The 1999 Institute of Medicine report increased the national

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1 CAP Laboratory Improvement Programs Patient Safety in Anatomic Pathology Measuring Discrepancy Frequencies and Causes Stephen S. Raab, MD; Raouf E. Nakhleh, MD; Stephen G. Ruby, MD Context. Anatomic pathology discrepancy frequencies have not been rigorously studied. Objective. To determine the frequency of anatomic pathology discrepancies and the causes of these discrepancies. Design. Participants in the College of American Pathologists Q-Probes program self-reported the number of anatomic pathology discrepancies in their laboratories by prospectively performing secondary review (post sign-out) of 1 surgical pathology or cytology specimens. Reasons for the secondary review included conferences, external review, internal quality assurance policy, and physician request. Participants. Seventy-four laboratories self-reported data. Main Outcome Measures. Frequency of anatomic pathology discrepancy; type of discrepancy (ie, change in margin status, change in diagnosis, change in patient information, or typographic error); effect of discrepancy on patient outcome (ie, no harm, near miss, or harm); and clarity of report. Results. The mean and median laboratory discrepancy frequencies were 6.7 and 5.1, respectively. Forty-eight percent of all discrepancies were due to a change within the same category of interpretation (eg, 1 tumor type was changed to another tumor type). Twenty-one percent of all discrepancies were due to a change across categories of interpretation (eg, a benign diagnosis was changed to a malignant diagnosis). Although the majority of discrepancies had no effect on patient care, 5.3 had a moderate or marked effect on patient care. Conclusions. This study establishes a mean multi-institutional discrepancy frequency (related to secondary review) of 6.7. (Arch Pathol Lab Med. 25;129: ) The 1999 Institute of Medicine report increased the national awareness of medical errors and patient safety. 1 Anatomic pathology errors are reported to occur in 1 to 43 of all anatomic pathology specimens, 2 19 and this exceptionally wide range depends on the methods of detection and the definition of what counts as an error. On review of the literature, Raab 2 estimated that the mean anatomic pathology error frequency ranged from 1 to 5, although this frequency was largely based on studies using single-institution data. No large-scale, multi-institutional anatomic pathology error studies have been conducted, and information on the effect of anatomic pathology error on patient outcome is generally lacking. Error detection in anatomic pathology most often depends on some form of secondary case review. 2 Secondary case review has been built into some pathology quality assurance practices (eg, review of a set percentage of cases, intradepartmental difficult case conferences, cytolog- Accepted for publication December 2, 24. From the Department of Pathology, University of Pittsburgh, Pittsburgh, Pa (Dr Raab); the Department of Pathology, St Luke s Hospital/ Mayo Clinic, Jacksonville, Fla (Dr Nakhleh); and the Department of Pathology, Palos Community Hospital, Palos Heights, Ill (Dr Ruby). The authors have no relevant financial interest in the products or companies described in this article. Reprints: Stephen S. Raab, MD, Department of Pathology, University of Pittsburgh, UPMC Shadyside Hospital, 515 Centre Ave, Pittsburgh, PA ( raabss@msx.upmc.edu). ic-histologic correlation, or review of all malignancies). Secondary case review also occurs in hospital patient-centered conferences (eg, tumor board); external consultation practices; or at the behest of clinicians, who may initiate communication when the pathology report does not correlate with the clinical findings. An error detected by 1 of these processes may be referred to as a discrepancy or a difference in interpretation or reporting between 2 pathologists. Error detection frequencies based on the different methods of secondary review have been variably studied. For example, the College of American Pathologists (CAP) has intensively studied gynecologic cytologic-histologic correlation and reported that paired cervical-vaginal cytology-biopsy specimens had a sensitivity and specificity of 89.4 and 64.8, respectively Based on nongynecologic cytologic-histologic correlation data, Clary et al 6 reported that 23 of interpretive discrepancies had a major impact on patient outcome. Other methods of secondary review have been studied in less detail. As a consequence, how these methods may be utilized to improve patient safety and be incorporated into laboratory continuous quality improvement programs is unknown. The CAP s Q-Probes program has measured and defined a number of key quality indicators in anatomic and clinical pathology. 21,22 This Q-Probes study is the first multi-institutional study to measure and to document anatomic pathology discrepancy frequencies and the effect of these discrepancies on patient outcome. Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al 459

