Search

Warts, hypogammaglobulinemia, infections, and myelokathexis (WHIM) syndrome (WS) is a combined immunodeficiency caused by gain-of-function mutations in the C-X-C chemokine receptor type 4 (CXCR4) gene. We characterize a unique international cohort of 66 patients, including 57 (86%) cases previously unreported, with variable clinical phenotypes. Of 17 distinct CXCR4 genetic variants within our cohort, 11 were novel pathogenic variants affecting 15 individuals (23%). All variants affect the same CXCR4 region and impair CXCR4 internalization resulting in hyperactive signaling. The median age of diagnosis in our cohort (5.5 years) indicates WHIM syndrome can commonly present in childhood, although some patients are not diagnosed until adulthood. The prevalence and mean age of recognition and/or onset of clinical manifestations within our cohort were infections 88%/1.6 years, neutropenia 98%/3.8 years, lymphopenia 88%/5.0 years, and warts 40%/12.1 years. However, we report greater prevalence and variety of autoimmune complications of WHIM syndrome (21.2%) than reported previously. Patients with versus without family history of WHIM syndrome were diagnosed earlier (22%, average age 1.3 years versus 78%, average age 5 years, respectively). Patients with a family history of WHIM syndrome also received earlier treatment, experienced less hospitalization, and had less end-organ damage. This observation reinforces previous reports that early treatment for WHIM syndrome improves outcomes. Only one patient died; death was attributed to complications of hematopoietic stem cell transplantation. The variable expressivity of WHIM syndrome in pediatric patients delays their diagnosis and therapy. Early-onset bacterial infections with severe neutropenia and/or lymphopenia should prompt genetic testing for WHIM syndrome, even in the absence of warts.

Objective To investigate the incidence and risk factors for hypogammaglobulinaemia and infectious complications associated with rituximab treatment in childhood-onset rheumatic diseases. Methods We performed a single-centre retrospective study of patients (n = 85) treated at Boston Children’s Hospital (BCH) from 2009 to 2019. Study subjects included patients (ages 6–24 years) who received rituximab for the treatment of a childhood-onset rheumatic disease. Results New-onset hypogammaglobulinaemia developed in 23 (27.1%) patients within 18 months of rituximab induction treatment. Twenty-two patients (25.9%) developed at least one infectious complication in the 18 months following the first rituximab infusion; of these, 11 (50%) had serious infections requiring inpatient treatment. After adjusting for potential confounders, exposure to pulse corticosteroid therapy in the month prior to rituximab use was a significant predictor of both new-onset hypogammaglobulinaemia (odds ratio [OR] 3.94; 95% CI: 1.07, 16.0; P = 0.044) and infectious complications (OR 15.3; 95% CI: 3.04, 126.8; P = 0.003). Post-rituximab hypogammaglobulinaemia was the strongest predictor of serious infectious complications (OR 7.89; 95% CI: 1.41, 65.6; P = 0.028). Younger age at rituximab use was also a significant predictor of new-onset hypogammaglobulinaemia (OR 0.83; 95% CI: 0.70, 0.97; P = 0.021). Compared with other rheumatic diseases, patients with vasculitis had a higher likelihood of developing infectious complications, including serious infections. Conclusion Although rituximab was well tolerated in terms of infectious complications in the majority of patients with childhood-onset rheumatic diseases, a substantial proportion developed new-onset hypogammaglobulinaemia and infectious complications following treatment. Our study highlights a role for heightened vigilance of rituximab-associated hypogammaglobulinaemia and infections in paediatric patients with rheumatic conditions.

BACKGROUND: Inhaled corticosteroid (ICS) response among patients with asthma is influenced by genetics, but biologically actionable insights based on associations have not been found. Various glucocorticoid response omics datasets are available to interrogate their biological effects. OBJECTIVE: We sought to identify functionally relevant ICS response genetic associations by integrating complementary multiomics datasets. METHODS: Variants with p-values

