Real-world Care Settings Research Articles

Critical care pharmacist perspectives on optimal practice models and prioritization of professional activities: A cross-sectional survey

Abstract Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Critical care pharmacists (CCPs) are essential members of the multidisciplinary critical care team. Professional activities of the CCP are outlined in a 2020 position paper on critical care pharmacy services. This study looks to characterize CCP perspectives for priorities in optimizing pharmacy practice models and professional activities. Methods This was a cross-sectional survey conducted from July 24 to September 20, 2023. A 41-question survey instrument was developed to assess 7 domains: demographics, CCP resource utilization, patient care, quality improvement, research and scholarship, training and education, and professional development. This voluntary survey was sent to members of the American College of Clinical Pharmacy’s Critical Care Practice and Research Network. The survey was open for a total of 6 weeks. Results There was a response rate of 20.7% (332 of 1,605 invitees), with 66.6% of respondents (n = 221) completing at least 90% of the survey questions. Most respondents were clinical specialists (58.2%) and/or practiced at an academic medical center (58.5%). Direct patient care, quality improvement and medication safety, and teaching and precepting were identified as the CCP activities of highest importance to CCPs. The CCP-to-patient ratios considered ideal were 1:11-15 (selected by 49.8% of respondents) and 1:16-20 (33.9% of respondents). The ideal percentage of time dedicated to direct patient care activities, as identified by survey respondents, was 50% (interquartile range, 40-50). Conclusion These findings highlight the professional activities viewed as having the highest priority by CCPs. Future research is needed to define optimal CCP practice models for the delivery of patient care in real-world settings.

Identifying Symptoms Prior to Pancreatic Ductal Adenocarcinoma Diagnosis in Real-World Care Settings: Natural Language Processing Approach.

Pancreatic cancer is the third leading cause of cancer deaths in the United States. Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, accounting for up to 90% of all cases. Patient-reported symptoms are often the triggers of cancer diagnosis and therefore, understanding the PDAC-associated symptoms and the timing of symptom onset could facilitate early detection of PDAC. This paper aims to develop a natural language processing (NLP) algorithm to capture symptoms associated with PDAC from clinical notes within a large integrated health care system. We used unstructured data within 2 years prior to PDAC diagnosis between 2010 and 2019 and among matched patients without PDAC to identify 17 PDAC-related symptoms. Related terms and phrases were first compiled from publicly available resources and then recursively reviewed and enriched with input from clinicians and chart review. A computerized NLP algorithm was iteratively developed and fine-trained via multiple rounds of chart review followed by adjudication. Finally, the developed algorithm was applied to the validation data set to assess performance and to the study implementation notes. A total of 408,147 and 709,789 notes were retrieved from 2611 patients with PDAC and 10,085 matched patients without PDAC, respectively. In descending order, the symptom distribution of the study implementation notes ranged from 4.98% for abdominal or epigastric pain to 0.05% for upper extremity deep vein thrombosis in the PDAC group, and from 1.75% for back pain to 0.01% for pale stool in the non-PDAC group. Validation of the NLP algorithm against adjudicated chart review results of 1000 notes showed that precision ranged from 98.9% (jaundice) to 84% (upper extremity deep vein thrombosis), recall ranged from 98.1% (weight loss) to 82.8% (epigastric bloating), and F1-scores ranged from 0.97 (jaundice) to 0.86 (depression). The developed and validated NLP algorithm could be used for the early detection of PDAC.

Impact of Electronic Patient-Reported Outcomes on Unplanned Consultations and Hospitalizations in Patients With Cancer Undergoing Systemic Therapy: Results of a Patient-Reported Outcome Study Compared With Matched Retrospective Data.

