Scaling care coordination through digital engagement: stepped-wedge trial assessing readmissions

OBJECTIVES

Transitions of care are pivotal, vulnerable times as patients are discharged from the hospital. Telephonic care coordination is standard care, but labor intensive. We implemented a patient postdischarge digital engagement (PDDE) program to scale coordination. We hypothesized that PDDE could reduce readmissions for low-risk patients and supplement care coordination for medium- and high-risk patients.

STUDY DESIGN

Pragmatic, stepped-wedge cluster randomization trial with 5 implementation waves based upon primary care clinic region.

METHODS

All inpatient hospital discharges between March 2020 and November 2020 were stratified by readmission risk. Low-risk patients were offered access to PDDE, and moderate-risk and high-risk patients were offered access to PDDE and care coordination. Readmission was defined as an unplanned inpatient admission within 30 days from discharge. An intention-to-treat primary analysis was conducted using mixed-effects logistic regression clustering for wave; a treatment-on-the-treated analysis was also conducted to assess the impact among program users.

RESULTS

A total of 5490 patient discharges were examined (2735 control; 2755 intervention); 1949 patients were high risk, 2032 were medium risk, and 1509 were low risk. PDDE intervention did not significantly affect readmission among low-risk (95% CI, -0.23 to 0.90; P  = .23), medium-risk (95% CI, -0.14 to 0.60; P  = .21), and high-risk (95% CI, -0.32 to 0.64; P  = .48) groups after adjustment for time and patient factors. In a treatment-on-the-treated analysis, among patients who activated the PDDE program, readmission was also similar among the low-, medium-, and high-risk cohorts.

CONCLUSIONS

Our study expanded resource-limited care coordination by offering low-risk patients a service they were unable to receive previously while having no impact on readmission. PDDE efficiently provided additional touch points between patients and providers.

Causal inference in medical records and complementary systems pharmacology for metformin drug repurposing towards dementia

Metformin, a diabetes drug with anti-aging cellular responses, has complex actions that may alter dementia onset. Mixed results are emerging from prior observational studies. To address this complexity, we deploy a causal inference approach accounting for the competing risk of death in emulated clinical trials using two distinct electronic health record systems. In intention-to-treat analyses, metformin use associates with lower hazard of all-cause mortality and lower cause-specific hazard of dementia onset, after accounting for prolonged survival, relative to sulfonylureas. In parallel systems pharmacology studies, the expression of two AD-related proteins, APOE and SPP1, was suppressed by pharmacologic concentrations of metformin in differentiated human neural cells, relative to a sulfonylurea. Together, our findings suggest that metformin might reduce the risk of dementia in diabetes patients through mechanisms beyond glycemic control, and that SPP1 is a candidate biomarker for metformin's action in the brain.

Overcoming Eurocentric bias makes for better science

To understand disease, scientists are producing comprehensive omics datasets. However, the majority of these are Eurocentric. Recently, the inclusion of patients from Asia and the Middle East in genomic analyses uncovered unique loci linked to COVID-19 severity. This demonstrates that focusing on diversity and underrepresented populations can benefit all.

Telemedicine and health disparities: Association between patient characteristics and telemedicine, in-person, telephone and message-based care during the COVID-19 pandemic

Telemedicine has been an essential form of care since the onset of the COVID-19 pandemic. However, telemedicine may exacerbate disparities for populations with limited digital literacy or access, such as older adults, racial minorities, patients of low income, rural residences, or limited English proficiency. From March 2020 to March 2022, this retrospective cohort study analyzed the use of in-person, phone/message, and telemedical care at a single tertiary care center in an oncology department. We investigated the association between economic, racial, ethnic, socioeconomic factors and forms of care, including in-person visits, telemedicine-based visits, and telephone/messages. The study results show that telemedicine utilization is lower among patients 65 and older, female patients, American Indian or Alaska Native patients, uninsured patients, and patients who require interpreters during clinical visits. As a result, it is unlikely that telemedicine will provide equal access to clinical care for all populations. On the other hand, in-person care utilization remains low in low-income and rural-living patients compared to the general population, while telephone and message use remains high in low-income and rural-living patients. We conclude that telemedicine is currently unable to close the utilization gap for populations of low socioeconomic status. Patients with low socioeconomic status use in-person care less frequently. For the disadvantaged, unusually high telephone or message utilization is unlikely to provide the same quality as in-person or telemedical care. Understanding the causes of disparity and promoting a solution to improve equal access to care for all patients is critical.

