Promoting Equity When Using the SNOT-22 Score: A Scoping Review and Literature Review

It is established that non-white people experience worse health outcomes than white people within the same population. Equity addresses differences between patient subgroups, allowing needs-based distribution of resources. The use of quality-of-life (QoL) tools to assist clinical decision making such as the SNOT-22 for chronic rhinosinusitis promotes equality, not equity, as quality-of-life (QoL) tools provide the same criteria of symptom scoring across diverse populations. We considered the effects of ethnicity and race on SNOT-22 scores and whether these scores should be adjusted to improve equity. PubMed and MEDLINE provided papers for a scoping review. A combination of the following search terms was used: patient-reported outcome measures (PROM) (OR) quality of life; (AND) race (OR) ethnicity (OR) disparities; (AND) otolaryngology (OR) SNOT-22 (OR) sinusitis. The first study identified no evidence of ethnic variability in SNOT-22 scores. However, the study did not represent the local population, including 86% white people. Other studies identified baseline SNOT-22 disparities with respect to population demographics, gender, and age. Ethnic differences appear to exist in acute sinusitis symptomatology. In other fields both within and outside of otorhinolaryngology, ethnic differences exist with regard to QoL tools. This scoping review identified a paucity of data in rhinology. However, evidence implies some form of correction to QoL scores could help promote equity for non-white patients.

Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science

Background In this paper we describe the use of the Consolidated Framework for Implementation Research (CFIR) to study implementation of a web-based, point-of-care, EHR-linked clinical decision support (CDS) tool designed to identify and provide care recommendations for adults with prediabetes (Pre-D CDS). Methods As part of a large NIH-funded clinic-randomized trial, we identified a convenience sample of interview participants from 22 primary care clinics in Minnesota, North Dakota, and Wisconsin that were randomly allocated to receive or not receive a web-based EHR-integrated prediabetes CDS intervention. Participants included 11 clinicians, 6 rooming staff, and 7 nurse or clinic managers recruited by study staff to participate in telephone interviews conducted by an expert in qualitative methods. Interviews were recorded and transcribed, and data analysis was conducted using a constructivist version of grounded theory. Results Implementing a prediabetes CDS tool into primary care clinics was useful and well received. The intervention was integrated with clinic workflows, supported primary care clinicians in clearly communicating prediabetes risk and management options with patients, and in identifying actionable care opportunities. The main barriers to CDS use were time and competing priorities. Finally, while the implementation process worked well, opportunities remain in engaging the care team more broadly in CDS use. Conclusions The use of CDS tools for engaging patients and providers in care improvement opportunities for prediabetes is a promising and potentially effective strategy in primary care settings. A workflow that incorporates the whole care team in the use of such tools may optimize the implementation of CDS tools like these in primary care settings. Trial registration Name of the registry: Clinicaltrial.gov. Trial registration number: NCT02759055. Date of registration: 05/03/2016. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT02759055 Prospectively registered.

eCOVID19 – Development of Ontology-based Clinical Decision Support System for COVID-19

Introduction: Humankind is passing through a period of significant instability and a worldwide health catastrophe that has never been seen before. COVID-19 spread over the world at an unprecedented rate. In this context, we undertook a rapid research project in the Sultanate of Oman. We developed ecovid19 application, an ontology-based clinical decision support system (CDSS) with teleconference capability for easy, fast diagnosis and treatment for primary health centers/Satellite Clinics of the Royal Oman Police (ROP) of Sultanate of Oman.Materials and Methods: The domain knowledge and clinical guidelines are represented using ontology. Ontology is one of the most powerful methods for formally encoding medical knowledge. The primary data was from the ROP hospital's medical team, while the secondary data came from articles published in reputable journals. The application includes a COVID-19 Symptom checker for the public users with a text interface and an AI-based voice interface and is available in English and Arabic. Based on the given information, the symptom checker provides recommendations to the user. The suspected cases will be directed to the nearby clinic if the risk of infection is high. Based on the patient's current medical condition in the clinic, the CDSS will make suitable suggestions to triage staff, doctors, radiologists, and lab technicians on procedures and medicines. We used Teachable Machine to create a TensorFlow model for the analysis of X-rays. Our CDSS also has a WebRTC (Web Real-Time Communication system) based teleconferencing option for communicating with expert clinicians if the patient develops difficulties or if expert opinion is requested.Results: The ROP hospital's specialized doctors tested our CDSS, and the user interfaces were changed based on their suggestions and recommendations. The team put numerous types of test cases to assess the clinical efficacy. Precision, sensitivity (recall), specificity, and accuracy were adequate in predicting the various categories of patient instances.Conclusion: The proposed CDSS has the potential to significantly improve the quality of care provided to Oman's citizens. It can also be tailored to fit other terrifying pandemics.