2 Table 1. Definition of Discrepancy Discrepancy: A discrepancy has occurred if there is any difference between the original interpretation and the interpretation after the second review. Discrepancies were further classified by cause into one of the following categories: Change in margin status: The interpretation of the margin status was changed from benign to malignant or vice versa. Change in categoric interpretation: An interpretation was changed from one categoric diagnosis, such as benign, to another categoric diagnosis, such as malignant. For purposes of this study, interpretations were classified within categories that were graded by their probability of a malignant clinical outcome (eg, a benign diagnosis was assigned a 1; atypical, 2; suspicious, 3; and malignant, 4). We considered a difference of 2 or more steps between the original and the review interpretation as a discrepancy. For example, if the original diagnosis was benign, and the review diagnosis was malignant, the difference in steps between these 2 diagnoses was 4 1 3, and this case was considered discrepant. If the step difference between the original and review interpretations was 1, we decided that a discrepancy had not occurred. Change within the same category of interpretation: An interpretation was changed from one benign interpretation to another benign interpretation or from one malignant interpretation to another malignant interpretation. A change from one tumor type to another fell within this category. For example, if the original interpretation was adenocarcinoma and the review diagnosis was epithelioid sarcoma, this case was placed within this category of discrepancy. Change in patient information: There was a change in the organ site, such as the left ovary to the right ovary. Typographic error Table 2. Definitions of Effects of Discrepancies Effect of discrepancy on patient management: Discrepancies were classified into the following categories based on patient outcome: Harm (significant event): A discrepancy that resulted in patient harm (eg, inappropriate treatment, loss of life or limb, psychological event). The effect of the significant event on patient outcome was assessed using a 3-point Likert scale (1 severe effect, 2 moderate effect, 3 mild effect). The pathologists performing the review judged the significance of the event. Near miss: A discrepancy that was detected before harm occurred, such as a discrepancy that was detected at a clinical pathologic conference before treatment was initiated. No harm: A discrepancy that did not result in patient harm, such as a typographic error that had no bearing on patient management. MATERIALS AND METHODS Laboratories enrolled in the CAP s volunteer Q-Probes quality improvement program participated in this study in 23. The Q- Probes program and the format for data collection and handling have been previously described in detail. 21 Participants prospectively identified 1 consecutive surgical pathology or cytology specimens that were reviewed by a second pathologist after a first pathologist had signed out that case. In order to standardize the data-collection process across all participating laboratories, pertinent terms were defined (Tables 1 and 2). For each case, the participating laboratory recorded the specimen type (surgical pathology or cytology), organ or anatomic site (chosen from a specified list), primary reason for secondary review (chosen from a specified list), clarity of the report, presence or absence of a discrepancy (Table 1), effect of discrepancy on patient outcome (Table 2), and modification of report (if performed). We subclassified discrepancies into several main groups of causes that have been previously described in the pathology literature. 2 The detection of particular discrepancy subtypes depends partly on the method of secondary review, described in more detail later. For example, change in margin status is more likely to be detected by a frozen-permanent section review, and change in categoric interpretation is more likely to be detected by cytologic-histologic correlation review. We arbitrarily chose a disagreement of 2 steps as constituting a categoric interpretation discrepancy, although even a 1-step discrepancy is an error. Raab 2 reported that 2-step discrepancies have a much greater probability of clinical significance compared with 1-step discrepancies. In addition, because interobserver variability studies have shown that 1-step discrepancies are much more common, we did not want to collect data on a large subset of cases that had little effect on patient care. 2 For changes in categoric interpretation, the original and review diagnoses were recorded. The taxonomy of the effect of a pathology discrepancy on patient outcome was based on the medical patient safety literature, which uses a taxonomy related to the effect of a failure of a planned action to be completed or the use of a wrong plan to achieve an aim. 1 Diagnostic error does not fit neatly into the category of an action