An Electronic Health Record Type 2 Diabetes Management Program Implementation and Outcomes in a Rural Practice

Type 2 diabetes mellitus is a chronic disease affecting 26 million people in the United States or 8.3% of the population. The prevalence of diabetes is rapidly increasing and increases with age. Treatment guidelines for Type 2 diabetes mellitus have been developed by the American Diabetes Association (2015) to decrease mortality and morbidity in patients with the disease. Utilization of current guidelines is a major component of providing evidence-based care. With the advent and widespread usage of electronic health records (EHR), a vehicle for point-of-care inclusion of accepted standardized guidelines exists. Including a reminder alert system within an existing EHR triggers providers to comply with current guidelines. Implementation of such a reminder system within a rural family medicine practice increased compliance with established guidelines. The guidelines measured in this study were blood pressure measurement at last visit, measurement of glycosylated hemoglobin within the last six months, and prescribed statin pharmacologic therapy. Glycosylated hemoglobin measurement increased by 16%, blood pressure measurement improved by 13%, and treatment with statin therapy increased by 16%. Implications for practice are inclusion of other Type 2 diabetes mellitus guidelines into the reminder alert system. Expansion of this system to iv include other chronic diseases with accepted evidence based guidelines may be designed and implemented based on this project

Strategies Rural Hospital Leaders Use to Implement Electronic Health Record

The Centers for Medicare and Medicaid Services issued over 144,000 payments totaling $7.1 billion to medical facilities that have adopted and successfully demonstrated meaningful use of certified electronic health record (EHR). Hospital organizations can increase cost savings by using the electronic components of EHRs to improve medical coding and reduce medical errors and transcription costs. Despite the incentives, some rural health care facilities are failing to progress. The purpose of this multiple case study was to explore the strategies rural hospital leaders used to implement an EHR. The target population consisted of rural hospital leaders who were involved in the successful implementation of an EHR in South Texas. The conceptual framework chosen for this study was the sociotechnical systems theory. Data were collected through telephone interviews using open-ended semistructured interviews with 5 participants from 4 rural hospitals who were involved in the EHR implementation. Data analysis occurred using Yin\u27s 5-step process which includes compiling, disassembling, reassembling, interpreting, and concluding. Data analysis included collecting information from government websites, company documents, and open-ended information to develop recurring themes. Several themes emerged including ongoing training, provider buy-in, constant communication, use of super users, and workflow maintenance. The findings could influence social change by making the delivery of health care more efficient and improving quality, safety, and access to health care services for patients

Use of electronic health record reminders to improve primary care providers’ colorectal cancer screening recommendations.

Background: Colorectal cancer (CRC) is the third most common worldwide cause of cancer morbidity and mortality. CRC mortality is preventable through regular screening. Electronic health record (EHR) reminders for providers can increase providers’ CRC screening recommendations and lead to earlier CRC diagnosis. According to the National Cancer Institute’s Screening and Risk Factors Report for Kentucky by County 2008-2010, 62.7% of adults in a rural Kentucky county aged 50-75 had completed a home based FOBT in the past two years or have ever had a colorectal endoscopy. Purpose: The purpose of this DNP project was to implement and evaluate an EHR CRC screening reminder for primary care providers (PCPs) at a rural Kentucky clinic. Methods: All PCPs at a rural Kentucky clinic were provided a one-on-one training session to review current CRC screening guidelines, discuss how to manage EHR reminders, and train on how to consistently document CRC screening status. The IT team was provided a virtual training session to review how to extract EHR data to determine which patients need a screening reminder and how to code in the EHR so that there will be an automatic provider screening recommendation reminder based on documented screening status. Intervention: EHR CRC screening reminders were inputted on all patients aged 45-75 who had been seen within the last three years and were not up to date with CRC screening based on documented screening status. Referrals were evaluated pre-intervention and compared to post-intervention data. CRC screening status documentation were evaluated post-intervention. Results: There was a +22.8% change pre-post in provider CRC screening recommendations (33.7%; 56.5% respectively). Only 8.2% of CRC screening recommendations were documented in the new area of the chart. Discussion: Implementing EHR CRC screening reminders provided a process that can increase CRC screening recommendations. In this study, 43.2% of patients were already up to date on CRC screening. 45.6% of patients refused CRC screening despite PCP recommendations being a key facilitator to screening updates. Keywords: Electronic health record reminders, colorectal cancer screening, primary car

