Dataset Information

Improvements in Patient Acceptance by Hospitals Following the Introduction of a Smartphone App for the Emergency Medical Service System: A Population-Based Before-and-After Observational Study in Osaka City, Japan.

ABSTRACT:

Background

Recently, the number of ambulance dispatches has been increasing in Japan, and it is therefore difficult for hospitals to accept emergency patients smoothly and appropriately because of the limited hospital capacity. To facilitate the process of requesting patient transport and hospital acceptance, an emergency information system using information technology (IT) has been built and introduced in various communities. However, its effectiveness has not been thoroughly revealed. We introduced a smartphone app system in 2013 that enables emergency medical service (EMS) personnel to share information among themselves regarding on-scene ambulances and the hospital situation.

Objective

The aim of this study was to assess the effects of introducing this smartphone app on the EMS system in Osaka City, Japan.

Methods

This retrospective study analyzed the population-based ambulance records of Osaka Municipal Fire Department. The study period was 6 years, from January 1, 2010 to December 31, 2015. We enrolled emergency patients for whom on-scene EMS personnel conducted hospital selection. The main endpoint was the difficulty experienced in gaining hospital acceptance at the scene. The definition of difficulty was making ?5 phone calls by EMS personnel at the scene to hospitals until a decision to transport was determined. The smartphone app was introduced in January 2013, and we compared the patients treated from 2010 to 2012 (control group) with those treated from 2013 to 2015 (smartphone app group) using an interrupted time-series analysis to assess the effects of introducing this smartphone app.

Results

A total of 600,526 emergency patients for whom EMS personnel selected hospitals were eligible for our analysis. There were 300,131 emergency patients in the control group (50.00%, 300,313/600,526) from 2010 to 2012 and 300,395 emergency patients in the smartphone app group (50.00%, 300,395/600,526) from 2013 to 2015. The rate of difficulty in hospital acceptance was 14.19% (42,585/300,131) in the control group and 10.93% (32,819/300,395) in the smartphone app group. No change over time in the number of difficulties in hospital acceptance was found before the introduction of the smartphone app (regression coefficient: -2.43, 95% CI -5.49 to 0.64), but after its introduction, the number of difficulties in hospital acceptance gradually decreased by month (regression coefficient: -11.61, 95% CI -14.57 to -8.65).

Conclusions

Sharing information between an ambulance and a hospital by using the smartphone app at the scene was associated with decreased difficulty in obtaining hospital acceptance. Our app and findings may be worth considering in other areas of the world where emergency medical information systems with IT are needed.

SUBMITTER: Katayama Y

PROVIDER: S-EPMC5616023 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improvements in Patient Acceptance by Hospitals Following the Introduction of a Smartphone App for the Emergency Medical Service System: A Population-Based Before-and-After Observational Study in Osaka City, Japan.

Katayama Yusuke Y Kitamura Tetsuhisa T Kiyohara Kosuke K Iwami Taku T Kawamura Takashi T Kawamura Takashi T Izawa Junichi J Gibo Koichiro K Komukai Sho S Hayashida Sumito S Kiguchi Takeyuki T Ohnishi Mitsuo M Ogura Hiroshi H Shimazu Takeshi T

JMIR mHealth and uHealth 20170911 9

<h4>Background</h4>Recently, the number of ambulance dispatches has been increasing in Japan, and it is therefore difficult for hospitals to accept emergency patients smoothly and appropriately because of the limited hospital capacity. To facilitate the process of requesting patient transport and hospital acceptance, an emergency information system using information technology (IT) has been built and introduced in various communities. However, its effectiveness has not been thoroughly revealed. ...[more]

PMID: 28893725

Similar Datasets

Project description:Background and purposeConsidering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion-associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stroke center offers an intriguing option for optimizing patient pathways.MethodsThis prospective in-field validation study included 200 patients with suspected acute ischemic stroke who were admitted by emergency medical service to a comprehensive stroke center. Ambulances were equipped with smartphones running an app-based Field Assessment Stroke Triage for Emergency Destination scale for transmission prior to admission. The primary measure was the predictive accuracy of the transmitted Field Assessment Stroke Triage for Emergency Destination for large vessel occlusion and the secondary measure the predictive accuracy for endovascular treatment.ResultsA Field Assessment Stroke Triage for Emergency Destination ⩾4 revealed very good accuracy to detect large vessel occlusion-related acute ischemic stroke with a sensitivity of 82.4% (95% confidence interval = 65.5-93.2), specificity of 78.3% (95% confidence interval = 71.3-84.3), and an area under the curve c-statistics of 0.89 (95% confidence interval = 0.85-0.94). Field Assessment Stroke Triage for Emergency Destination ⩾4 correctly identified 84% of patients who received endovascular treatment [73.5% specificity (95% confidence interval = 66.4-79.8)] with an area under the curve c-statistics of 0.82 (95% confidence interval = 0.74-0.89). In a hypothetical triage model of an urban setting, one secondary transportation would be avoided with every fifth patient screened.ConclusionA smartphone app-based stroke triage completed by emergency medical service personnel showed adequate quality for the Field Assessment Stroke Triage for Emergency Destination to identify large vessel occlusion-associated acute ischemic stroke. We demonstrate feasibility of the use of a medical messaging service in prehospital stroke care. Based on these first results, a randomized trial evaluating the clinical benefit of such a triage system in an urban setting is currently in preparation.Clinical Trial Registration: https://clinicaltrials.gov Unique identifier: NCT04404504.

