Online questionnaire on genetic testing for intractable diseases in Japan: response to and issues associated with the revised medical care act.

In Japan, most genetic testing for intractable diseases has been conducted in research laboratories in the past. However, since the Revised Medical Care Act came into effect on December 1, 2018, genetic testing in compliance with this act has become a major issue. To collect information on this topic, we conducted an online survey of members of the research groups for intractable diseases, which play a central role in medical care and research on intractable diseases with the support of the Ministry of Health, Labor and Welfare, five months after the enactment of the act. We separated the surveyed facilities into those that conducted genetic testing in their own laboratories ("testing facilities") and those that outsourced genetic testing ("outsourcing facilities"). Ninety-five and 66 responses regarding genetic testing were obtained from the testing and outsourcing facilities, respectively. Genetic analysis was the most commonly conducted genetic testing method, accounting for 60% or more of the tests. At the testing facilities that conducted comprehensive analysis with a next-generation sequencer, the number of target diseases for genetic testing was observed to be higher. In these testing facilities, more than 70% were research laboratories. In contrast, at the outsourcing facilities, testing was outsourced to registered clinical laboratories in many cases or to research laboratories. The proportion of genetic testing covered by public medical insurance at the outsourcing facilities was two times higher than that at the testing facilities. The importance of quality control for genetic testing was generally well acknowledged, but there was apprehension regarding the increased cost and burden on staff of quality control assurance, and many testing facilities viewed genetic testing as difficult. The research groups could handle the examination and interpretation of the genetic testing results, and many groups gathered and registered patient information. Within the intractable disease medical support network, there was a relatively large number of collaborations, with studies supported by the Japan Agency for Medical Research and Development (AMED) and Initiative on Rare and Undiagnosed Diseases (IRUD) projects. There were many requests for genetic testing to be covered by public medical insurance. In the future, the implementation of genetic testing using a next-generation sequencer at clinical laboratories with guaranteed quality control and the development of a system for collaboration with research groups will be necessary.

Partners in care.

This festschrift contribution, written for my colleague and mentor John Graham, reflects on geneticist-genetic counselor interactions in clinical care, samples of alternative models of care for pediatric and general genetic counselors, and avenues for expanding access to genetic healthcare services utilizing genetic counselors.

Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data.

Observational healthcare data, such as electronic health records and administrative claims, offer potential to estimate effects of medical products at scale. Observational studies have often been found to be nonreproducible, however, generating conflicting results even when using the same database to answer the same question. One source of discrepancies is error, both random caused by sampling variability and systematic (for example, because of confounding, selection bias, and measurement error). Only random error is typically quantified but converges to zero as databases become larger, whereas systematic error persists independent from sample size and therefore, increases in relative importance. Negative controls are exposure-outcome pairs, where one believes no causal effect exists; they can be used to detect multiple sources of systematic error, but interpreting their results is not always straightforward. Previously, we have shown that an empirical null distribution can be derived from a sample of negative controls and used to calibrate P values, accounting for both random and systematic error. Here, we extend this work to calibration of confidence intervals (CIs). CIs require positive controls, which we synthesize by modifying negative controls. We show that our CI calibration restores nominal characteristics, such as 95% coverage of the true effect size by the 95% CI. We furthermore show that CI calibration reduces disagreement in replications of two pairs of conflicting observational studies: one related to dabigatran, warfarin, and gastrointestinal bleeding and one related to selective serotonin reuptake inhibitors and upper gastrointestinal bleeding. We recommend CI calibration to improve reproducibility of observational studies.

Hybrid prevalence estimation: Method to improve intervention coverage estimations.

