Patient Retention in a Substance Use Disorder Telemedicine Clinic.

OBJECTIVES: Although research has continued to show that substance use disorders (SUDs) can be treated effectively with evidence-based treatment, there continues to be gaps in access, and utilization remains low. Alternative SUD treatment methods, including telemedicine, are increasingly being explored to reach patients where traditional in-person treatment approaches are inaccessible. This cross-sectional study aimed to explore SUD treatment retention, specifically comparing telemedicine-delivered opioid use disorder (OUD) treatment with a traditional in-person treatment delivery approach. METHODS: Patients at Cahaba Medical Care, an FQHC in Birmingham, AL with a diagnosis of OUD and undergoing buprenorphine/naloxone or buprenorphine treatment were categorized into two groups: treatment and control. The dependent variable, retention to SUD treatment, was assessed at four different time periods over 12 months to determine patient SUD consultation appointment attendance. Multiple linear regression was used to examine the relationship between SUD treatment retention and delivery mode. Correlations were obtained to assess associations between frequency of urine drug screens performed and SUD treatment retention. RESULTS: As the number of the urine drug screens patients received increased by 1, the number of SUD treatment program consultations patients attended increased by 0.69 (P < 0.001). There was no significant difference in SUD treatment retention between traditional in-person and telemedicine delivered approaches, however. CONCLUSIONS: The findings of this study suggest that a telemedicine-delivered treatment program equals retention effectiveness when compared with in-person delivery. This suggests that leveraging telemedicine to treat patients with SUD could be an effective alternative for those unable to access treatment or who are less likely to attend or complete traditional in-person treatment sessions.

Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection.

BACKGROUND: The semantics of entities extracted from a clinical text can be dramatically altered by modifiers, including entity negation, uncertainty, conditionality, severity, and subject. Existing models for determining modifiers of clinical entities involve regular expression or features weights that are trained independently for each modifier. METHODS: We develop and evaluate a multi-task transformer architecture design where modifiers are learned and predicted jointly using the publicly available SemEval 2015 Task 14 corpus and a new Opioid Use Disorder (OUD) data set that contains modifiers shared with SemEval as well as novel modifiers specific for OUD. We evaluate the effectiveness of our multi-task learning approach versus previously published systems and assess the feasibility of transfer learning for clinical entity modifiers when only a portion of clinical modifiers are shared. RESULTS: Our approach achieved state-of-the-art results on the ShARe corpus from SemEval 2015 Task 14, showing an increase of 1.1% on weighted accuracy, 1.7% on unweighted accuracy, and 10% on micro F1 scores. CONCLUSIONS: We show that learned weights from our shared model can be effectively transferred to a new partially matched data set, validating the use of transfer learning for clinical text modifiers.

Improving Communication with Family Members during a Global Pandemic: Effect on Patient Experience.

OBJECTIVES: Communication with patients and their families/caregivers to facilitate informed decision making is an integral part of patient/family-centered care. Due to the high coronavirus disease 2019 (COVID-19) infection rates and limited personal protective equipment, healthcare systems were forced to restrict patient visitors, limit patient-provider interactions, and implement other changes in treatment protocols that disturbed traditional communications and risked eroding patient/family-centered care and adversely affected patient satisfaction. This article focuses on changes in patient experience in two dedicated COVID-19 units of an academic medical center located in the US South as a result of the enhanced communication process implemented specifically during the COVID-19 pandemic. METHODS: This retrospective quality improvement project used data from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys, fielded between January 1, 2021 and August 31, 2021, to understand the role of a proactive communication initiative in patient satisfaction. RESULTS: Our results show that HCAHPS scores for hospital unit hospital unit 4 (HSP4) in all categories increased over time, with the greatest improvements seen in the responsiveness of staff and care transition; however, HCAHPS scores for hospital unit HSP3 remained stable, with a small increase in responsiveness of staff. CONCLUSIONS: Our findings suggest that communication is a critical factor in patient satisfaction, demonstrating the efficacy of a swift and innovative initiative to improve communication with family/caregivers, which may have been linked to better patient experiences. Developing communication strategies is crucial for enhancing patient satisfaction.

COVID-19 Pandemic Impact on Nursing Homes Financial Performance.

