Impact of regional medical network systems on emergency transport time for older patients in Japan: a retrospective observational study

Abstract

Background

The Saitama Tone Health and Medical Care Region Medical Collaboration Promotion Council has established a regional medical network system (Patient-Centered Digital Health Records, Tonetto) that shares medical information among healthcare facilities and provides medical services to Tonetto users. This system has facilitated the sharing of medical information between core hospitals, general hospitals, and clinics, thereby contributing to improved medical care. Furthermore, Tonetto has facilitated the availability of patient information for emergency transport. This study aimed to evaluate the impact of Tonetto on emergency transportation times for older patients.

Methods

The study population consisted of 1,820 older patients (aged 65 and over) among 2,542 emergency patients transported to East Saitama General Hospital between January and December 2023. Based on their registration status in the Tonetto system, the patients were divided into two groups: a Tonetto-registered group (n = 319) and a Tonetto-nonregistered group (n = 1,501). Statistical analysis was performed using a general linear model that included main effects and interaction terms for the three categories of transport distance (< 5, 5–10, and ≥ 10 km) and two categories of Tonetto registration status. The difference in transport time was estimated based on Tonetto registration status for each transport distance category. To control for confounding variables, the model included severity, age, sex, and transport distance as covariates.

Results

The difference in transport time (minutes) between the Tonetto-nonregistered group and the Tonetto-registered group (95% confidence interval) was − 0.3 (− 3.0, 2.4), − 3.5 (− 8.9, 1.9), − 24.3 (− 38.3, − 10.2), respectively. A reduction of 24 min in transport time was observed in the Tonetto-registered group for distances of 10 km or more (p = 0.001).

Conclusions

Tonetto registration was associated with a substantial reduction in emergency transport time for older patients over long distances. These findings demonstrate the potential of regional medical information networks to improve the efficiency of emergency care and support the development of a nationwide emergency medical information system in Japan.

Background

Emergency personnel are tasked with transporting patients to emergency medical institutions appropriately. Moreover, they must be able to identify whether a patient is an emergency case and transport them directly to the proper medical institution. In addition to on-site activities, it is necessary to establish an environment where the degree of urgency and severity can be assessed. In addition, it is necessary to share information with medical institutions to respond appropriately to emergency patients. The Ministry of Health, Labour and Welfare in Japan considered a “system that allows medical information to be checked nationwide (ACTION1)” in emergency medical situations in its Medical Information Utilization Working Group [1]. Efforts have been made to establish a system that enables medical personnel to view patient medical information during emergencies through the Mynaportal of the Ministry of Health, Labor and Welfare in Japan. The Mynaportal is an online government-managed platform that enables individuals in Japan to securely access and share their personal information, including health information. It is envisioned that patient information will be collected and made available through the use of Mynaportal, thus reducing the burden of checking medical history and current treatment progress [1]. Emergency care studies have found that transport time is an important factor in emergency care research [2]. In the future, it will be necessary to determine whether reducing transport time can improve outcomes [3]; however, emergency care research is still in its early stages [4]. The primary outcome of this study was transport time. Specifically, we examined the impact of a regional health information sharing system on the efficiency of emergency medical transport.

Patient-centered digital health records, including electronic health records (EHRs), patient portals, and personal health records (PHRs), allow patients to have a more active role in their care. They provide patients with access to their medical records, such as medication lists, laboratory and imaging results, allergies, and correspondence [5]. Patient-centered digital health records can significantly help to engage and empower patients with chronic health conditions [6–9]. EHRs are becoming an indispensable tool for clinical decision support and efficient allocation of medical resources through patient record keeping, information sharing, and the analysis of past data regarding emergency medical care [10–13].

This present study focused on the regional medical network system used for emergency activities in the Tone Health and Medical Care Area of Saitama Prefecture (Tonetto) [14]. Recognized as an advanced example of patient-centered digital health records used in emergency care, this system was featured as a successful model on the website of Japan’s Ministry of Internal Affairs and Communications.

The purpose of the present study was to examine how the regional medical network system “Tonetto” has been used in emergency medical care by analyzing differences in transport times between registered and nonregistered older patients, who comprise the majority of the users.

