Developing a quality and safety assessment framework for Iran's military hospitals.

BACKGROUND: The first crucial step towards military hospitals performance improvement is to develop a local and scientific tool to assess quality and safety based on the context and aims of military hospitals. This study introduces a Quality and Safety Assessment Framework (Q&SAF) for Iran's military hospitals. METHODS: This is a literature review which continued with a qualitative study. The Q&SAF for Iran's military hospitals was developed initially, through a review of the WHO's framework for hospital performance, literature review (other related framework), review of military hospital-related local documents, consultations with a national and sub-national expert. Finally, the Delphi technique used to finalize the framework. RESULTS: Based on the literature review results; 13 hospital Q&SAF were identified. After reviewing literature review results and expert opinions; Iran's military hospitals Q&SAF was developed with 58 indictors in five dimensions including clinical effectiveness, safety, efficiency, patient-centeredness, and Responsive Management (Command and Control). The efficiency dimension had the highest number of indictors (19 indictors), whereas the patient-centered dimension had the lowest number of indices (4 indictors). CONCLUSION: Regarding the comprehensiveness of the developed assessment framework due to its focus on the majority of quality dimensions and important components of the hospital's performance, it can be used as a useful tool for assessing and continuously improving the quality of hospitals, particularly military hospitals.

[Six Sigma driven QC management in hepatitis C serology]. / La méthodologie six sigma dans la gestion des contrôles de qualité en sérologie de l'hépatite C.

The Westgard quality control (QC) rules are often applied in infectious diseases serology to validate the quality of results, but this requires a reasonable tradeoff between maximum sensitivity to errors and minimum false rejections. This article, in addition to illustrate the six sigma methodology in the QC management of the (anti-HCV Architect®) test, it discusses the main influencing factors on sigma value. Data from low positive and in-kit control materials spreading over 6 months and using four reagent kits, were used to calculate the precision of the test. The difference between the control material reactivity and the cut-off defined the error budget. Sigma values were > 6, which indicates that the method produces four erroneous results per million tests. The application of the six sigma concept made it possible to argue the choice of the new QC strategy (use of 13S rule with one positive control) and to relax the existing QC rules. This work provides a framework for infectious diseases serology laboratories to evaluate tests performances against a quality requirement and design an optimal QC strategy.

Predicting the error magnitude in patient-specific QA during radiotherapy based on ResNet.

BACKGROUND: The error magnitude is closely related to patient-specific dosimetry and plays an important role in evaluating the delivery of the radiotherapy plan in QA. No previous study has investigated the feasibility of deep learning to predict error magnitude. OBJECTIVE: The purpose of this study was to predict the error magnitude of different delivery error types in radiotherapy based on ResNet. METHODS: A total of 34 chest cancer plans (172 fields) of intensity-modulated radiation therapy (IMRT) from Eclipse were selected, of which 30 plans (151 fields) were used for model training and validation, and 4 plans including 21 fields were used for external testing. The collimator misalignment (COLL), monitor unit variation (MU), random multi-leaf collimator shift (MLCR), and systematic MLC shift (MLCS) were introduced. These dose distributions of portal dose predictions for the original plans were defined as the reference dose distribution (RDD), while those for the error-introduced plans were defined as the error-introduced dose distribution (EDD). Different inputs were used in the ResNet for predicting the error magnitude. RESULTS: In the test set, the accuracy of error type prediction based on the dose difference, gamma distribution, and RDD + EDD was 98.36%, 98.91%, and 100%, respectively; the root mean squared error (RMSE) was 1.45-1.54, 0.58-0.90, 0.32-0.36, and 0.15-0.24; the mean absolute error (MAE) was 1.06-1.18, 0.32-0.78, 0.25-0.27, and 0.11-0.18, respectively, for COLL, MU, MLCR and MLCS. CONCLUSIONS: In this study, error magnitude prediction models with dose difference, gamma distribution, and RDD + EDD are established based on ResNet. The accurate prediction of the error magnitude under different error types can provide reference for error analysis in patient-specific QA.

A TPS integrated machine learning tool for predicting patient-specific quality assurance outcomes in volumetric-modulated arc therapy.

