Multilevel approaches to address disparities in lung cancer screening: a study protocol.

BACKGROUND: Low-dose computed tomography (lung cancer screening) can reduce lung cancer-specific mortality by 20-24%. Based on this evidence, the United States Preventive Services Task Force recommends annual lung cancer screening for asymptomatic high-risk individuals. Despite this recommendation, utilization is low (3-20%). Lung cancer screening may be particularly beneficial for African American patients because they are more likely to have advanced disease, lower survival, and lower screening rates compared to White individuals. Evidence points to multilevel approaches that simultaneously address multiple determinants to increase screening rates and decrease lung cancer burden in minoritized populations. This study will test the effects of provider- and patient-level strategies for promoting equitable lung cancer screening utilization. METHODS: Guided by the Health Disparities Research Framework and the Practical, Robust Implementation and Sustainability Model, we will conduct a quasi-experimental study with four primary care clinics within a large health system (MedStar Health). Individuals eligible for lung cancer screening, defined as 50-80 years old, ≥ 20 pack-years, currently smoking, or quit < 15 years, no history of lung cancer, who have an appointment scheduled with their provider, and who are non-adherent to screening will be identified via the EHR, contacted, and enrolled (N = 184 for implementation clinics, N = 184 for comparison clinics; total N = 368). Provider participants will include those practicing at the partner clinics (N = 26). To increase provider-prompted discussions about lung screening, an electronic health record (EHR) clinician reminder will be sent to providers prior to scheduled visits with the screening-eligible participants. To increase patient-level knowledge and patient activation about screening, an inreach specialist will conduct a pre-visit phone-based educational session with participants. Patient participants will be assessed at baseline and 1-week post-visit to measure provider-patient discussion, screening intentions, and knowledge. Screening referrals and screening completion rates will be assessed via the EHR at 6 months. We will use mixed methods and multilevel assessments of patients and providers to evaluate the implementation outcomes (adoption, feasibility, acceptability, and fidelity). DISCUSSION: The study will inform future work designed to measure the independent and overlapping contributions of the multilevel implementation strategies to advance equity in lung screening rates. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04675476. Registered December 19, 2020.

Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records.

BACKGROUND: Despite established relationships between diabetic status and an increased risk for COVID-19 severe outcomes, there is a limited number of studies examining the relationships between diabetes complications and COVID-19-related risks. We use the Adapted Diabetes Complications Severity Index to define seven diabetes complications. We aim to understand the risk for COVID-19 infection, hospitalization, mortality, and longer length of stay of diabetes patients with complications. METHODS: We perform a retrospective case-control study using Electronic Health Records (EHRs) to measure differences in the risks for COVID-19 severe outcomes amongst those with diabetes complications. Using multiple logistic regression, we calculate adjusted odds ratios (OR) for COVID-19 infection, hospitalization, and in-hospital mortality of the case group (patients with diabetes complications) compared to a control group (patients without diabetes). We also calculate adjusted mean difference in length of stay between the case and control groups using multiple linear regression. RESULTS: Adjusting demographics and comorbidities, diabetes patients with renal complications have the highest odds for COVID-19 infection (OR = 1.85, 95% CI = [1.71, 1.99]) while those with metabolic complications have the highest odds for COVID-19 hospitalization (OR = 5.58, 95% CI = [3.54, 8.77]) and in-hospital mortality (OR = 2.41, 95% CI = [1.35, 4.31]). The adjusted mean difference (MD) of hospital length-of-stay for diabetes patients, especially those with cardiovascular (MD = 0.94, 95% CI = [0.17, 1.71]) or peripheral vascular (MD = 1.72, 95% CI = [0.84, 2.60]) complications, is significantly higher than non-diabetes patients. African American patients have higher odds for COVID-19 infection (OR = 1.79, 95% CI = [1.66, 1.92]) and hospitalization (OR = 1.62, 95% CI = [1.39, 1.90]) than White patients in the general diabetes population. However, White diabetes patients have higher odds for COVID-19 in-hospital mortality. Hispanic patients have higher odds for COVID-19 infection (OR = 2.86, 95% CI = [2.42, 3.38]) and shorter mean length of hospital stay than non-Hispanic patients in the general diabetes population. Although there is no significant difference in the odds for COVID-19 hospitalization and in-hospital mortality between Hispanic and non-Hispanic patients in the general diabetes population, Hispanic patients have higher odds for COVID-19 hospitalization (OR = 1.83, 95% CI = [1.16, 2.89]) and in-hospital mortality (OR = 3.69, 95% CI = [1.18, 11.50]) in the diabetes population with no complications. CONCLUSIONS: The presence of diabetes complications increases the risks of COVID-19 infection, hospitalization, and worse health outcomes with respect to in-hospital mortality and longer hospital length of stay. We show the presence of health disparities in COVID-19 outcomes across demographic groups in our diabetes population. One such disparity is that African American and Hispanic diabetes patients have higher odds of COVID-19 infection than White and Non-Hispanic diabetes patients, respectively. Furthermore, Hispanic patients might have less access to the hospital care compared to non-Hispanic patients when longer hospitalizations are needed due to their diabetes complications. Finally, diabetes complications, which are generally associated with worse COVID-19 outcomes, might be predominantly determining the COVID-19 severity in those infected patients resulting in less demographic differences in COVID-19 hospitalization and in-hospital mortality.

