Measures to Improve Diagnostic Safety in Clinical Practice

Exploring diagnostic events and first referrals in cancer patient pathways in primary care. A questionnaire survey

BACKGROUND

Cancer diagnostic pathways in general practice are often nonlinear, and several events can delay timely diagnosis.

OBJECTIVES

To explore cancer diagnostic processes in general practice, examining how patients' symptom presentations, sex, and age are associated with the occurrence of predefined potentially delaying events and the first referrals.

METHOD

General practices in 3 Danish Regions were invited to participate in a questionnaire survey, addressing patient's symptom presentation, diagnostic process events, and first referral. The general practitioners (GPs) received a list of their incident cancer patients from the preceding 2 years.

RESULTS

In total 187 general practices participated, including 5,908 patients with the cancer diagnostic pathways initiated in general practice. Presenting with nonspecific symptoms was associated with potentially delaying events, even when the patient also had specific symptoms. Almost half of the patients were referred to a cancer patient pathway (CPP) first, men more often than women, and 10% were referred for acute hospitalization. In 23% of the diagnostic processes, GPs initially treated or referred patients on suspicion of another disease rather than cancer and waited due to normal examinations in 1 out of 20 patients. Excluding sex-specific cancers, these 2 events were more prevalent in women. Men less often complied to the follow-up agreement. Younger patients were less often first referred to a CPP and together with older patients more often first acutely hospitalized.

CONCLUSION

In cancer diagnostic processes in general practice, first referrals and the occurrence of potentially delaying events are associated with the patient's age, sex, and specificity of symptoms.

The PRIDx framework to engage payers in reducing diagnostic errors in healthcare

OBJECTIVES

No framework currently exists to guide how payers and providers can collaboratively develop and implement incentives to improve diagnostic safety. We conducted a literature review and interviews with subject matter experts to develop a multi-component 'Payer Relationships for Improving Diagnoses (PRIDx)' framework, that could be used to engage payers in diagnostic safety efforts.

CONTENT

The PRIDx framework, 1) conceptualizes diagnostic safety links to care provision, 2) illustrates ways to promote payer and provider engagement in the design and adoption of accountability mechanisms, and 3) explicates the use of data analytics. Certain approaches suggested by PRIDx were refined by subject matter expert interviewee perspectives.

SUMMARY

The PRIDx framework can catalyze public and private payers to take specific actions to improve diagnostic safety.

OUTLOOK

Implementation of the PRIDx framework requires new types of partnerships, including external support from public and private payer organizations, and requires creation of strong provider incentives without undermining providers' sense of professionalism and autonomy. PRIDx could help facilitate collaborative payer-provider approaches to improve diagnostic safety and generate research concepts, policy ideas, and potential innovations for engaging payers in diagnostic safety improvement activities.

Systematic comparison of variant calling pipelines of target genome sequencing cross multiple next-generation sequencers

Targeted genomic sequencing (TS) greatly benefits precision oncology by rapidly detecting genetic variations with better accuracy and sensitivity owing to its high sequencing depth. Multiple sequencing platforms and variant calling tools are available for TS, making it excruciating for researchers to choose. Therefore, benchmarking study across different platforms and pipelines available for TS is imperative. In this study, we performed a TS of Reference OncoSpan FFPE (HD832) sample enriched by TSO500 panel using four commercially available sequencers, and analyzed the output 50 datasets using five commonly-used bioinformatics pipelines. We systematically investigated the sequencing quality and variant detection sensitivity, expecting to provide optimal recommendations for future research. Four sequencing platforms returned highly concordant results in terms of base quality (Q20 > 94%), sequencing coverage (>97%) and depth (>2000×). Benchmarking revealed good concordance of variant calling across different platforms and pipelines, among which, FASTASeq 300 platform showed the highest sensitivity (100%) and precision (100%) in high-confidence variants calling when analyzed by SNVer and VarScan 2 algorithms. Furthermore, this sequencer demonstrated the shortest sequencing time (∼21 h) at the sequencing mode PE150. Through the intersection of 50 datasets generated in this study, we recommended a novel set of variant genes outside the truth set published by HD832, expecting to replenish HD832 for future research on tumor variant diagnosis. Besides, we applied these five tools to another panel (TargetSeq One) for Twist cfDNA Pan-cancer Reference Standard, comprehensive consideration of SNP and InDel sensitivity, SNVer and VarScan 2 performed best among them. Furthermore, SNVer and VarScan 2 also performed best for six cancer cell lines samples regarding SNP and InDel sensitivity. Considering the dissimilarity of variant calls across different pipelines for datasets from the same platform, we recommended an integration of multiple tools to improve variant calling sensitivity and accuracy for the cancer genome. Illumina and GeneMind technologies can be used independently or together by public health laboratories performing tumor TS. SNVer and VarScan 2 perform better regarding variant detection sensitivity for three typical tumor samples. Our study provides a standardized target sequencing resource to benchmark new bioinformatics protocols and sequencing platforms.