PURPOSE: Machine learning (ML) models have been demonstrated to be beneficial for optimizing the workload of patient-specific quality assurance (PSQA). Implementing them in clinical routine frequently requires third-party applications beyond the treatment planning system (TPS), slowing down the workflow. To address this issue, a PSQA outcomes predictive model was carefully selected and validated before being fully integrated into the TPS. MATERIALS AND METHODS: Nine ML algorithms were evaluated using cross-validation. The learning database was built by calculating complexity metrics (CM) and binarizing PSQA results into "pass"/"fail" classes for 1767 VMAT arcs. The predictive performance was evaluated using area under the ROC curve (AUROC), sensitivity, and specificity. The ML model was integrated into the TPS via a C# script. Script-guided reoptimization impact on PSQA and dosimetric results was evaluated on ten VMAT plans with "fail"-predicted arcs. Workload reduction potential was also assessed. RESULTS: The selected model exhibited an AUROC of 0.88, with a sensitivity and specificity exceeding 50 % and 90 %, respectively. The script-guided reoptimization of the ten evaluated plans led to an average improvement of 1.4 ± 0.9 percentage points in PSQA results, while preserving the quality of the dose distribution. A yearly savings of about 140 h with the use of the script was estimated. CONCLUSIONS: The proposed script is a valuable complementary tool for PSQA measurement. It was efficiently integrated into the clinical workflow to enhance PSQA outcomes and reduce PSQA workload by decreasing the risk of failing QA and thereby, the need for repeated replanning and measurements.

Quality assurance framework for rapid automatic analysis deployment in medical imaging.

PURPOSE: Automatic image analysis algorithms have an increasing role in clinical quality assurance (QA) in medical imaging. Although the implementation of QA calculation algorithms may be straightforward at the development level, actual deployment of a new method to clinical routine may require substantial additional effort from supporting services. We sought to develop a multimodal system that enables rapid implementation of new QA analysis methods in clinical practice. METHODS: The QA system was built using freely available open-source software libraries. The included features were results database, database interface, interactive user interface, e-mail error dispatcher, data processing backend, and DICOM server. An in-house database interface was built, providing the developers of analyses with simple access to the results database. An open-source DICOM server was used for image traffic and automatic initiation of modality-specific QA image analyses. RESULTS: The QA framework enabled rapid adaptation of new analysis methods to automatic image processing workflows. The system provided online data review via an easily accessible user interface. In case of deviations, the system supported simultaneous review of the results for the user and QA expert to trigger corrective actions. In particular, embedded error thresholds, trend analyses, and error-feedback channels were provided to facilitate continuous monitoring and to enable pre-emptive corrective actions. CONCLUSION: An effective and novel QA framework incorporating easy adaptation and scalability to automated image analysis methods was developed. The framework provides an efficient and responsive web-based tool to manage the normal operation, trends, errors, and abnormalities in medical image quality.

Machine Log File and Calibration Errors-based Patient-specific Quality Assurance (QA) for Volumetric Modulated Arc Therapy (VMAT).

INTRODUCTION: Dose reconstructed based on linear accelerator (linac) log-files is one of the widely used solutions to perform patient-specific quality assurance (QA). However, it has a drawback that the accuracy of log-file is highly dependent on the linac calibration. The objective of the current study is to represent a new practical approach for a patient-specific QA during Volumetric modulated arc therapy (VMAT) using both log-file and calibration errors of linac. METHODS: A total of six cases, including two head and neck neoplasms, two lung cancers, and two rectal carcinomas, were selected. The VMAT-based delivery was optimized by the TPS of Pinnacle^3 subsequently, using Elekta Synergy VMAT linac (Elekta Oncology Systems, Crawley, UK), which was equipped with 80 Multi-leaf collimators (MLCs) and the energy of the ray selected at 6 MV. Clinical mode log-file of this linac was used in this study. A series of test fields validate the accuracy of log-file. Then, six plans of test cases were delivered and log-file of each was obtained. The log-file errors were added to the corresponding plans through the house script and the first reconstructed plan was obtained. Later, a series of tests were performed to evaluate the major calibration errors of the linac (dose-rate, gantry angle, MLC leaf position) and the errors were added to the first reconstruction plan to generate the second reconstruction plan. At last, all plans were imported to Pinnacle and recalculated dose distribution on patient CT and ArcCheck phantom (SUN Nuclear). For the former, both target and OAR dose differences between them were compared. For the latter, γ was evaluated by ArcCheck, and subsequently, the surface dose differences between them were performed. RESULTS: Accuracy of log-file was validated. If error recordings in the log file were only considered, there were four arcs whose proportion of control points with gantry angle errors more than ± 1°larger than 35%. Errors of leaves within ± 0.5 mm were 95% for all arcs. The distinctness of a single control point MU was bigger, but the distinctness of cumulative MU was smaller. The maximum, minimum, and mean doses for all targets were distributed between -6.79E-02-0.42%, -0.38-0.4%, 2.69E-02-8.54E-02% respectively, whereas for all OAR, the maximum and mean dose were distributed between -1.16-2.51%, -1.21-3.12% respectively. For the second reconstructed dose: the maximum, minimum, and mean dose for all targets was distributed between 0.0995~5.7145%, 0.6892~4.4727%, 0.5829~1.8931% separately. Due to OAR, maximum and mean dose distribution was observed between -3.1462~6.8920%, -6.9899~1.9316%, respectively. CONCLUSION: Patient-specific QA based on the log-file could reflect the accuracy of the linac execution plan, which usually has a small influence on dose delivery. When the linac calibration errors were considered, the reconstructed dose was closer to the actual delivery and the developed method was accurate and practical.