Patient-Reported Data Augment Prediction Models of Persistent Opioid Use after Elective Upper Extremity Surgery.

BACKGROUND: Opioids play a role in pain management after surgery, but prolonged use contributes to developing opioid use disorder. Identifying patients at risk of prolonged use is critical for deploying interventions that reduce or avoid opioids; however, available predictive models do not incorporate patient-reported data (PRD), and it remains unclear whether PRD can predict postoperative use behavior. The authors used a machine learning approach leveraging preoperative PRD and electronic health record data to predict persistent opioid use after upper extremity surgery. METHODS: Included patients underwent upper extremity surgery, completed preoperative PRD questionnaires, and were prescribed opioids after surgery. The authors trained models using a 2018 cohort and tested in a 2019 cohort. Opioid use was determined by patient report and filled prescriptions up to 6 months after surgery. The authors assessed model performance using area under the receiver operating characteristic, sensitivity, specificity, and Brier score. RESULTS: Among 1656 patients, 19% still used opioids at 6 weeks, 11% at 3 months, and 9% at 6 months. The XGBoost model trained on PRD plus electronic health record data achieved area under the receiver operating characteristic 0.73 at 6 months. Factors predictive of prolonged opioid use included income; education; tobacco, drug, or alcohol abuse; cancer; depression; and race. Protective factors included preoperative Patient-Reported Outcomes Measurement Information System Global Physical Health and Upper Extremity scores. CONCLUSIONS: This opioid use prediction model using preintervention data had good discriminative performance. PRD variables augmented electronic health record-based machine learning algorithms in predicting postsurgical use behaviors and were some of the strongest predictors. PRD should be used in future efforts to guide proper opioid stewardship. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

Preoperative Patient-Reported Data Indicate the Risk of Prolonged Opioid Use After Hand and Upper Extremity Surgeries.

PURPOSE: Opioids play an important role in pain management after surgery but also increase the risk of prolonged opioid use in patients. The identification of patients who are more likely to use opioids after intended short-term treatment is critical for employing alternative management approaches or targeted interventions for the prevention of opioid-related problems. We used patient-reported data (PRD) and electronic health record information to identify factors predictive of prolonged opioid use after surgery. METHODS: We used our institutional registry containing data on all patients who underwent elective upper extremity surgeries. We evaluated factors associated with prolonged opioid use in the cohort from the year 2018 to 2019. We then validated our results using the 2020 cohort. The predictive variables included preoperative PRD and electronic health record data. Opioid use was determined based on patient reports and/or filled opioid prescriptions 3 months after surgery. We conducted bivariate regression, followed by multivariable regression analyses, and model validation using area under the receiver operating curve. RESULTS: We included 2,114 patients. In our final model on the 2018-2019 electronic health records and PRD data (n = 1,589), including numerous patient-reported outcome questionnaire scores, patients who were underweight and had undergone trauma-related surgery had higher odds of being on opioids at 3 months. Additionally, each 5-unit decrease in the preoperative Patient-Reported Outcomes Measurement Information System Global Physical Health score was associated with a 30% increased odds of being on opioids at 3 months. The area under the receiver operating curve of our model was 70.4%. On validation using data from the 2020 cohort, the area under the receiver operating curve was 60.3%. The Hosmer-Lemeshow test indicated a good fit. CONCLUSIONS: We found that preoperative questionnaire scores were associated with prolonged postoperative opioid use, independent of other variables. Furthermore, PRD may provide unique patient-level insights, alongside other factors, to improve our understanding of postsurgical pain management. TYPE OF STUDY/LEVEL OF EVIDENCE: Prognostic II.

Notice to comply: A systematic review of clinician compliance with guidelines surrounding acute hospital-based infection management.

