancer on opioid therapy at an academic cancer center in the United States. Outcomes included UDT ordering patterns and clinician management practices in response to aberrant definitive UDT results.

RESULTS

Our study revealed an overallUDT ordering rate of 3.7% among 10,371 patients with cancer on opioid therapy. Among 143 patients for whom definitive UDTs were ordered, oncologists only ordered 14 (9.8%) UDTs, while palliative care ordered the majority (n=129; 90.2%). Fifty-five (38.5%) patients had aberrant results, and the most common aberrancy was presence of illicit drugs [22 (15.4%)]. Clinicians rarely made medication changes [20 (36.4%)] when UDT results were aberrant, and in the setting of possible fentanyl use (n=8), only 3 (37.5%) patients were started/switched to methadone, and none were started/switched to buprenorphine.

CONCLUSION

Overall UDT ordering was infrequent for patients with cancer on opioid therapy, especially by oncologists, and clinicians rarely make prescribing changes when definitive UDT results were aberrant. More definitive guidance related to UDT ordering and opioid management are needed for patients with cancer and aberrant UDT results.

Low Rate of Completion of Recommended Tests and Referrals in an Academic Primary Care Practice with Resident Trainees

BACKGROUND

A frequent, preventable cause of diagnostic errors involves failure to follow up on diagnostic tests, referrals, and symptoms-termed "failure to close the diagnostic loop." This is particularly challenging in a resident practice where one third of physicians graduate annually, and rates of patient loss due to these transitions may lead to more opportunities for failure to close diagnostic loops. The aim of this study was to determine the prevalence of failure of loop closure in a resident primary care clinic compared to rates in the faculty practice and identify factors contributing to failure.

METHODS

This retrospective cohort study included all patient visits from January 1, 2018, to December 31, 2021, at two academic medical center-based primary care practices where residents and faculty practice in the same setting. The primary outcome was prevalence of failure to close the loop for (1) dermatology referrals, (2) colonoscopy, and (3) cardiac stress testing. The primary predictor was resident vs. faculty status of the ordering provider. The authors present an unadjusted analysis and the results of a multivariable logistic regression analysis incorporating all patient factors to determine their association with loop closure.

RESULTS

Of 12,282 orders for referrals and tests for the three studied areas, 1,929 (15.7%) were ordered by a resident physician. Of resident orders for all three tests, 52.9% were completed within the designated time vs. 58.4% for orders placed by attending physicians (p < 0.01). In an unadjusted analysis by test type, a similar trend was seen for colonoscopy (51.4% completion rate for residents vs. 57.5% for attending physicians, p < 0.01) and for cardiac stress testing (55.7% completion rate for residents vs. 61.2% for attending physicians), though a difference was not seen for dermatology referrals (64.2% completion rate for residents vs. 63.7% for attending physicians). In an adjusted analysis, patients with resident orders were less likely than attendings to close the loop for all test types combined (odds ratio 0.88, 95% confidence interval 0.79-0.98), with low rates of test completion for both physician groups.

CONCLUSION

Loop closure for three diagnostic interventions was low for patients in both faculty and resident primary care clinics, with lower loop closure rates in resident clinics. Failure to close diagnostic loops presents a safety challenge in primary care and is of particular concern for training programs.

Do patients who read visit notes on the patient portal have a higher rate of "loop closure" on diagnostic tests and referrals in primary care? A retrospective cohort study

OBJECTIVES

The 2021 US Cures Act may engage patients to help reduce diagnostic errors/delays. We examined the relationship between patient portal registration with/without note reading and test/referral completion in primary care.

MATERIALS AND METHODS

Retrospective cohort study of patients with visits from January 1, 2018 to December 31, 2021, and order for (1) colonoscopy, (2) dermatology referral for concerning lesions, or (3) cardiac stress test at 2 academic primary care clinics. We examined differences in timely completion ("loop closure") of tests/referrals for (1) patients who used the portal and read ≥1 note (Portal + Notes); (2) those with a portal account but who did not read notes (Portal Account Only); and (3) those who did not register for the portal (No Portal). We estimated the predictive probability of loop closure in each group after adjusting for socio-demographic and clinical factors using multivariable logistic regression.

RESULTS

Among 12 849 tests/referrals, loop closure was more common among Portal+Note-readers compared to their counterparts for all tests/referrals (54.2% No Portal, 57.4% Portal Account Only, 61.6% Portal+Notes, P < .001). In adjusted analysis, compared to the No Portal group, the odds of loop closure were significantly higher for Portal Account Only (OR 1.2; 95% CI, 1.1-1.4), and Portal+Notes (OR 1.4; 95% CI, 1.3-1.6) groups. Beyond portal registration, note reading was independently associated with loop closure (P = .002).

DISCUSSION AND CONCLUSION

Compared to no portal registration, the odds of loop closure were 20% higher in tests/referrals for patients with a portal account, and 40% higher in tests/referrals for note readers, after controlling for sociodemographic and clinical factors. However, important safety gaps from unclosed loops remain, requiring additional engagement strategies.

Completion Rates and Timeliness of Diagnostic Colonoscopies for Rectal Bleeding in Primary Care

BACKGROUND

Rectal bleeding is the most common presenting symptom of colorectal cancer, and guidelines recommend timely follow-up, usually with colonoscopy to ensure timely diagnoses of colorectal cancer.

OBJECTIVE

Identify loop closure rates and vulnerable process points for patients with rectal bleeding.

DESIGN

Retrospective cohort study, using medical record review of patients aged ≥ 40 with index diagnosis of rectal bleeding at 2 primary practices-an urban academic practice and affiliated community health center, between January 1, 2018, and December 31, 2020. Patients were classified as having completed recommended follow-up workup ("closed loop") vs. not ("open loop"). Open loop patient cases were categorized into six types of process failures.

PARTICIPANTS

A total of 837 patients had coded diagnoses of rectal bleeding within study window. Sixty-seven were excluded based on prior colectomy, clinical presentation more consistent with upper GI bleed, no rectal bleeding documented on chart review, or expired during the follow-up period, leaving 770 patients included.

MAIN MEASURES

Primary outcomes were percentages of patient cases classified as "open loops" and distribution of these cases into six categories of process failure that were identified.

KEY RESULTS

22.3% of patients (N = 172) failed to undergo timely recommended workup for rectal bleeding. Largest failure categories were patients for whom no procedure was ordered (N = 62, 36%), followed by patients with procedures ordered but never scheduled (N = 44, 26%) or scheduled but subsequently cancelled or not kept (N = 31, 18%). While open loops increased after the onset of the COVID-19 pandemic, this difference was not significant within our study period.

