Evaluating Factors Associated With Telehealth Appropriateness in Outpatient Rheumatoid Arthritis Encounters Using the Encounter Appropriateness Score for You (EASY).

OBJECTIVE: Telehealth has been proposed as a safe and effective alternative to in-person care for rheumatoid arthritis (RA). The purpose of this study was to evaluate factors associated with telehealth appropriateness in outpatient RA encounters. METHODS: A prospective cohort study (January 1, 2021, to August 31, 2021) was conducted using electronic health record data from outpatient RA encounters in a single academic rheumatology practice. Rheumatology providers rated the telehealth appropriateness of their own encounters using the Encounter Appropriateness Score for You (EASY) immediately following each encounter. Robust Poisson regression with generalized estimating equations modeling was used to evaluate the association of telehealth appropriateness with patient demographics, RA clinical characteristics, comorbid noninflammatory causes of joint pain, previous and current encounter characteristics, and provider characteristics. RESULTS: During the study period, 1823 outpatient encounters with 1177 unique patients with RA received an EASY score from 25 rheumatology providers. In the final multivariate model, factors associated with increased telehealth appropriateness included higher average provider preference for telehealth in prior encounters (relative risk [RR] 1.26, 95% CI 1.21-1.31), telehealth as the current encounter modality (RR 2.27, 95% CI 1.95-2.64), and increased patient age (RR 1.05, 95% CI 1.01-1.09). Factors associated with decreased telehealth appropriateness included moderate (RR 0.81, 95% CI 0.68-0.96) and high (RR 0.57, 95% CI 0.46-0.70) RA disease activity and if the previous encounters were conducted by telehealth (RR 0.83, 95% CI 0.73-0.95). CONCLUSION: In this study, telehealth appropriateness was most associated with provider preference, the current and previous encounter modality, and RA disease activity. Other factors like patient demographics, RA medications, and comorbid noninflammatory causes of joint pain were not associated with telehealth appropriateness.

Encounter Appropriateness Score for You Model: Development and Pilot Implementation of a Predictive Model to Identify Visits Appropriate for Telehealth in Rheumatology.

OBJECTIVE: We aimed to develop a decision-making tool to predict telehealth appropriateness for future rheumatology visits and expand telehealth care access. METHODS: The model was developed using the Encounter Appropriateness Score for You (EASY) and electronic health record data at a single academic rheumatology practice from January 1, 2021, to December 31, 2021. The EASY model is a logistic regression model that includes encounter characteristics, patient sociodemographic and clinical characteristics, and provider characteristics. The goal of pilot implementation was to determine if model recommendations align with provider preferences and influence telehealth scheduling. Four providers were presented with future encounters that the model identified as candidates for a change in encounter modality (true changes), along with an equal number of artificial (false) recommendations. Providers and patients could accept or reject proposed changes. RESULTS: The model performs well, with an area under the curve from 0.831 to 0.855 in 21,679 encounters across multiple validation sets. Covariates that contributed most to model performance were provider preference for and frequency of telehealth encounters. Other significant contributors included encounter characteristics (current scheduled encounter modality) and patient factors (age, Routine Assessment of Patient Index Data 3 scores, diagnoses, and medications). The pilot included 201 encounters. Providers were more likely to agree with true versus artificial recommendations (Cohen's κ = 0.45, P < 0.001), and the model increased the number of appropriate telehealth visits. CONCLUSION: The EASY model accurately identifies future visits that are appropriate for telehealth. This tool can support shared decision-making between patients and providers in deciding the most appropriate follow-up encounter modality.

Noninvasive Ventilation or CPAP for Postextubation Support in Small Infants.