PURPOSE: To identify and characterize studies evaluating clinician compliance with infection-related guidelines, and to explore trends in guideline design and implementation strategies. DATA SOURCES: PubMed database, April 2017. Followed the PRISMA Statement for systematic reviews. STUDY SELECTION: Scope was limited to studies reporting compliance with guidelines pertaining to the prevention, detection, and/or treatment of acute hospital-based infections. Initial search (1,499 titles) was reduced to 49 selected articles. DATA EXTRACTION: Extracted publication and guideline characteristics, outcome measures reported, and any results related to clinician compliance. Primary summary measures were frequencies and distributions of characteristics. Interventions that led to improved compliance results were analyzed to identify trends in guideline design and implementation. RESULTS OF DATA SYNTHESIS: Of the 49 selected studies, 18 (37%), 13 (27%), and 10 (20%) focused on sepsis, pneumonia, and general infection, respectively. Six (12%), 17 (35%), and 26 (53%) studies assessed local, national, and international guidelines, respectively. Twenty studies (41%) reported 1-instance compliance results, 28 studies (57%) reported 2-instance compliance results (either before-and-after studies or control group studies), and 1 study (2%) described compliance qualitatively. Average absolute change in compliance for minimal, decision support, and multimodal interventions was 10%, 14%, and 25%, respectively. Twelve studies (24%) reported no patient outcome alongside compliance. CONCLUSIONS: Multimodal interventions and quality improvement initiatives seem to produce the greatest improvement in compliance, but trends in other factors were inconsistent. Additional research is required to investigate these relationships and understand the implications behind various approaches to guideline design, communication, and implementation, in addition to effectiveness of protocol impact on relevant patient outcomes.

Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis.

In caring for patients with sepsis, the current structure of electronic health record systems allows clinical providers access to raw patient data without imputation of its significance. There are a wide range of sepsis alerts in clinical care that act as clinical decision support tools to assist in early recognition of sepsis; however, there are serious shortcomings in existing health information technology for alerting providers in a meaningful way. Little work has been done to evaluate and assess existing alerts using implementation and process outcomes associated with health information technology displays, specifically evaluating clinician preference and performance. We developed graphical model displays of two popular sepsis scoring systems, quick Sepsis Related Organ Failure Assessment and Predisposition, Infection, Response, Organ Failure, using human factors principles grounded in user-centered and interaction design. Models will be evaluated in a larger research effort to optimize alert design to improve the collective awareness of high-risk populations and develop a relevant point-of-care clinical decision support system for sepsis.

Not all organ dysfunctions are created equal - Prevalence and mortality in sepsis.

PURPOSE: While organ dysfunctions within sepsis have been widely studied, interaction between measures of organ dysfunction remains an understudied area. The objective of this study is to quantify the impact of organ dysfunction on in-hospital mortality in infected population. MATERIALS AND METHODS: Descriptive and multivariate analyses of retrospective data including patients (age ≥ 18 years) hospitalized at the study hospital from July 2013 to April 2016 who met the criteria for an infection visit (62,057 unique visits). RESULTS: The multivariate logistic regression model had an area under the curve of 0.9. Highest odds ratio (OR) associated with increased mortality risk was identified as fraction of inspired oxygen (FiO2) > 21% (OR = 5.8 and 95% Confidence Interval (CI) 1.8-35.6), and elevated lactate >2.0 mmol/L (OR = 2.45 (95% CI = 2.1-2.8)). Most commonly observed measures of organ dysfunction within mortality visits included elevated lactate (> 2.0 mmol/L), mechanical ventilation, and oxygen saturation (SpO2)/FiO2 ratio (< 421) at least once within 48 h prior to or 24 h after anti-infective administration. CONCLUSION: There exist differences in measures of organ dysfunction occurrence and their association with mortality. These findings support increased clinical efforts to identify sepsis patients to inform diagnostic decisions.

Data-driven approach to Early Warning Score-based alert management.

BACKGROUND: Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals. METHODS: We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure. RESULTS: We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics. CONCLUSION: EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.

The Patient in Precision Medicine: A Systematic Review Examining Evaluations of Patient-Facing Materials.

Precision medicine (PM) has the potential to tailor healthcare to the individual patient by using their genetic information to guide treatment choices. However, this process is complex and difficult to understand for patients and providers alike. With a recent push in the healthcare community to understand the patient experience and engage patients in their care, it is important to give patients the opportunity to learn about PM. We performed a systematic review to identify previous work assessing the quality of patient-facing PM materials from 2008 to July 2018. Ten studies were identified, which used varying methods and measures. A qualitative assessment was conducted to compare key elements of the studies, including study design, characteristics of the participant population, what measurements were used to assess the PM materials, understandability, preference, psychological reactions, and the type of PM materials being assessed. The studies identified provide important groundwork by highlighting consistent aspects of design that aid in comprehension. Eight of the ten studies focused on the content and organization of genomic test results, while the remaining two assessed educational tools. Two main design elements that appeared across the studies were appropriately designed visual aids and simplified language. The studies identified were limited by the participant populations that were used, which were primarily white and well educated. Only one study attempted to oversample patient populations typically underrepresented in this type of research. Through our systematic review, it is evident that the breadth of knowledge in this field is limited in scope and that more work must be done to ensure that patients can engage in their care when faced with PM.