CONCLUSIONS

Significant numbers of patients presenting to primary care with rectal bleeding fail to undergo recommended workup. The majority either have no procedure ordered, or procedure ordered but never scheduled or cancelled and not kept, suggesting these are important failure modes to target in future interventions. Ensuring reliable ordering and processes for timely scheduling and completion of procedures represent critical areas for improving the diagnostic process for patients with rectal bleeding in primary care.

Completion of Recommended Tests and Referrals in Telehealth vs In-Person Visits

Importance

Use of telehealth has increased substantially in recent years. However, little is known about whether the likelihood of completing recommended tests and specialty referrals-termed diagnostic loop closure-is associated with visit modality.

Objectives

To examine the prevalence of diagnostic loop closure for tests and referrals ordered at telehealth visits vs in-person visits and identify associated factors.

Design, Setting, and Participants

In a retrospective cohort study, all patient visits from March 1, 2020, to December 31, 2021, at 1 large urban hospital-based primary care practice and 1 affiliated community health center in Boston, Massachusetts, were evaluated.

Main Measures

Prevalence of diagnostic loop closure for (1) colonoscopy referrals (screening and diagnostic), (2) dermatology referrals for suspicious skin lesions, and (3) cardiac stress tests.

Results

The study included test and referral orders for 4133 patients (mean [SD] age, 59.3 [11.7] years; 2163 [52.3%] women; 203 [4.9%] Asian, 1146 [27.7%] Black, 2362 [57.1%] White, and 422 [10.2%] unknown or other race). A total of 1151 of the 4133 orders (27.8%) were placed during a telehealth visit. Of the telehealth orders, 42.6% were completed within the designated time frame vs 58.4% of those ordered during in-person visits and 57.4% of those ordered without a visit. In an adjusted analysis, patients with telehealth visits were less likely to close the loop for all test types compared with those with in-person visits (odds ratio, 0.55; 95% CI, 0.47-0.64).

Conclusions

The findings of this study suggest that rates of loop closure were low for all test types across all visit modalities but worse for telehealth. Failure to close diagnostic loops presents a patient safety challenge in primary care that may be of particular concern during telehealth encounters.

Exploring relationships between physician stress, burnout, and diagnostic elements in clinician notes

OBJECTIVES

To understand the relationship between stressful work environments and patient care by assessing work conditions, burnout, and elements of the diagnostic process.

METHODS

Notes and transcripts of audiotaped encounters were assessed for verbal and written documentation related to psychosocial data, differential diagnosis, acknowledgement of uncertainty, and other diagnosis-relevant contextual elements using 5-point Likert scales in seven primary care physicians (PCPs) and 28 patients in urgent care settings. Encounter time spent vs time needed (time pressure) was collected from time stamps and clinician surveys. Study physicians completed surveys on stress, burnout, and work conditions using the Mini-Z survey.

RESULTS

Physicians with high stress or burnout were less likely to record psychosocial information in transcripts and notes (psychosocial information noted in 0% of encounters in 4 high stress/burned-out physicians), whereas low stress physicians (n=3) recorded psychosocial information consistently in 67% of encounters. Burned-out physicians discussed a differential diagnosis in only 31% of encounters (low counts concentrated in two physicians) vs. in 73% of non-burned-out doctors' encounters. Burned-out and non-burned-out doctors spent comparable amounts of time with patients (about 25 min).

CONCLUSIONS

Key diagnostic elements were seen less often in encounter transcripts and notes in burned-out urgent care physicians.

How does work environment relate to diagnostic quality? A prospective, mixed methods study in primary care

OBJECTIVES

The quest to measure and improve diagnosis has proven challenging; new approaches are needed to better understand and measure key elements of the diagnostic process in clinical encounters. The aim of this study was to develop a tool assessing key elements of the diagnostic assessment process and apply it to a series of diagnostic encounters examining clinical notes and encounters' recorded transcripts. Additionally, we aimed to correlate and contextualise these findings with measures of encounter time and physician burnout.

DESIGN

We audio-recorded encounters, reviewed their transcripts and associated them with their clinical notes and findings were correlated with concurrent Mini Z Worklife measures and physician burnout.

SETTING

Three primary urgent-care settings.

PARTICIPANTS

We conducted in-depth evaluations of 28 clinical encounters delivered by seven physicians.

RESULTS

Comparing encounter transcripts with clinical notes, in 24 of 28 (86%) there was high note/transcript concordance for the diagnostic elements on our tool. Reliably included elements were red flags (92% of notes/encounters), aetiologies (88%), likelihood/uncertainties (71%) and follow-up contingencies (71%), whereas psychosocial/contextual information (35%) and mentioning common pitfalls (7%) were often missing. In 22% of encounters, follow-up contingencies were in the note, but absent from the recorded encounter. There was a trend for higher burnout scores being associated with physicians less likely to address key diagnosis items, such as psychosocial history/context.

CONCLUSIONS

A new tool shows promise as a means of assessing key elements of diagnostic quality in clinical encounters. Work conditions and physician reactions appear to correlate with diagnostic behaviours. Future research should continue to assess relationships between time pressure and diagnostic quality.

Diagnostic excellence in primary care

Diagnostic excellence is based on six fundamental principles of healthcare quality proposed by the Institute of Medicine in 2001, which state that diagnoses must be safe, effective, patient-centered, timely, efficient, and equitable.

Closing the Loop: Re-engineering the Assessment and Tracking of Symptoms in Primary Care

Reliable systems that track the continuation, progression, or resolution of a patient's symptoms over time are essential for reliable diagnosis and ensuring that patients harboring more worrisome diagnoses are safely followed up. Given their first-contact role and increasing stresses on busy primary care clinicians and practices, new processes that make these tasks easier rather than creating more work for busy clinicians are especially needed.Some symptoms are sufficiently worrisome that they demand an urgent diagnosis and treatment while others result in a differential that can be more safely explored over time, or less differentiated and worrisome that they are best managed with the "test of time" to see if they resolve, worsen, or evolve into symptoms that are more worrisome. Regardless, it is essential that clinicians are able to reliably track symptoms over time, yet this capacity is rarely available or explicit. Working with systems engineers, we are developing prototypes for such systems and are working on their implementation and evaluation. In this commentary, we describe approaches to this essential, but underappreciated, problem in primary care.

Developing a Framework and Electronic Tool for Communicating Diagnostic Uncertainty in Primary Care: A Qualitative Study

IMPORTANCE

Communication of information has emerged as a critical component of diagnostic quality. Communication of diagnostic uncertainty represents a key but inadequately examined element of diagnosis.

OBJECTIVE

To identify key elements facilitating understanding and managing diagnostic uncertainty, examine optimal ways to convey uncertainty to patients, and develop and test a novel tool to communicate diagnostic uncertainty in actual clinical encounters.

