The Association of Frailty and Neighborhood Disadvantage with Emergency Department Visits and Hospitalizations in Older Adults.

BACKGROUND: Risk stratification and population management strategies are critical for providing effective and equitable care for the growing population of older adults in the USA. Both frailty and neighborhood disadvantage are constructs that independently identify populations with higher healthcare utilization and risk of adverse outcomes. OBJECTIVE: To examine the joint association of these factors on acute healthcare utilization using two pragmatic measures based on structured data available in the electronic health record (EHR). DESIGN: In this retrospective observational study, we used EHR data to identify patients aged ≥ 65 years at Atrium Health Wake Forest Baptist on January 1, 2019, who were attributed to affiliated Accountable Care Organizations. Frailty was categorized through an EHR-derived electronic Frailty Index (eFI), while neighborhood disadvantage was quantified through linkage to the area deprivation index (ADI). We used a recurrent time-to-event model within a Cox proportional hazards framework to examine the joint association of eFI and ADI categories with healthcare utilization comprising emergency visits, observation stays, and inpatient hospitalizations over one year of follow-up. KEY RESULTS: We identified a cohort of 47,566 older adults (median age = 73, 60% female, 12% Black). There was an interaction between frailty and area disadvantage (P = 0.023). Each factor was associated with utilization across categories of the other. The magnitude of frailty's association was larger than living in a disadvantaged area. The highest-risk group comprised frail adults living in areas of high disadvantage (HR 3.23, 95% CI 2.99-3.49; P < 0.001). We observed additive effects between frailty and living in areas of mid- (RERI 0.29; 95% CI 0.13-0.45; P < 0.001) and high (RERI 0.62, 95% CI 0.41-0.83; P < 0.001) neighborhood disadvantage. CONCLUSIONS: Considering both frailty and neighborhood disadvantage may assist healthcare organizations in effectively risk-stratifying vulnerable older adults and informing population management strategies. These constructs can be readily assessed at-scale using routinely collected structured EHR data.

Cardiovascular health assessment in routine cancer follow-up in community settings: survivor risk awareness and perspectives.

BACKGROUND: Guidelines recommend cardiovascular risk assessment and counseling for cancer survivors. For effective implementation, it is critical to understand survivor cardiovascular health (CVH) profiles and perspectives in community settings. We aimed to (1) Assess survivor CVH profiles, (2) compare self-reported and EHR-based categorization of CVH factors, and (3) describe perceptions regarding addressing CVH during oncology encounters. METHODS: This cross-sectional analysis utilized data from an ongoing NCI Community Oncology Research Program trial of an EHR heart health tool for cancer survivors (WF-1804CD). Survivors presenting for routine care after potentially curative treatment recruited from 8 oncology practices completed a pre-visit survey, including American Heart Association Simple 7 CVH factors (classified as ideal, intermediate, or poor). Medical record abstraction ascertained CVD risk factors and cancer characteristics. Likert-type questions assessed desired discussion during oncology care. RESULTS: Of 502 enrolled survivors (95.6% female; mean time since diagnosis = 4.2 years), most had breast cancer (79.7%). Many survivors had common cardiovascular comorbidities, including high cholesterol (48.3%), hypertension or high BP (47.8%) obesity (33.1%), and diabetes (20.5%); 30.5% of survivors received high cardiotoxicity potential cancer treatment. Less than half had ideal/non-missing levels for physical activity (48.0%), BMI (18.9%), cholesterol (17.9%), blood pressure (14.1%), healthy diet (11.0%), and glucose/ HbA1c (6.0%). While > 50% of survivors had concordant EHR-self-report categorization for smoking, BMI, and blood pressure; cholesterol, glucose, and A1C were unknown by survivors and/or missing in the EHR for most. Most survivors agreed oncology providers should talk about heart health (78.9%). CONCLUSIONS: Tools to promote CVH discussion can fill gaps in CVH knowledge and are likely to be well-received by survivors in community settings. TRIAL REGISTRATION: NCT03935282, Registered 10/01/2020.

Child Opportunity Index and Pediatric Intensive Care Outcomes: A Multicenter Retrospective Study in the United States.

