scholarly journals Comparing Clinical Characteristics of Influenza and Common Coronavirus Infections Using Electronic Health Records

2020 ◽  
Author(s):  
Dadong Li ◽  
Donna M Wolk ◽  
Michael N Cantor
Keyword(s):  
Electronic Health Records ◽  
Influenza A ◽  
Health Records ◽  
Icu Admission ◽  
Admission Rates ◽  
Risk Of Death ◽  
Significant Difference ◽  
Electronic Health ◽  
Poor Outcomes ◽  
Coronavirus Infections

Abstract Background We compared outcomes in inpatients and outpatients, pre-COVID-19, who were infected with either coronavirus or influenza. Methods Using deidentified electronic health records data from the Geisinger-Regeneron partnership, we compared patients with RT-PCR–positive tests for the 4 common coronaviruses (229E, HKU1, NL63, OC43) or influenza (A and B) from June 2016 to February 2019. Results Overall, 52 833 patients were tested for coronaviruses and influenza. For patients ≥21 years old, 1555 and 3991 patient encounters had confirmed positive coronavirus and influenza tests, respectively. Both groups had similar intensive care unit (ICU) admission rates (7.2% vs 6.1%, P = .12), although patients with coronavirus had significantly more pneumonia (15% vs 7.4%, P < .001) and higher death rate within 30 days (4.9% vs 3.0%, P < .001). After controlling for other covariates, coronavirus infection still had a higher risk of death and pneumonia than influenza (odds ratio, 1.64 and 2.05, P < .001), with no significant difference in ICU admission rates. Conclusions Common coronaviruses cause significant morbidity, with potentially worse outcomes than influenza. Identifying a subset of patients who are more susceptible to poor outcomes from common coronavirus infections may help plan clinical interventions in patients with suspected infections.

scholarly journals Academic Electronic Health Records in Undergraduate Nursing Education: Mixed Methods Pilot Study (Preprint)

2021 ◽  
Author(s):  
Manal Kleib ◽  
Deirdre Jackman ◽  
Uirá Duarte Wisnesky ◽  
Shamsa Ali
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Nursing Programs ◽  
Health Record ◽  
Health Records ◽  
Undergraduate Nursing ◽  
Significant Difference ◽  
Before And After ◽  
The Mean ◽  
Electronic Health

BACKGROUND Teaching students about electronic health records presents challenges for most nursing programs, primarily because of the limited training opportunities within clinical practice settings. A simulated electronic health record is an experiential, learner-centered strategy that enables students to acquire and apply the informatics knowledge needed for working with electronic records in a safe learning environment before the students have encounters with real patients. OBJECTIVE The aim of this study is to provide a preliminary evaluation of the Lippincott DocuCare simulated electronic health record and determine the feasibility issues associated with its implementation. METHODS We used one-group pretest-posttest, surveys, and focus group interviews with students and instructors to pilot the DocuCare simulated electronic health record within an undergraduate nursing program in Western Canada. Volunteering students worked through 4 case scenarios during a 1-month pilot. Self-reported informatics knowledge and attitudes toward the electronic health record, accuracy of computerized documentation, satisfaction, and students’ and educators’ experiences were examined. Demographic and general information regarding informatics learning was also collected. RESULTS Although 23 students participated in this study, only 13 completed surveys were included in the analysis. Almost two-thirds of the students indicated their overall understanding of nursing informatics as being fair or inadequate. The two-tailed paired samples <i>t</i> test used to evaluate the impact of DocuCare on students’ self-reported informatics knowledge and attitudes toward the electronic health record revealed a statistically significant difference in the mean score of knowledge before and after using DocuCare (before: mean 2.95, SD 0.58; after: mean 3.83, SD 0.39; <i>t</i><sub>12</sub>=5.80, two-tailed; <i>P</i>&lt;.001). There was no statistically significant difference in the mean scores of attitudes toward the electronic health record before and after using DocuCare (before: mean 3.75, SD 0.40; after: mean 3.70, SD 0.34; <i>t</i><sub>12</sub>=0.39, two-tailed; <i>P</i>=.70). Students’ documentation scores varied from somewhat accurate to completely accurate; however, performance improved for the majority of students as they progressed from case scenarios 1 to 4. Both the faculty and students were highly satisfied with DocuCare and highly recommended its integration. Focus groups with 7 students and 3 educators revealed multiple themes. The participants shared suggestions regarding the DocuCare product customization and strategies for potential integration in undergraduate nursing programs. CONCLUSIONS This study demonstrated the feasibility and suitability of the DocuCare program as a tool to enhance students’ learning about informatics and computerized documentation in electronic health records. Recommendations will be made to academic leadership in undergraduate programs on the basis of this study. Furthermore, a controlled evaluation study will be conducted in the future.