error, and the resulting outcome of the patient is often difficult to assess. In particular, distinguishing between a no-harm and a near-miss event may be problematic. We defined a near-miss event as an error that was detected before harm occurred; an example is when a diagnostic error was picked up at a conference (or another means of secondary review) before a particular treatment protocol was initiated. In this case, if the error had not been detected, we assume that some degree of harm would have occurred. We recognize that harm (eg, psychologic) may still have occurred in this case, but we classified this event as a near miss, because the ability of the review pathologist to identify this type of harm was limited in this study. We defined a no-harm event as occurring when a diagnostic error occurred that would not cause patient harm even if the error had been undetected. An example of a no-harm event was a typographic error, such as writing the word brest instead of breast in the diagnostic line. We defined a significant event as an error resulting in patient harm. 1 We provided the review pathologist a 3-point Likert scale to grade the severity of this harm, recognizing that this grading was subjective. Grzybicki et al 27 showed that even with more well-defined criteria for patient harm, there is little agreement among pathologists as to the effect of an error on patient outcome; thus, although subclassifying harm needs further study, we wanted to measure the general view of the participant institutions in assessing harm. We did not require the pathologist to perform medical record review but only to assess the error severity based on the information available at the time of detection. In general, the pathologist had some degree of knowledge of the clinical outcome. This information varied depending on the method of detection; for example, more information may be available if a clinician requests secondary review compared to if a cytologic-histologic correlation is performed. Autopsy cases were the only anatomic pathology case type excluded from this study. Multiple specimens with a secondary review from the same case or specimens from different cases associated with the same patient were included in the study. Secondary review is the main method used to detect anatomic pathology errors. The recorded reasons why cases were reviewed were as follows: intradepartmental conference, request by clinician, interdepartmental conference, specified institutional quality 46 Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al

3 assurance policy, and extradepartmental review. These methods encompass the majority of forms of secondary review, although participants also could choose the category of other if none of these methods applied. We chose to examine multiple methods, because single institutions often do not review a sufficient number of cases using a single method for statistical significance testing in the time frame provided by this Q-Probes study. We also wanted to determine if discrepancies were detected at different frequencies and had different clinical import depending on the method of detection. Institutional quality assurance policies include cytologic-histologic correlation, random review, and frozenpermanent section correlation. We recognize that these methods of review detect only a fraction of discrepancies (because in most institutions, the majority of cases do not undergo secondary review) and exclude those errors detected prior to sign-out. However, some of these forms of secondary review are the most likely means to detect clinically significant error, the subcategory of error that some authors believe is the most important to track and eradicate. The clarity of the report question referred to how understandable the original report was perceived to be from the standpoint of the review pathologist. The review pathologist determined the report clarity using a 4-point Likert scale (ie, clear, mildly unclear, moderately unclear, markedly unclear). A limitation in this assessment was that clinicians, who were the users of the diagnostic information, did not perform the analysis, and previous authors have indicated discrepancies between clinician and pathologist impression of report clarity. 28 We also recognize that the clarity assessment was subjective, because definitive criteria of clarity were not provided. The lack of clarity may be an example of error, particularly for reports assessed to be moderately or markedly unclear, because this lack of clarity could result in improper patient management. Laboratories could choose 3 options regarding computerized report modification after a discrepancy was detected: (1) the original report was deleted and replaced with a new report; (2) the original report was marked with a qualifier, and a new report was appended; or (3) the original report was not marked or modified, but a new report was appended. Institutional demographic and practice variable information was obtained by completion of a questionnaire. These data included annual