[Quality characteristics and relevance to care of psychodynamic training outpatient clinics:The QVA Project]. / Qualitätsmerkmale und Versorgungsrelevanz psychodynamischer Ausbildungsambulanzen: Das QVA-Projekt.

Introduction: Quality assurance (QA) in outpatient psychotherapy is currently undergoing a process of change. Hitherto, QA has been conducted by means of an expert review procedure (the so-called "Gutachterverfahren"), inter- and supervision as well as further mandatory training. Data-based QA systems have been increasingly discussed in recent years. On behalf of the G-BA, the IQTIG has recently published a draft of a legally binding QA procedure, which has, however, raised substantial concerns and resistance. Design: TheQVA project has two objectives. First, it provides participating training outpatient clinics with a data-driven QA system that enables an automated and risk-adjusted overall evaluation based on relevant patient and referral parameters. Second, the data is used to conduct research on important issues regarding the relevant psychotherapeutic care provided by outpatient clinics. Results: Since the start of data collection in 2022, n = 2058 patients have been recruited so far (March 2023), and a complete baseline diagnostic report has been generated for n = 1112 patients. The cross-sectional analyses of all patients assessed so far show a high burden of depression, interpersonal problems and impaired quality of life with severe impairment of personality functions, pronounced conflict diagnosis and high utilization of inpatient and day hospital treatments. Discussion: This paper describes an easy-to-implement data-based QA system for psychodynamic training outpatient clinics, while at the same time allowing for the examination of healthcare- relevant questions in a large sample. The first experiences show that the system works technically stable and was well-received by the participating outpatient clinics.

Evaluation of a high resolution diode array for CyberKnife quality assurance.

PURPOSE: The CyberKnife quality assurance (QA) program relies mainly on the use of radiochromic film (RCF). We aimed at evaluating high-resolution arrays of detectors as an alternative to films for CyberKnife machine QA. METHODS: This study will test the SRS Mapcheck (Sun Nuclear, Melbourne, Florida, USA) diode array and its own software, which allows three tests of the CyberKnife QA program to be performed. The first one is a geometrical accuracy test based on the delivery of two orthogonal beams (Automated Quality Assurance, AQA). Besides comparing the constancy and repeatability of both methods, known errors will be introduced to check their sensitivity. The second checks the constancy of the iris collimator field sizes (Iris QA). Changes in the field sizes will be introduced to study the array sensitivity. The last test checks the correct positioning of the multileaf collimator (MLC). It will be tested introducing known systematic displacements to whole banks and to single leaves. RESULTS: The results of the RCF and diode array were equivalent (maximum differences of 0.18 ± 0.14 mm) for the AQA test, showing the array a higher reproducibility. When known errors were introduced, both methods behaved linearly with similar slopes. Regarding Iris QA, the array measurements are highly linear when changes in the field sizes are introduced. Linear regressions show slopes of 0.96-1.17 with r2 above 0.99 in all field sizes. Diode array seems to detect changes of 0.1 mm. In MLC QA, systematic errors of the whole bank of leaves were not detected by the array, while single leaf errors were detected. CONCLUSIONS: The diode array is sensitive and accurate in the AQA and Iris QA tests, which give us the possibility of substituting RCF with a diode array. QA would be performed faster than using the film procedure, obtaining reliable results. Regarding the MLC QA, the inability to detect systematic displacements make it difficult to confidently use the detector.

