Effectiveness of subcutaneous monoclonal antibody treatment in emergency department outpatients with COVID-19.

Objectives: To evaluate whether subcutaneous neutralizing monoclonal antibody (mAb) treatment given in the emergency department (ED) setting was associated with reduced hospitalizations, mortality, and severity of disease when compared to nontreatment among mAb-eligible patients with coronavirus disease 2019 (COVID-19). Methods: This retrospective observational cohort study of ED patients utilized a propensity score-matched analysis to compare patients who received subcutaneous casirivimab and imdevimab mAb to nontreated COVID-19 control patients in November-December 2021. The primary outcome was all-cause hospitalization within 28 days, and secondary outcomes were 90-day hospitalization, 28- and 90-day mortality, and ED length of stay (LOS). Results: Of 1340 patients included in the analysis, 490 received subcutaneous casirivimab and imdevimab, and 850 did not received them. There was no difference observed for 28-day hospitalization (8.4% vs. 10.6%; adjusted odds ratio [aOR] 0.79, 95% confidence intervals [CI] 0.53-1.17) or 90-day hospitalization (11.6% vs. 12.5%; aOR 0.93, 95% CI 0.65-1.31). However, mortality at both the 28-day and 90-day timepoints was substantially lower in the treated group (28-day 0.6% vs. 3.1%; aOR 0.18, 95% CI 0.08-0.41; 90-day 0.6% vs. 3.9%; aOR 0.14, 95% CI 0.06-0.36). Among hospitalized patients, treated patients had shorter hospital LOS (5.7 vs. 11.4 days; adjusted rate ratio [aRR] 0.47, 95% CI 0.33-0.69), shorter intensive care unit LOS (3.8 vs. 10.2 days; aRR 0.22, 95% CI 0.14-0.35), and the severity of hospitalization was lower (aOR 0.45, 95% CI 0.21-0.97) compared to untreated. Conclusions: Among ED patients who presented for symptomatic COVID-19 during the Delta variant phase, ED subcutaneous casirivimab/imdevimab treatment was not associated with a decrease in hospitalizations. However, treatment was associated with lower mortality at 28 and 90 days, hospital LOS, and overall severity of illness.

Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

ED-based COVID-19 vaccination campaign finds higher vaccination rates for individuals from racial and ethnic minority groups compared with clinic setting.

BACKGROUND: Emergency department visits associated with Coronavirus Disease 2019 (COVID-19) continue to indicate racial and ethnic inequities. We describe the sociodemographic characteristics of individuals receiving COVID-19 vaccination in the emergency department and compare with an outpatient clinic population and emergency department (ED) patients who were eligible but not vaccinated. METHODS: We conducted a retrospective analysis of electronic health record data at an urban academic ED from May to July 2021. The primary aim was to characterize the ED-vaccinated population, compared with ED patients who were eligible but unvaccinated and the physically adjacent outpatient vaccination clinic population. RESULTS: A total of 627 COVID-19 vaccinations were administered in the ED. Overall, 49% of ED patients during that time had already received at least one vaccine dose prior to ED arrival. Hispanic, non-Hispanic Black patients, and patients on non-commercial insurance had higher odds of being vaccinated in the ED as compared with outpatient clinic setting. Among eligible ED patients, men and patients who were uninsured/self-pay were more likely to accept ED vaccination. CONCLUSIONS: This ED COVID-19 vaccination campaign demonstrated a higher likelihood to vaccinate individuals from racial/ethnic minority groups, those with high social vulnerability, and non-commercial insurance, when compared with a co-located outpatient vaccination clinic.

Real-World Evidence of Neutralizing Monoclonal Antibodies for Preventing Hospitalization and Mortality in COVID-19 Outpatients.