Project description:BACKGROUND:The majority of middle-aged to older patients with chronic conditions report forgetting to take medications as prescribed. The promotion of patients' smartphone medication reminder app (SMRA) use shows promise as a feasible and cost-effective way to support their medication adherence. Providing training on SMRA use, guided by the technology acceptance model (TAM), could be a promising intervention to promote patients' app use. OBJECTIVE:The aim of this pilot study was to (1) assess the feasibility of an SMRA training session designed to increase patients' intention to use the app through targeting perceived usefulness of app, perceived ease of app use, and positive subjective norm regarding app use and (2) understand the ways to improve the design and implementation of the training session in a hospital setting. METHODS:A two-group design was employed. A total of 11 patients older than 40 years (median=58, SD=9.55) and taking 3 or more prescribed medications took part in the study on one of two different dates as participants in either the training group (n=5) or nontraining group (n=6). The training group received an approximately 2-hour intervention training session designed to target TAM variables regarding one popular SMRA, the Medisafe app. The nontraining group received an approximately 2-hour control training session where the participants individually explored Medisafe app features. Each training session was concluded with a one-time survey and a one-time focus group. RESULTS:Mann-Whitney U tests revealed that the level of perceived ease of use (P=.13) and the level of intention to use an SMRA (P=.33) were higher in the training group (median=7.00, median=6.67, respectively) than in the nontraining group (median=6.25, median=5.83). However, the level of perceived usefulness (U=4.50, Z=-1.99, P=.05) and the level of positive subjective norm (P=.25) were lower in the training group (median=6.50, median=4.29) than in the nontraining group (median=6.92, median=4.50). Focus groups revealed the following participants' perceptions of SMRA use in the real-world setting that the intervention training session would need to emphasize in targeting perceived usefulness and positive subjective norm: (1) the participants would find an SMRA to be useful if they thought the app could help address specific struggles in medication adherence in their lives and (2) the participants think that their family members (or health care providers) might view positively the participants' SMRA use in primary care settings (or during routine medical checkups). CONCLUSIONS:Intervention training session, guided by TAM, appeared feasible in targeting patients' perceived ease of use and, thereby, increasing intention to use an SMRA. Emphasizing the real-world utility of SMRA, the training session could better target patients' perceived usefulness and positive subjective norm that are also important in increasing their intention to use the app.

Project description:The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Project description:BackgroundThere is strong evidence suggesting that higher levels of cardiorespiratory fitness (CRF) are associated with a healthier metabolic profile, and that CRF can serve as a powerful predictor of morbidity and mortality. In this context, a smartphone app based on the 2-km walk test (UKK test) would provide the possibility to assess CRF remotely in individuals geographically distributed around a country or continent, and even between continents, with minimal equipment and low costs.ObjectiveThe overall aim of this study was to evaluate the validity and reliability of 2kmFIT-App developed for Android and iOS mobile operating systems to estimate maximum oxygen consumption (VO2max) as an indicator of CRF. The specific aims of the study were to determine the validity of 2kmFIT-App to track distance and calculate heart rate (HR).MethodsTwenty participants were included for field-testing validation and reliability analysis. The participants completed the UKK test twice using 2kmFIT-App. Distance and HR were measured with the app as well as with accurate methods, and VO2max was estimated using the UKK test equation.ResultsThe validity results showed the following mean differences (app minus criterion): distance (-70.40, SD 51.47 meters), time (-0.59, SD 0.45 minutes), HR (-16.75, SD 9.96 beats/minute), and VO2max (3.59, SD 2.01 ml/kg/min). There was moderate validity found for HR (intraclass correlation coefficient [ICC] 0.731, 95% CI -0.211 to 0.942) and good validity found for VO2max (ICC 0.878, 95% CI -0.125 to 0.972). The reliability results showed the following mean differences (retest minus test): app distance (25.99, SD 43.21 meters), app time (-0.15, SD 0.94 seconds), pace (-0.18, SD 0.33 min/km), app HR (-4.5, 13.44 beats/minute), and app VO2max (0.92, SD 3.04 ml/kg/min). There was good reliability for app HR (ICC 0.897, 95% CI 0.742-0.959) and excellent validity for app VO2max (ICC 0.932, 95% CI 0.830-0.973). All of these findings were observed when using the app with an Android operating system, whereas validity was poor when the app was used with iOS.ConclusionsThis study shows that 2kmFIT-App is a new, scientifically valid and reliable tool able to objectively and remotely estimate CRF, HR, and distance with an Android but not iOS mobile operating system. However, certain limitations such as the time required by 2kmFIT-App to calculate HR or the temperature environment should be considered when using the app.

Dataset Information

Improvements in Patient Acceptance by Hospitals Following the Introduction of a Smartphone App for the Emergency Medical Service System: A Population-Based Before-and-After Observational Study in Osaka City, Japan.

Background

Objective

Methods

Results

Conclusions

Publications

Improvements in Patient Acceptance by Hospitals Following the Introduction of a Smartphone App for the Emergency Medical Service System: A Population-Based Before-and-After Observational Study in Osaka City, Japan.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets