Pulmonary arterial hypertension (PAH) has a high morbidity rate and is fatal if left untreated. Increasing evidence supports early intervention, possibly with initial combination therapy. PAH-specific pharmaceuticals, however, are expensive and may have serious adverse effects, particularly when used in combination. The currently dynamic health care economy reinforces the need for a review of early intervention from both outcomes and economic perspectives. We aimed to review the clinical and economic impact of PAH therapy, particularly examining drug cost, hospitalization burden, and health care economics impact, and the effect of early intervention on clinical outcomes. We searched PubMed, Scopus, Ovid, and MEDLINE databases from 2005 to 2017 for studies comparing drug cost, clinical outcomes, and hospitalization burden associated with therapy for PAH. Emerging data indicate that early therapy is effective, but drug therapy is expensive, particularly with combination therapy. Efficacy studies also generally show benefit of combination therapy for patients in World Health Organization functional class II, with a consistent decrease in hospitalization. Pharmacoeconomic studies are limited but indicate that increased pharmacy costs are at least partially offset by decreased health care utilization, particularly inpatient care. Modeling also shows a cost benefit with combination therapy at 2 years. Nonetheless, more rigorously collected health care economic data should be incorporated into future drug efficacy trials to provide a clearer understanding of the impact and the associated cost benefit of early PAH therapy. Increasing evidence in support of early intervention and combination therapy for PAH is associated with rising medication costs that are largely offset by reduced hospitalization, on the basis of the currently available literature. Nonetheless, the studies performed to date have methodologic limitations that highlight the need for prospective studies using more robust economic modeling.

Background A detailed understanding of electronic health record (EHR) workflow patterns and information use is necessary to inform user-centered design of critical care information systems. While developing a longitudinal medical record visualization tool to facilitate electronic chart review (ECR) for medical intensive care unit (MICU) clinicians, we found inadequate research on clinician–EHR interactions. Objective We systematically studied EHR information use and workflow among MICU clinicians to determine the optimal selection and display of core data for a revised EHR interface. Methods We conducted a direct observational study of MICU clinicians performing ECR for unfamiliar patients during their routine daily practice at an academic medical center. Using a customized manual data collection instrument, we unobtrusively recorded the content and sequence of EHR data reviewed by clinicians. Results We performed 32 ECR observations among 24 clinicians. The median (interquartile range [IQR]) chart review duration was 9.2 (7.3–14.7) minutes, with the largest time spent reviewing clinical notes (44.4%), laboratories (13.3%), imaging studies (11.7%), and searching/scrolling (9.4%). Historical vital sign and intake/output data were never viewed in 31% and 59% of observations, respectively. Clinical notes and diagnostic reports were browsed ≥10 years in time for 60% of ECR sessions. Clinicians viewed a median of 7 clinical notes, 2.5 imaging studies, and 1.5 diagnostic studies, typically referencing a select few subtypes. Clinicians browsed a median (IQR) of 26.5 (22.5–37.25) data screens to complete their ECR, demonstrating high variability in navigation patterns and frequent back-and-forth switching between screens. Nonetheless, 47% of ECRs begin with review of clinical notes, which were also the most common navigation destination. Conclusion Electronic chart review centers around the viewing of clinical notes among MICU clinicians. Convoluted workflows and prolonged searching activities indicate room for system improvement. Using study findings, specific design recommendations to enhance usability for critical care information systems are provided.

Pulmonary arterial hypertension (PAH) is a devastating disease with significant morbidity and mortality. There are many psychosocial and financial implications of this disease; however, little is known how this affects the treatment of PAH patients. A questionnaire-based prospective cohort study was performed on 106 PAH patients from a Pulmonary Hypertension Center and the Pulmonary Hypertension Association national conference in 2018. The demographic, treatment, psychosocial, employment, financial impact on treatment data was obtained. The majority of patients had cardiopulmonary symptoms despite treatment. The symptoms affected their social and work lives, with about one in three applying for disability because of their PAH. The majority of PAH patients had insurance coverage, but still noted a significant financial burden of the disease, with nearly a half who needed financial assistance to pay for their PAH medications. Thirty (28.3%; 95% CI, 20.6–37.5%) patients mentioned they changed their medication regimen, with some skipping doses outright (28 [26.4%; 95% CI, 19–35.6%]) in order to save money. PAH continues to cause significant psychosocial and financial burden on patients despite advances in medications. This impact ranged from dissatisfaction with quality of life, to unemployment, to altering their medication regimen to save money.

Background Artificial Intelligent Virtual Assistants (AIVA) is a segment of artificial intelligence that is rapidly developing. However, its utilization to address patients' frequently asked questions remains unexplored. Methods We developed an AIVA to answer questions related to 10 frequent topics asked by plastic surgery patients in our institution. Between July 27, 2018, and August 10 of 2018, we recruited subjects with administrative positions at our health care institution to chat with the virtual assistant. They asked, with their own words, 1 question for each topic and filled out a satisfaction questionnaire. Postsurvey analysis of questions and answers allowed assessment of the virtual assistant's accuracy. Results Thirty participants completed the survey. The majority was female (70%), and the mean age was 27.76 years (SD, 8.68 [19–51] years). The overall accuracy of the plastic surgery AIVA was 92.3% (277/294 questions), and participants considered the answer correct in 83.3% of the time (250/294 answers). Most of the participants considered the AIVA easy to use, answered adequately, and could be helpful for patients. However, when asked if this technology could replace a human assistant, they stayed neutral.