Methods

Study design

This retrospective observational study used data from emergency transport confirmation forms and electronic medical records from Higashi Saitama General Hospital. Ethical approval was obtained from the National Institute of Public Health Institutional Review Board (NIPH-IBRA#23028) and the Japan Medical Alliance East Saitama General Hospital (No. 2024001). This study was performed in accordance with the principles of the Declaration of Helsinki and the Ethical Guidelines for Medical and Biological Research Involving Human Subjects in Japan. The need for patient consent was waived by both committees. To ensure transparency, information regarding the study, including its objectives and procedures, was posted on the East Saitama General Hospital website, allowing potential participants to opt out.

Regional medical network system: Tonetto

Tonetto [14] is an application used by residents of the Tone Health Medical Care Zone (Area: 473.95 km²), which consists of seven cities and two towns in northeastern Saitama Prefecture [15]. It is linked to local medical institutions, dispensing pharmacies, and emergency services, and facilitates the sharing of medical information (Fig. 1). The Tone Health Medical Care Zone is one of 10 secondary medical districts in Saitama Prefecture, which has a population of approximately 640,000. Saitama Prefecture has one of the lowest ratios of doctors, nurses, and medical facilities per capita in Japan, and the Tone Medical District has a high aging rate of approximately 30% [15]. The contract for Tonetto expired at the end of fiscal year 2022, and operations ceased at the end of fiscal year 2023; however, the system is still available in specific regions, medical districts, or municipalities upon request [16].

Fig. 1.

Services of the Tonetto system. The Tonetto contract began in 2012 and expired at the end of fiscal year 2022

Study procedure and characteristics of the study population

All emergency patients transported to Higashi Saitama General Hospital between January 2023 and December 2023 were included. The analysis focused on older patients (aged ≥ 65 years). Data were obtained from emergency transport confirmation forms and electronic medical records.

The following variables were extracted (Fig. 2): transport distance (km), Tonetto registration status, age, sex, severity at initial assessment, illness/injury type, and transport time (min).

Fig. 2.

Study population

Transport distance was measured using Google Maps (Google LLC, https://maps.google.com) as the driving distance from the emergency call location to Higashi Saitama General Hospital. Transport distance was categorized into three groups (≤ 5 km [median], > 5 km [median] to < 10 km, and ≥ 10 km [17]). The determination of the median was based on the distribution of the study population. The rationale for choosing 10 km was that it would inform us whether the transport route was within the Tone Health Medical Care Zone. Age was categorized as follows: infants (0–6 years), children (7–17 years), adults (18–64 years), and older adults (≥ 65 years). As recorded on the emergency transport confirmation forms, severity was classified as mild, moderate, severe, or fatal. Illness/injury type was categorized as general injuries, traffic accidents, heart disease, cerebrovascular disease, respiratory disease, gastrointestinal disease, neoplasms, sensory system diseases, mental disorders, or other diseases.

Transport time was defined as the interval from emergency call to hospital arrival.

Statistical analysis

The χ² test, t-test, or Wilcoxon rank-sum test was used to compare the characteristics of patients transported to the hospital by ambulance, depending on whether or not they were registered with Tonetto. Transport time served as the outcome in a general linear model estimating differences between Tonetto-registered and unregistered patients across transport-distance categories. Model 1 evaluated the main effects of Tonetto registration status (registered vs. unregistered) on transport distance (categorized as < 5 km [median], ≥ 5 km [median], and < 10 km, and ≥ 10 km). Model 2 incorporated these effects along with their interaction terms. To control for confounding variables, the model included severity (mild, moderate, or severe), age, sex, and transport distance as covariates. We also calculated the difference in transfer time between groups with and without Tonetto. This was done by adding the partial regression coefficients of the main effect (Tonetto) and the interaction terms (Tonetto × Transport Distance Category) in Model 2. The values for the differences in transport times between Tonetto-registered and nonregistered patients across the three transport-distance categories were calculated based on the coefficient estimates from the general linear model results in Model 2. A P value < 0.05 was considered statistically significant. Stata version 19.5 software (Stata Corp., College Station, TX, USA) was used to analyze the data.