The evaluation of electronic patient-reported outcomes (ePROs) is increasingly being used in clinical studies of patients with cancer and enables structured and standardized data collection in patients' everyday lives. So far, few studies or analyses have focused on the medical benefit of ePROs for patients. The current exploratory analysis aimed to obtain an initial indication of whether the use of the Consilium Care app (recently renamed medidux; mobile Health AG) for structured and regular self-assessment of side effects by ePROs had a recognizable effect on incidences of unplanned consultations and hospitalizations of patients with cancer compared to a control group in a real-world care setting without app use. To analyze this, the incidences of unplanned consultations and hospitalizations of patients with cancer using the Consilium Care app that were recorded by the treating physicians as part of the patient reported outcome (PRO) study were compared retrospectively to corresponding data from a comparable population of patients with cancer collected at 2 Swiss oncology centers during standard-of-care treatment. Patients with cancer in the PRO study (178 included in this analysis) receiving systemic therapy in a neoadjuvant or noncurative setting performed a self-assessment of side effects via the Consilium Care app over an observational period of 90 days. In this period, unplanned (emergency) consultations and hospitalizations were documented by the participating physicians. The incidence of these events was compared with retrospective data obtained from 2 Swiss tumor centers for a matched cohort of patients with cancer. Both patient groups were comparable in terms of age and gender ratio, as well as the distribution of cancer entities and Joint Committee on Cancer stages. In total, 139 patients from each group were treated with chemotherapy and 39 with other therapies. Looking at all patients, no significant difference in events per patient was found between the Consilium group and the control group (odds ratio 0.742, 90% CI 0.455-1.206). However, a multivariate regression model revealed that the interaction term between the Consilium group and the factor "chemotherapy" was significant at the 5% level (P=.048). This motivated a corresponding subgroup analysis that indicated a relevant reduction of the risk for the intervention group in the subgroup of patients who underwent chemotherapy. The corresponding odds ratio of 0.53, 90% CI 0.288-0.957 is equivalent to a halving of the risk for patients in the Consilium group and suggests a clinically relevant effect that is significant at a 2-sided 10% level (P=.08, Fisher exact test). A comparison of unplanned consultations and hospitalizations from the PRO study with retrospective data from a comparable cohort of patients with cancer suggests a positive effect of regular app-based ePROs for patients receiving chemotherapy. These data are to be verified in the ongoing randomized PRO2 study (registered on ClinicalTrials.gov; NCT05425550). ClinicalTrials.gov NCT03578731; https://www.clinicaltrials.gov/ct2/show/NCT03578731. RR2-10.2196/29271.

Inter-observer agreement among specialists in the diagnosis of oral potentially malignant disorders and oral cancer using store-and-forward technology.

Oral cancer is a leading cause of morbidity and mortality. Screening and mobile Health (mHealth)-based approach facilitates early detection remotely in a resource-limited settings. Recent advances in eHealth technology have enabled remote monitoring and triage to detect oral cancer in its early stages. Although studies have been conducted to evaluate the diagnostic efficacy of remote specialists, to our knowledge, no studies have been conducted to evaluate the consistency of remote specialists. The aim of this study was to evaluate interobserver agreement between specialists through telemedicine systems in real-world settings using store-and-forward technology. The two remote specialists independently diagnosed clinical images (n=822) from image archives. The onsite specialist diagnosed the same participants using conventional visual examination, which was tabulated. The diagnostic accuracy of two remote specialists was compared with that of the onsite specialist. Images that were confirmed histopathologically were compared with the onsite diagnoses and the two remote specialists. There was moderate agreement (k= 0.682) between two remote specialists and (k= 0.629) between the onsite specialist and two remote specialists in the diagnosis of oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, respectively, and those of remote specialist 2 were 95.8% and 60%, respectively, each compared with histopathology. The diagnostic accuracy of the two remote specialists was optimal, suggesting that "store and forward" technology and telehealth can be an effective tool for triage and monitoring of patients. Telemedicine is a good tool for triage and enables faster patient care in real-world settings.

Adaptive Nutrition Intervention Stabilizes Serum Phosphorus Levels in Hemodialysis Patients: A Multicenter Decentralized Clinical Trial Using Real-World Data

This study aims to evaluate the effect of an adaptive nutritional and educational intervention for patients on hemodialysis (HD) in a routine care setting, using real-world data from electronic health records. Decentralized clinical trial of seven HD facilities recruited patients who have been on HD for over 3months (N=153) for an 8-week adaptive intervention protocol. Patients were divided into four groups: (1) control (2) education intervention (3) meal intervention (4) education and meal interventions. Educational contents were digitally delivered via mobile phones and premade meals tailored on laboratory findings were home-delivered. Changes in serum electrolytes and malnutrition inflammation score (MIS) were analyzed. Meal intervention statistically significantly stabilized serum phosphorus level (β=-0.81mg/dL, 95% confidence interval=[-1.40, -0.22]) at week 8, with increased likelihood of being within target serum value range (odds ratio=1.21, 95% confidence interval=[1.04, 1.40]). Meal group showed better nutritional status (MIS=3.65) than the education group (MIS=5.10) at week 8 (adjusted p<.05). No significant changes were observed in serum potassium level, depression, and self-efficacy. It was demonstrated that an adaptive meal intervention in a real-world care setting may benefit serum phosphorus control and nutritional status of patients on HD, without negative effect on depression levels or self-efficacy. More work is needed to develop an effective educational intervention.