Nijmegen breakage syndrome (NBS) is a DNA repair disorder characterized by combined immunodeficiency and a high predisposition to lymphoid malignancies. The majority of NBS patients are identified with a homozygous five base pair deletion in the Nibrin (NBN) gene (c.657_661del5, p.K219fsX19) with a founder effect observed in Caucasian European populations, especially of Slavic origin. We present here an analysis of a cohort of 136 NBS patients of Eastern Slav origin across Belarus, Ukraine, Russia, and Latvia with a focus on understanding the geographic distribution, incidence of malignancy, and treatment outcomes of this cohort. Our analysis shows that Belarus had the highest prevalence of NBS (2.3 per 1,000,000), followed by Ukraine (1.3 per 1,000,000), and Russia (0.7 per 1,000,000). Of note, the highest concentration of NBS cases was observed in the western regions of Belarus and Ukraine, where NBS prevalence exceeds 20 cases per 1,000,000 people, suggesting the presence of an “Eastern Slavic NBS hot spot.” The median age at diagnosis of this cohort ranged from 4 to 5 years, and delay in diagnosis was more pervasive in smaller cities and rural regions. A total of 62 (45%) patients developed malignancies, more commonly in males than females (55.2 vs. 34.2%; p=0.017). In 27 patients, NBS was diagnosed following the onset of malignancies (mean age: 8 years). Malignancies were mostly of lymphoid origin and predominantly non-Hodgkin lymphoma (NHL) (n=42, 68%); 38% of patients had diffuse large B-cell lymphoma. The 20-year overall survival rate of patients with malignancy was 24%. However, females with cancer experienced poorer event-free survival rates than males (16.6% vs. 46.8%, p=0.036). Of 136 NBS patients, 13 underwent hematopoietic stem cell transplantation (HSCT) with an overall survival of 3.5 years following treatment (range: 1 to 14 years). Indications for HSCT included malignancy (n=7) and immunodeficiency (n=6). Overall, 9% of patients in this cohort reached adulthood. Adult survivors reported diminished quality of life with significant physical and cognitive impairments. Our study highlights the need to improve timely diagnosis and clinical management of NBS among Eastern Slavs. Genetic counseling and screening should be offered to individuals with a family history of NBS, especially in hot spot regions. © Copyright © 2021 Sharapova, Pashchenko, Bondarenko, Vakhlyarskaya, Prokofjeva, Fedorova, Savchak, Mareika, Valiev, Popa, Tuzankina, Vlasova, Sakovich, Polyakova, Rumiantseva, Naumchik, Kulyova, Aleshkevich, Golovataya, Minakovskaya, Belevtsev, Latysheva, Latysheva, Beznoshchenko, Akopyan, Makukh, Kozlova, Varabyou, Ballow, Ong, Walter, Kondratenko, Kostyuchenko and Aleinikova. We thank all doctors for clinical help for patients. We also appreciate the support of patient and their parents for agreeing to take part in this study. TP thanks Sergey?Nikulshin, Marika Grutupa, and Zanna Kovalova. We thank Joseph Dasso for editing this manuscript, primarily for proper English.

OBJECTIVE To investigate the effects of early introduction of biologic disease-modifying antirheumatic drugs (bDMARDs) on the disease course in untreated polyarticular juvenile idiopathic arthritis (JIA). METHODS We analyzed data on patients with polyarticular JIA participating in the Start Time Optimization of Biologics in Polyarticular JIA (STOP-JIA) study (n = 400) and a comparator cohort (n = 248) from the Childhood Arthritis and Rheumatology Research Alliance Registry. Latent class trajectory modeling (LCTM) was applied to identify subgroups of patients with distinct disease courses based on disease activity (clinical Juvenile Arthritis Disease Activity Score in 10 joints) over 12 months from baseline. RESULTS In the STOP-JIA study, 198 subjects (49.5%) received bDMARDs within 3 months of baseline assessment. LCTM analyses generated 3 latent classes representing 3 distinct disease trajectories, characterized by slow, moderate, or rapid disease activity improvement over time. Subjects in the rapid improvement trajectory attained inactive disease within 6 months from baseline. Odds of being in the rapid improvement trajectory versus the slow improvement trajectory were 3.6 times as high (95% confidence interval 1.32-10.0; P = 0.013) for those treated with bDMARDs ≤3 months from baseline compared with subjects who started bDMARDs >3 months after baseline, after adjusting for demographic characteristics, clinical attributes, and baseline disease activity. Shorter disease duration at first rheumatology visit approached statistical significance as a predictor of favorable trajectory without bDMARD treatment. CONCLUSION Starting bDMARDs within 3 months of baseline assessment is associated with more rapid achievement of inactive disease in subjects with untreated polyarticular JIA. These results demonstrate the utility of trajectory analysis of disease course as a method for determining treatment efficacy.

Background Real‐world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts—a crucial first step underpinning the validity of research results—remains a challenge. We developed and evaluated claims‐based case ascertainment algorithms for pulmonary hypertension (PH), comparing conventional decision rules with state‐of‐the‐art machine‐learning approaches. Methods and Results We analyzed an electronic health record‐Medicare linked database from two large academic tertiary care hospitals (years 2007–2013). Electronic health record charts were reviewed to form a gold standard cohort of patients with (n=386) and without PH (n=164). Using health encounter data captured in Medicare claims (including patients’ demographics, diagnoses, medications, and procedures), we developed and compared 2 approaches for identifying patients with PH: decision rules and machine‐learning algorithms using penalized lasso regression, random forest, and gradient boosting machine. The most optimal rule‐based algorithm—having ≥3 PH‐related healthcare encounters and having undergone right heart catheterization—attained an area under the receiver operating characteristic curve of 0.64 (sensitivity, 0.75; specificity, 0.48). All 3 machine‐learning algorithms outperformed the most optimal rule‐based algorithm ( P Conclusions Research‐grade case identification algorithms for PH can be derived and rigorously validated using machine‐learning algorithms. Simple decision rules commonly applied in published literature performed poorly; more complex rule‐based algorithms may potentially address the limitation of this approach. PH research using claims data would be considerably strengthened through the use of validated algorithms for cohort ascertainment.