BACKGROUND: Neutralizing monoclonal antibodies (mAbs) were authorized for the treatment of COVID-19 outpatients based on clinical trials completed early in the pandemic, which were underpowered for mortality and subgroup analyses. Real-world data studies are promising for further assessing rapidly deployed therapeutics. RESEARCH QUESTION: Did mAb treatment prevent progression to severe disease and death across pandemic phases and based on risk factors, including prior vaccination status? STUDY DESIGN AND METHODS: This observational cohort study included nonhospitalized adult patients with SARS-CoV-2 infection from November 2020 to October 2021 using electronic health records from a statewide health system plus state-level vaccine and mortality data. Using propensity matching, we selected approximately 2.5 patients not receiving mAbs for each patient who received mAb treatment under emergency use authorization. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and hospitalization severity. RESULTS: Of 36,077 patients with SARS-CoV-2 infection, 2,675 receiving mAbs were matched to 6,677 patients not receiving mAbs. Compared with mAb-untreated patients, mAb-treated patients had lower all-cause hospitalization (4.0% vs 7.7%; adjusted OR, 0.48; 95% CI, 0.38-0.60) and all-cause mortality (0.1% vs 0.9%; adjusted OR, 0.11; 95% CI, 0.03-0.29) to day 28; differences persisted to day 90. Among hospitalized patients, mAb-treated patients had shorter hospital length of stay (5.8 vs 8.5 days) and lower risk of mechanical ventilation (4.6% vs 16.6%). Results were similar for preventing hospitalizations during the Delta variant phase (adjusted OR, 0.35; 95% CI, 0.25-0.50) and across subgroups. Number-needed-to-treat (NNT) to prevent hospitalization was lower for subgroups with higher baseline risk of hospitalization; for example, multiple comorbidities (NNT = 17) and not fully vaccinated (NNT = 24) vs no comorbidities (NNT = 88) and fully vaccinated (NNT = 81). INTERPRETATION: Real-world data revealed a strong association between receipt of mAbs and reduced hospitalization and deaths among COVID-19 outpatients across pandemic phases. Real-world data studies should be used to guide practice and policy decisions, including allocation of scarce resources.

The Role of Academic Health Systems in Leading the "Third Wave" of Digital Health Innovation.

Investors, entrepreneurs, health care pundits, and venture capital firms all agree that the health care sector is awaiting a digital revolution. Steven Case, in 2016, predicted a "third wave" of innovation that would leverage big data, artificial intelligence, and machine learning to transform medicine and finally achieve reduced costs, improved efficiency, and better patient outcomes. Academic medical centers (AMCs) have the infrastructure and resources needed by digital health intrapreneurs and entrepreneurs to innovate, iterate, and optimize technology solutions for the major pain points of modern medicine. With large unique patient data sets, strong research programs, and subject matter experts, AMCs have the ability to assess, optimize, and integrate new digital health tools with feedback at the point of care and research-based clinical validation. As AMCs begin to explore digital health solutions, they must decide between forming internal teams to develop these innovations or collaborating with external companies. Although each has its drawbacks and benefits, AMCs can both benefit from and drive forward the digital health innovations that will result from this journey. This viewpoint will provide an explanation as to why AMCs are ideal incubators for digital health solutions and describe what these organizations will need to be successful in leading this "third wave" of innovation.

Machine Learning-Based Exploratory Clinical Decision Support for Newly Diagnosed Patients With Acute Myeloid Leukemia Treated With 7 + 3 Type Chemotherapy or Venetoclax/Azacitidine.

PURPOSE: There are currently limited objective criteria to help assist physicians in determining whether an individual patient with acute myeloid leukemia (AML) is likely to do better with induction with either standard 7 + 3 chemotherapy or targeted therapy with venetoclax plus azacitidine. The study goal was to address this need by developing exploratory clinical decision support methods. PATIENTS AND METHODS: Univariable and multivariable analysis as well as comparison of a range of machine learning (ML) predictors were performed using cohorts of 120 newly diagnosed 7 + 3-treated AML patients compared with 101 venetoclax plus azacitidine-treated patients. RESULTS: A variety of features in the two patient cohorts were identified that may potentially correlate with short- and long-term outcomes, toxicities, and other considerations. A subset of these diagnostic features was then used to develop ML-based predictors with relatively high areas under the curve of short- and long-term outcomes, hospital stays, transfusion requirements, and toxicities for individual patients treated with either venetoclax/azacitidine or 7 + 3. CONCLUSION: Potential ML-based approaches to clinical decision support to help guide individual patients with newly diagnosed AML to either 7 + 3 or venetoclax plus azacitidine induction therapy were identified. Larger cohorts with separate test and validation studies are necessary to confirm these initial findings.