scholarly journals Academic Electronic Health Records in Undergraduate Nursing Education: Mixed Methods Pilot Study

JMIR Nursing ◽  
10.2196/26944 ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. e26944
Author(s):  
Manal Kleib ◽  
Deirdre Jackman ◽  
Uirá Duarte Wisnesky ◽  
Shamsa Ali
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Nursing Programs ◽  
Health Record ◽  
Health Records ◽  
Undergraduate Nursing ◽  
Significant Difference ◽  
Before And After ◽  
The Mean ◽  
Electronic Health

Background Teaching students about electronic health records presents challenges for most nursing programs, primarily because of the limited training opportunities within clinical practice settings. A simulated electronic health record is an experiential, learner-centered strategy that enables students to acquire and apply the informatics knowledge needed for working with electronic records in a safe learning environment before the students have encounters with real patients. Objective The aim of this study is to provide a preliminary evaluation of the Lippincott DocuCare simulated electronic health record and determine the feasibility issues associated with its implementation. Methods We used one-group pretest-posttest, surveys, and focus group interviews with students and instructors to pilot the DocuCare simulated electronic health record within an undergraduate nursing program in Western Canada. Volunteering students worked through 4 case scenarios during a 1-month pilot. Self-reported informatics knowledge and attitudes toward the electronic health record, accuracy of computerized documentation, satisfaction, and students’ and educators’ experiences were examined. Demographic and general information regarding informatics learning was also collected. Results Although 23 students participated in this study, only 13 completed surveys were included in the analysis. Almost two-thirds of the students indicated their overall understanding of nursing informatics as being fair or inadequate. The two-tailed paired samples t test used to evaluate the impact of DocuCare on students’ self-reported informatics knowledge and attitudes toward the electronic health record revealed a statistically significant difference in the mean score of knowledge before and after using DocuCare (before: mean 2.95, SD 0.58; after: mean 3.83, SD 0.39; t12=5.80, two-tailed; P<.001). There was no statistically significant difference in the mean scores of attitudes toward the electronic health record before and after using DocuCare (before: mean 3.75, SD 0.40; after: mean 3.70, SD 0.34; t12=0.39, two-tailed; P=.70). Students’ documentation scores varied from somewhat accurate to completely accurate; however, performance improved for the majority of students as they progressed from case scenarios 1 to 4. Both the faculty and students were highly satisfied with DocuCare and highly recommended its integration. Focus groups with 7 students and 3 educators revealed multiple themes. The participants shared suggestions regarding the DocuCare product customization and strategies for potential integration in undergraduate nursing programs. Conclusions This study demonstrated the feasibility and suitability of the DocuCare program as a tool to enhance students’ learning about informatics and computerized documentation in electronic health records. Recommendations will be made to academic leadership in undergraduate programs on the basis of this study. Furthermore, a controlled evaluation study will be conducted in the future.

scholarly journals dxpr: an R package for generating analysis-ready data from electronic health records—diagnoses and procedures

2021 ◽  
Vol 7 ◽  
pp. e520
Author(s):  
Yi-Ju Tseng ◽  
Hsiang-Ju Chiu ◽  
Chun Ju Chen
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Clinical Data ◽  
Data Analytics ◽  
Medical Information ◽  
Ductus Arteriosus ◽  
R Package ◽  
Health Records ◽  
Significant Difference ◽  
Electronic Health