Nijmegen breakage syndrome (NBS) is a DNA repair disorder characterized by combined immunodeficiency and a high predisposition to lymphoid malignancies. The majority of NBS patients are identified with a homozygous five base pair deletion in the Nibrin (NBN) gene (c.657_661del5, p.K219fsX19) with a founder effect observed in Caucasian European populations, especially of Slavic origin. We present here an analysis of a cohort of 136 NBS patients of Eastern Slav origin across Belarus, Ukraine, Russia, and Latvia with a focus on understanding the geographic distribution, incidence of malignancy, and treatment outcomes of this cohort. Our analysis shows that Belarus had the highest prevalence of NBS (2.3 per 1,000,000), followed by Ukraine (1.3 per 1,000,000), and Russia (0.7 per 1,000,000). Of note, the highest concentration of NBS cases was observed in the western regions of Belarus and Ukraine, where NBS prevalence exceeds 20 cases per 1,000,000 people, suggesting the presence of an “Eastern Slavic NBS hot spot.” The median age at diagnosis of this cohort ranged from 4 to 5 years, and delay in diagnosis was more pervasive in smaller cities and rural regions. A total of 62 (45%) patients developed malignancies, more commonly in males than females (55.2 vs. 34.2%; p=0.017). In 27 patients, NBS was diagnosed following the onset of malignancies (mean age: 8 years). Malignancies were mostly of lymphoid origin and predominantly non-Hodgkin lymphoma (NHL) (n=42, 68%); 38% of patients had diffuse large B-cell lymphoma. The 20-year overall survival rate of patients with malignancy was 24%. However, females with cancer experienced poorer event-free survival rates than males (16.6% vs. 46.8%, p=0.036). Of 136 NBS patients, 13 underwent hematopoietic stem cell transplantation (HSCT) with an overall survival of 3.5 years following treatment (range: 1 to 14 years). Indications for HSCT included malignancy (n=7) and immunodeficiency (n=6). Overall, 9% of patients in this cohort reached adulthood. Adult survivors reported diminished quality of life with significant physical and cognitive impairments. Our study highlights the need to improve timely diagnosis and clinical management of NBS among Eastern Slavs. Genetic counseling and screening should be offered to individuals with a family history of NBS, especially in hot spot regions.

To investigate racial and ethnic differences in pulmonary hypertension subtypes and survival differences in a pediatric population.This was a retrospective analysis of a cohort of patients with pulmonary hypertension (aged ≤18 years) enrolled in the Pediatric Pulmonary Hypertension Network registry between 2014 and 2018, comprising patients at eight Pediatric Centers throughout North America (n = 1417).Among children diagnosed after the neonatal period, pulmonary arterial hypertension was more prevalent among Asians (OR, 1.83; 95% CI, 1.21-2.79; P = .0045), lung disease-associated pulmonary hypertension among blacks (OR, 2.09; 95% CI, 1.48-2.95; P .0001), idiopathic pulmonary arterial hypertension among whites (OR, 1.58; 95% CI, 1.06-2.41; P = .0289), and pulmonary veno-occlusive disease among Hispanics (OR, 6.11; 95% CI, 1.34-31.3; P = .0184). Among neonates, persistent pulmonary hypertension of the newborn (OR, 4.07; 95% CI, 1.54-10.0; P = .0029) and bronchopulmonary dysplasia (OR, 8.11; 95% CI, 3.28-19.8; P .0001) were more prevalent among blacks, and congenital diaphragmatic hernia was more prevalent among whites (OR, 2.29; 95% CI, 1.25-4.18; P = .0070). An increased mortality risk was observed among blacks (HR, 1.99; 95% CI, 1.03-3.84; P = .0396), driven primarily by the heightened mortality risk among those with lung disease-associated pulmonary hypertension (HR, 2.84; 95% CI, 1.15-7.04; P = .0241).We found significant racial variability in the prevalence of pulmonary hypertension subtypes and survival outcomes among children with pulmonary hypertension. Given the substantial burden of this disease, further studies to validate phenotypic differences and to understand the underlying causes of survival disparities between racial and ethnic groups are warranted.

BACKGROUND Prophylactic treatment of postoperative Crohn's disease (CD) plays a critical role in maintaining clinical remission. We performed the first study in the last decade to examine secular trends in the use of pharmacologic interventions after ileocolonic resection in the United States, to understand whether clinical practice converges with recent advances in scientific knowledge. METHODS A retrospective study of a U.S. national claims database was performed. The study cohort included 106 CD patients in the years 1999 to 2001 (prebiologic era) and 294 CD patients in the years 2009 to 2011 (postbiologic era), who underwent ileocolonic resection. Medication use in the 12 months after the surgery was examined. RESULTS Significant variations in care were evident in both study periods. Across the 2 study periods, there was an increased use of biologics (from 0% to 36.4%) and a substantial reduction in the use of 5-aminosalicylic acid (from 50.9% to 28.2%; P < 0.0001). Therapeutic interventions that have been found ineffective in published studies continued to be widely applied: one-third of patients were prescribed corticosteroids, and several cases of prolonged use of corticosteroids or antibiotics were observed in both cohorts. Disease behavior (penetrating, stricturing, or nonpenetrating and nonstricturing) was not associated with the choice of postoperative therapeutic interventions, with the exception of an increased use of antibiotics among patients with penetrating disease. CONCLUSIONS There is a substantial gap between advances in postoperative care for ileocolonic CD and clinical practice. Strategies to expedite the integration of new knowledge and evidence into practice are urgently needed.

