scholarly journals Digital transformation of the emergency department-inpatient interface (EDii): integration for future innovation

2020 ◽  
Vol 44 (5) ◽  
pp. 666
Author(s):  
Andrew Staib ◽  
Clair Sullivan ◽  
Cara Joyce Cabilan ◽  
Rohan Cattell ◽  
Rob Eley
Keyword(s):  
Electronic Medical Records ◽  
Patient Outcomes ◽  
Medical Records ◽  
Emergency Admission ◽  
Tertiary Hospital ◽  
Digital Transformation ◽  
Relative Reduction ◽  
Process Measures ◽  
The Impact

As the focus of clinicians and government shifts from speciality-based care to system-based key performance indicators such as the National Emergency Access Target (NEAT) or the 4-h rule, integration between emergency department (ED) and inpatient clinical workflows and information systems is becoming increasingly necessary. Such system measures drive the implementation of integrated electronic medical records (ieMR) to digitally integrate these workflows. The objective of this case study was to describe the impact of digital transformation of the ED–in-patient interface (EDii) of a large tertiary hospital on process measures and clinical outcomes for patients requiring emergency admission to hospital. Data were collected from routine clinical and administrative information systems to measure process and clinical outcome measures, including ED length of stay, compliance with the 4-h rule and in-patient mortality between 28 November 2014 and 28 February 2017. The 4-h rule compliance for all patients, as well as for the EDii group (admitted to hospital excluding short stay ward), declined after digitisation. There were 55 fewer deaths in the postintervention group (15% relative reduction; P = 0.02) and a 10% relative reduction in adjusted mortality as measured by the Hospital Standardised Mortality Ratio for emergency patients (eHSMR), which did not reach statistical significance. Digital deceleration in ED performance did occur with an ieMR rollout, but worsening of key patient outcomes was not observed. What is known about this topic? Much has been written about the introduction of electronic medical records (EMRs) in emergency departments. This work sits alongside a substantial body of evidence outlining the relationship between process measures of ED performance and important patient outcomes. However, much less is known about the impact of digital transformation on the complex adaptive system that is the EDii and the impact of digitisation on the vulnerable group of patients who require emergency admission to hospital. What does this paper add? The objective of this case study was to describe the effect of a rapid rollout of an integrated EMR. This EMR simultaneously transformed care delivery both in the ED and the inpatient space and impacted on the politically and clinically sensitive performance and outcome measures of the EDii in a large tertiary hospital. The present study is the first that specifically examined the effect of digitisation at the EDii. What are the implications for practitioners? The understanding that digital deceleration will occur, but that with good patient outcome monitoring worsening of key patient outcomes is not likely to occur, now holds a key place in digital transformation planning. The measures of the EDii examined in this case study provide a foundation for this montoring.

scholarly journals The impact of the COVID-19 pandemic on digital globalization

2021 ◽  
Vol 129 ◽  
pp. 06008
Author(s):  
Maria Loredana Popescu ◽  
Svetlana Platagea Gombos ◽  
Sorin Burlacu ◽  
Amza Mair
Keyword(s):  
Global Economy ◽  
World Economy ◽  
Value Added ◽  
Digital Transformation ◽  
Lessons Learned ◽  
Health Crisis ◽  
Main Research ◽  
Documentary Analysis ◽  
The Impact

Research background: After more than a year of the Covid-19 pandemic, we can investigate whether it caused a shock to the global economy, pushing for deglobalization, or on the contrary, it was a challenge for digital globalization and digital transformation of economies. Through this research we join the research contributions that examine the process towards digital globalization that characterizes the world economy, its impact on businesses, consumers, and governments. We also discuss the challenges posed by the crisis caused by the coronavirus pandemic to globalization and perhaps the acceleration of the digital transformation of economies. Purpose of the article: The aim of this research is to highlight the impact of the COVID-19 pandemic in the age of digital globalization. Methods: Documentary analysis, as the main research method, is doubled by a case study that allows us to highlight the specific characteristics of digital globalization. Findings & Value added: The findings of the research allowed us to highlight the essential aspects of digital globalization that were perhaps exacerbated by the Covid-19 pandemic, but which contribute greatly to understanding the phenomenon of globalization. Our research also reveals four lessons learned in the COVID-19 pandemic. We also present some considerations regarding the globalization after the health crisis.

scholarly journals Predicting bloodstream infection outcome using machine learning

