Healthcare Quality Measurement in Orthopaedic Surgery: Current State of the Art

Improving quality of care in arthroplasty is of increasing importance to payors, hospitals, surgeons, and patients. Efforts to compel improvement have traditionally focused measurement and reporting of data describing structural factors, care processes (or ‘quality measures’), and clinical outcomes. Reporting structural measures (eg, surgical case volume) has been used with varying degrees of success. Care process measures, exemplified by initiatives such as the Surgical Care Improvement Project measures, are chosen based on the strength of randomized trial evidence linking the process to improved outcomes. However, evidence linking improved performance on Surgical Care Improvement Project measures with improved outcomes is limited. Outcome measures in surgery are of increasing importance as an approach to compel care improvement with prominent examples represented by the National Surgical Quality Improvement Project. Although outcomes-focused approaches are often costly, when linked to active benchmarking and collaborative activities, they may improve care broadly. Moreover, implementation of computerized data systems collecting information formerly collected on paper only will facilitate benchmarking. In the end, care will only be improved if these data are used to define methods for innovating care systems that deliver better outcomes at lower or equivalent costs

Occupational post-exposure prophylaxis among healthcare workers: a scoping review of factors affecting optimal utilization.

INTRODUCTION: Post-exposure prophylaxis (PEP) is an efficacious prevention method when initiated promptly after an HIV exposure. Yet, PEP has been underutilized, even among healthcare workers (HCWs) with occupational exposure in sites with PEP policies and procedures and access to PEP medications. It is important to understand the dynamics of uneven PEP use in what appears to be an optimal context to better protect the health and wellbeing of HCWs. METHODS: We conducted a scoping review to elucidate factors influencing HCWs use of PEP after occupational exposure. We searched PubMed, PsychInfo and Google Scholar for peer-reviewed literature published in English from 2014 to 2022 using the terms HIV, postexposure/post-exposure prophylaxis, acceptability, healthcare workers, and values and preferences. An inductive narrative review of the resulting 53 studies identified core themes. RESULTS: Nearly all studies (96%) with various HCW types and settings occurred in low- and middle-income countries (LMICs) in Africa and Asia. Identified themes arrayed along a trajectory of PEP use experience: awareness/knowledge; acceptability; availability/access; uptake/use; adherence/completion. Across studies, awareness of PEP for HIV prevention was high, knowledge about drug regimens and healthcare facility policies was moderate to low; acceptability of PEP was moderate to high; PEPs perceived accessibility/availability was inconsistent and varied by geographic location and setting; HCWs uptake of PEP was low, affected by not knowing how to report an exposure and being unaware of PEP availability; and adherence/completion of PEP regimens was moderate to low, impeded by side effects and a belief that completing regimens was unnecessary to avert seroconversion. HCWs consistently expressed concern about HIV stigma. DISCUSSION: Findings are limited by the inconsistent use of constructs across studies and a lack of clarity about reporting exposure events. Multi-level approaches are needed to address the interplay of individual, social and structural barriers that diminish HCWs PEP use. Improved training, incident reporting, 24-hour access to non-stigmatizing PEP services and monitoring of adherence/completion are essential to optimizing HCWs PEP use. CONCLUSIONS: Lessons from HCWs experience in LMICs may inform understanding of PEP under-use among people in these settings with non-occupational exposures

Living with COVID-19 and preparing for future pandemics: revisiting lessons from the HIV pandemic

In April, 2020, just months into the COVID-19 pandemic, an international group of public health researchers published three lessons learned from the HIV pandemic for the response to COVID-19, which were to: anticipate health inequalities, create an enabling environment to support behavioural change, and engage a multidisciplinary effort. We revisit these lessons in light of more than 2 years’ experience with the COVID-19 pandemic. With specific examples, we detail how inequalities have played out within and between countries, highlight factors that support or impede the creation of enabling environments, and note ongoing issues with the scarcity of integrated science and health system approaches. We argue that to better apply lessons learned as the COVID-19 pandemic matures and other infectious disease outbreaks emerge, it will be imperative to create dialogue among polarised perspectives, identify shared priorities, and draw on multidisciplinary evidence

Performance of point-of-care severity scores to predict prognosis in patients admitted through the emergency department with COVID-19.

BACKGROUND: Identifying COVID-19 patients at the highest risk of poor outcomes is critical in emergency department (ED) presentation. Sepsis risk stratification scores can be calculated quickly for COVID-19 patients but have not been evaluated in a large cohort. OBJECTIVE: To determine whether well-known risk scores can predict poor outcomes among hospitalized COVID-19 patients. DESIGNS, SETTINGS, AND PARTICIPANTS: A retrospective cohort study of adults presenting with COVID-19 to 156 Hospital Corporation of America (HCA) Healthcare EDs, March 2, 2020, to February 11, 2021. INTERVENTION: Quick Sequential Organ Failure Assessment (qSOFA), Shock Index, National Early Warning System-2 (NEWS2), and quick COVID-19 Severity Index (qCSI) at presentation. MAIN OUTCOME AND MEASURES: The primary outcome was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) admission, mechanical ventilation, and vasopressors receipt. Patients scored positive with qSOFA ≥ 2, Shock Index > 0.7, NEWS2 ≥ 5, and qCSI ≥ 4. Test characteristics and area under the receiver operating characteristics curves (AUROCs) were calculated. RESULTS: We identified 90,376 patients with community-acquired COVID-19 (mean age 64.3 years, 46.8% female). 17.2% of patients died in-hospital, 28.6% went to the ICU, 13.7% received mechanical ventilation, and 13.6% received vasopressors. There were 3.8% qSOFA-positive, 45.1% Shock Index-positive, 49.8% NEWS2-positive, and 37.6% qCSI-positive at ED-triage. NEWS2 exhibited the highest AUROC for in-hospital mortality (0.593, confidence interval [CI]: 0.588-0.597), ICU admission (0.602, CI: 0.599-0.606), mechanical ventilation (0.614, CI: 0.610-0.619), and vasopressor receipt (0.600, CI: 0.595-0.604). CONCLUSIONS: Sepsis severity scores at presentation have low discriminative power to predict outcomes in COVID-19 patients and are not reliable for clinical use. Severity scores should be developed using features that accurately predict poor outcomes among COVID-19 patients to develop more effective risk-based triage

Association Between a Serotonin Transporter Gene Variant and Hopelessness Among Men in the Heart and Soul Study

Hopelessness is associated with mortality in patients with cardiac disease even after accounting for severity of depression. We sought to determine whether a polymorphism in the promoter region of the serotonin transporter gene (5-HTTLPR) is associated with increased hopelessness, and whether this effect is modified by sex, age, antidepressant use or depression in patients with coronary heart disease. We conducted a cross-sectional study of 870 patients with stable coronary heart disease. Our primary outcomes were hopelessness score (range 0-8) and hopeless category (low, moderate and high) as measured by the Everson hopelessness scale. Analysis of covariance and ordinal logistic regression were used to examine the independent association of genotype with hopelessness. Compared to patients with l/l genotype, adjusted odds of a higher hopeless category increased by 35% for the l/s genotype and 80% for s/s genotype (p-value for trend = 0.004). Analysis of covariance demonstrated that the effect of 5-HTTLPR genotype on hopelessness was modified by sex (.04), but not by racial group (p = 0.63). Among men, odds of higher hopeless category increased by 40% for the l/s genotype and by 2.3-fold for s/s genotype (p-value p < 0.001), compared to no effect in the smaller female sample (p = 0.42). Results stratified by race demonstrated a similar dose-response effect of the s allele on hopelessness across racial groups. We found that the 5-HTTLPR is independently associated with hopelessness among men with cardiovascular disease

Physician Use of Advance Care Planning Discussions in a Diverse Hospitalized Population

Two decades after the Patient Self Determination Act it is unknown how often physicians have advance care planning (ACP) discussions with hospitalized patients. The objective of this study is to investigate use of ACP discussions in a multi-ethnic, multi-lingual hospitalized population. Cross-sectional communication study of hospitalized patients. The Participants are 369 patients at one urban county hospital and one academic medical center. Interventions are not applicable. Participants were asked at baseline and a post-discharge interview whether hospital physicians had discussed either (a) what type of treatment they would want if they could not make decisions for themselves or (b) whether they would want cardiopulmonary resuscitation if needed. We compared patient characteristics for those who did and did not have an ACP discussion. Only 151 (41%) participants reported an ACP discussion. Rates of ACP were low across ethnic, language, education and age groups. In a multivariate model, scoring higher on a co-morbidity scale was associated with higher odds of reporting having had an ACP discussion during hospitalization; this finding remained after adjusting for time period and site of data collection. Multiethnic, multi-lingual hospitalized patients reported low rates of ACP discussions with their physicians regardless of ethnicity, English proficiency, education level or age

Expert-augmented machine learning.

Machine learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption is limited by the level of trust afforded by given models. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of humans and machines. Here, we present expert-augmented machine learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We used a large dataset of intensive-care patient data to derive 126 decision rules that predict hospital mortality. Using an online platform, we asked 15 clinicians to assess the relative risk of the subpopulation defined by each rule compared to the total sample. We compared the clinician-assessed risk to the empirical risk and found that, while clinicians agreed with the data in most cases, there were notable exceptions where they overestimated or underestimated the true risk. Studying the rules with greatest disagreement, we identified problems with the training data, including one miscoded variable and one hidden confounder. Filtering the rules based on the extent of disagreement between clinician-assessed risk and empirical risk, we improved performance on out-of-sample data and were able to train with less data. EAML provides a platform for automated creation of problem-specific priors, which help build robust and dependable machine-learning models in critical applications