An economic analysis of the EHAS telemedicine system in Alto Amazonas.
Telemedicine systems providing voice communication and email by radio were installed at seven health centres (HCs) and 32 health posts (HPs) in the Alto Amazonas province of Peru during 2001. A cost analysis was performed to estimate the net effect on direct resource consumption from the perspective of society. Prior to the availability of the EHAS telemedicine system, there was a mean of 11.1 urgent patient referrals per year from the HPs and 14.0 referrals per year from the HCs. After the implementation of telemedicine, patient referrals fell to 2.5 per year from the HPs (P = 0.03) and to 8.4 per year from the HCs (P = 0.17). The net economic effect of the telemedicine programme over a four-year period was clearly positive, amounting to annual net savings of US$320,126 (using a 5% discounting rate). A one-way sensitivity analysis using a range of values for the discounting rate, and the number of urgent referrals, confirms that the programme was efficient (i.e. it made net financial savings) in all cases. From the restricted budgetary perspective of the health network, the results also demonstrate that the additional operational costs (telephone and maintenance) introduced by the telemedicine system were lower than the direct cost-savings produced for the health-care network.
Martínez
Andrés
A
Departamento de Teoría de la Señal y Comunicaciones, Universidad Rey Juan Carlos, Madrid, Spain. andres.martinez@urjc.es
Villarroel
Valentín
V
Puig-Junoy
Jaume
J
Seoane
Joaquín
J
del Pozo
Francisco
F
D003362:Cost-Benefit Analysis; D004630:Emergencies; D017048:Health Care Costs; D006295:Health Resources / Q000191:economics / Q000706:statistics & numerical data; D006801:Humans; D017059:Models, Econometric; D010568:Peru; D012017:Referral and Consultation / Q000706:statistics & numerical data; D019035:Rural Health Services / Q000191:economics* / Q000706:statistics & numerical data; D017216:Telemedicine / Q000191:economics* / Q000706:statistics & numerical data