Errors in Diagnosis of Spinal Epidural Abscesses in the Era of Electronic Health Records.

PURPOSE: With this study, we set out to identify missed opportunities in diagnosis of spinal epidural abscesses to outline areas for process improvement. METHODS: Using a large national clinical data repository, we identified all patients with a new diagnosis of spinal epidural abscess in the Department of Veterans Affairs (VA) during 2013. Two physicians independently conducted retrospective chart reviews on 250 randomly selected patients and evaluated their records for red flags (eg, unexplained weight loss, neurological deficits, and fever) 90 days prior to diagnosis. Diagnostic errors were defined as missed opportunities to evaluate red flags in a timely or appropriate manner. Reviewers gathered information about process breakdowns related to patient factors, the patient-provider encounter, test performance and interpretation, test follow-up and tracking, and the referral process. Reviewers also determined harm and time lag between red flags and definitive diagnoses. RESULTS: Of 250 patients, 119 had a new diagnosis of spinal epidural abscess, 66 (55.5%) of which experienced diagnostic error. Median time to diagnosis in error cases was 12 days, compared with 4 days in cases without error (P <.01). Red flags that were frequently not evaluated in error cases included unexplained fever (n = 57; 86.4%), focal neurological deficits with progressive or disabling symptoms (n = 54; 81.8%), and active infection (n = 54; 81.8%). Most errors involved breakdowns during the patient-provider encounter (n = 60; 90.1%), including failures in information gathering/integration, and were associated with temporary harm (n = 43; 65.2%). CONCLUSION: Despite wide availability of clinical data, errors in diagnosis of spinal epidural abscesses are common and involve inadequate history, physical examination, and test ordering. Solutions should include renewed attention to basic clinical skills.

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

BACKGROUND: Delays in following up abnormal test results are a common problem in outpatient settings. Surveillance systems that use trigger tools to identify delayed follow-up can help reduce missed opportunities in care. OBJECTIVE: To develop and test an electronic health record (EHR)-based trigger algorithm to identify instances of delayed follow-up of abnormal thyroid-stimulating hormone (TSH) results in patients being treated for hypothyroidism. DESIGN: We developed an algorithm using structured EHR data to identify patients with hypothyroidism who had delayed follow-up (>60 days) after an abnormal TSH. We then retrospectively applied the algorithm to a large EHR data warehouse within the Department of Veterans Affairs (VA), on patient records from two large VA networks for the period from January 1, 2011, to December 31, 2011. Identified records were reviewed to confirm the presence of delays in follow-up. KEY RESULTS: During the study period, 645,555 patients were seen in the outpatient setting within the two networks. Of 293,554 patients with at least one TSH test result, the trigger identified 1250 patients on treatment for hypothyroidism with elevated TSH. Of these patients, 271 were flagged as potentially having delayed follow-up of their test result. Chart reviews confirmed delays in 163 of the 271 flagged patients (PPV = 60.1%). CONCLUSIONS: An automated trigger algorithm applied to records in a large EHR data warehouse identified patients with hypothyroidism with potential delays in thyroid function test results follow-up. Future prospective application of the TSH trigger algorithm can be used by clinical teams as a surveillance and quality improvement technique to monitor and improve follow-up.

Finding Diagnostic Errors in Children Admitted to the PICU.