Background Enriched electronic health records (EHRs) contain crucial information related to disease progression, and this information can help with decision-making in the health care field. Data analytics in health care is deemed as one of the essential processes that help accelerate the progress of clinical research. However, processing and analyzing EHR data are common bottlenecks in health care data analytics. Methods The dxpr R package provides mechanisms for integration, wrangling, and visualization of clinical data, including diagnosis and procedure records. First, the dxpr package helps users transform International Classification of Diseases (ICD) codes to a uniform format. After code format transformation, the dxpr package supports four strategies for grouping clinical diagnostic data. For clinical procedure data, two grouping methods can be chosen. After EHRs are integrated, users can employ a set of flexible built-in querying functions for dividing data into case and control groups by using specified criteria and splitting the data into before and after an event based on the record date. Subsequently, the structure of integrated long data can be converted into wide, analysis-ready data that are suitable for statistical analysis and visualization. Results We conducted comorbidity data processes based on a cohort of newborns from Medical Information Mart for Intensive Care-III (n = 7,833) by using the dxpr package. We first defined patent ductus arteriosus (PDA) cases as patients who had at least one PDA diagnosis (ICD, Ninth Revision, Clinical Modification [ICD-9-CM] 7470*). Controls were defined as patients who never had PDA diagnosis. In total, 381 and 7,452 patients with and without PDA, respectively, were included in our study population. Then, we grouped the diagnoses into defined comorbidities. Finally, we observed a statistically significant difference in 8 of the 16 comorbidities among patients with and without PDA, including fluid and electrolyte disorders, valvular disease, and others. Conclusions This dxpr package helps clinical data analysts address the common bottleneck caused by clinical data characteristics such as heterogeneity and sparseness.

scholarly journals Atrial fibrillation and oral anticoagulation in older people with frailty: a nationwide primary care electronic health records cohort study

2020 ◽  
Author(s):  
Chris Wilkinson ◽  
Andrew Clegg ◽  
Oliver Todd ◽  
Kenneth Rockwood ◽  
Mohammad E Yadegarfar ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Electronic Health Records ◽  
Older People ◽  
Oral Anticoagulation ◽  
Stroke Prevention ◽  
Stroke Risk ◽  
Health Records ◽  
Risk Of Death ◽  
Increased Risk ◽  
Electronic Health

Abstract Background Atrial fibrillation (AF) is common in older people and is associated with increased stroke risk that may be reduced by oral anticoagulation (OAC). Frailty also increases with increasing age, yet the extent of OAC prescription in older people according to extent of frailty in people with AF is insufficiently described. Methods An electronic health records study of 536,955 patients aged ≥65 years from ResearchOne in England (384 General Practices), over 15.4 months, last follow-up 11th April 2017. OAC prescription for AF with CHA2DS2-Vasc ≥2, adjusted (demographic and treatments) risk of all-cause mortality, and subsequent cerebrovascular disease, bleeding and falls were estimated by electronic frailty index (eFI) category of fit, mild, moderate and severe frailty. Results AF prevalence and mean CHA2DS2-Vasc for those with AF increased with increasing eFI category (fit 2.9%, 2.2; mild 11.2%, 3.2; moderate 22.2%, 4.0; and severe 31.5%, 5.0). For AF with CHA2DS2-Vasc ≥2, OAC prescription was higher for mild (53.2%), moderate (55.6%) and severe (53.4%) eFI categories than fit (41.7%). In those with AF and eligible for OAC, frailty was associated with increased risk of death (HR for severe frailty compared with fit 4.09, 95% confidence interval 3.43–4.89), gastrointestinal bleeding (2.17, 1.45–3.25), falls (8.03, 4.60–14.03) and, among women, stroke (3.63, 1.10–12.02). Conclusion Among older people in England, AF and stroke risk increased with increasing degree of frailty; however, OAC prescription approximated 50%. Given competing demands of mortality, morbidity and stroke prevention, greater attention to stratified stroke prevention is needed for this group of the population.

scholarly journals Comparison of the cohort selection performance of Australian Medicines Terminology to Anatomical Therapeutic Chemical mappings

2019 ◽  
Vol 26 (11) ◽  
pp. 1237-1246
Author(s):  
Guan N Guo ◽  
Jitendra Jonnagaddala ◽  
Sanjay Farshid ◽  
Vojtech Huser ◽  
Christian Reich ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Anatomical Therapeutic Chemical ◽  
Research Network ◽  
Common Data Model ◽  
Health Records ◽  
Number Of Patients ◽  
Significant Difference ◽  
Cohort Selection ◽  
Electronic Health ◽  
The Impact