Display Omitted Using EMR data to measure downtime effects on clinical processes.A matched case-control design is used to examine downtime effects.The effects of downtime vary with the type of IT problem.Even brief system downtimes may impact patient care.Having application potential to other clinical processes with established workflow. ObjectiveTo introduce and evaluate a method that uses electronic medical record (EMR) data to measure the effects of computer system downtime on clinical processes associated with pathology testing and results reporting. Materials and methodsA matched case-control design was used to examine the effects of five downtime events over 11-months, ranging from 5 to 300min. Four indicator tests representing different laboratory workflows were selected to measure delays and errors: potassium, haemoglobon, troponin and activated partial thromboplastin time. Tests exposed to a downtime were matched to tests during unaffected control periods by test type, time of day and day of week. Measures included clinician read time (CRT), laboratory turnaround time (LTAT), and rates of missed reads, futile searches, duplicate orders, and missing test results. ResultsThe effects of downtime varied with the type of IT problem. When clinicians could not logon to a results reporting system for 17-min, the CRT for potassium and haemoglobon tests was five (10.3 vs. 2.0days) and six times (13.4 vs. 2.1days) longer than control (p=0.01-0.04; p=0.0001-0.003). Clinician follow-up of tests was also delayed by another downtime involving a power outage with a small effect. In contrast, laboratory processing of troponin tests was unaffected by network services and routing problems. Errors including missed reads, futile searches, duplicate orders and missing test results could not be examined because the sample size of affected tests was not sufficient for statistical testing. ConclusionThis study demonstrates the feasibility of using routinely collected EMR data with a matched case-control design to measure the effects of downtime on clinical processes. Even brief system downtimes may impact patient care. The methodology has potential to be applied to other clinical processes with established workflows where tasks are pre-defined such as medications management.

Key Points Question In patients receiving rituximab, what are the current rates of screening and recognition of hypogammaglobulinemia, and what are the infectious risks and predictors for increased mortality? Findings In a cohort study of 4479 patients receiving rituximab, many patients were found as not being screened or not being properly identified as having hypogammaglobulinemia. Following rituximab therapy, there was a significant increase in severe infections in the overall study cohort, increased mortality was associated with severe infections in the 6 months before and after rituximab therapy, and higher cumulative doses of immunoglobulin replacement therapy were associated with a reduced risk of severe infections. Meaning Many patients are not being screened or properly identified as having hypogammaglobulinemia before or after rituximab therapy, which may contribute to inferior outcomes with excess morbidity and mortality; monitoring routine serum immunoglobulin levels before and after rituximab therapy may help identify patients at high risk for developing infections and who may benefit from immunoglobulin replacement therapy., Importance Rituximab is an anti-CD20 chimeric antibody used in a wide variety of clinical indications. There has not been widespread adoption of consistent immune monitoring before and after rituximab therapy. However, there is a subset of patients who develop prolonged, symptomatic hypogammaglobulinemia following rituximab, and monitoring before and after rituximab therapy could help to identify these patients and initiate measures to prevent excess morbidity and mortality. Objective To determine the current levels of screening for hypogammaglobulinemia (specifically, low immunoglobulin G), infectious risks associated with hypogammaglobulinemia, and variables associated with an increased risk of mortality. Design, Setting, and Participants A cohort study was conducted of 8633 patients receiving rituximab from January 1, 1997, to December 31, 2017, at a large, tertiary referral center (Partners HealthCare System). Exposures Rituximab administration. Main Outcomes and Measures The primary outcome measures were immunoglobulin measurements, infectious complications, and mortality. Cox regression analysis was used to examine the results of infectious complications on survival, adjusted for age, sex, and indication for rituximab use. Results Of the 8633 patients who received rituximab in the large, academic, health care system, 4479 satisfied inclusion criteria, with a mean (SD) age of 59.8 (16.2) years; 2280 patients (50.9%) were women. Most patients (3824 [85.4%]) did not have immunoglobulin levels checked before rituximab therapy. Of those who had levels determined, hypogammaglobulinemia was noted in 313 (47.8%) patients before initiation of rituximab. Following rituximab administration, worsening hypogammaglobulinemia was noted. There was an increase in severe infections after rituximab use in the study cohort (from 17.2% to 21.7%; P, This cohort study examines the association of screening for hypogammaglobulinemia with the risk of infection and mortality in patients who received rituximab therapy.

Populationwide mammography screening has been associated with a substantial rise in false-positive mammography findings and breast cancer overdiagnosis. However, there is a lack of current data on the associated costs in the United States. We present costs due to false-positive mammograms and breast cancer overdiagnoses among women ages 40-59, based on expenditure data from a major US health care insurance plan for 702,154 women in the years 2011-13. The average expenditures for each false-positive mammogram, invasive breast cancer, and ductal carcinoma in situ in the twelve months following diagnosis were $852, $51,837 and $12,369, respectively. This translates to a national cost of $4 billion each year. The costs associated with false-positive mammograms and breast cancer overdiagnoses appear to be much higher than previously documented. Screening has the potential to save lives. However, the economic impact of false-positive mammography results and breast cancer overdiagnoses must be considered in the debate about the appropriate populations for screening.