Real-World Evidence of the Neutralizing Monoclonal Antibody Sotrovimab for Preventing Hospitalization and Mortality in COVID-19 Outpatients.

BACKGROUND: It is not known whether sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic coronavirus disease 2019 (COVID-19) patients, is also effective in preventing the progression of severe disease and mortality following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant infection. METHODS: In an observational cohort study of nonhospitalized adult patients with SARS-CoV-2 infection, 1 October 2021-11 December 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data, we used propensity matching to select 3 patients not receiving mAbs for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization. RESULTS: Of 10 036 patients with SARS-CoV-2 infection, 522 receiving sotrovimab were matched to 1563 not receiving mAbs. Compared to mAb-untreated patients, sotrovimab treatment was associated with a 63% decrease in the odds of all-cause hospitalization (raw rate 2.1% vs 5.7%; adjusted odds ratio [aOR], 0.37; 95% confidence interval [CI], .19-.66) and an 89% decrease in the odds of all-cause 28-day mortality (raw rate 0% vs 1.0%; aOR, 0.11; 95% CI, .0-.79), and may reduce respiratory disease severity among those hospitalized. CONCLUSIONS: Real-world evidence demonstrated sotrovimab effectiveness in reducing hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Delta variant phase.

Real World Evidence of the Neutralizing Monoclonal Antibody Sotrovimab for Preventing Hospitalization and Mortality in COVID-19 Outpatients.

Background: It is not known whether sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic COVID-19 patients, is effective against the SARS-CoV-2 Delta variant to prevent progression to severe disease and mortality. Methods: Observational cohort study of non-hospitalized adult patients with SARS-CoV-2 infection from October 1 st 2021 - December 11 th 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data. We used propensity matching to select 3 patients not receiving mAbs for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization. Results: Of 10,036 patients with SARS-CoV-2 infection, 522 receiving sotrovimab were matched to 1,563 not receiving mAbs. Compared to mAb-untreated patients, sotrovimab treatment was associated with a 63% decrease in the odds of all-cause hospitalization (raw rate 2.1% versus 5.7%; adjusted OR 0.37, 95% CI 0.19-0.66) and an 89% decrease in the odds of all-cause 28-day mortality (raw rate 0% versus 1.0%; adjusted OR 0.11, 95% CI 0.0-0.79), and may reduce respiratory disease severity among those hospitalized. Conclusion: Real-world evidence demonstrated sotrovimab effectiveness in reducing hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Delta variant phase.

COVID-19 Vaccine Clinic Real-Time Throughput Analysis: Development and Implementation of an Innovative Data Collection Tool.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic has presented the healthcare system with a plethora of challenges, including implementation of an efficient vaccination strategy. Mass vaccinations have been used during previous pandemics; however, the associated data have largely been limited to theoretical simulations and post hoc analysis. METHODS: An innovative data collection tool was created to deliver real-time data analysis during a drive-through mass vaccination. Patients were assigned unique identification numbers at the clinic entrance. Using these identification numbers, and the web-based spreadsheet, patients were tracked throughout the vaccination process. Static timestamps corresponding to the entry and exit at each checkpoint were recorded in real time. RESULTS: Data were collected on a total of 3,744 vehicles over five clinic days. Total time was collected, from entry to exit, on 2,860 vehicles. Registration and vaccination times were collected on 3,111 vehicles. Of the vehicles sampled, 1,588 (42%) had data points associated with all checkpoints. CONCLUSIONS: This open-source, innovative data collection tool was successfully implemented in our mass vaccination clinic for tracking patients in real time providing actionable data on overall throughput efficiency. This cost-effective tool can be used on a variety of healthcare-related projects to provide data-driven evaluation on the efficiency of care.