Alerts as Coordination Mechanisms

In this study, we explore how clinical decision support features can be designed to aid teams in caring for patients during time-critical medical emergencies. We interviewed 12 clinicians with experience in leading pediatric trauma resuscitations to elicit design requirements for decision support alerts and how these alerts should be designed for teams with shared leadership. Based on the interview data, we identified three types of decision support alerts: reminders to perform tasks, alerts to changes in patient status, and suggestions for interventions. We also found that clinicians perceived alerts in this setting as coordination mechanisms and that some alert preferences were associated with leader experience levels. From these findings, we contribute three perspectives on how alerts can aid coordination and discuss implications for designing decision support alerts for shared leadership in time-critical medical processes.

Patients’ and physicians’ experiences with remote consultations in primary care, during the covid-19 pandemic: a multi-method rapid review of the literature.

BackgroundDuring the COVID-19 pandemic, many countries implemented remote consultations in primary care to protect patients and staff from infection.AimThe aim of this review was to synthesise the literature exploring patients’ and physicians’ experiences with remote consultations in primary care, during the pandemic, with the further aim of informing their future delivery.Design & settingRapid literature review.MethodWe searched PubMed and PsychInfo for studies that explored patients’ and physicians’ experiences with remote consultations in primary care. To determine the eligibility of studies, we reviewed their titles and abstracts, prior to the full paper. We then extracted qualitative and quantitative data from those that were eligible, and synthesised the data using thematic and descriptive synthesis.ResultsA total of twenty-four studies were eligible for inclusion in the review. Most were performed in the United States of America (n=7, 29%) or Europe (n=7, 29%). Patient and physician experiences were categorised into perceived ‘advantages’ and ‘issues’. Key advantages experienced by patients and physicians included: ‘Reduced risk of COVID-19’ and ‘Increased convenience’, while key issues included: ‘a lack of confidence in / access to required technology’ and a ‘loss of non-verbal communication’, which exacerbated clinical decision making.ConclusionThis review identified a number of advantages and issues experienced by patients and physicians using remote consultations in primary care. The results suggest that, while remote consultations are more convenient, and protect patients and staff against COVID-19, they result in the loss of valuable non-verbal communication, and are not accessible to all.

A Mixed-Methods Feasibility Study of a Novel AI-Enabled, Web-Based, Clinical Decision Support System for the Treatment of Major Depression in Adults

The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in the treatment of adults with major depression. Patients had a baseline appointment, followed by a minimum of two appointments with the CDSS. For both physicians and patients, study exit questionnaires and interviews were conducted to assess perceived clinical utility, impact on patient-physician relationship, and understanding and trust in the CDSS. 17 patients consented to participate in the study, of which 14 completed. 86% of physicians (6/7) felt the information provided by the CDSS provided a more comprehensive understanding of patient situations and 71% (5/7) felt the information was helpful. 86% of physicians (6/7) reported the AI/predictive model was useful when making treatment decisions. 62% of patients (8/13) reported improvement in their care as a result of the tool. 46% of patients (6/13) felt the app significantly or somewhat improved their relationship with their physicians; 54% felt it did not change. 71% of physicians (5/7) and 62% of patients (8/13) rated they trusted the tool. Qualitative results are analyzed and presented. Findings suggest physicians perceived the tool as useful in conducting appointments and used it while making treatment decisions. Physicians and patients generally found the tool trustworthy, and it may have positive effects on physician-patient relationships.