OBJECTIVES: To evaluate for associations between a child's neighborhood, as categorized by Child Opportunity Index (COI 2.0), and 1) PICU mortality, 2) severity of illness at PICU admission, and 3) PICU length of stay (LOS). DESIGN: Retrospective cohort study. SETTING: Fifteen PICUs in the United States. PATIENTS: Children younger than 18 years admitted from 2019 to 2020, excluding those after cardiac procedures. Nationally-normed COI category (very low, low, moderate, high, very high) was determined for each admission by census tract, and clinical features were obtained from the Virtual Pediatric Systems LLC (Los Angeles, CA) data from each site. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 33,901 index PICU admissions during the time period, median patient age was 4.9 years and PICU mortality was 2.1%. There was a higher percentage of admissions from the very low COI category (27.3%) than other COI categories (17.2-19.5%, p < 0.0001). Patient admissions from the high and very high COI categories had a lower median Pediatric Index of Mortality 3 risk of mortality (0.70) than those from the very low, low, and moderate COI groups (0.71) ( p < 0.001). PICU mortality was lowest in the very high (1.7%) and high (1.9%) COI groups and highest in the moderate group (2.5%), followed by very low (2.3%) and low (2.2%) ( p = 0.001 across categories). Median PICU LOS was between 1.37 and 1.50 days in all COI categories. Multivariable regression revealed adjusted odds of PICU mortality of 1.30 (95% CI, 0.94-1.79; p = 0.11) for children from a very low versus very high COI neighborhood, with an odds ratio [OR] of 0.996 (95% CI, 0.993-1.00; p = 0.05) for mortality for COI as an ordinal value from 0 to 100. Children without insurance coverage had an OR for mortality of 3.58 (95% CI, 2.46-5.20; p < 0.0001) as compared with those with commercial insurance. CONCLUSIONS: Children admitted to a cohort of U.S. PICUs were often from very low COI neighborhoods. Children from very high COI neighborhoods had the lowest risk of mortality and observed mortality; however, odds of mortality were not statistically different by COI category in a multivariable model. Children without insurance coverage had significantly higher odds of PICU mortality regardless of neighborhood.

Endometrial cancer survivors' perceptions of their cardiovascular disease risk (results from WF-1804CD AH-HA).

OBJECTIVE: Despite considerable burden of cardiovascular disease (CVD), data on endometrial cancer survivors' CVD perceptions are lacking. We assessed survivors' perspectives on addressing CVD risk during oncology care. METHODS: This cross-sectional analysis utilized data from an ongoing trial of an EHR heart health tool (R01CA226078 & UG1CA189824) conducted through the NCI Community Oncology Research Program (NCORP, WF-1804CD). Endometrial cancer survivors post-potentially curative treatment were recruited from community practices and completed a pre-visit baseline survey, including American Heart Association Simple 7 CVD factors. Likert-type questions assessed confidence in understanding CVD risk, CVD risk perception, and desired discussion during oncology care. Medical record abstraction ascertained data on CVD and cancer characteristics. RESULTS: Survivors (N = 55, median age = 62; 62% 0-2 years post-diagnosis) were predominately white, non-Hispanic (87%). Most agreed/strongly agreed heart disease poses a risk to their health (87%) and oncology providers should talk to patients about heart health (76%). Few survivors reported smoking (12%) but many had poor/intermediate values for blood pressure (95%), body mass index (93%), fasting glucose/A1c (60%), diet (60%), exercise (47%) and total cholesterol (53%). 16% had not seen a PCP in the last year; these survivors were more likely to report financial hardship (22% vs 0%; p = 0.02). Most reported readiness to take steps to maintain or improve heart health (84%). CONCLUSIONS: Discussions of CVD risk during routine oncology care are likely to be well received by endometrial cancer survivors. Strategies are needed to implement CVD risk assessment guidelines and to enhance communication and referrals with primary care. Clinical Trials #: NCT03935282.

Impact of the COVID-19 Pandemic on Diabetes Care Among a North Carolina Patient Population.

