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BackgroundGraduate medical education (GME) program leaders struggle to incorporate quality measures in the ambulatory care setting, leading to knowledge gaps on how to provide feedback to residents and programs. While nationally collected quality of care data are available, their reliability for individual resident learning and for GME program improvement is understudied.ObjectiveTo examine the reliability of the Healthcare Effectiveness Data and Information Set (HEDIS) clinical performance measures in family medicine and internal medicine GME programs and to determine whether HEDIS measures can inform residents and their programs with their quality of care.MethodsFrom 2014 to 2017, we collected HEDIS measures from 566 residents in 8 family medicine and internal medicine programs under one sponsoring institution. Intraclass correlation was performed to establish patient sample sizes required for 0.70 and 0.80 reliability levels at the resident and program levels. Differences between the patient sample sizes required for reliable measurement and the actual patients cared for by residents were calculated.ResultsThe highest reliability levels for residents (0.88) and programs (0.98) were found for the most frequently available HEDIS measure, colorectal cancer screening. At the GME program level, 87.5% of HEDIS measures had sufficient sample sizes for reliable measurement at alpha 0.7 and 75.0% at alpha 0.8. Most resident level measurements were found to be less reliable.ConclusionsGME programs may reliably evaluate HEDIS performance pooled at the program level, but less so at the resident level due to patient volume.

ObjectiveTo reweight the Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator [PSI] 90) from weights based solely on the frequency of component PSIs to those that incorporate excess harm reflecting patients' preferences for outcome-related health states.Data sourcesNational administrative and claims data involving hospitalizations in nonfederal, nonrehabilitation, acute care hospitals.Study designWe estimated the average excess aggregate harm associated with the occurrence of each component PSI using a cohort sample for each indicator based on denominator-eligible records. We used propensity scores to account for potential confounding in the risk models for each PSI and weighted observations to estimate the "average treatment effect in the treated" for those with the PSI event. We fit separate regression models for each harm outcome. Final PSI weights reflected both the disutilities and the frequencies of the harms.Data collection/extraction methodsWe estimated PSI frequencies from the 2012 Healthcare Cost and Utilization Project State Inpatient Databases with present on admission data and excess harms using 2012-2013 Centers for Medicare & Medicaid Services Medicare Fee-for-Service data.Principal findingsIncluding harms in the weighting scheme changed individual component weights from the original frequency-based weighting. In the reweighted composite, PSIs 11 ("Postoperative Respiratory Failure"), 13 ("Postoperative Sepsis"), and 12 ("Perioperative Pulmonary Embolism or Deep Vein Thrombosis") contributed the greatest harm, with weights of 29.7%, 21.1%, and 20.4%, respectively. Regarding reliability, the overall average hospital signal-to-noise ratio for the reweighted PSI 90 was 0.7015. Regarding discrimination, among hospitals with greater than median volume, 34% had significantly better PSI 90 performance, and 41% had significantly worse performance than benchmark rates (based on percentiles).ConclusionsReformulation of PSI 90 with harm-based weights is feasible and results in satisfactory reliability and discrimination, with a more clinically meaningful distribution of component weights.

ObjectiveThe aim of the study was to analyze diverse patients' experiences throughout the medication use process to inform the development of overarching interventions that support safe medication use in community settings.MethodsUsing a qualitative observational approach, we conducted approximately 18 hours of direct observation of the medication use process across multiple settings for a sample of vulnerable, high-risk patients. Observers recorded detailed field notes during the observations. To enrich the observational findings, we also conducted six semistructured interviews with medication safety experts representing a diversity of perspectives. Barriers and facilitators to safe medication use were identified based on inductive coding of the data.ResultsA variety of safety vulnerabilities plague all stages of the medication use process and many of the well-established evidence-based interventions aimed at improving the safety of medication use at key stages of the process have not been widely implemented in community settings observed in this study. Key safety vulnerabilities identified include: limited English proficiency, low health literacy, lack of clinician continuity, incomplete medication reconciliation and counseling, unsafe medication storage and disposal habits, and conflicting healthcare agendas with caregivers.ConclusionsOur findings underscore a need for overarching, comprehensive interventions that span the entire process of medication use, including integrated communication systems between clinicians, pharmacies, and patients, and a "patient navigator" program that assists patients in navigating the entire medication-taking process. Collective ownership of the medication management system and mutual motivation for devising collaborative solutions is needed among key sectors.