Monitoring performance in laparoscopic gastric bypass surgery using risk-adjusted cumulative sum at 2 high-volume centers.

BACKGROUND: Traditional surgical outcomes are measured retrospectively and intermittently, limiting opportunities for early intervention. OBJECTIVES: The objective of this study was to use risk-adjusted cumulative sum (RA-CUSUM) to track perioperative surgical outcomes for laparoscopic gastric bypass. We hypothesized that RA-CUSUM could identify performance variations between surgeons. SETTING: Two mid-Atlantic quaternary care academic centers. METHODS: Patient-level data from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) were abstracted for laparoscopic gastric bypasses performed by 3 surgeons at 2 high-volume centers from 2014 to 2021. Estimated probabilities of serious complications, reoperation, and readmission were derived from the MBSAQIP risk calculator. RA-CUSUM curves were generated to signal observed-to-expected odds ratios (ORs) of 1.5 (poor performance) and .5 (superior performance). Control limits were set based on a false positive rate of 5% (α = .05). RESULTS: We included 1192 patients: Surgeon A = 767, Surgeon B = 188, and Surgeon C = 237. Overall rates of serious complications, 30-day reoperations, and 30-day readmissions were 3.9%, 2.5%, and 5.2% respectively, with expected rates of 4.7%, 2.2%, and 5.8%. RA-CUSUM signaled lower-than-expected (OR < .5) rates of readmission and serious complication in Surgeon A, and higher-than-expected (OR > 1.5) readmission rate in Surgeon C. Surgeon A further demonstrated an early period of higher-than-expected (OR > 1.5) reoperation rate before April 2015, followed by superior performance thereafter (OR < .5). Surgeon B's performance generally reflected expected standards throughout the study period. CONCLUSIONS: RA-CUSUM adjusts for clinical risk factors and identifies performance outliers in real-time. This approach to analyzing surgical outcomes is applicable to quality improvement, root-cause analysis, and surgeon incentivization.

The effect of dose gradients on gamma comparison insensitivity in patient specific QA comparisons.

BACKGROUND: While many have speculated on the reasons for gamma comparison insensitivity for patient-specific quality assurance analysis, the true reasons for insensitivity have not yet been elucidated. Failing to understand the reasons for this technique's insensitivity limits our ability to either improve the gamma metric to increase sensitivity of the comparison or the capacity to develop new comparison techniques that circumvent the limitations of the gamma comparison. PURPOSE: To understand the underlying cause(s) for gamma comparison insensitivity and determine if simple plan characteristics can quantitatively predict for gamma comparison sensitivity. METHODS: Known MLC and MU errors of varying magnitudes were induced on simple test fields to preliminarily investigate where gamma failures first begin to appear as error magnitude is increased. Gamma value maps between error-induced plan calculations and error-free plan calculations were created for 20 IMRT and 20 VMAT cases, each on three different detector geometries-ArcCHECK, MapCHECK, and Delta4. Gamma value maps were qualitatively compared to dose-gradient maps, and quantitative comparisons were performed between various plan descriptors and the computed gamma sensitivity for five different classes of induced errors were utilized to determine if any plan descriptor could predict the gamma sensitivity on a case-by-case basis. All comparisons were performed in a calculation-only scenario to remove uncertainties introduced by comparisons made with real patient specific QA measurements. RESULTS: Gamma value maps with increasing induced error magnitude illustrated that gamma comparisons fail first in high-dose, low-gradient regions of the field. Conversely, in areas of high gradient, gamma values typically remain low, even in the presence of large errors, regardless of detector geometry and gamma normalization setting. Thus, the complex, and often overlapping, high dose gradients in plans appear to be a limiting factor in gamma comparison sensitivity as the number of points along these gradients may often outnumber the points available for failing the comparison in lower gradient regions of the field. None of the simple plan descriptors studied were able to quantitively predict gamma comparison sensitivity, suggesting that quantitatively predicting the sensitivity of gamma comparisons on a case-by-case basis may require a combination of multiple factors or metrics not studied here. CONCLUSIONS: Simple plan descriptors and the number of points in high-dose, low-gradient regions of the field did not quantitively predict for gamma comparison sensitivity. However, it is clear from gradient and gamma value maps that gamma comparisons fail first in high-dose, low-gradient regions of the field in the presence of known induced errors, which we have shown to be independent of detector geometry and gamma comparison normalization setting. Gamma comparison sensitivity is thus limited by the ever-increasing complexity of plans and is particularly important to consider as treatment volumes become smaller and the complexity of overlapping plan gradients increases. This suggests that new methods for patient-specific QA comparisons are required to circumvent this limitation.