In this study, researchers reviewed electronic health record data to assess whether the coronavirus disease 2019 pandemic was associated with disruptions in diabetes care processes of A1C testing, retinal screening, and nephropathy evaluation among patients receiving care with Wake Forest Baptist Health in North Carolina. Compared with the pre-pandemic period, they found an increase of 13-21 percentage points in the proportion of patients delaying diabetes care for each measure during the pandemic. Alarmingly, delays in A1C testing were greatest for individuals with the most severe disease and may portend an increase in diabetes complications.

Sex and race differences in safety and effectiveness of the HEART pathway accelerated diagnostic protocol for acute chest pain.

BACKGROUND: The HEART Pathway is an accelerated diagnostic protocol for Emergency Department patients with possible acute coronary syndrome. The objective was to compare the safety and effectiveness of the HEART Pathway among women vs men and whites vs non-whites. METHODS: A subgroup analysis of the HEART Pathway Implementation Study was conducted. Adults with chest pain were accrued from November 2013 to January 2016 from 3 Emergency Departments in North Carolina. The primary outcomes were death and myocardial infarction (MI) and hospitalization rates at 30 days. Logistic regression evaluated for interactions of accelerated diagnostic protocol implementation with sex or race and changes in outcomes within subgroups. RESULTS: A total of 8,474 patients were accrued, of which 53.6% were female and 34.0% were non-white. The HEART Pathway identified 32.6% of females as low-risk vs 28.5% of males (P = 002) and 35.6% of non-whites as low-risk vs 28.0% of whites (P < .0001). Among low-risk patients, death or MI at 30 days occurred in 0.4% of females vs 0.5% of males (P = .70) and 0.5% of non-whites vs 0.3% of whites (P = .69). Hospitalization at 30 days was reduced by 6.6% in females (aOR: 0.74, 95% CI: 0.64-0.85), 5.1% in males (aOR: 0.87, 95% CI: 0.75-1.02), 8.6% in non-whites (aOR: 0.72, 95% CI: 0.60-0.86), and 4.5% in whites (aOR: 0.83, 95% CI: 0.73-0.94). Interactions were not significant. CONCLUSION: Women and non-whites are more likely to be classified as low-risk by the HEART Pathway. HEART Pathway implementation is associated with decreased hospitalizations and a very low death and MI rate among low-risk patients regardless of sex or race.

Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study.

BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. METHODS: A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children's hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children's Hospital, Cincinnati, OH, Seattle Children's Hospital, Seattle, WA, and Children's Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. RESULTS: Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. CONCLUSIONS: Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth.

HEART Pathway Implementation Safely Reduces Hospitalizations at One Year in Patients With Acute Chest Pain.

STUDY OBJECTIVE: We determine whether implementation of the HEART (History, ECG, Age, Risk Factors, Troponin) Pathway is safe and effective in emergency department (ED) patients with possible acute coronary syndrome through 1 year of follow-up. METHODS: A preplanned analysis of 1-year follow-up data from a prospective pre-post study of 8,474 adult ED patients with possible acute coronary syndrome from 3 US sites was conducted. Patients included were aged 21 years or older, evaluated for possible acute coronary syndrome, and without ST-segment elevation myocardial infarction. Accrual occurred for 12 months before and after HEART Pathway implementation, from November 2013 to January 2016. The HEART Pathway was integrated into the electronic health record at each site as an interactive clinical decision support tool. After integration, ED providers prospectively used the HEART Pathway to identify patients with possible acute coronary syndrome as low risk (appropriate for early discharge without stress testing or angiography) or nonlow risk (appropriate for further inhospital evaluation). Safety (all-cause death and myocardial infarction) and effectiveness (hospitalization) at 1 year were determined from health records, insurance claims, and death index data. RESULTS: Preimplementation and postimplementation cohorts included 3,713 and 4,761 patients, respectively. The HEART Pathway identified 30.7% of patients as low risk; 97.5% of them were free of death and myocardial infarction within 1 year. Hospitalization at 1 year was reduced by 7.0% in the postimplementation versus preimplementation cohort (62.1% versus 69.1%; adjusted odds ratio 0.70; 95% confidence interval 0.63 to 0.78). Rates of death or myocardial infarction at 1 year were similar (11.6% versus 12.4%; adjusted odds ratio 1.00; 95% confidence interval 0.87 to 1.16). CONCLUSION: HEART Pathway implementation was associated with decreased hospitalizations and low adverse event rates among low-risk patients at 1-year follow-up.

