Serological survey to estimate SARS-CoV-2 infection and antibody seroprevalence at a large public university: A cross-sectional study.

OBJECTIVE: This study investigated the seroprevalence of SARS-CoV-2 antibodies among adults over 18 years. DESIGN: Prospective cohort study. SETTINGS: A large public university. PARTICIPANTS: This study took volunteers over 5 days and recruited 1064 adult participants. PRIMARY OUTCOME MEASURES: Seroprevalence of SARS-CoV-2-specific antibodies due to previous exposure to SARS-CoV-2 and/or vaccination. RESULTS: The seroprevalence of the antireceptor binding domain (RBD) antibody was 90% by a lateral flow assay and 88% by a semiquantitative chemiluminescent immunoassay. The seroprevalence for antinucleocapsid was 20%. In addition, individuals with previous natural COVID-19 infection plus vaccination had higher anti-RBD antibody levels compared with those who had vaccination only or infection only. Individuals who had a breakthrough infection had the highest anti-RBD antibody levels. CONCLUSION: Accurate estimates of the cumulative incidence of SARS-CoV-2 infection can inform the development of university risk mitigation protocols such as encouraging booster shots, extending mask mandates or reverting to online classes. It could help us to have clear guidance to act at the first sign of the next surge as well, especially since there is a surge of COVID-19 subvariant infections.

Prospective sampling bias in COVID-19 recruitment methods: experimental evidence from a national randomized survey testing recruitment materials.

BACKGROUND: In the context of the COVID-19 pandemic, social science research has required recruiting many prospective participants. Many researchers have explicitly taken advantage of widespread public interest in COVID-19 to advertise their studies. Leveraging this interest, however, risks creating unrepresentative samples due to differential interest in the topic. In this study, we investigate the design of survey recruitment materials with respect to the views of resultant participants. METHODS: Within a pan-Canadian survey (stratified random mail sampling, n = 1969), the design of recruitment invitations to prospective respondents was experimentally varied, with some prospective respondents receiving COVID-specific recruitment messages and others receiving more general recruitment messages (described as research about health and health policy). All respondents participated, however, in the same survey, allowing comparison of both demographic and attitudinal features between these groups. RESULTS: Respondents recruited via COVID-19 specific postcards were more likely to agree that COVID-19 is serious and believe that they were likely to contract COVID-19 compared to non-COVID respondents (odds = 0.71, p = 0.04; odds = 0.74, p = 0.03 respectively; comparing health to COVID-19 framed respondents). COVID-19 specific respondents were more likely to disagree that the COVID-19 threat was exaggerated compared to the non-COVID survey respondents (odds = 1.44, p = 0.02). CONCLUSIONS: COVID-19 recruitment framing garnered a higher response rate, as well as a sample with greater concern about coronavirus risks and impacts than respondents who received more neutrally framed recruitment materials.

Using Automation, Prioritization, and Collaboration to Manage a COVID-19 Case Surge in Maricopa County, Arizona, 2020.

During summer 2020, the Maricopa County Department of Public Health (MCDPH) responded to a surge in COVID-19 cases. We used internet-based platforms to automate case notifications, prioritized investigation of cases more likely to have onward transmission or severe COVID-19 based on available preinvestigation information, and partnered with Arizona State University (ASU) to scale investigation capacity. We assessed the speed of automated case notifications and accuracy of our investigation prioritization criteria. Timeliness of case notification-the median time between receipt of a case report at MCDPH and first case contact-improved from 11 days to <1 day after implementation of automated case notification. We calculated the sensitivity and positive predictive value (PPV) of the investigation prioritization system by applying our high-risk prioritization criteria separately to data available pre- and postinvestigation to determine whether a case met these criteria preinvestigation, postinvestigation, or both. We calculated the sensitivity as the percentage of cases classified postinvestigation as high risk that had also been classified as high risk preinvestigation. We calculated PPV as the percentage of all cases deemed high risk preinvestigation that remained so postinvestigation. During June 30 to July 31, 2020, a total of 55 056 COVID-19 cases with an associated telephone number (94% of 58 570 total cases) were reported. Preinvestigation, 8799 (16%) cases met high-risk criteria. Postinvestigation, 17 037 (31%) cases met high-risk criteria. Sensitivity was 52% and PPV was 98%. Automating case notifications, prioritizing investigations, and collaborating with ASU improved the timeliness of case contact, focused public health resources toward high-priority cases, and increased investigation capacity. Establishing partnerships between health departments and academia might be a helpful strategy for future surge capacity planning.