Results

Characteristics of the study population

This study consisted of 1,820 older patients (aged 65 and over) among 2,542 emergency patients transported to East Saitama General Hospital from January 2023 to December 2023 (Fig. 2). Based on their registration status in the Tonetto system, the patients were divided into two groups: a Tonetto-registered group (319 patients) and a Tonetto-nonregistered group (1,501 patients). The characteristics of the older patients (aged 65 and over) in this study between the Tonetto-registered group and the Tonetto-nonregistered group are listed in Table 1. The mean age was significantly higher in the Tonetto-registered group compared with that in the nonregistered group (82.2 vs. 80.9 years, p = 0.002). The proportion of male patients was similar between the two groups (52.4% vs. 52.1%, p = 0.935). With respect to disease categories, general injuries accounted for 18.8% in the Tonetto-registered group and 16.9% in the nonregistered group. Other disease categories, including cerebrovascular, respiratory, digestive, cardiovascular, sensory, neoplasms, and psychiatric diseases, showed similar distributions between the two groups, with no statistical significance observed (p = 0.381). The proportion of patients with mild (50.8%), moderate (43.6%), and severe (5.6%) events in the registered group was similar to that in the nonregistered group (45.8%, 47.4%, and 6.9%, respectively; p = 0.244). Moreover, no statistically significant differences were observed between the registered and nonregistered groups for either transport distance (p = 0.111) or transport time (p = 0.080).

Table 1.

Characteristics of older patients (≥ 65 years) that were transported to the hospital by emergency services

	All	Tonetto		P value
	(n = 1820)	Registered (n = 319)	Nonregistered (n = 1501)
Age (years), Mean (SD)	81.1 (0.2)	82.2 (0.4)	80.9 (0.2)	0.002 a
Sex male, n (%)	949 (52.1)	167 (52.4)	782 (52.1)	0.935 b
Disease
General Injury, n (%)	313 (17.2)	60 (18.8)	253 (16.9)	0.381 b
Cerebrovascular Disease, n (%)	169 (9.3)	25 (7.8)	144 (9.6)
Respiratory Disease, n (%)	124(6.8)	24 (7.5)	100 (6.7)
Gastrointestinal disease, n (%)	119 (6.5)	24 (7.5)	95 (6.3)
Cardiovascular Disease, n (%)	81 (4.5)	14 (4.4)	67 (4.5)
Traffic Injury, n (%)	59 (3.2)	5 (1.6)	54 (3.6)
Sensory Disease, n (%)	33 (1.8)	4 (1.3)	29 (1.9)
Neoplasm, n (%)	27 (1.5)	6 (1.9)	21 (1.4)
Psychiatry Disease, n (%)	15 (0.8)	3 (0.9)	12 (0.8)
Other, n (%)	862 (47.4)	708 (47.2)	154 (48.3)
Missing	18 (1.0)	0 (0.0)	18 (1.2)
Severity
Mild, n (%)	849 (46.6)	162 (50.8)	687 (45.8)	0.244 b
Moderate, n (%)	850 (46.7)	139 (43.6)	711 (47.4)
Severe, n (%)	121 (6.6)	18 (5.6)	103 (6.9)
Transport Distance(km)				0.111 c
Mean (SD)	5.1 (4.5)	4.6 (3.7)	5.3 (4.7)
Median [Interquartile range]	4.1 [2.9,6.0]	3.8 [2.9,5.7]	4.1 [ 2.9,6.3]
Min	0.1	0.1	0.1
Max	53	52	53
Transport Time(minute)				0.080 c
Mean (SD)	52.5 (19.3)	50.1 (14.4)	53 (20.1)
Median [Interquartile range]	48 [42,57]	47 [ 41, 56 ]	49 [42,58 ]
Min	21	26	21
Max	219	169	219

Tonetto is the Regional Medical Network System that is Patient-Centered Digital Health Records

SD: Standard Deviation, IQR: Interquartile range

a t-test

b χ² test

c Wilcoxon rank-sum test

Tonetto registration status and transport time association

Table 2 depicts the results of the general linear model analysis for Models 1 and 2. The results from Model 2 in Table 2 were used for calculating the values in Table 3.

Table 2.