BACKGROUND: Infants with a high risk of extubation failure are often treated with noninvasive ventilation (NIV) or CPAP, but data on the role of these support modalities following extubation are sparse. This report describes our experience using NIV or CPAP to support infants following extubation in our pediatric ICUs (PICUs). METHODS: We performed a retrospective study of children < 10 kg receiving postextubation NIV or CPAP in our PICUs. Data on demographics, medical history, type of support, vital signs, pulse oximetry, near-infrared spectroscopy (NIRS), gas exchange, support settings, and re-intubation were extracted from the electronic medical record. Support was classified as prophylactic if planned before extubation and rescue if initiated within 24 h of extubation. We compared successfully extubated and re-intubated subjects using chi-square test for categorical variables and Mann-Whitney test for continuous variables. RESULTS: We studied 51 subjects, median age 44 (interquartile range 0.5-242) d and weight 3.7 (3-4.9) kg. There were no demographic differences between groups, except those re-intubated were more likely to have had cardiac surgery prior to admission (0% vs 14%, P = .040). NIV was used in 31 (61%) and CPAP in 20 (39%) subjects. Prophylactic support was initiated in 25 subjects (49%), whereas rescue support was needed in 26 subjects (51%). Twenty-two subjects (43%) required re-intubation. Re-intubation rate was higher for rescue support (58% vs 28%, P = .032). Subjects with a pH < 7.35 (4.3% vs 42.0%, P = .003) and lower somatic NIRS (39 [24-56] vs 62 [46-72], P = .02) were more likely to be re-intubated. The inspiratory positive airway pressure, expiratory positive airway pressure, and FIO2 were higher in subjects who required re-intubation. CONCLUSIONS: NIV or CPAP use was associated with a re-intubation rate of 43% in a heterogeneous sample of high-risk infants. Acidosis, cardiac surgery, higher FIO2 , lower somatic NIRS, higher support settings, and application of rescue support were associated with the need for re-intubation.

Assessing clinical site readiness for electronic health record (EHR)-to-electronic data capture (EDC) automated data collection.

BACKGROUND: eSource software is used to automatically copy a patient's electronic health record data into a clinical study's electronic case report form. However, there is little evidence to assist sponsors in identifying the best sites for multi-center eSource studies. METHODS: We developed an eSource site readiness survey. The survey was administered to principal investigators, clinical research coordinators, and chief research information officers at Pediatric Trial Network sites. RESULTS: A total of 61 respondents were included in this study (clinical research coordinator, 22; principal investigator, 20; and chief research information officer, 19). Clinical research coordinators and principal investigators ranked medication administration, medication orders, laboratory, medical history, and vital signs data as having the highest priority for automation. While most organizations used some electronic health record research functions (clinical research coordinator, 77%; principal investigator, 75%; and chief research information officer, 89%), only 21% of sites were using Fast Healthcare Interoperability Resources standards to exchange patient data with other institutions. Respondents generally gave lower readiness for change ratings to organizations that did not have a separate research information technology group and where researchers practiced in hospitals not operated by their medical schools. CONCLUSIONS: Site readiness to participate in eSource studies is not merely a technical problem. While technical capabilities are important, organizational priorities, structure, and the site's support of clinical research functions are equally important considerations.

Timing of Treatment Outcomes and Risk Factors for Failure of BPAP in Patients Hospitalized for COPD Exacerbation.

BACKGROUND: Patients hospitalized for COPD exacerbation have an increased risk of mortality, particularly among those who fail bi-level positive airway pressure (BPAP) for hypercapnic respiratory failure subsequently requiring invasive mechanical ventilation. Therefore, we sought to investigate the treatment course of BPAP and factors associated with BPAP treatment failure. METHODS: We performed a retrospective cohort study using real-world evidence to investigate subjects with COPD who were treated with BPAP during a hospitalization for COPD exacerbation. Treatment outcomes were defined within 7 d from BPAP initiation as either failure, persistent, or success. Failure was defined as death or progression to invasive ventilation. Persistent was defined as receiving BPAP during hospital day 7. Success was defined as liberation from BPAP prior to hospital day 7 and not meeting criteria for failure. Unadjusted multinomial logistic regression models were used to examine the association between BPAP treatment outcomes and 17 recipient characteristics. RESULTS: Among the 427 clinical encounters, 78% were successful, 10% were persistent, and 12% experienced failure. The median time to failure and success was 8 h and 16 h, respectively. Increasing age, body mass index (BMI), bicarbonate level, and creatinine level were significantly associated with either BPAP treatment failure, persistent treatment, or both. CONCLUSIONS: The first 8 h following initiation of BPAP is a critical time period where patients are at high risk for life-threatening decompensation. Careful consideration should be given to increasing age, BMI, bicarbonate level, and creatinine level as these factors were associated with BPAP treatment failure or persistent treatment.