Delivering excellent health services requires accurate health information systems (HIS) data. Poor-quality data can lead to poor judgments and outcomes. Unlike probability surveys, which are representative of the population and carry accuracy estimates, HIS do not, but in many countries the HIS is the primary source of data used for administrative estimates. However, HIS are not structured to detect gaps in service coverage and leave communities exposed to unnecessary health risks. Here we propose a method to improve informatics by combining HIS and probability survey data to construct a hybrid estimator. This technique provides a more accurate estimator than either data source alone and facilitates informed decision-making. We use data from vitamin A and polio vaccination campaigns in children from Madagascar and Benin to demonstrate the effect. The hybrid estimator is a weighted average of two measurements and produces SEs and 95% confidence intervals (CIs) for the hybrid and HIS estimators. The estimates of coverage proportions using the combined data and the survey estimates differ by no more than 3%, while decreasing the SE by 1-6%; the administrative estimates from the HIS and combined data estimates are very different, with 3-25 times larger CI, questioning the value of administrative estimates. Estimators of unknown accuracy may lead to poorly formulated policies and wasted resources. The hybrid estimator technique can be applied to disease prevention services for which population coverages are measured. This methodology creates more accurate estimators, alongside measured HIS errors, to improve tracking the public's health.

Sharing Patient-Controlled Real-World Data Through the Application of the Theory of Commons: Action Research Case Study.

BACKGROUND: Technological advances have radically changed the opportunities for individuals with chronic conditions to practice self-care and to coproduce health care and research. Digital technologies enable patients to perform tasks traditionally carried out by health care professionals in a more convenient way, at lower costs, and without compromising quality. Patients may also share real-world data with other stakeholders to promote individual and population health. However, there is a need for legal frameworks that enable patient privacy and control in such sharing of real-world data. We believe that this need could be met by the conceptualization of patient-controlled real-world data as knowledge commons, which is a resource shared by a group of people. OBJECTIVE: This study aimed to propose a conceptual model that describes how patient-controlled real-world data can be shared effectively in chronic care management, in a way that supports individual and population health, while respecting personal data privacy and control. METHODS: An action research approach was used to develop a solution to enable patients, in a self-determined way, to share patient-controlled data to other settings. We chose the context of cystic fibrosis (CF) care in Sweden, where coproduction between patients, their families, and health care professionals is critical in the introduction of new drugs. The first author, who is a lawyer and parent of children with CF, was a driver in the change process. All coauthors collaborated in the analysis. We collected primary and secondary data reflecting changes during the time period from 2012 to 2020, and performed a qualitative content analysis guided by the knowledge commons framework. RESULTS: Through a series of changes, a national system for enabling patients to share patient-controlled real-world data to different stakeholders in CF care was implemented. The case analysis resulted in a conceptual model consisting of the following three knowledge commons arenas that contributed to patient-controlled real-world data collection, use, and sharing: (1) patient world arena involving the private sphere of patients and families; (2) clinical microsystem arena involving the professional sphere at frontline health care clinics; and (3) round table arena involving multiple stakeholders from different settings. Based on the specification of property rights, as presented in our model, the patient can keep control over personal health information and may grant use rights to other stakeholders. CONCLUSIONS: Health information exchanges for sharing patient-controlled real-world data are pivotal to enable patients, health care professionals, health care funders, researchers, authorities, and the industry to coproduce high-quality care and to introduce and follow-up novel health technologies. Our model proposes how technical and legal structures that protect the integrity and self-determination of patients can be implemented, which may be applicable in other chronic care settings as well.

Two sets of qualitative research reporting guidelines: An analysis of the shortfalls.

Findings from qualitative research may make valuable contributions to the evidence informing healthcare practice. Qualitative research methodologies and methods, however, are less familiar to health researchers and research consumers when compared with quantitative methods. Qualitative research reporting guidelines and their merit have been hotly debated for at least two decades. Herein I discuss two sets of qualitative research reporting guidelines endorsed by many high tiered health research journals: Consolidated criteria for reporting qualitative research and Standards for reporting qualitative research. Six aspects of the two sets of guidelines are compared. The first aspect is the focus of the guidelines. The latter five aspects are items included in the guidelines: reflexivity, participant sampling and saturation, data collection, member checking, and data analysis. Except for reflexivity, these items were selected for comparison as they include features of, or strategies to, enhance the rigor of qualitative research that are applicable within some but not all qualitative methodologies. Reflexivity, a central feature of rigor within all qualitative research, is discussed for its suboptimal representation in both sets of reporting guidelines. Without regular and critical review of reporting guidelines, efforts to promote the design, conduct, and reporting of rigorous qualitative health research to support evidence-informed practice may be undermined. Moreover, for qualitative research reporting guidelines to be useful, they must be applied appropriately and in a flexible manner by researchers and reviewers. This paper has implications for researchers, journal editors, reviewers, and research consumers.

Assessing the quality of health research from an Indigenous perspective: the Aboriginal and Torres Strait Islander quality appraisal tool.

BACKGROUND: The lack of attention to Indigenous epistemologies and, more broadly, Indigenous values in primary research, is mirrored in the standardised critical appraisal tools used to guide evidence-based practice and systematic reviews and meta-syntheses. These critical appraisal tools offer no guidance on how validity or contextual relevance should be assessed for Indigenous populations and cultural contexts. Failure to tailor the research questions, design, analysis, dissemination and knowledge translation to capture understandings that are specific to Indigenous peoples results in research of limited acceptability and benefit and potentially harms Indigenous peoples. A specific Aboriginal and Torres Strait Islander Quality Appraisal Tool is needed to address this gap. METHOD: The Aboriginal and Torres Strait Islander Quality Appraisal Tool (QAT) was developed using a modified Nominal Group and Delphi Techniques and the tool's validity, reliability, and feasibility were assessed over three stages of independent piloting. National and international research guidelines were used as points of reference. Piloting of the Aboriginal and Torres Strait Islander QAT with Aboriginal and Torres Strait Islander and non-Indigenous experts led to refinement of the tool. RESULTS: The Aboriginal and Torres Strait Islander QAT consists of 14 questions that assess the quality of health research from an Aboriginal and Torres Strait Islander perspective. The questions encompass setting appropriate research questions; community engagement and consultation; research leadership and governance; community protocols; intellectual and cultural property rights; the collection and management of research material; Indigenous research paradigms; a strength-based approach to research; the translation of findings into policy and practice; benefits to participants and communities involved; and capacity strengthening and two-way learning. Outcomes from the assessment of the tool's validity, reliability, and feasibility were overall positive. CONCLUSION: This is the first tool to appraise research quality from the perspective of Indigenous peoples. Through the uptake of the Aboriginal and Torres Strait Islander QAT we hope to improve the quality and transparency of research with Aboriginal and Torres Strait Islander peoples, with the potential for greater improvements in Aboriginal and Torres Strait Islander health and wellbeing.

Administrative data identify sickle cell disease: A critical review of approaches in U.S. health services research.

To identify people living with sickle cell disease (SCD) and study their healthcare utilization, researchers can either use clinical records linked to administrative data or use billing diagnosis codes in stand-alone administrative databases. Correct identification of individuals clinically managed for SCD using diagnosis codes in claims databases is limited by the accuracy of billing codes in outpatient encounters. In this critical review, we assess the strengths and limitations of claims-based SCD case-finding algorithms in stand-alone administrative databases that contain both inpatient and outpatient records. Validation studies conducted using clinical records and newborn screening for confirmation of SCD case status have found that algorithms that require three or more nonpharmacy claims or one inpatient claim plus two or more outpatient claims with SCD codes show acceptable accuracy (positive predictive value and sensitivity) in children and adolescents. Future studies might seek to assess the accuracy of case-finding algorithms over the lifespan.

Individual, institutional, and scientific environment factors associated with questionable research practices in the reporting of messages and conclusions in scientific health services research publications.