Design and Implementation of a COVID-19 Case Investigation Program: An Academic-Public Health Partnership, Arizona, 2020.

From May through July 2020, Arizona was a global hotspot for new COVID-19 cases. In response to the surge of cases, local public health departments looked for innovative ways to form external partnerships to address their staffing needs. In collaboration with the Maricopa County Department of Public Health, the Arizona State University Student Outbreak Response Team (SORT) created and implemented a virtual call center to conduct public health case investigations for COVID-19. SORT officially launched a dedicated COVID-19 case investigation program after 3 weeks of program design and training. From June 29 through November 8, 2020, SORT recruited and trained 218 case investigators, completed 5000 case patient interviews, and closed 10 000 cases. Our team also developed process improvements to address disparities in case investigation timeliness. A strong infrastructure designed to accommodate remote case investigations, paired with a large workforce, enabled SORT to provide additional surge capacity for the county's high volume of cases. University-driven multidisciplinary case investigator teams working in partnership with state, tribal, and local public health staff members can be an effective tool for supporting a diverse and growing public health workforce. We discuss the essential design factors involved in building a university program to complement local COVID-19 response efforts, including workflows for case management, volunteer case investigator recruitment and training, secure technology platforms for conducting case investigations remotely, and robust data-tracking procedures for maintaining quality control and timely case reporting.

Elucidating symptoms of COVID-19 illness in the Arizona CoVHORT: a longitudinal cohort study.

OBJECTIVE: To elucidate the symptoms of laboratory-confirmed COVID-19 cases as compared with laboratory-confirmed negative individuals and to the untested general population among all participants who reported symptoms within a large prospective cohort study. SETTING AND DESIGN: This work was conducted within the framework of the Arizona CoVHORT, a longitudinal prospective cohort study conducted among Arizona residents. PARTICIPANTS: Eligible participants were any individual living in Arizona and were recruited from across Arizona via COVID-19 case investigations, participation in testing studies and a postcard mailing effort. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was a comparison of the type and frequency of symptoms between COVID-19-positive cases, tested but negative individuals and the general untested population who reported experiencing symptoms consistent with COVID-19. RESULTS: Of the 1335 laboratory-confirmed COVID-19 cases, 180 (13.5%) reported having no symptoms. Of those that did report symptoms, the most commonly reported were fatigue (82.2%), headache (74.6%), aches, pains or sore muscles (66.3%), loss of taste or smell (62.8) and cough (61.9%). In adjusted logistic regression models, COVID-19-positive participants were more likely than negative participants to experience loss of taste and smell (OR 12.1; 95% CI 9.6 to 15.2), bone or nerve pain (OR 3.0; 95% CI 2.2 to 4.1), headache (OR 2.6; 95% CI 2.2 to 3.2), nausea (OR 2.4; 95% CI 1.9 to 3.1) or diarrhoea (OR 2.1; 95% CI 1.7 to 2.6). Fatigue (82.9) and headache (74.9) had the highest sensitivities among symptoms, while loss of taste or smell (87.2) and bone or nerve pain (92.9) had the high specificities among significant symptoms associated with COVID-19. CONCLUSION: When comparing confirmed COVID-19 cases with either confirmed negative or untested participants, the pattern of symptoms that discriminates SARS-CoV-2 infection from those arising from other potential circulating pathogens may differ from general reports of symptoms among cases alone.

Consequences of COVID-19 on adolescents in Arizona: A longitudinal study protocol.