Tools for large-scale data analytics of an international multi-center study in radiation oncology for cervical cancer.

PURPOSE: To develop and implement a software that enables centers, treating patients with state-of-the-art radiation oncology, to compare their patient, treatment, and outcome data to a reference cohort, and to assess the quality of their treatment approach. MATERIALS AND METHODS: A comprehensive data dashboard was designed, which al- lowed holistic assessment of institutional treatment approaches. The software was tested in the ongoing EMBRACE-II study for locally advanced cervical cancer. The tool created individualized dashboards and automatic analysis scripts, verified pro- tocol compliance and checked data for inconsistencies. Identified quality assurance (QA) events were analysed. A survey among users was conducted to assess usability. RESULTS: The survey indicated favourable feedback to the prototype and highlighted its value for internal monitoring. Overall, 2302 QA events were identified (0.4% of all collected data). 54% were due to missing or incomplete data, and 46% originated from other causes. At least one QA event was found in 519/1001 (52%) of patients. QA events related to primary study endpoints were found in 16% of patients. Sta- tistical methods demonstrated good performance in detecting anomalies, with precisions ranging from 71% to 100%. Most frequent QA event categories were Treatment Technique (27%), Patient Characteristics (22%), Dose Reporting (17%), Outcome 156 (15%), Outliers (12%), and RT Structures (8%). CONCLUSION: A software tool was developed and tested within a clinical trial in radia- tion oncology. It enabled the quantitative and qualitative comparison of institutional patient and treatment parameters with a large multi-center reference cohort. We demonstrated the value of using statistical methods to automatically detect implau- sible data points and highlighted common pitfalls and uncertainties in radiotherapy for cervical cancer.

Simple quality assurance based on filtered back projection for geometrical/irradiation accuracy in single-isocenter multiple-target stereotactic radiotherapy.

In single-isocenter multiple-target stereotactic radiotherapy (SIMT-SRT), it is difficult to evaluate both the geometrical accuracy and absorbed dose measurement when irradiating off-isocenter targets. This study aimed to develop a simple quality assurance (QA) method to evaluate off-isocenter irradiation position accuracy in SIMT-SRT and compare its feasibility with that of a commercial device. First, we created two types of inserts and metallic balls with a diameter of 5 mm to be inserted into a commercially available phantom (SIMT phantom). Second, we developed a dedicated analysis software using Python for the Winston-Lutz test (WLT). Third, an image processing software, including the filtered back-projection algorithm, was developed to analyze the images obtained using an electronic portal imaging device (EPID). Fourth, the feasibility of our method was evaluated by comparing it with the results of WLT using two commercially available phantoms: WL-QA and MultiMet-WL cubes. Notably, 92% of the results in one-dimensional deviations were within 0.26 mm (EPID pixel width). The correlation coefficients were 0.52, 0.92, and 0.96 in the left-right, superior-inferior, and anterior-posterior directions, respectively. In the WLT, a maximum two-dimensional deviation of 0.70 mm was detected in our method, while the deviation in the other method was within 0.5 mm. The advantage of our method is that it can evaluate the geometrical accuracy at any gantry angle during dynamic rotation irradiation using a filtered back-projection algorithm, even if the target is located off the isocenter. Our method can perform WLT at arbitrary positions and is suitable for the QA of dynamic rotation irradiation using an EPID.

Dosimetric validation of a GPU-based dose engine for a fast in silico patient-specific quality assurance program in light ion beam therapy.

