LMIC examples Flashcards

1
Q

Prosocial motivation example

A

Deserranno. 2019 - clinical health workers in Uganda recruited in the low-pay group were found to be more pro-socially motivated.

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2
Q

Secondary moral hazard example

A

Lagarde et al. 2021: Study in South Africa - increase in unecessary care from provider in group with high cover insurance.

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3
Q

Lack of knowledge on health conditions

A

Cohen et al 2015 - inappropriate use of antimalarials in Kenya, partly due to incorrect beliefs about illness.

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4
Q

Methods to overcome present bias

A

Small nudges to create present benefits: Lagarde and Riumallo-Herl (2022) showed that incentives doubled the uptake of CVD screening and reduced the number of dropouts after blood tests.

Banerjee et al. 2010 showed higher percentage of full immunisations in the group who received raw lentils and metal plates.

Commitment devices: CARES programme Giné et al. (2010) - lose invested money (sunk cost fallacy) if fails to quit smoking. Participants who signed up were 30-65% more likely to stop smoking.

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5
Q

Effect of P4P in LMICs

A

Diaconu et al 2021. Low certainty in evidence of effect on health outcomes, overall quality and absenteeism. Moderate evidence for P4P improving some health outcomes for untargeted conditions.
Das et al 2016. P4P is effective in improving processes in antenatal care but further research is required to establish effect on health outcomes.
Bonfrer et al 2014 - improved quality of care for prenatal services in Burundi.

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6
Q

Collective model case studies

A

Target women for decision making in healthcare (Nyqvist and Jayachandran 2017). Found that men attended health education classes less than women in Uganda and were also less likely to put what they had learnt into practice. Men attending class increased women’s knowledge but not the other way around.

Conditional cash transfers (Duflo. 2003) - increase in weight for height of girls by 1.2 SD in group where women received a pension. No change in men with pension group.

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7
Q

User charges

A

Mixed evidence on impact of user charges on use of services.

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