This perspective paper seeks to lay out an efficient approach for health care providers, researchers, and other stakeholders involved in interventions aimed at improving care coordination to partner in locating and using applicable care coordination theory. The objective is to learn from relevant theory-based literature about fit between intervention options and coordination needs, thereby bringing insights from theory to enhance intervention design, implementation, and troubleshooting. To take this idea from an abstract notion to tangible application, our workgroup on models and measures from the Veterans Health Administration (VA) State of the Art (SOTA) conference on care coordination first summarizes our distillation of care coordination theoretical frameworks (models) into three common conceptual domains-context of an intervention, locus in which an intervention is applied, and specific design features of the intervention. Then we apply these three conceptual domains to four cases of care coordination interventions ("use cases") chosen to represent various scopes and stages of interventions to improve care coordination for veterans. Taken together, these examples make theory more accessible and practical by demonstrating how it can be applied to specific cases. Drawing from theory offers one method to anticipate which intervention options match a particular coordination situation.

Diagnostic disparities are preventable differences in diagnostic errors or opportunities to achieve diagnostic excellence. There is a need to summarize solutions with explicit considerations for addressing diagnostic disparities. We aimed to describe potential solutions to diagnostic disparities, organize them into an action-oriented typology with illustrative examples, and characterize these solutions to identify gaps for their further development. During four human-centered design workshops composed of diverse expertise, participants ideated and clarified potential solutions to diagnostic disparities and were supported by environmental literature scan inputs. Nineteen individual semi-structured interviews with workshop participants validated identified solution examples and solution type characterizations, refining the typology. Our typology organizes 21 various types of potential diagnostic disparities solutions into four primary expertise categories needed for implementation: healthcare systems' internal expertise, educator-, multidisciplinary patient safety researcher-, and health IT-expertise. We provide descriptions of potential solution types ideated as focused on disparities and compare those to existing examples. Six types were characterized as having diagnostic-disparity-focused examples, five as having diagnostic-focused examples, and 10 as only having general healthcare examples. Only three solution types had widespread implementation. Twelve had implementation on limited scope, and six were mostly hypothetical. We describe gaps that inform the progress needed for each of the suggested solution types to specifically address diagnostic disparities and be suitable for the implementation in routine practice. Numerous opportunities exist to tailor existing solutions and promote their implementation. Likely enablers include new perspectives, more evidence, multidisciplinary collaborations, system redesign, meaningful patient engagement, and action-oriented coalitions. [ABSTRACT FROM AUTHOR]

Objectives: To identify COVID-19 infectious disease models that accounted for social determinants of health (SDH). Methods: We searched MEDLINE, EMBASE, Cochrane Library, medRxiv, and the Web of Science from December 2019 to August 2020. We included mathematical modelling studies focused on humans investigating COVID-19 impact and including at least one SDH. We abstracted study characteristics (e.g., country, model type, social determinants of health) and appraised study quality using best practices guidelines. Results: 83 studies were included. Most pertained to multiple countries (n = 15), the United States (n = 12), or China (n = 7). Most models were compartmental (n = 45) and agent-based (n = 7). Age was the most incorporated SDH (n = 74), followed by gender (n = 15), race/ethnicity (n = 7) and remote/rural location (n = 6). Most models reflected the dynamic nature of infectious disease spread (n = 51, 61%) but few reported on internal (n = 10, 12%) or external (n = 31, 37%) model validation. Conclusion: Few models published early in the pandemic accounted for SDH other than age. Neglect of SDH in mathematical models of disease spread may result in foregone opportunities to understand differential impacts of the pandemic and to assess targeted interventions [ABSTRACT FROM AUTHOR]

BackgroundPrimary care teams face daily time pressures both during patient encounters and outside of appointments.ObjectivesWe theorize 2 types of time pressure, and test hypotheses about organizational determinants and patient consequences of time pressure.Research designCross-sectional, observational analysis of data from concurrent surveys of care team members and their patients.SubjectsPatients (n=1291 respondents, 73.5% response rate) with diabetes and/or coronary artery disease established with practice teams (n=353 respondents, 84% response rate) at 16 primary care sites, randomly selected from 2 Accountable Care Organizations.Measures and analysisWe measured team member perceptions of 2 potentially distinct time pressure constructs: (1) encounter-level, from 7 questions about likelihood that time pressure results in missing patient management opportunities; and (2) practice-level, using practice atmosphere rating from calm to chaotic. The Patient Assessment of Chronic Illness Care (PACIC-11) instrument measured patient-reported experience. Multivariate logistic regression models examined organizational predictors of each time pressure type, and hierarchical models examined time pressure predictors of patient-reported experiences.ResultsEncounter-level and practice-level time pressure measures were not correlated, nor predicted by the same organizational variables, supporting the hypothesis of two distinct time pressure constructs. More encounter-level time pressure was most strongly associated with less health information technology capability (odds ratio, 0.33; P