Real-world implementation evaluation of an electronic health record-integrated consumer informatics tool that collects patient-generated contextual data

OBJECTIVE

Use the RE-AIM framework to examine the implementation of a patient contextual data (PCD) Tool designed to share patients' needs, values, and preferences with care teams ahead of clinical encounters.

MATERIALS & METHODS

Observational study that follows initial PCD Tool scaling across primary care at a Midwestern academic health network. Program invitations, enrollment, patient submissions, and clinician views were tracked over a 1-year study period. Logistic regression modeled the likelihood of using the PCD Tool, accounting for patient covariates.

RESULTS

Of 58,874 patients who could be contacted by email, 9,183 (15.6%) became PCD Tool users. Overall, 76% of primary care providers had patients who used the PCD Tool. Older age, female gender, non-minority race, patient portal activation, and Medicare coverage were significantly associated with increased likelihood of use. Number of office visits, medical issues, and behavioral health conditions also associated with use. Primary care staff viewed 18.7% of available PCD Tool summaries, 1.1% to 57.6% per clinic.

DISCUSSION

The intervention mainly reached non-minority patients and patients who used more health services. Given the requirement for an email address on file, some patients may have been underrepresented. Overall, patient reach and adoption and clinician adoption, implementation, and maintenance of this Tool were modest but stable, consistent with a non-directive approach to fostering adoption by introducing the Tool in the absence of clear expectations for use.

CONCLUSION

Healthcare organizations must implement effective methods to increase the reach, adoption, implementation, and maintenance of PCD tools across all patient populations. Assisting people, particularly racial minorities, with PCD Tool registration and actively supporting clinician use are critical steps in implementing technology that facilitates care.

Impact of Pre-visit Contextual Data Collection on Patient-Physician Communication and Patient Activation: a Randomized Trial

BACKGROUND

Patient contextual data (PCD) are often missing from electronic health records, limiting the opportunity to incorporate preferences and life circumstances into care. Engaging patients through tools that collect and summarize such data may improve communication and patient activation. However, differential tool adoption by race might widen health care disparities.

OBJECTIVE

Determine if a digital tool designed to collect and present PCD improves communication and patient activation; secondarily, evaluate if use impacts outcomes by race.

DESIGN, SETTING, AND PARTICIPANTS

A pragmatic, two-armed, non-blinded, randomized controlled trial conducted during 2019 in a primary care setting.

INTERVENTION

The PCD tool (PatientWisdom) invited patients to identify preferences, values, goals, and barriers to care. Patients were randomized to a standard pre-visit email or facilitated enrollment with dedicated outreach to encourage use of the tool.

MAIN OUTCOMES AND MEASURES

Outcomes of interest were post-visit patient communication and patient activation measured by the Communication Assessment Tool (CAT) and Patient Activation Measure (PAM), respectively. Outcomes were evaluated using treatment-on-the-treated (TOT) and intention-to-treat (ITT) principles.

KEY RESULTS

A total of 301 patients were enrolled. Facilitated enrollment resulted in a five-fold increase in uptake of the PCD tool. TOT analysis indicated that the PCD tool was associated with notable increases in specific CAT items rated as excellent: "treated me with respect" (+ 13 percentage points; p = 0.04), "showed interest in my ideas" (+ 14 percentage points; p = 0.03), "showed care and concern" (+ 16 percentage points; p = 0.02), and "spent about the right amount of time with me" (+ 11 percentage points; p = 0.05). There were no significant pre/post-visit differences in PAM scores between arms (- 4.41 percentage points; p = 0.58). ITT results were similar. We saw no evidence of the treatment effect varying by race in ITT or TOT analyses.

CONCLUSIONS AND RELEVANCE

The inclusion of PCD enhanced essential aspects of patient-provider communication but did not affect patient activation. Outcomes did not differ by race.

TRIAL REGISTRATION

Clincaltrials.gov identifier: NCT03766841.

Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities

BACKGROUND

The telemedicine industry has been experiencing fast growth in recent years. The outbreak of coronavirus disease 2019 (COVID-19) further accelerated the deployment and utilization of telemedicine services. An analysis of the socioeconomic characteristics of telemedicine users to understand potential socioeconomic gaps and disparities is critical for improving the adoption of telemedicine services among patients.

