scholarly journals Linking Electronic Health Records to Better Understand Breast Cancer Patient Pathways Within and Between Two Health Systems

2015 ◽  
Vol 3 (1) ◽  
pp. 5 ◽  
Author(s):  
Caroline A. Thompson ◽  
Allison W. Kurian ◽  
Harold S. Luft
Keyword(s):  
Breast Cancer ◽  
Electronic Health Records ◽  
Cancer Patient ◽  
Breast Cancer Patient ◽  
Health Systems ◽  
Health Records ◽  
Patient Pathways ◽  
Electronic Health

Abstract P148: Heart Disease Among Breast Cancer Patients

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Tekeda F Ferguson ◽  
Sunayana Kumar ◽  
Denise Danos
Keyword(s):  
Breast Cancer ◽  
Heart Disease ◽  
Electronic Health Records ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Health Concern ◽  
Breast Cancer Patients ◽  
Health Records ◽  
Electronic Health

Purpose: In conjunction with women being diagnosed earlier with breast cancer and a rapidly aging population, advances in cancer therapies have swiftly propelled cardiotoxicity as a major health concern for breast cancer patients. Frequent cardiotoxicity outcomes include: reduced left ventricular ejection fraction (LVEF), myocardial infarction, asymptomatic or hospitalized heart failure, arrhythmias, hypertension, and thromboembolism. The purpose of this study was to use an electronic health records system determine if an increased odds of heart disease was present among women with breast cancer. Methods: Data from the Research Action for Health Network (REACHnet) was used for the analysis. REACHnet is a clinical data research network that uses the common data model to extract electronic health records (EHR) from health networks in Louisiana (n=100,000).Women over the age of 30 with data (n=35,455) were included in the analysis. ICD-9 diagnosis codes were used to classify heart disease (HD) (Hypertensive HD, Ischemic HD, Pulmonary HD, and Other HD) and identify breast cancer patients. Additional EHR variables considered were smoking status, and patient vitals. Chi-square tests, crude, and adjusted logistic regression models were computed utilizing SAS 9.4. Results: Utilizing diagnoses codes our study team has estimated 28.6% of women over the age of 30 with a breast cancer diagnosis (n=816) also had a heart disease diagnosis, contrasted with 15.6% of women without a breast cancer diagnosis. Among patients with heart disease, there was no significant difference in the distribution of the type of heart disease diagnoses by breast cancer status (p=0.87). There was a 2.21 (1.89, 2.58) crude odds ratio of having a CVD diagnoses among breast cancer cases when referenced to cancer free women. After adjusting for age (30-49, 50-64, 65+), race (black/white), and comorbidities (obesity/overweight, diabetes, current smoker) there was an increased risk of heart disease (OR: 1.24 (1.05, 1.47)). Conclusion: The short-term and long-term consequences of cardiotoxicity on cancer treatment risk-to-benefit ratio, survivorship issues, and competing causes of mortality are increasingly being acknowledged. Our next efforts will include making advances in predictive risk modeling. Maximizing benefits while reducing cardiac risks needs to become a priority in oncologic management and monitoring for late-term toxic effects.

scholarly journals Identifying common treatments from Electronic Health Records with missing information. An application to breast cancer

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244004
Author(s):  
Onintze Zaballa ◽  
Aritz Pérez ◽  
Elisa Gómez Inhiesto ◽  
Teresa Acaiturri Ayesta ◽  
Jose A. Lozano
Keyword(s):  
Breast Cancer ◽  
Electronic Health Records ◽  
Health System ◽  
Expert Knowledge ◽  
Missing Information ◽  
Cancer Disease ◽  
Health Records ◽  
Treatment Pathways ◽  
Complete Treatment ◽  
Electronic Health

The aim of this paper is to analyze the sequence of actions in the health system associated with a particular disease. In order to do that, using Electronic Health Records, we define a general methodology that allows us to: (i) identify the actions in the health system associated with a disease; (ii) identify those patients with a complete treatment for the disease; (iii) and discover common treatment pathways followed by the patients with a specific diagnosis. The methodology takes into account the characteristics of the EHRs, such as record heterogeneity and missing information. As an example, we use the proposed methodology to analyze breast cancer disease. For this diagnosis, 5 groups of treatments, which fit in with medical practice guidelines and expert knowledge, were obtained.

