Electronic Health Record Use Issues and Diagnostic Error: A Scoping Review and Framework

Diagnosis Documentation Done Right: Cross-Specialty Standard for the Diagnosis Section in German Discharge Summaries - A Mixed-Methods Study

BACKGROUND

The diagnosis section in hospital discharge summaries is critical for continuity of care and patient safety, yet it varies widely in quality, format, and content due to a lack of standards.

OBJECTIVE

This study aims to develop a cross-specialty standard for the structure and content of the diagnosis section, based on the preferences of German physicians. The study examines physicians' satisfaction with the diagnosis section, their rating of its importance, and their preferences for its specific elements, comparing perspectives between inpatient and outpatient physicians.

DESIGN, PARTICIPANTS, APPROACH

This mixed-methods study integrated a scoping review, focus group discussion, and a nationwide survey of 602 physicians (317 outpatient primary care and 285 inpatient physicians; 4.1% response rate), most trained in internal medicine. Quantitative analyses evaluated physician satisfaction and preferences, while qualitative feedback provided deeper insights regarding preferred content and format.

KEY RESULTS

Although 95.7% of physicians considered the diagnosis section crucial for follow-up care, only 36.9% were satisfied with its current content and format. 91.2% supported standardizing the diagnosis section, identifying 18 content elements to be included for every current treatment diagnosis. Strong consensus (> 95.0% agreement) was reached for "name of the diagnosis," "severity/stage/classification/TNM," "localization/extent/pattern of involvement," "course e.g., acute, chronic, recurrent," "expression," "complications," "date of initial diagnosis," and "etiology/cause." 86.4% preferred separating current and chronic/prior diagnoses with headings. Outpatient physicians were more likely than inpatient physicians to rate "ICD-10 codes" as mandatory (46.2% vs. 14.8%, p < 0.001) and to consider "recommendations for further procedures" (76.6% vs. 63.6%, p < 0.001) and "follow-up appointments" (77.3% vs. 63.5%, p < 0.001) as necessary. Additionally, a list of practical recommendations for clinicians to better document diagnoses was derived.

CONCLUSIONS

This study proposes a cross-specialty standard for the diagnosis section based on physician preferences for a clearly structured format and 18 key content elements.

A synthesized differential diagnosis is associated with fewer diagnostic errors compared to an inventorial list

OBJECTIVES

Emergency department (ED) encounters carry high risk of diagnostic error. Understanding how providers process information and reach diagnostic conclusions may identify interventions to reduce diagnostic errors. We aimed to determine if pediatric ED notes documenting a simple inventory of alternative diagnoses (inventorial differential diagnosis (DDx)) increased the odds of subsequent diagnostic error compared to encounters where the DDx was explicitly linked to specific data elements in the encounter (synthesized).

METHODS

This is a cohort study of children 0-22 years who experienced unplanned admission within 10 days of an index pediatric ED or urgent care visit. Documented DDx (inventorial vs. synthesized) in the index visit notes served as the predictor variable. The primary outcome was presence of diagnostic error. Propensity scores were created using patient demographics and complexity and visit acuity. Propensity score matched patients were compared with multivariable conditional logistic regression to assess association between documented DDx and diagnostic error.

RESULTS

Propensity scores matched 303 patient pairs of inventorial and synthesized DDx from 869 charts screened in for review. The adjusted odds ratio for diagnostic error at a subsequent unplanned admission was 1.79 (95 % CI 1.17-2.75) when an inventorial DDx was documented relative to synthesized. This finding includes adjustments for the number of diagnostic tests, obtaining a subspecialty consult and number of hospitalizations in the prior 6 months.

CONCLUSIONS

An inventorial DDx in pediatric emergency medical decision making is associated with significantly higher odds of subsequent diagnostic error, offering an actionable, simple opportunity for all providers to improve patient care.

"Everything is electronic health record-driven": the role of the electronic health record in the emergency department diagnostic process

Objectives

There is limited knowledge on how providers and patients in the emergency department (ED) use electronic health records (EHRs) to facilitate the diagnostic process. While EHRs can support diagnostic decision-making, EHR features that are not user-centered may increase the likelihood of diagnostic error. We aimed to identify how EHRs facilitate or impede the diagnostic process in the ED and to identify opportunities to reduce diagnostic errors and improve care quality.