specimen volume, number of institutional practicing pathologists, type and frequency of institutional review conferences (eg, breast, chest, or endocrine conference), and institutional quality assurance methods of secondary review. The discrepancy frequency (expressed as a percentage) was calculated for the aggregate data and for each institution. The discrepancy frequency was calculated as the number of discrepancies divided by the total number of cases reviewed, multiplied by 1. Discrepancies and report clarity assessments were subclassified by organ type (and further broken down by effect on patient outcome). The correlation of the main indicator variable (discrepancy frequency) was assessed for each of the predictor variables separately by using nonparametric Wilcoxon rank sum or Kruskal- Wallis tests. The 2 goodness-of-fit test was used to test for associations between the presence of a discrepancy and other caselevel variables. Statistically significant associations are defined at the P.5 level. The reason for case review was correlated with the effect of the discrepancy on patient outcome. Some participating institutions did not answer all of the questions on the demographics form or on the input forms. These institutions were excluded only from the tabulations and the analyses that required the missing data element. Table 3. Percentile Distribution of Anatomic Pathology Discrepancy Rate All Institutional Percentiles 5th N 1th 25th (Median) 75th 9th Discrepancy rate, RESULTS A total of 74 institutions submitted data for this study. Most institutions (87.8) were located in the United States, with the remainder located in Canada (n 7), Australia (1), and Saudi Arabia (1). Of the participating institutions, 31 were teaching hospitals, and 23 had a pathology residency program. The Joint Commission on Accreditation of Healthcare Organizations inspected the majority of the institutions (68) participating in this study, and the CAP inspected 82 of laboratories contributing data. The participants institutional sizes were as follows: 39.7 had fewer than 15 beds; 39.7, 151 to 3 beds; 9.5, 31 to 45 beds; 3.2, 451 to 6 beds; and 7.9, more than 6 beds. Private nonprofit institutions comprised 54.9 of the institutions; 11.1 were private forprofit institutions; 9.5 were state, county, or city hospitals; 6.3 were university hospitals; 3.2 were federal governmental institutions; and 15.9 were other. Fiftythree percent of the institutions were within a city, 28.1 were suburban, and 15.6 were rural. The annual mean number (and SD) of surgical pathology, nongynecologic cytology, and gynecologic specimens per institution were (19 567), 1898 (2376), and (44 93), respectively. The mean and median numbers of pathologists at each institution were 6 and 4, respectively. The 74 institutions performed secondary review of 6186 anatomic pathology specimens (5268 surgical pathology specimens and 847 cytology specimens), and each institution collected data on a range of from 2 to 1 specimens (median, 99 specimens). In aggregate, 415 discrepancies were reported, and the overall mean anatomic pathology discrepancy frequency was 6.7. The overall mean surgical pathology discrepancy frequency was 6.8 (356 discrepancies of 5255 reviewed cases), and the overall mean cytology discrepancy frequency was 6.5 (55 discrepancies of 844 reviewed cases); neither of the specimen types had a higher discrepancy frequency (P.78). The distribution of the anatomic pathology discrepancy frequencies is listed in Table 3. Higher percentile ranks indicate lower discrepancy frequencies. The number of reviewed specimens, overall discrepancy frequency, and the discrepancy classification by organ type are shown in Table 4. The most common organ types reviewed in this study were female genital tract and breast. None of the organ types had a higher frequency of discrepancy than other organ types (P.15). For the organ types with higher volumes reviewed ( 2 cases), a change in categoric interpretation (ie, an error type more likely to be associated with harm) occurred more frequently in the female genital tract, male genital tract, and lymph node. A change in margin status occurred most frequently in breast specimens. In Table 5, the effect of the discrepancy on patient outcome and the report modification in response to a discrepancy are listed by organ type. Some form of harm was seen in the majority of organs, although specimen type (cytology or surgical pathology) or organ type did not correlate with effect on patient outcome (P.73 and P.83, respectively). Harm was observed in 2.8 (11 cases) of breast specimens and in 25.3 (21 cases) of female genital tract specimens in which a discrepancy was detected. Neither specimen type nor organ type correlated with the Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al 461

