Avoid equipment graveyards: rigorous process to improve identification and procurement of effective, affordable, and usable newborn devices in low-resource hospital settings

BACKGROUND

Millions of newborns die annually from preventable causes, with the highest rates occurring in Africa. Reducing neonatal mortality requires investment to scale hospital care, which includes providing hospitals with appropriate technology to care for small and sick newborns. Expensive medical devices designed for high-resource settings often fail to withstand conditions in low-resource hospitals, including humidity, dust, frequent user turnover, complex maintenance, lack of stable power, or difficulty sourcing expensive consumables. Rigorous evaluation protocols are needed to identify effective, affordable, rugged, and easy-to-use medical devices appropriate for quality hospital-based newborn care in low-resource hospitals.

METHODS

We developed an evidence-based technology review process to identify medical devices suitable for small and sick newborn care in low-resource hospitals. The eight-step process consists of: identifying devices needed for effective newborn care; defining Target Product Profiles (TPPs); identifying commercially-available products that may meet TPPs; conducting desk research to evaluate technologies against TPPs; performing technical performance verification testing under laboratory conditions; verifying technical performance after exposure to heat, humidity, dust, and power loss; performing usability evaluations with nurses, and qualifying devices that pass all steps. Devices were purchased, installed, and monitored in newborn wards across Kenya, Malawi, Nigeria, and Tanzania.

RESULTS

Of 271 devices considered, only 45 (16.6%) met corresponding TPPs based on desk research. Thirty-nine were purchased and evaluated in the laboratory; five (12.8%) failed to meet TPPs. Thirty-four products passing laboratory evaluation underwent short-term environmental testing; only one (2.9%) device failed. Thirty-seven products underwent usability testing with 127 clinicians; surprisingly, 14 (37.8%) failed to meet TPPs. Twenty-three products passed all evaluations, and 2457 devices were installed across 65 newborn wards in Kenya, Malawi, Nigeria, and Tanzania. Continuous device monitoring reported minimal device failures, with failed devices typically returned to service within two days, resulting in an average uptime (service days divided by days installed) of 99%.

CONCLUSION

An evidence-based device selection process can improve procurement of effective, affordable, rugged, usable newborn care devices for low-resource hospitals, and feedback to manufacturers can improve device quality. Similar processes could be adapted beyond newborn care to identify medical devices suitable for implementation in any low-resource setting.

International Image Concordance Study to Compare a Point-of-Care Tampon Colposcope With a Standard-of-Care Colposcope

OBJECTIVE

Barriers to cervical cancer screening in low-resource settings include lack of accessible, high-quality services, high cost, and the need for multiple visits. To address these challenges, we developed a low-cost, intravaginal, optical cervical imaging device, the point-of-care tampon (POCkeT) colposcope and evaluated whether its performance is comparable with a standard-of-care colposcope.

MATERIALS AND METHODS

There were 2 protocols, which included 44 and 18 patients. For the first protocol, white-light cervical images were collected in vivo, blinded by device, and sent electronically to 8 physicians from high-, middle-, and low-income countries. For the second protocol, green-light images were also collected and sent electronically to the highest performing physician from the first protocol who has experience in both a high- and low-income country. For each image, physicians completed a survey assessing cervix characteristics and severity of precancerous lesions. Corresponding pathology was obtained for all image pairs.

RESULTS

For the first protocol, average percent agreement between devices was 70% across all physicians. The POCkeT and standard-of-care colposcope images had 37% and 51% agreement with pathology for high-grade squamous intraepithelial lesions (HSILs), respectively. Investigation of HSIL POCkeT images revealed decreased visibility of vascularization and lack of contrast in lesion margins. After changes were made for the second protocol, the 2 devices achieved similar agreement to pathology for HSIL lesions (55%).

CONCLUSIONS

Based on the exploratory study, physician interpretation of cervix images acquired using a portable, low-cost POCkeT colposcope was comparable to a standard-of-care colposcope.

Model-based normalization for iterative 3D PET image reconstruction

We describe a method for normalization in 3D PET for use with maximum a posteriori (MAP) or other iterative model-based image reconstruction methods. This approach is an extension of previous factored normalization methods in which we include separate factors for detector sensitivity, geometric response, block effects and deadtime. Since our MAP reconstruction approach already models some of the geometric factors in the forward projection, the normalization factors must be modified to account only for effects not already included in the model. We describe a maximum likelihood approach to joint estimation of the count-rate independent normalization factors, which we apply to data from a uniform cylindrical source. We then compute block-wise and block-profile deadtime correction factors using singles and coincidence data, respectively, from a multiframe cylindrical source. We have applied this method for reconstruction of data from the Concorde microPET P4 scanner. Quantitative evaluation of this method using well-counter measurements of activity in a multicompartment phantom compares favourably with normalization based directly on cylindrical source measurements.

Internet2-based 3D PET image reconstruction using a PC cluster

We describe an approach to fast iterative reconstruction from fully three-dimensional (3D) PET data using a network of PentiumIII PCs configured as a Beowulf cluster. To facilitate the use of this system, we have developed a browser-based interface using Java. The system compresses PET data on the user's machine, sends these data over a network, and instructs the PC cluster to reconstruct the image. The cluster implements a parallelized version of our preconditioned conjugate gradient method for fully 3D MAP image reconstruction. We report on the speed-up factors using the Beowulf approach and the impacts of communication latencies in the local cluster network and the network connection between the user's machine and our PC cluster.