Real World Evidence of Neutralizing Monoclonal Antibodies for Preventing Hospitalization and Mortality in COVID-19 Outpatients.

BACKGROUND: Neutralizing monoclonal antibodies (mAbs) are authorized for early symptomatic COVID-19 patients. Whether mAbs are effective against the SARS-CoV-2 Delta variant, among vaccinated patients, or for prevention of mortality remains unknown. OBJECTIVE: To evaluate the effectiveness of mAb treatment in preventing progression to severe disease during the Delta phase of the pandemic and based on key baseline risk factors. DESIGN SETTING AND PATIENTS: Observational cohort study of non-hospitalized adult patients with SARS-CoV-2 infection from November 2020-October 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data. Using propensity matching, we selected approximately 2.5 patients not receiving mAbs for each patient who received mAbs. EXPOSURE: Neutralizing mAb treatment under emergency use authorization. MAIN OUTCOMES: The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization. RESULTS: Of 36,077 patients with SARS-CoV-2 infection, 2,675 receiving mAbs were matched to 6,677 not receiving mAbs. Compared to mAb-untreated patients, mAb-treated patients had lower all-cause hospitalization (4.0% vs 7.7%; adjusted OR 0.48, 95%CI 0.38-0.60) and all-cause mortality (0.1% vs. 0.9%; adjusted OR 0.11, 95%CI 0.03-0.29) to day 28; differences persisted to day 90. Among hospitalized patients, mAb-treated patients had shorter hospital length of stay (5.8 vs. 8.5 days) and lower risk of mechanical ventilation (4.6% vs. 16.6%). Relative effectiveness was similar in preventing hospitalizations during the Delta variant phase (adjusted OR 0.35, 95%CI 0.25-0.50) and across subgroups. Lower number-needed-to-treat (NNT) to prevent hospitalization were observed for subgroups with higher baseline risk of hospitalization (e.g., multiple comorbidities (NNT=17) and not fully vaccinated (NNT=24) vs. no comorbidities (NNT=88) and fully vaccinated (NNT=81). CONCLUSION: Real-world evidence demonstrated mAb effectiveness in reducing hospitalization among COVID-19 outpatients, including during the Delta variant phase, and conferred an overall 89% reduction in 28-day mortality. Early outpatient treatment with mAbs should be prioritized, especially for individuals with highest risk for hospitalization.

The Case for Virtual Sepsis Surveillance and Intervention.

Study Objective:To determine whether deployment of an integrated virtual sepsis surveillance program could improve time to antibiotics and mortality in a longitudinal cohort of non-present on admission (NPOA) sepsis cases.Methods:We used an uncontrolled pre- and poststudy design to compare time to antibiotics and mortality between a time-based cohort of NPOA sepsis cases separated by the deployment of a virtual sepsis surveillance program.Results:A total of 566 NPOA sepsis cases were included in this study. Three hundred and thirty-five cases compromised the preintervention arm, whereas the postintervention cohort included 231 cases. After deployment of the virtual sepsis surveillance program, median time to antibiotics improved from 92 to 59 min (p < 0.001). Mortality was reduced from 30% to 21% (p = 0.015).Conclusion:Deployment of a virtual sepsis surveillance program resulted in a decreased time to antibiotics and an overall reduction in NPOA sepsis mortality.

Optimizing planning and design of COVID-19 drive-through mass vaccination clinics by simulation.

