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This network has led us to propose this approach to solve medical technology management projects, where the strengths of each subgroup complement each other. This structure will lead to a more integrated approach to healthcare technology management and will ensure higher quality solutions.

This work presents the methodology to design a small imaging unit in a small regional hospital that takes into account the real imaging needs in the region regardless of current administrative guidelines. The situation of the imaging facilities in Mexico's states is studied and compared with other countries, and a project plan is designed for the specific state (Guerrero) where the clinic is to be located. The proposal includes the acquisition of a basic suite of modalities that include an ultrasound system, a mammography unit, and a conventional X-ray system in addition to a CT system that is not available anywhere within the state. The system should be primarily digital and should incorporate a simple picture archiving and communications system that can be the basis of a future telemedicine unit. The conclusion of this study also proposes changes in the segmented and pyramidal structure of the Mexican health system in order to provide higher quality care at the lower level, to reduce bottlenecks, and to provide higher quality health care near the patient's home.

Intradialytic hypotension occurs in 10–30% of hemodialysis (HD) sessions. This phenomenon affects the cardiovascular system’s functions, which are reflected in the activity of the autonomic nervous system (ANS). To indirectly assess the ANS during HD, we analyzed the mean R–R intervals and the spectral power of heart rate variability (HRV) from 20 end-stage renal disease patients divided into hypotensive and non-hypotensive groups. The spectrotemporal analysis was accomplished using short-time Fourier transform with 10 min epochs of HRV overlapping by 40%. The spectral power was divided into three segments according to high frequency, low frequency, and very low frequency bandwidths and averaged to fit quadratic regression models. The analysis of the mean R–R intervals showed significant differences between the groups (p = 0.029). The power variation over time was significant in each spectral band (p ≪ 0.05). The average power, maximum power, and time when the peak was reached differed for each band and between groups, showing the ability to correctly identify the decompensation of the ANS and discriminate between hypotensive and non-hypotensive patients. Additionally, the changes in the sympathovagal ratio were not significant and very scattered for the hypotensive group (p = 0.23) compared to the non-hypotensive group, where the changes were significant (p ≪ 0.05) and much less scattered.

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