OBJECTIVES

This study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area.

METHODS

Electronic health record review of patients using telemedicine services compared with those not using telemedicine services within an academic-community health system: patient demographics (e.g., age, gender, race, and ethnicity), insurance status, and socioeconomic determinants obtained through block-level census data in Milwaukee area. The telemedicine users were compared with all other patients using regression analysis. The telemedicine adoption rates were calculated across regional ZIP codes to analyze the geographic patterns of telemedicine adoption.

RESULTS

A total of 104,139 patients used telemedicine services during the study period. Patients who used video visits were younger (median age 48.12), more likely to be White (odds ratio [OR] 1.34; 95% confidence interval [CI], 1.31-1.37), and have private insurance (OR 1.43; CI, 1.41-1.46); patients who used telephone visits were older (median age 57.58), more likely to be Black (OR 1.31; CI 1.28-1.35), and have public insurance (OR 1.30; CI 1.27-1.32). In general, Latino and Asian populations were less likely to use telemedicine; women used more telemedicine services in general than men. In the multiple regression analysis of social determinant factors across 126 ZIP codes, college education (coefficient 1.41, p = 0.01) had a strong correlation to video telemedicine adoption rate.

CONCLUSION

Adoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type. The study reveals the potential inequities and disparities in telemedicine adoption.

Addressing depression and behavioral health needs through a digital program at scale

Depression and anxiety disorders are prevalent mental health conditions; yet they are often unrecognized, under-addressed and/or under-treated, and specialty treatment for these conditions is oftentimes difficult to access. By acting either as a bridge to therapy or as a form of therapy, digital tools, such as those that provide internet-based cognitive behavioral therapy (iCBT), may help clinicians support their patients' mental health needs. At one academic health system, a digital mental health program was deployed in primary care and outpatient behavioral health programs to help patients meet needs identified through screening or clinical visits. Over the first two years of operation, 138 clinicians (40% of eligible clinicians) prescribed the program to 2,228 unique patients, from which 1,117 (48.9%) enrolled. Patients who enrolled tended to be younger and healthier than non-enrollees. On average, enrolled patients spent 114.6 minutes within the iCBT program. Clinical improvement was assessed using pre- and post PHQ-9 and GAD-7 scores for depression and anxiety, respectively. Pre/Post scores were compared using Wilcoxon Rank Sum test. Patients with at least moderate depression had an average 23% reduction in PHQ-9 scores (median change -3(interquartile range 7), p<0.001) and those with at least moderate anxiety had a 26% reduction in GAD-7 scores (-4(7), p<0.001). Improvements were clinically and statistically significant. Future steps include performing a cost analysis to understand whether models utilizing iCBT are net cost-saving for health systems.

The Bugs In the Virtual Clinic: Confronting Telemedicine’s Challenges Through Empathy and Support (Preprint)

Although telemedicine has been an important conduit for clinical care during the COVID-19 pandemic, not all patients have been able to meaningfully participate in this mode of health care provision. Challenges with accessing telemedicine using consumer technology can interfere with the ability of patients and clinicians to meaningfully connect and lead to significant investments in time by clinicians and their staff. In this narrative case, we identify issues related to patients’ use of technology, make comparisons between telehealth adoption and the deployment of electronic health records, and propose that building intuitive and supported digital care experiences for patients is required to make virtual care sustainable.

The Impact of Previsit Contextual Data Collection on Patient-Provider Communication and Patient Activation: Study Protocol for a Randomized Controlled Trial

BACKGROUND

Patient-centered care is respectful of and responsive to individual patient preferences, needs, and values. To provide patient-centered care, clinicians need to know and incorporate patients' context into their communication and care with patients. Patient contextual data (PCD) encompass social determinants of health and patients' needs, values, goals, and preferences relevant to their care. PCD can be challenging to collect as a routine component of the time-limited primary care visit.

OBJECTIVE

This study aims to determine if patient-provider communication and patient activation are different for patient users and patient nonusers of an electronic health record (EHR)-integrated PCD tool and assess if the impact of using PCD on patient-provider communication and patient activation differs for Black and White patients.