Introduction: The long-term impact of COVID-19 is unknown. We developed a 5-year prospective cohort study designed to generate actionable community-informed research about the consequences of COVID-19 on adolescents ages 12-17 years in Arizona. Methods: The study has two primary outcomes: 1) acute and long-term outcomes of COVID-19 illness and 2) symptoms of depression and anxiety. Data is collected using an online survey with plans to integrate qualitative data collection methods. The survey is administered at baseline, 4, and 8 months in year one, and annually in years two through five. This study is informed by Intersectionality Theory, which considers the diverse identities adolescents have that are self and socially defined and the influence they have collectively and simultaneously. To this end, a sample of variables collected is race/ethnicity, language usage, generational status, co-occurring health conditions, and gender. Additional measures capture experiences in social contexts such as home (parent employment, food, and housing security), school (remote learning, type of school), and society (racism). Results: Findings are not presented because the manuscript is a protocol designed to describe the procedure instead of report results. Discussion: The unique contributions of the study is its focus on COVID-19 the illness and COVID-19 the socially experienced pandemic and the impact of both on adolescents.

Accuracy of Case-Based Seroprevalence of SARS-CoV-2 Antibodies in Maricopa County, Arizona.

We conducted a community seroprevalence survey in Arizona, from September 12 to October 1, 2020, to determine the presence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used the seroprevalence estimate to predict SARS-CoV-2 infections in the jurisdiction by applying the adjusted seroprevalence to the county's population. The estimated community seroprevalence of SARS-CoV-2 infections was 4.3 times greater (95% confidence interval = 2.2, 7.5) than the number of reported cases. Field surveys with representative sampling provide data that may help fill in gaps in traditional public health reporting. (Am J Public Health. 2022;112(1):38-42. https://doi.org/10.2105/AJPH.2021.306568).

Association Between K-12 School Mask Policies and School-Associated COVID-19 Outbreaks - Maricopa and Pima Counties, Arizona, July-August 2021.

CDC recommends universal indoor masking by students, staff members, faculty, and visitors in kindergarten through grade 12 (K-12) schools, regardless of vaccination status, to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Schools in Maricopa and Pima Counties, which account for >75% of Arizona's population (2), resumed in-person learning for the 2021-22 academic year during late July through early August 2021. In mid-July, county-wide 7-day case rates were 161 and 105 per 100,000 persons in Maricopa and Pima Counties, respectively, and 47.6% of Maricopa County residents and 59.2% of Pima County residents had received at least 1 dose of a COVID-19 vaccine. School districts in both counties implemented variable mask policies at the start of the 2021-22 academic year (Table). The association between school mask policies and school-associated COVID-19 outbreaks in K-12 public noncharter schools open for in-person learning in Maricopa and Pima Counties during July 15-August 31, 2021, was evaluated.

Post-acute sequelae of COVID-19 in a non-hospitalized cohort: Results from the Arizona CoVHORT.

Clinical presentation, outcomes, and duration of COVID-19 has ranged dramatically. While some individuals recover quickly, others suffer from persistent symptoms, collectively known as long COVID, or post-acute sequelae of SARS-CoV-2 (PASC). Most PASC research has focused on hospitalized COVID-19 patients with moderate to severe disease. We used data from a diverse population-based cohort of Arizonans to estimate prevalence of PASC, defined as experiencing at least one symptom 30 days or longer, and prevalence of individual symptoms. There were 303 non-hospitalized individuals with a positive lab-confirmed COVID-19 test who were followed for a median of 61 days (range 30-250). COVID-19 positive participants were mostly female (70%), non-Hispanic white (68%), and on average 44 years old. Prevalence of PASC at 30 days post-infection was 68.7% (95% confidence interval: 63.4, 73.9). The most common symptoms were fatigue (37.5%), shortness-of-breath (37.5%), brain fog (30.8%), and stress/anxiety (30.8%). The median number of symptoms was 3 (range 1-20). Amongst 157 participants with longer follow-up (≥60 days), PASC prevalence was 77.1%.

Availability, variety and distribution of healthy and unhealthy foods and beverages sold at street food stands in Mexico City.