DESIGN, SETTING, AND PARTICIPANTS

A 5-stage qualitative study was performed between July 2018 and April 2020, at an academic primary care clinic in Boston, Massachusetts, with a convenience sample of 24 primary care physicians (PCPs), 40 patients, and 5 informatics and quality/safety experts. First, a literature review and panel discussion with PCPs were conducted and 4 clinical vignettes of typical diagnostic uncertainty scenarios were developed. Second, these scenarios were tested during think-aloud simulated encounters with expert PCPs to iteratively draft a patient leaflet and a clinician guide. Third, the leaflet content was evaluated with 3 patient focus groups. Fourth, additional feedback was obtained from PCPs and informatics experts to iteratively redesign the leaflet content and workflow. Fifth, the refined leaflet was integrated into an electronic health record voice-enabled dictation template that was tested by 2 PCPs during 15 patient encounters for new diagnostic problems. Data were thematically analyzed using qualitative analysis software.

MAIN OUTCOMES AND MEASURES

Perceptions and testing of content, feasibility, usability, and satisfaction with a prototype tool for communicating diagnostic uncertainty to patients.

RESULTS

Overall, 69 participants were interviewed. A clinician guide and a diagnostic uncertainty communication tool were developed based on the PCP interviews and patient feedback. The optimal tool requirements included 6 key domains: most likely diagnosis, follow-up plan, test limitations, expected improvement, contact information, and space for patient input. Patient feedback on the leaflet was iteratively incorporated into 4 successive versions, culminating in a successfully piloted prototype tool as an end-of-visit voice recognition dictation template with high levels of patient satisfaction for 15 patients with whom the tool was tested.

CONCLUSIONS AND RELEVANCE

In this qualitative study, a diagnostic uncertainty communication tool was successfully designed and implemented during clinical encounters. The tool demonstrated good workflow integration and patient satisfaction.

Pharmacists' role in detection and evaluation of adverse drug reactions: Developing proactive systems for pharmacosurveillance

PURPOSE

To identify current challenges in detection of medication-related symptoms, and review technology-based opportunities to increase the patient-centeredness of postmarketing pharmacosurveillance to promote more accountable, safer, patient-friendly, and equitable medication prescribing.

SUMMARY

Pharmacists have an important role to play in detection and evaluation of adverse drug reactions (ADRs). The pharmacist's role in medication management should extend beyond simply dispensing drugs, and this article delineates the rationale and proactive approaches for pharmacist detection and assessment of ADRs. We describe a stepwise approach for assessment, best practices, and lessons learned from a pharmacist-led randomized trial, the CEDAR (Calling for Detection of Adverse Drug Reactions) project.

CONCLUSION

Health systems need to be redesigned to more fully utilize health information technologies and pharmacists in detecting and responding to ADRs.

Improving diagnosis: adding context to cognition

BACKGROUND

The environment in which clinicians provide care and think about their patients is a crucial and undervalued component of the diagnostic process.

CONTENT

In this paper, we propose a new conceptual model that links work conditions to clinician responses such as stress and burnout, which in turn impacts the quality of the diagnostic process and finally patient diagnostic outcomes. The mechanism for these interactions critically depends on the relationship between working memory (WM) and long-term memory (LTM), and ways WM and LTM interactions are affected by working conditions.

SUMMARY

We propose a conceptual model to guide interventions to improve work conditions, clinician reactions and ultimately diagnostic process, accuracy and outcomes.

OUTLOOK

Improving diagnosis can be accomplished if we are able to understand, measure and increase our knowledge of the context of care.

Lessons Learned in Implementing a Chronic Opioid Therapy Management System

OBJECTIVES

Opioid misuse has resulted in significant morbidity and mortality in the United States, and safer opioid use represents an important challenge in the primary care setting. This article describes a research collaborative of health service researchers, systems engineers, and clinicians seeking to improve processes for safer chronic opioid therapy management in an academic primary care center. We present implementation results and lessons learned along with an intervention toolkit that others may consider using within their organization.

METHODS

Using iterative improvement lifecycles and systems engineering principles, we developed a risk-based workflow model for patients on chronic opioids. Two key safe opioid use process metrics-percent of patients with recent opioid treatment agreements and urine drug tests-were identified, and processes to improve these measures were designed, tested, and implemented. Focus groups were conducted after the conclusion of implementation, with barriers and lessons learned identified via thematic analysis.

RESULTS

Initial surveys revealed a lack of knowledge regarding resources available to patients and prescribers in the primary care clinic. In addition, 18 clinicians (69%) reported largely "inheriting" (rather than initiating) their chronic opioid therapy patients. We tracked 68 patients over a 4-year period. Although process measures improved, full adherence was not achieved for the entire population. Barriers included team structure, the evolving opioid environment, and surveillance challenges, along with disruptions resulting from the 2019 novel coronavirus.

CONCLUSIONS

Safe primary care opioid prescribing requires ongoing monitoring and management in a complex environment. The application of a risk-based approach is possible but requires adaptability and redundancies to be reliable.

Latent Class Analysis of Prescribing Behavior of Primary Care Physicians in the Veterans Health Administration

BACKGROUND

Benzodiazepines, opioids, proton-pump inhibitors (PPIs), and antibiotics are frequently prescribed inappropriately by primary care physicians (PCPs), without sufficient consideration of alternative options or adverse effects. We hypothesized that distinct groups of PCPs could be identified based on their propensity to prescribe these medications.

OBJECTIVE

To identify PCP groups based on their propensity to prescribe benzodiazepines, opioids, PPIs, and antibiotics, and patient and PCP characteristics associated with identified prescribing patterns.

DESIGN

Retrospective cohort study using VA data and latent class regression analyses to identify prescribing patterns among PCPs and examine the association of patient and PCP characteristics with class membership.

PARTICIPANTS

A total of 2524 full-time PCPs and their patient panels (n = 2,939,636 patients), from January 1, 2017, to December 31, 2018.

MAIN MEASURES

We categorized PCPs based on prescribing volume quartiles for the four drug classes, based on total days' supply dispensed of each medication by the PCP to their patients (expressed as days' supply per 1000 panel patient-days). We used latent class analysis to group PCPs based on prescribing and used multinomial logistic regression to examine patient and PCP characteristics associated with latent class membership.

KEY RESULTS

PCPs were categorized into four groups (latent classes): low intensity (23% of cohort), medium-intensity overall/high-intensity PPI (36%), medium-intensity overall/high-intensity opioid (20%), and high intensity (21%). PCPs in the high-intensity group were predominantly in the highest quartile of prescribers for all four drugs (68% in the highest quartile for benzodiazepine, 86% opioids, 64% PPIs, 62% antibiotics). High-intensity PCPs (vs. low intensity) were substantially less likely to be female (OR: 0.30, 95% CI: 0.21-0.42) or practice in the northeast versus other census regions (OR: 0.10, 95% CI: 0.06-0.17).

