Abstract:

Objective: The geographic morphology of Greece has created inequalities in the provision of obstetric and gynaecology (O&G) services resulting in patients from rural areas having to travel to city hospitals to receive treatment. This study focuses on using quantitative analysis to evaluate the efficiency impact of introducing telemedicine services for O&G services in Greece. Setting: 32 O&G units located in rural and urban areas in Greece. Methods: Data envelopment analysis was used to evaluate the efficiency impact of introducing telemedicine services into the thirty-two O&G units Results: DEA indicated that substantial improvements in efficiency and cost savings could be achieved by introducing telemedicine for O&G services. It was estimated that efficiency could be improved by an overall reduction of approximately 6.5% in the number of beds, 10.6% in the number of obstetricians and gynaecologists, and 6.4% in overall expenditure. The improvements in efficiency were greatest in the peripheral regions where DEA suggested that beds could be reduced by 12.1% and the number of obstetricians and gynaecologists by 26.5%. Expenditure was predicted to increase in the peripheral regions due to the increased number of patients treated in them, but this increase was more than offset by a reduction in expenditure in city hospitals since these same patients no longer travelled to them for treatment. This produced estimated overall cost savings of more than 13 million Euros. DEA also enabled identification of the changes that needed to be made to individual units and the magnitude of these changes. This information is essential to policy and decision makers. Conclusion: The introduction of telemedicine to O&G services will produce significant patient, financial and healthcare benefits. These benefits include prevention of unnecessary travel by female patients, better geographical distribution of obstetric and gynaecology cases, increased provision of services and more efficient use of resources in rural areas. DEA enables identification of the changes that need to be made to individual units. © The Journal on Information Technology in Healthcare.

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