scholarly journals Comparing associations between frailty and mortality in hospitalised older adults with or without COVID-19 infection: a retrospective observational study using electronic health records

2020 ◽  
Author(s):  
Rhiannon K Owen ◽  
Simon P Conroy ◽  
Nicholas Taub ◽  
Will Jones ◽  
Daniele Bryden ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Older People ◽  
Illness Severity ◽  
Test Results ◽  
Clinical Frailty Scale ◽  
Health Records ◽  
The Mean ◽  
Electronic Health ◽  
Baseline Covariates ◽  
Related Mortality

Abstract Background The aim of this study was to describe outcomes in hospitalised older people with different levels of frailty and COVID-19 infection. Methods We undertook a single-centre, retrospective cohort study examining COVID-19-related mortality using electronic health records, for older people (65 and over) with frailty, hospitalised with or without COVID-19 infection. Baseline covariates included demographics, early warning scores, Charlson Comorbidity Indices and frailty (Clinical Frailty Scale, CFS), linked to COVID-19 status. Findings We analysed outcomes on 1,071 patients with COVID-19 test results (285 (27%) were positive for COVID-19). The mean age at ED arrival was 79.7 and 49.4% were female. All-cause mortality (by 30 days) rose from 9 (not frail) to 33% (severely frail) in the COVID-negative cohort but was around 60% for all frailty categories in the COVID-positive cohort. In adjusted analyses, the hazard ratio for death in those with COVID-19 compared to those without COVID-19 was 7.3 (95% CI: 3.00, 18.0) with age, comorbidities and illness severity making small additional contributions. Interpretation In this study, frailty measured using the CFS appeared to make little incremental contribution to the hazard of dying in older people hospitalised with COVID-19 infection; illness severity and comorbidity had a modest association with the overall adjusted hazard of death, whereas confirmed COVID-19 infection dominated, with a sevenfold hazard for death.

scholarly journals Graphical display of diagnostic test results in electronic health Records: a comparison of 8 systems

2015 ◽  
Vol 22 (4) ◽  
pp. 900-904 ◽  
Author(s):  
Dean F Sittig ◽  
Daniel R Murphy ◽  
Michael W Smith ◽  
Elise Russo ◽  
Adam Wright ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Laboratory Test ◽  
Clinical Laboratory ◽  
Negative Impact ◽  
Laboratory Data ◽  
Test Results ◽  
Health Records ◽  
Laboratory Test Results ◽  
Data Points ◽  
Electronic Health

Abstract Accurate display and interpretation of clinical laboratory test results is essential for safe and effective diagnosis and treatment. In an attempt to ascertain how well current electronic health records (EHRs) facilitated these processes, we evaluated the graphical displays of laboratory test results in eight EHRs using objective criteria for optimal graphs based on literature and expert opinion. None of the EHRs met all 11 criteria; the magnitude of deficiency ranged from one EHR meeting 10 of 11 criteria to three EHRs meeting only 5 of 11 criteria. One criterion (i.e., the EHR has a graph with y-axis labels that display both the name of the measured variable and the units of measure) was absent from all EHRs. One EHR system graphed results in reverse chronological order. One EHR system plotted data collected at unequally-spaced points in time using equally-spaced data points, which had the effect of erroneously depicting the visual slope perception between data points. This deficiency could have a significant, negative impact on patient safety. Only two EHR systems allowed users to see, hover-over, or click on a data point to see the precise values of the x–y coordinates. Our study suggests that many current EHR-generated graphs do not meet evidence-based criteria aimed at improving laboratory data comprehension.

scholarly journals Evaluating the Use of Electronic Health Records for Type 2 Diabetes Surveillance in 2 California Counties, 2010-2014

2017 ◽  
Vol 132 (4) ◽  
pp. 463-470 ◽  
Author(s):  
Maxwell J. Richardson ◽  
Stephen K. Van Den Eeden ◽  
Eric Roberts ◽  
Assiamira Ferrara ◽  
Susan Paulukonis ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Diagnosis ◽  
Family Income ◽  
Census Data ◽  
Diabetes Prevalence ◽  
Future Research ◽  
Test Results ◽  
Health Records ◽  
Hba1c Test ◽  
Electronic Health