Abstract Objective Electronic health records are increasingly utilized for observational and clinical research. Identification of cohorts using electronic health records is an important step in this process. Previous studies largely focused on the methods of cohort selection, but there is little evidence on the impact of underlying vocabularies and mappings between vocabularies used for cohort selection. We aim to compare the cohort selection performance using Australian Medicines Terminology to Anatomical Therapeutic Chemical (ATC) mappings from 2 different sources. These mappings were taken from the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) and the Pharmaceutical Benefits Scheme (PBS) schedule. Materials and Methods We retrieved patients from the electronic Practice Based Research Network data repository using 3 ATC classification groups (A10, N02A, N06A). The retrieved patients were further verified manually and pooled to form a reference standard which was used to assess the accuracy of mappings using precision, recall, and F measure metrics. Results The OMOP-CDM mappings identified 2.6%, 15.2%, and 24.4% more drugs than the PBS mappings in the A10, N02A and N06A groups respectively. Despite this, the PBS mappings generally performed the same in cohort selection as OMOP-CDM mappings except for the N02A Opioids group, where a significantly greater number of patients were retrieved. Both mappings exhibited variable recall, but perfect precision, with all drugs found to be correctly identified. Conclusion We found that 1 of the 3 ATC groups had a significant difference and this affected cohort selection performance. Our findings highlighted that underlying terminology mappings can greatly impact cohort selection accuracy. Clinical researchers should carefully evaluate vocabulary mapping sources including methodologies used to develop those mappings.

Survival in relation to multimorbidity patterns in older adults in primary care in Barcelona, Spain (2010–2014): a longitudinal study based on electronic health records

2018 ◽  
Vol 72 (3) ◽  
pp. 185-192 ◽  
Author(s):  
Carolina Ibarra-Castillo ◽  
Marina Guisado-Clavero ◽  
Concepció Violan-Fors ◽  
Mariona Pons-Vigués ◽  
Tomàs López-Jiménez ◽  
...  
Keyword(s):  
Older Adults ◽  
Electronic Health Records ◽  
Mortality Rates ◽  
Respiratory Pattern ◽  
Index Number ◽  
Age Group ◽  
Health Records ◽  
Risk Of Death ◽  
Electronic Health ◽  
Prospective Longitudinal

BackgroundSeveral studies have analysed the characteristics of multimorbidity patterns but none have evaluated the relationship with survival. The purpose of this study was to compare survival across older adults with different chronic multimorbidity patterns (CMPs).MethodsProspective longitudinal observational study using electronic health records for 190 108 people aged ≥65 years in Barcelona, Spain (2009–2014). CMPs were identified by cluster analysis. Mortality rates were estimated using the Catalan population structure and individual time at risk. Survival according to CMP (Cox regression) was analysed using hazard ratios (HRs) and 95% confidence intervals (CIs) with stratification by sex and age group (65–79, 80–94) and adjustment for age at onset, deprivation index, number of chronic conditions and invoiced drugs.ResultsThe highest mortality rates were observed in men, adults aged 80–94 years, socially disadvantaged quintiles and people prescribed more drugs and with fewer conditions. Using the musculoskeletal pattern as the reference category, men with the digestive-respiratory pattern had a higher risk of death, with adjusted HRs of 6.16 (95% CI 5.37 to 7.06) in the 65–79 age group and 2.62 (95% CI 2.31 to 2.97) in the 80–94 age group. In women, the cardiovascular pattern was associated with the highest risk, with adjusted HRs of 6.34 (95% CI 5.28 to 7.61) in the 65–79 age group and 3.05 (95% CI 2.73 to 3.41) in the 80–94 age group. These patterns were also associated with the highest mortality rates.ConclusionsMortality and survival vary according to CMPs in older adults stratified by sex and age. Our findings are useful for guiding the design and implementation of clinical management strategies.

scholarly journals Comparing Characteristics of Patients Who Connect Their iPhones to an Electronic Health Records System Versus Patients Who Connect Without Personal Devices: Cohort Study

10.2196/14871 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e14871 ◽  
Author(s):  
William J Gordon ◽  
David W Bates ◽  
Daniel Fuchs ◽  
John Pappas ◽  
Sara Silacci ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Health Data ◽  
Adult Patients ◽  
Patient Portal ◽  
Health Records ◽  
Early Results ◽  
Access To Health ◽  
Significant Difference ◽  
Electronic Health ◽  
Personal Devices