Drive-through clinics have previously been utilized in vaccination efforts and are now being more widely adopted for COVID-19 vaccination in different parts of the world by offering many advantages including utilizing existing infrastructure, large daily throughput and enforcing social distancing by default. Successful, effective, and efficient drive-through facilities require a suitable site and keen focus on layout and process design. To demonstrate the role that high fidelity computer simulation can play in planning and design of drive-through mass vaccination clinics, we used multiple integrated discrete event simulation (DES) and agent-based modelling methods. This method using AnyLogic simulation software to aid in planning, design, and implementation of one of the largest and most successful early COVID-19 mass vaccination clinics operated by UCHealth in Denver, Colorado. Simulations proved to be helpful in aiding the optimization of UCHealth drive through mass vaccination clinic design and operations by exposing potential bottlenecks, overflows, and queueing, and clarifying the necessary number of supporting staff. Simulation results informed the target number of vaccinations and necessary processing times for different drive through station set ups and clinic formats. We found that modern simulation tools with advanced visual and analytical capabilities to be very useful for effective planning, design, and operations management of mass vaccination facilities.

Improved antibiotic prescribing using indication-based clinical decision support in the emergency department.

BACKGROUND: Evaluate an indication-based clinical decision support tool to improve antibiotic prescribing in the emergency department. METHODS: Encounters where an antibiotic was prescribed between January 2015 and October 2017 were analyzed before and after the introduction of a clinical decision support tool to improve clinicians' selection of a guideline-approved antibiotic based on clinical indication. Evaluation was conducted on a pre-defined subset of conditions that included skin and soft tissue infections, respiratory infections, and urinary infections. The primary outcome was ordering of a guideline-approved antibiotic prescription at the drug and duration of therapy level. A mixed model following a binomial distribution with a logit link was used to model the difference in proportions of guideline-approved prescriptions before and after the intervention. RESULTS: For conditions evaluated, selection rate of a guideline-approved antibiotic for a given indication improved from 67.1% to 72.2% (P < 0.001). When duration of therapy is included as a criterion, selection of a guideline-approved antibiotic was lower and improved from 24.7% to 31.4% (P < 0.001), highlighting that duration of therapy is often missing at the time of prescribing. The most substantial improvements were seen for pneumonia and pyelonephritis with an increase from 87.9% to 97.5% and 62.8% to 82.6%, respectively. Other significant improvements were seen for abscess, cellulitis, and urinary tract infections. CONCLUSION: Antibiotic prescribing can be improved both at the drug and duration of therapy level using a non-interruptive and indication based-clinical decision support approach. Future research and quality improvement efforts are needed to incorporate duration of therapy guidelines into the antibiotic prescribing process.

Surviving a Medical Malpractice Lawsuit.

Being named in a medical malpractice case is one of the most stressful events in a physician's career. This article reviews the legal system and the medical malpractice process. It details the steps a physician experiences during a medical malpractice case, from being served to the deposition and then to trial and appeals if the physician loses. This article also reviews necessary steps to take in order to proactively participate in one's own defense.

Reduced admission rates and resource utilization for chest pain patients using an electronic health record-embedded clinical pathway in the emergency department.

OBJECTIVES: Assess the impact of an electronic health record (EHR)-embedded clinical pathway (ePATH) as compared to a paper-based clinical decision support tool on outcomes for patients presenting to the emergency department (ED) with suspected acute coronary syndrome (ACS). METHODS: A retrospective, quasi-experimental study using difference-in-differences and interrupted time series specifications to evaluate the impact of an EHR-embedded clinical pathway between April 2013 and July 2017. The intervention was implemented in February 2016 at a large academic tertiary hospital and compared to a local community hospital without the intervention. Eligible patients included adults (>18 years) presenting to the ED with chest pain who had a troponin ordered within 2 hours of arrival and a chest pain-related diagnosis. Patients with initial evidence of acute myocardial infarction were excluded. Primary outcomes included rates of admission and stress testing, hospital length of stay, and occurrence of major adverse cardiac events. RESULTS: On average, there were 170 chest pain visits per month at the intervention site. The frequency of hospital admission (unadjusted 28.2% to 20.9%, P < 0.001) and stress testing (unadjusted 15.8% to 12.7%, P < 0.001) significantly declined after ePATH implementation. After comparison with the comparator site, ePATH was still associated with a significant reduction in hospital admissions (-10.79%, P < 0.001) and stress testing (-6.05%, P < 0.001). Hospital length of stay and rates of major adverse cardiac events did not significantly change. CONCLUSIONS: Implementation of ePATH for patients presenting to the ED with chest pain was associated with safe reductions in hospital admission and stress testing. ePATH appears to be an effective tool for implementing evidence-based guidelines for ED patients with chest pain.