METHODS

We describe a randomized controlled trial of a prospective cohort of non-Hispanic White and Black patients who receive primary care services at a midwestern academic health care system in the United States. We will evaluate whether providing PCD through a consumer informatics tool enhances patient-provider communication, as measured by the Communication Assessment Tool, and we will evaluate patient activation, as measured by the Patient Activation Measure for PCD tool users and nonusers. Furthermore, owing to racial disparities in care and communication, we seek to determine if the adoption and use of the tool might narrow the differences between patient groups.

RESULTS

The trial was funded in November 2017 and received local ethics review approval in February 2019. The study began recruitment in April 2019 and enrollment concluded in October 2019 with 301 participants. The analysis was completed in May 2020, and trial results are expected to be published in winter 2020.

CONCLUSIONS

Recently, there has been increased attention to the role of health information technology tools to enable patients to collaborate with providers through the sharing of PCD. The adoption of such tools may overcome the barriers of current EHRs by directly engaging patients to submit their contextual data. Effectively, these tools would support the EHR in providing a more holistic understanding of the patient. Research further supports that individuals who have robust digital engagement using consumer informatics tools have higher participation in treatment follow-up and self-care across populations. Therefore, it is critical to investigate interventions that elicit and share patients' social risks and care preferences with the health care team as a mechanism to improve individualized care and reduce the gap in health outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03766841; https://clinicaltrials.gov/ct2/show/NCT03766841.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/20309.

[A perimyocarditis revealing eosinophilic granulomatosis with polyangiitis]

Churg-Strauss syndrome (CSS) or eosinophilic granulomatosis with polyangiitis is a systemic vasculitis characterized by necrotizing arteritis, eosinophilic infiltration and extravascular granuloma; that may involve several organs. Cardiac involvement is the first cause of death in this vasculitis. These include myocarditis, pericarditis, coronary heart disease, dysrhythmias, and rarely valvular involvement. We report the observation of CSS revealed by acute perimyocarditis.

Association of Use of Online Symptom Checkers With Patients' Plans for Seeking Care

This cross-sectional study examines the association of patient use of a free online symptom checker tool with patient plans for seeking medical care.

Clinical trials of neurointervention : 2007-2018

BACKGROUND

ClinicalTrials.gov is one of the largest trials' registries in the world.

OBJECTIVE

To leverage the ClinicalTrials.gov database to define the portfolio of clinical trials of neurointervention.

METHODS

We restricted our extraction to interventional clinical trials submitted between 2007 and 2018, and included MeSH terms that are part of the nervous system (n=19 344) or cardiovascular disease (n=19 234) categories and included a list of neurointerventional terms. The characteristics of trials, geographic distribution, dissemination, and funding sources were explored using descriptive and regression models.

RESULTS

A total of 206 neurointerventional clinical trials across 1691 medical centers were identified. Acute stroke was the most studied conditions (68, 33%), followed by aneurysms (63, 31%), carotid stenosis (48, 24%), intracranial atherosclerotic disease (7, 3.5%), cerebral venous thrombosis (6, 3%), arteriovenous malformation (4, 2%), idiopathic intracranial hypertension (3, 1.5%), and others (6, 3%). Overall, 59 (29%) trials were completed, 79 (37%) were active trials (28% recruiting), and 22 (11%) were terminated or suspended. Academic centers and industry were the most common primary funding source (63% and 29%, respectively), with no funding source reported in 16 (7.7%) trials. Among 77 completed or terminated trials, only 9 (11.7%) trials reported findings within 12 months. Median time to publication for trials funded by academia was 1.66 years (interquartile range (IQR) 0.7-2.1) versus 2.1 years (IQR 1.2-3.25) for industry-funded studies.

CONCLUSIONS

A low dissemination rate for results and a high rate of study non-completion, as well as lack of geographic dispersion of trials appear to be major challenges in the field.

Predictive analytics and machine learning in stroke and neurovascular medicine

Advances in predictive analytics and machine learning supported by an ever-increasing wealth of data and processing power are transforming almost every industry. Accuracy and precision of predictive analytics have significantly increased over the past few years and are evolving at an exponential pace. There have been significant breakthroughs in using Predictive Analytics in healthcare where it is held as the foundation of precision medicine. Yet, although the research in the field is expanding with the profuse volume of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Regardless of the status of its current contribution, the field of predictive analytics is expected to fundamentally change the way we diagnose and treat diseases, as well as the conduct of biomedical science research. In this review, we describe the main tools and techniques in predictive analytics and will analyze the trends in application of these techniques over the recent years. We will also provide examples of its application in medicine and more specifically in stroke and neurovascular research and outline current limitations.