No knowledge gap in human physiology after remote teaching for second year medical students throughout the Covid-19 pandemic

The COVID-19 pandemic had a disruptive effect on higher education. A critical question is whether these changes affected students' learning outcomes. Knowledge gaps have consequences for future learning and may-in health professionals' education-also pose a threat to patient safety. Current research has shortcomings and does not allow for clear-cut interpretation. Our context is instruction in human physiology in an undergraduate medical program from high stakes end of term examinations. The sequence of imposed measures to slow the COVID-19 pandemic created a natural experiment, allowing for comparisons in performance during in-person versus remote instruction.In a two-factorial design, mode of instruction (in-person vs. remote) and mode of assessment (in-person vs. remote) were analyzed using both basic (non-parametric statistics, T-tests) and advanced statistical methods (linear mixed-effects model; resampling techniques). Test results from a total of N = 1095 s-year medical students were included in the study.We did not find empirical evidence of knowledge gaps; rather, students received comparable or higher scores during remote teaching. We interpret these findings as empirical evidence that both students and teachers adapted to pandemic disruption in a way that did not lead to knowledge gaps.We conclude that highly motivated students had no reduction in academic achievement. Moreover, we have developed an accessible digital exam system for secure, fair, and effective assessments which is sufficiently defensible for making pass/fail decisions.

Developing electronic clinical quality measures to assess the cancer diagnostic process

OBJECTIVE

Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance.

MATERIALS AND METHODS

We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of appropriate follow-up, and exclusions that signified follow-up was unnecessary. Clinicians reviewed 100 positive and 20 negative randomly selected records for each eCQM at each site to validate accuracy and categorized missed opportunities related to system, provider, or patient factors.

RESULTS

We implemented the CRC eCQM at both sites, while the lung cancer eCQM was only implemented at the VA due to lack of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. For the CRC eCQM, the rate of appropriate follow-up was 36.0% (26 746/74 314 patients) in the VA after removing clinical exclusions and 41.1% at Geisinger (1009/2461 patients; P < .001). Similarly, the rate of appropriate evaluation for lung cancer in the VA was 61.5% (25 166/40 924 patients). Reviewers most frequently attributed missed opportunities at both sites to provider factors (84 of 157).

CONCLUSIONS

We implemented 2 eCQMs to evaluate the diagnostic process in cancer at 2 large health systems. Health care organizations can use these eCQMs to monitor diagnostic performance related to cancer.

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.

A Metasynthesis and Meta-analysis of the Impact and Diagnostic Safety of COVID-19 Symptom Agnostic Rapid Testing in Low- and Middle-Income Countries: Protocol for a Systematic Review

BACKGROUND

Amid all public health measures to contain COVID-19, the most challenging has been how to break the transmission chain. This has been even more challenging in low- and middle-income countries (LMICs). A public health emergency warrants a public health perspective, which comes down to prevention. Rapid mass testing has been advocated throughout the pandemic as a way to promptly deal with asymptomatic infections, but its usefulness in LMICs is yet to be fully understood.

OBJECTIVE

The study objectives of this paper are to (1) investigate the impact of the different rapid mass testing options for SARS-CoV-2 that have been delivered at point of care in LMICs and (2) evaluate the diagnostic safety (accuracy) of rapid mass testing for SARS-CoV-2 in LMICs.

METHODS

This review will systematically search records in PubMed, EBSCOhost, Cochrane library, Global Index Medicus COVID-19 Register, and Scopus. Records will be managed using Mendeley reference manager and SWIFT-Review. Risk of bias for randomized controlled trials will be assessed using the RoB 2 assessment tool, while nonrandomized interventions will be assessed using the tool developed by the Evidence Project. A narrative approach will be used to synthesize data under the first objective, and either a meta-analysis or synthesis without meta-analysis for the second objective. Tables, figures, and textual descriptions will be used to present findings. The overall body of evidence for the first objective will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach, and for the second objective using GRADE.