4 Table 4. Number of Specimens and Discrepancy by Organ Type Overall Discrepancy, Change in Margin, Change in Categoric Interpretation, Change in Same Category, Change in Patient Information, Typographic Error, Specimens, No. Organ ( of Total) Genital, female 982 (15.9) Breast 796 (12.9) Lung 463 (7.5) Genital, male 355 (5.7) Soft tissue 345 (5.6) Lymph node 288 (4.7) Hepatobiliary 24 (3.9) Urinary tract 181 (2.9) Pharynx 141 (2.3) Endocrine 125 (2.) Bone marrow 17 (1.7) Bone 99 (1.6) Neuropathology 88 (1.4) Kidney 55 (.9) Pancreas 31 (.5) Salivary gland 29 (.5) Spleen 11 (.2) Gastrointestinal and other 1841 (29.8) Total Organ Table 5. Genital, female Breast Lung Genital, male Soft tissue Lymph node Hepatobiliary Urinary tract Pharynx Endocrine Bone marrow Bone Neuropathology Kidney Pancreas Salivary gland Spleen Gastrointestinal and other Effect of Discrepancy on Patient Management and Pathology Response by Organ Type Marked Harm, Moderate Harm, Effect on Patient Outcome Mild Harm, Near Miss, No Harm, Report Change Yes, No, Total report modification in response to a discrepancy (P.15 and P.14, respectively). In Table 6, the clarity of the report is listed by organ type. Markedly and moderately unclear reports were seen infrequently and only in a few specimen types, such as female genital tract, breast, and lung. Because of the large number of cells with a value of, a 2 goodness-of-fit test was not performed. In Table 7, the discrepancy type, original and review interpretations for categoric discrepancies, and the effect of the discrepancy on patient outcome are shown. A change in the same category of diagnosis was the most common discrepancy detected. For changes in categoric interpretation, the review diagnosis tended to be shifted downward to a benign or upward to a malignant diagnosis, and there were fewer nondefinitive (atypical or suspicious) diagnoses compared with the original diagnosis. When a discrepancy occurred, the most common classification, based on patient outcome, was a no-harm event. Anatomic pathology discrepancy specimen-centered variables, including specimen type and origin, discrepancy type, primary reason for review, the effect of discrepancy on patient outcome, and the response to a discrepancy in the form of a report change, were evaluated to identify any associations. The statistically significant associations are shown in Table 8. A request for review directed by a clinician was much more likely to be associated with a discrepancy than all other reasons for review. If a discrepancy occurred, a change in categoric interpretation was more likely to be seen in cytology specimens compared with surgical pathology specimens and related to extradepartmental review compared with all other rea- 462 Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al

5 Table 6. Organ Clear, Genital, female Breast Lung Genital, male Soft tissue Lymph node Hepatobiliary Urinary tract Pharynx Endocrine Bone marrow Bone Neuropathology Kidney Pancreas Salivary gland Spleen Gastrointestinal and other Clarity of Report by Organ Type Mildly Unclear, Moderately Unclear, Markedly Unclear, Total Table 7. Discrepancy Type, the Original and Review Diagnoses for Categoric Discrepancies, and the Effect of Discrepancy on Patient Outcome Discrepancy type Change within same category Change in categoric interpretation Typographic error Change in patient information Change in margin status Original interpretation for categoric discrepancies Benign Atypical Suspicious Malignant Reviewed interpretation for categoric discrepancies Benign Atypical Suspicious Malignant Effect on patient outcome Harm Marked Moderate Mild Near miss No harm Specimens, No. () (1) (47.8) (2.9) (18.5) (9.1) (3.7) (29.8) (32.1) (16.) (16.) (33.3) (25.9) (8.3) (33.3) (16.6) (2.1) (3.2) (11.3) (8.7) (74.7) sons for review. If a near-miss event occurred, the reason for case review was more likely to be extradepartmental review compared with all other reasons for review. Table 9 shows that the reason for case review correlated with patient outcome in discrepant cases (P.2). Harm occurred more frequently in discrepant cases that were reviewed at the request of a clinician (23.5) and interdepartmental conference (25.). Clinician-directed review was the most common method that detected a discrepancy (23. of all cases reviewed). The majority of discrepant cases detected at an intradepartmental conference were associated with no-harm events. Of the 74 institutions, the number that had a conference devoted to breast review was 33; chest, 21; endocrine, 8; gastrointestinal, 22; general surgical, 29; genitourinary tract, 18; gynecologic, 26; head and neck, 16; hematopathology, 2; liver, 15; renal, 18; and tumor board, 6. Institutional quality assurance practices were measured as well: 52 institutions had an intradepartmental conference for difficult cases; 31 reviewed a percentage of cases after sign-out; 22 reviewed all malignancies before sign-out; 19 reviewed a percentage of cases before sign-out; 6 reviewed all malignancies after sign-out; and 1 reviewed all cases before sign-out. Of the institutions that made changes to the reports after an error, 43 issued an amended report and did not retrieve the original report; 3 retrieved the original report, stamped it in error, and