Patient and Physician Perspectives on the Use of a Connected Ecosystem for Diabetes Management: International Cross-Sectional Observational Study.

BACKGROUND: Collaboration between people with type 2 diabetes (T2DM) and their health care teams is important for optimal control of the disease and outcomes. Digital technologies could potentially tie together several health care-related devices and platforms into connected ecosystems (CES), but attitudes about CES are unknown. OBJECTIVE: We surveyed convenience samples of patients and physicians to better understand which patient characteristics are associated with higher likelihoods of (1) participating in a potential CES program, as self-reported by patients with T2DM and (2) clinical benefit from participation in a potential CES program, as reported by physicians. METHODS: Adults self-reporting a diagnosis of T2DM and current insulin use (n=197), and 33 physicians whose practices included ≥20% of such patients, were enrolled in the United States, France, and Germany. We surveyed both groups about the likelihood of patient participation in a CES. We then examined the associations between patients' clinical and sociodemographic characteristics and this likelihood. We also described characteristics of patients likely to clinically benefit from CES use, according to physicians. RESULTS: Compared with patients in Germany and France, US patients were younger (mean age 45.3 [SD 11.9] years vs 61.9 [SD 9.2] and 65.8 [SD 9.4] years, respectively), more often female, more highly educated, and more often working full-time. In all, 51 (44.7%) US patients, 16 (36.4%) German patients, and 18 (46.3%) French patients indicated strong interest in a CES program, and 115 (78.7%) reported currently using ≥1 connected device or app. However, physicians believed that only 11.3%-19.2% of their patients were using connected devices or apps to manage their disease. Physicians also reported infrequently recommending or prescribing connected devices to their patients, although ≥80% (n=28) of them thought that a CES could help support their patients in managing their disease. The factors most predictive of patient likelihood of participating in a CES program were cost, inclusion of medication reminders, and linking blood glucose levels to behaviors such as eating and exercise. In all countries, the most common patient expectations for a CES program were that it could help them eat more healthfully, increase their physical activity, increase their understanding of how blood glucose relates to behavior such as exercise and eating, and reduce stress. Physicians thought that newly diagnosed patients, sicker patients-those who had been hospitalized for diabetes, were currently using insulin, or who had any comorbid condition-and patients who were nonadherent to treatment were most likely to benefit from CES use. CONCLUSIONS: In this study, there was a high degree of interest in the future use of CES, although additional education is needed among both patients with T2DM and their physicians to achieve the full potential of such systems to improve self-management and clinical care for the disease.

Influence of Digital Intervention Messaging on Influenza Vaccination Rates Among Adults With Cardiovascular Disease in the United States: Decentralized Randomized Controlled Trial.

BACKGROUND: Seasonal influenza affects 5% to 15% of Americans annually, resulting in preventable deaths and substantial economic impact. Influenza infection is particularly dangerous for people with cardiovascular disease, who therefore represent a priority group for vaccination campaigns. OBJECTIVE: We aimed to assess the effects of digital intervention messaging on self-reported rates of seasonal influenza vaccination. METHODS: This was a randomized, controlled, single-blind, and decentralized trial conducted at individual locations throughout the United States over the 2020-2021 influenza season. Adults with self-reported cardiovascular disease who were members of the Achievement mobile platform were randomized to receive or not receive a series of 6 patient-centered digital intervention messages promoting influenza vaccination. The primary end point was the between-group difference in self-reported vaccination rates at 6 months after randomization. Secondary outcomes included the levels of engagement with the messages and the relationship between vaccination rates and engagement with the messages. Subgroup analyses examined variation in intervention effects by race. Controlling for randomization group, we examined the impact of other predictors of vaccination status, including cardiovascular condition type, vaccine drivers or barriers, and vaccine knowledge. RESULTS: Of the 49,138 randomized participants, responses on the primary end point were available for 11,237 (22.87%; 5575 in the intervention group and 5662 in the control group) participants. The vaccination rate was significantly higher in the intervention group (3418/5575, 61.31%) than the control group (3355/5662, 59.25%; relative risk 1.03, 95% CI 1.004-1.066; P=.03). Participants who were older, more educated, and White or Asian were more likely to report being vaccinated. The intervention was effective among White participants (P=.004) but not among people of color (P=.42). The vaccination rate was 13 percentage points higher among participants who completed all 6 intervention messages versus none, and at least 2 completed messages appeared to be needed for effectiveness. Participants who reported a diagnosis of COVID-19 were more likely to be vaccinated for influenza regardless of treatment assignment. CONCLUSIONS: This personalized, evidence-based digital intervention was effective in increasing vaccination rates in this population of high-risk people with cardiovascular disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT04584645; https://clinicaltrials.gov/ct2/show/NCT04584645.