BACKGROUND: Health Services Research findings (HSR) reported in scientific publications may become part of the decision-making process on healthcare. This study aimed to explore associations between researcher's individual, institutional, and scientific environment factors and the occurrence of questionable research practices (QRPs) in the reporting of messages and conclusions in scientific HSR publications. METHODS: We employed a mixed-methods study design. We identified factors possibly contributing to QRPs in the reporting of messages and conclusions through a literature review, 14 semi-structured interviews with HSR institutional leaders, and 13 focus-groups amongst researchers. A survey corresponding with these factors was developed and shared with 172 authors of 116 scientific HSR publications produced by Dutch research institutes in 2016. We assessed the included publications for the occurrence of QRPs. An exploratory factor analysis was conducted to identify factors within individual, institutional, and environmental domains. Next, we conducted bivariate analyses using simple Poisson regression to explore factors' association with the number of QRPs in the assessed HSR publications. Factors related to QRPs with a p-value < .30 were included in four multivariate models tested through a multiple Poisson regression. RESULTS: In total, 78 (45%) participants completed the survey (51.3% first authors and 48.7% last authors). Twelve factors were included in the multivariate analyses. In all four multivariate models, a higher score of "pressure to create societal impact" (Exp B = 1.28, 95% CI [1.11, 1.47]), was associated with higher number of QRPs. Higher scores on "specific training" (Exp B = 0.85, 95% CI [0.77-0.94]) and "co-author conflict of interest" (Exp B = 0.85, 95% CI [0.75-0.97]) factors were associated with a lower number of QRPs. Stratification between first and last authors indicated different factors were related to the occurrence of QRPs for these groups. CONCLUSION: Experienced pressure to create societal impact is associated with more QRPs in the reporting of messages and conclusions in HSR publications. Specific training in reporting messages and conclusions and awareness of co-author conflict of interests are related to fewer QRPs. Our results should stimulate awareness within the field of HSR internationally on opportunities to better support reporting in scientific HSR publications.

Repurposing NGO data for better research outcomes: a scoping review of the use and secondary analysis of NGO data in health policy and systems research.

BACKGROUND: Non-governmental organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas, including the evaluation of health policy and programmes. METHODS: A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytical approach provided a comprehensive overview and descriptive analyses of the studies that (1) used data produced or collected by or about NGOs; (2) performed secondary analysis of the NGO data (beyond the use of an NGO report as a supporting reference); and (3) analysed NGO-collected clinical data. RESULTS: Of the 156 studies that performed secondary analysis of NGO-produced or collected data, 64% (n = 100) used NGO-produced reports (mostly to a limited extent, as a contextual reference or to critique NGO activities) and 8% (n = 13) analysed NGO-collected clinical data. Of these studies, 55% (n = 86) investigated service delivery research topics and 48% (n = 51) were undertaken in developing countries and 17% (n = 27) in both developing and developed countries. NGOs were authors or co-authors of 26% of the studies. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), albeit with some limitations such as inconsistent and missing data. CONCLUSION: We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics such as conflict-affected areas. NGO-academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. The use of NGO data use could enable relevant and timely research in the areas of programme evaluation and health policy and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries.

Creating what is necessary for optimizing psychotherapy.

The dimensions of mental health status (MHS), all those that may influence MHS, and the measures to represent these dimensions must come to be agreed upon and all of them included in every study of psychotherapy effectiveness in order for these studies' results to be properly comparable, decisive, and cumulative. This is essential for eventually achieving a psychotherapy effectiveness research (PER) that is adequate for informing individual case psychotherapy practice rather than only reporting average case psychotherapy practice results. Cooperation among researchers and practitioners as well as between these is necessary in the form of their democratic central governance of programmatic PER, its coordination with practice, and its results' integration into individual case practice. This is the ideal that PER should strive for rather than continue in its present wastefully fragmented, least economically developed countries' mentally ill neglected, and practitioner experience underutilized manner.

Working Towards the Development and Implementation of Precision Mental Healthcare: An Example.