Nursing homes expressed concern about potential severe adverse financial outcomes of COVID-19, with worries extending to the possibility of some facilities facing closure. Maintaining a strong financial well-being is crucial, and there were concerns that the pandemic might have significantly impacted both expenses and income. This longitudinal study aimed to analyze the financial performance of nursing homes during COVID-19 pandemic. Specifically, we examined the impact of the pandemic on nursing home operating margins, operating revenue per resident day, and operating cost per resident day. The study utilized secondary data from various sources, including CMS Medicare cost reports, Brown University's Long Term Care Focus (LTCFocus), CMS Payroll-Based Journal, CMS Care Compare, Area Health Resource File, Provider Relief Fund distribution data, and CDC's NH COVID-19 public file. The sample consisted of 45 833 nursing home-year observations from 2018 to 2021. Fixed-effects regression analysis was employed to assess the impact of the pandemic on financial performance while controlling for various organizational and market characteristics. The study found that nursing homes' financial performance deteriorated during the COVID-19 pandemic. Operating margins decreased by approximately 4.3%, while operating costs per resident day increased by $26.51, outweighing the increase in operating revenue per resident day by about $17. Occupancy rates, payer mix, and staffing intensity were found to impact financial performance. The study highlights the significant financial impact of the COVID-19 pandemic on nursing homes. While nursing homes faced substantial financial strains, the findings offered lessons for the future, underscoring the need for nursing homes to improve the accuracy of their cost reports and enhance financial transparency and accountability.

Value of Electronic Health Records Measured Using Financial and Clinical Outcomes: Quantitative Study.

BACKGROUND: The Health Information Technology for Economic and Clinical Health Act of 2009 was legislated to reduce health care costs, improve quality, and increase patient safety. Providers and organizations were incentivized to exhibit meaningful use of certified electronic health record (EHR) systems in order to achieve this objective. EHR adoption is an expensive investment, given the resources and capital that are invested. Due to the cost of the investment, a return on the EHR adoption investment is expected. OBJECTIVE: This study performed a value analysis of EHRs. The objective of this study was to investigate the relationship between EHR adoption levels and financial and clinical outcomes by combining both financial and clinical outcomes into one conceptual model. METHODS: We examined the multivariate relationships between different levels of EHR adoption and financial and clinical outcomes, along with the time variant control variables, using moderation analysis with a longitudinal fixed effects model. Since it is unknown as to when hospitals begin experiencing improvements in financial outcomes, additional analysis was conducted using a 1- or 2-year lag for profit margin ratios. RESULTS: A total of 5768 hospital-year observations were analyzed over the course of 4 years. According to the results of the moderation analysis, as the readmission rate increases by 1 unit, the effect of a 1-unit increase in EHR adoption level on the operating margin decreases by 5.38%. Hospitals with higher readmission payment adjustment factors have lower penalties. CONCLUSIONS: This study fills the gap in the literature by evaluating individual relationships between EHR adoption levels and financial and clinical outcomes, in addition to evaluating the relationship between EHR adoption level and financial outcomes, with clinical outcomes as moderators. This study provided statistically significant evidence (P<.05), indicating that there is a relationship between EHR adoption level and operating margins when this relationship is moderated by readmission rates, meaning hospitals that have adopted EHRs could see a reduction in their readmission rates and an increase in operating margins. This finding could further be supported by evaluating more recent data to analyze whether hospitals increasing their level of EHR adoption would decrease readmission rates, resulting in an increase in operating margins. Hospitals would incur lower penalties as a result of improved readmission rates, which would contribute toward improved operating margins.

Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text.

Natural Language Processing can be used to identify opioid use disorder in patients from clinical text1. We annotate a corpus of clinical text for mentions of concepts associated with unhealthy use of opiates including concept modifiers such as negation, subject, uncertainty, relation to document time and illicit use.

Evaluation of a COVID-19 Risk Tool.

Some of the most vexing issues with the COVID-19 pandemic were the inability of schools and work areas to track symptoms. Technology solutions to mitigate repercussions of the COVID-19 pandemic include tools that provide guidelines and interfaces to influence behavior, reduce exposure to the disease, and enable policy-driven avenues to return to a sense of normalcy (e.g., school and work). This presentation presents the implementation and early evaluation of a return-to-work COVID-19 symptom and risk assessment tool.