RESULTS

The screening of records has been finalized. We hope to finalize the synthesis by the end of February 2023 and to prepare the manuscript for publication by April 2023. The study will be reported in accordance with standard guidelines for the reporting of systematic reviews. Review results will be disseminated through conferences and their peer-reviewed publication in a relevant journal.

CONCLUSIONS

This review highlights the role of a preventive approach in infection control using rapid mass testing. It also flags the overriding need to involve users and providers in the evaluation of such tests in the settings for which they are intended. This will be the first review to the best of our knowledge to generate both qualitative and quantitative evidence regarding rapid mass testing specific to LMICs.

TRIAL REGISTRATION

PROSPERO CRD42022283776; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283776.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/41132.

Creating a Safety Net Process to Improve Colon Cancer Diagnosis in Patients With Rectal Bleeding

Background Failure to follow up on patients with rectal bleeding is common and may result in a delay in diagnosis of colorectal cancer or in missing high-risk adenomas. The authors' purpose was to create an electronic patient safety net for those diagnosed with rectal bleeding but who did not have colonoscopy to ensure proper detection of colonic abnormalities, including colon cancer. Methods In an integrated health delivery system serving < 4.6 million patients in Southern California, from 2014 to 2019, the authors electronically identified patients with rectal bleeding aged 45 to 80 years but with no recently documented colonoscopy. These cases were reviewed by a gastroenterologist to determine if colonoscopy was appropriate. The physician looked for known documentation as to the cause of rectal bleeding and verified no contraindications to the procedure; if indicated, testing was offered. Results Using the authors' safety net program, 1430 patients with rectal bleeding who needed and completed a colonoscopy were identified. Of those patients, 7.5% had an advanced adenoma or cancer, with a total of 20 cancers, and 34% had findings that warranted more frequent colonoscopy. Conclusions The authors designed a safety net system that was able to capture information on patients with rectal bleeding who had not had a colonoscopy and detected in 34% colonic pathology that would have otherwise gone undetected. The program did not require many resources to implement and had the ability to potentially prevent harm from reaching patients whose rectal bleeding did not get prompt workup. Other health systems and practices should consider implementing a similar system.

Creating a Learning Health System for Improving Diagnostic Safety: Pragmatic Insights from US Health Care Organizations

OBJECTIVE

To identify challenges and pragmatic strategies for improving diagnostic safety at an organizational level using concepts from learning health systems METHODS: We interviewed 32 safety leaders across the USA on how their organizations approach diagnostic safety. Participants were recruited through email and represented geographically diverse academic and non-academic settings. The interview included questions on culture of reporting and learning from diagnostic errors; data gathering and analysis activities; diagnostic training and educational activities; and engagement of clinical leadership, staff, patients, and families in diagnostic safety activities. We conducted an inductive content analysis of interview transcripts and two reviewers coded all data.

RESULTS

Of 32 participants, 12 reported having a specific program to address diagnostic errors. Multiple barriers to implement diagnostic safety activities emerged: serious concerns about psychological safety associated with diagnostic error; lack of infrastructure for measurement, monitoring, and improvement activities related to diagnosis; lack of leadership investment, which was often diverted to competing priorities related to publicly reported measures or other incentives; and lack of dedicated teams to work on diagnostic safety. Participants provided several strategies to overcome barriers including adapting trigger tools to identify safety events, engaging patients in diagnostic safety, and appointing dedicated diagnostic safety champions.

CONCLUSIONS

Several foundational building blocks related to learning health systems could inform organizational efforts to reduce diagnostic error. Promoting an organizational culture specific to diagnostic safety, using science and informatics to improve measurement and analysis, leadership incentives to build institutional capacity to address diagnostic errors, and patient engagement in diagnostic safety activities can enable progress.

Parallels between our response to COVID-19 and patient safety

The response to the COVID-19 pandemic and the approach to patient safety share three important concepts: the challenges of preventing rare events, use of rules, and tolerance for uncertainty. We discuss how each of these ideas can be utilised in perioperative safety to create a high-reliability system.

Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes

BACKGROUND

The 21st Century Cures Act mandates patients' access to their electronic health record (EHR) notes. To our knowledge, no previous work has systematically invited patients to proactively report diagnostic concerns while documenting and tracking their diagnostic experiences through EHR-based clinician note review.

OBJECTIVE

To test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes.