A novel digital approach to describe real world outcomes among patients with constipation.

Understanding day-to-day variations in symptoms and medication management can be important in describing patient centered outcomes for people with constipation. Patient Generated Health Data (PGHD) from digital devices is a potential solution, but its utility as a tool for describing experiences of people with frequent constipation is unknown. We conducted a virtual, 16-week prospective study of individuals with frequent constipation from an online wellness platform that connects mobile consumer digital devices including wearable monitors capable of passively collecting steps, sleep, and heart rate data. Participants wore a Fitbit monitoring device for the study duration and were administered daily and monthly surveys assessing constipation symptom severity and medication usage. A set of 38 predetermined day-level behavioral activity metrics were computed from minute-level data streams for steps, sleep and heart rate. Mixed effects regression models were used to compare activity metrics between constipation status (irregular or constipated vs. regular day), medication use (medication day vs. non-medication day) and the interaction of medication day with irregular or constipation days, as well as to model likelihood to treat with constipation medications based on daily self-reported symptom severity. Correction for multiple comparisons was performed with the Benjamini-Hochberg procedure for false discovery rate. This study analyzed 1540 enrolled participants with completed daily surveys (mean age 36.6 sd 10.0, 72.8% female, 88.8% Caucasian). Of those, 1293 completed all monthly surveys and 756 had sufficient Fitbit data density for analysis of activity metrics. At a daily-level, 22 of the 38 activity metrics were significantly associated with bowel movement or medication treatment patterns for constipation. Participants were measured to have fewer steps on irregular days compared to regular days (-200 steps, 95% CI [-280, -120]), longer periods of inactivity on constipated days (9.1 min, 95% CI [5.2, 12.9]), reduced total sleep time on irregular and constipated days (-2.4 min, 95% CI [-4.3, -0.4] and -4.0 min, 95% CI [-6.5, -1.4], respectively). Participants reported greater severity of symptoms for bloating, hard stool, difficulty passing, and painful bowel movements on irregular, constipation and medication days compared to regular days with no medication. Interaction analysis of medication days with irregular or constipation days observed small increases in severity compared to non-medication days. Participants were 4.3% (95% CI 3.2, 5.3) more likely to treat with medication on constipated days versus regular. No significant increase in likelihood was observed for irregular days. Daily likelihood to treat increased for each 1-point change in symptom severity of bloating (2.4%, 95% CI [2.0, 2.7]), inability to pass (2.2%, 95% CI [1.4, 3.0]) and incomplete bowel movements (1.3%, 95% CI [0.9, 1.7]). This is the first large scale virtual prospective study describing the association between passively collected PGHD and constipation symptoms and severity at a day-to-day granularity level. Constipation status, irregular or constipated, was associated with a number of activity metrics in steps and sleep, and likelihood to treat with medication increased with increasing severity for a number of constipation symptoms. Given the small magnitude of effect, further research is needed to understand the clinical relevance of these results. PGHD may be useful as a tool for describing real world patient centered experiences for people with constipation.

Quantifying the Impact of Influenza Among Persons With Type 2 Diabetes Mellitus: A New Approach to Determine Medical and Physical Activity Impact.

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM). METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline). RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza. CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Design, Recruitment, and Baseline Characteristics of a Virtual 1-Year Mental Health Study on Behavioral Data and Health Outcomes: Observational Study.

BACKGROUND: Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and progression of mental health conditions. OBJECTIVE: This virtual 1-year observational study was designed with the objective of creating a longitudinal data set combining self-reported health outcomes, health care utilization, and quality of life data with activity tracker and app-based behavioral data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity. METHODS: Individuals who were existing members of an online health community (Achievement, Evidation Health Inc) and were 18 years or older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9, and 12. In this analysis, we report on baseline characteristics of the sample, including mental health disease severity and health care utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and health care utilization. RESULTS: Of the 1304 participants enrolled in the study, 1277 individuals completed the baseline survey and 1068 individuals had sufficient activity tracker data. Mean age was 33 (SD 9) years, and the majority of the study population was female (77.2%, 994/1288) and identified as Caucasian (88.3%, 1137/1288). At baseline, 94.8% (1211/1277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively tracked behavioral traits are associated with more severe forms of anxiety or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep. CONCLUSIONS: These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.

Large-scale influenza vaccination promotion on a mobile app platform: A randomized controlled trial.