Substance Use Telemedicine Retention and Outcomes.

Evidence-based SUD treatments are available, yet utilization remains low demonstrating the need to utilize alternative treatment delivery methods. We assess the effectiveness of an SUD treatment program delivered via telemedicine and in-person mode over 12 months. 40% of the intervention group remained engaged and 46% remained opioid free.

Foundational domains and competencies for baccalaureate health informatics education.

BACKGROUND: Foundational domains are the building blocks of educational programs. The lack of foundational domains in undergraduate health informatics (HI) education can adversely affect the development of rigorous curricula and may impede the attainment of CAHIIM accreditation of academic programs. OBJECTIVE: This White Paper presents foundational domains developed by AMIA's Academic Forum Baccalaureate Education Committee (BEC) which include corresponding competencies (knowledge, skills, and attitudes) that are intended for curriculum development and CAHIIM accreditation quality assessment for undergraduate education in applied health informatics. METHODS: The AMIA BEC used the previously published master's foundational domains as a guide to creating a set of competencies for health informatics at the undergraduate level to assess graduates from undergraduate health informatics programs for competence at graduation. A consensus method was used to adapt the domains for undergraduate level course work and harmonize the foundational domains with the currently adapted domains for HI master's education. RESULTS: Ten foundational domains were developed to support the development and evaluation of baccalaureate health informatics education. DISCUSSION: This article will inform future work towards building CAHIIM accreditation standards to ensure that higher education institutions meet acceptable levels of quality for undergraduate health informatics education.

The Utility of Predictive Modeling and a Systems Process Approach to Reduce Emergency Department Crowding: A Position Paper.

Emergency department (ED) crowding and its main causes, exit block and boarding, continue to threaten the quality and safety of ED care. Most interventions to reduce crowding have not been comprehensive or system solutions, only focusing on part of the care procession and not directly affecting boarding reduction. This position paper proposes that the ED crowding problem can be optimally addressed by applying a systems approach using predictive modeling to identify patients at risk of being admitted to the hospital and uses that information to initiate the time-consuming bed management process earlier in the care continuum, shortening the time during which patients wait in the ED for an inpatient bed assignment, thus removing the exit block that causes boarding and subsequently reducing crowding.

Corrigendum: User perceptions about sharing exposure notification information for communicable diseases.

[This corrects the article DOI: 10.3389/fdgth.2022.926683.].

Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study.

BACKGROUND: Some of the most vexing issues with the COVID-19 pandemic were the inability of facilities and events, such as schools and work areas, to track symptoms to mitigate the spread of the disease. To combat these challenges, many turned to the implementation of technology. Technology solutions to mitigate repercussions of the COVID-19 pandemic include tools that provide guidelines and interfaces to influence behavior, reduce exposure to the disease, and enable policy-driven avenues to return to a sense of normalcy. This paper presents the implementation and early evaluation of a return-to-work COVID-19 symptom and risk assessment tool. The system was implemented across 34 institutions of health and education in Alabama, including more than 174,000 users with over 4 million total uses and more than 86,000 reports of exposure risk between July 2020 and April 2021. OBJECTIVE: This study aimed to explore the usage of technology, specifically a COVID-19 symptom and risk assessment tool, to mitigate exposure to COVID-19 within public spaces. More specifically, the objective was to assess the relationship between user-reported symptoms and exposure via a mobile health app, with confirmed COVID-19 cases reported by the Alabama Department of Public Health (ADPH). METHODS: This cross-sectional study evaluated the relationship between confirmed COVID-19 cases and user-reported COVID-19 symptoms and exposure reported through the Healthcheck web-based mobile application. A dependent variable for confirmed COVID-19 cases in Alabama was obtained from ADPH. Independent variables (ie, health symptoms and exposure) were collected through Healthcheck survey data and included measures assessing COVID-19-related risk levels and symptoms. Multiple linear regression was used to examine the relationship between ADPH-confirmed diagnosis of COVID-19 and self-reported health symptoms and exposure via Healthcheck that were analyzed across the state population but not connected at the individual patient level. RESULTS: Regression analysis showed that the self-reported information collected by Healthcheck significantly affects the number of COVID-19-confirmed cases. The results demonstrate that the average number of confirmed COVID-19 cases increased by 5 (high risk: ß=5.10; P=.001), decreased by 24 (sore throat: ß=-24.03; P=.001), and increased by 21 (nausea or vomiting: ß=21.67; P=.02) per day for every additional self-report of symptoms by Healthcheck survey respondents. Congestion or runny nose was the most frequently reported symptom. Sore throat, low risk, high risk, nausea, or vomiting were all statistically significant factors. CONCLUSIONS: The use of technology allowed organizations to remotely track a population as it is related to COVID-19. Healthcheck was a platform that aided in symptom tracking, risk assessment, and evaluation of status for admitting individuals into public spaces for people in the Alabama area. The confirmed relationship between symptom and exposure self-reporting using an app and population-wide confirmed cases suggests that further investigation is needed to determine the opportunity for such apps to mitigate disease spread at a community and individual level.