Leonard Bickman's (2020) Festschrift paper in the special issue "The Future of Children's Mental Health Services" on improving mental health services is an impressive reflection of his career, highlighting his major insights and the development of mental health services research as a whole. Five major difficulties in this field's current research and practice are attentively delineated: poor diagnostics, measurement problems, disadvantages of randomized controlled trials (RCTs), lack of feedback and personalized treatments. Dr. Bickman recommends possible solutions based on his extensive experience and empirical findings. We agree with his thoughts and illustrate how we, challenged with the same problems, have attempted to develop clinically informed research and evidence-based clinical practice. A comprehensive feedback system that deals with the aforementioned problems is briefly described. It includes pre-treatment recommendations for treatment strategies and an empirically informed dropout prediction based on a variety of data sources. In addition to treatment recommendations, continuous feedback as well as individualized treatment adaptation tools are provided during ongoing therapy. New projects are being implemented to further improve the system by including new data assessment strategies and sources, e.g., ecological momentary assessment (EMA) and automated video analysis.

Designing the Future of Children's Mental Health Services.

Advancements in evidence-based psychosocial interventions, digital technologies, and implementation strategies (i.e., health services research products) for youth mental health services have yet to yield significant improvement in public health outcomes. Achieving such impact will require that these research products are easy to use, useful, and contextually appropriate. This paper describes how human-centered design (HCD), an approach that aligns product development with the needs of the people and settings that use those products, can be leveraged to improve youth mental health services. We articulate how HCD can advance accessibility, effectiveness, and equity, with specific consideration of unique aspects of youth mental health services.

Beyond a Seat at the Table: The Added Value of Family Stakeholders to Improve Care, Research, and Education in Neonatology.

OBJECTIVES: To analyze activities involving veteran resource parents and patients in a family partnership program; their perspectives were also explored. STUDY DESIGN: The multiple roles assumed by family stakeholders in neonatal initiatives were reviewed. Quality control questionnaires were distributed to resource parents and patients and providers who worked with them. Mixed methods were used to analyze results. RESULTS: Thirty resource parents and patients were involved in a total of 653 activities related to clinical care (n = 413), teaching (n = 31), and research (n = 209); 7 initiatives were described to illustrate the positive impact of family stakeholders on clinical care, teaching, and/or research. Resource parents and patients had different degrees and intensity of involvement: all were involved in low-risk initiatives and 9 in more complex activities. In the questionnaire, family stakeholders all described positive impacts associated with their participation and benefits to themselves, such as meaning making. Three resource parents reported traumatic memories that occurred during medical simulations. The majority of providers report that resource parents and patients improved their projects, but some also report this new collaboration is complex. CONCLUSIONS: Although stakeholder participation increasingly is recommended, practical knowledge and the impact of their participation is scarce. Having several resource parents and patients bring their contributions may be more valuable than a few "expert stakeholders." Recruiting and orienting resource parents and patients toward different types of activities should take into account the complexity and risks of the tasks. Family stakeholders are appreciated and have a positive impact on projects in which they are involved.

Using Data From the Healthcare Cost and Utilization Project for State Health Policy Research.

BACKGROUND: The Healthcare Cost and Utilization Project (HCUP), the nation's most complete source of all-payer hospital care data, supports analyses at the national, regional, state and community levels. However, national HCUP data are often used in inappropriate ways in studies of state-specific issues. OBJECTIVE: To describe the opportunities and challenges of using HCUP data to conduct state health policy research and to provide empirical examples of what can go wrong when using the national HCUP data inappropriately. RESEARCH DESIGN: Comparison of results from state-level analyses using national HCUP data and the state-specific HCUP data recommended by the Agency for Healthcare Research and Quality (AHRQ). Analyses included trends in state-specific rates of cesarean delivery and a difference-in-differences analysis of Connecticut's Medicaid expansion. SUBJECTS: Hospital discharges from the 2004 to 2011 HCUP Nationwide Inpatient Samples (NIS) and State Inpatient Databases (SID). MEASURES: Cesarean delivery rates, discharges per capita, and discharges by the payer. RESULTS: State-level estimates derived from the NIS are volatile and often provide misleading policy conclusions relative to estimates from the SID. CONCLUSIONS: The NIS should not be used for state-level research. AHRQ provides resources to assist analysts with state-specific studies using SID files.

