Background: In order to proactively manage congestive heart failure (CHF) patients, an effective CHF case finding algorithm is required to process both structured and unstructured electronic medical records (EMR) to allow complementary and cost-efficient identification of CHF patients.
Methods And Results: We set to identify CHF cases from both EMR codified and natural language processing (NLP) found cases. Using narrative clinical notes from all Maine Health Information Exchange (HIE) patients, the NLP case finding algorithm was retrospectively (July 1, 2012-June 30, 2013) developed with a random subset of HIE associated facilities, and blind-tested with the remaining facilities. The NLP based method was integrated into a live HIE population exploration system and validated prospectively (July 1, 2013-June 30, 2014). Total of 18,295 codified CHF patients were included in Maine HIE. Among the 253,803 subjects without CHF codings, our case finding algorithm prospectively identified 2411 uncodified CHF cases. The positive predictive value (PPV) is 0.914, and 70.1% of these 2411 cases were found to be with CHF histories in the clinical notes.
Conclusions: A CHF case finding algorithm was developed, tested and prospectively validated. The successful integration of the CHF case findings algorithm into the Maine HIE live system is expected to improve the Maine CHF care.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ijmedinf.2015.06.007 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Research on truck-drone collaborative route planning for rural logistics delivery services.
Sci Rep
December 2024
Department of Production Engineering, KTH Royal Institute of Technology, 11428, Stockholm, Sweden.
This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics.
View Article and Find Full Text PDFA Greedy Tabu Dual Heuristic algorithm for the cyclic pickup and delivery problem with 3D loading constraints.
Sci Rep
December 2024
Shandong University of Science and Technology, College of Transportation, Qingdao, 266590, China.
The optimization of auto parts supply chain logistics plays a decisive role in the development of the automotive industry. To reduce logistics costs and improve transportation efficiency, this paper addresses the joint optimization problem of multi-vehicle pickup and delivery transportation paths under time window constraints, coupled with the three-dimensional loading of goods. The model considers mixed time windows, three-dimensional loading constraints, cyclic pickup and delivery paths, varying vehicle loads and volumes, flow balance, and time window constraints.
View Article and Find Full Text PDFBidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
View Article and Find Full Text PDFIncreased expression of plasma mir-9-3p and let-7b-3p in methamphetamine use disorder and its clinical significance.
Sci Rep
December 2024
Department of Drug Prohibition and Public Security, Criminal Investigation Police University of China, Shenyang, 110035, China.
Methamphetamine use disorder has emerged as a significant public health concern globally. This study endeavors to elucidate the alterations in expression changes of miRNAs in the plasma of methamphetamine use disorder and elucidate the alterations in miRNA expression in the plasma of individuals with methamphetamine use disorder and investigate the relationship between these differentially expressed miRNAs and the disorder itself, cravings for methamphetamine, and associated mental disorders. Furthermore, the study seeks to clarify the expression of downstream target molecules of specific miRNAs in the plasma of methamphetamine use disorder, assess the diagnostic utility of these miRNAs and their target molecules, explore their potential as biomarkers, and identify potential targets for the diagnosis and treatment of methamphetamine use disorder.
View Article and Find Full Text PDFDifferential effects of fine particulate matter constituents on acute coronary syndrome onset.
Nat Commun
December 2024
School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, China.
Fine particulate matter has been linked with acute coronary syndrome. Nevertheless, the key constituents remain unclear. Here, we conduct a nationwide case-crossover study in China during 2015-2021 to quantify the associations between fine particulate matter constituents (organic matter, black carbon, nitrate, sulfate, and ammonium) and acute coronary syndrome, and to identify the critical contributors.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!