While health-care providers have used incentives in an attempt to motivate patients to obtain vaccinations, their effect on vaccination rates has not been systematically evaluated on a large scale. In this study, we examined whether mobile applications may improve population vaccination rates through enhanced communication and incentives education. Our study is the first randomized controlled trial assessing the effect of large-scale messaging combined with individualized incentives on influenza-vaccination rates. In this trial, we delivered messages regarding influenza vaccinations to 50,286 adults, aged 18 through 65, then compared the subsequent vaccination rate, the effectiveness of the message content and the timing. Multiple rounds of messaging occurred over a seven-week period during the 2016 flu season, after which vaccination rates were observed for one week. Participants were randomly assigned to one of three messaging approaches: conspicuous (highlighting the amount of rewards to be received for obtaining a flu shot); generic (promoting vaccinations with no mention of rewards); or no-message. Evidence of vaccination obtainment was indicated by medical and pharmacy claims, augmented by patients self-reporting through the mobile wellness app during the study period. Of the people assigned to receive messaging, 23.2% obtained influenza vaccination, compared to 22.0% of people who obtained vaccination in the no-messaging control arm. This difference was statistically significant (p < 0.01). The research revealed that messaging effectiveness decreased after each successive batch sent, suggesting that most participants responsive to messaging would become activated immediately after receiving one alert. Interestingly, in this large-scale study, there were no significant differences between conspicuous incentives and generic messaging, suggesting an important area for future research. Trial Registration: clinicaltrials.gov identifier: NCT02908893.

Alignment and clustering of breast cancer patients by longitudinal treatment history.

Longitudinal treatment histories may offer valuable information about clinical practice patterns to the clinical researcher as part of data exploration, cohort identification, or discovery of potentially beneficial or harmful practices in the health care community. We present a novel approach to temporal clustering of patient treatment information based on the semantic similarity of longitudinal histories. Using combined breast cancer registry data from two neighboring health care institutions, we constructed a database of longitudinal treatment histories that included surgical procedures, radiation therapy, chemotherapy, and hormone replacement therapy. We then did pair-wise similarity comparisons of treatment histories, and used the similarity measures to cluster patients with machine learning methods. An evaluation of our results found that patients clustered on stage of breast cancer and type of treatment provided. We propose that this approach can be applied towards identification of similar cohorts, and for discovery of novel or anomalous clinical practice patterns.

Local alignment tool for clinical history: temporal semantic search of clinical databases.

Data collected through electronic health records is increasingly used for clinical research purposes. Common research tasks like identifying treatment cohorts based on similar treatment histories, assessing adherence to protocol based care, or determining clinical 'best practices' can be difficult given the complex array of treatment choices and the longitudinal nature of patient care. We present a temporal sequence alignment strategy to find patients with similar treatment histories starting from their initial regimen. The algorithm relies on a user defined threshold heuristic to further reduce the search space in large clinical databases. It also uses an ontology based scoring schema to measure the distance between two clinical treatment histories. We validate the algorithm with a search for patients who are placed on a guideline recommended alternative regimen for HIV after failing initial ideal therapy. Our approach can be used to summarize patterns of care as well as predict outcomes of care.

Extracting cancer quality indicators from electronic medical records: evaluation of an ontology-based virtual medical record approach.

Measuring quality in clinical care is a time-consuming manual task. The vast amounts of clinical data collected through electronic medical records (EMRs) create an opportunity to develop tools that automatically assess quality indicators; however, the diversity of EMR implementations limits the ability to implement general, reusable methods. We evaluate an ontology-based virtual medical record (VMR) approach as a standardized, sharable methodology for defining data abstractions needed for quality of care assessment. Using a set of cancer quality indicators, we conducted a requirements analysis for modeling these abstractions with an OWL-based VMR. We found that the VMR approach needs to be extended to support population-based aggregations of clinical events, models of intended versus completed actions, and models of workflow and delivery systems. Incorporating the patient perspective on quality also requires additional extension of the VMR. We are using these results to create a virtual quality record based on EMR data.

Comparison of ontology-based semantic-similarity measures.

Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. Such a comparison can offer insight on the validity of different approaches. We compared 3 approaches to semantic similarity-metrics (which rely on expert opinion, ontologies only, and information content) with 4 metrics applied to SNOMED-CT. We found that there was poor agreement among those metrics based on information content with the ontology only metric. The metric based only on the ontology structure correlated most with expert opinion. Our results suggest that metrics based on the ontology only may be preferable to information-content-based metrics, and point to the need for more research on validating the different approaches.

Hyponatremia and cerebrovascular spasm in aneurysmal subarachnoid hemorrhage.

