| Literature DB >> 30245884 |
Tae-Hun Lee1, Jae-Hyun Han2, Ashish Ranjan Sharma1, Young-A Choi1, Dong Won Kim1, Sang-Soo Lee3, Moo-Eob Ahn1,3.
Abstract
Due to an increase in traffic collisions, the demand for prehospital medical services is on the rise, even in low-resource countries where emergency ambulance services have not been previously provided. To build a sustainable and continuous prehospital ambulance operation model, it is necessary to consider the medical system and economic conditions of the corresponding country. In an attempt to construct a prehospital ambulance operation model that ensures continuous operation, a pilot "emergency patient transporting service from field to hospital" operation was established for approximately three months in Kinshasa, the capital of the DR Congo. To construct a continuously operating model even after the pilot operation, willingness to pay (WTP) by type of emergency medical and transport service was investigated by implementing the contingent valuation method (CVM). Using CVM, the WTP for prehospital emergency services targeting ambulance services personnel, patients, policemen, and hospital staff participating in the pilot operation was calculated. The results of the pilot operation revealed that there were a total of 212 patients with a mean patient number of 2.4 per day. A total of 155 patients used the services for hospital transport, while 121 patients used the services for traffic collisions. Traffic collisions were the category in which ambulance services were most frequently needed (66.2%). Pay services were most frequently utilized in the home-visit services category (40.9%). Based on these results, eight independently operated ambulance operation models and sixteen models that utilize hospital medical personnel and policemen already belonging to existing institutions were proposed. In an effort to implement emergency medical ambulance services in the DR Congo, medical staff receiving pay for performance (incentive pay) should be deployed in the field and on call. Accordingly, with respect to sustainable development goals, various pay-for-service models should be used.Entities:
Year: 2018 PMID: 30245884 PMCID: PMC6136570 DOI: 10.1155/2018/8701957
Source DB: PubMed Journal: Emerg Med Int ISSN: 2090-2840 Impact factor: 1.112
Requirements for ambulance services (units: frequency, %).
| Areas | 1st place | 2nd place | 3rd place | Weighted total frequencies × |
|---|---|---|---|---|
| Traffic collisions | 88 (66.2) | 15 (11.3) | 14 (10.5) | 308 |
| Non-traffic injuries | 23 (17.3) | 46 (34.6) | 30 (22.6) | 191 |
| Emergency disease | 14 (10.5) | 49 (36.8) | 49 (36.8) | 189 |
| Drug intoxication | 2 (1.5) | 5 (3.8) | 9 (6.8) | 25 |
| Hospital to hospital transporting | 6 (4.5) | 18 (13.5) | 30 (22.6) | 84 |
| Others | - | - | 1 (0.8) | 1 |
×Weighted total frequencies (score) = frequencies of 1st place cases × 3 + frequencies of 2nd place cases × 2 + frequencies of 3rd place cases × 1.
Emergency ambulance services costs (units: frequency, %).
| Targeted service personnel (group) | Field-to-hospital transporting service | Hospital-to-hospital transporting service | Home-visiting-medical service | Total | p-value |
|---|---|---|---|---|---|
| Patients | 3(18.8) | 1(6.3) | 12(75.0) | 16(100) | 0.011 |
| Policemen | 8(40.0) | 2(10.0) | 10(50.0) | 20(100) | 0.011 |
| Hospital staff | 20(31.7) | 19(20.2) | 24(38.1) | 63(100) | 0.011 |
| Ambulance personnel | 10(35.7) | 12(42.9) | 6(21.4) | 28(100) | 0.011 |
| Total | 41(32.3) | 34(26.8) | 52(40.9) | 127(100) | 0.011 |
×p<0.05, ××p<0.01.
Data are Frequency (rate) P-values are for Χ2 as appropriate.