RWD84 A Comparison of Oral Aripiprazole with an Ingestible Sensor with Oral Atypical Antipsychotic Treatment and Impact on Psychiatric Hospitalizations in Adults with Schizophrenia in a Real-World Care Setting

To compare the risk of psychiatric hospitalization among adults with schizophrenia using aripiprazole with an ingestible sensor (AS), to those on oral atypical antipsychotic (OAA) treatment in the real world.

Rates and Correlates of Uptake of Continuous Glucose Monitors Among Adults with Type 2 Diabetes in Primary Care and Endocrinology Settings.

Clinical trials indicate continuous glucose monitor (CGM) use may benefit adults with type 2 diabetes, but CGM rates and correlates in real-world care settings are unknown. We sought to ascertain prevalence and correlates of CGM use and to examine rates of new CGM prescriptions across clinic types and medication regimens. Retrospective cohort using electronic health records in a large academic medical center in the Southeastern US. Adults with type 2 diabetes and a primary care or endocrinology visit during 2021. Age, gender, race, ethnicity, insurance, clinic type, insulin regimen, hemoglobin A1c values, CGM prescriptions, and prescribing clinic type. Among 30,585 adults with type 2 diabetes, 13% had used a CGM. CGM users were younger and more had private health insurance (p < .05) as compared to non-users; 72% of CGM users had an intensive insulin regimen, but 12% were not taking insulin. CGM users had higher hemoglobin A1c values (both most recent and most proximal to the first CGM prescription) than non-users. CGM users were more likely to receive endocrinology care than non-users, but 23% had only primary care visits in 2021. For each month in 2021, a mean of 90.5 (SD 12.5) people started using CGM. From 2020 to 2021, monthly rates of CGM prescriptions to new users grew 36% overall, but 125% in primary care. Most starting CGM in endocrinology had an intensive insulin regimen (82% vs. 49% starting in primary care), whereas 28% starting CGM in primary care were not using insulin (vs. 5% in endocrinology). CGM uptake for type 2 diabetes is increasing rapidly, with most growth in primary care. These trends present opportunities for healthcare system adaptations to support CGM use and related workflows in primary care to support growth in uptake.

The effects of ketamine on symptoms of depression and anxiety in real-world care settings: A retrospective controlled analysis

IntroductionKetamine intravenous therapy (KIT) appears effective for treating depression in controlled trials testing a short series of infusions. A rapidly proliferating number of clinics offer KIT for depression and anxiety, using protocols without a strong evidence basis. Controlled comparison of mood and anxiety from real-world KIT clinics, and the stability of outcomes, is lacking. MethodsWe performed a retrospective controlled analysis on patients treated with KIT in ten community clinics across the US, between 08/2017‐03/2020. Depression and anxiety symptoms were evaluated using the Quick Inventory of Depressive Symptomatology-Self Report 16-item (QIDS) and the Generalized Anxiety Disorder 7-item (GAD-7) scales, respectively. Comparison data sets from patients who did not undergo KIT were obtained from previously published real-world studies. ResultsOf 2758 patients treated, 714 and 836 met criteria for analysis of KIT induction and maintenance outcomes, respectively. Patients exhibited significant and concordant reduction in both anxiety and depression symptoms after induction (Cohen's d = -1.17 and d = -1.56, respectively). Compared to two external datasets of KIT-naive depressed patients or patients starting standard antidepressant therapy, KIT patients experienced a significantly greater reduction in depression symptoms at eight weeks (Cohen's d = -1.03 and d = -0.62 respectively). Furthermore, we identified a subpopulation of late-responders. During maintenance, up to a year post-induction, increases in symptoms were minimal. LimitationsDue to the retrospective nature of the analyses, interpreting this dataset is limited by incomplete patient information and sample attrition. ConclusionsKIT treatment elicited robust symptomatic relief that remained stable up to one year of follow-up.

Longitudinal evaluation on negative symptoms in young people at Ultra-High Risk (UHR) of psychosis: results from a 2-year follow-up study in a real-world care setting.