BACKGROUND: Hyponatremia develops in approximately a third of patients with aneurysmal subarachnoid hemorrhage (SAH). Studies have been conflicting about the association between hyponatremia and cerebrovascular spasm (CVS). AIMS: To investigate whether hyponatremia can signal the onset of CVS. SETTINGS AND DESIGN: Retrospective chart review of all patients with SAH treated at a tertiary-care university hospital from January to May 2002. MATERIALS AND METHODS: 106 patients were included in the study. Serum sodium levels were recorded from days 1 to 14 of hospitalization. Hyponatremia was defined as serum sodium level<135 meq/l and a fall in sodium level of >4 meq/l from the admission sodium level. The presence of CVS was determined by transcranial doppler sonography. Patients were assigned to one of four groups based on the presence or absence of CVS and hyponatremia. STATISTICAL ANALYSIS: Student's t-test was used for comparison of means. A logistical regression model was constructed and odds ratios (OR) were calculated. RESULTS: 41 patients developed hyponatremia and 44 developed CVS. Among the 41 with hyponatremia, 22 (54%) had evidence of CVS, whereas among the 65 patients without hyponatremia, 22 (34%) had evidence of CVS (P=0.023). Among those with hyponatremia, the mean sodium drop was 7.9 meq/L in those with CVS compared to 7.0 meq/L in those without CVS (P=0.068). More than half of those with hyponatremia and CVS (13/22) developed hyponatremia at least a day before CVS was diagnosed. CONCLUSION: In patients with SAH, hyponatremia is associated with a significantly greater risk of developing CVS and may precede CVS by at least one day.

Assessing and documenting general competencies in otolaryngology resident training programs.

OBJECTIVES: The objectives of this study were to: 1) implement web-based instruments for assessing and documenting the general competencies of otolaryngology resident education, as outlined by the Accreditation Council of Graduate Medical Education (ACGME); and 2) examine the benefit and validity of this online system for measuring educational outcomes and for identifying insufficiencies in the training program as they occur. METHODS: We developed an online assessment system for a surgical postgraduate education program and examined its feasibility, usability, and validity. Evaluations of behaviors, skills, and attitudes of 26 residents were completed online by faculty, peers, and nonphysician professionals during a 3-year period. Analyses included calculation and evaluation of total average performance scores of each resident by different evaluators. Evaluations were also compared with American Board of Otolaryngology-administered in-service examination (ISE) scores for each resident. Convergent validity was examined statistically by comparing ratings among the different evaluator types. RESULTS: Questionnaires and software were found to be simple to use and efficient in collecting essential information. From July 2002 to June 2005, 1,336 evaluation forms were available for analysis. The average score assigned by faculty was 4.31, significantly lower than that by nonphysician professionals (4.66) and residents evaluating peers (4.63) (P < .001), whereas scores were similar between nonphysician professionals and resident peers. Average scores between faculty and nonphysician groups showed correlation in constructs of communication and relationship with patients, but not in those of professionalism and documentation. Correlation was observed in respect for patients but not in medical knowledge between faculty and resident peer groups. Resident ISE scores improved in the third year of the study and demonstrated high correlation with faculty perceptions of medical knowledge (r = 0.65, P = .007). CONCLUSIONS: Compliance for completion of forms was 97%. The system facilitated the educational management of our training program along multiple dimensions. The small perceptual differences among a highly selected group of residents have made the unambiguous validation of the system challenging. The instruments and approach warrant further study. Improvements are likely best achieved in broad consultation among other otolaryngology programs.

A comparison of humanistic qualities among medical students, residents, and faculty physicians in internal medicine.

Humanistic qualities of integrity, respect and compassion are important components of medical education. Studies, however, suggest that students may not perceive their faculty physicians as humanistic. Knowing how the perception of humanistic qualities varies by training level may offer insight on how we teach humanism. In this study, the authors compared humanistic quality scores of fourth-year medical students, internal medicine residents, and attending physicians on a general medicine ward of a teaching hospital. A validated nursing survey to assess humanistic qualities among physicians was distributed to randomly selected nurses on the medicine wards. The survey measured physician relationships with other medical staff, the patient, and family members. Each item was scored on a 5-point Likert scale. Composite scores for physician to staff relationships and physician to patient/family relationships, as well as an overall evaluation score, were compared across levels of physician training. A t test was done to determine statistical significance across training levels. No statistically significant differences were found between internal medicine residents and attending physicians. Subinterns appear to have better perceived qualities of humanism compared with resident and attending physicians. Because resident and attending physicians play an important role in medical education, efforts should be made to improve the perceived humanistic qualities of both resident and attending physicians.