Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism

WeChat assisted electronic symptom measurement for patients with adenomyosis

PURPOSE

Symptom assessment is central to appropriate adenomyosis management. Using a WeChat mini-program-based portal, we aimed to establish a valid symptom assessment scale of adenomyosis (AM-SAS) to precisely and timely identify needs of symptom management and ultimately, to alert disease recurrence.

METHODS

A combination of intensive interviews of patients with adenomyosis and natural language processing on WeChat clinician-patient group communication was used to generate a pool of symptom items-related to adenomyosis. An expert panel shortened the list to form the provisional AM-SAS. The AM-SAS was built in a Wechat mini-programmer and sent to patients to exam the psychotically validity and clinical applicability through classic test theory and item response theory.

RESULTS

Total 338 patients with adenomyosis (29 for interview, 179 for development, and 130 for external validation) and 86 gynecologists were included. The over 90% compliance to the WeChat-based symptom evaluate. The AM-SAS demonstrated the uni-dimensionality through Rasch analysis, good internal consistency (all Cronbach's alphas above 0.8), and test-retest reliability (intraclass correlation coefficients ranging from 0.65 to 0.84). Differences symptom severity score between patients in the anemic and normal hemoglobin groups (3.04 ± 3.17 vs. 5.68 ± 3.41, P < 0.001). In external validation, AM-SAS successfully detected differences in symptom burden and physical status between those with or without relapse.

CONCLUSION

Electronic PRO-based AM-SAS is a valuable instrument for monitoring AM-related symptoms. As an outcome measure of multiple symptoms in clinical trials, the AM-SAS may identify patients who need extensive care after discharge and capture significant beneficial changes of patients may have been overlooked.

TRIAL REGISTRATION

This trial was approved by the institutional review board of the Chongqing Medical University and three participating hospitals (Medical Ethics Committee of Nanchong Central Hospital, Medical Ethics Committee of Affiliated Hospital of Southwest Medical University, and Medical Ethics Committee of Haifu Hospital) and registered in the Chinese Clinical Trial Registry (registration number ChiCTR2000038590), date of registration was 26/10/2020.

Reducing the Risk of Delayed Colorectal Cancer Diagnoses Through an Ambulatory Safety Net Collaborative

BACKGROUND

An estimated 12 million adults in the United States experience delayed diagnoses and other diagnostic errors annually. Ambulatory safety nets (ASNs) are an intervention to reduce delayed diagnoses by identifying patients with abnormal results overdue for follow-up using registries, workflow redesign, and patient navigation. The authors sought to co-design a collaborative and implement colorectal cancer (CRC) ASNs across various health care settings.

METHODS

A working group was convened to co-design implementation guidance, measures, and the collaborative model. Collaborative sites were recruited through a medical professional liability insurance program and chose to begin with developing an ASN for positive at-home CRC screening or overdue surveillance colonoscopy. The 18-month Breakthrough Series Collaborative ran from January 2022 to July 2023, with sites continuing to collect data while sustaining their ASNs. Data were collected from sites monthly on patients in the ASN, including the proportion that was successfully contacted, scheduled, and completed a follow-up colonoscopy.

RESULTS

Six sites participated; four had an operational ASN at the end of the Breakthrough Series, with the remaining sites launching three months later. From October 2022 through February 2024, the Collaborative ASNs collectively identified 5,165 patients from the registry as needing outreach. Among patients needing outreach, 3,555 (68.8%) were successfully contacted, 2,060 (39.9%) were scheduled for a colonoscopy, and 1,504 (29.1%) completed their colonoscopy.

CONCLUSION

The Collaborative successfully identified patients with previously abnormal CRC screening and facilitated completion of follow-up testing. The CRC ASN Implementation Guide offers a comprehensive road map for health care leaders interested in implementing CRC ASNs.

Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments

OBJECTIVE

Diagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).

METHODS

Using two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit.

RESULTS

We applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for "missed" = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen's kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%).

CONCLUSION

In a large national EHR repository, a symptom-disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.

Application of electronic trigger tools to identify targets for improving diagnostic safety

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.

Understanding Test Results Follow-Up in the Ambulatory Setting: Analysis of Multiple Perspectives

BACKGROUND

Delayed or incomplete test result follow-up, which can lead to missed and/or delayed diagnosis, is an important issue in the ambulatory setting. Delayed test result follow-up has been linked to poorer patient outcomes and increased risk of mortality and accounts for a large portion of medical malpractice claims. Yet improvements are difficult, reflecting the complexity of the test result follow-up process. Test result follow-up safety culture was investigated using qualitative and quantitative patient safety and quality of care data at an academic medical center.

METHODS

After an environmental scan, five sources of data were used to compass multiple perspectives on safety culture-two national surveys (AHRQ MO SOPS for safety culture and CG-CAHPS for patient satisfaction); patient and family complaints; safety reports; and provider response times to test message results in the electronic health record.

RESULTS

The following metrics were inspected: how patients and providers estimated the frequency for providing timely test results; how patients' satisfaction with their provider correlated with their provider's response time to test result messages; and qualitative themes in patient complaints and safety reports filed by clinic. The institution was compared to national benchmarks using surveys. As test result response time decreased, patient satisfaction increased (p = 0.0073).

CONCLUSION

Test result follow-up culture was investigated using tools typically used to examine patient satisfaction and experience and staff culture. Use of these five sources of data led to an examination of multiple perspectives in follow-up culture and identification of possible explanations for inappropriate follow-up. These data sources can be further explored to identify possible solutions.

Assessing the Burden of Abnormal LFTs and the Role of the Electronic Health Record: A Retrospective Study

BACKGROUND

Primary care clinicians encounter abnormal liver function tests (LFTs) frequently. This study assesses the prevalence of abnormal LFTs and patient follow-up patterns in response.

METHODS

This is a retrospective study from 2007-2016 of adult patients with abnormal LFTs seen in an internal medicine clinic. The proportion of patients with follow-up testing and the time (in days) to repeat LFTs were the primary outcomes measured. Results were evaluated before and after the implementation of the institution's electronic health record (EHR).

RESULTS

This study identified a period prevalence for abnormal LFTs of 39%. Of these, 9,545 unique patients met inclusion criteria, with 8,415 patients (88.2%) possessing follow-up LFTs and no significant difference in the proportion of patients receiving follow-up by degree of initial abnormality. Median time to follow-up in mild abnormalities (1-2 times normal) was 138 days, compared to 21 days for severe abnormalities (>4 times normal, P < 0.0001). Reduced time to repeat testing across all spectrums of abnormality was observed following EHR implementation, but proportions of missing follow-up did not improve. A multivariable logistic regression model identified younger age, poverty, living over 50 miles from clinic, recent cohort entry and a lower magnitude of abnormality as predictors for missing repeat LFT testing (area under the curve = 0.838 [95% CI: 0.827-0.849]).

CONCLUSIONS

Abnormal LFTs were detected in 39% of all patients seen. The degree of LFT abnormality did not influence rates of follow-up testing, but does appear to play a role in the timing of repeat testing, when obtained. Follow-up rates did not improve with EHR implementation.