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Roger Osayende, a former management consultant, must advise the Ministry of Health of Ektu, a fictional country in Central Africa, on how to implement a new point-of-care diagnostic test for infants with HIV. In Ektu, mothers often transmitted HIV infection to infants during pregnancy, delivery, or breastfeeding due to inadequate resources to invest in prevention efforts. The existing procedure to diagnose infants with HIV required collecting dried blood samples at more than two hundred healthcare facilities around the country and transporting them to a central laboratory in the capital for testing. This process was characterized by significant delays due to long transportation times, batching of samples in transportation and processing in the lab, and concomitant congestion in the lab. This delay resulted in loss to follow-up, that is, lost patients due to mothers not collecting their infants' results. A new point-of-care device was about to be introduced, which would obviate the need for this centralized processing and the resulting diagnostic delay. The key decision under consideration is where to place the devices to maximize their effectiveness.

Understand the importance of making public health decisions based on a data-driven, logical framework   Uncover the link between operational performance of the healthcare system and health outcomes at the population level   Appreciate the relevance of operational decisions in enhancing or diminishing the effectiveness of a medical technology   Use process analysis concepts to characterize various components of delays

The purpose of this paper is to compare the ability of the Morse Fall Scale (MFS) and Farmer's fall-risk assessment tool (FFAT) to identify correlations between risk factors and falls among older adult long-term care (LTC) facility residents.

This was a correlational retrospective study. 200 medical records of older adults hospitalized in a LTC facility in central Israel, from January 2017 to January 2018, were examined.

Of all the residents, 75% and 99.5% of the residents were identified as having a high fall risk according to the MFS and FFAT, respectively. Only 12.5% of residents actually fell. MFS score was weakly correlated with actual falls (odds ratio = 1.035). It was also found that all fallers fell during their first week at the facility.

Future research should explore the ability of the tools to capture changes in the fall risk by repeat assessments, as this has not been examined in the present study.

The MFS and FFAT tool may have little value in assessing fall risk in older adult LTC facility residents. Therefore, nurses should perform a clinical evaluation of each individual patient. In addition, nurses should place a particular emphasis on fall risk and prevention during the first week following admission.

The findings of the present study raise doubts regarding the utility of the common practice of assessing fall risk in older adult LTC facility residents using the tools MFS and the FFAT, thus emphasizing the need to adopt a different approach.