CONCLUSIONS

VA PCPs can be classified into four clearly differentiated groups based on their prescribing of benzodiazepines, opioids, PPIs, and antibiotics, suggesting an underlying typology of prescribing. High-intensity PCPs were more likely to be male.

Development and Usability Testing of the Agency for Healthcare Research and Quality Common Formats to Capture Diagnostic Safety Events

OBJECTIVES

A lack of consensus around definitions and reporting standards for diagnostic errors limits the extent to which healthcare organizations can aggregate, analyze, share, and learn from these events. In response to this problem, the Agency for Healthcare Research and Quality (AHRQ) began the development of the Common Formats for Event Reporting for Diagnostic Safety Events (CFER-DS). We conducted a usability assessment of the draft CFER-DS to inform future revision and implementation.

METHODS

We recruited a purposive sample of quality and safety personnel working in 8 U.S. healthcare organizations. Participants were invited to use the CFER-DS to simulate reporting for a minimum of 5 cases of diagnostic safety events and then provide written and verbal qualitative feedback. Analysis focused on participants' perceptions of content validity, ease of use, and potential for implementation.

RESULTS

Estimated completion time was 30 to 90 minutes per event. Participants shared generally positive feedback about content coverage and item clarity but identified reporter burden as a potential concern. Participants also identified opportunities to clarify several conceptual definitions, ensure applicability across different care settings, and develop guidance to operationalize use of CFER-DS. Findings led to refinement of content and supplementary materials to facilitate implementation.

CONCLUSIONS

Standardized definitions of diagnostic safety events and reporting standards for contextual information and contributing factors can help capture and analyze diagnostic safety events. In addition to usability testing, additional feedback from the field will ensure that AHRQ's CFER-DS is useful to a broad range of users for learning and safety improvement.

Analysis of Radiology Report Recommendation Characteristics and Rate of Recommended Action Performance

IMPORTANCE

Following up on recommendations from radiologic findings is important for patient care, but frequently there are failures to carry out these recommendations. The lack of reliable systems to characterize and track completion of actionable radiology report recommendations poses an important patient safety challenge.

OBJECTIVES

To characterize actionable radiology recommendations and, using this taxonomy, track and understand rates of loop closure for radiology recommendations in a primary care setting.

DESIGN, SETTING, AND PARTICIPANTS

Radiology reports in a primary care clinic at a large academic center were redesigned to include actionable recommendations in a separate dedicated field. Manual review of all reports generated from imaging tests ordered between January 1 and December 31, 2018, by primary care physicians that contained actionable recommendations was performed. For this quality improvement study, a taxonomy system that conceptualized recommendations was developed based on 3 domains: (1) what is recommended (eg, repeat a test or perform a different test, specialty referral), (2) specified time frame in which to perform the recommended action, and (3) contingency language qualifying the recommendation. Using this framework, a 2-stage process was used to review patients' records to classify recommendations and determine loop closure rates and factors associated with failure to complete recommended actions. Data analysis was conducted from April to July 2021.

MAIN OUTCOMES AND MEASURES

Radiology recommendations, time frames, and contingencies. Rates of carrying out vs not closing the loop on these recommendations in the recommended time frame were assessed.

RESULTS

A total of 598 radiology reports were identified with structured recommendations: 462 for additional or future radiologic studies and 196 for nonradiologic actions (119 specialty referrals, 47 invasive procedures, and 43 other actions). The overall rate of completed actions (loop closure) within the recommended time frame was 87.4%, with 31 open loop cases rated by quality expert reviewers to pose substantial clinical risks. Factors associated with successful loop closure included (1) absence of accompanying contingency language, (2) shorter recommended time frames, and (3) evidence of direct radiologist communication with the ordering primary care physicians. A clinically significant lack of loop closure was found in approximately 5% of cases.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that creating structured radiology reports featuring a dedicated recommendations field permits the development of taxonomy to classify such recommendations and determine whether they were carried out. The lack of loop closure suggests the need for more reliable systems.

Characteristics of Disease-Specific and Generic Diagnostic Pitfalls: A Qualitative Study

IMPORTANCE

Progress in understanding and preventing diagnostic errors has been modest. New approaches are needed to help clinicians anticipate and prevent such errors. Delineating recurring diagnostic pitfalls holds potential for conceptual and practical ways for improvement.

OBJECTIVES

To develop the construct and collect examples of "diagnostic pitfalls," defined as clinical situations and scenarios vulnerable to errors that may lead to missed, delayed, or wrong diagnoses.

DESIGN, SETTING, AND PARTICIPANTS

This qualitative study used data from January 1, 2004, to December 31, 2016, from retrospective analysis of diagnosis-related patient safety incident reports, closed malpractice claims, and ambulatory morbidity and mortality conferences, as well as specialty focus groups. Data analyses were conducted between January 1, 2017, and December 31, 2019.

MAIN OUTCOMES AND MEASURES

From each data source, potential diagnostic error cases were identified, and the following information was extracted: erroneous and correct diagnoses, presenting signs and symptoms, and areas of breakdowns in the diagnostic process (using Diagnosis Error Evaluation and Research and Reliable Diagnosis Challenges taxonomies). From this compilation, examples were collected of disease-specific pitfalls; this list was used to conduct a qualitative analysis of emerging themes to derive a generic taxonomy of diagnostic pitfalls.

RESULTS

A total of 836 relevant cases were identified among 4325 patient safety incident reports, 403 closed malpractice claims, 24 ambulatory morbidity and mortality conferences, and 355 focus groups responses. From these, 661 disease-specific diagnostic pitfalls were identified. A qualitative review of these disease-specific pitfalls identified 21 generic diagnostic pitfalls categories, which included mistaking one disease for another disease (eg, aortic dissection is misdiagnosed as acute myocardial infarction), failure to appreciate test result limitations, and atypical disease presentations.

CONCLUSIONS AND RELEVANCE

Recurring types of pitfalls were identified and collected from diagnostic error cases. Clinicians could benefit from knowledge of both disease-specific and generic cross-cutting pitfalls. Study findings can potentially inform educational and quality improvement efforts to anticipate and prevent future errors.

Evaluating a patient safety learning laboratory to create an interdisciplinary ecosystem for health care innovation

BACKGROUND

In response to the complexity, challenges, and slow pace of innovation, health care organizations are adopting interdisciplinary team approaches. Systems engineering, which is oriented to creating new, scalable processes that perform with higher reliability and lower costs, holds promise for driving innovation in the face of challenges to team performance. A patient safety learning laboratory (lab) can be an essential aspect of fostering interdisciplinary team innovation across multiple projects and organizations by creating an ecosystem focused on deploying systems engineering methods to accomplish process redesign.