OBJECTIVE: To examine differences in the availability, variety and distribution of foods and beverages sold at street food stands (SFS) across neighbourhood income levels in Mexico City. DESIGN: Cross-sectional. SETTING: Twenty neighbourhoods representing low-, middle- and high-income levels in Mexico City. PARTICIPANTS: Direct observations of SFS (n 391). RESULTS: The availability of healthy foods such as fruits/vegetables was high in middle- and high-income neighbourhoods, whereas the availability of unhealthy foods such as processed snacks was higher in low-income neighbourhoods. However, statistically significant differences in food availability across neighbourhoods were only observed for dairy and processed snack items (P < 0·05). Similarly, differences in variety were only observed for cereal and processed snacks (P < 0·05). No statistically significant differences were seen for variety of fruits/vegetable across neighbourhood income levels (P > 0·05). No statistically significant differences across neighbourhood income levels were observed for beverage availability and variety (P > 0·05). Although street foods and beverages were often distributed near homes, public transportation centres and worksites, no differences were observed across neighbourhood income levels (P > 0·05). CONCLUSIONS: Findings suggest that SFS can be a source of both unhealthy foods and healthy foods for communities across neighbourhoods in Mexico City. Additional studies are needed to assess the relationship between street food and beverage availability, and consumption.

Development and Interrater Reliability of a Street Food Stand Assessment Tool.

OBJECTIVE: To design and test the interrater reliability of a Street Food Stand Assessment Tool (SFSAT). DESIGN: Variables were adapted from validated assessment tools, field observations, and the Mexican Dietary Guidelines. Two researchers tested the SFSAT by observing street food stands (SFS) in 3 middle- to high-income neighborhoods. SETTING: Mexico City. PARTICIPANTS: Fifty-two SFS. VARIABLES MEASURED: The SFSAT contains 14 items for SFS characteristics and 44 items for food and beverages. ANALYSIS: Percent agreement and kappa interrater reliability scores were calculated for each variable. RESULTS: Almost perfect kappa interrater reliability scores (0.81-1.00) were reported for 62.7% of SFS characteristic items. Interrater reliability scores for food and beverage availability and variety ranged from 0.00-1.00, whereas the percent agreement for these items ranged from 59.6%-100.0%. CONCLUSIONS AND IMPLICATIONS: The SFSAT is a reliable assessment tool to measure the availability and variety of street foods and beverages in Mexico City. Future research can update and adapt the SFSAT to the street food environment of other cities-in Mexico and abroad.

Street Food Stand Availability, Density, and Distribution Across Income Levels in Mexico City.

Street food stands (SFS) are an understudied element of the food environment. Previous SFS studies have not used a rigorous approach to document the availability, density, and distribution of SFS across neighborhood income levels and points of access in Mexico City. A random sample (n = 761) of street segments representing 20 low-, middle-, and high-income neighborhoods were assessed using geographic information system (GIS) and ground-truthing methods. All three income levels contained SFS. However, SFS availability and density were higher in middle-income neighborhoods. The distribution of SFS showed that SFS were most often found near homes, transportation centers, and worksites. SFS availability near schools may have been limited by local school policies. Additional studies are needed to further document relationships between SFS availability, density, and distribution, and current structures and processes.

Design of the Arizona CoVHORT: A Population-Based COVID-19 Cohort.

This study is a prospective, population-based cohort of individuals with a history of SARS-CoV-2 infection and those without past infection through multiple recruitment sources. The main study goal is to track health status over time, within the diverse populations of Arizona and to identify the long-term consequences of COVID-19 on health and well-being. A total of 2,881 study participants (16.2% with a confirmed SARS-CoV-2 infection) have been enrolled as of December 22, 2020, with a target enrollment of 10,000 participants and a planned follow-up of at least 2 years. This manuscript describes a scalable study design that utilizes a wide range of recruitment sources, leveraging electronic data collection to capture and link longitudinal participant data on the current and emerging issues associated with the COVID-19 pandemic. The cohort is built within a collaborative infrastructure that includes new and established partnerships with multiple stakeholders, including the state's public universities, local health departments, tribes, and tribal organizations. Challenges remain for ensuring recruitment of diverse participants and participant retention, although the electronic data management system and timing of participant contact can help to mitigate these problems.

COVID-19 healthcare demand projections: Arizona.