Negative Symptoms (NS) severely affect real-world functioning also in young people at UHR for developing psychosis. However, longitudinal research on beneficial effects of specialized treatments for NS in UHR people is still relatively scarce and inconclusive, especially in real-world care settings. The aims of the present research were: (1) to evaluate the longitudinal stability of NS levels in young UHR subjects treated within a specialized "Early Intervention in Psychosis" (EIP) program across a 2-year follow-up period, and (2) to investigate any relevant association of NS changes with the specific treatment components offered within the EIP program. One hundred UHR individuals (aged 12-25years) completed the Positive And Negative Syndrome Scale (PANSS). A multiple linear regression analysis was conducted to examine significant associations between longitudinal changes in NS severity levels and the EIP treatment components. Across the follow-up, a significant decrease in NS clinical severity was observed. This reduction was associated with the intensity of individual psychotherapy sessions provided in the first year of treatment, a shorter duration of untreated illness at entry and the 2-year longitudinal decrease in positive symptom levels. In conclusion, NS are relevant in UHR people, but decrease over time together with the delivery of specialized EIP interventions. Specifically, our results showed that individual psychotherapy may reduce the clinical severity of NS at least during the first year of treatment.

Minority Patients in the US Receiving Chimeric Antigen Receptor (CAR) T-Cell Therapy: A SEER-Based Simulation on Representation and Impact of Proximity to Authorized Treatment Center (ATC)

Background Patients (pts) of minority race or ethnicity are often underrepresented in oncology clinical trials (Awidi et al. JCO Oncol Pract. 2021) despite differences in the incidence of most cancer types, including B-cell malignancies, across races and ethnicities (Teras et al. CA Cancer J Clin 2016; Feng et al. Am J Epidemiol 2021). Both clinical trials and real-world (RW) studies have demonstrated significant clinical benefits of CAR T-cell therapy for pts with B-cell malignancies. To understand potential underrepresentation of minority pts, we conducted a series of simulations to estimate proportions of minority pts potentially eligible for either CAR T-cell trials or receiving standard-of-care CAR T-cell therapy in RW settings. We also assessed whether proximity to a CAR T-cell ATC is a barrier for treatment. Methods Race/ethnicity demographics (mutually exclusive groups of non-Hispanic White [NHW], non-Hispanic Black [NHB], non-Hispanic Other [NHO], and Hispanic [any race]) for US pts ≥ 20 years old with large B-cell lymphoma (LBCL), follicular lymphoma (FL), mantle cell lymphoma (MCL), and B-cell precursor acute lymphoblastic leukemia (B-ALL) were estimated for both trial and RW settings based on 5-year limited-duration prevalence prior to January 1, 2019 from the SEER Research Plus Data (17 registries, November 2021 submission), and US County Population Data (1969-2020). Estimated proportions and 95% confidence intervals (CIs) were simulated based on 3000 random samples per cancer type. Sample sizes for trial settings corresponded to US enrollment in clinical trials of axicabtagene ciloleucel (axi-cel) and brexucabtagene autoleucel (brexu-cel), while those for RW settings were based on accrual targets for post-authorization safety studies (PASS) using the CIBMTR registry (Table). Sampling was performed for counties within 50 miles [mi] of trial-associated ATCs or commercial ATCs for trial or RW settings, and for the entire US. Results As of January 1, 2019, approximately 177 million of 246 million people (72%) ≥ 20 years old lived within 50 mi of a commercial ATC in the US, of which 13% were NHB and 17% were Hispanic (Table). In clinical trial settings, the estimated proportion of NHB pts ≤ 50 mi of an ATC ranged from 5% in FL to 7% in LBCL (Table). The estimates were numerically higher, but not statistically significant, compared with actual enrollment in trials, except in B-ALL (7% [3%-12%] estimated vs 3% enrolled). Compared with actual trial enrollment, the estimated proportions (95% CI) of Hispanic pts were statistically higher across all indications (LBCL, 14% [10%-18%] estimated vs 7% enrolled; FL, 15% [9%-21%] estimated vs 5% enrolled; and B-ALL, 39% [30%-48%] estimated vs 29% enrolled) except in MCL (12% [4%-19%] estimated vs 15% enrolled). In RW settings, the estimated proportions of NHB pts were comparable to those in trial settings across all indications, whereas estimates of Hispanic pts were numerically lower (Table). The reported proportion of NHB pts with LBCL in PASS (5%) was statistically lower than the estimated proportion (8% [95% CI 7%-9%]). To further assess the impact of proximity to ATCs, the estimated proportions were compared between regions ≤ 50 mi of an ATC and the entire US. Proportions of NHB pts ≤ 50 mi of an ATC across all disease types were comparable with the estimates of the entire US, regardless of trial or RW settings (Table). While for Hispanic pts, the estimated proportions ≤ 50 mi of an ATC were numerically higher compared with the estimates of the entire US; but the estimates were comparable in RW settings. Conclusions This is the first simulation study to estimate the proportions of minority pts by considering disease prevalence and proximity to CAR T-cell ATCs. The possibility of patient underrepresentation is raised as the actual enrolled proportions of minority pts with certain B-cell malignancies were numerically lower than simulation-based estimates, even though most findings were not statistically significant. Based on the simulation, the estimated proportions of minority pts were comparable or even higher in regions close to ATCs indicating that proximity to ATCs may not be a key barrier for trial participation and accessibility of care. Further investigation into other factors influencing diversity in trials and accessibility of state-of-the-art cancer care in RW settings is warranted. MG and Z-HH contributed equally. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Artificial intelligence applications used in the clinical response to COVID-19: A scoping review.