METHODS

In a large integrated health system, patients aged 18-85 years actively using the patient portal and seen between October 2019 and February 2020 were invited to respond to an online questionnaire if an EHR algorithm detected any recent unexpected return visit following an initial primary care consultation ("at-risk" visit). We developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to several dimensions of the diagnostic process based on notes review and recall of recent "at-risk" visits. Additional questions assessed patients' trust in their providers and their general feelings about the visit. The primary outcome was a self-reported diagnostic concern. Multivariate logistic regression tested whether the primary outcome was predicted by instrument variables.

RESULTS

Of 293 566 visits, the algorithm identified 1282 eligible patients, of whom 486 responded. After applying exclusion criteria, 418 patients were included in the analysis. Fifty-one patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements "the care plan the provider developed for me addressed all my medical concerns" [odds ratio (OR), 2.65; 95% confidence interval [CI], 1.45-4.87) and "I trust the provider that I saw during my visit" (OR, 2.10; 95% CI, 1.19-3.71) and agreed with the statement "I did not have a good feeling about my visit" (OR, 1.48; 95% CI, 1.09-2.01).

CONCLUSION

Patients can identify diagnostic concerns based on a proactive online structured evaluation of visit notes. This surveillance strategy could potentially improve transparency in the diagnostic process.

Harnessing Event Report Data to Identify Diagnostic Error During the COVID-19 Pandemic

INTRODUCTION

COVID-19 exposed systemic gaps with increased potential for diagnostic error. This project implemented a new approach leveraging electronic safety reporting to identify and categorize diagnostic errors during the pandemic.

METHODS

All safety event reports from March 1, 2020, to February 28, 2021, at an academic medical center were evaluated using two complementary pathways (Pathway 1: all reports with explicit mention of COVID-19; Pathway 2: all reports without explicit mention of COVID-19 where natural language processing [NLP] plus logic-based stratification was applied to identify potential cases). Cases were evaluated by manual review to identify diagnostic error/delay and categorize error type using a recently proposed classification framework of eight categories of pandemic-related diagnostic errors.

RESULTS

A total of 14,230 reports were included, with 95 (0.7%) identified as cases of diagnostic error/delay. Pathway 1 (n = 1,780 eligible reports) yielded 45 reports with diagnostic error/delay (positive predictive value [PPV] = 2.5%), of which 35.6% (16/45) were attributed to pandemic-related strain. In Pathway 2, the NLP-based algorithm flagged 110 safety reports for manual review from 12,450 eligible reports. Of these, 50 reports had diagnostic error/delay (PPV = 45.5%); 94.0% (47/50) were related to strain. Errors from all eight categories of the taxonomy were found on analysis.

CONCLUSION

An event reporting-based strategy including use of simple-NLP-identified COVID-19-related diagnostic errors/delays uncovered several safety concerns related to COVID-19. An NLP-based approach can complement traditional reporting and be used as a just-in-time monitoring system to enable early detection of emerging risks from large volumes of safety reports.

'More than words' - Interpersonal communication, cognitive bias and diagnostic errors

During the diagnostic process, clinicians may make assumptions, prematurely judge or diagnose patients based on their appearance, their speech or how they are portrayed by other clinicians. Such judgements can be a major source of diagnostic error and are often linked to unconscious cognitive biases - faulty quick-fire thinking patterns that impact clinical reasoning. Patient safety is profoundly influenced by cognitive bias and language, i.e. how information is presented or gathered, and then synthesised by clinicians to form and communicate diagnostic decisions. Here, we discuss the intricate links between interpersonal communication, cognitive bias, and diagnostic error from a patient's, a linguist's and clinician's perspective. We propose that through patient engagement and applied health communication research, we can enhance our understanding of how the interplay of communication behaviours, biases and errors can impact upon the patient experience and diagnostic error. In doing so, we provide new avenues for collaborative diagnostic error research striving towards healthcare improvements and safer diagnosis.

Diagnostic error regarding the cause of cytopenia when increasing psychotropic drugs: Two case reports

Several psychotropic drugs can cause cytopenia, especially after increasing dosages or initiating treatment. However, cytopenia in patients with psychiatric disorders can also be due to other conditions such as leukemia. In this report, we discuss two cases of cytopenia that occurred during the adjustment of psychotropic medications in patients with severe psychiatric illness. The initial diagnosis in each case was drug-induced cytopenia; however, later, the cause of cytopenia was found to be acute promyelocytic leukemia. When cytopenia is observed while increasing the dosage of psychotropic drugs, suspicious drugs should be discontinued, though the possibility that cytopenia could be due to other reasons should be considered. If there are no signs of recovering blood cells or if cytopenia is severe, psychiatrists should consult hematologists promptly.