Mapping the delineation of practice to the AMIA foundational domains for applied health informatics.

OBJECTIVE: This article reports on the alignment between the foundational domains and the delineation of practice (DoP) for health informatics, both developed by the American Medical Informatics Association (AMIA). Whereas the foundational domains guide graduate-level curriculum development and accreditation assessment, providing an educational pathway to the minimum competencies needed as a health informatician, the DoP defines the domains, tasks, knowledge, and skills that a professional needs to competently perform in the discipline of health informatics. The purpose of this article is to determine whether the foundational domains need modification to better reflect applied practice. MATERIALS AND METHODS: Using an iterative process and through individual and collective approaches, the foundational domains and the DoP statements were analyzed for alignment and eventual harmonization. Tables and Sankey plot diagrams were used to detail and illustrate the resulting alignment. RESULTS: We were able to map all the individual DoP knowledge statements and tasks to the AMIA foundational domains, but the statements within a single DoP domain did not all map to the same foundational domain. Even though the AMIA foundational domains and DoP domains are not in perfect alignment, the DoP provides good examples of specific health informatics competencies for most of the foundational domains. There are, however, limited DoP knowledge statements and tasks mapping to foundational domain 6-Social and Behavioral Aspects of Health. DISCUSSION: Both the foundational domains and the DoP were developed independently, several years apart, and for different purposes. The mapping analyses reveal similarities and differences between the practice experience and the curricular needs of health informaticians. CONCLUSIONS: The overall alignment of both domains may be explained by the fact that both describe the current and/or future health informatics professional. One can think of the foundational domains as representing the broad foci for educational programs for health informaticians and, hence, they are appropriately the focus of organizations that accredit these programs.

Evaluating Outcomes and Time Delays of a Non-Trainee-Driven Hospitalist Procedure Service.

BACKGROUND AND OBJECTIVES: Ultrasound guidance has become standard of care in hospital medicine for invasive bedside procedures, especially central venous catheter placement. Despite ultrasound-guided bedside procedures having a high degree of success, only a few hospitalists perform them. This is because these are usually performed by radiologists or in the setting of trainee-run procedure teams. We sought to determine the impact of a non-trainee driven , hospitalist-run procedure service relative to time from consult to procedure. METHODS: The University of Alabama at Birmingham Hospital (UAB), Department of Hospital Medicine, trained 8 non-trainee hospitalist physicians (from existing staff) to implement the ultrasound-guided procedure service. This study examines consult to procedure completion time since the implementation of the procedure service (2014 to 2020). Univariate analyses are used to analyze pre-implementation (2012-2014), pilot (2014-2016), and post-implementation data (2016-2018 initial, and 2018-2020 sustained). RESULTS: Results suggest a 50% reduction in time from consult to procedure completion when compared with the period before implementation of the nontrainee hospitalist procedure service. CONCLUSIONS: A hospitalist procedure service, which does not include trainees, results in less time lag from consult to procedure completion time, which could increase patient satisfaction and improve throughput. As such, this study has wide generalizability to community hospitals and other nonacademic medical centers that may not have trainees.

Early Performance of the Patients Over Paperwork Initiative among Family Medicine Physicians.