Results of the general linear model: the relationship between Tonetto registration status and transport distance

Model *	Predictors		Coefficients c		95%CI e		P value
			β	SE d	Lower	Upper
Model1	Tonetto a		−1.93	1.10	−4.09	0.23	0.080
	Transport-Distance Category b	< 5 km	Reference
		≥ 5 km and < 10 km	3.02	1.11	0.85	5.19	0.006
		≥ 10 km	7.01	2.86	1.41	12.61	0.014
Model2	Tonetto a × Transport-Distance Category b	< 5 km	Reference
		≥ 5 km and < 10 km	−3.17	2.37	−7.82	1.48	0.181
		≥ 10 km	−23.97	7.04	−37.78	−10.17	0.001
	Tonetto a		−0.31	1.36	−2.97	2.35	0.820
	Transport-Distance Category b	< 5 km	Reference
		≥ 5 km and < 10 km	3.48	1.19	1.14	5.82	0.004
		≥ 10 km	8.07	2.86	2.45	13.69	0.005

*General linear models were adjusted for severity (1, Mild; 2, Moderate; and 3, Severe), age, gender and transport distance

Model1: R-squared = 0.155, Model2: R-squared = 0.161

a Classification of Tonetto: 0, Not Registered and 1, Registered

b Classification of Transport-Distance Category: 0; Transport distance < 5 km, 1; 5 km ≤ Transport distance < 10 km, 2; Transport Distance ≥ 10 km

c β: partial regression coefficient, d SE: Standard Error, e CI: Confidence interval

Table 3.

Difference in transport time based on Tonetto registration status for the transport-distance category

	The difference in transport time between the groups with and without Tonetto registration
	Minute	95%CI *
		Lower	Upper
< 5 km (Reference)	−0.31	−2.97	2.35
≥ 5 km and < 10 km	−3.48 a	−8.89	1.93
≥ 10 km	−24.28 b	−38.34	−10.22

The following calculations have been made using the estimates for the coefficients in the general linear model results (Table 2)

^a The main effect (− 0.31) + Interaction term (− 3.17)

^b The main effect (− 0.31) + Interaction term (− 23.97)

* CI: Confidence interval

The association between Tonetto registration (independent variable: 0 = not registered; 1 = registered) and transport time (dependent variable) is presented in Table 2. In Model 1, the transport time was not significantly associated with Tonetto registration (β = −1.93, p = 0.080). Moreover, in Model 2 (which included interaction terms between transport time and transport-distance categories), association between the transport time and Tonetto registration remained nonsignificant for transport distances of ≥ 5 and < 10 km (β = −3.17, p = 0.181). However, it showed a significant negative association for transport distances ≥ 10 km (β = −23.97, p = 0.001).

Table 3 lists the differences in transport time between Tonetto-registered patients and nonregistered patients across three transport-distance categories. The results from Model 2 in Table 2 were used for determining the values of Table 3. For distances less than 5 km, the difference in transport time was − 0.31 min (95% CI: −2.97 to 2.35). For the 5–10 km category, the difference was − 3.48 min (95% CI: −8.89 to 1.93). However, patients registered with Tonetto, however, had significantly shorter transport times in the ≥ 10 km category, with a difference of − 24.28 min (95% CI: −38.34 to − 10.22).

Discussion

In this study, we determined whether the availability of patient-centered digital health records resulted in efficient transportation to emergency medical facilities. The results indicated that for patients registered in the regional medical network system (Patient-centered digital health records; Tonetto), emergency transport time was reduced for the long-distance transport of older patients. This indicates the usefulness of Tonetto for emergencies.

Older patients comprise a quarter of all emergency department visits, with many comorbidities that may complicate the delivery of care [18]. The proportion of older patients (aged 65 and over) in the study population accounted for approximately 70% among the emergency patients transported to East Saitama General Hospital. Moreover, approximately 90% of the patients enrolled in Tonetto were older (aged 65 and over). Solutions to support the improved quality of care and patient outcomes in the emergency department are needed and present an opportunity to deliver great benefits to older patients [19]. In Australia, the national personally controlled EHR (My Health Record, MHR) was adopted as an opt-out system in 2019 [20]. EHRs provide detailed medical information, including patient medical history and current medications, which supports decision-making regarding diagnosis, treatment, and transport at the prehospital emergency scene [21]; however, My Health Record, Australia’s national electronic health record, had low access rates among physicians and nurses, despite frequent use by emergency departments for patients aged 65 and older [20].