Identification of very low-risk acute chest pain patients without troponin testing.

BACKGROUND: The HEART Pathway combines a History ECG Age Risk factor (HEAR) score and serial troponins to risk stratify patients with acute chest pain. However, it is unclear whether patients with HEAR scores of <1 require troponin testing. The objective of this study is to measure the major adverse cardiac event (MACE) rate among patients with <1 HEAR scores and determine whether serial troponin testing is needed to achieve a miss rate <1%. METHODS: A secondary analysis of the HEART Pathway Implementation Study was conducted. HEART Pathway risk assessments (HEAR scores and serial troponin testing at 0 and 3 hours) were completed by the providers on adult patients with chest pain from three US sites between November 2014 and January 2016. MACE (composite of death, myocardial infarction (MI) and coronary revascularisation) at 30 days was determined. The proportion of patients with HEAR scores of <1 diagnosed with MACE within 30 days was calculated. The impact of troponin testing on patients with HEAR scores of <1 was determined using Net Reclassification Improvement Index (NRI). RESULTS: Providers completed HEAR assessments on 4979 patients and HEAR scores<1 occurred in 9.0% (447/4979) of patients. Among these patients, MACE at 30 days occurred in 0.9% (4/447; 95% CI 0.2% to 2.3%) with two deaths, two MIs and 0 revascularisations. The sensitivity and negative predictive value for MACE in the HEAR <1 was 97.8% (95%CI 94.5% to 99.4%) and 99.1% (95% CI 97.7% to 99.8%), respectively, and were not improved by troponin testing. Troponin testing in patients with HEAR <1 correctly reclassified two patients diagnosed with MACE, and was elevated among seven patients without MACE yielding an NRI of 0.9% (95%CI -0.7 to 2.4%). CONCLUSION: These data suggest that patients with HEAR scores of 0 and 1 represent a very low-risk group that may not require troponin testing to achieve a missed MACE rate <1%. Trial registration number NCT02056964.

Safely Identifying Emergency Department Patients With Acute Chest Pain for Early Discharge.

BACKGROUND: The HEART Pathway (history, ECG, age, risk factors, and initial troponin) is an accelerated diagnostic protocol designed to identify low-risk emergency department patients with chest pain for early discharge without stress testing or angiography. The objective of this study was to determine whether implementation of the HEART Pathway is safe (30-day death and myocardial infarction rate <1% in low-risk patients) and effective (reduces 30-day hospitalizations) in emergency department patients with possible acute coronary syndrome. METHODS: A prospective pre-post study was conducted at 3 US sites among 8474 adult emergency department patients with possible acute coronary syndrome. Patients included were ≥21 years old, investigated for possible acute coronary syndrome, and had no evidence of ST-segment-elevation myocardial infarction on ECG. Accrual occurred for 12 months before and after HEART Pathway implementation from November 2013 to January 2016. The HEART Pathway accelerated diagnostic protocol was integrated into the electronic health record at each site as an interactive clinical decision support tool. After accelerated diagnostic protocol integration, ED providers prospectively used the HEART Pathway to identify patients with possible acute coronary syndrome as low risk (appropriate for early discharge without stress testing or angiography) or non-low risk (appropriate for further in-hospital evaluation). The primary safety and effectiveness outcomes, death, and myocardial infarction (MI) and hospitalization rates at 30 days were determined from health records, insurance claims, and death index data. RESULTS: Preimplementation and postimplementation cohorts included 3713 and 4761 patients, respectively. The HEART Pathway identified 30.7% as low risk; 0.4% of these patients experienced death or MI within 30 days. Hospitalization at 30 days was reduced by 6% in the postimplementation versus preimplementation cohort (55.6% versus 61.6%; adjusted odds ratio, 0.79; 95% CI, 0.71-0.87). During the index visit, more MIs were detected in the postimplementation cohort (6.6% versus 5.7%; adjusted odds ratio, 1.36; 95% CI, 1.12-1.65). Rates of death or MI during follow-up were similar (1.1% versus 1.3%; adjusted odds ratio, 0.88; 95% CI, 0.58-1.33). CONCLUSIONS: HEART Pathway implementation was associated with decreased hospitalizations, increased identification of index visit MIs, and a very low death and MI rate among low-risk patients. These findings support use of the HEART Pathway to identify low-risk patients who can be safely discharged without stress testing or angiography. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov . Unique identifier: NCT02056964.

Holiday Discharges Are Associated with Higher 30-Day General Internal Medicine Hospital Readmissions at an Academic Medical Center.

OBJECTIVE: Academic medical centers face unique challenges in educating physician trainees in effective discharge practices to prevent readmissions. Meanwhile, residents must handle high workloads coupled with frequent rotations to different services. This study aimed to determine whether daily service census, service turnover, time of discharge, and day of discharge increase the risk of 30-day readmission. METHODS: All of the discharges from two academic general internal medicine teaching services between October 1, 2013 and September 30, 2014 were included in this observational data analysis. Variables were fit to a 30-day, all-cause readmission outcome using multiple logistic regression with inverse probability of treatment weighting and multiple imputations with chained equations. The following potential confounding variables were included in the model: health system utilization, demographics, laboratory values, and comorbidities. RESULTS: Among 1935 total discharges, 258 patients (13.3%) were readmitted within 30 days of the index discharge. Turnover, service census, weekend discharge, and time of discharge were not significantly associated with the risk of readmission. Patients discharged during holiday periods had higher odds of readmission (odds ratio 2.56, 95% confidence interval 2.01-3.25), whereas patients discharged on an intern switch day had lower odds of readmission (odds ratio 0.33, 95% confidence interval 0.27-0.41). CONCLUSIONS: Patients who are discharged during holiday periods are at a higher risk of readmission after adjusting for potential confounders. These results also suggest that discharge on an intern switch day had a protective effect on readmission. Further work is needed to examine whether these findings can be replicated, and, if confirmed, to determine to what extent these associations are causal.

Nutritional markers may identify patients with greater risk of re-admission after geriatric hip fractures.

PURPOSE: Osteoporotic hip fractures are increasing in prevalence with the growing elderly population. Morbidity and mortality remain high following osteoporotic hip fractures despite advances in medical and surgical treatments. The associated costs and medical burdens are increased with a re-admission following hip fracture treatment. This study sought to identify demographic and clinical values that may be a predictive model for 30-day re-admission risk following operative management of an isolated hip fracture. METHODS: Between January 1, 2013 and April 30, 2015 all patients admitted to a single academic medical centre for treatment of a hip fracture were reviewed. Candidate variables included standard demographics, common laboratory values, and markers of comorbid conditions and nutrition status. A 30-day, all-cause re-admission model was created utilizing multivariate logistic regression. RESULTS: A total of 607 patients with hip fractures were identified and met the inclusion criteria; of those patients, 67 were re-admitted within 30 days. Univariate analysis indicates that the re-admission group had more comorbidities (p < 0.001) and lower albumin (p = 0.038) and prealbumin (p < 0.001). The final, reduced model contained 12 variables and incorporated four out of five nutritional makers with an internally, cross-validated C-statistic of 0.811 (95% CI: 0.754, 0.867). CONCLUSION: Our results indicate that specific nutritional laboratory markers at the index admission may identify patients that have a greater risk of re-admission after hip fracture. This model identifies potentially modifiable risk factors and may allow orthogeriatricians to better educate patients and better treat post-operative nutritional status and care.

Association of glucagon-like peptide-1 receptor agonist use and rates of acute myocardial infarction, stroke and overall mortality in patients with type 2 diabetes mellitus in a large integrated health system.