Beginning in March 2020, the United States emerged as the global epicenter for COVID-19 cases with little to guide policy response in the absence of extensive data available for reliable epidemiological modeling in the early phases of the pandemic. In the ensuing weeks, American jurisdictions attempted to manage disease spread on a regional basis using non-pharmaceutical interventions (i.e., social distancing), as uneven disease burden across the expansive geography of the United States exerted different implications for policy management in different regions. While Arizona policymakers relied initially on state-by-state national modeling projections from different groups outside of the state, we sought to create a state-specific model using a mathematical framework that ties disease surveillance with the future burden on Arizona's healthcare system. Our framework uses a compartmental system dynamics model using a SEIRD framework that accounts for multiple types of disease manifestations for the COVID-19 infection, as well as the observed time delay in epidemiological findings following public policy enactments. We use a compartment initialization logic coupled with a fitting technique to construct projections for key metrics to guide public health policy, including exposures, infections, hospitalizations, and deaths under a variety of social reopening scenarios. Our approach makes use of X-factor fitting and backcasting methods to construct meaningful and reliable models with minimal available data in order to provide timely policy guidance in the early phases of a pandemic.

The importance of widespread testing for COVID-19 pandemic: systems thinking for drive-through testing sites.

On 11 March 2020, the World Health Organisation (WHO) declared COVID-19 a pandemic. Early epidemiological estimates show that COVID-19 is highly transmissible, infecting populations across the globe in a short amount of time. WHO has recommended widespread clinical testing in order to contain COVID-19. However, mass testing in emergency department (ED) settings may result in crowded EDs and increase transmission risk for healthcare staff and other ED patients. Drive-through COVID-19 testing sites are an effective solution to quickly collect samples from suspected cases with minimal risk to healthcare personnel and other patients. Nevertheless, there are many logistical and operational challenges, such as shortages of testing kits, limited numbers of healthcare staff and long delays for collecting samples. Solving these problems requires an understanding of disease dynamics and epidemiology, as well as the logistics of mass distribution. In this position paper, we provide a conceptual framework for addressing these challenges, as well as some insights from prior literature and experience on developing decision support tools for public health departments.

Relationship between different levels of the Mexican food environment and dietary intake: a qualitative systematic review.

OBJECTIVE: To investigate the possible associations between the food environment and dietary intake in the Mexican population. DESIGN: Four databases (PubMed, PsychInfo, Web of Science and SCIelo) were used to retrieve relevant articles using an open timeframe. Articles were reviewed if they contained a systematic measure (i.e. food checklist) of the food environment (e.g. food availability) and dietary intake. SETTING: Urban and rural communities in Mexico. PARTICIPANTS: Population-based studies of Mexican communities. RESULTS: Twenty studies that assessed at least one food environment level, and at least one dietary outcome, were reviewed. Findings from these studies showed that changes in the Mexican food environment seem to be associated with higher availability of energy-dense foods. Energy-dense foods can be linked to a high consumption in household, environment and community food environments. When both nutrient-dense and energy-dense foods were present, individuals were more likely to consume foods with added sugars, fats and salt options than nutrient-dense items. CONCLUSIONS: The various levels of the food environment (i.e. household, school, community) exposed participants to energy-dense foods. Although nutrient-dense foods were present in all three levels, individuals were more likely to consume energy-dense food items. Not all three levels of the food environment are well represented in the urban and rural settings. Most studies on the community food environment were done in rural areas, whereas most studies on the school food environment were done in urban settings. Additional rigorously designed studies are needed to document the relationship between the food environment and dietary intake in the Mexican population.

Nurses' Perceptions of Implant Barcode Scanning in Surgical Services.

The US Food and Drug Administration's 2013 Unique Device Identification System Rule requires manufacturers to label devices with unique identifiers. Implantable devices are now shipped with unique identifiers, and many electronic health records have fields to incorporate them. Health policy changes have prompted hospital systems to assess implementation of implant barcode scanning systems to capture unique device identifiers. Project aims were to assess predictors of operating room nurses' acceptance of a new implant barcode scanning system, describe operating room nurses' perceptions of the system value, and identify operating room nurses' perceived gaps in system implementation. An online survey was disseminated to operating room nurses, and focus groups were conducted with orthopedic operating room nurses in an academic medical center that had recently implemented an implant barcode scanning system in surgical services. Predictors of barcode scanning acceptance included perceived usefulness for patient care, perceived ease of use, and perceived usefulness (self). Nurses perceived the system to be more accurate and valuable for patient safety. Perceived gaps in system implementation related to communication, completeness of the system, consistency in process, and training. Understanding nurse perceptions of new barcode scanning systems and engaging them in the implementation process are key areas for success and optimization of these systems.