Telehealth Made EASY: Understanding Provider Perceptions of Telehealth Appropriateness in Outpatient Rheumatology Encounters.

OBJECTIVE: The purpose of this study was to evaluate a novel scoring system, the Encounter Appropriateness Score for You (EASY), to assess provider perceptions of telehealth appropriateness in rheumatology encounters. METHODS: The EASY scoring system prompts providers to rate their own encounters as follows: in-person or telehealth acceptable, EASY = 1; in-person preferred, EASY = 2; or telehealth preferred, EASY = 3. Assessment of the EASY scoring system occurred at a single academic institution from January 1, 2021, to August 31, 2021. Data were collected in three rounds: 1) initial survey (31 providers) assessing EASY responsiveness to five hypothetical scenarios, 2) follow-up survey (34 providers) exploring EASY responsiveness to 11 scenario modifications, and 3) assessment of EASYs documented in clinic care. RESULTS: The initial and follow-up surveys demonstrated responsiveness of EASYs to different clinical and nonclinical factors. For instance, less than 20% of providers accepted telehealth when starting a biologic for active rheumatoid arthritis, although more than 35% accepted telehealth in the same scenario if the patient lived far away or was well known to the provider. Regarding EASY documentation, 27 providers provided EASYs for 12,381 encounters. According to these scores, telehealth was acceptable or preferred for 29.7% of all encounters, including 21.4% of in-person encounters. Conversely, 24.4% of telehealth encounters were scored as in-person preferred. CONCLUSION: EASY is simple, understandable, and responsive to changes in the clinical scenario. We have successfully accumulated 12,381 EASYs that can be studied in future work to better understand telehealth utility and optimize telehealth triage.

Evaluating Site-Level Implementations of the HL7 FHIR Standard to Support eSource Data Exchange in Clinical Research.

Direct extraction and use of electronic health record (EHR) data is a long-term and multifaceted endeavor that includes design, development, implementation and evaluation of methods and tools for semi-automating tasks in the research data collection process, including, but not limited to, medical record abstraction (MRA). A systematic mapping of study data elements was used to measure the coverage of the Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) standard for a federally sponsored, pragmatic cardiovascular randomized controlled trial (RCT) targeting adults. We evaluated site-level implementations of the HL7® FHIR® standard to investigate study- and site-level differences that could affect coverage and offer insight into the feasibility of a FHIR-based eSource solution for multicenter clinical research.

Impact of the COVID-19 pandemic on patterns of outpatient cardiovascular care.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic brought about abrupt changes in the way health care is delivered, and the impact of transitioning outpatient clinic visits to telehealth visits on processes of care and outcomes is unclear. METHODS: We evaluated ordering patterns during cardiovascular telehealth clinic visits in the Duke University Health System between March 15 and June 30, 2020 and 30-day outcomes compared with in-person visits in the same time frame in 2020 and in 2019. RESULTS: Within the Duke University Health System, there was a 33.1% decrease in the number of outpatient cardiovascular visits conducted in the first 15 weeks of the COVID-19 pandemic, compared with the same time period in 2019. As a proportion of total visits initially booked, 53% of visits were cancelled in 2020 compared to 35% in 2019. However, patients with cancelled visits had similar demographics and comorbidities in 2019 and 2020. Telehealth visits comprised 9.3% of total visits initially booked in 2020, with younger and healthier patients utilizing telehealth compared with those utilizing in-person visits. Compared with in-person visits in 2020, telehealth visits were associated with fewer new (31.6% for telehealth vs 44.6% for in person) or refill (12.9% vs 15.6%, respectively) medication prescriptions, electrocardiograms (4.3% vs 31.4%), laboratory orders (5.9% vs 21.8%), echocardiograms (7.3% vs 98%), and stress tests (4.4% vs 6.6%). When adjusted for age, race, and insurance status, those who had a telehealth visit or cancelled their visit were less likely to have an emergency department or hospital encounter within 30 days compared with those who had in-person visits (adjusted rate ratios (aRR) 0.76 [95% 0.65, 0.89] and aRR 0.71 [95% 0.65, 0.78], respectively). CONCLUSIONS: In response to the perceived risks of routine medical care affected by the COVID-19 pandemic, different phenotypes of patients chose different types of outpatient cardiology care. A better understanding of these differences could help define necessary and appropriate mode of care for cardiology patients.