filed the report in the chart; 3 destroyed the original reports; and 3 handled the change using other methods. COMMENT This is the first study to determine a baseline anatomic pathology discrepancy frequency across multiple pathology laboratories. Based on secondary pathologist review, the mean anatomic pathology discrepancy frequency (based on cases reviewed through several different methods) was 6.7, and the variability across laboratories was striking, with the 25th and 75th percentiles being 1. and 1., respectively. Discrepancy represents one form of error, and based on literature review of a number of error-detection methods, Raab 2 estimated that the mean laboratory error frequency ranged from 1 to 5. The discrepancy frequency established in this Q-Probes study is based on review of selected cases (a targeted group of cases studied), a bias that may overestimate overall laboratory error. Error frequencies partly depend on the method of case detection, and the more thoroughly one looks for error, the more frequently one will find it. 1,29 As expected, some of the secondary review methods used in this study detected more error than other methods; for example, clinician-directed review detected a discrepancy (23. of cases) more frequently than random review (4.3). In general, methods Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al 463

6 Table 8. Primary reason for review (P.1) Request by clinician All other reasons Discrepancy type: change in categoric interpretation Specimen type (P.1) Cytology Surgical pathology Primary reason for secondary review (P.3) Extradepartmental review Discrepancy type: change in same category of diagnosis Specimen type (P.1) Cytology Surgical pathology Discrepancy type: change in patient information Primary reason for secondary review (P.1) Request by clinician Effect on patient outcome: near miss Primary reason for secondary review (P.1) Extradepartmental review Effect on patient outcome: no harm Primary reason for secondary review (P.1) Intradepartmental review Response to a discrepancy: report change Primary reason for secondary review (P.1) Interdepartmental conference Request by clinician Statistically Significant Associations No. of Specimens No. With Discrepancy Table 9. Reason for Review Correlated With Effect on Patient Outcome Errors Effect on Patient Outcome Reason for Review Detected, No. ( of Cases Reviewed) Harm, No. () Near Miss, No. () No Harm, No. () Total Intradepartmental review Request by clinician Interdepartmental review Selected by quality assurance review Extradepartmental review 47 (7.1) 8 (23.) 48 (4.8) 127 (4.3) 92 (8.6) 2 (5.3) 12 (23.5) 8 (25.) 13 (14.6) 8 (14.) 2 (5.3) 3 (5.9) 2 (6.3) 8 (9.) 12 (21.1) 34 (89.5) 36 (7.6) 22 (68.8) 68 (76.4) 37 (64.9) Total of case review that involve clinical input are a better means to detect error but are harder to perform. Pathologists have studied error frequency using intralaboratory quality assurance methods in some detail. The most commonly studied review method is correlation, such as frozen-permanent section correlation or cytologichistologic correlation, a form of review mandated by the Clinical Laboratory Improvement Amendments of Using this review process and the total number of cases as the denominator, Clary et al 6 reported that 2.26 and.44 of nongynecologic cytology and histology cases were discrepant. This Q-Probes study showed that the error frequency based on extradepartmental conference review was 7.1, whereas Raab et al 3 reported an error frequency of 8.9, with severe significant events occurring in 7. of all errors. McBroom and Ramsay 11 reported that 9. of cases reviewed at a clinicopathologic conference had a change in diagnosis. This similarity in error frequency across studies and across many institutions may indicate a true benchmark. Benchmarking and reducing anatomic pathology error frequency clearly is just beginning, and prior to this study, the benchmarks were based on single-institution or anecdotal data. 2 The correlation of error frequencies with particular secondary review practices and existing laboratory error reduction programs is largely unknown. Lack of subspecialty expertise may contribute to higher error frequencies, although error data detected using extradepartmental specialty academic institution review may be biased and may overreport error. 4,7,31 Underreporting of error because of biased review methods, lack of understandable error taxonomy, and individual fears invariably exists, 464 Arch Pathol Lab Med Vol 129, April 25 Patient Safety in Anatomic Pathology Raab et al

