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Tag: electronic health record
03/15/2023

ONC: Majority of Office-Based Physicians Used Telehealth in 2021

Article Excerpt: A report from the Office of the National Coordinator for Health Information Technology found that telehealth use grew noticeably over the course of the COVID-19 pandemic, with high rates of not only provider adoption but also satisfaction. Throughout the COVID-19 pandemic, it became apparent that telehealth was an effective method for providing and receiving care. However, as the severity of the public health emergency diminished, questions surrounding telehealth and its continued use arose.

Full Article: https://tinyurl.com/4cru2w4c

Article Source: mHealth Intelligence

Posted in: Methodologies & Analytics // Tagged: ; ; ; ; ;
12/06/2022

The Future of Medical Technology: Key Trends in Virtual Care and Telemedicine

Article Excerpt: From Internet of Things (IoT) technology and electronic medical records (EMR) in hospitals, to remote patient monitoring devices, the industry is finding new ways to provide patients with better care. nnovations in virtual care have been explored for years, but the COVID-19 pandemic increased demand exponentially as patients were unable to attend in-person appointments. Whilst face-to-face clinic visits will not be entirely replaced, several key trends are anticipated in virtual care and telemedicine for 2022 and beyond.

Full Article: https://tinyurl.com/y5vaeazj

Article Source: Medical Device Network

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ;
10/17/2022

Designing an electronic medical record alert to identify hospitalised patients with HIV: successes and challenges

El-Nahal W, Grader-Beck T, Gebo K, Holmes E, Herne K, Moore R, Thompson D, Berry S. Designing an electronic medical record alert to identify hospitalised patients with HIV: successes and challenges. BMJ Health Care Inform 2022;29:e100521. doi:10.1136/bmjhci-2021-100521

An electronic medical record (EMR) alert system was developed to use readily available data elements to accurately identify hospitalized people with HIV. Authors described the design and implementation of the EMR alert and methods to evaluate its accuracy for identifying people with HIV. Over 24 months, the EMR alert was used to notify an intervention team and data abstraction team in real time about admissions of people with HIV. Sensitivity was assessed by comparing the machine-learning alert system to manual chart reviews. Positive predictive value (probability that a patient with a positive test result actually has the disease), was assessed by false positives identified in chart review (not having HIV despite alert triggering). Results demonstrated high sensitivity (sensitivity=100%, 95% CI 82-100%) and good predictive value (84%, 95% CI 82-86%). A combination of data (diagnosis, prescriptions, and lab orders) in the EMR alert system achieved high sensitivity and positive predictive value in identifying people with HIV. ICD Code diagnoses were the strongest contributors to predictive value, compared to the other criteria. Use of data-driven alerts in electronic health record systems can facilitate the deployment of multidisciplinary teams for medication review, education, case management, and outpatient linkage to follow-up.

Posted in: Cutting Edge Literature // Tagged: ; ; ; ; ;
09/22/2022

Artificial Intelligence Tools Quickly Detect Signs of Injection Drug Use in Patients’ Health Records

Article Excerpt: An automated process that combines natural language processing and machine learning identified people who inject drugs (PWID) in electronic health records more quickly and accurately than current methods that rely on manual record reviews. Currently, people who inject drugs are identified through International Classification of Diseases (ICD) codes that are specified in patients’ electronic health records by the health care providers or extracted from those notes by trained human coders who review them for billing purposes. But there is no specific ICD code for injection drug use, so providers and coders must rely on a combination of non-specific codes as proxies to identify PWIDs—a slow approach that can lead to inaccuracies.

Full Article: https://tinyurl.com/2p9b7wc3

Article Source: Medical XPress

Posted in: Emerging Technologies, Methodologies & Analytics // Tagged: ; ; ; ; ; ;
08/24/2022

ONC, CDC say Integration Framework Can Combat Opioid Crisis

Article Excerpt: For the past five years, the Office of the National Coordinator for Health IT and the Centers for Disease Control and Prevention have been working together on an interactive resource for states and health systems called the Integration Framework. The tool is meant to give guidance to help improve integration of state prescription drug monitoring programs (PDMPs) within clinicians’ workflows. It includes best practices for implementing advanced clinical decision support systems to help flag potential opioid abuse, and it outlines steps to help advance and scale PDMP integration with IT systems, such as electronic health records, health information exchanges and pharmacy systems.

