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

Charting Diagnostic Safety: Exploring Patient-Provider Discordance in Medical Record Documentation

BACKGROUND

The 21st Century Cures Act enables patients to access their medical records, thus providing a unique opportunity to engage patients in their diagnostic journey.

OBJECTIVE

To explore the concordance between patients' self-reported diagnostic concerns and clinician-interpreted information in their electronic health records.

DESIGN

We conducted a mixed-methods analysis of a cohort of 467 patients who completed a structured data collection instrument (the Safer Dx Patient) to identify diagnostic concerns while reviewing their clinician's notes. We conducted a qualitative content analysis of open-ended responses on both the tools and the case summaries. Two clinical chart reviewers, blinded to patient-reported diagnostic concerns, independently conducted chart reviews using a different structured instrument (the Revised Safer Dx Instrument) to identify diagnostic concerns and generate case summaries. The primary outcome variable was chart review-identified diagnostic concerns. Multivariate logistic regression tested whether the primary outcome was concordant with patient-reported diagnostic concerns.

SETTING

Geisinger, a large integrated healthcare organization in rural and semi-urban Pennsylvania.

PARTICIPANTS

Cohort of adult patients actively using patient portals and identified as "at-risk" for diagnostic concerns using an electronic trigger algorithm based on unexpected visit patterns in a primary care setting.

RESULTS

In 467 cohort patients, chart review identified 31 (6.4%) diagnostic concerns, of which only 11 (21.5%) overlapped with 51 patient-reported diagnostic concerns. Content analysis revealed several areas of discordant understanding of the diagnostic process between clinicians and patients. Multivariate logistic regression analysis showed that clinician-identified diagnostic concerns were associated with patients who self-reported "I feel I was incorrectly diagnosed during my visit" (odds ratio 1.65, 95% CI 1.17-2.3, p < 0.05).

CONCLUSION

Patients and clinicians appear to have certain differences in their mental models of what is considered a diagnostic concern. Efforts to integrate patient perspectives and experiences with the diagnostic process can lead to better measurement of diagnostic safety.

The 1-minute preceptor to improve diagnostic reasoning in a primary care nurse practitioner residency program

BACKGROUND

The One-Minute Preceptor (OMP) model to teach diagnostic reasoning and Reporter, Interpreter, Manager, and Educator (RIME) framework to measure progress are used in physician training. Little is known about the use of these tools in nurse practitioner (NP) training.

LOCAL PROBLEM

Precepting NP trainees at the Veterans Affairs (VA) is not standardized. A standardized approach to precepting NP residency trainees using the OMP model and RIME scoring was evaluated for improvement and helpfulness.

METHODS

A quality-improvement project with two Plan-Do-Study-Act (PDSA) cycles were conducted over a 12-week period. Mean RIME scores, preceptor self-efficacy, and use of teaching skills were measured preintervention and postintervention. Data were analyzed using a paired sample t -test and descriptive statistics.

INTERVENTIONS

A convenience sample of preceptors and trainees was recruited from a large VA medical center. A 1-hour workshop educated preceptors with role playing and return demonstrations on OMP techniques and RIME scoring. The teachings were applied to standardize precepting and assess diagnostic reasoning. Trainee self-scoring and results triggered conversations to fulfil the identified gaps.

RESULTS

Mean RIME scores improved (1.62 [0.17] vs. 2.23 [0.38], p < .001) post 12-week intervention. Mean RIME scores improved between PDSA cycle 1 and cycle 2 (2.07 [0.25] vs. 2.48 [0.39], p < .001). Preceptors (91%) and trainees (100%) found the OMP model and RIME framework helpful.

CONCLUSION

Use of the OMP improved diagnostic reasoning in NP trainees. The OMP and RIME framework provided standardization of precepting and trainee discussions on improvements.

Exploring Clinical Lessons Learned by Experienced Hospitalists from Diagnostic Errors and Successes

BACKGROUND

Diagnostic errors cause significant patient harm. The clinician's ultimate goal is to achieve diagnostic excellence in order to serve patients safely. This can be accomplished by learning from both errors and successes in patient care. However, the extent to which clinicians grow and navigate diagnostic errors and successes in patient care is poorly understood. Clinically experienced hospitalists, who have cared for numerous acutely ill patients, should have great insights from their successes and mistakes to inform others striving for excellence in patient care.

OBJECTIVE

To identify and characterize clinical lessons learned by experienced hospitalists from diagnostic errors and successes.

DESIGN

A semi-structured interview guide was used to collect qualitative data from hospitalists at five independently administered hospitals in the Mid-Atlantic area from February to June 2022.

PARTICIPANTS

12 academic and 12 community-based hospitalists with ≥ 5 years of clinical experience.