Research into using artificial intelligence (AI) in health care is growing and several observers predicted that AI would play a key role in the clinical response to the COVID-19. Many AI models have been proposed though previous reviews have identified only a few applications used in clinical practice. In this study, we aim to (1) identify and characterize AI applications used in the clinical response to COVID-19; (2) examine the timing, location, and extent of their use; (3) examine how they relate to pre-pandemic applications and the U.S. regulatory approval process; and (4) characterize the evidence that is available to support their use. We searched academic and grey literature sources to identify 66 AI applications that performed a wide range of diagnostic, prognostic, and triage functions in the clinical response to COVID-19. Many were deployed early in the pandemic and most were used in the U.S., other high-income countries, or China. While some applications were used to care for hundreds of thousands of patients, others were used to an unknown or limited extent. We found studies supporting the use of 39 applications, though few of these were independent evaluations and we found no clinical trials evaluating any application's impact on patient health. Due to limited evidence, it is impossible to determine the extent to which the clinical use of AI in the pandemic response has benefited patients overall. Further research is needed, particularly independent evaluations on AI application performance and health impacts in real-world care settings.

Technologies for Interoperable Internet of Medical Things Platforms to Manage Medical Emergencies in Home and Prehospital Care: Protocol for a Scoping Review.

BackgroundPopulation growth and aging have highlighted the need for more effective home and prehospital care. Interconnected medical devices and applications, which comprise an infrastructure referred to as the Internet of Medical Things (IoMT), have enabled remote patient monitoring and can be important tools to cope with these demographic changes. However, developing IoMT platforms requires profound knowledge of clinical needs and challenges related to interoperability and how these can be managed with suitable technologies.ObjectiveThe purpose of this scoping review is to summarize the best practices and technologies to overcome interoperability concerns in IoMT platform development for medical emergencies in home and prehospital care.MethodsThis scoping review will be conducted in accordance with Arksey and O’Malley’s 5-stage framework and adhere to the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols) guidelines. Only peer-reviewed articles published in English will be considered. The databases/web search engines that will be used are IEEE Xplore, PubMed, Scopus, Google Scholar, National Center for Biotechnology Information, SAGE Journals, and ScienceDirect. The search process for relevant literature will be divided into 4 different steps. This will ensure that a suitable approach is followed in terms of search terms, limitations, and eligibility criteria. Relevant articles that meet the inclusion criteria will be screened in 2 stages: abstract and title screening and full-text screening. To reduce selection bias, the screening process will be performed by 2 reviewers.ResultsThe results of the preliminary search indicate that there is sufficient literature to form a good foundation for the scoping review. The search was performed in April 2022, and a total of 4579 articles were found. The main clinical focus is the prevention and management of falls, but other medical emergencies, such as heart disease and stroke, are also considered. Preliminary results show that little attention has been given to real-time IoMT platforms that can be deployed in real-world care settings. The final results are expected to be presented in a scoping review in 2023 and will be disseminated through scientific conference presentations, oral presentations, and publication in a peer-reviewed journal.ConclusionsThis scoping review will provide insights and recommendations regarding how interoperable real-time IoMT platforms can be developed to handle medical emergencies in home and prehospital care. The findings of this research could be used by researchers, clinicians, and implementation teams to facilitate future development and interdisciplinary discussions.International Registered Report Identifier (IRRID)DERR1-10.2196/40243