AIMS: To assess the potential impact of glucagon-like peptide-1 receptor agonist (GLP-1RA) exposure on cardiovascular disease (CVD) and mortality outcomes in patients with type 2 diabetes (T2D), using a large retrospective cohort. RESEARCH DESIGN AND METHODS: Patients who had T2D between 2005 and 2014 (N = 105 862) were identified from the electronic health record system at Cleveland Clinic using a validated electronic phenotype. A time-dependent, Cox, multiple regression analysis was used to assess the association between GLP-1RA exposure and risk of acute myocardial infarction (AMI), stroke/cerebrovascular accident (CVA), and overall mortality, as well as the composite of all three outcomes. The findings were further evaluated by assessing the effect of GLP-1RAs on the same variables in patients with and without prior CVD. The model adjusted for differences in demographic information, hypertension, laboratory/vital signs, history of outcomes, and T2D medications. RESULTS: There were significantly lower rates of AMI (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.65 to 0.99; P = .045), CVA (HR 0.82, 95% CI 0.74 to 0.91, P < .001), overall mortality (HR 0.48, 95% CI 0.41 to 0.57; P < .001), and the composite outcome (HR 0.82, 95% CI 0.74 to 0.91; P < .002) during the consolidated time that patients were exposed to GLP-1RAs compared to corresponding rates during intervals without GLP-1RA exposure. GLP-1RA treatment was associated with a significant decrease in CVA, mortality, and the composite outcome in patients with and without established CVD, not significantly affecting AMI in these subgroups. CONCLUSIONS: GLP-1RA exposure was found to be associated with a reduction in the risk of cardiovascular events observed and overall mortality among patients with T2D with and without established CVD, after adjusting for potential confounders.

Patient Perspectives on a Targeted Text Messaging Campaign to Encourage Screening for Diabetes: Qualitative Study.

BACKGROUND: A sizeable proportion of prediabetes and diabetes cases among adults in the United States remain undiagnosed. Patient-facing clinical decision support (CDS) tools that leverage electronic health records (EHRs) have the potential to increase diabetes screening. Given the widespread mobile phone ownership across diverse groups, text messages present a viable mode for delivering alerts directly to patients. The use of unsolicited text messages to offer hemoglobin A1c (HbA1c) screening has not yet been studied. It is imperative to gauge perceptions of "cold texts" to ensure that information and language are optimized to promote engagement with text messages that affect follow-through with health behaviors. OBJECTIVE: This study aims to gauge the perceptions of and receptiveness to text messages to inform content that would facilitate engagement with text messages intended to initiate a mobile health (mHealth) intervention for targeted screening. Messages were designed to invite those not already diagnosed with diabetes to make a decision to take part in HbA1c screening and walk them through the steps required to perform the behavior based solely on an automated text exchange. METHODS: In total, 6 focus groups were conducted at Wake Forest Baptist Health (WFBH) between September 2019 and February 2020. The participants were adult patients without diabetes who had completed an in-person visit at the Family and Community Medicine Clinic within the previous year. We displayed a series of text messages and asked the participants to react to the message content and suggest improvements. Content was deductively coded with respect to the Health Belief Model (HBM) and inductively coded to identify other emergent themes that could potentially impact engagement with text messages. RESULTS: Participants (N=36) were generally receptive to the idea of receiving a text-based alert for HbA1c screening. Plain language, personalization, and content, which highlighted perceived benefits over perceived susceptibility and perceived severity, were important to participants' understanding of and receptiveness to messages. The patient-physician relationship emerged as a recurring theme in which patients either had a desire or held an assumption that their provider would be working behind the scenes throughout each step of the process. Participants needed further clarification to understand the steps involved in following through with HbA1c screening and receiving results. CONCLUSIONS: Our findings suggest that patients may be receptive to text messages that alert them to a risk of having an elevated HbA1c in direct-to-patient alerts that use cold texting. Using plain and positive language, integrating elements of personalization, and defining new processes clearly were identified by participants as modifiable content elements that could act as facilitators that would help overcome barriers to engagement with these messages. A patient's relationship with their provider and the financial costs associated with texts and screening may affect receptiveness and engagement in this process.

Incidence, severity and detection of blood pressure and heart rate perturbations in postoperative ward patients after noncardiac surgery.