The Emergence of Undergraduate Majors in Global Health: Systematic Review of Programs and Recommendations for Future Directions.

Global health education has been expanding rapidly and several universities have created an undergraduate major degree (bachelor's degree) in global heath or global health studies. Because there are currently no national guidelines for undergraduate degrees in global health, each of these programs was developed along individual lines. To guide the development of future global health majors, we conducted a systematic review of undergraduate majors in global health. We identified eight programs and invited program directors or representatives to a symposium at the Consortium of Universities for Global Health 2016 conference to review their existing undergraduate major in global health and to discuss lessons learned and recommendations for other colleges and universities seeking to develop undergraduate degrees in global health. We noted significant diversity among the existing programs in terms of required courses, international field experiences, and thesis research projects. In this review, we describe these global health programs, their student characteristics, as well as the key educational competencies, program requirements, and core global health courses. Based on program reviews and discussions, we identify seven recommendations for the development and expansion of an undergraduate major in global health and discuss issues that have arisen in the curricular development of these programs that warrant further exploration. As the field of global health education continues to expand, following these students after graduation will be essential to ensure that the degree programs in global health both meet student needs and launch students on viable career pathways.

Mortality and transmissibility patterns of the 1957 influenza pandemic in Maricopa County, Arizona.

BACKGROUND: While prior studies have quantified the mortality burden of the 1957 H2N2 influenza pandemic at broad geographic regions in the United States, little is known about the pandemic impact at a local level. Here we focus on analyzing the transmissibility and mortality burden of this pandemic in Arizona, a setting where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high. METHODS: Using archival death certificates from 1954 to 1961, we quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 H2N2 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and assumed generation intervals of 3 and 4 days. Local newspaper articles published during 1957-1958 were also examined. RESULTS: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 16.59 in the elderly (≥65 years). All other age groups exhibit very low excess-mortality and the typical U-shaped age-pattern was absent. However, the standardized mortality ratio was greatest (4.06) among children and young adolescents (5-14 years) from October 1957-March 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957-1958 period, when the mean reproduction number was estimated at 1.08-1.11, assuming 3- or 4-day generation intervals with exponential or fixed distributions. CONCLUSIONS: Maricopa County exhibited very low mortality impact associated with the 1957 influenza pandemic. Understanding the relatively low excess-mortality rates and transmissibility in Maricopa County during this historic pandemic may help public health officials prepare for and mitigate future outbreaks of influenza.

National projections of time, cost and failure in implantable device identification: Consideration of unique device identification use.

BACKGROUND: U.S. health care is responding to significant regulation and meaningful incentives for higher quality care, patient safety, electronic documentation and data exchange. FDA's Unique Device Identification (UDI) Rule, a relatively new regulation aligned with these goals, requires standard labeling of medical devices by manufacturers. This lays the foundation for UDI scanning and documentation in the electronic health record, expected to change the landscape of medical device identification and postmarket surveillance. METHODS: We developed national projections for time, cost and failure in implant identification prior to revision total hip and knee arthroplasty (THA/TKA) using American Association of Hip and Knee Surgeons 2012 membership survey data, Nationwide Inpatient Sample 2011 data and THA/TKA demand projection data. RESULTS: Our projections suggest that cumulative surgeon time spent identifying failed implants could reach 133,000 h in 2030, representing opportunity to perform over 500,000 15 min established patient office visits. Staff time could reach 220,000 h with a cost of $3.3m. Failed implants that cannot be identified may be greater than 50,000 preoperatively and 25,000 intraoperatively in 2030. CONCLUSION: Study projections indicate significant time, cost and inability to identify failed implants, supporting need for improvement of implant documentation. FDA's UDI Rule sets the foundation for UDI scanning and documentation in the electronic health record, a process poised to serve as the standard system for device documentation.