scholarly journals Electronic Health Records, Interoperability and Patient Safety in Health Systems of High-income Countries: A Systematic Review Protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e044941
Author(s):  
Edmond Li ◽  
Jonathan Clarke ◽  
Ana Luisa Neves ◽  
Hutan Ashrafian ◽  
Ara Darzi
Keyword(s):  
Systematic Review ◽  
Patient Safety ◽  
Electronic Health Records ◽  
Health Systems ◽  
Risk Of Bias ◽  
High Income ◽  
The Body ◽  
Health Records ◽  
Electronic Health ◽  
The Impact

IntroductionThe availability and routine use of electronic health records (EHRs) have become commonplace in healthcare systems of many high-income countries. While there is an ever-growing body of literature pertaining to their use, evidence surrounding the importance of EHR interoperability and its impact on patient safety remains less clear. There is, therefore, a need and opportunity to evaluate the evidence available regarding this relationship so as to better inform health informatics development and policies in the years to come. This systematic review aims to evaluate the impact of EHR interoperability on patient safety in health systems of high-income countries.Methods and analysisA systematic literature review will be conducted via a computerised search through four databases: PubMed, Embase, Health Management Information Consortium and PsycInfo for relevant articles published between 2010 and 2020. Outcomes of interest will include impact on patient safety and the broader effects on health systems. Quality of the randomised quantitative studies will be assessed using Cochrane Risk of Bias Tool. Non-randomised papers will be evaluated with the Risk of Bias In Non-Randomised Studies—of Interventions tool. Drummond’s Checklist will be used for publications pertaining to economic evaluation. The National Institute for Health and Care Excellence quality appraisal checklist will be used to assess qualitative studies. A narrative synthesis will be conducted for included studies, and the body of evidence will be summarised in a summary of findings table.Ethics and disseminationThis review will summarise published studies with non-identifiable data and, thus, does not require ethical approval. Findings will be disseminated through preprints, open access peer-reviewed publications, and conference presentations.PROSPERO registration numberCRD42020209285.

scholarly journals Diabetes and hypertension among South Asians in New York and Atlanta leveraging hospital electronic health records

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jeannette M. Beasley ◽  
Joyce C. Ho ◽  
Sarah Conderino ◽  
Lorna E. Thorpe ◽  
Megha Shah ◽  
...  
Keyword(s):  
New York ◽  
Electronic Health Records ◽  
Health Systems ◽  
South Asian ◽  
South Asians ◽  
New York University ◽  
Health Records ◽  
Asian Patients ◽  
The Us ◽  
Electronic Health

Abstract Background Diabetes and hypertension disparities are pronounced among South Asians. There is regional variation in the prevalence of diabetes and hypertension in the US, but it is unknown whether there is variation among South Asians living in the US. The objective of this study was to compare the burden of diabetes and hypertension between South Asian patients receiving care in the health systems of two US cities. Methods Cross-sectional analyses were performed using electronic health records (EHR) for 90,137 South Asians receiving care at New York University Langone in New York City (NYC) and 28,868 South Asians receiving care at Emory University (Atlanta). Diabetes was defined as having 2 + encounters with a diagnosis of diabetes, having a diabetes medication prescribed (excluding Acarbose/Metformin), or having 2 + abnormal A1C levels (≥ 6.5%) and 1 + encounter with a diagnosis of diabetes. Hypertension was defined as having 3 + BP readings of systolic BP ≥ 130 mmHg or diastolic BP ≥ 80 mmHg, 2 + encounters with a diagnosis of hypertension, or having an anti-hypertensive medication prescribed. Results Among South Asian patients at these two large, private health systems, age-adjusted diabetes burden was 10.7% in NYC compared to 6.7% in Atlanta. Age-adjusted hypertension burden was 20.9% in NYC compared to 24.7% in Atlanta. In Atlanta, 75.6% of those with diabetes had comorbid hypertension compared to 46.2% in NYC. Conclusions These findings suggest differences by region and sex in diabetes and hypertension risk. Additionally, these results call for better characterization of race/ethnicity in EHRs to identify ethnic subgroup variation, as well as intervention studies to reduce lifestyle exposures that underlie the elevated risk for type 2 diabetes and hypertension development in South Asians.

scholarly journals Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records

2018 ◽  
Vol 55 (6) ◽  
pp. 1492-1499 ◽  
Author(s):  
Alexander W. Forsyth ◽  
Regina Barzilay ◽  
Kevin S. Hughes ◽  
Dickson Lui ◽  
Karl A. Lorenz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Electronic Health Records ◽  
Learning Methods ◽  
Health Records ◽  
Cancer Symptoms ◽  
Machine Learning Methods ◽  
Electronic Health
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