Rapid health data repository allocation using predictive machine learning

Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Blockchain-based health record systems largely regulated by technology have emerged as another type of repository. Repositories for storing health data differ from one another based on cost, level of security and quality of performance. Not only has the type of repositories increased in recent years, but the quantum of health data to be stored has increased. For instance, the advent of wearable sensors that capture physiological signs has resulted in an exponential growth in digital health data. The increase in the types of repository and amount of data has driven a need for intelligent processes to select appropriate repositories as data is collected. However, the storage allocation decision is complex and nuanced. The challenges are exacerbated when health data are continuously streamed, as is the case with wearable sensors. Although patients are not always solely responsible for determining which repository should be used, they typically have some input into this decision. Patients can be expected to have idiosyncratic preferences regarding storage decisions depending on their unique contexts. In this paper, we propose a predictive model for the storage of health data that can meet patient needs and make storage decisions rapidly, in real-time, even with data streaming from wearable sensors. The model is built with a machine learning classifier that learns the mapping between characteristics of health data and features of storage repositories from a training set generated synthetically from correlations evident from small samples of experts. Results from the evaluation demonstrate the viability of the machine learning technique used. © The Author(s) 2020

Utilizing TIGER Competencies to Improve Informatics Practice

Nursing Informatics (NI) is quickly becoming an essential part of nursing. From the classroom, to the bedside, and to the boardroom, nurses across the nursing continuum are expected to use NI in their practice with the hopes of delivering better quality care to their patients. However, the training and education of NI provided to all levels of nurses is unable to keep up with the pace of technology. This project seeks to improve the NI competency of the nursing workforce at a pediatric hospital through an educational course using NI competencies identified by the Technology Informatics Guiding Educational Reform (TIGER) Initiative (2009). The value of this project is that it addresses the gap in NI education and competencies at a 265-bed pediatric hospital and creates a NI curriculum that is relevant, timely, and teaches nurses the essential skills to use NI to provide quality care and become a driver of patient quality outcomes

Finding a Cure: The Case for Regulation and Oversight of Electronic Health Record Systems

In the foreseeable future, it is likely that the familiar, paper-based patient medical files will become a thing of the past. On April 26, 24, President George W. Bush announced a plan to ensure that all Americans\u27 health records are computerized within ten years and to establish a National Health Information Network. Many advocates are enthusiastically promoting the adoption of health information technology (HIT) and electronic health record (HER) systems as a means to improve U.S. health care. HER systems often not only serve as record-keeping systems, but also have multiple capabilities, including drug ordering, decision support, alerts concerning patient allergies and potential drug interactions, reminders concerning routine tests, and various treatment management and data analysis tools. Because these capabilities require sophisticated software, significant risks of software failure exist, which can lead to life-threatening medical errors. Thus far, scholars have not provided a comprehensive assessment of the benefits and risks of this complex technology and evaluated the need for careful regulatory oversight akin to that required, in principle, by the FDA for life-critical medical devices. This paper begins to fill that gap. It analyzes HER systems from both legal and technical perspectives and focuses on how the law can be used as a tool to promote HIT. It is the first law journal article to provide an extensive proposal for regulations to maximize the technology\u27s benefits and reliability. We argue that the advantages of HER systems will outweigh their risks only if these systems are developed and maintained with rigorous adherence to best software engineering and medical informatics practices. To ensure that these goals are achieved, regulatory intervention is needed. The paper carefully delineates recommendations that address the questions of who should regulate HER systems and how they should be regulated, including their approval and continual monitoring. It also proposes requirements for several significant features, including decision support mechanisms, audit trails, and interoperability. Because HER systems are safety-critical, the public\u27s health and welfare will depend upon their effective oversight