Depressed Mood in First Episode Schizophrenia: Findings From a 1-Year Follow-Up in an Italian Real-World Care Setting

Introduction: Depression in schizophrenia is associated with poor outcomes and suicide risk. However, it is overlooked in both research and clinical practice, especially in First Episode Schizophrenia (FES). Methods: In this letter to the editor, we reported relevant findings on relevant comorbid depressed mood in an Italian sample of FES patients during a 1-year follow-up period within an “Early Intervention in Psychosis” (EIP) program. The Positive And Negative Syndrome Scale (PANSS) was completed by 159 participant. Results: At baseline, 53 (33.3%) participants showed a relevant depressed mood (as measured with a PANSS “Depression” G6 item subscore of ≥ 5). At entry, a relevant depressed mood was associated with a greater percentage of females and a higher PANSS “Positive Symptoms” score. Across the follow-up, FES individuals improved their depression severity levels. This reduction was significantly related to improvments in positive symptoms levels. Conclusions: Depression is relatively common in FES, already at the recruitment in EIP services. However, its severity decreases overtime within specialized EIP programs.

Real world effectiveness of digital mental health services during the COVID-19 pandemic.

BackgroundThe COVID-19 pandemic created an unprecedented need for mental health services that can be remotely delivered. Digital mental health services that offer personalized care recommendations hold promise to efficiently expand service, but evidence of the effectiveness of digitally delivered mental health care in real-world settings remains limited.MethodsA retrospective cohort of adults (N = 1,852) receiving care through a digital mental health platform with elevated depressive symptoms during the COVID-19 pandemic was analyzed to estimate changes in subjective well-being and clinical improvement in depressive symptoms (using the World Health Organization-Five [WHO-5] Well-Being Index), as well as compare the relative effectiveness and cost of different care utilization patterns.ResultsThe average improvement in WHO-5 score was 10.1 points (CI: 9.3–10.9, p<0.001) at follow-up, which constituted a medium effect size (d = 0.73). The odds of clinical improvement in depressive symptoms were significantly greater among those who utilized telecoaching (aOR = 2.45, 95%CI: 1.91–3.15, p < .001), teletherapy (aOR = 2.01, 95%CI: 1.57–2.57, p < .001), and both services (aOR = 2.28, 95%CI: 1.67–3.11, p < .001) compared to those who only utilized assessments, adjusting for baseline WHO-5 score, age, sex, and number of days between baseline and follow-up assessments. The average estimated cost of care for telecoaching was $124 per individual, which was significantly less than teletherapy ($413) or both services ($559).ConclusionDigitally delivered care with a therapist and/or coach was effective in improving subjective well-being and clinical improvement in depressive symptoms. Although clinical outcomes were similar across utilization patterns, the cost of care was lowest among those utilizing telecoaching.

A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems.

Health care is shifting toward become proactive according to the concept of P5 medicine–a predictive, personalized, preventive, participatory and precision discipline. This patient-centered care heavily leverages the latest technologies of artificial intelligence (AI) and robotics that support diagnosis, decision making and treatment. In this paper, we present the role of AI and robotic systems in this evolution, including example use cases. We categorize systems along multiple dimensions such as the type of system, the degree of autonomy, the care setting where the systems are applied, and the application area. These technologies have already achieved notable results in the prediction of sepsis or cardiovascular risk, the monitoring of vital parameters in intensive care units, or in the form of home care robots. Still, while much research is conducted around AI and robotics in health care, adoption in real world care settings is still limited. To remove adoption barriers, we need to address issues such as safety, security, privacy and ethical principles; detect and eliminate bias that could result in harmful or unfair clinical decisions; and build trust in and societal acceptance of AI.

