Contextual Factors Relevant to Implementing Social Risk Factor Screening and Referrals in Cancer Survivorship: A Qualitative Study.

Introduction: Social risk factors such as food insecurity and lack of transportation can negatively affect health outcomes, yet implementation of screening and referral for social risk factors is limited in medical settings, particularly in cancer survivorship. Methods: We conducted 18 qualitative, semistructured interviews among oncology teams in 3 health systems in Washington, DC, during February and March 2022. We applied the Exploration, Preparation, Implementation, Sustainment Framework to develop a deductive codebook, performed thematic analysis on the interview transcripts, and summarized our results descriptively. Results: Health systems varied in clinical and support staff roles and capacity. None of the participating clinics had an electronic health record (EHR)-based process for identifying patients who completed their cancer treatment ("survivors") or a standardized cancer survivorship program. Their capacities also differed for documenting social risk factors and referrals in the EHR. Interviewees expressed awareness of the prevalence and effect of social risk factors on cancer survivors, but none employed a systematic process for identifying and addressing social risk factors. Recommendations for increasing screening for social risk factors included designating a person to fulfill this role, improving data tracking tools in the EHR, and creating systems to maintain up-to-date information and contacts for community-based organizations. Conclusion: The complexity of cancer care workflows and lack of reimbursement results in a limited ability for clinic staff members to screen and make referrals for social risk factors. Creating clinical workflows that are flexible and tailored to staffing realities may contribute to successful implementation of a screening and referral program. Improving ongoing communication with community-based organizations to address needs was deemed important by interviewees.

Bridging the Digital Health Divide: Characterizing Patient Portal Users and Nonusers in the U.S.

OBJECTIVE: The objectives of this study were to (1) examine demographic differences between patient portal users and nonusers; and (2) examine health literacy, patient self-efficacy, and technology usage and attitudes between patient portal users and nonusers. METHODS: Data were collected from Amazon Mechanical Turk (MTurk) workers from December 2021 to January 2022. MTurk workers completed an online survey, which asked about their health, access to technology, health literacy, patient self-efficacy, media and technology attitudes, and patient portal use for those with an account. A total of 489 MTurk workers completed the survey. Data were analyzed using latent class analysis (LCA) and multivariate logistic regression models. RESULTS: Latent class analysis models revealed some qualitative differences between users and nonusers of patient portals in relation to neighborhood type, education, income, disability status, comorbidity of any type, insurance type, and the presence or absence of primary care providers. These results were partially confirmed by logistic regression models, which showed that participants with insurance, a primary care provider, or a disability or comorbid condition were more likely to have a patient portal account. CONCLUSIONS: Our study findings suggest that access to health care, along with ongoing patient health needs, influence the usage of patient portal platforms. Patients with health insurance have the opportunity to access health care services, including establishing a relationship with a primary care provider. This relationship can be critical to a patient ever creating a patient portal account and actively engaging in their care, including communicating with their care team.

A novel application of SMART on FHIR architecture for interoperable and scalable integration of patient-reported outcome data with electronic health records.

OBJECTIVE: Despite a proliferation of applications (apps) to conveniently collect patient-reported outcomes (PROs) from patients, PRO data are yet to be seamlessly integrated with electronic health records (EHRs) in a way that improves interoperability and scalability. We applied the newly created PRO standards from the Office of the National Coordinator for Health Information Technology to facilitate the collection and integration of standardized PRO data. A novel multitiered architecture was created to enable seamless integration of PRO data via Substitutable Medical Apps and Reusable Technologies on Fast Healthcare Interoperability Resources apps and scaled to different EHR platforms in multiple ambulatory settings. MATERIALS AND METHODS: We used a standards-based approach to deploy 2 apps that source and surface PRO data in real-time for provider use within the EHR and which rely on PRO assessments from an external center to streamline app and EHR integration. RESULTS: The apps were developed to enable patients to answer validated assessments (eg, a Patient-Reported Outcomes Measurement Information System including using a Computer Adaptive Test format). Both apps were developed to populate the EHR in real time using the Health Level Seven FHIR standard allowing providers to view patients' data during the clinical encounter. The process of implementing this architecture with 2 different apps across 18 ambulatory care sites and 3 different EHR platforms is described. CONCLUSION: Our approach and solution proved feasible, secure, and time- and resource-efficient. We offer actionable guidance for this technology to be scaled and adapted to promote adoption in diverse ambulatory care settings and across different EHRs.

The Available Criteria for Different Sepsis Scoring Systems in the Emergency Department-A Retrospective Assessment.

OBJECTIVE: The goal of the study was to assess the criteria availability of eight sepsis scoring methods within 6 hours of triage in the emergency department (ED). DESIGN: Retrospective data analysis study. SETTING: ED of MedStar Washington Hospital Center (MWHC), a 912-bed urban, tertiary hospital. PATIENTS: Adult (age ≥ 18 years) patients presenting to the MWHC ED between June 1, 2017 and May 31, 2018 and admitted with a diagnosis of severe sepsis with or without shock. MAIN OUTCOMES MEASURED: Availability of sepsis scoring criteria of eight different sepsis scoring methods at three time points-0 Hours (T0), 3 Hours (T1) and 6 Hours (T2) after arrival to the ED. RESULTS: A total of 50 charts were reviewed, which included 23 (46%) males and 27 (54%) females. Forty-eight patients (96%) were Black or African American. Glasgow Coma Scale was available for all 50 patients at T0. Vital signs, except for temperature, were readily available (>90%) at T0. The majority of laboratory values relevant for sepsis scoring criteria were available (>90%) at T1, with exception to bilirubin (66%) and creatinine (80%). NEWS, PRESEP and qSOFA had greater than 90% criteria availability at triage. SOFA and SIRS consistently had the least percent of available criteria at all time points in the ED. CONCLUSION: The availability of patient data at different time points in a patient's ED visit suggests that different scoring methods could be utilized to assess for sepsis as more patient information becomes available.

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.

Risky Business: Predicting patient mortality at a glance.

Clinicians are constantly forecasting patient trajectories to make critical point of care decisions intended to influence clinical outcomes. Little is known, however, about how providers interpret mortality risk against validated scoring systems. This research aims to understand how providers forecast mortality specifically for that of patients with sepsis. Defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, sepsis is commonly hard to diagnose, progresses rapidly, and lacks a "gold standard" test. Participants were nurses and doctors from the general medical and surgical floors of six different hospitals. Each was presented with ten different patient cases, categorized into low and high severity sepsis, and were asked about care decisions, along with estimations of mortality risk. The resulting data provides a unique look into the differences of risk forecasting between profession and patient severity.

Score at the Door: A retrospective data analysis of sepsis scoring criteria in the Emergency Department.

The goal of this study was to assess the availability of the criteria of eight sepsis scoring methods (SIRS, NEWS, PRESEP, SOFA, qSOFA, SPEED, MEDS, and PIRO) within six hours of triage in the emergency department (ED). Data was analyzed through a retrospective collection of adult (age >18 years) patients presenting to the MedStar Washington Hospital Center (MWHC) emergency department between June 1, 2017 and May 31, 2018 and admitted with a sepsis or sepsis-related diagnosis that progressed to sepsis before discharge. Vital signs are frequently available upon arrival to the ED, while laboratory values tend to be available within three hours and often are not repeated again within the first six hours after arrival. The availability of patient data at different time points in a patient's ED visit suggests that different scoring methods could be utilized to more effectively diagnose and accurately risk-stratify patients within the sepsis spectrum as more information about the patient becomes available.