BACKGROUND: With rapid evolutions of fast and sophisticated calculation techniques and delivery technologies, clinics are almost facing a daily patient-specific (PS) plan adaptation, which would make a conventional experimental quality assurance (QA) workflow unlikely to be routinely feasible. Therefore, in silico approaches are foreseen by means of second-check independent dose calculation systems possibly handling machine log-files. PURPOSE: To validate the in-house developed GPU-dose engine, FRoG, for light ion beam therapy (protons and carbon ions) as a second-check independent calculation system and to integrate machine log-file analysis into the patient-specific quality assurance (PSQA) program. METHODS: Spot sizes, depth-dose distributions, and absolute dose calibrations were configured into FRoG and a set of nine regular-shaped targets in combination with more than 170 clinical treatment fields were tested against pinpoint ionization chamber measurements. Both the treatment planning system DICOM RTplans and machine treatment log-files were used as input for the dose kernel in water, and a 3D local γ (1 mm/2%) index was used as the main evaluation metric. RESULTS: Calculated configuration data matched experimental measurements with submillimetric agreement. For regular-shaped targets, the unsigned average relative difference between calculated and measured dose values was less than 2% for both protons and carbon ions. The mean γ passing rate (PR) was around 98% for both particle species. For clinical treatment beams, DICOM-based recalculations showed a γ-PR more than 99% for both particle species. The same level of agreement was preserved for protons when moving to log-file-based recalculations. A score of around 95% was registered for carbon ion beams, once excluding low-quality machine log-files. Unsigned average relative difference against acquired data was less than 2% also for real clinical beams. CONCLUSIONS: FRoG was proven as an accurate and reliable tool for PSQA in scanning light ion beam therapy. The proposed method allows for an extremely efficient workflow, without compromising the quality of the plan verification procedure.

Assessing a New Prescreening Score for the Simplified Evaluation of the Clinical Quality and Relevance of eHealth Apps: Instrument Validation Study.

BACKGROUND: In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution. OBJECTIVE: We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions. METHODS: The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution's targeted population size, the level of clinical assessment, and information about the provider. RESULTS: In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33). CONCLUSIONS: This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

The value of monitoring amended reports in cytopathology quality programs: A biennial review.

BACKGROUND: Quality and safety are the foundation of the practice of cytopathology. Review of key performance indicator (KPI) data can shine a light on laboratory vulnerabilities and potential areas for targeted improvement. The rate and content of amendment reports is a frequently monitored KPI in anatomic pathology, but few have studied its value in cytopathology. The goal of this study was to examine the frequency, classification, and outcome of amendments for a large cytopathology laboratory. METHODS: All amendment reports issued for cases during a 2-year period from July 2019 to June 2021 were included in the study. Amendments were classified into three error type root causes: Specimen Identification Error, General Report Defects, and Diagnostic Error. RESULTS: A total of 202 amendment reports were issued equating to a rate of 0.275%. A total of 83 (41.1%) were gynecologic cases and 119 (58.9%) were nongynecologic cases. Within the gynecologic cases, 13 (15.7%) cases were due to Specimen Identification Error, 13 (15.7%) cases were due to Diagnostic Error, and 57 (68.7%) cases were due to General Report Defects. Within the nongynecologic cases, 15 (12.6%) cases were due to Specimen Identification Error, 30 (25.2%) cases were due to General Report Defects, and 74 (62.2%) cases were due to Diagnostic Error with 32 of these due to true diagnostic change. Discovery methods included following re-review after additional clinical information was provided, reinterpretation after additional ancillary testing was performed, or conference review. There was no correlation with years in practice. CONCLUSIONS: Studying amendment reports is an underrecognized and valuable quality assurance tool. Amendments can help provide information about types of errors, monitor laboratory processes, and help guide quality improvement endeavors.

Assessment of National External Quality Assurance Programme of Pakistan as a tool for improving quality of lab results among participating laboratories.

OBJECTIVE: To assess the impact of the National External Quality Assessment Programme of Pakistan NEQAPP in improving the quality of laboratory results among the participating laboratories. METHODS: The cross-sectional observational study was conducted from July to December 2020 at the Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan, in association with the National Quality Assurance Programme of Pakistan. A survey questionnaire was developed and sent to the participating laboratories via email. Frequencies of their responses were calculated and data was analysed using SPSS 21. RESULTS: Of the 150 laboratories approached, 145(96.6%) responded. Among them, 140 (96.6%) laboratories were satisfied by the information provided on the programme's portal, 123(84.8%s) were pleased with the responsiveness of the programme manager, 140(96.6%) reported quality of services had improved after participation in the programme, 129(89%) indicated that the clinician's confidence had enhanced, and 122(84%) said the participation in the programme had improved the credibility of their respective of laboratories. CONCLUSIONS: The National External Quality Assessment Programme of Pakistan was found to have significantly contributed in improving the quality of laboratory results among the participating laboratories.