Emotional experience of the diagnostic process of a rare disease and the perception of support systems: A scoping review

AIMS AND OBJECTIVE

To explore the experience of adult patients and adult patients' families, and their perception of the support systems received during the diagnostic process of rare diseases.

BACKGROUND

There are about 7,000 rare diseases that affect 7% of the world's population. Rare diseases are often underdiagnosed. This has been reported to have deleterious physical and psychological consequences in both the patients and their families, especially when institutional support during this process is low.

DESIGN

A scoping review was carried out following the 6-phase model proposed by Arksey & O'Malley and Levac et al., including the consultation phase in which patients diagnosed with rare diseases were interviewed to seek their views on the bibliographic evidence reviewed and their experience during the diagnostic process.

METHODS

The databases consulted were PubMed, CINAHL, Web of Science, SCOPUS, Cochrane Library, PsycINFO, OpenGrey, ProQuest Dissertations and Theses Global. They were explored from inception-July 2020, and qualitative, quantitative and mixed method studies were included. The Mixed Methods Appraisal Tool was used for the critical evaluation of the articles. The review was based on the guidance in the PRISMA-ScR statement.

RESULTS

The initial search identified 2,350 articles, of which 20 fully met the inclusion criteria and were therefore reviewed. In this analysis appeared two dimensions: internal factors: emotional aspects, and external factors: resources and support systems.

RELEVANCE TO CLINICAL

This review provides evidence on the emotional impact of the diagnostic process and during the communication phase of the definitive diagnosis. Health systems and professionals must be strengthened in order to improve the information, training and resources. Nurses can play a key role in coordinating communication and follow-up of those affected.

Overutilization and underutilization of autoantibody tests in patients with suspected autoimmune disorders

OBJECTIVES

Diagnostic Management Teams (DMTs) are one strategy for reducing diagnostic errors. This study examined errors in serology test selection after a positive antinuclear antibody (ANA) test in patients with suspected systemic autoimmune rheumatic disorder (SARD).

METHODS

This retrospective study included 246 patient cases reviewed by our ANA DMT from March to August 2019. The DMT evaluated the appropriateness of tests beyond ANA screening tests (overutilization, underutilization, or both) based on American College of Rheumatology recommendations and classified cases into diagnostic error or no error groups. Errors were quantified, and patient and provider characteristics associated with diagnostic errors were assessed.

RESULTS

Among 246 cases, 60.6% had at least one diagnostic error in test selection. The number of sub-serology tests ordered was 2.4 times higher in the diagnostic error group than in the no error group. The likelihood of at least one diagnostic error was higher in males and African American/Black patients, although the differences were not statistically significant. Providers from general internal medicine, primary care, and non-rheumatology specialties were approximately two times more likely to make diagnostic errors than rheumatology specialists.

CONCLUSIONS

Diagnostic errors in test selection after a positive ANA for patients with suspected SARD were common, although there were fewer errors when ordered by rheumatology specialists. These findings support the need to develop strategies to reduce diagnostic errors in test selection for autoimmunity evaluation and suggest that implementation of a DMT can be useful for providing guidance to clinicians to reduce overutilization and underutilization of laboratory tests.

Improving Diagnosis Through Education

Diagnosis is the cornerstone of providing safe and effective medical care. Still, diagnostic errors are all too common. A key to improving diagnosis in practice is improving diagnosis education, yet formal education about diagnosis is often lacking, idiosyncratic, and not evidence based. In this Invited Commentary, the authors describe the outcomes of a national consensus project to identify key competencies for diagnosis and the themes that emerged as part of this work. The 12 competencies the authors describe span 3 categories-individual, teamwork, and system related-and address ideal diagnostic practice for all health professionals. In addition, the authors identify strategies for improving diagnosis education, including the use of theory-based pedagogy and interprofessional approaches, the recognition of the role of the health care system to enhance or inhibit the diagnostic process, and the need to focus on the individual attributes necessary for high-quality diagnosis, such as humility and curiosity. The authors conclude by advocating for increasing and improving the assessment of individual and team-based diagnostic performance in health professions education programs.