Full Article: https://tinyurl.com/2w5z9smr

Article Source: Health IT News

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ;
08/19/2022

HIMSSCast: Using EHRs to Confront the Opioid Crisis

Article Excerpt: Electronic health records systems are at the core of health IT. They are essential tools in the delivery of healthcare. Further, they can be used to help solve complex healthcare problems. This HIMSSCast podcast focuses on how EHRs can be used to fight the opioid crisis in the United States. The guest is David Bucciferro, vice chair of the Electronic Health Record Association. He also is co-chair of the EHRA’s Opioid Crisis Task Force and a special advisor to Foothold Technology.

Full Article: https://tinyurl.com/2nrw526r

Article Source: Healthcare IT News

Posted in: Emerging Technologies // Tagged: ; ; ;
07/11/2022

Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): A retrospective deep learning study

Afshar M, Sharma B, Dligach D, Oguss M, Brown R, Chhabra N, Thompson HM, Markossian T, Joyce C, Churpek MM, & Karnik NS (2022). Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study. The Lancet (British Edition), 4(6), e426–e435. https://doi.org/10.1016/S2589-7500(22)00041-3

SMART-AI is a substance misuse algorithm to support referral to treatment using artificial intelligence. The tool is a machine learning classifier tool for identifying alcohol misuse, opioid misuse, and non-opioid drug misuse using clinical notes collected in the electronic health records. Using of patients (N=16,917) during the first 24 hours of hospitalization, the prospective primary analysis consisted of temporal validation done to examine misuse classification and the association to outcomes and treatment referrals. Results from manual screening identified 3.5% of patients had any type of substance misuse and 11% of these patients had more than one type of misuse. SMART-AI showed good calibration and validity, with a false negative rate of 0.18-0.19 and a false positive rate of 0.03 between non-Hispanic Black and non-Hispanic White subgroups. The results also show prediction performance can change over time or in differing patient settings, where prevalence of substance misuse varies. There were also significant changes during the COVID-19 pandemic which required the algorithm to be recalibrated. Overall, this study demonstrated that clinical notes from the electronic health record during initial hospitalization can be used to identify substance misuse accurately with the help of artificial intelligence and may be used to potentially improve screening rates.

Posted in: Cutting Edge Literature // Tagged: ; ; ; ; ; ;
06/27/2022

Digital Tool Helps Emergency Department Doctors Treat Opioid Use Disorder

Article Excerpt: Emergency departments (EDs) are an important point of care for people with opioid use disorder. But EDs in the United States have been slow to meet patient needs for opioid use treatments like buprenorphine, past research shows. A new tool developed by Yale researchers aims to close this gap by helping physicians feel more prepared to offer these medications. In a recent trial, the researchers found that the tool — called EMergency department-initiated BuprenorphinE for opioid use Disorder (EMBED) — increased the number of physicians initiating buprenorphine treatment in the ED. Their findings were reported June 27 in the BMJ, a global medical journal.

Full Article: https://tinyurl.com/2p9ej3sj

Article Source: Yale News

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ; ;
04/14/2022

New Bill Aims to Improve Behavioral Health IT Adoption

Article Excerpt: An April 6 press release announced that Congresswoman Doris Matsui (D-CA) and Congressman Markwayne Mullin (R-OK) introduced a new act focused on improving behavioral health providers are not left behind when it comes to health information technology, including electronic health records (EHRs). The act, dubbed The Behavioral Health Information Technologies (BHIT) Now Act, aims to coordinate mental and physical health are by supporting behavioral health providers to adopt health IT systems.

Full Article: https://tinyurl.com/y7b5urue

Article Source: Healthcare Innovation

Posted in: Regulation & Policy // Tagged: ; ; ; ;