PURPOSE

We sought to identify the role and activities of a learning ecosystem that support interdisciplinary team innovation through evaluation of a patient safety learning lab.

METHODS

Our study included three participating learning lab project teams. We applied a mixed-methods approach using a convergent design that combined data from qualitative interviews of team members conducted as teams neared the completion of their redesign projects, as well as evaluation questionnaires administered throughout the 4-year learning lab.

RESULTS

Our results build on learning theories by showing that successful learning ecosystems continually create alignment between interdisciplinary teams' activities, organizational context, and innovation project objectives. The study identified four types of alignment, interpersonal/interprofessional, informational, structural, and processual, and supporting activities for alignment to occur.

CONCLUSION

Interdisciplinary learning ecosystems have the potential to foster health care improvement and innovation through alignment of team activities, project goals, and organizational contexts.

PRACTICE IMPLICATIONS

This study applies to interdisciplinary teams tackling multilevel system challenges in their health care organization and suggests that the work of such teams benefits from the four types of alignment. Alignment on all four dimensions may yield best results.

Indication alerts to improve problem list documentation

BACKGROUND

Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication.

METHODS

We analyzed medication orders from 2 healthcare systems that used an innovative indication alert. We collected data at site 1 between December 2018 and January 2020, and at site 2 between May and June 2021. We reviewed random samples of 100 charts from each site that had problems added in response to the alert. Outcomes were: (1) alert yield, the proportion of triggered alerts that led to a problem added and (2) problem accuracy, the proportion of problems placed that were accurate by chart review.

RESULTS

Alerts were triggered 131 134, and 6178 times at sites 1 and 2, respectively, resulting in a yield of 109 055 (83.2%) and 2874 (46.5%), P< .001. Orders were abandoned, for example, not completed, in 11.1% and 9.6% of orders, respectively, P<.001. Of the 100 sample problems, reviewers deemed 88% ± 3% and 91% ± 3% to be accurate, respectively, P = .65, with a mean of 90% ± 2%.

CONCLUSIONS

Indication alerts triggered by medication orders initiated in the absence of a justifying diagnosis were useful for populating problem lists, with yields of 83.2% and 46.5% at 2 healthcare systems. Problems were placed with a reasonable level of accuracy, with 90% ± 2% of problems deemed accurate based on chart review.

Patient engagement in system redesign teams: a process of social identity

PURPOSE

Studies demonstrate how patient roles in system redesign teams reflect a continuum of involvement and influence. This research shows the process by which patients move through this continuum and effectively engage within redesign projects.

DESIGN/METHODOLOGY/APPROACH

The authors studied members of redesign teams, consisting of 5-10 members: clinicians, systems engineers, health system staff and patient(s), from three health systems working on separate projects in a patient safety learning lab. Weekly team meetings were observed, January 2016-April 2018, 17 semi-structured interviews were conducted and findings through a patient focus group were refined. Grounded theory was used to analyze field notes and transcripts.

FINDINGS

Results show how the social identity process enables patients to move through stages in a patient engagement continuum (informant, partner and active change agent). Initially, patient and team member perceptions of the patient's role influence their respective behaviors (activating, directing, framing and sharing). Subsequently, patient and team member behaviors influence patient contributions on the team, which can redefine patient and team member perceptions of the patient's role.

ORIGINALITY/VALUE

As health systems grow increasingly complex and become more interested in responding to patient expectations, understanding how to effectively engage patients on redesign teams gains importance. This research investigates how and why patient engagement on redesign teams changes over time and what makes different types of patient roles valuable for team objectives. Findings have implications for how redesign teams can better prepare, anticipate and support the changing role of engaged patients.

Systems Analysis of a Dedicated Ambulatory Respiratory Unit for Seeing and Ensuring Follow-up of Patients With COVID-19 Symptoms

COVID-19 necessitated significant care redesign, including new ambulatory workflows to handle surge volumes, protect patients and staff, and ensure timely reliable care. Opportunities also exist to harvest lessons from workflow innovations to benefit routine care. We describe a dedicated COVID-19 ambulatory unit for closing testing and follow-up loops characterized by standardized workflows and electronic communication, documentation, and order placement. More than 85% of follow-ups were completed within 24 hours, with no observed staff, nor patient infections associated with unit operations. Identified issues include role confusion, staffing and gatekeeping bottlenecks, and patient reluctance to visit in person or discuss concerns with phone screeners.

Laboratory-Generated Urine Toxicology Interpretations: A Mixed Methods Study

BACKGROUND

Clinicians frequently order urine drug testing (UDT) for patients on chronic opioid therapy (COT), yet often have difficulty interpreting test results accurately.

OBJECTIVES

To evaluate the implementation and effectiveness of a laboratory-generated urine toxicology interpretation service for clinicians prescribing COT.

STUDY DESIGN

Type II hybrid-convergent mixed methods design (implementation) and pre-post prospective cohort study with matched controls (effectiveness).

SETTING

Four ambulatory sites (2 primary care, 1 pain management, 1 palliative care) within 2 US academic medical institutions.

METHODS

Interpretative reports were generated by the clinical chemistry laboratory and were provided to UDT ordering providers via inbox message in the electronic health record (EHR). The Partners Institutional Review Board approved this study.Participants were primary care, pain management, and palliative care clinicians who ordered liquid chromatography-mass spectrometry UDT for COT patients in clinic. Intervention was a laboratory-generated interpretation service that provided an individualized interpretive report of UDT results based on the patient's prescribed medications and toxicology metabolites for clinicians who received the intervention (n = 8) versus matched controls (n = 18).Implementation results included focus group and survey feedback on the interpretation service's usability and its impact on workflow, clinical decision making, clinician-patient relationships, and interdisciplinary teamwork. Effectiveness outcomes included UDT interpretation concordance between the clinician and laboratory, documentation frequency of UDT results interpretation and communication of results to patients, and clinician prescribing behavior at follow-up.

RESULTS

Among the 8 intervention clinicians (median age 58 [IQR 16.5] years; 2 women [25%]) on a Likert scale from 1 ("strongly disagree") to 5 ("strongly agree"), 7 clinicians reported at 6 months postintervention that the interpretation service was easy to use (mean 5 [standard deviation {SD}, 0]); improved results comprehension (mean 5 [SD, 0]); and helped them interpret results more accurately (mean 5 [SD, 0]), quickly (mean 4.67 [SD, 0.52]), and confidently (mean 4.83 [SD, 0.41]). Although there were no statistically significant differences in outcomes between cohorts, clinician-laboratory interpretation concordance trended toward improvement (intervention 22/32 [68.8%] to 29/33 [87.9%] vs. control 21/25 [84%] to 23/30 [76.7%], P = 0.07) among cases with documented interpretations.