7 but this has not been thoroughly studied in pathology laboratories. Some leading patient safety researchers, such as Resar et al, 32 have argued that error prevention programs should target errors that have an effect on patient outcome, rather than all errors. These Q-Probes study data show that the majority of anatomic pathology discrepancies do not result in harm, similar to the data reported in nonpathology fields. 1 Determining the effect of a pathology error on patient outcome is challenging because of contact and temporal barriers between pathology and clinical care. Thorough medical record review generally is not performed after a pathology error has occurred, and health care systems invariably lack personnel trained in the intricacies of the triad of pathology reporting, patient safety, and assessing patient outcomes. Grzybicki et al 27 reported that even with data from medical record review, pathologists showed poor agreement in determining if harm actually occurred. We used pathologist self-assessment to determine error severity, and acknowledging the biases inherent in this process, we found that 16.6 of all errors resulted in some form of patient harm. This indicates that 1.1 of all anatomic pathology cases that underwent secondary review were associated with a harmful significant event. Because secondary review processes tend to be varied across institutions, the probability is high that a relatively large percentage of pathology errors resulting in harm go undetected. Statistical significance testing did not show that any body site was most likely to be associated with an error. However, some organs (eg, female genital tract and breast) tended to have higher associations with a discrepancy resulting in clinical harm compared with other organs. Using medical chart review to determine clinical follow-up of errors detected through cytologic-histologic correlation, Clary et al 6 reported that the most common cytology specimens associated with harm were pulmonary and breast specimens. In a study examining errors associated with malpractice claims, Troxel and Sabella 15 also identified that diagnostic errors in breast cytology specimens were associated with harm; in addition, they identified other organ or specimen types, such as prostate needle biopsies, Papanicolaou tests, and melanocytic skin lesions, as being associated with errors resulting in harm. In this Q-Probes study, discrepancies detected in cytology specimens were more likely (compared with surgical pathology specimens) to have a 2-step change in diagnosis, and this change often meant that the original diagnosis was either a false-negative or false-positive diagnosis. These types of errors are more likely to have a clinical effect than other types of errors. 2 Harm was more likely to be associated with cases reviewed at the behest of a clinician and cases sent for extradepartmental review. Although researchers have studied anatomic pathology diagnostic variability, the relationship of variability and error is not sufficiently addressed in the pathology literature. Strictly speaking, variability is a form of error, and secondary case review is simply a means to unearth differences in diagnosis or errors. In practice, some pathologists would like to maintain that true diagnostic errors are errors that most reasonable pathologists would agree are errors. However, establishing the true diagnosis is a complex and controversial task (eg, do we use a panel of practicing pathologists or experts?) that has not been well studied in anatomic pathology. Our study did not address methods of establishing the accuracy of the original and review diagnoses. However, some methods of secondary review were performed with knowledge of clinical outcome, which, although biasing the review pathologist (compared with the original pathologist, who lacked this bias), provides a window on the actual effect of the diagnosis. This Q-Probes study recorded errors other than interpretive errors. Typographic errors and changes in patient information infrequently result in harm, but when harm occurs, it may be severe, with far-reaching consequences (eg, switching of patient specimens). Pathology laboratories place checks in the system in order to limit these error types, although these safeguards are generally not formally shared across laboratories. The frequency of marked harm as a result of these errors is known only through small studies or anecdotally, 9,33,34 resulting in a lack of widespread system learning. Our study was not detailed enough to drill down into these error types. The lack of report clarity is an example of error that is difficult to quantify and falls within the realm of communication error. Poor communication is an important source of error in clinical medicine and may result in severe harm 35 ; Dovey et al 25 reported that 5.8 of family practice errors were a result of miscommunication. Report clarity is subjective, and Powsner et al 28 reported that surgeons misunderstood 3 of pathology reports. As expected, in this Q-Probes study, pathologists believed that the majority of reports were clear, and less than 1 were perceived as markedly unclear. This confirms the conclusion by Powsner et al 28 that a communication gap exists between pathologists and clinicians. The fact that clinicians request that a certain percentage of cases be reviewed underscores a potential communication problem but shows as well a functioning means of detecting error. 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