OBJECTIVES: In 2019, the Centers for Medicare & Medicaid Services began implementing the Patients Over Paperwork (POP) initiative in response to clinicians reporting burdensome documentation regulations. To date, no study has evaluated how these policy changes have influenced documentation burden. METHODS: Our data came from the electronic health records of an academic health system. Using quantile regression models, we assessed the association between the implementation of POP and clinical documentation word count using data from family medicine physicians in an academic health system from January 2017 to May 2021 inclusive. Studied quantiles included the 10th, 25th, 50th, 75th, and 90th quantiles. We controlled for patient-level (race/ethnicity, primary language, age, comorbidity burden), visit-level (primary payer, level of clinical decision making involved, whether a visit was done through telemedicine, whether a visit was for a new patient), and physician-level (sex) characteristics. RESULTS: We found that the POP initiative was associated with lower word counts across all of the quantiles. In addition, we found lower word counts among notes for private payers and telemedicine visits. Conversely, higher word counts were observed in notes that were written by female physicians, notes for new patient visits, and notes involving patients with greater comorbidity burden. CONCLUSIONS: Our initial evaluation suggests that documentation burden, as measured by word count, has declined over time, particularly following implementation of the POP in 2019. Additional research is needed to see whether the same occurs when examining other medical specialties, clinician types, and longer evaluation periods.

Content Analysis for a Statewide Substance Use Disorder and Pain Management Curriculum for Health Professional Students (ALAHOPE).

OBJECTIVES: Alabama's health professions schools have many common goals when it comes to educating their students about substance use disorder (SUD) and pain, but a statewide consistent SUD and pain management curriculum does not exist in Alabama. The ALAbama Health professionals' Opioid and Pain management Education (ALAHOPE) project set out to create an interprofessional curriculum around SUD and pain management that all Alabama health professions schools can use to promote consistent evidence-based teaching and a patient-centered approach around these two topics. An adapted form of the Kern model of curriculum development was used to guide the project. The first dimension of this model is problem identification, which requires identifying the desired future state. One of many assessments performed to identify the desired future state was an analysis of six external curricula. The purpose of this assessment was to critically document and analyze existing SUD and pain management curricula to inform the ALAHOPE curriculum content. METHODS: The learning objectives and detailed content topics of each curriculum were documented and categorized into content topics. These broad topics were used as one piece of a cross-thematic analysis of several future state assessments that led to the development of broad curriculum goals for the ALAHOPE curriculum project. RESULTS: Common trends found in the analyzed curricula included learning objectives not being all-inclusive or not matching the actual curricula content, combining SUD and pain management content, and including the risks of treating pain with controlled substances in content solely created for pain management. CONCLUSIONS: These results can be used to help inform other SUD and pain management educational content.

Competency analysis and educational strategies to meet the demand for a learning health system workforce.

Learning Health Systems (LHS) require a workforce with specific knowledge and skills to identify and address healthcare quality issues, develop solutions to address those issues, and sustain and spread improvements within and outside the organization. Educational programs are tasked with designing learning opportunities that can meet these organizational needs. This manuscript explores different mechanisms for addressing challenges to creating educational programs to prepare individuals who can work in and lead LHS. Strategies and recommendations for educational programs to support the LHS include the creation of a new program, collaborating across existing programs, and producing a set of instructional materials.

Multiple Electronic Health Record-Based Measures of Social Determinants of Health to Predict Return to the Emergency Department Following Discharge.

Health care systems continue to struggle with preventing 30-day readmissions to their institutions. Social determinants of health (SDOH) are important predictors of repeat visits to the hospital. In many health systems, SDOH data are limited to those variables that are most relevant to care delivery or payment (eg, race, gender, insurance status). Despite calls for integrating a more robust set of measures (eg, measures of health behaviors and living conditions) into the electronic health record (EHR), these data often have missing values necessitating the use of imputation to build a comprehensive picture of patients who are likely to return to the health system. Using logistic regression analyses and imputation of missing data from 2017 to 2018, this study uses measures found in the EHR (eg, tobacco use, living situation, problems at home, education) to assess those SDOH that might predict a return to the emergency department within 30 days of discharge from a health system. In both imputed and raw data, the total number of recorded health conditions was the most important predictor and collectively SDOH variables made a relatively small contributions in determining the likelihood of a return to the hospital. Although SDOH variables might be important in the design of programs aimed at preventing readmissions, they may not be useful in readmission predictive models.