Figure S1. Average clinical read time (CRT) for tests ordered on a given day of admission. (DOCX 100 kb)

Background Debates about the benefits and harms of mammography continue despite the accumulation of evidence. We sought to quantify the disagreement across systematic reviews of mammography and determine whether author or design characteristics were associated with conclusions that were favourable to the use of mammography for routine breast cancer screening. Methods We identified systematic reviews of mammography published between January 2000 and November 2015, and extracted information about the selection of evidence, age groups, the use of meta-analysis, and authors’ professions and financial competing interest disclosures. Conclusions about specific age groups were graded as favourable if they stated that there were meaningful benefits, that benefits of mammography outweighed harms, or that harms were inconsequential. The main outcome measures were the proportions of favourable conclusions relative to review design and author characteristics. Results From 59 conclusions identified in 50 reviews, 42% (25/59) were graded as favourable by two investigators. Among the conclusions produced by clinicians, 63% (12/19) were graded as favourable compared to 32% (13/40) from other authors. In the 50–69 age group where the largest proportion of systematic reviews were focused, conclusions drawn by authors without financial competing interests (odds ratio 0.06; 95% CI 0.07–0.56) and non-clinicians (odds ratio 0.11; 95% CI 0.01–0.84) were less likely to be graded as favourable. There was no trend in the proportion of favourable conclusions over the period, and we found no significant association between review design characteristics and favourable conclusions. Conclusions Differences in the conclusions of systematic reviews of the evidence for mammography have persisted for 15 years. We found no strong evidence that design characteristics were associated with greater support for the benefits of mammography in routine breast cancer screening. Instead, the results suggested that the specific expertise and competing interests of the authors influenced the conclusions of systematic reviews. Electronic supplementary material The online version of this article (doi:10.1186/s13643-017-0495-6) contains supplementary material, which is available to authorized users.

Rationale: Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. Objective: We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. Methods and Results: A retrospective cohort study comprising 6 943 263 children (, National Institutes of Health (U.S.) (Award U01HL121518)

Objective To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures. Methods A syndromic surveillance system was developed to monitor a laboratory information system at a tertiary hospital. Four indices were monitored: (1) total laboratory records being created; (2) total records with missing results; (3) average serum potassium results; and (4) total duplicated tests on a patient. The goal was to detect HIT system failures causing: data loss at the record level; data loss at the field level; erroneous data; and unintended duplication of data. Time-series models of the indices were constructed, and statistical process control charts were used to detect unexpected behaviors. The ability of the models to detect HIT system failures was evaluated using simulated failures, each lasting for 24 h, with error rates ranging from 1% to 35%. Results In detecting data loss at the record level, the model achieved a sensitivity of 0.26 when the simulated error rate was 1%, while maintaining a specificity of 0.98. Detection performance improved with increasing error rates, achieving a perfect sensitivity when the error rate was 35%. In the detection of missing results, erroneous serum potassium results and unintended repetition of tests, perfect sensitivity was attained when the error rate was as small as 5%. Decreasing the error rate to 1% resulted in a drop in sensitivity to 0.65–0.85. Conclusions Syndromic surveillance methods can potentially be applied to monitor HIT systems, to facilitate the early detection of failures.

Multiple provider prescribing of interacting drugs is a preventable cause of morbidity and mortality, and fragmented care is a major contributing factor. We applied social network analysis to examine the impact of provider patient-sharing networks on the risk of multiple provider prescribing of interacting drugs. We performed a retrospective analysis of commercial healthcare claims (years 2008–2011), including all non-elderly adult beneficiaries (n = 88,494) and their constellation of care providers. Patient-sharing networks were derived based on shared patients, and care constellation cohesion was quantified using care density, defined as the ratio between the total number of patients shared by provider pairs and the total number of provider pairs within the care constellation around each patient. In our study, 2% (n = 1796) of patients were co-prescribed interacting drugs by multiple providers. Multiple provider prescribing of interacting drugs was associated with care density (odds ratio per unit increase in the natural logarithm of the value for care density 0.78; 95% confidence interval 0.74–0.83; p

Objectives To explore the feasibility of using statistical text classification to automatically detect extreme-risk events in clinical incident reports. Methods Statistical text classifiers based on Naive Bayes and Support Vector Machine (SVM) algorithms were trained and tested on clinical incident reports to automatically detect extreme-risk events, defined by incidents that satisfy the criteria of Severity Assessment Code (SAC) level 1. For this purpose, incident reports submitted to the Advanced Incident Management System by public hospitals from one Australian region were used. The classifiers were evaluated on two datasets: (1) a set of reports with diverse incident types (n=120); (2) a set of reports associated with patient misidentification (n=166). Results were assessed using accuracy, precision, recall, F-measure, and area under the curve (AUC) of receiver operating characteristic curves. Results The classifiers performed well on both datasets. In the multi-type dataset, SVM with a linear kernel performed best, identifying 85.8% of SAC level 1 incidents (precision=0.88, recall=0.83, F-measure=0.86, AUC=0.92). In the patient misidentification dataset, 96.4% of SAC level 1 incidents were detected when SVM with linear, polynomial or radial-basis function kernel was used (precision=0.99, recall=0.94, F-measure=0.96, AUC=0.98). Naive Bayes showed reasonable performance, detecting 80.8% of SAC level 1 incidents in the multi-type dataset and 89.8% of SAC level 1 patient misidentification incidents. Overall, higher prediction accuracy was attained on the specialized dataset, compared with the multi-type dataset. Conclusion Text classification techniques can be applied effectively to automate the detection of extreme-risk events in clinical incident reports.

