Medicare meets the cloud: the development of a secure platform for the storage and analysis of claims data.

Introduction: Cloud-based solutions are a modern-day necessity for data intense computing. This case report describes in detail the development and implementation of Amazon Web Services (AWS) at Emory-a secure, reliable, and scalable platform to store and analyze identifiable research data from the Centers for Medicare and Medicaid Services (CMS).

Materials And Methods: Interdisciplinary teams from CMS, MBL Technologies, and Emory University collaborated to ensure compliance with CMS policy that consolidates laws, regulations, and other drivers of information security and privacy.

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives.

Background: Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap.

An AdaBoost-based algorithm to detect hospital-acquired pressure injury in the presence of conflicting annotations.

Hospital-acquired pressure injury is one of the most harmful events in clinical settings. Patients who do not receive early prevention and treatment can experience a significant financial burden and physical trauma. Several hospital-acquired pressure injury prediction algorithms have been developed to tackle this problem, but these models assume a consensus, gold-standard label (i.

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives.

Background: Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap.

Radiation Oncologist Shortage Creates Opportunity for NPs.

A 50% estimated increase in new cancer cases over the next few decades will significantly challenge health care systems already strained by a shortage of oncology providers. Radiation oncology (RO), 1 of 3 three primary pillars of oncology care, treats half of all new cancer cases. Workforce shortages, reimbursement changes, delays in patient treatment, and the lack of follow-up care all continue to increase pressure on RO centers to boost efficiency, improve patient and staff retention, and strive for service satisfaction.

Evaluating Natural Language Processing Packages for Predicting Hospital-Acquired Pressure Injuries From Clinical Notes.

Incidence of hospital-acquired pressure injury, a key indicator of nursing quality, is directly proportional to adverse outcomes, increased hospital stays, and economic burdens on patients, caregivers, and society. Thus, predicting hospital-acquired pressure injury is important. Prediction models use structured data more often than unstructured notes, although the latter often contain useful patient information.

Evaluation of available risk scores to predict multiple cardiovascular complications for patients with type 2 diabetes mellitus using electronic health records.

Aims: Various cardiovascular risk prediction models have been developed for patients with type 2 diabetes mellitus. Yet few models have been validated externally. We perform a comprehensive validation of existing risk models on a heterogeneous population of patients with type 2 diabetes using secondary analysis of electronic health record data.

Hepatitis C care cascade in a large academic healthcare system, 2012 to 2018.

To determine the hepatitis C virus (HCV) care cascade among persons who were born during 1945 to 1965 and received outpatient care on or after January 2014 at a large academic healthcare system. Deidentified electronic health record data in an existing research database were analyzed for this study. Laboratory test results for HCV antibody and HCV ribonucleic acid (RNA) indicated seropositivity and confirmatory testing.

A Comprehensive and Improved Definition for Hospital-Acquired Pressure Injury Classification Based on Electronic Health Records: Comparative Study.

Background: Patients develop pressure injuries (PIs) in the hospital owing to low mobility, exposure to localized pressure, circulatory conditions, and other predisposing factors. Over 2.5 million Americans develop PIs annually.

State of DNP education: Lessons learned from a novel academic fellowship in teaching and education.

Objective: We examine the gap between the current and desired state of Doctor of Nursing Practice (DNP) education from the perspective of postdoctoral (DNP) teaching and education fellows.

Observations: In the assessment of the DNP Essentials framework, command of scholarly and scientific writing, ability to demonstrate critical thought, and significant variation in clinical experience among DNP graduates are top concerns.

Discussion: These inconsistencies are problematic to the professional and public value of this terminal degree in nursing.

GASP: Graph-based Approximate Sequential Pattern Mining for Electronic Health Records.

Sequential pattern mining can be used to extract meaningful sequences from electronic health records. However, conventional sequential pattern mining algorithms that discover all frequent sequential patterns can incur a high computational and be susceptible to noise in the observations. Approximate sequential pattern mining techniques have been introduced to address these shortcomings yet, existing approximate methods fail to reflect the true frequent sequential patterns or only target single-item event sequences.

Examining the Concordance in the Documented Pressure Injury Site, Stage, and Count in Medical Information Mart for Intensive Care-III.

Objectives: This study aimed to compare the concordance of pressure injury (PI) site, stage, and count documented in electronic health records (EHRs); explore if PI count during each patient hospitalization is consistent based on PI site or stage count in the diagnosis or chart event records; and examine if discrepancies in PI count were associated with patient characteristics.

Methods: Hospitalization records with the International Classification of Diseases ninth edition (ICD-9) codes, chart events from two systems (CareVue, MetaVision), and clinical notes on PI were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database. PI site and stage counts from individual hospitalization were computed.

Grady Health System's Mobile Integrated Health Program: A Statistical Analysis of Low-Acuity 911 Calls.

Grady's Mobile Integrated Health (MIH) program works to manage outpatient health concerns that otherwise burden EDs, improve quality of care, and connect patients to the appropriate level of care and resources. This prospective study collected data from 09/01/2019-03/31/2020 to analyze Grady's MIH response to low-acuity 911 calls compared to a traditional EMS (ACLS/BLS) response. A total of 2,759 EMS calls were reviewed.

Privacy-preserving Sequential Pattern Mining in distributed EHRs for Predicting Cardiovascular Disease.

From electronic health records (EHRs), the relationship between patients' conditions, treatments, and outcomes can be discovered and used in various healthcare research tasks such as risk prediction. In practice, EHRs can be stored in one or more data warehouses, and mining from distributed data sources becomes challenging. Another challenge arises from privacy laws because patient data cannot be used without some patient privacy guarantees.

Toolkit for Best Practice Use of Electronic Health Record Data in Quality Improvement.

This project piloted an educational intervention focused on use and management of EHR data by Doctor of Nursing Practice students in quality improvement initiatives. Recommendations from academic and clinical nursing promote the integration of EHR data findings into practice. Nursing's general lack of understanding about how to use and manage data is a barrier to using EHR data to guide quality improvement initiatives.

Predictors of progression through the cascade of care to a cure for hepatitis C patients using decision trees and random forests.

Background: This study uses machine learning techniques to identify sociodemographic and clinical predictors of progression through the hepatitis C (HCV) cascade of care for patients in the 1945-1965 birth cohort in the Southern United States.

Methods: We compared sociodemographic and clinical variables between groups of patients for three care outcomes: linkage to care, initiation of antiviral treatment, and virologic cure. A decision tree model and random forest model were built for each outcome.

A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care.

Background: There is wide recognition that, with the rapid implementation of electronic health records (EHRs), large data sets are available for research. However, essential standardized nursing data are seldom integrated into EHRs and clinical data repositories. There are many diverse activities that exist to implement standardized nursing languages in EHRs; however, these activities are not coordinated, resulting in duplicate efforts rather than building a shared learning environment and resources.