This guideline was developed to identify evidence-based best practices in haemophilia care delivery, and discuss the range of care providers and services that are most important to optimize outcomes for persons with haemophilia (PWH) across the United States. The guideline was developed following specific methods described in detail in this supplement and based on the GRADE (Grading of Recommendations, Assessment, Development and Evaluation approach). Direct evidence from published literature and the haemophilia community, as well as indirect evidence from other chronic diseases, were reviewed, synthesized and applied to create evidence-based recommendations. The Guideline panel suggests that the integrated care model be used over non-integrated care models for PWH (conditional recommendation, moderate certainty in the evidence). For PWH with inhibitors and those at high risk for inhibitor development, the same recommendation was graded as strong, with moderate certainty in the evidence. The panel suggests that a haematologist, a specialized haemophilia nurse, a physical therapist, a social worker and round-the-clock access to a specialized coagulation laboratory be part of the integrated care team, over an integrated care team that does not include all of these components (conditional recommendation, very low certainty in the evidence). Based on available evidence, the integrated model of care in its current structure, is suggested for optimal care of PWH. There is a need for further appropriately designed studies that address unanswered questions about specific outcomes and the optimal structure of the integrated care delivery model in haemophilia.

Summary Background Clinical evidence shows that pediatric anesthesia patients are subject to a higher rate of life‐threatening medical errors than their adult counterparts. Medication error in adult anesthesia is estimated to occur to 1 in 133 anesthetic administrations, but such a figure has not been determined for pediatric anesthesia patients. Individual studies of medication error in pediatric anesthesia have ranged from rates of 0.01% to 1.92% of anesthetic uses. The present study is a systematic review that employs a meta‐analytic estimate to determine the rate of medication error in pediatric anesthesia. Methods A systematic review of the literature on pediatric anesthesia medication error was conducted using Medline, Cochrane Database, PROSPERO, and Clinicaltrials.gov. A meta‐analytic estimate was used to determine the medication error rate for all of the included studies. Subgroup sensitivity analysis was used to evaluate possible sources of heterogeneity in included studies. Results Of the 433 initially screened records, 13 studies met inclusion criteria. Meta‐analytic estimate of medication error rate across all studies was 0.08% (95% CI 0.05%‐0.10%), or 1 out of 1250 anesthetics. Ten different countries were represented in the studies. Sample size of anesthetics reported on ranged from 296 to 2 316 635. Data collecting periods ranged from 3 months to 15 years. Six included studies individually reported higher rates of medication error in patients under 1 year of age. Conclusion The present systematic review revealed a medication error rate of 1 per 1250 anesthetic administrations in pediatric anesthesia. This result is significantly lower than would be expected given reported rates of medication error in adult anesthesia, which raises questions regarding the validity of research methods and reporting of medication error in pediatric anesthesia. Future investigations of medication error should employ methodologies other than self‐reporting of error, such as retrospective chart review.

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Background Residency program prestige is an important variable medical students consider when creating their rank list. Doximity Residency Navigator is a ranking system that previous reports have shown significantly influences medical student application decisions. Doximity's use of peer nomination as a central component of its methodology for determining program rank has drawn criticism for its lack of objectivity. Doximity has not published information regarding how peer nomination and more objective measures are statistically weighted in reputation calculation. Objective This study assesses whether a strong negative correlation exists between residency program size and Doximity ranking. Methods A cross-sectional study of Doximity residency rankings from the 2018–2019 academic year was conducted. Data extracted from Doximity included program rank, size, and age. Data were additionally collected from the Blue Ridge Institute for Medical Research, National Institutes of Health, funding in 2018 and the US News & World Report Best Medical Schools 2019–2020. A multivariable linear regression model was used that included Doximity ranking as the outcome variable and residency program size as the predictor variable with adjustment for the aforementioned variables. Results Sixteen of the 28 specialties on Doximity were included in the analysis, representing 3388 unique residency programs. After adjustment for covariates, residency program size was a significant predictor of Doximity ranking (β = -1.84; 95% CI -2.01 to -1.66, P < .001). Conclusions These findings support the critique that the Doximity reputation ranking system may favor larger residency programs. More transparency for Doximity reputation ranking algorithm is warranted.

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Informed consent for pediatric anesthesia challenges practitioners to navigate complex ethical, medical, and legal ambiguities. A patient's status as a minor does not negate the importance of his or her participation in the decision-making process but, rather, necessitates a nuanced evaluation of age and development to involve the patient to an appropriate extent. Given the complexities involved with pediatric informed consent in anesthesia practice and research, it is important to understand the experience of key stakeholders involved. For this review, we searched Medline, the Cochrane database, PROSPERO, and Clinicaltrials.gov for studies involving pediatric anesthesia informed consent. Inclusion and exclusion criteria were designed to select for studies that included issues related to informed consent as primary outcomes. The following data were extracted from included studies: title, authors, date of publication, study type, intervention, data collection method, participant type (ie, parent, pediatric patient, anesthesia provider), number of participants, pediatric patient age range, and primary outcome measures. Twenty-two articles were included for final review: studies of informed consent in pediatric anesthesia span many aspects of informed consent. Parental understanding has been studied most often (7/22 studies), followed by parental preferences (5/22 studies) and provider-related outcomes (5/22 studies) such as time spent interacting with patients, subjective reporting on amount of training related to informed consent, and provider satisfaction with the informed consent process. Outcomes pertaining to pediatric patients themselves constitute the smallest number of studies, including child anxiety (1/22), child understanding (1/22), and child refusal (1/22). Among the parties involved, parents have been most frequently identified as the subjects of these studies (2719/3805 subjects across all included studies, or 71% of all subjects). Pediatric patients are the least frequently involved subjects of studies that investigate informed consent in pediatric anesthesia (493/3805, or 13% of all subjects). Anesthesia providers and investigators have been study subjects (593/3805, or 16% of all subjects) for a range of topics including time spent interacting with patient, nature of informed consent conversation in relation to trainee status, satisfaction with informed consent process, and priorities for informed consent content. The aim of the present narrative review is to summarize the work that has been done on informed consent for pediatric anesthesia.

The prevalence of microcephaly in Colombia from 1982 to 2013, before the introduction of ZV, ranged from 0.3 to 3.1 per 10,000 births, with an average of 1.8 (95% CI 1.7-1.8) per 10,000 births. These findings are important to determine if the prevalence after the introduction of the Zika virus infection registered significant changes.