The estimated costs for emergency ambulance services (Units: frequency, USD).
| Item | Group | N | Mean | SD | F- or | p-value |
|---|---|---|---|---|---|---|
| Field-to-hospital ambulance service | Patients | 19 | 26.63 | 20.13 | 21.537 | 0.001×× |
| Policemen | 20 | 37.00 | 33.73 | |||
| Hospital staff | 63 | 60.40 | 31.00 | |||
| Ambulance personnel | 30 | 54.50 | 27.05 | |||
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| Hospital-to-hospital ambulance service | Patients | 19 | 31.53 | 24.80 | 34.703 | 0.001×× |
| Policemen | 20 | 49.50 | 25.64 | |||
| Hospital staff | 63 | 76.83 | 23.27 | |||
| Ambulance personnel | 31 | 66.61 | 32.80 | |||
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| Home-visiting medical service | Patients | 19 | 5.32 | 2.96 | 73.213 | 0.001×× |
| Policemen | 20 | 35.10 | 32.95 | |||
| Hospital staff | 63 | 60.63 | 12.30 | |||
| Ambulance personnel | 31 | 86.77 | 21.66 | |||
×p<0.05, ××p<0.001.
Data are frequency (rate) and the mean± S.D. P values are for Χ2, t test as appropriate.
Analysis of prehospital emergency medical services based cost-service (units: USD).
| Principal operator | personnel composition | Scenario | Service type | Daily op. rate | Op. costs |
|---|---|---|---|---|---|
| Independent Emergency service team Operation-[Operation Control Center Manpower] | 3-crew physician model (physician + nurse + driver) | 1 | field-to-hospital | 100% | 22.27 |
| 2 | field-to-hospital | 50% | -32.15 | ||
| Hospital-to-hospital | 25% | 66.61 | |||
| Home-visiting | 25% | 86.77 | |||
| 2-crew physician model (physician + driver) | 3 | field-to-hospital | 100% | 18.16 | |
| 4 | field-to-hospital | 50% | -40.37 | ||
| Hospital-to-hospital | 25% | 66.61 | |||
| Home-visiting | 25% | 86.77 | |||
| 3-crew EMT model (nurse + nurse + driver) | 5 | field-to-hospital | 100% | 18.16 | |
| 6 | field-to-hospital | 75% | 2.01 | ||
| Hospital-to-hospital | 25% | 66.61 | |||
| 2-crew EMT model (nurse + driver) | 7 | field-to-hospital | 100% | 14.05 | |
| 8 | field-to-hospital | 75% | -3.47 | ||
| Hospital-to-hospital | 25% | 66.61 | |||
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| Hospital organization utilized | 3-crew physician model (physician+nurse+driver) | 9 | field-to-hospital | 100% | 21.93 |
| 10 | field-to-hospital | 50% | -24.88 | ||
| Hospital-to-hospital | 25% | 76.83 | |||
| Home-visiting | 25% | 60.63 | |||
| 2-crew physician model (physician+driver) | 11 | field-to-hospital | 100% | 17.82 | |
| 12 | field-to-hospital | 50% | -33.10 | ||
| Hospital-to-hospital | 25% | 76.83 | |||
| Home-visiting | 25% | 60.63 | |||
| 3-crew physician incentive model (physician + nurse + driver) | 13 | field-to-hospital | 100% | 8.52 | |
| 14 | field-to-hospital | 50% | -51.68 | ||
| Hospital-to-hospital | 25% | 76.83 | |||
| Home-visiting | 25% | 60.63 | |||
| 2-crew physician incentive model (physician + driver) | 15 | field-to-hospital | 100% | 8.24 | |
| 16 | field-to-hospital | 50% | -52.24 | ||
| Hospital-to-hospital | 25% | 76.83 | |||
| Home-visiting | 25% | 60.63 | |||
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| Police organization utilized | 3-crew EMT model (nurse + nurse + driver) | 17 | field-to-hospital | 100% | 17.82 |
| 18 | field-to-hospital | 75% | 7.26 | ||
| Hospital-to-hospital | 25% | 49.50 | |||
| 2-crew EMT model (nurse + driver) | 19 | field-to-hospital | 100% | 13.71 | |
| 20 | field-to-hospital | 75% | 1.78 | ||
| Hospital-to-hospital | 25% | 49.50 | |||
| 3-crew EMT incentive model (nurse + nurse + driver) | 21 | field-to-hospital | 100% | 8.24 | |
| 22 | field-to-hospital | 75% | -5.51 | ||
| Hospital-to-hospital | 25% | 49.50 | |||
| 2-crew EMT incentive model (nurse + driver) | 23 | field-to-hospital | 100% | 7.96 | |
| 24 | field-to-hospital | 75% | -5.88 | ||
| Hospital-to-hospital | 25% | 49.50 | |||
∗ denotes an income and Op. denotes operational cost.