Emergency department front-end split-flow experience: 'physician in intake'.

Background: Emergency department (ED) crowding is a critical problem in the delivery of acute unscheduled care. Many causes are external to the ED, but antiquated operational traditions like triage also contribute. A physician intake model has been shown to be beneficial in a single-centre study, but whether this solution is generalisable is not clear. We aimed to characterise the current state of front-end intake models in a national sample of EDs and quantify their effects on throughput measures. Methods: We performed a descriptive mixed-method analysis of ED process changes implemented by a cross section of self-selecting institutions who reported 2 years of demographic/operational data and structured process descriptions of any 'new front-end processes to replace traditional nurse-based triage'. Results: Among 25 participating institutions, 19 (76%) provided data. While geographically diverse, most were urban, academic adult level 1 trauma centres. Thirteen (68%) reported implementing a new intake process. All were run by attending emergency physicians, and six (46%) also included advanced practice providers. Daily operating hours ranged from 8 to 16 (median 12, IQR 10.25-15.85), and the majority performed labs, imaging and medication administration and directly discharged patients. Considering each site's before-and-after data as matched pairs, physician-driven intake was associated with mean decreases in arrival-to-provider time of 25 min (95% CI 13 to 37), ED length of stay 36 min (95% CI 12 to 59), and left before being seen rate 1.2% (95% CI 0.6% to 1.8%). Conclusions: In this cross section of primarily academic EDs, implementing a physician-driven front-end intake process was feasible and associated with improvement in operational metrics.

Virtual Reality-Based Resilience Programs: Feasibility and Implementation for Inpatient Oncology Nurses.

The high prevalence of compassion fatigue contributes to burnout among oncology nurses. Interventions are needed to support individuals across diverse roles and practice settings in oncology. Virtual reality (VR) is an emerging technology that has been applied in healthcare education and training and is being explored as an intervention to reduce stress and support wellness for healthcare providers. This article reviews recommendations from an implementation project about a VR intervention for oncology nurses.

Advancing evidence-based digital health through an innovative research environment: an academic-industry collaboration case report.

The proliferation of technology enthuses clinicians, researchers, and entrepreneurs to revolutionize health care and care delivery. Intersecting in the field of digital health, academic-industry collaboration (AIC) play a critical role in advancing evidence-based innovations into real world application. AIC models vary, but historically have not included the strong emphasis on rapid research and discovery that the digital health field demands. Due to the voluminous availability of real time patient and client data, academic health centers offer a rich interdisciplinary environment to develop, pilot and evaluate innovations in pragmatic settings. Despite the opportunity between academic health centers and industry to advance digital health innovation through rapid research, limited evidence exists of such collaboration. The purpose of this case report is to examine an AIC facilitating research of new health technologies within an academic health center. This paper presents a case report involving collaboration between diverse technology industry partners and an academic health center that encompasses a university health system (UCHealth), a university technology transfer office (CU Innovations), an innovation center (CARE Innovation Center), and research collaborators (mHealth Impact Laboratory). Case assertions discuss the lessons learned and recommendations when implementing such collaboration in practice. The principal finding is that academic health centers offer an innovative environment for AIC in digital health. Collaborations between academia and industry provide much promise in ensuring health innovations are scientifically sound while meeting the needs of a rapidly evolving technical climate.