Objectives: Electronic health records (EHRs) and electronic laboratory records (ELRs) are increasingly seen as a rich source of data for performing public health surveillance activities and monitoring community health status. Their potential for surveillance of chronic illness, however, may be underused. Our objectives were to (1) evaluate the use of EHRs and ELRs for diabetes surveillance in 2 California counties and (2) examine disparities in diabetes prevalence by geography, income, and race/ethnicity. Methods: We obtained data on a clinical diagnosis of diabetes and hemoglobin A1c (HbA1c) test results for adult members of Kaiser Permanente Northern California living in Contra Costa County or Solano County at any time during 2010-2014. We evaluated the validity of using HbA1c test results to determine diabetes prevalence, using clinical diagnoses as a gold standard. We estimated disparities in diabetes prevalence by combining HbA1c test results with US Census data on income, race, and ethnicity. Results: When compared with a clinical diagnosis of diabetes, data on a patient’s 5-year maximum HbA1c value ≥6.5% yielded the best combination of sensitivity (87.4%) and specificity (99.2%). The prevalence of 5-year maximum HbA1c ≥6.5% decreased with increasing median family income and increased with greater proportions of residents who were either non-Hispanic black or Hispanic. Conclusions: Timely diabetes surveillance data from ELRs can be used to document disparities, target interventions, and evaluate changes in population health. ELR data may be easier to access than a patient’s entire EHR, but outcome metric validation with diabetes diagnoses would need to be ongoing. Future research should validate ELR and EHR data across multiple providers.

Functional clustering methods for longitudinal data with application to electronic health records

2020 ◽  
pp. 096228022096563
Author(s):  
Bret Zeldow ◽  
James Flory ◽  
Alisa Stephens-Shields ◽  
Marsha Raebel ◽  
Jason A Roy
Keyword(s):  
Electronic Health Records ◽  
Longitudinal Data ◽  
Mixed Models ◽  
Dirichlet Process ◽  
Dirichlet Process Prior ◽  
Health Records ◽  
Time Points ◽  
Longitudinal Outcome ◽  
Electronic Health ◽  
Baseline Covariates

We develop a method to estimate subject-level trajectory functions from longitudinal data. The approach can be used for patient phenotyping, feature extraction, or, as in our motivating example, outcome identification, which refers to the process of identifying disease status through patient laboratory tests rather than through diagnosis codes or prescription information. We model the joint distribution of a continuous longitudinal outcome and baseline covariates using an enriched Dirichlet process prior. This joint model decomposes into (local) semiparametric linear mixed models for the outcome given the covariates and simple (local) marginals for the covariates. The nonparametric enriched Dirichlet process prior is placed on the regression and spline coefficients, the error variance, and the parameters governing the predictor space. This leads to clustering of patients based on their outcomes and covariates. We predict the outcome at unobserved time points for subjects with data at other time points as well as for new subjects with only baseline covariates. We find improved prediction over mixed models with Dirichlet process priors when there are a large number of covariates. Our method is demonstrated with electronic health records consisting of initiators of second-generation antipsychotic medications, which are known to increase the risk of diabetes. We use our model to predict laboratory values indicative of diabetes for each individual and assess incidence of suspected diabetes from the predicted dataset.

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 Exploring patients’ perceptions of accessing electronic health records: Innovation in healthcare

2017 ◽  
Vol 25 (1) ◽  
pp. 203-215 ◽  
Author(s):  
Sofie Wass ◽  
Vivian Vimarlund ◽  
Axel Ros
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Patient Involvement ◽  
Decision Makers ◽  
Health Record ◽  
Test Results ◽  
Healthcare Information ◽  
Health Records ◽  
Widespread Implementation ◽  
Electronic Health

The more widespread implementation of electronic health records has led to new ways of providing access to healthcare information, allowing patients to view their medical notes, test results, medicines and so on. In this article, we explore how patients perceive the possibility to access their electronic health record online and whether this influences patient involvement. The study includes interviews with nine patients and a survey answered by 56 patients. Our results show that patients perceive healthcare information to be more accessible and that electronic health record accessibility improves recall, understanding and patient involvement. However, to achieve the goal of involving patients as active decision-makers in their own treatment, electronic health records need to be fully available and test results, referrals and information on drug interactions need to be offered. As patient access to electronic health records spreads, it is important to gain a deeper understanding of how documentation practices can be changed to serve healthcare professionals and patients.

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.

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