Unanticipated Respiratory Compromise and Unplanned Intubations on General Medical and Surgical Floors.

BACKGROUND: Unanticipated respiratory compromise that lead to unplanned intubations is a known phenomenon in hospitalized patients. Most events occur in patients at high risk in well-monitored units; less is known about the incidence, risk factors, and trajectory of patients thought at low risk on lightly monitored general care wards. The aims of our study were to quantify demographic and clinical characteristics associated with unplanned intubations on general care floors and to analyze the medications administered, monitoring strategies, and vital-sign trajectories before the event. METHODS: We performed a multicenter retrospective cohort study of hospitalized subjects on the general floor who had unanticipated, unplanned intubations on general care floors from August 2014 to February 2018. RESULTS: We identified 448 unplanned intubations. The incidence rate was 0.420 per 1,000 bed-days (95% CI 0.374-0.470) in the academic hospital and was 0.430 (95% CI 0.352-0.520) and 0.394 per 1,000 bed-days (95% CI 0.301-0.506) at our community hospitals. Extrapolating these rates to total hospital admissions in the United States, we estimate 64,000 events annually. The mortality rate was 49.1%. Within 12 h preceding the event, 35.3% of the subjects received opiates. All received vital-sign assessments. Most were monitored with pulse oximetry. In contrast, 2.5% were on cardiac telemetry, and only 4 subjects used capnography; 53.7% showed significant vital-sign changes in the 24 h before the event. However, 46.3% had no significant change in any vital signs. CONCLUSIONS: Our study showed unanticipated respiratory compromise that required an unplanned intubation of subjects on the general care floor, although not common, carried a high mortality. Besides pulse oximetry and routine vital-sign assessments, very little monitoring was in use. A significant portion of the subjects had no vital-sign abnormalities leading up to the event. Further research is needed to determine the phenotype of the different etiologies of unexpected acute respiratory failure to identify better risk stratification and monitoring strategies.

Open-source, Rapid Reporting of Dementia Evaluations.

The National Institutes of Health Alzheimer's Disease Center consortium requires member institutions to build and maintain a longitudinally characterized cohort with a uniform standard data set. Increasingly, centers are employing electronic data capture to acquire data at annual evaluations. In this paper, the University of Kansas Alzheimer's Disease Center reports on an open-source system of electronic data collection and reporting to improve efficiency. This Center capitalizes on the speed, flexibility and accessibility of the system to enhance the evaluation process while rapidly transferring data to the National Alzheimer's Coordinating Center. This framework holds promise for other consortia that regularly use and manage large, standardized datasets.

Simulating retrieval from a highly clustered network: implications for spoken word recognition.

Network science describes how entities in complex systems interact, and argues that the structure of the network influences processing. Clustering coefficient, C - one measure of network structure - refers to the extent to which neighbors of a node are also neighbors of each other. Previous simulations suggest that networks with low C dissipate information (or disease) to a large portion of the network, whereas in networks with high C information (or disease) tends to be constrained to a smaller portion of the network (Newman, 2003). In the present simulation we examined how C influenced the spread of activation to a specific node, simulating retrieval of a specific lexical item in a phonological network. The results of the network simulation showed that words with lower C had higher activation values (indicating faster or more accurate retrieval from the lexicon) than words with higher C. These results suggest that a simple mechanism for lexical retrieval can account for the observations made in Chan and Vitevitch (2009), and have implications for diffusion dynamics in other fields.

Oncogenes and pathway identification using filter-based approaches between various carcinoma types in lung.

Lung cancer accounts for the most cancer-related deaths. The identification of cancer-associated genes and the related pathways are essential to prevent many types of cancer. In this paper, a more systematic approach is considered. First, we did pathway analysis using Hyper Geometric Distribution (HGD) and significantly overrepresented sets of reactions were identified. Second, feature-selection-based Particle Swarm Optimisation (PSO), Information Gain (IG) and the Biomarker Identifier (BMI) for the identification of different types of lung cancer were used. We also evaluated PSO and developed a new method to determine the BMI thresholds to prioritize genes. We were able to identify sets of key genes that can be found in several pathways. Experimental results show that our method simplifies features effectively and obtains higher classification accuracy than the other methods from the literature.