A methodological systematic review of meta-ethnography conduct to articulate the complex analytical phases.

BACKGROUND: Decision making in health and social care requires robust syntheses of both quantitative and qualitative evidence. Meta-ethnography is a seven-phase methodology for synthesising qualitative studies. Developed in 1988 by sociologists in education Noblit and Hare, meta-ethnography has evolved since its inception; it is now widely used in healthcare research and is gaining popularity in education research. The aim of this article is to provide up-to-date, in-depth guidance on conducting the complex analytic synthesis phases 4 to 6 of meta-ethnography through analysis of the latest methodological evidence. METHODS: We report findings from a methodological systematic review conducted from 2015 to 2016. Fourteen databases and five other online resources were searched. Expansive searches were also conducted resulting in inclusion of 57 publications on meta-ethnography conduct and reporting from a range of academic disciplines published from 1988 to 2016. RESULTS: Current guidance on applying meta-ethnography originates from a small group of researchers using the methodology in a health context. We identified that researchers have operationalised the analysis and synthesis methods of meta-ethnography - determining how studies are related (phase 4), translating studies into one another (phase 5), synthesising translations (phase 6) and line of argument synthesis - to suit their own syntheses resulting in variation in methods and their application. Empirical research is required to compare the impact of different methods of translation and synthesis. Some methods are potentially better at preserving links with the context and meaning of primary studies, a key principle of meta-ethnography. A meta-ethnography can and should include reciprocal and refutational translation and line of argument synthesis, rather than only one of these, to maximise the impact of its outputs. CONCLUSION: The current work is the first to articulate and differentiate the methodological variations and their application for different purposes and represents a significant advance in the understanding of the methodological application of meta-ethnography.

Advancing complexity science in healthcare research: the logic of logic models.

BACKGROUND: Logic models are commonly used in evaluations to represent the causal processes through which interventions produce outcomes, yet significant debate is currently taking place over whether they can describe complex interventions which adapt to context. This paper assesses the logic models used in healthcare research from a complexity perspective. A typology of existing logic models is proposed, as well as a formal methodology for deriving more flexible and dynamic logic models. ANALYSIS: Various logic model types were tested as part of an evaluation of a complex Patient Experience Toolkit (PET) intervention, developed and implemented through action research across six hospital wards/departments in the English NHS. Three dominant types of logic model were identified, each with certain strengths but ultimately unable to accurately capture the dynamics of PET. Hence, a fourth logic model type was developed to express how success hinges on the adaption of PET to its delivery settings. Aspects of the Promoting Action on Research Implementation in Health Services (PARIHS) model were incorporated into a traditional logic model structure to create a dynamic "type 4" logic model that can accommodate complex interventions taking on a different form in different settings. CONCLUSION: Logic models can be used to model complex interventions that adapt to context but more flexible and dynamic models are required. An implication of this is that how logic models are used in healthcare research may have to change. Using logic models to forge consensus among stakeholders and/or provide precise guidance across different settings will be inappropriate in the case of complex interventions that adapt to context. Instead, logic models for complex interventions may be targeted at facilitators to enable them to prospectively assess the settings they will be working in and to develop context-sensitive facilitation strategies. Researchers should be clear as to why they are using a logic model and experiment with different models to ensure they have the correct type.

Maximising data value and avoiding data waste: a validation study in stroke research.