APPROACH

A constructivist qualitative approach was used and "reflexive thematic analysis" of interview transcripts was conducted to identify themes and patterns of meaning across the dataset.

RESULTS

Five themes were generated from the data based on clinical lessons learned by hospitalists from diagnostic errors and successes. The ideas included appreciating excellence in clinical reasoning as a core skill, connecting with patients and other members of the health care team to be able to tap into their insights, reflecting on the diagnostic process, committing to growth, and prioritizing self-care.

CONCLUSIONS

The study identifies key lessons learned from the errors and successes encountered in patient care by clinically experienced hospitalists. These findings may prove helpful for individuals and groups that are authentically committed to moving along the continuum from diagnostic competence towards excellence.

Partnership as a Pathway to Diagnostic Excellence: The Challenges and Successes of Implementing the Safer Dx Learning Lab

BACKGROUND

Learning health system (LHS) approaches could potentially help health care organizations (HCOs) identify and address diagnostic errors. However, few such programs exist, and their implementation is poorly understood.

METHODS

The authors conducted a qualitative evaluation of the Safer Dx Learning Lab, a partnership between a health system and a research team, to identify and learn from diagnostic errors and improve diagnostic safety at an organizational level. The research team conducted virtual interviews to solicit participant feedback regarding experiences with the lab, focusing specifically on implementation and sustainment issues.

RESULTS

Interviews of 25 members associated with the lab identified the following successes: learning and professional growth, improved workflow related to streamlining the process of reporting error cases, and a psychologically safe culture for identifying and reporting diagnostic errors. However, multiple barriers also emerged: competing priorities between clinical responsibilities and research, time-management issues related to a lack of protected time, and inadequate guidance to disseminate findings. Lessons learned included understanding the importance of obtaining buy-in from leadership and interested stakeholders, creating a psychologically safe environment for reporting cases, and the need for more protected time for clinicians to review and learn from cases.

CONCLUSION

Findings suggest that a learning health systems approach using partnerships between researchers and a health system affected organizational culture by prioritizing learning from diagnostic errors and encouraging clinicians to be more open to reporting. The study findings can help organizations overcome barriers to engage clinicians and inform future implementation and sustainment of similar initiatives.

Developing the Safer Dx Checklist of Ten Safety Recommendations for Health Care Organizations to Address Diagnostic Errors

BACKGROUND

Most health care organizations (HCOs) find diagnostic errors hard to address. The research team developed a checklist (the Safer Dx Checklist) of 10 high-priority safety practices HCOs can use to conduct a proactive risk assessment to address diagnostic error.

METHODS

First, the team identified potential practices based on reviews of recent literature, reports by national and international organizations, and interviews with quality/safety leaders. Then a Delphi panel was conducted, followed by an online expert panel, to prioritize 10 practices. The prioritization process considered impact on safety and feasibility of practice implementation within a one- to three-year time frame. Finally, cognitive walkthroughs were conducted for a face-validity check with end users. The team also conducted content analysis in each step to look for themes that influenced prioritization or checklist implementation.

RESULTS

A total of 71 practices for prioritization were identified through the Delphi panel of 28 experts; 65% of participants reached consensus on 28 practices. A multidisciplinary panel of 10 experts helped prioritize and refine the top 10 practices, which were then developed into a checklist paired with implementation guidance. Practices included themes related to creating organizational and leadership accountability for improving diagnosis, including patients in diagnostic safety work, and developing and implementing organizational infrastructure for measurement and improvement activities. Qualitative analysis revealed insights for implementation. End users at three different HCOs helped refine implementation guidance for the checklist.

CONCLUSION

The researchers identified 10 safety practices to help organizations conduct a proactive, systematic assessment of risks to timely and accurate diagnosis. The Safer Dx Checklist can enable HCOs to begin implementing strategies to address diagnostic error.

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.

Translating electronic health record-based patient safety algorithms from research to clinical practice at multiple sites

Introduction

Researchers are increasingly developing algorithms that impact patient care, but algorithms must also be implemented in practice to improve quality and safety.

Objective

We worked with clinical operations personnel at two US health systems to implement algorithms to proactively identify patients without timely follow-up of abnormal test results that warrant diagnostic evaluation for colorectal or lung cancer. We summarise the steps involved and lessons learned.

Methods

Twelve sites were involved across two health systems. Implementation involved extensive software documentation, frequent communication with sites and local validation of results. Additionally, we used automated edits of existing code to adapt it to sites’ local contexts.

Results

All sites successfully implemented the algorithms. Automated edits saved sites significant work in direct code modification. Documentation and communication of changes further aided sites in implementation.

Conclusion

Patient safety algorithms developed in research projects were implemented at multiple sites to monitor for missed diagnostic opportunities. Automated algorithm translation procedures can produce more consistent results across sites.

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.