Most UK scientists who publish extremely highly-cited papers do not secure funding from major public and charity funders: A descriptive analysis

The UK is one of the largest funders of health research in the world, but little is known about how health funding is spent. Our study explores whether major UK public and charitable health research funders support the research of UK-based scientists producing the most highly-cited research. To address this question, we searched for UK-based authors of peer-reviewed papers that were published between January 2006 and February 2018 and received over 1000 citations in Scopus. We explored whether these authors have held a grant from the National Institute for Health Research (NIHR), the Medical Research Council (MRC) and the Wellcome Trust and compared the results with UK-based researchers who serve currently on the boards of these bodies. From the 1,370 papers relevant to medical, biomedical, life and health sciences with more than 1000 citations in the period examined, we identified 223 individuals from a UK institution at the time of publication who were either first/last or single authors. Of those, 164 are still in UK academic institutions, while 59 are not currently in UK academia (have left the country, are retired, or work in other sectors). Of the 164 individuals, only 59 (36%; 95% CI: 29-43%) currently hold an active grant from one of the three funders. Only 79 (48%; 95% CI: 41-56%) have held an active grant from any of the three funders between 2006-2017. Conversely, 457 of the 664 board members of MRC, Wellcome Trust, and NIHR (69%; 95% CI: 65-72%) have held an active grant in the same period by any of these funders. Only 7 out of 655 board members (1.1%) were first, last or single authors of an extremely highly-cited paper. There are many reasons why the majority of the most influential UK authors do not hold a grant from the country's major public and charitable funding bodies. Nevertheless, the results are worrisome and subscribe to similar patterns shown in the US. We discuss possible implications and suggest ways forward.

From Pharmacovigilance to Clinical Care Optimization

In order to ensure the continued, safe administration of pharmaceuticals, particularly those agents that have been recently introduced into the market, there is a need for improved surveillance after product release. This is particularly so because drugs are used by a variety of patients whose particular characteristics may not have been fully captured in the original market approval studies. Even well-conducted, randomized controlled trials are likely to have excluded a large proportion of individuals because of any number of issues. The digitization of medical care, which yields rich and accessible drug data amenable to analytic techniques, provides an opportunity to capture the required information via observational studies. We propose the development of an open, accessible database containing properly de-identified data, to provide the substrate for the required improvement in pharmacovigilance. A range of stakeholders could use this to identify delayed and low-frequency adverse events. Moreover, its power as a research tool could extend to the detection of complex interactions, potential novel uses, and subtle subpopulation effects. This far-reaching potential is demonstrated by our experience with the open Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) intensive care unit database. The new database could also inform the development of objective, robust clinical practice guidelines. Careful systematization and deliberate standardization of a fully digitized pharmacovigilance process is likely to save both time and resources for healthcare in general.

A cannonball through the chest: disseminated tuberculosis, threatening the aortic arch

BACKGROUND

In 2012 the World Health Organization reported 8.7 million new cases of Tuberculosis worldwide, causing 1.4 million deaths (1). Despite modern drug therapy, this disease continues to present in novel ways and mimic other diseases causing misdiagnosis.

AIM

We report this case to educate on the reason to suspect atypical Tuberculosis presentation, even if a common disease is diagnosed, when Tuberculosis remains in the differential. We also demonstrate that with globalization and patient moving between countries, that these presentations can occur in locations, where such atypical manifestations are very uncommon.

CASE

We report on a 48 year old man with one month of malaise, fever, productive cough, night sweats, chills, pleuritic chest pain, weight loss and progressive non-painful swelling on his thorax. Initial diagnoses of interstitial pneumonia and a thoracic subcutaneous abscess were made. Needle drainage was attempted, with thick purulent material returned. When the sternum was not struck with the needle, a thoracic computed tomography scan was performed. A milliary pattern was noted in the lungs, with a large abscess present anteriorly, completely obliterating the manubrium, approaching the aorta with distant lesions. Subsequent analysis showed the material to be pan-sensitive M. Tuberculosis.

CONCLUSION

The issue that this case raises is that when tuberculosi is in the differential, even common diseases may in fact be atypical manifestations of tuberculosis. In addition, when a shallow surgical procedure is going to be performed on the thoracic soft tissues, particularly when tuberculosis is suspected, imaging of the thorax should be obtained.