Although the use of EHRs, including patient-centered digital health records, in the emergency department has great potential to improve the quality and efficiency of patient care, there remain some significant challenges and barriers [22]. For example, “Hospital Admission Difficulty Cases” in which paramedics have to make multiple calls to find a hospital that will accept a patient, are a problem in the Japanese emergency system [23]. Previous studies indicate that older patients and female patients tended to remain longer in the emergency department [23, 24]. To address this issue, it is necessary to establish digital information devices.

The results of our study indicated that registration in the Tonetto regional medical information network brought about a considerable reduction in the transport time for older patients during long-distance emergency transfers. The registration with Tonetto was considered to have simplified the selection of transport destinations and improved information transfer at handover, leading to a swift and smooth acceptance of the patients. In practice, information useful for emergency transport was collected from individuals who wished to participate in Tonetto, at the time of registration. This included information regarding allergy status, chronic illnesses, current medications, primary care physician, and emergency contact details of close relatives. However, in the current study, we could only obtain registration status data for the Tonetto. Due to the retrospective observational design of the study, we could not ascertain whether emergency personnel actually accessed the Tonetto information.

In Japan, a new initiative entitled “My Number Emergency” is being implemented, wherein emergency medical personnel utilize the My Number health insurance cards of the patients to access information that aids in hospital selection and other decisions (https://www.soumu.go.jp/menu_news/s-news/01shoubo01_02001005.html). This will enable appropriate transportation of emergency patients to medical facilities, leading to a reduction in transportation time. The results of the present study provide insight for creating a system that enables medical information to be checked nationwide during medical emergencies.

The present study has several limitations. First, transport distance was estimated using Google Maps based on car routes; actual distances may vary depending on route selection, temporary road conditions, or emergency transport protocols. Notably, Google Maps is widely used in emergency medicine research [25]. Second, although this retrospective observational analysis showed the effectiveness of Tonetto registration after adjusting for measured confounders, residual confounding from unmeasured variables cannot be excluded. Replication in other settings is necessary. Third, although the choice of three distance categories lacked an explicit initial rationale, the study area—the Tone Health Medical Zone (474 km²)—is approximately equivalent to a circle with a 9 km radius. Thus, a 10 km cutoff was selected as it approximates this boundary and is commonly applied in emergency medical service operations. Although the specific cut-points used to divide distance in this study may not be directly generalizable, we anticipate that the effects of the regional medical network system would be more pronounced at longer transport distances in other settings.

Conclusion

Registration in the Tonetto regional medical information network significantly reduced transport time for older patients during long-distance emergency transfers. These findings highlight the system’s potential to improve emergency medical care and support the development of a nationwide platform providing real-time access to patient medical information. Future research should identify the most relevant types of patient-centered digital health records for emergency care, develop effective sharing methods based on illness severity, and continue validating the system to ensure efficient emergency department management.

Abbreviations

PHRs

Personal health records

EHRs

Electronic health records

CI

Confidence intervals

Author contributions

A.M. and K.H. developed the study design with the support of Y.Y. and T.N. A.M. and A.N. were engaged in data collection. A.M. and A.S performed the statistical analysis and drafted the first manuscript. All authors read and gave fundamental comments on the manuscript and approved the final version.

Funding

This work was supported by a Grant from the Taiju Life Social Welfare Foundation and a Basic Research Grant from the Ministry of Health, Labour, and Welfare entitled “Research on the Establishment of a Regional Medical Information Infrastructure for Health Promotion.”

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Ethical approval for this study was obtained from the institutional review board of the National Institute of Public Health (NIPH-IBRA#23028) and Japan Medical Alliance East Saitama General Hospital (No. 2024001). To ensure that research participants had the opportunity to refuse participation, information regarding the purpose of the study and its implementation will be disclosed on the website of Higashi Saitama General Hospital. In addition, participants were provided with the opportunity to opt out of the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.