Methodologic and Reporting Quality of Economic Evaluations in Hand and Wrist Surgery: A Systematic Review.

BACKGROUND: Economic evaluations can inform decision-making; however, previous publications have identified poor quality of economic evaluations in surgical specialties. METHODS: Study periods were from January 1, 2006, to April 20, 2020 (methodologic quality) and January 1, 2014, to April 20, 2020 (reporting quality). Primary outcomes were methodologic quality [Guidelines for Authors and Peer Reviewers of Economic Submissions to The BMJ (Drummond's checklist), 33 points; Quality of Health Economic Studies (QHES), 100 points; Consensus on Health Economic Criteria (CHEC), 19 points] and reporting quality (Consolidated Health Economic Evaluation Standards (CHEERS) statement, 24 points). RESULTS: Forty-seven hand economic evaluations were included. Partial economic analyses (i.e., cost analysis) were the most common (n = 34; 72 percent). Average scores of full economic evaluations (i.e., cost-utility analysis and cost-effectiveness analysis) were: Drummond's checklist, 27.08 of 33 (82.05 percent); QHES, 79.76 of 100 (79.76 percent); CHEC, 15.54 of 19 (81.78 percent); and CHEERS, 20.25 of 24 (84.38 percent). Cost utility analyses had the highest methodologic and reporting quality scores: Drummond's checklist, 28.89 of 35 (82.54 percent); QHES, 86.56 of 100 (86.56 percent); CHEC, 16.78 of 19 (88.30 percent); and CHEERS, 20.8 of 24 (86.67 percent). The association (multiple R) between CHEC and CHEERS was strongest: CHEC, 0.953; Drummond's checklist, 0.907; and QHES, 0.909. CONCLUSIONS: Partial economic evaluations in hand surgery are prevalent but not very useful. The Consensus on Health Economic Criteria and Consolidated Health Economic Evaluation Standards should be used in tandem when undertaking and evaluating economic evaluation in hand surgery.

A population-based study of administrative data linkage to measure melanoma surgical and pathology quality.

BACKGROUND: Continuous quality improvement is important for cancer systems. However, collecting and compiling quality indicator data can be time-consuming and resource-intensive. Here we explore the utility and feasibility of linked routinely collected health data to capture key elements of quality of care for melanoma in a single-payer, universal health care setting. METHOD: This pilot study utilized a retrospective population-based cohort from a previously developed linked administrative data set, with a 65% random sample of all invasive cutaneous melanoma cases diagnosed 2007-2012 in the province of Ontario. Data from the Ontario Cancer Registry was utilized, supplemented with linked pathology report data from Cancer Care Ontario, and other linked administrative data describing health care utilization. Quality indicators identified through provincial guidelines and international consensus were evaluated for potential collection with administrative data and measured where possible. RESULTS: A total of 7,654 cases of melanoma were evaluated. Ten of 25 (40%) candidate quality indicators were feasible to be collected with the available administrative data. Many indicators (8/25) could not be measured due to unavailable clinical information (e.g. width of clinical margins). Insufficient pathology information (6/25) or health structure information (1/25) were less common reasons. Reporting of recommended variables in pathology reports varied from 65.2% (satellitosis) to 99.6% (body location). For stage IB-II or T1b-T4a melanoma patients where SLNB should be discussed, approximately two-thirds met with a surgeon experienced in SLNB. Of patients undergoing full lymph node dissection, 76.2% had adequate evaluation of the basin. CONCLUSIONS: We found that use of linked administrative data sources is feasible for measurement of melanoma quality in some cases. In those cases, findings suggest opportunities for quality improvement. Consultation with surgeons offering SLNB was limited, and pathology report completeness was sub-optimal, but was prior to routine synoptic reporting. However, to measure more quality indicators, text-based data sources will require alternative approaches to manual collection such as natural language processing or standardized collection. We recommend development of robust data platforms to support continuous re-evaluation of melanoma quality indicators, with the goal of optimizing quality of care for melanoma patients on an ongoing basis.