Materials and Methods

We conducted semistructured interviews with 10 physicians, 15 nurses, and 8 patients across 4 EDs. Data were analyzed using a hybrid thematic analysis approach, which blends deductive (ie, using multiple conceptual frameworks) and inductive coding strategies. A team of 4 coders performed coding.

Results

We identified 4 themes, 3 at the care team level and 1 at the patient level. At the care team level, the benefits of the EHR in the diagnostic process included (1) customizing features to facilitate diagnostic workup and (2) aiding in communication. However, (3) EHR-driven protocols were found to potentially burden the care process and reliance on asynchronous communication could impede team dynamics. At the patient-level, we found that (4) patient portals facilitated meaningful patient engagement through timely delivery of results.

Discussion

While EHRs can improve the diagnostic process, they can also impair communication and increase workload. Electronic health record design should leverage provider-created tools to improve usability and enhance diagnostic safety.

Conclusions

Our findings have important implications for health information technology design and policy. Further work should assess optimal ways to release patient results via the EHR portal.

Realizing the Full Potential of Clinical Decision Support: Translating Usability Testing into Routine Practice in Health Care Operations

BACKGROUND

 Clinical Decision Support (CDS) tools have a mixed record of effectiveness, often due to inadequate alignment with clinical workflows and poor usability. While there is a consensus that usability testing methods address these issues, in practice, usability testing is generally only used for selected projects (such as funded research studies). There is a critical need for CDS operations to apply usability testing to all CDS implementations.

OBJECTIVES

 In this State of the Art/Best Practice paper, we share challenges with scaling usability in health care operations and alternative methods and CDS governance structures to enable usability testing as a routine practice.

METHODS

 We coalesce our experience and results of applying guerilla in situ usability testing to over 20 projects in a 1-year period with the proposed solution.

RESULTS

 We demonstrate the feasibility of adopting "guerilla in situ usability testing" in operations and their effectiveness in incorporating user feedback and improving design.

CONCLUSION

 Although some methodological rigor was relaxed to accommodate operational speed, the benefits outweighed the limitations. Broader adoption of usability testing may transform CDS implementation and improve health outcomes.

The burden of diagnostic error in dentistry: A study on periodontal disease misclassification

BACKGROUND

Periodontal disease constitutes a widely prevalent category of non-communicable diseases and ranks among the top 10 causes of disability worldwide. Little however is known about diagnostic errors in dentistry. In this work, by retrospectively deploying an electronic health record (EHR)-based trigger tool, followed by gold standard manual review, we provide epidemiological estimates on the rate of diagnostic misclassification in dentistry through a periodontal use case.

METHODS

An EHR-based trigger tool (a retrospective record review instrument that uses a list of triggers (or clues), i.e., data elements within the health record, to alert reviewers to the potential presence of a wrong diagnosis) was developed, tested and run against the EHR at the two participating sites to flag all cases having a potential misdiagnosis. All cases flagged as potentially misdiagnosed underwent extensive manual reviews by two calibrated domain experts. A subset of the non-flagged cases was also manually reviewed.

RESULTS

A total of 2,262 patient charts met the study's inclusion criteria. Of these, the algorithm flagged 1,124 cases as potentially misclassified and 1,138 cases as potentially correctly diagnosed. When the algorithm identified a case as potentially misclassified, compared to the diagnosis assigned by the gold standard, the kappa statistic was 0.01. However, for cases the algorithm marked as potentially correctly diagnosed, the review against the gold standard showed a kappa statistic of 0.9, indicating near perfect agreement. The observed proportion of diagnostic misclassification was 32 %. There was no significant difference by clinic or provider characteristics.

CONCLUSION

Our work revealed that about a third of periodontal cases are misclassified. Diagnostic errors have been reported to happen more frequently than other types of errors, and to be more preventable. Benchmarking diagnostic quality is a first step. Subsequent research endeavor will delve into comprehending the factors that contribute to diagnostic errors in dentistry and instituting measures to prevent them.