STUDY OBJECTIVE: We sought to determine changes in continuous mean and systolic blood pressure and heart rate in a cohort of non-cardiac surgical patients recovering on the postoperative ward. Furthermore, we estimated the proportion of vital signs changes that would remain undetected with intermittent vital signs checks. DESIGN: Retrospective cohort. SETTING: Post-operative general ward. PATIENTS: 14,623 adults recovering from non-cardiac surgical procedures. INTERVENTIONS & MEASUREMENTS: Using a wireless, noninvasive monitor, we recorded postoperative blood pressure and heart rate at 15-s intervals and encouraged nursing intervention as clinically indicated. MAIN RESULTS: 7% of our cohort of 14,623 patients spent >15 sustained minutes with a MAP <65 mmHg, and 23% had MAP <75 mmHg for 15 sustained minutes. Hypertension was more common, with 67% of patients spending at least 60 sustained minutes with MAP >110 mmHg. Systolic pressures <90 mmHg were present for 15 sustained minutes in about a fifth of all patients, and 40% of patients had pressures >160 mmHg sustained for 30 min. 40% of patients were tachycardic with heart rates >100 beats/min for at least continuous 15 min and 15% of patients were bradycardic at a threshold of <50 beats/min for 5 sustained minutes. Conventional vital sign assessments at 4-h intervals would have missed 54% of mean pressure episodes <65 mmHg sustained >15 min, 20% of episodes of mean pressures >130 mmHg sustained >30 min, 36% of episodes of heart rate > 120 beats/min sustained <10 min, and 68% of episodes of heart rate sustained <40 beats per minute for >3 min. CONCLUSIONS: Substantial hemodynamic disturbances persisted despite implementing continuous portable ward monitoring coupled with nursing alarms and interventions. A significant proportion of these changes would have gone undetected using traditional intermittent monitoring. Better understanding of effective responses to alarms and appropriate interventions on hospital wards remains necessary.

Using Electronic Health Records for the Learning Health System: Creation of a Diabetes Research Registry.

Electronic health records (EHRs) were originally developed for clinical care and billing. As such, the data are not collected, organized, and curated in a fashion that is optimized for secondary use to support the Learning Health System. Population health registries provide tools to support quality improvement. These tools are generally integrated with the live EHR, are intended to use a minimum of computing resources, and may not be appropriate for some research projects. Researchers may require different electronic phenotypes and variable definitions from those typically used for population health, and these definitions may vary from study to study. Establishing a formal registry that is mapped to the Observation Medical Outcomes Partnership common data model provides an opportunity to add custom mappings and more easily share these with other institutions. Performing preprocessing tasks such as data cleaning, calculation of risk scores, time-to-event analysis, imputation, and transforming data into a format for statistical analyses will improve efficiency and make the data easier to use for investigators. Research registries that are maintained outside the EHR also have the luxury of using significant computational resources without jeopardizing clinical care data. This paper describes a virtual Diabetes Registry at Atrium Health Wake Forest Baptist and the plan for its continued development.

Creating learning health systems and the emerging role of biomedical informatics.

INTRODUCTION: The nature of information used in medicine has changed. In the past, we were limited to routine clinical data and published clinical trials. Today, we deal with massive, multiple data streams and easy access to new tests, ideas, and capabilities to process them. Whereas in the past getting information for decision-making was a challenge, now, it is how to analyze, evaluate and prioritize all that is readily available through the multitude of data-collecting devices. Clinicians must become adept with the tools needed to deal with the era of big data, requiring a major change in how we learn to make decisions. Major change is often met with resistance and questions about value. A Learning Health System is an enabler to encourage the development of such tools and demonstrate value in improved decision-making. METHODS: We describe how we are developing a Biomedical Informatics program to help our medical institution's evolution as an academic Learning Health System, including strategy, training for house staff and examples of the role of informatics from operations to research. RESULTS: We described an array of learning health system implementations and educational programs to improve healthcare and prepare a cadre of physicians with basic information technology skills. The programs have been well accepted with, for example, increasing interest and enrollment in the educational programs. CONCLUSIONS: We are now in an era when large volumes of a wide variety of data are readily available. The challenge is not so much in the acquisition of data, but in assessing the quality, relevance and value of the data. The data we can get may not be the data we need. In the past, sources of data were limited, and trial results published in journals were the major source of evidence for decision making. The advent of powerful analytics systems has changed the concept of evidence. Clinicians will have to develop the skills necessary to work in the era of big data. It is not reasonable to expect that all clinicians will also be data scientists. However, understanding the role of AI and predictive analytics, and how to apply them, will become progressively more important. Programs such as the one being implemented at Wake Forest fill that need.