LIMITATIONS

This study has a low sample size and was conducted at 2 large academic medical institutions and may not be generalizable to community settings.

CONCLUSIONS

Interpretations were well received by clinicians but did not significantly improve laboratory-clinician interpretation concordance, interpretation documentation frequency, or opioid-prescribing behavior.

How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions

PURPOSE

To examine the extent to which outpatient clinicians currently document drug indications in prescription instructions.

METHODS

Free-text sigs were extracted from all outpatient prescriptions generated by the computerized prescriber order entry system of a major academic institution during a 5-year period. Natural language processing was used to identify drug indications. The data set was analyzed to determine the rates at which prescribers included indications. It was stratified by provider specialty, drug class, and specific medications, to determine how often these indications were in prescriptions for as-needed (PRN) versus non-PRN medications.

RESULTS

During the study period, 4,356,086 prescriptions were ordered. Indications were included in 322,961 orders (7.41%). From these orders, 249,262 indications (77.18%) were written for PRN orders. Although internal medicine prescribers generated the highest number of medication orders, they included indications in only 6.26% of their prescriptions, whereas orthopedic surgery providers had the highest rate of documenting indications (33.41%). Pain was the most common indication, accounting for 30.35% of all documented indications. The drug class with the highest number of sigs-containing indications was narcotic analgesics. Non-PRN chronic medication prescriptions rarely included the indication.

CONCLUSION

Prescribers rarely included drug indications in electronic free-text prescription instructions, and, when they did, it was mostly for PRN uses such as pain.

Provider Misinterpretation, Documentation, and Follow-Up of Definitive Urine Drug Testing Results

BACKGROUND

Urine drug testing (UDT) is an essential tool to monitor opioid misuse among patients on chronic opioid therapy. Inaccurate interpretation of UDT can have deleterious consequences. Providers' ability to accurately interpret and document UDT, particularly definitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) results, has not been widely studied.

OBJECTIVE

To examine whether providers correctly interpret, document, and communicate LC-MS/MS UDT results.

DESIGN

This is a retrospective chart review of 160 UDT results (80 aberrant; 80 non-aberrant) between August 2017 and February 2018 from 5 ambulatory clinics (3 primary care, 1 oncology, 1 pain management). Aberrant results were classified into one or more of the following categories: illicit drug use, simulated compliance, not taking prescribed medication, and taking a medication not prescribed. Accurate result interpretation was defined as concordance between the provider's documented interpretation and an expert laboratory toxicologist's interpretation. Outcome measures were concordance between provider and laboratory interpretation of UDT results, documentation of UDT results, results acknowledgement in the electronic health record, communication of results to the patient, and rate of prescription refills.

KEY RESULTS

Aberrant results were most frequently due to illicit drug use. Overall, only 88 of the 160 (55%) had any documented provider interpretations of which 25/88 (28%) were discordant with the laboratory toxicologist's interpretation. Thirty-six of the 160 (23%) documented communication of the results to the patient. Communicating results was more likely to be documented if the results were aberrant compared with non-aberrant (33/80 [41%] vs. 3/80 [4%], p < 0.001). In all cases where provider interpretations were discordant with the laboratory interpretation, prescriptions were refilled.

CONCLUSIONS

Erroneous provider interpretation of UDT results, infrequent documentation of interpretation, lack of communication of results to patients, and prescription refills despite inaccurate interpretations are common. Expert assistance with urine toxicology interpretations may be needed to improve provider accuracy when interpreting toxicology results.

Missed diagnosis of cancer in primary care: Insights from malpractice claims data

BACKGROUND

In the ambulatory setting, missed cancer diagnoses are leading contributors to patient harm and malpractice risk; however, there are limited data on the malpractice case characteristics for these cases.

OBJECTIVE

The aim of this study was to examine key features and factors identified in missed cancer diagnosis malpractice claims filed related to primary care and evaluate predictors of clinical and claim outcomes.

METHODS

We analyzed 2155 diagnostic error closed malpractice claims in outpatient general medicine. We created multivariate models to determine factors that predicted case outcomes.

RESULTS

Missed cancer diagnoses represented 980 (46%) cases of primary care diagnostic errors, most commonly from lung, colorectal, prostate, or breast cancer. The majority (76%) involved errors in clinical judgment, such as a failure or delay in ordering a diagnostic test (51%) or failure or delay in obtaining a consult or referral (37%). These factors were independently associated with higher-severity patient harm. The majority of these errors were of high severity (85%).

CONCLUSIONS

Malpractice claims involving missed diagnoses of cancer in primary care most often involve routine screening examinations or delays in testing or referral. Our findings suggest that more reliable closed-loop systems for diagnostic testing and referrals are crucial for preventing diagnostic errors in the ambulatory setting.

Effect of Restriction of the Number of Concurrently Open Records in an Electronic Health Record on Wrong-Patient Order Errors: A Randomized Clinical Trial

IMPORTANCE

Recommendations in the United States suggest limiting the number of patient records displayed in an electronic health record (EHR) to 1 at a time, although little evidence supports this recommendation.

OBJECTIVE

To assess the risk of wrong-patient orders in an EHR configuration limiting clinicians to 1 record vs allowing up to 4 records opened concurrently.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial included 3356 clinicians at a large health system in New York and was conducted from October 2015 to April 2017 in emergency department, inpatient, and outpatient settings.

INTERVENTIONS

Clinicians were randomly assigned in a 1:1 ratio to an EHR configuration limiting to 1 patient record open at a time (restricted; n = 1669) or allowing up to 4 records open concurrently (unrestricted; n = 1687).

MAIN OUTCOMES AND MEASURES

The unit of analysis was the order session, a series of orders placed by a clinician for a single patient. The primary outcome was order sessions that included 1 or more wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder measure (an electronic query that identifies orders placed for a patient, retracted, and then reordered shortly thereafter by the same clinician for a different patient).

RESULTS

Among the 3356 clinicians who were randomized (mean [SD] age, 43.1 [12.5] years; mean [SD] experience at study site, 6.5 [6.0] years; 1894 females [56.4%]), all provided order data and were included in the analysis. The study included 12 140 298 orders, in 4 486 631 order sessions, placed for 543 490 patients. There was no significant difference in wrong-patient order sessions per 100 000 in the restricted vs unrestricted group, respectively, overall (90.7 vs 88.0; odds ratio [OR], 1.03 [95% CI, 0.90-1.20]; P = .60) or in any setting (ED: 157.8 vs 161.3, OR, 1.00 [95% CI, 0.83-1.20], P = .96; inpatient: 185.6 vs 185.1, OR, 0.99 [95% CI, 0.89-1.11]; P = .86; or outpatient: 7.9 vs 8.2, OR, 0.94 [95% CI, 0.70-1.28], P = .71). The effect did not differ among settings (P for interaction = .99). In the unrestricted group overall, 66.2% of the order sessions were completed with 1 record open, including 34.5% of ED, 53.7% of inpatient, and 83.4% of outpatient order sessions.