BackgroundMissed evidence-based monitoring in high-risk conditions (e.g., cancer) leads to delayed diagnosis. Current technological solutions fail to close this safety gap. In response, we aim to demonstrate a novel method to identify common vulnerabilities across clinics and generate attributes for context-flexible population-level monitoring solutions for widespread implementation to improve quality.MethodsBased on interviews with staff in otolaryngology, pulmonary, urology, breast, and gastroenterology clinics at a large urban publicly funded health system, we applied journey mapping to co-develop a visual representation of how patients are monitored for high-risk conditions. Using a National Academies framework and context-sensitivity theory, we identified common systems vulnerabilities and developed preliminary concepts for improving the robustness for monitoring patients with high-risk conditions ("design seeds" for potential solutions). Finally, we conducted a face validity and prioritization assessment of the design seeds with the original interviewees.ResultsWe identified five high-risk situations for potentially consequential diagnostic delays arising from suboptimal patient monitoring. All situations related to detection of cancer (head and neck, lung, prostate, breast, and colorectal). With clinic participants we created 5 journey maps, each representing specialty clinic workflow directed at evidence-based monitoring. System vulnerabilities common to the different clinics included challenges with: data systems, communications handoffs, population-level tracking, and patient activities. Clinic staff ranked 13 design seeds (e.g., keep patient list up to date, use triggered notifications) addressing these vulnerabilities. Each design seed has unique evaluation criteria for the usefulness of potential solutions developed from the seed.ConclusionsWe identified and ranked 13 design seeds that characterize situations that clinicians described 'wake them up at night', and thus could reduce their anxiety, save time, and improve monitoring of high-risk patients. We anticipate that the design seed approach promotes robust and context-sensitive solutions to safety and quality problems because it provides a human-centered link between the experienced problem and various solutions that can be tested for viability. The study also demonstrates a novel integration of industrial and human factors methods (journey mapping, process tracing and design seeds) linked to implementation theory for use in designing interventions that anticipate and reduce implementation challenges.

The article emphasizes the critical importance of accurate diagnosis in healthcare, highlighting that a correct diagnosis is essential for effective treatment and patient safety. Topics include multifaceted role of diagnosis in health promotion, the impact of diagnostic errors on patient outcomes, and initiatives to improve diagnostic safety, particularly in light of World Patient Safety Day 2024's focus on reducing diagnostic errors and enhancing patient engagement in the diagnostic process.

The experience of pregnancy and motherhood is complex and changeable, marked by feelings of fulfilment, growth, and joy, but also depression, stress, anxiety, increased conflict, and regret. Yet the chaotic realities of motherhood remain taboo subjects, rarely discussed, in society and across the media. This paper shows how discussion forums can work as powerful outlets to capture the meaningful expression of viewpoints that mothers may not feel able to articulate or confess elsewhere. These anonymous online spaces offer a supportive space where the reality of the often-hidden maternal experience can be communicated, in resistance to the dominant narratives reinforcing the idea of the “good” mother. Analysis of UK forum Mumsnet suggests that public digital communities provide a valuable space to explore a socially relevant research area relating to maternal suicide and lived experience. This paper responds to a need to understand how women discuss suicidal thoughts, facilitating an understanding of the hidden discourse around motherhood. Through thematic analysis of Mumsnet posts (n = 4,186), five themes were identified: escaping the burden of motherhood; motherhood or pregnancy trauma as a trigger; feeling that children would be better off without them; children being a reason to live; and perceived shameful thoughts leading to silenced feelings. [ABSTRACT FROM AUTHOR]

Background There is a critical need to identify specific causes of and tailored solutions to diagnostic error in sexual and gender minority (SGM) populations. Purpose To identify challenges to diagnosis in SGM adults, understand the impacts of patient-reported diagnostic errors on patients' lives and elicit solutions. Methods Qualitative study using in-depth semistructured interviews. Participants were recruited using convenience and snowball sampling. Recruitment efforts targeted 22 SGM-focused organisations, academic centres and clinics across the USA. Participants were encouraged to share study details with personal contacts. Interviews were analysed using codebook thematic analysis. Results Interviewees (n=20) ranged from 20 to 60 years of age with diverse mental and physical health symptoms. All participants identified as sexual minorities, gender minorities or both. Thematic analysis revealed challenges to diagnosis. Provider-level challenges included pathologisation of SGM identity; dismissal of symptoms due to anti-SGM bias; communication failures due to providers being distracted by SGM identity and enforcement of cis-heteronormative assumptions. Patient-level challenges included internalised shame and stigma. Intersectional challenges included biases around factors like race and age. Patient-reported diagnostic error led to worsening relationships with providers, worsened mental and physical health and increased self-advocacy and community-activism. Solutions to reduce diagnostic disparities included SGM-specific medical education and provider training, using inclusive language, asking questions, avoiding assumptions, encouraging diagnostic coproduction, upholding high care standards and ethics, involving SGM individuals in healthcare improvement and increasing research on SGM health. Conclusions Anti-SGM bias, queerphobia, lack of provider training and heteronormative attitudes hinder diagnostic decision-making and communication. As a result, SGM patients report significant harms. Solutions to mitigate diagnostic disparities require an intersectional approach that considers patients' gender identity, sexual orientation, race, age, economic status and system-level changes. [ABSTRACT FROM AUTHOR]

