scholarly journals The Effectiveness of Near-Field Communication Integrated with a Mobile Electronic Medical Record System: Emergency Department Simulation Study

10.2196/11187 ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. e11187 ◽  
Author(s):  
Kwang Yul Jung ◽  
Taerim Kim ◽  
Jaegon Jung ◽  
JeanHyoung Lee ◽  
Jong Soo Choi ◽  
...  
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Simulation Study ◽  
Near Field ◽  
Electronic Medical Record System ◽  
Near Field Communication ◽  
Record System ◽  
Medical Record System

scholarly journals Effectiveness of Near-field Communication Integrated with Mobile Electronic Medical Record System in Terms of Physician Turn-around Time in an Emergency Department: Simulation Study (Preprint)

2018 ◽  
Author(s):  
Kwang Yul Jung ◽  
Taerim Kim ◽  
Jaegon Jung ◽  
JeanHyoung Lee ◽  
Jong Soo Choi ◽  
...  
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Simulation Study ◽  
Near Field ◽  
Near Field Communication ◽  
Record System ◽  
System Usability Scale ◽  
Laboratory Results ◽  
Turn Around Time

BACKGROUND Mobile electronic medical record (EMR) systems are widely used based on the wide availability of smartphones; their ability to improve efficiency in medical practice has been demonstrated. However, the quantitative effectiveness of mobile EMR systems has rarely been measured. OBJECTIVE The aim of this study is to determine the effectiveness of near-field communication (NFC) integrated with a mobile EMR system in terms of physician turn-around time in an emergency department (ED). METHODS A simulation study was performed in an ED. 25 participants working in the ED participated in two scenarios, using mobile or a PC: one is locating randomly designated patients in the ED from the ED entrance, and the other is looking up the laboratory results of an ED patient at the bedside. Upon accomplishing the scenarios, participants responded to a 10 question questionnaire using a system usability scale (SUS). The main metric was turn-around time for each scenario. The secondary metric was the usability of the system, graded by the study subjects. RESULTS Locating patients from the ED entrance took 93.0 s (mean) using the mobile scenario, whereas it took 57.3 s (mean) using the PC scenario, which is significantly faster (P < .001). Searching for laboratory results of the patients at the bedside took 25.2 s (mean) using the mobile scenario, and 61.5 s (mean) using the PC scenario, which is significant (P < .001). Sensitivity analysis comparing only the time for login and looking up the relevant information also found mobile to be significantly faster. The mean SUS score of NFC-mobile EMR was 71.9 points. CONCLUSIONS NFC integrated with mobile EMR helped physician practice to be more efficient, with good usability. CLINICALTRIAL IRB File No - SMC 2018-01-144-001

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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