OBJECTIVES: To determine the feasibility of linking data from the Australian Stroke Clinical Registry (AuSCR), the National Death Index (NDI), and state-managed databases for hospital admissions and emergency presentations; to evaluate data completeness and concordance between datasets for common variables. DESIGN, SETTING, PARTICIPANTS: Cohort design; probabilistic/deterministic data linkage of merged records for patients treated in hospital for stroke or transient ischaemic attack from New South Wales, Queensland, Victoria, and Western Australia. MAIN OUTCOME MEASURES: Descriptive statistics for data matching success; concordance of demographic variables common to linked databases; sensitivity and specificity of AuSCR in-hospital death data for predicting NDI registrations. RESULTS: Data for 16 214 patients registered in the AuSCR during 2009-2013 were linked with one or more state datasets: 15 482 matches (95%) with hospital admissions data, and 12 902 matches (80%) with emergency department presentations data were made. Concordance of AuSCR and hospital admissions data exceeded 99% for sex, age, in-hospital death (each κ = 0.99), and Indigenous status (κ = 0.83). Of 1498 registrants identified in the AuSCR as dying in hospital, 1440 (96%) were also recorded by the NDI as dying in hospital. In-hospital death in AuSCR data had 98.7% sensitivity and 99.6% specificity for predicting in-hospital death in the NDI. CONCLUSION: We report the first linkage of data from an Australian national clinical quality disease registry with routinely collected data from several national and state government health datasets. Data linkage enriches the clinical registry dataset and provides additional information beyond that for the acute care setting and quality of life at follow-up, allowing clinical outcomes for people with stroke (mortality and hospital contacts) to be more comprehensively assessed.

Evidence Review Conducted for the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery: Focus on Anesthesiology for Total Hip Arthroplasty.

Successes using enhanced recovery after surgery (ERAS) protocols for total hip arthroplasty (THA) are increasingly being reported. As in other surgical subspecialties, ERAS for THA has been associated with superior outcomes, improved patient satisfaction, reduced length of hospital stay, and cost savings. Nonetheless, the adoption of ERAS to THA has not been universal. The Agency for Healthcare Research and Quality, in partnership with the American College of Surgeons and the Johns Hopkins Medicine Armstrong Institute for Patient Safety and Quality, has developed the Safety Program for Improving Surgical Care and Recovery. We have conducted an evidence review to select anesthetic interventions that positively influence outcomes and facilitate recovery after THA. A literature search was performed for each intervention, and the highest levels of available evidence were considered. Anesthesiology-related interventions for pre- (carbohydrate loading/fasting, multimodal preanesthetic medications), intra- (standardized intraoperative pathway, regional anesthesia, ventilation, tranexamic acid, fluid minimization, glycemic control), and postoperative (multimodal analgesia) phases of care are included. We have summarized the best available evidence to recommend the anesthetic components of care for ERAS for THA. There is evidence in the literature and from society guidelines to support the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery goals for THA.

Evidence Review Conducted for the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery: Focus on Anesthesiology for Total Knee Arthroplasty.

Enhanced recovery after surgery (ERAS) has rapidly gained popularity in a variety of surgical subspecialities. A large body of literature suggests that ERAS leads to superior outcomes, improved patient satisfaction, reduced length of hospital stay, and cost benefits, without affecting rates of readmission after surgery. These patterns have been described for patients undergoing elective total knee arthroplasty (TKA); however, adoption of ERAS to orthopedic surgery has lagged behind other surgical disciplines. The Agency for Healthcare Research and Quality, in partnership with the American College of Surgeons and the Johns Hopkins Medicine Armstrong Institute (AI) for Patient Safety and Quality, has developed the Safety Program for Improving Surgical Care and Recovery. The program comprises a national effort to incorporate best practice in perioperative care and improve patient safety, for over 750 hospitals and multiple procedures over the next 5 years, including orthopedic surgery. We have conducted a full evidence review of anesthetic interventions to derive anesthesiology-related components of an evidence-based ERAS pathway for TKA. A PubMed search was performed for each protocol component, focusing on the highest levels of evidence in the literature. Search findings are summarized in narrative format. Anesthesiology components of care were identified and evaluated across the pre-, intra-, and postoperative phases. A summary of the best available evidence, together with recommendations for inclusion in ERAS protocols for TKA, is provided. There is extensive evidence in the literature, and from society guidelines to support the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery goals for TKA.