Filling a gap in safety metrics: development of a patient-centred framework to identify and categorise patient-reported breakdowns related to the diagnostic process in ambulatory care

BACKGROUND

Patients and families are important contributors to the diagnostic team, but their perspectives are not reflected in current diagnostic measures. Patients/families can identify some breakdowns in the diagnostic process beyond the clinician's view. We aimed to develop a framework with patients/families to help organisations identify and categorise patient-reported diagnostic process-related breakdowns (PRDBs) to inform organisational learning.

METHOD

A multi-stakeholder advisory group including patients, families, clinicians, and experts in diagnostic error, patient engagement and safety, and user-centred design, co-developed a framework for PRDBs in ambulatory care. We tested the framework using standard qualitative analysis methods with two physicians and one patient coder, analysing 2165 patient-reported ambulatory errors in two large surveys representing 25 425 US respondents. We tested intercoder reliability of breakdown categorisation using the Gwet's AC1 and Cohen's kappa statistic. We considered agreement coefficients 0.61-0.8=good agreement and 0.81-1.00=excellent agreement.

RESULTS

The framework describes 7 patient-reported breakdown categories (with 40 subcategories), 19 patient-identified contributing factors and 11 potential patient-reported impacts. Patients identified breakdowns in each step of the diagnostic process, including missing or inaccurate main concerns and symptoms; missing/outdated test results; and communication breakdowns such as not feeling heard or misalignment between patient and provider about symptoms, events, or their significance. The frequency of PRDBs was 6.4% in one dataset and 6.9% in the other. Intercoder reliability showed good-to-excellent reliability in each dataset: AC1 0.89 (95% CI 0.89 to 0.90) to 0.96 (95% CI 0.95 to 0.97); kappa 0.64 (95% CI 0.62, to 0.66) to 0.85 (95% CI 0.83 to 0.88).

CONCLUSIONS

The PRDB framework, developed in partnership with patients/families, can help organisations identify and reliably categorise PRDBs, including some that are invisible to clinicians; guide interventions to engage patients and families as diagnostic partners; and inform whole organisational learning.

The Diagnostic Error Index: A Quality Improvement Initiative to Identify and Measure Diagnostic Errors

OBJECTIVE

To develop a diagnostic error index (DEI) aimed at providing a practical method to identify and measure serious diagnostic errors.

STUDY DESIGN

A quality improvement (QI) study at a quaternary pediatric medical center. Five well-defined domains identified cases of potential diagnostic errors. Identified cases underwent an adjudication process by a multidisciplinary QI team to determine if a diagnostic error occurred. Confirmed diagnostic errors were then aggregated on the DEI. The primary outcome measure was the number of monthly diagnostic errors.

RESULTS

From January 2017 through June 2019, 105 cases of diagnostic error were identified. Morbidity and mortality conferences, institutional root cause analyses, and an abdominal pain trigger tool were the most frequent domains for detecting diagnostic errors. Appendicitis, fractures, and nonaccidental trauma were the 3 most common diagnoses that were missed or had delayed identification.

CONCLUSIONS

A QI initiative successfully created a pragmatic approach to identify and measure diagnostic errors by utilizing a DEI. The DEI established a framework to help guide future initiatives to reduce diagnostic errors.

Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation

Background

Patient complaints are associated with adverse events and malpractice claims but underused in patient safety improvement.

Objective

To systematically evaluate the use of patient complaint data to identify safety concerns related to diagnosis as an initial step to using this information to facilitate learning and improvement.

Methods

We reviewed patient complaints submitted to Geisinger, a large healthcare organisation in the USA, from August to December 2017 (cohort 1) and January to June 2018 (cohort 2). We selected complaints more likely to be associated with diagnostic concerns in Geisinger’s existing complaint taxonomy. Investigators reviewed all complaint summaries and identified cases as ‘concerning’ for diagnostic error using the National Academy of Medicine’s definition of diagnostic error. For all ‘concerning’ cases, a clinician-reviewer evaluated the associated investigation report and the patient’s medical record to identify any missed opportunities in making a correct or timely diagnosis. In cohort 2, we selected a 10% sample of ‘concerning’ cases to test this smaller pragmatic sample as a proof of concept for future organisational monitoring.

Results

In cohort 1, we reviewed 1865 complaint summaries and identified 177 (9.5%) concerning reports. Review and analysis identified 39 diagnostic errors. Most were categorised as ‘Clinical Care issues’ (27, 69.2%), defined as concerns/questions related to the care that is provided by clinicians in any setting. In cohort 2, we reviewed 2423 patient complaint summaries and identified 310 (12.8%) concerning reports. The 10% sample (n=31 cases) contained five diagnostic errors. Qualitative analysis of cohort 1 cases identified concerns about return visits for persistent and/or worsening symptoms, interpersonal issues and diagnostic testing.