CLINICAL SIGNIFICANCE

This study sheds light on the significance of diagnostic excellence in the delivery of dental care, and highlights the potential role of technology in aiding diagnostic decision-making at the point of care.

Perceptions of hospital electronic health record (EHR) training, support, and patient safety by staff position and tenure

BACKGROUND

Hospitals rely on their electronic health record (EHR) systems to assist with the provision of safe, high quality, and efficient health care. However, EHR systems have been found to disrupt clinical workflows and may lead to unintended consequences associated with patient safety and health care professionals' perceptions of and burden with EHR usability and interoperability. This study sought to explore the differences in staff perceptions of the usability and safety of their hospital EHR system by staff position and tenure.

METHODS

We used data from the AHRQ Surveys on Patient Safety Culture® (SOPS®) Hospital Survey Version 1.0 Database and the SOPS Health Information Technology Patient Safety Supplemental Items ("Health IT item set") collected from 44 hospitals and 8,880 staff in 2017. We used regression modeling to examine perceptions of EHR system training, EHR support & communication, EHR-related workflow, satisfaction with the EHR system, and the frequency of EHR-related patient safety and quality issues by staff position and tenure, while controlling for hospital ownership type and bed-size.

RESULTS

In comparison to RNs, pharmacists had significantly lower (unfavorable) scores for EHR system training (regression coefficient = -0.07; p = 0.047), and physicians, hospital management, and the IT staff were significantly more likely to report high frequency of inaccurate EHR information (ORs = 2.03, 1.34, 1.72, respectively). Compared to staff with 11 or more years of hospital tenure, new staff (less than 1 year at the hospital) had significantly lower scores for EHR system training, but higher scores for EHR support & communication (p < 0.0001). Dissatisfaction of the EHR system was highest among physicians and among staff with 11 or more years tenure at the hospital.

CONCLUSIONS

There were significant differences in the Health IT item set's results across staff positions and hospital tenure. Hospitals can implement the SOPS Health IT Patient Safety Supplemental Items as a valuable tool for identifying incongruity in the perceptions of EHR usability and satisfaction across staff groups to inform targeted investment in EHR system training and support.

Human Factors and Organizational Issues in Health Informatics: Review of Recent Developments and Advances

OBJECTIVE

In this paper we focus on a review of key articles published in the past two years (2022 and 2023) in the areas of human factors and organizational issues in health informatics.

METHODS

We reviewed manuscripts that were published in primary human factors, human factors engineering and health informatics journals. This involved conducting a series of searches using PubMed, Web of Science, and Google Scholar for articles related to human factors in healthcare published in 2022 and 2023.

RESULTS

The range of applications that have been designed and analyzed using human factors approaches has been rapidly expanding, including increased number of articles around topics such as the following: AI in healthcare, patient-centered design, usability of mHealth, organizational issues, and work around ensuring system safety. This includes study of applications designed for use by both patients and health providers applying both qualitative and quantitative approaches to user requirements, user-centered system design and human factors analysis and evaluation.

CONCLUSION

The importance of human factors is becoming recognized as new forms of health technology appear. A multi-level perspective on human factors, that considers human factors at multiple levels, from the individual user to the complex social and organizational context, was described to consider the range and diversity of human factors approaches in healthcare. Such an approach will be needed to drive the design and evaluation of useful and usable healthcare information technologies.

Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview

Electronic Health Records (EHR) are increasingly being perceived as a unique source of data for clinical research as they provide unprecedentedly large volumes of real-time data from real-world settings. In this review of the secondary uses of EHR, we identify the anticipated breadth of opportunities, pointing out the data deficiencies and potential biases that are likely to limit the search for true causal relationships. This paper provides a comprehensive overview of the types of biases that arise along the pathways that generate real-world evidence and the sources of these biases. We distinguish between two levels in the production of EHR data where biases are likely to arise: (i) at the healthcare system level, where the principal source of bias resides in access to, and provision of, medical care, and in the acquisition and documentation of medical and administrative data; and (ii) at the research level, where biases arise from the processes of extracting, analyzing, and interpreting these data. Due to the plethora of biases, mainly in the form of selection and information bias, we conclude with advising extreme caution about making causal inferences based on secondary uses of EHRs.