Developing Health Care Organizations That Pursue Learning and Exploration of Diagnostic Excellence: An Action Plan

Reducing errors in diagnosis is the next big challenge for patient safety. Diagnostic safety improvement efforts should become a priority for health care organizations, payers, and accrediting bodies; however, external incentives, policies, and practical guidance to develop these efforts are largely absent. In this Perspective, the authors highlight ways in which health care organizations can pursue learning and exploration of diagnostic excellence (LEDE). Building on current evidence and their recent experiences in developing such a learning organization at Geisinger, the authors propose a 5-point action plan and corresponding policy levers to support development of LEDE organizations. These recommendations, which are applicable to many health care organizations, include (1) implementing a virtual hub to coordinate organizational activities for improving diagnosis, such as identifying risks and prioritizing interventions that cross intra-institutional silos while promoting a culture of learning and safety; (2) participating in novel scientific initiatives to generate and translate evidence, given the rapidly evolving "basic science" of diagnostic excellence; (3) avoiding the "tyranny of metrics" by focusing on measurement for improvement rather than using measures to reward or punish; (4) engaging clinicians in activities for improving diagnosis and framing missed opportunities positively as learning opportunities rather than negatively as errors; and (5) developing an accountable culture of engaging and learning from patients, who are often underexplored sources of information. The authors also outline specific policy actions to support organizations in implementing these recommendations. They suggest this action plan can stimulate scientific, practice, and policy progress needed for achieving diagnostic excellence and reducing preventable patient harm.

Operational measurement of diagnostic safety: state of the science

Reducing the incidence of diagnostic errors is increasingly a priority for government, professional, and philanthropic organizations. Several obstacles to measurement of diagnostic safety have hampered progress toward this goal. Although a coordinated national strategy to measure diagnostic safety remains an aspirational goal, recent research has yielded practical guidance for healthcare organizations to start using measurement to enhance diagnostic safety. This paper, concurrently published as an Issue Brief by the Agency for Healthcare Research and Quality, issues a "call to action" for healthcare organizations to begin measurement efforts using data sources currently available to them. Our aims are to outline the state of the science and provide practical recommendations for organizations to start identifying and learning from diagnostic errors. Whether by strategically leveraging current resources or building additional capacity for data gathering, nearly all organizations can begin their journeys to measure and reduce preventable diagnostic harm.

Patient Safety Culture, Health Information Technology Implementation, and Medical Office Problems That Could Lead to Diagnostic Error

BACKGROUND

Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment or by leading to unnecessary or harmful treatment.

OBJECTIVES

The aim of the study was to investigate the relationship between patient safety culture, health information technology (IT) implementation, and the frequency of problems that could lead to diagnostic errors in the medical office setting, such as unavailable test results, unavailable medical records, or unpursued abnormal results.

METHODS

We used survey data from 925 medical offices nationwide that voluntarily submitted results to the 2012 Agency for Healthcare Research and Quality Medical Office Surveys on Patient Safety Culture database. At the office level, we ran a multivariate regression model to estimate the effect of culture on problem frequency while controlling for office-reported implementation levels of health IT, office characteristics such as the number of locations, and survey characteristics such as the percent of respondents that were physicians.

RESULTS

The most frequent problem was "results from a lab or imaging test were not available when needed"; across 925 offices, the average was 15% reporting that it happened daily or weekly. Higher overall culture scores were significantly associated with fewer occurrences of each problem assessed. Compared with offices with completed health IT implementation, offices in the process of health IT implementation had higher frequency of problems.

CONCLUSIONS

This study offers insight into how patient safety culture and health IT implementation in medical offices can influence the frequency of breakdowns in processes of care, thereby identifying potential vulnerabilities that can increase diagnostic errors.

Pediatric Clinician Comfort Discussing Diagnostic Errors for Improving Patient Safety: A Survey

INTRODUCTION

Meaningful conversations about diagnostic errors require safety cultures where clinicians are comfortable discussing errors openly. However, clinician comfort discussing diagnostic errors publicly and barriers to these discussions remain unexplored. We compared clinicians' comfort discussing diagnostic errors to other medical errors and identified barriers to open discussion.

METHODS

Pediatric clinicians at 4 hospitals were surveyed between May and June 2018. The survey assessed respondents' comfort discussing medical errors (with varying degrees of system versus individual clinician responsibility) during morbidity and mortality conferences and privately with peers. Respondents reported the most significant barriers to discussing diagnostic errors publicly. Poststratification weighting accounted for nonresponse bias; the Benjamini-Hochberg adjustment was applied to control for false discovery (significance set at P < 0.018).

RESULTS

Clinicians (n = 838; response rate 22.6%) were significantly less comfortable discussing all error types during morbidity and mortality conferences than privately (P < 0.004) and significantly less comfortable discussing diagnostic errors compared with other medical errors (P < 0.018). Comfort did not differ by clinician type or years in practice; clinicians at one institution were significantly less comfortable discussing diagnostic errors compared with peers at other institutions. The most frequently cited barriers to discussing diagnostic errors publicly included feeling like a bad clinician, loss of reputation, and peer judgment of knowledge base and decision-making.