2021 ◽  
Author(s):  
Yazeed Zoabi ◽  
Orli Kehat ◽  
Dan Lahav ◽  
Ahuva Weiss-Meilik ◽  
Amos Adler ◽  
...  
Keyword(s):  
Electronic Medical Records ◽  
Patient Outcomes ◽  
Medical Records ◽  
Bloodstream Infections ◽  
Operating Characteristics ◽  
Is Implementation ◽  
Adverse Health Outcomes ◽  
Receiver Operating Characteristics Curve ◽  
History Of ◽  
Poor Outcomes

Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of patients at high risk of poor outcomes of BSI is important for earlier decision making and effective patient stratification. We developed electronic medical record-based ma-chine learning models that predict patient outcomes of BSI. The area under the receiver-operating characteristics curve was 0.82 for a full featured inclusive model, and 0.81 for a compact model using only 25 features. Our models were trained, using electronic medical records that include demographics, blood tests, and the medical and diagnosis history of 7,889 hospitalized patients diagnosed with BSI. Among the implications of this work is implementation of the models as a basis for selective rapid microbiological identification, toward earlier administration of appropriate antibiotic therapy. Additionally, our models may help reduce the development of BSI and its associated adverse health outcomes and complications.

Electronic Medical Records and Public Perceptions

2013 ◽  
Vol 8 (3) ◽  
pp. 38-57
Author(s):  
Tarik Abdel-Monem ◽  
Mitchel N. Herian ◽  
Nancy Shank
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Online Survey ◽  
Public Attitudes ◽  
Public Perceptions ◽  
Deliberative Discussion ◽  
The Impact ◽  
Opinion Polls

Public attitudes about electronic medical records (EMRs) have been primarily gauged by one-time opinion polls. The authors investigated the impact of an interactive deliberative polling process on general attitudes towards EMRs and perceptions of governmental roles in the area. An initial online survey was conducted about EMRs among a sample of respondents (n = 138), and then surveyed a sub-sample after they had engaged in a deliberative discussion about EMR issues with peers and policymakers (n = 24). Significant changes in opinions about EMRs and governmental roles were found following the deliberative discussion. Overall support for EMRs increased significantly, although concerns about security and confidentiality remained. This indicates that one way to address concerns about EMRs is to provide opportunities for deliberation with policymakers. The policy and theoretical implications of these findings are briefly discussed within.

scholarly journals ELECTRONIC MEDICAL RECORD ALGORITHM TO IDENTIFY UNDIAGNOSED (PRE)DIABETES: A CASE STUDY FROM HAWAIʻI

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S934-S934
Author(s):  
David Stupplebeen ◽  
Tetine L Sentell ◽  
Lance Ching ◽  
Blythe Nett ◽  
Hermina Taylor ◽  
...  
Keyword(s):  
Older Adults ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Laboratory ◽  
Older Men ◽  
State Health ◽  
Missed Opportunities ◽  
The Past ◽  
Department Of Health

Abstract An estimated one-quarter of United States’ older adults (≥65 years) have diabetes (DM) while half have prediabetes (PreDM). Timely diagnosis can prevent disease progression, but significant proportions of PreDM/DM are undiagnosed. Among Hawai‘i adults, one-third of diabetes and two-thirds of prediabetes cases are undiagnosed; rates for older adults are unknown. Algorithms integrated into Electronic Medical Records (EMR) may improve care by identifying probable undiagnosed cases in patient panels using clinical/laboratory measures. We assessed one algorithm developed by the Hawai‘i Department of Health that identified individuals overdue for screening or with Pre/DM using the records of 20,362 adult patients (51.33% were >65) from a major state health system. 6,371 (31.3%) patients were excluded from analysis; they had no HbA1c screening in the past year or were overdue for screening (70%) based on standard guidelines. Of the remaining 13,991 patients, 7317 were older adults; 6130 (84%) had a PreDM (50.6%) or DM (33.2%) HbA1c value; the rest were controlled or false-positive. Of those older adults with probable PreDM/DM, 38.6% were undiagnosed. Adults >65 were significantly more likely to be flagged with undiagnosed PreDM compared to their younger counterparts (58 versus 54%, p<.001). Notably, 61% of older men flagged with PreDM were undiagnosed. Of the 5,737 patients identified with DM, 22% of those 65 were undiagnosed. Given the recognized high burden of diabetes among older adults, results indicate substantial missed opportunities for the prevention and early treatment of this condition as identified by an EMR algorithm.

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