Improving Infusion Pump Safety Through Usability Testing.

With the recognition that the introduction of new technology causes changes in workflow and may introduce new errors to the system, usability testing was performed to provide data on nursing practice and interaction with infusion pump technology. Usability testing provides the opportunity to detect and analyze potentially dangerous problems with the design of infusion pumps that could cause or allow avoidable errors. This work will reduce preventable harm through the optimization of health care delivery.

Predicting violent behavior in clinical settings: a case-control study of a mental health inpatient unit.

In order to assist staff in recognizing patients prone to violence and guide their clinical decision-making, this study summarizes mental health inpatient unit incidents over a one-year period. Results describe demographic and clinical information for patients, and evaluate risk assessment tools currently used to predict risk. A retrospective analysis included data on patients involved in incidents and frequency matched controls. There were a total of 44 incidents, caused by 38 unique patients. A constructed model to estimate patient characteristics and risk of violent incidents included involuntary admittance (OR 2.07, 95% CI 1.05-6.11, p = 0.039), more than one admission at the facility (OR 4.18, 95% CI 1.71-10.22, p = 0.002) and Global Subjective Irritability on day one (OR 4.24, 95% CI 1.77-10.16, p = 0.001). Violent incidents on the mental inpatient unit threaten safety and disrupt the therapeutic environment. The findings may be useful in aiding clinicians to quickly recognize patients that are prone to violence.

Wrong-side thoracentesis: lessons learned from root cause analysis.

IMPORTANCE: Despite the recognized value of the Joint Commission's Universal Protocol and the implementation of time-outs, incorrect surgical procedures are still among the most common types of sentinel events and can have fatal consequences. OBJECTIVES: To examine a root cause analysis database for reported wrong-side thoracenteses and to determine the contributing factors associated with their occurrence. DESIGN, SETTING, AND PARTICIPANTS: We searched the National Center for Patient Safety database for wrong-side thoracenteses performed in ambulatory clinics and hospital units other than the operating room reported from January 1, 2004, through December 31, 2011. MAIN OUTCOMES AND MEASURES: Data extracted included patient factors, clinical features, team structure and function, adherence to bottom-line patient safety measures, complications, and outcomes. RESULTS: Fourteen cases of wrong-side thoracenteses are identified. Contributing factors included failure to perform a time-out (n=12), missing indication of laterality on the patient's consent form (n=10), absence of a site mark on the patient's skin within the sterile field (n=12), and absent verification of medical images (n=7). Complications included pneumothoraces (n=4), hemorrhage (n=3), and death directly attributable to the wrong-side thoracentesis (n=2). Teamwork and communication failure, unawareness of existing policy, and a deficit in training and education were the most common root causes of wrong-side thoracentesis. CONCLUSIONS AND RELEVANCE: Prevention of wrong-site procedures and accompanying patient harm outside the operating room requires adherence to the Universal Protocol and time-outs, effective teamwork, training and education, mentoring, and patient assessment for early detection of complications. The time-outs provide protected time and place for error detection and recovery.

Efficacy of acupressure and acustimulation bands for the prevention of motion sickness.

INTRODUCTION: The purpose of this study was to examine whether acupressure and acustimulation prevent motion sickness, taking into consideration whether or not the acupressure and acustimulation are administered properly. These techniques claim to reduce nausea through stimulation of the P6/Neiguan acupuncture point by applying acupressure or electrical acustimulation. METHODS: The Acuband and ReliefBand were used to administer acupressure and acustimulation, respectively. There were 77 subjects who were assigned to 1 of 5 conditions: Acuband trained or untrained; ReliefBand trained or untrained; or placebo. Subjects were exposed to a 20-min baseline and a maximum of 20 min of optokinetic drum rotation. Untrained subjects read the device directions, used it as they deemed appropriate, and completed a usability analysis following drum exposure. Trained subjects read the device directions and were trained to use the device appropriately prior to drum exposure. Symptoms and gastric myoelectric activity were monitored during baseline and rotation. RESULTS: In all conditions, symptoms of motion sickness and gastric tachyarrhythmia increased, and 3 cpm gastric myoelectric activity decreased, during drum exposure. The only difference found between conditions was a potential delay in symptom onset for the ReliefBand compared with the Acuband. While the Acuband was found difficult to use (0 untrained subjects used it correctly) and only a few minor usability issues were identified for the ReliefBand, usability had no impact on efficacy. DISCUSSION: Neither band nor placebo prevented the development of motion sickness, regardless of whether the bands were used correctly or incorrectly.