Background While individual access to health records has traditionally been through paper and other physical media, there has been a recent push toward digitizing this process. Direct patient access to health data through application programming interfaces (APIs) is an important part of current United States policy initiatives, and Apple has created the product “Health Records on iPhone” to leverage APIs for this purpose. Objective The objective of this study was to examine the characteristics of patients at our institution who connected their personal iPhone devices to our electronic health records (EHRs) system through “Health Records on iPhone”, as compared to patients at our institution who used our patient portal but did not connect a personal device to our system. Methods We examined adult patients at our institution who had authorized an iPhone device to download their health data from the Partners HealthCare EHR via APIs through “Health Records on iPhone” from February 18, 2018 (the date this feature was enabled at our health system) until February 17, 2019. We compared these patients to adult patients who used our portal at least once during this period but did not authorize an iPhone device to download their data via APIs. Results Variables associated with an increased likelihood of using “Health Records on iPhone” included male gender (adjusted OR 3.36; 95% CI 3.11-3.62; P<.001) and younger age, particularly below 50 years of age. With each decade of age over 50, people were less likely to be “Health Records on iPhone” product users. Asian patients were more likely to use the product than Caucasian patients (adjusted OR 1.32; 95% CI 1.16-1.51; P<.001), though there was no significant difference between African Americans and Caucasians (adjusted OR 1.15; 95% CI 0.94-1.41; P=.17). Patients who resided in higher ZIP code income quartiles were more likely to be users than those in the lowest quartile. Conclusions Early results from the implementation of patient-facing APIs at a single institution suggest that there are opportunities for expanding these technologies to ensure all patients are aware of, and have access to, their health data on their personal devices. More work is needed on expanding these technologies to different patient populations.

scholarly journals The Impact of Electronic Health Records on the Duration of Patients’ Visits: Time and Motion Study

10.2196/16502 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e16502 ◽  
Author(s):  
Abdulrahman Mohammed Jabour
Keyword(s):  
Electronic Health Records ◽  
Health Records ◽  
Web Based ◽  
Randomized Sampling ◽  
Time And Motion ◽  
Significant Difference ◽  
Longitudinal Observation ◽  
Waiting Area ◽  
Electronic Health ◽  
The Impact

Background Despite the many benefits of electronic health records (EHRs), studies have reported that EHR implementation could create unintended changes in the workflow if not studied and designed properly. These changes may impact the time patients spend on the various steps of their visits, such as the time spent in the waiting area and the time spent with a physician. The amount of time patients spend in the waiting area before consultation is often a strong predictor of patient satisfaction, willingness to come back for a return visit, and overall experience. The majority of prior studies that examined the impact of EHR systems on time focused on single aspects of patient visits or user (physicians or nurses) activities. The impact of EHR use on patients’ time spent during the different aspects of the visit is rarely investigated. Objective This study aimed to evaluate the impact of EHR systems on the amount of time spent by patients on different tasks during their visit to primary health care (PHC) centers. Methods A time and motion observational study was conducted at 4 PHC centers. The PHC centers were selected using stratified randomized sampling. Of the 4 PHC centers, 2 used an EHR system and 2 used a paper-based system. Each group had 1 center in a metropolitan area and another in a rural area. In addition, a longitudinal observation was conducted at one of the PHC centers after 1 year and again after 2 years of implementation. The analysis included descriptive statistics and group comparisons. Results The results showed no significant difference in the amount of time spent by patients in the reception area (P=.26), in the waiting area (P=.57), consultation time (P=.08), and at the pharmacy (P=.28) between the EHR and paper based groups. However, there was a significant difference (P<.001) in the amount of time spent on all tasks between the PHC centers located in metropolitan and rural areas. The longitudinal observation also showed reduction in the registration time (from 5.5 [SD 3.5] min to 0.9 [SD 0.5] min), which could be attributed to the introduction of a Web-based booking system. Conclusions The variation in the time patients spend at PHC centers is more likely to be attributed to the facility location than EHR use. The changes in the introduction of new tools and functions, however, such as the Web-based booking system, can impact the duration of patients’ visits.

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