CONCLUSIONS AND RELEVANCE

A strategy that limited clinicians to 1 EHR patient record open compared with a strategy that allowed up to 4 records open concurrently did not reduce the proportion of wrong-patient order errors. However, clinicians in the unrestricted group placed most orders with a single record open, limiting the power of the study to determine whether reducing the number of records open when placing orders reduces the risk of wrong-patient order errors.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT02876588.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

IMPORTANCE

The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed.

OBJECTIVE

To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017.

MAIN OUTCOMES AND MEASURES

Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors.

RESULTS

Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype.

CONCLUSIONS AND RELEVANCE

Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.

Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record

BACKGROUND

Drug-drug interaction (DDI) alerts in electronic health records (EHRs) can help prevent adverse drug events, but such alerts are frequently overridden, raising concerns about their clinical usefulness and contribution to alert fatigue.

OBJECTIVE

To study the effect of conversion to a commercial EHR on DDI alert and acceptance rates.

DESIGN

Two before-and-after studies.

PARTICIPANTS

3277 clinicians who received a DDI alert in the outpatient setting.

INTERVENTION

Introduction of a new, commercial EHR and subsequent adjustment of DDI alerting criteria.

MAIN MEASURES

Alert burden and proportion of alerts accepted.

KEY RESULTS

Overall interruptive DDI alert burden increased by a factor of 6 from the legacy EHR to the commercial EHR. The acceptance rate for the most severe alerts fell from 100 to 8.4%, and from 29.3 to 7.5% for medium severity alerts (P < 0.001). After disabling the least severe alerts, total DDI alert burden fell by 50.5%, and acceptance of Tier 1 alerts rose from 9.1 to 12.7% (P < 0.01).

CONCLUSIONS

Changing from a highly tailored DDI alerting system to a more general one as part of an EHR conversion decreased acceptance of DDI alerts and increased alert burden on users. The decrease in acceptance rates cannot be fully explained by differences in the clinical knowledge base, nor can it be fully explained by alert fatigue associated with increased alert burden. Instead, workflow factors probably predominate, including timing of alerts in the prescribing process, lack of differentiation of more and less severe alerts, and features of how users interact with alerts.

Using drug knowledgebase information to distinguish between look-alike-sound-alike drugs

Objective

To extract drug indications from a commercial drug knowledgebase and determine to what extent drug indications can discriminate between look-alike-sound-alike (LASA) drugs.

Methods

We extracted drug indications disease concepts from the MedKnowledge Indications module from First Databank Inc. (South San Francisco, CA) and associated them with drugs on the Institute for Safe Medication Practices (ISMP) list of commonly confused drug names. We used high-level concepts (rather than granular concepts) to represent the general indications for each drug. Two pharmacists reviewed each drug's association with its high-level indications concepts for accuracy and clinical relevance. We compared the high-level indications for each commonly confused drug pair and categorized each pair as having a complete overlap, partial overlap or no overlap in high-level indications.

Results

Of 278 LASA drug pairs, 165 (59%) had no overlap and 58 (21%) had partial overlap in high-level indications. Fifty-five pairs (20%) had complete overlap in high-level indications; nearly half of these were comprised of drugs with the same active ingredient and route of administration (e.g., Adderall, Adderall XR).

Conclusions

Drug indications data from a drug knowledgebase can discriminate between many LASA drugs.

Computerized prescriber order entry-related patient safety reports: analysis of 2522 medication errors

Objective

To examine medication errors potentially related to computerized prescriber order entry (CPOE) and refine a previously published taxonomy to classify them.

Materials and Methods

We reviewed all patient safety medication reports that occurred in the medication ordering phase from 6 sites participating in a United States Food and Drug Administration-sponsored project examining CPOE safety. Two pharmacists independently reviewed each report to confirm whether the error occurred in the ordering/prescribing phase and was related to CPOE. For those related to CPOE, we assessed whether CPOE facilitated (actively contributed to) the error or failed to prevent the error (did not directly cause it, but optimal systems could have potentially prevented it). A previously developed taxonomy was iteratively refined to classify the reports.

Results

Of 2522 medication error reports, 1308 (51.9%) were related to CPOE. Of these, CPOE facilitated the error in 171 (13.1%) and potentially could have prevented the error in 1137 (86.9%). The most frequent categories of "what happened to the patient" were delays in medication reaching the patient, potentially receiving duplicate drugs, or receiving a higher dose than indicated. The most frequent categories for "what happened in CPOE" included orders not routed to or received at the intended location, wrong dose ordered, and duplicate orders. Variations were seen in the format, categorization, and quality of reports, resulting in error causation being assignable in only 403 instances (31%).

Discussion and Conclusion

Errors related to CPOE commonly involved transmission errors, erroneous dosing, and duplicate orders. More standardized safety reporting using a common taxonomy could help health care systems and vendors learn and implement prevention strategies.

Screening for medication errors using an outlier detection system

Objective

The study objective was to evaluate the accuracy, validity, and clinical usefulness of medication error alerts generated by an alerting system using outlier detection screening.

Materials and Methods

Five years of clinical data were extracted from an electronic health record system for 747 985 patients who had at least one visit during 2012-2013 at practices affiliated with 2 academic medical centers. Data were screened using the system to detect outliers suggestive of potential medication errors. A sample of 300 charts was selected for review from the 15 693 alerts generated. A coding system was developed and codes assigned based on chart review to reflect the accuracy, validity, and clinical value of the alerts.

Results

Three-quarters of the chart-reviewed alerts generated by the screening system were found to be valid in which potential medication errors were identified. Of these valid alerts, the majority (75.0%) were found to be clinically useful in flagging potential medication errors or issues.

Discussion

A clinical decision support (CDS) system that used a probabilistic, machine-learning approach based on statistically derived outliers to detect medication errors generated potentially useful alerts with a modest rate of false positives. The performance of such a surveillance and alerting system is critically dependent on the quality and completeness of the underlying data.

Conclusion

The screening system was able to generate alerts that might otherwise be missed with existing CDS systems and did so with a reasonably high degree of alert usefulness when subjected to review of patients' clinical contexts and details.