CONCLUSIONS

Clinicians are more uncomfortable discussing diagnostic errors than other types of medical errors. The most frequent barriers involve the public perception of clinical performance. Addressing this aspect of safety culture may improve clinician participation in efforts to reduce harm from diagnostic errors.

Understanding the roles of three academic communities in a prospective learning health ecosystem for diagnostic excellence

Inaccurate, untimely, and miscommunicated medical diagnoses represent a wicked problem requiring comprehensive and coordinated approaches, such as those demonstrated in the characteristics of learning health systems (LHSs). To appreciate a vision for how LHS methods can optimize processes and outcomes in medical diagnosis (diagnostic excellence), we interviewed 32 individuals with relevant expertise: 18 who have studied diagnostic processes using traditional behavioral science and health services research methods, six focused on machine learning (ML) and artificial intelligence (AI) approaches, and eight multidisciplinary researchers experienced in advocating for and incorporating LHS methods, ie, scalable continuous learning in health care. We report on barriers and facilitators, identified by these subjects, to applying their methods toward optimizing medical diagnosis. We then employ their insights to envision the emergence of a learning ecosystem that leverages the tools of each of the three research groups to advance diagnostic excellence. We found that these communities represent a natural fit forward, in which together, they can better measure diagnostic processes and close the loop of putting insights into practice. Members of the three academic communities will need to network and bring in additional stakeholders before they can design and implement the necessary infrastructure that would support ongoing learning of diagnostic processes at an economy of scale and scope.

Payment Innovations To Improve Diagnostic Accuracy And Reduce Diagnostic Error

Diagnostic accuracy is essential for treatment decisions but is largely unaccounted for by payers, including in fee-for-service Medicare and proposed Alternative Payment Models (APMs). We discuss three payment-related approaches to reducing diagnostic error. First, coding changes in the Medicare Physician Fee Schedule could facilitate the more effective use of teamwork and information technology in the diagnostic process and better support the cognitive work and time commitment that physicians make in the quest for diagnostic accuracy, especially in difficult or uncertain cases. Second, new APMs could be developed to focus on improving diagnostic accuracy in challenging cases and make available support resources for diagnosis, including condition-specific centers of diagnostic expertise or general diagnostic centers of excellence that provide second (or even third) opinions. Performing quality improvement activities that promote safer diagnosis should be a part of the accountability of APM recipients. Third, the accuracy of diagnoses that trigger APM payments and establish payment amounts should be confirmed by APM recipients. Implementation of these multipronged approaches can make current payment models more accountable for addressing diagnostic error and position diagnostic performance as a critical component of quality-based payment.

Tracking Progress in Improving Diagnosis: A Framework for Defining Undesirable Diagnostic Events

Diagnostic error is a prevalent, harmful, and costly phenomenon. Multiple national health care and governmental organizations have recently identified the need to improve diagnostic safety as a high priority. A major barrier, however, is the lack of standardized, reliable methods for measuring diagnostic safety. Given the absence of reliable and valid measures for diagnostic errors, we need methods to help establish some type of baseline diagnostic performance across health systems, as well as to enable researchers and health systems to determine the impact of interventions for improving the diagnostic process. Multiple approaches have been suggested but none widely adopted. We propose a new framework for identifying "undesirable diagnostic events" (UDEs) that health systems, professional organizations, and researchers could further define and develop to enable standardized measurement and reporting related to diagnostic safety. We propose an outline for UDEs that identifies both conditions prone to diagnostic error and the contexts of care in which these errors are likely to occur. Refinement and adoption of this framework across health systems can facilitate standardized measurement and reporting of diagnostic safety.

Decision-making skills improve with critical care training: Using simulation to measure progress

PURPOSE

Health care professionals are expected to acquire decision-making skills during their training, but few methods are available to assess progress in acquiring these essential skills. The purpose of this study was to determine whether a simulation methodology could be used to assess whether decision-making skills improve during critical care training.

MATERIALS AND METHODS

Sixteen simulated scenarios were designed to assess a critical care provider's ability to make decisions in the care of a critical ill patient. Seventeen (17) critical care providers managed 8 of the scenarios early during their training and then managed a second set of 8 scenarios (T2) at the conclusion of their training.