Objective To model how individual violations in routine clinical processes cumulatively contribute to the risk of adverse events in hospital using an agent-based simulation framework. Design An agent-based simulation was designed to model the cascade of common violations that contribute to the risk of adverse events in routine clinical processes. Clinicians and the information systems that support them were represented as a group of interacting agents using data from direct observations. The model was calibrated using data from 101 patient transfers observed in a hospital and results were validated for one of two scenarios (a misidentification scenario and an infection control scenario). Repeated simulations using the calibrated model were undertaken to create a distribution of possible process outcomes. The likelihood of end-of-chain risk is the main outcome measure, reported for each of the two scenarios. Results The simulations demonstrate end-of-chain risks of 8% and 24% for the misidentification and infection control scenarios, respectively. Over 95% of the simulations in both scenarios are unique, indicating that the in-patient transfer process diverges from prescribed work practices in a variety of ways. Conclusions The simulation allowed us to model the risk of adverse events in a clinical process, by generating the variety of possible work subject to violations, a novel prospective risk analysis method. The in-patient transfer process has a high proportion of unique trajectories, implying that risk mitigation may benefit from focusing on reducing complexity rather than augmenting the process with further rule-based protocols.

Prescription benzodiazepine overdose continues to cause significant morbidity and mortality in the US. Multiple-provider prescribing, due to either fragmented care or “doctor-shopping,” contributes to the problem. To elucidate the effect of provider professional relationships on multiple-provider prescribing of benzodiazepines, using social network analytics. A retrospective analysis of commercial healthcare claims spanning the years 2008 through 2011. Provider patient-sharing networks were modelled using social network analytics. Care team cohesion was measured using care density, defined as the ratio between the total number of patients shared by provider pairs within a patient’s care team and the total number of provider pairs in the care team. Relationships within provider pairs were further quantified using a range of network metrics, including the number and proportion of patients or collaborators shared. The relationship between patient-sharing network metrics and the likelihood of multiple prescribing of benzodiazepines. Patients between the ages of 18 and 64 years who received two or more benzodiazepine prescriptions from multiple providers, with overlapping coverage of more than 14 days. A total of 5659 patients and 1448 provider pairs were included in our study. Among these, 1028 patients (18.2 %) received multiple prescriptions of benzodiazepines, involving 445 provider pairs (30.7 %). Patients whose providers rarely shared patients had a higher risk of being prescribed overlapping benzodiazepines; the median care density was 8.1 for patients who were prescribed overlapping benzodiazepines and 10.1 for those who were not (p

Objective: To analyse patient safety events associated with England’s national program for IT (NPfIT). Methods: Retrospective analysis of all safety events managed by a dedicated IT safety team between September 2005 and November 2011 was undertaken. Events were reviewed against an existing classification for problems associated with IT. The proportion of reported events per problem type, consequences, source of report, resolution within 24 hours, time of day and day of week were examined. Sub-group analyses were undertaken for events involving patient harm and those that occurred on a large scale. Results: Of the 850 events analysed, 68% (n=574) described potentially hazardous circumstances, 24% (n=205) had an observable impact on care delivery, 4% (n=36) were a near miss, and 3% (n=22) were associated with patient harm, including three deaths (0·35%). Eleven events did not have a noticeable consequence (1%) and two were complaints (

In the current landscape of decentralized and increasingly specialized and fragmented healthcare services, managing the quality of the handoff process is critical in ensuring continuity of patient care. This chapter explores some of the challenges with patient handoff through two case studies. In the first case, inadequate handoff led to a maternal death by postpartum hemorrhage; in the second, communication breakdown resulted in a death by overdose of analgesia. A chain of communication failures, combined with a confluence of human and system errors, cumulatively cascaded into these unfortunate events. Key problems contributing to poor patient handoff included communication failures caused by diversity of expertise and expectations and unavailability of information after transition of care. Communication problems were further exacerbated by workload and resource constraints, and the absence of guidelines and well-defined inter-team lines of responsibility. Strategies to improve handoff should include training individual care providers, as well as tackling the underlying systemic issues. These include standardizing critical clinical processes and inter-team lines of responsibility, instituting induction program to ensure new staff members are familiar with the relevant protocols, providing adequate supervision for junior staff members, better coordination of available resources, and improving information availability through information technology.

Background Ineffective communication of infection control requirements during transitions of care is a potential cause of non-compliance with infection control precautions by healthcare personnel. In this study, interventions to enhance communication during inpatient transfers between wards and radiology were implemented, in the attempt to improve adherence to precautions during transfers. Methods Two interventions were implemented, comprising (i) a pre-transfer checklist used by radiology porters to confirm a patient’s infectious status; (ii) a coloured cue to highlight written infectious status information in the transfer form. The effectiveness of the interventions in promoting adherence to standard precautions by radiology porters when transporting infectious patients was evaluated using a randomised crossover trial at a teaching hospital in Australia. Results 300 transfers were observed over a period of 4 months. Compliance with infection control precautions in the intervention groups was significantly improved relative to the control group (p