Conclusions

Analysis of patient complaint data and corresponding medical record review identifies patterns of failures in the diagnostic process reported by patients and families. Health systems could systematically analyse available data on patient complaints to monitor diagnostic safety concerns and identify opportunities for learning and improvement.

Perceptual Gaps Between Clinicians and Technologists on Health Information Technology-Related Errors in Hospitals: Observational Study

BACKGROUND

Health information technology (HIT) has been widely adopted in hospital settings, contributing to improved patient safety. However, many types of medical errors attributable to information technology (IT) have negatively impacted patient safety. The continued occurrence of many errors is a reminder that HIT software testing and validation is not adequate in ensuring errorless software functioning within the health care organization.

OBJECTIVE

This pilot study aims to classify technology-related medical errors in a hospital setting using an expanded version of the sociotechnical framework to understand the significant differences in the perceptions of clinical and technology stakeholders regarding the potential causes of these errors. The paper also provides some recommendations to prevent future errors.

METHODS

Medical errors were collected from previous studies identified in leading health databases. From the main list, we selected errors that occurred in hospital settings. Semistructured interviews with 5 medical and 6 IT professionals were conducted to map the events on different dimensions of the expanded sociotechnical framework.

RESULTS

Of the 2319 identified publications, 36 were included in the review. Of the 67 errors collected, 12 occurred in hospital settings. The classification showed the "gulf" that exists between IT and medical professionals in their perspectives on the underlying causes of medical errors. IT experts consider technology as the source of most errors and suggest solutions that are mostly technical. However, clinicians assigned the source of errors within the people, process, and contextual dimensions. For example, for the error "Copied and pasted charting in the wrong window: Before, you could not easily get into someone else's chart accidentally...because you would have to pull the chart and open it," medical experts highlighted contextual issues, including the number of patients a health care provider sees in a short time frame, unfamiliarity with a new electronic medical record system, nurse transitions around the time of error, and confusion due to patients having the same name. They emphasized process controls, including failure modes, as a potential fix. Technology experts, in contrast, discussed the lack of notification, poor user interface, and lack of end-user training as critical factors for this error.

CONCLUSIONS

Knowledge of the dimensions of the sociotechnical framework and their interplay with other dimensions can guide the choice of ways to address medical errors. These findings lead us to conclude that designers need not only a high degree of HIT know-how but also a strong understanding of the medical processes and contextual factors. Although software development teams have historically included clinicians as business analysts or subject matter experts to bridge the gap, development teams will be better served by more immersive exposure to clinical environments, leading to better software design and implementation, and ultimately to enhanced patient safety.

A Program to Provide Clinicians with Feedback on Their Diagnostic Performance in a Learning Health System

PROBLEM

Reducing diagnostic errors requires improving both systems and individual clinical reasoning. One strategy to achieve diagnostic excellence is learning from feedback. However, clinicians remain uncomfortable receiving feedback on their diagnostic performance. Thus, a team of researchers and clinical leaders aimed to develop and implement a diagnostic performance feedback program for learning that mitigates potential clinician discomfort.

APPROACH

The program was developed as part of a larger project to create a learning health system around diagnostic safety at Geisinger, a large, integrated health care system in rural Pennsylvania. Steps included identifying potential missed opportunities in diagnosis (MODs) from various sources (for example, risk management, clinician reports, patient complaints); confirming MODs through chart review; and having trained facilitators provide feedback to clinicians about MODs as learning opportunities. The team developed a guide for facilitators to conduct effective diagnostic feedback sessions and surveyed facilitators and recipients about their experiences and perceptions of the feedback sessions.

OUTCOMES

28 feedback sessions occurred from January 2019 to June 2020, involving MODs from emergency medicine, primary care, and hospital medicine. Most facilitators (90.6% [29/32]) reported that recipients were receptive to learning and discussing MODs. Most recipients reported that conversations were constructive and nonpunitive (83.3% [25/30]) and allowed them to take concrete steps toward improving diagnosis (76.7% [23/30]). Both groups believed discussions would improve future diagnostic safety (93.8% [30/32] and 70.0% [21/30], respectively).

KEY INSIGHTS AND NEXT STEPS

An institutional program was developed and implemented to deliver diagnostic performance feedback. Such a program may facilitate learning and improvement to reduce MODs. Future efforts should assess long-term effects on diagnostic performance and patient outcomes.

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.

Focused ethnography: a new tool to study diagnostic errors?

While much attention has been given to quantifying errors in diagnosis, how best to study the process of diagnosis is less clear. Focused ethnography as a methodology is particularly valuable for studying healthcare processes because it examines specific questions, situations or problems among a smaller group of individuals. In this paper, we review this approach and illustrate how we applied it to study diagnostic errors in hospitalized patients.