Low Peak Inspiratory Flow Rates are Common Among COPD Inpatients and are Associated with Increased Healthcare Resource Utilization: A Retrospective Cohort Study.

Background: Patients with chronic obstructive pulmonary disease (COPD) can have low peak inspiratory flow (PIF), especially after hospitalization for acute exacerbation of COPD (AECOPD). Purpose: To characterize patients hospitalized for AECOPD, and to assess the prevalence of low PIF, changes in PIF after hospitalization, and the association of low PIF with healthcare resource utilization (HRU) outcomes. Patients and Methods: A retrospective cohort study was conducted using electronic health record data of hospitalized COPD patients in the Wake Forest Baptist Health system (01/01/2017 through 06/30/2020). Patients with a first eligible AECOPD hospitalization (index hospitalization) who were discharged before 05/31/2020 were included. PIF was measured using the In-Check DIAL™ at both medium-low resistance (R-2) and high resistance (R-5) during the index hospitalization. For R-2 and R-5, PIF was divided into low PIF (< 60 L/min; < 30 L/min) and high PIF (≥ 60 L/min; ≥ 30 L/min) groups. The primary outcome was the prevalence of low PIF. The stability of PIF after hospitalization was described. Adjusted regression models evaluated associations between low PIF and subsequent 30-day readmissions, 90-day readmissions, and HRU outcomes, including hospitalizations, emergency department visits, inpatient days, and intensive care unit (ICU) days. Results: In total, 743 patients with PIF measured at R-2 and R-5 during a AECOPD hospitalization were included. The prevalence of low PIF was 56.9% at R-2 and 14.7% at R-5. PIF values were relatively stable after hospitalization. Adjusted analyses showed significant increases in HRU (all-cause hospitalizations [31%], COPD hospitalizations [33%], COPD inpatient days [46%], and COPD ICU days [24%]) during the follow-up period among patients with low PIF (< 60 L/min) at R-2. The 30- and 90-day readmission risks were similar between patients with low PIF and high PIF. Conclusion: Low PIF is common among patients hospitalized for AECOPD, relatively stable after hospital discharge, and associated with increased HRU.

Characteristics of Adult Primary Care Patients Who Use the Patient Portal: A Cross-Sectional Analysis.

BACKGROUND: The patient portal allows patients to engage with their health care team beyond the clinical encounter. While portals can improve patient outcomes, there may be disparities in which patients access the portal by sociodemographic factors. Understanding the characteristics of patients who use the portal could help design future interventions to expand portal adoption. OBJECTIVES: This study aimed to (1) examine the socioeconomic factors, comorbid conditions, and health care utilization among patients of a large academic primary care network who are users and non-users of the patient portal; and (2) describe the portal functions most frequently utilized. METHODS: We included all adult patients at Atrium Health Wake Forest Baptist who had at least two primary care visits between 2018 and 2019. Patients' demographics, comorbidities, health care utilization, and portal function usage were extracted from the electronic health record and merged with census data (income, education, and unemployment) from the American Community Survey. A myWakeHealth portal user was defined as a patient who used a bidirectional portal function at least once during the study period. We used multivariable logistic regression to determine which patient characteristics were independently associated with being a portal user. RESULTS: Of the 178,720 patients who met inclusion criteria, 32% (N = 57,122) were users of myWakeHealth. Compared to non-users, users were more likely to be 18 to 64 years of age, female, non-Hispanic White, married, commercially insured, have higher disease burden, and have lower health care utilization. Patients residing in areas with the highest educational attainment had 51% higher odds of being a portal user than the lowest (p <0.001). Among portal users, the most commonly used function was messaging clinic providers. CONCLUSION: We found that patient demographics and area socioeconomic factors were associated with patient portal adoption. These findings suggest that efforts to improve portal adoption should be targeted at vulnerable patients.