Perioperative Nurses’ Perceptions Pre-Implementation of an Electronic Medical Record System

2021 ◽  
Author(s):  
Agnes Njane ◽  
Rebecca Jedwab ◽  
Rafael Calvo ◽  
Naomi Dobroff ◽  
Nicholas Glozier ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Care Delivery ◽  
Theoretical Domains Framework ◽  
Perioperative Nurses ◽  
Medical Record System ◽  
Focus Group Data ◽  
Emr Adoption ◽  
Facilitators And Barriers ◽  
Nurses Perceptions

The use of electronic medical record (EMR) systems is transforming health care delivery in hospitals. Perioperative nurses work in a unique high-risk health setting, hence require specific considerations for EMR implementation. This research explored perioperative nurses’ perceptions of facilitators and barriers to the implementation of an EMR in their workplace to make context-specific recommendations about strategies to optimise EMR adoption. Using a qualitative exploratory descriptive design, focus group data were collected from 27 perioperative nurses across three hospital sites. Thematic analyses revealed three themes: 1) The world is going to change; 2) What does it mean for me? and 3) We can do it, but we have some reservations. Mapping coded data to the Theoretical Domains Framework identified prominent facilitators and barriers, and informed recommended implementation strategies for EMR adoption by perioperative nurses.

scholarly journals Older Nurses’ Perceptions of an Electronic Medical Record Implementation

2021 ◽  
Author(s):  
Shaluni Tissera ◽  
Rebecca Jedwab ◽  
Rafael Calvo ◽  
Naomi Dobroff ◽  
Nicholas Glozier ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Psychological Factors ◽  
Mixed Methods Design ◽  
Sequential Mixed Methods ◽  
Group Data ◽  
Focus Group Data ◽  
Emr Adoption ◽  
Facilitators And Barriers ◽  
Nurses Perceptions

In Australia, almost 40% of nurses are aged 50 years and older. These nurses may be vulnerable to leaving the workforce due to challenges experienced during electronic medical record (EMR) implementations. This research explored older nurses’ perceptions of factors expected to influence their adoption of an EMR, to inform recommendations to support implementation. The objectives were to: 1) measure psychological factors expected to influence older nurses’ adoption of the EMR; and 2) explore older nurses’ perceptions of facilitators and barriers to EMR adoption. An explanatory sequential mixed methods design was used to collect survey and focus group data from older nurses, prior to introducing an EMR system. These nurses were highly engaged with their work; 79.3% reported high wellbeing scores. However, their motivation appeared to be predominantly governed by external rather than internal influences. Themes reflecting barriers to EMR and resistance to adoption emerged in the qualitative data.

Facilitators and Barriers to the Adoption of an Electronic Medical Record System by Intensive Care Nurses

2021 ◽  
Author(s):  
Somtochukwu Amaka Osajiuba ◽  
Rebecca Jedwab ◽  
Rafael Calvo ◽  
Naomi Dobroff ◽  
Nicholas Glozier ◽  
...  
Keyword(s):  
Intensive Care ◽  
Medical Record ◽  
Electronic Medical Record ◽  
New Technology ◽  
Electronic Medical Record System ◽  
Unintended Consequences ◽  
Record System ◽  
Medical Record System ◽  
Facilitators And Barriers ◽  
Nurses Perceptions

Introducing new technology, such as an electronic medical record (EMR) into an Intensive Care Unit (ICU), can contribute to nurses’ stress and negative consequences for patient safety. The aim of this study was to explore ICU nurses’ perceptions of factors expected to influence their adoption of an EMR in their workplace. The objectives were to: 1) measure psychological factors expected to influence ICU nurses’ adoption of EMR, and 2) explore perceptions of facilitators and barriers to the implementation of an EMR in their workplace. Using an explanatory sequential mixed method approach, data were collected using surveys and focus groups. ICU nurses reported high scores for motivation, work engagement and wellbeing. Focus group analyses revealed two themes: Hope the EMR will bring a new world and Fear of unintended consequences. Recommendations relate to strategies for education and training, environmental restructuring and enablement. Overall, ICU nurses were optimistic about EMR implementation.

scholarly journals Forecast of Outpatient Visits to a Tertiary Eyecare Network in India Using the EyeSmart Electronic Medical Record System

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 749
Author(s):  
Gumpili Sai Prashanthi ◽  
Nareen Molugu ◽  
Priyanka Kammari ◽  
Ranganath Vadapalli ◽  
Anthony Vipin Das
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Time Series Data ◽  
Resource Planning ◽  
Healthcare Services ◽  
Electronic Medical Record System ◽  
Series Data ◽  
Record System ◽  
Outpatient Visits ◽  
Medical Record System

India is home to 1.3 billion people. The geography and the magnitude of the population present unique challenges in the delivery of healthcare services. The implementation of electronic health records and tools for conducting predictive modeling enables opportunities to explore time series data like patient inflow to the hospital. This study aims to analyze expected outpatient visits to the tertiary eyecare network in India using datasets from a domestically developed electronic medical record system (eyeSmart™) implemented across a large multitier ophthalmology network in India. Demographic information of 3,384,157 patient visits was obtained from eyeSmart EMR from August 2010 to December 2017 across the L.V. Prasad Eye Institute network. Age, gender, date of visit and time status of the patients were selected for analysis. The datapoints for each parameter from the patient visits were modeled using the seasonal autoregressive integrated moving average (SARIMA) modeling. SARIMA (0,0,1)(0,1,7)7 provided the best fit for predicting total outpatient visits. This study describes the prediction method of forecasting outpatient visits to a large eyecare network in India. The results of our model hold the potential to be used to support the decisions of resource planning in the delivery of eyecare services to patients.

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