Advances in knowledge: Handover and communication errors are prevalent in medical imaging. System-wide changes that facilitate effective communication are required. Conclusion: The handover of patients and clinical information to and from medical imaging is fraught with error, often compromising patient safety and resulting in communication of delayed or wrong diagnoses, unnecessary radiation exposure and a waste of limited resources. Corrective strategies to address safety concerns related to new information technologies, patient transfer and inadequate test result notification policies are relevant to all healthcare settings. Methods: 71 search terms, related to clinical handover and communication, were applied to 3976 incidents in the Radiology Events Register. Detailed classification and thematic analysis of a subset of incidents that involved handover or communication (n5298) were undertaken to identify the most prevalent types of error and to make recommendations about patient safety initiatives in medical imaging. Objective: To determine the type and nature of incidents occurring within medical imaging settings in Australia and identify strategies that could be engaged to reduce the risk of their re-occurrence. Results: Incidents occurred most frequently during patient preparation (34%), when requesting imaging (27%) and when communicating a diagnosis (23%). Frequent problems within each of these stages of the imaging cycle included: inadequate handover of patients (41%) or unsafe or inappropriate transfer of the patient to or from medical imaging (35%); incorrect information on the request form (52%); and delayed communication of a diagnosis (36%) or communication of a wrong diagnosis (36%). Refereed/Peer-reviewed

The objective of this paper is to analyze healthcare information technology (HIT) events associated with patient harm submitted to the US Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database. We examined the problems in 46 relevant events submitted to MAUDE from January 2008 to July 2010 to identify natural categories of problems from a clinical perspective. CPOE and PACS were involved in 93% of the events. Adverse events were associated with medications in 41%, clinical processes in 33%, radiation in 15% and surgery in 11%. There were four deaths. Strategies to improve the safety of HIT should focus on designing safe user interfaces, integrated checks of key identifiers and decision support, and engineering safer clinical processes.

Objective: To expand an emerging classification for problems with health information technology (HIT) using reports submitted to the US Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database. Design: HIT events submitted to MAUDE were retrieved using a standardized search strategy. Using an emerging classification with 32 categories of HIT problems, a subset of relevant events were iteratively analyzed to identify new categories. Two coders then independently classified the remaining events into one or more categories. Free-text descriptions were analyzed to identify the consequences of events. Measurements: Descriptive statistics by number of reported problems per category and by consequence; inter-rater reliability analysis using the k statistic for the major categories and consequences. Results: A search of 899 768 reports from January 2008 to July 2010 yielded 1100 reports about HIT. After removing duplicate and unrelated reports, 678 reports describing 436 events remained. The authors identified four new categories to describe problems with software functionality, system configuration, interface with devices, and network configuration; the authors' classification with 32 categories of HIT problems was expanded by the addition of these four categories. Examination of the 436 events revealed 712 problems, 96% were machine related, and 4% were problems at the human-computer interface. Almost half (46%) of the events related to hazardous circumstances. Of the 46 events (11%) associated with patient harm, four deaths were linked to HIT problems (0.9% of 436 events). Conclusions: Only 0.1% of the MAUDE reports searched were related to HIT. Nevertheless, Food and Drug Administration reports did prove to be a useful new source of information about the nature of software problems and their safety implications with potential to inform strategies for safe design and implementation. Refereed/Peer-reviewed

Background/Purpose: In 2009, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) established a longitudinal multi-center, multiple disease U.S. national registry (CARRA Registry) for pediatric rheumatology with the intent of providing a new framework to drive observational clinical research and best practices, evidence-based care. Simultaneously, recognizing that widely variable therapeutic approaches hinder the ability to conduct meaningful comparative effectiveness studies and pragmatic trials in pediatric rheumatic diseases, CARRA investigators convened expert groups to formulate new consensus-based treatment plans (CTPs) in 5 major pediatric rheumatic disease areas. As the CTP approaches are adopted, it is important to establish baseline treatment variability across pediatric rheumatic diseases and clinical sites in the CARRA network. Using longitudinal data from the CARRA Registry, we provide a first description of variability of care across the network. Methods: We examine variations of medication usage across 55 clinical sites in the treatment of 8 rheumatic conditions, including juvenile idiopathic arthritis (JIA), SLE and mixed connective tissue disease (MCTD), juvenile dermatomyositis (JDM), localized scleroderma, systemic sclerosis, juvenile primary fibromyalgia syndrome (JPFS), sarcoidosis, and vasculitis. Management of uveitis in JIA patients was also assessed. Study participants include all CARRA registry subjects enrolled in May 2010 through December 2013. Medications were categorized into 4 major classes: biologics, DMARDs, steroids and NSAIDs. We compare the percentage of patients exposed to each medication class at each; care variations were quantified using dispersion measures of standard deviation and range. A subgroup analysis was conducted to assess care variations among the largest group of subjects with similar characteristics of and low disease activity (JIA subjects with an average active joint count of 0 to 1 averaged over the enrolment period), where treatment were hypothesized to be most similar. Results: 8,869 subjects were included in data analysis. Therapeutic approaches were highly variable for all 8 rheumatic diseases (Table 1, Fig 1). Subgroup analysis for JIA showed persistence of variability (Fig 2). Conclusion: We quantify a substantial degree of therapeutic practice variability across sites, persisting across disease-severity-matched cohorts. Although enrollment bias is a significant limitation, the magnitude of the variability for the largest cohort (JIA) and persistence across multiple diseases and subtypes supports a widespread effect. This baseline quantification and methods developed for assessing variability will support ongoing efforts to monitor new consensus treatment protocol-based standardization efforts across the CARRA network.