OBJECTIVES: To determine whether the Safer Dx Instrument, a structured tool for finding diagnostic errors in primary care, can be used to reliably detect diagnostic errors in patients admitted to a PICU. DESIGN AND SETTING: The Safer Dx Instrument consists of 11 questions to evaluate the diagnostic process and a final question to determine if diagnostic error occurred. We used the instrument to analyze four "high-risk" patient cohorts admitted to the PICU between June 2013 and December 2013. PATIENTS: High-risk cohorts were defined as cohort 1: patients who were autopsied; cohort 2: patients seen as outpatients within 2 weeks prior to PICU admission; cohort 3: patients transferred to PICU unexpectedly from an acute care floor after a rapid response and requiring vasoactive medications and/or endotracheal intubation due to decompensation within 24 hours; and cohort 4: patients transferred to PICU unexpectedly from an acute care floor after a rapid response without subsequent decompensation in 24 hours. INTERVENTIONS: Two clinicians used the instrument to independently review records in each cohort for diagnostic errors, defined as missed opportunities to make a correct or timely diagnosis. Errors were confirmed by senior expert clinicians. MEASUREMENTS AND MAIN RESULTS: Diagnostic errors were present in 26 of 214 high-risk patient records (12.1%; 95% CI, 8.2-17.5%) with the following frequency distribution: cohort 1: two of 16 (12.5%); cohort 2: one of 41 (2.4%); cohort 3: 13 of 44 (29.5%); and cohort 4: 10 of 113 (8.8%). Overall initial reviewer agreement was 93.6% (κ, 0.72). Infections and neurologic conditions were the most commonly missed diagnoses across all high-risk cohorts (16/26). CONCLUSIONS: The Safer Dx Instrument has high reliability and validity for diagnostic error detection when used in high-risk pediatric care settings. With further validation in additional clinical settings, it could be useful to enhance learning and feedback about diagnostic safety in children.

Accuracy of the Safer Dx Instrument to Identify Diagnostic Errors in Primary Care.

IMPORTANCE: Diagnostic errors are common and harmful, but difficult to define and measure. Measurement of diagnostic errors often depends on retrospective medical record reviews, frequently resulting in reviewer disagreement. OBJECTIVES: We aimed to test the accuracy of an instrument to help detect presence or absence of diagnostic error through record reviews. DESIGN: We gathered questions from several previously used instruments for diagnostic error measurement, then developed and refined our instrument. We tested the accuracy of the instrument against a sample of patient records (n = 389), with and without previously identified diagnostic errors (n = 129 and n = 260, respectively). RESULTS: The final version of our instrument (titled Safer Dx Instrument) consisted of 11 questions assessing diagnostic processes in the patient-provider encounter and a main outcome question to determine diagnostic error. In comparison with the previous sample, the instrument yielded an overall accuracy of 84 %, sensitivity of 71 %, specificity of 90 %, negative predictive value of 86 %, and positive predictive value of 78 %. All 11 items correlated significantly with the instrument's error outcome question (all p values ≤ 0.01). Using factor analysis, the 11 questions clustered into two domains with high internal consistency (initial diagnostic assessment, and performance and interpretation of diagnostic tests) and a patient factor domain with low internal consistency (Cronbach's alpha coefficients 0.93, 0.92, and 0.38, respectively). CONCLUSIONS: The Safer Dx Instrument helps quantify the likelihood of diagnostic error in primary care visits, achieving a high degree of accuracy for measuring their presence or absence. This instrument could be useful to identify high-risk cases for further study and quality improvement.

Lack of timely follow-up of abnormal imaging results and radiologists' recommendations.

PURPOSE: Abnormal imaging results may not always lead to timely follow-up. We tested whether certain aspects of communication in radiology reports influence the response of the referring providers, and hence follow-up on abnormal findings. METHODS: We focused on 2 communication-related items that we hypothesized could affect follow-up: expressions of doubt in the radiology report, and recommendations for further imaging. After institutional review board approval, we conducted a retrospective review of 250 outpatient radiology reports from a multispecialty ambulatory clinic of a tertiary-care Veterans Affairs facility. The selected studies included 92 cases confirmed to lack timely follow-up (ie, further tests or consultations, treatment, and/or communication to the patient within 4 weeks), as determined in a previous study. An additional 158 cases with documented timely follow-up served as controls. Doubt in the narrative was measured by the presence of key phrases (eg, "unable to exclude," "cannot exclude," "cannot rule out," "possibly," and "unlikely"), in the absence of which we used reviewer interpretation. A physician blinded to follow-up outcomes collected the data. RESULTS: Patients whose reports contained recommendations for further imaging were more likely to have been lost to follow-up at 4 weeks compared with patients without such recommendations (P = .01). Language in the report suggestive of doubt did not affect the timeliness of follow-up (P = .59). CONCLUSIONS: Abnormal imaging results with recommendations for additional imaging may be more vulnerable to lack of timely follow-up. Additional safeguards, such as tracking systems, should be developed to prevent failure to follow up on such results.