A retrospective analysis of ketamine intravenous therapy for depression in real-world care settings

BackgroundOutcomes of ketamine intravenous therapy (KIT) for depression in real-world care settings have been minimally evaluated. We set out to quantify treatment response to KIT in a large sample of patients from community-based practices. MethodsWe retrospectively analyzed 9016 depression patients who received KIT between 2016 and 2020 at one of 178 community practices across the United States. Depression symptoms were evaluated using the Patient Health Questionnaire-9 (PHQ-9). The induction phase of KIT was defined to be a series of 4–8 infusions administered over 7 to 28 days. ResultsAmong the 537 patients who underwent induction and had sufficient data, 53.6% of patients showed a response (≥ 50% reduction in PHQ-9 score) at 14–31 days post-induction and 28.9% remitted (PHQ-9 score drop to < 5). The effect size was d = 1.5. Among patients with baseline suicidal ideation (SI), 73.0% exhibited a reduction in SI. A subset (8.4%) of patients experienced an increase in depressive symptoms after induction while 6.0% of patients reported increased SI. The response rate was uniform across 4 levels of baseline depression severity. However, more severe illness was weakly correlated with a greater drop in scores while remission status was weakly inversely correlated with depression severity. Kaplan-Meier analyses showed that a patient who responds to KIT induction has approximately 80% probability of sustaining response at 4 weeks and approximately 60% probability at 8 weeks, even without maintenance infusions. ConclusionKIT can elicit a robust antidepressant response in community clinics; however, a small percentage of patients worsened.

Real-world evidence and product development: Opportunities, challenges and risk mitigation

Real-world evidence (RWE) is derived from real-world data (RWD) sources including electronic health records, claims data, registries (disease, product) and pragmatic clinical trials. The importance of RWE derived from RWD has been once again demonstrated during the coronavirus disease 2019 (COVID-19) pandemic, as it can improve patient care by complementing information obtained from traditional clinical trial programs. Additionally, RWE can generate insights into disease mechanisms, epidemiology, patient flows in and out of healthcare systems, and drivers and barriers to optimal clinical care in real-world settings. Identifying unmet medical needs is crucial as it often can inform which investigational new drugs enter clinical trial testing, and RWE studies from hospital settings have contributed substantial progress here. RWE can also optimize the design of clinical studies, inform benefit risk assessments and use networks of pragmatic studies to help with clinical trial feasibilities and eventual trial initiation. The challenges of RWD include data quality, reproducibility and accuracy which may affect validity. RWD and RWE must be fit for purpose and one must be cognizant of inherent biases.

The Role of Implementation Science in Reducing Sexual and Gender Minority Mental Health Disparities.

Owing to multiple and multilevel ecological factors, sexual and gender minority (SGM) populations exhibit persistent mental health disparities. SGM populations are also at increased risk for never being reached by evidence-based mental health care in real-world settings, which is essential for reducing these disparities. To be maximally effective in reducing these disparities, we must strive to bring our research findings into routine clinical care quickly. Implementation science can help SGM health researchers achieve this goal. This perspective outlines how researchers can use implementation science theories and methods to reduce SGM mental health disparities more efficiently and more durably.

Value from health data: European opportunity to catalyse progress in digital health

Value from health data: European opportunity to catalyse progress in digital health

A systematic literature review of recommendations for referral to specialty care for patients with epilepsy

ObjectiveIn epilepsy, patients who receive appropriate care receive treatment that differs substantially from those that do not. Given the need for a more detailed assessment of the role of specialty referral in the care of patients with epilepsy, this systematic literature review identified epilepsy care guidelines and recommendations that specifically address when and why people with epilepsy should be referred to specialty care. MethodsThis study identified recent (in the last 10 years) publications that made best-practice recommendations for referring people with epilepsy to a neurologist or epileptologist. We searched six databases in December 2018: MEDLINE (PubMed), Cochrane Library, ProQuest, Web of Science, CINAHL (Ebsco), Scopus (Elsevier). Search terms included “Epilepsy” OR “Seizures,” “Guideline” OR “Practice Parameter,” and “Referral.” ResultsThe 15 full-text articles identified included formal guidelines, summaries of these guidelines, or professional commentary that builds upon existing guidelines. Most of these publications came from the U.K and its National Institute for Health and Care Excellence. Overall, the included recommendations for referral varied considerably both for new-onset and refractory epilepsy. Although these recommendations were not consistent, it is reasonable to refer patients following the failure of 2 anti-seizure medication (ASM) trials. SignificanceGuidelines and informal recommendations are not consistent regarding best practices for specialty care referral for patients with epilepsy. These guidelines and recommendations should consider the context of care in real-world settings and suggest pragmatic approaches that optimize seizure control and functioning.