Objectives To explore the feasibility of using statistical text classification techniques to automatically categorise clinical incident reports. Methods Statistical text classifiers based on Naive Bayes and Support Vector Machine algorithms were trained and tested on incident reports submitted by public hospitals to identify two classes of clinical incidents: inadequate clinical handover and incorrect patient identification. Each classifier was trained on 600 reports (300 positives, 300 negatives), and tested on 372 reports (248 positives, 124 negatives). The results were evaluated using standard measures of accuracy, precision, recall, F-measure and area under curve (AUC) of receiver operating characteristics (ROC). Classifier learning rates were also evaluated, using classifier accuracy against training set size. Results All classifiers performed well in categorising clinical handover and patient identification incidents. Naive Bayes attained the best performance on handover incidents, correctly identifying 86.29% of reporter-classified incidents (precision=0.84, recall=0.90, F-measure=0.87, AUC=0.93) and 91.53% of expert-classified incidents (precision=0.87, recall=0.98, F-measure=0.92, AUC=0.97). For patient identification incidents, the best results were obtained when Support Vector Machine with radial-basis function kernel was used to classify reporter-classified reports (accuracy=97.98%, precision=0.98, recall=0.98, F-measure=0.98, AUC=1.00); and when Naive Bayes was used on expert-classified reports (accuracy=95.97%, precision=0.95, recall=0.98, F-measure=0.96, AUC=0.99). A relatively small training set was found to be adequate, with most classifiers achieving an accuracy above 80% when the training set size was as small as 100 samples. Conclusions This study demonstrates the feasibility of using text classification techniques to automatically categorise clinical incident reports.

Objectives To study the extent and execution of redundant processes during inpatient transfers to Radiology, and their impact on errors during the transfer process; to explore the use of causal and reliability analyses for modelling error detection and redundancy in the transfer process; and to provide guidance on potential system improvements. Methods A prospective observational study at a metropolitan teaching hospital. 101 patient transfers to Radiology were observed over a 6-month period, and errors in patient transfer process were recorded. Fault Tree Analysis was used to model error paths and identify redundant steps. Reliability Analysis was used to quantify system reliability. Results 420 errors were noted, an average of four errors per transfer. No incidents of patient harm were recorded. Inadequate handover was the most common error (43.1%), followed by failure to perform patient identification checks (41.9%), patient inadequately prepared for transfer (7.4%), inadequate infection control precautions (2.9%), inadequate clinical escort (2.1%), inadequate transport vehicle (2.1%) and equipment failure (0.2%). Four redundant steps for communicating patients' infectious status were identified (reliability=0.07, 0.37, 0.26, 0.31). Collectively, these yielded a system reliability of 0.7. The low reliability of each individual step was due to its low rate of execution. Conclusions Analysis of the transfer process revealed a number of redundancies that safeguard against transfer errors. However, they were relatively ineffective in preventing errors, due to the poor compliance rate. Thus, the authors advocate increasing compliance to existing redundant processes as an improvement strategy, before investing resources on new processes.

Objective To analyze patient safety incidents associated with computer use to develop the basis for a classification of problems reported by health professionals. Design Incidents submitted to a voluntary incident reporting database across one Australian state were retrieved and a subset (25%) was analyzed to identify ‘natural categories’ for classification. Two coders independently classified the remaining incidents into one or more categories. Free text descriptions were analyzed to identify contributing factors. Where available medical specialty, time of day and consequences were examined. Measurements Descriptive statistics; inter-rater reliability. Results A search of 42 616 incidents from 2003 to 2005 yielded 123 computer related incidents. After removing duplicate and unrelated incidents, 99 incidents describing 117 problems remained. A classification with 32 types of computer use problems was developed. Problems were grouped into information input (31%), transfer (20%), output (20%) and general technical (24%). Overall, 55% of problems were machine related and 45% were attributed to human–computer interaction. Delays in initiating and completing clinical tasks were a major consequence of machine related problems (70%) whereas rework was a major consequence of human–computer interaction problems (78%). While 38% (n=26) of the incidents were reported to have a noticeable consequence but no harm, 34% (n=23) had no noticeable consequence. Conclusion Only 0.2% of all incidents reported were computer related. Further work is required to expand our classification using incident reports and other sources of information about healthcare IT problems. Evidence based user interface design must focus on the safe entry and retrieval of clinical information and support users in detecting and correcting errors and malfunctions.

Erratum to: J Gen Intern Med DOI: 10.1007/s11606-015-3470-8 The odds ratio for the relationship between median care density and multiple prescribing of benzodiazepine was incorrectly reported in the text as 0.76 (95% CI 0.60 – 0.95; p=0.028). It should have read, “Backward stepwise logistic regression revealed that median care density was negatively associated with the risk of an overlapping benzodiazepine prescription (OR 0.76; 95% CI 0.60 – 0.95; p=0.0178) after adjusting for covariates (Table 3).” In the Discussion, it should have also read the following: “Consistent with these studies, in univariate analysis, we showed a significant relationship between the number of prescribers and overlapping benzodiazepine prescriptions; however, the magnitude of the association was reduced when considered alongside care density in multivariate analysis.”