Los vacíos normativos contribuyen a la exclusión estructural de las poblaciones desplazadas por la fuerza que buscan empleo en las plataformas digitales de trabajo. Aun cuando se pueden resolver estos problemas, persiste la duda sobre la viabilidad de estas plataformas como camino al empoderamiento económico. [ABSTRACT FROM AUTHOR]

Regulatory vacuums contribute to the structural exclusion of forcibly displaced populations seeking work on digital labour platforms. Even where these issues can be overcome, questions remain as to the viability of these platforms as a path to economic empowerment. [ABSTRACT FROM AUTHOR]

One factor potentially driving healthcare and hospital worker (HHW)'s declining mental health during the COVID-19 pandemic is feeling betrayed by institutional leaders, coworkers, and/or others' pandemic-related responses and behaviors. We investigated whether HHWs' betrayal-based moral injury was associated with greater mental distress and post-traumatic stress disorder (PTSD) symptoms related to COVID-19. We also examined if these associations varied between clinical and non-clinical staff. From July 2020 to January 2021, cross-sectional online survey data were collected from 1,066 HHWs serving COVID-19 patients in a large urban US healthcare system. We measured betrayal-based moral injury in three groups: institutional leaders, coworkers/colleagues, and people outside of healthcare. Multivariate logistic regression analyses were performed to investigate whether betrayal-based moral injury was associated with mental distress and PTSD symptoms. Approximately one-third of HHWs reported feeling betrayed by institutional leaders, and/or people outside healthcare. Clinical staff were more likely to report feelings of betrayal than non-clinical staff. For all respondents, 49.5% reported mental distress and 38.2% reported PTSD symptoms. Having any feelings of betrayal increased the odds of mental distress and PTSD symptoms by 2.9 and 3.3 times, respectively. These associations were not significantly different between clinical and non-clinical staff. As health systems seek to enhance support of HHWs, they need to carefully examine institutional structures, accountability, communication, and decision-making patterns that can result in staff feelings of betrayal. Building trust and repairing ruptures with HHWs could prevent potential mental health problems, increase retention, and reduce burnout, while likely improving patient care. [ABSTRACT FROM AUTHOR]

An editorial is presented which reviews the development and updates of the AHRQ's "Making Health Care Safer" reports, highlighting their role in improving patient safety. It discusses the historical context of these reports, their impact on patient safety practices (PSPs), and the latest findings from recent rapid reviews on patient and family engagement and opioid stewardship.

Objectives: In the context of validating a measure of patient report specific to diagnostic accuracy in emergency department or urgent care, this study investigates patients' and care partners' perceptions of diagnoses as accurate and explores variations in how they reason while they assess accuracy. Methods: In February 2022, we surveyed a national panel of adults who had an emergency department or urgent care visit in the past month to test a patient-reported measure. As part of the survey validation, we asked for free-text responses about why the respondents indicated their (dis)agreement with 2 statements comprising patient-reported diagnostic accuracy: 1) the explanation they received of the health problem was true and 2) the explanation described what to expect of the health problem. Those paired free-text responses were qualitatively analyzed according to themes created inductively. Results: A total of 1,116 patients and care partners provided 982 responses coded into 10 themes, which were further grouped into 3 reasoning types. Almost one-third (32%) of respondents used only corroborative reasoning in assessing the accuracy of the health problem explanation (alignment of the explanation with either test results, patients' subsequent health trajectory, their medical knowledge, symptoms, or another doctor's opinion), 26% used only perception-based reasoning (perceptions of diagnostic process, uncertainty around the explanation received, or clinical team's attitudes), and 27% used both types of reasoning. The remaining 15% used general beliefs or nonexplicated logic (used only about accurate diagnoses) and combinations of general reasoning with perception-based and corroborative. Conclusions: Patients and care partners used multifaceted reasoning in their assessment of diagnostic accuracy. Implications: As health care shifts toward meaningful diagnostic co-production and shared decision making, in-depth understanding of variations in patient reasoning and mental models informs use in clinical practice. Highlights: An analysis of 982 responses examined how patients and care partners reason about the accuracy of diagnoses they received in emergency or urgent care. In reasoning, people used their perception of the process and whether the diagnosis matched other factual information they have. We introduce "patient reasoning" in the diagnostic measurement context as an area of further research to inform diagnostic shared decision making and co-production of health. [ABSTRACT FROM AUTHOR]