What do Australian consumers, pharmacists and prescribers think about documenting indications on prescriptions and dispensed medicines labels?: A qualitative study

BACKGROUND

Documenting the indication on prescriptions and dispensed medicines labels is not standard practice in Australia. However, previous studies that have focused on the content and design of dispensed medicines labels, have suggested including the indication as a safety measure. The aim of this study was to investigate the perspectives of Australian consumers, pharmacists and prescribers on documenting the indication on prescriptions and dispensed medicines labels.

METHODS

Semi-structured interviews were conducted and mock-up of dispensed medicines labels were designed for participants. Consumers (n = 19) and pharmacists (n = 7) were recruited by convenience sample at community pharmacies in Sydney (Australia) and prescribers (n = 8), including two medical students, were recruited through snowballing.

RESULTS

Thirty-four participants were interviewed. Most participants agreed that documenting the indication would be beneficial especially for patients who are forgetful or take multiple medications. Participants also believed it would improve consumers' medication understanding and adherence. Prescribers and pharmacists believed it could help reduce prescribing and dispensing errors by matching the drug/dosage to the correct indication. Prescribers refrained from documenting the indication to protect patients' privacy; however, most patients did not consider documenting the indication as a breach of privacy. Prescribers raised concerns about the extra time to include indications on prescriptions and best language to document indications, using plain language as opposed to medical terminology.

CONCLUSIONS

All interviewed stakeholders identified numerous benefits of documenting the indication on prescriptions and dispensed medicines labels. Whether these potential benefits can be realized remains unknown and addressing prescribers' concern regarding the time involved in documenting the indication on prescriptions remains a challenge for vendors of electronic medication management systems.

A national survey assessing the number of records allowed open in electronic health records at hospitals and ambulatory sites

To reduce the risk of wrong-patient errors, safety experts recommend limiting the number of patient records providers can open at once in electronic health records (EHRs). However, it is unknown whether health care organizations follow this recommendation or what rationales drive their decisions. To address this gap, we conducted an electronic survey via 2 national listservs. Among 167 inpatient and outpatient study facilities using EHR systems designed to open multiple records at once, 44.3% were configured to allow ≥3 records open at once (unrestricted), 38.3% allowed only 1 record open (restricted), and 17.4% allowed 2 records open (hedged). Decision-making centered on efforts to balance safety and efficiency, but there was disagreement among organizations about how to achieve that balance. Results demonstrate no consensus on the number of records to be allowed open at once in EHRs. Rigorous studies are needed to determine the optimal number of records that balances safety and efficiency.

Learning from errors: analysis of medication order voiding in CPOE systems

OBJECTIVE

Medication order voiding allows clinicians to indicate that an existing order was placed in error. We explored whether the order voiding function could be used to record and study medication ordering errors.

MATERIALS AND METHODS

We examined medication orders from an academic medical center for a 6-year period (2006-2011; n  = 5 804 150). We categorized orders based on status (void, not void) and clinician-provided reasons for voiding. We used multivariable logistic regression to investigate the association between order voiding and clinician, patient, and order characteristics. We conducted chart reviews on a random sample of voided orders ( n  = 198) to investigate the rate of medication ordering errors among voided orders, and the accuracy of clinician-provided reasons for voiding.

RESULTS

We found that 0.49% of all orders were voided. Order voiding was associated with clinician type (physician, pharmacist, nurse, student, other) and order type (inpatient, prescription, home medications by history). An estimated 70 ± 10% of voided orders were due to medication ordering errors. Clinician-provided reasons for voiding were reasonably predictive of the actual cause of error for duplicate orders (72%), but not for other reasons.

DISCUSSION AND CONCLUSION

Medication safety initiatives require availability of error data to create repositories for learning and training. The voiding function is available in several electronic health record systems, so order voiding could provide a low-effort mechanism for self-reporting of medication ordering errors. Additional clinician training could help increase the quality of such reporting.

Primary Care Collaboration to Improve Diagnosis and Screening for Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer death, reducible by screening and early diagnosis, yet many patients fail to receive recommended screening. As part of an academic improvement collaborative, 25 primary care practices worked to improve CRC screening and diagnosis.

METHODS

The project featured triannual learning sessions, monthly conference calls, practice coach support, and monthly reporting. The project phases included literature review and interviews with national leaders/organizations, development of driver diagrams to identify key factors and change ideas, project launch and practice team planning, and a practice improvement phase.

RESULTS

The project activities included (1) inventory of barriers and best practices, (2) driver diagram to drive improvements, (3) list of changes to try, (4) compilation of lessons learned, and (5) five key changes to optimize screening and follow-up. Practices leveraged prior transformation efforts to track patients for screening and follow-up during and between office visits. By mapping processes, testing changes, and collecting data, sites targeted opportunities to improve quality, safety, efficiency, and patient and care team experience. Successful change interventions centered around partnering with gastroenterology, engaging leadership, leveraging registries and health information technology, promoting alternative screening options, and partnering with and supporting patients. Several practices achieved improvement in screening rates, while others demonstrated no change from baseline during the 10-month testing and implementation phase (July 2014-April 2015).

CONCLUSION

The collaborative effectively engaged teams in a broad set of process improvements with key lessons learned related to barriers, information technology challenges, outreach challenges/strategies, and importance of stakeholder and patient engagement.

The global burden of diagnostic errors in primary care

Diagnosis is one of the most important tasks performed by primary care physicians. The World Health Organization (WHO) recently prioritized patient safety areas in primary care, and included diagnostic errors as a high-priority problem. In addition, a recent report from the Institute of Medicine in the USA, 'Improving Diagnosis in Health Care', concluded that most people will likely experience a diagnostic error in their lifetime. In this narrative review, we discuss the global significance, burden and contributory factors related to diagnostic errors in primary care. We synthesize available literature to discuss the types of presenting symptoms and conditions most commonly affected. We then summarize interventions based on available data and suggest next steps to reduce the global burden of diagnostic errors. Research suggests that we are unlikely to find a 'magic bullet' and confirms the need for a multifaceted approach to understand and address the many systems and cognitive issues involved in diagnostic error. Because errors involve many common conditions and are prevalent across all countries, the WHO's leadership at a global level will be instrumental to address the problem. Based on our review, we recommend that the WHO consider bringing together primary care leaders, practicing frontline clinicians, safety experts, policymakers, the health IT community, medical education and accreditation organizations, researchers from multiple disciplines, patient advocates, and funding bodies among others, to address the many common challenges and opportunities to reduce diagnostic error. This could lead to prioritization of practice changes needed to improve primary care as well as setting research priorities for intervention development to reduce diagnostic error.

Sick Children Crying for Help: Fostering Adverse Event Reports

In a Perspective, Gordon Schiff discusses the importance of appropriately analyzing adverse event reports.