RESULTS

Provider's mean global scenario scores (0-9) increased significantly fromT1 and T2 (5.64 ± 0.74) and (6.54 ± 0.64) with a large effect size (1.3). Acute care nurse practitioners and fellows achieved similar overall scores at the conclusion of their training (ACNP 6.43 ± 0.57; Fellows 6.64 ± 0.72).

CONCLUSIONS

These findings provide evidence to support the validity of a simulation-based method to assess progress in decision-making skills. A simulation methodology could be used to establish a performance standard that determined a provider's ability to make independent decisions.

Sepsis as a model for improving diagnosis

Diagnostic safety could theoretically be improved by high-level interventions, such as improving clinical reasoning or eliminating system-related defects in care, or by focusing more specifically on a single problem or disease. In this review, we consider how the timely diagnosis of sepsis has evolved and improved as an example of the disease-focused approach. This progress has involved clarifying and revising the definitions of sepsis, efforts to raise awareness, faster and more reliable laboratory tests and a host of practice-level improvements based on health services research findings and recommendations. We conclude that this multi-faceted approach incorporating elements of the 'learning health system' model has improved the early recognition and treatment of sepsis, and propose that this model could be productively applied to improve timely diagnosis in other time-sensitive conditions.

Stroke Chameleons and Stroke Mimics in the Emergency Department

PURPOSE OF REVIEW

We discuss the frequency of stroke misdiagnosis in the emergency department (ED), identify common diagnostic pitfalls, describe strategies to reduce diagnostic error, and detail ongoing research.

RECENT FINDINGS

The National Academy of Medicine has re-defined and highlighted the importance of diagnostic errors for patient safety. Recent rates of stroke under-diagnosis (false-negative cases, "stroke chameleons") range from 2-26% and 30-43% for stroke over-diagnosis (false-positive cases, "stroke mimics"). Failure to diagnosis stroke can preclude time-sensitive treatments and has been associated with poor outcomes. Strategies have been developed to improve detection of posterior circulation stroke syndromes, but ongoing work is needed to reduce under-diagnosis in other atypical stroke presentations. The published rates of harm associated with stroke over-diagnosis, particularly thrombolysis of stroke mimics, remain low. Additional strategies to improve the accuracy of stroke diagnosis should focus on rapid clinical reasoning in the time-sensitive setting of acute ischemic stroke and identifying imperfections in the healthcare system which may contribute to diagnostic error.

Managing diagnostic uncertainty in primary care: a systematic critical review

Background

Diagnostic uncertainty is one of the largest contributory factors to the occurrence of diagnostic errors across most specialties in medicine and arguably uncertainty is greatest in primary care due to the undifferentiated symptoms primary care physicians are often presented with. Physicians can respond to diagnostic uncertainty in various ways through the interplay of a series of cognitive, emotional and ethical reactions. The consequences of such uncertainty however can impact negatively upon the primary care practitioner, their patients and the wider healthcare system. Understanding the nature of the existing empirical literature in relation to managing diagnostic uncertainty in primary medical care is a logical and necessary first step in order to understand what solutions are already available and/or to aid the development of any training or feedback aimed at better managing this uncertainty. This review is the first to characterize the existing empirical literature on managing diagnostic uncertainty in primary care.

Methods

Sixteen databases were systematically searched from inception to present with no restrictions. Hand searches of relevant websites and reference lists of included studies were also conducted. Two authors conducted abstract/article screening and data extraction. PRISMA guidelines were adhered to.

Results

Ten studies met the inclusion criteria. A narrative and conceptual synthesis was undertaken under the premises of critical reviews. Results suggest that studies have focused on internal factors (traits, skills and strategies) associated with managing diagnostic uncertainty with only one external intervention identified. Cognitive factors ranged from the influences of epistemological viewpoints to practical approaches such as greater knowledge of the patient, utilizing resources to hand and using appropriate safety netting techniques. Emotional aspects of uncertainty management included clinicians embracing uncertainty and working with provisional diagnoses. Ethical aspects of uncertainty management centered on communicating diagnostic uncertainties with patients. Personality traits and characteristics influenced each of the three domains.

Conclusions

There is little empirical evidence on how uncertainty is managed in general practice. However we highlight how the extant literature can be conceptualised into cognitive, emotional and ethical aspects of uncertainty which may help clinicians be more aware of their own biases as well as provide a platform for future research.

Trial registration

PROSPERO registration: CRD42015027555

Electronic supplementary material

The online version of this article (doi:10.1186/s12875-017-0650-0) contains supplementary material, which is available to authorized users.