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Subsidies, Information, and the Timing of
Children’s Health Care in Mali
Anja Sautmann, Samuel Brown
(Brown University)
an...
Introduction
Introduction
I Lack of adequate care for acute illness contributes to continually
high child mortality rates
I Broad polic...
Introduction
I Two common health
policies:
I Biweekly healthworker visits
I Subsidies for “5 killers of
children” “Action ...
Introduction
What constitutes overuse and underuse?
I Value of care depends on (often unobserved) health status
I In this ...
A Dynamic Model of Demand for
Healthcare
Model: Timing of Care
I Assume a child in an ongoing spell of (given) symptoms
I If illness absorptive, or full informatio...
Model: Timing of Care
Show: optimal “care seeking strategy” specifies after how many days to
go see a doctor
I Depends on
I...
Predictions
1. Free care leads to earlier care: can reduce underuse, but may
increase overuse.
2. Better information
2.1 c...
Data and Randomized Control Trial
Data: Action for Health RCT
Fall 2012: baseline survey
I Location: Sikoro, peri-urban area of Bamako, Mali
I 650 compounds...
Study Area
Data: Action for Health RCT
January 2013: independently randomize
1. “Free” care: free services and medications for childr...
Symptom Data
Symptoms recorded and relative frequency:
Mean SD Mean SD
Number,of,days: 59.94 (9.37) 17.94 (15.89)
Percenta...
Data: Spells and Need for Care
Spell: contiguous period of symptoms, ending with doctor visit or
recovery.
Policymaker pre...
Results
Outcomes: Unconditional Utilization
I Subsidies
I decrease CSCOM visit costs by 70% (2964 to 893 CFA on average)
I increas...
Outcomes: Over- and Underuse
early
care	
required early
care	
required early
care	
required early
care	
required
374 407 3...
Day by day probability of care seeking
0%	
2%	
4%	
6%	
8%	
10%	
12%	
14%	
1	 2	 3	 4	 5	 6	 7	 >7	
Probability	of	Formal	C...
Demand for Care: Interpretation and
Applications
Implications for Overuse and Underuse
1. Overuse:
I Near zero probability of care-seeking on “early” days
I No additional ...
Predicting Care Seeking For Other Disease Environments
I Care-seeking probabilities based on symptoms: allow out-of-sample...
Other Results
Health Outcome Effects of subsidies:
I Average illness spell length reduced by 0.8 days – recall, only 30%
re...
Conclusion
Summary of Results
I Open the black box of healthcare demand, estimate timing of care
conditional on illness incidence
I R...
Policy Relevance
I Immediate policy impact:
I Changes to the programs of our cooperating partner Mali Health
I Focus on su...
Thank you!
Treatment Groups: Attrition
Control Healthworker Free	care	 HW	&	FC All
Original	Sample 463 433 451 417 1764
Not	Found	at	...
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Child Poverty Research Day: Reducing Non-Economic Poverty - Anja Sautmann, 'Subsidies, Information, and the Timing of Children's Health Care in Mali'

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Child Poverty Research Day: Anja Sautmann
Institute of Development Studies, Brighton.
18th November 2016

Published in: Education
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Child Poverty Research Day: Reducing Non-Economic Poverty - Anja Sautmann, 'Subsidies, Information, and the Timing of Children's Health Care in Mali'

  1. 1. Subsidies, Information, and the Timing of Children’s Health Care in Mali Anja Sautmann, Samuel Brown (Brown University) and Mark Dean (Columbia University) Child Poverty Research Day November 18, 2016
  2. 2. Introduction
  3. 3. Introduction I Lack of adequate care for acute illness contributes to continually high child mortality rates I Broad policy swing in primary care for children: from “user fees” (Bamako Initiative) to free access (e.g. Burkina Faso 2016) I New focus on acute care and urban areas I Debate over subsidies for acute care: I Absent other distortions, subsidies can cause overuse and waste: price is a measure of value I But subsidies can overcome underuse if there are access barriers or inefficiencies: lack of access to credit, lack of information, benefits not taken into account by parents (child welfare, longrun health, infection risk) I Complementary policy: health education and information to encourage efficient use Question: Can subsidies, supplemented with information policies, curb underuse of care without creating overuse (in urban populations)?
  4. 4. Introduction I Two common health policies: I Biweekly healthworker visits I Subsidies for “5 killers of children” “Action for Health” NGO Mali Health I Idea of “integrated care” and information as a tool to optimize healthcare use I Following guidelines of Integrated Management of Childhood Illness (IMCI) by WHO/Unicef
  5. 5. Introduction What constitutes overuse and underuse? I Value of care depends on (often unobserved) health status I In this paper: I Model and estimate timing of care within an illness spell I As benchmark for overuse/underuse use guidelines of Integrated Management of Childhood Illness (IMCI) by WHO/Unicef Supply-side effects of large-scale demand change I In this paper: randomized control trial, supply-side fixed
  6. 6. A Dynamic Model of Demand for Healthcare
  7. 7. Model: Timing of Care I Assume a child in an ongoing spell of (given) symptoms I If illness absorptive, or full information about its course: either go to doctor immediately, or never. Intuition for delaying a visit: I Initially, child may recover on her own; can save a visit I If symptoms do not abate: probability of not recovering is increasing over time ) Longer illness is more likely “serious”
  8. 8. Model: Timing of Care Show: optimal “care seeking strategy” specifies after how many days to go see a doctor I Depends on I seriousness of the illness/symptoms I cost vs. benefit of a visit. I Parents may disagree on the optimal choice ) Parents seek care too early or too late I Subsidies: reduce the cost threshold and lead parents to seek care earlier I Information: can teach parents about the optimal action according to policy
  9. 9. Predictions 1. Free care leads to earlier care: can reduce underuse, but may increase overuse. 2. Better information 2.1 can reduce underuse and overuse 2.2 but may increase underuse if parents do not agree with the information 3. Free care and better information may be complements: potential to reduce underuse without creating overuse. ) Motivates policies that combine the two (e.g. IMCI)
  10. 10. Data and Randomized Control Trial
  11. 11. Data: Action for Health RCT Fall 2012: baseline survey I Location: Sikoro, peri-urban area of Bamako, Mali I 650 compounds, 1544 children; below local poverty line Attrition I Two public health clinics provide basic primary care – “CSCom” I Large households (>6 members), USD 63 weekly income, 50% literate, undernourished children (-0.61 W4H z-score) Typical of the fast-growing population of urban poor in Sub-Saharan Africa Urban setting means better care, but also a risk for overuse!
  12. 12. Study Area
  13. 13. Data: Action for Health RCT January 2013: independently randomize 1. “Free” care: free services and medications for children under 5 at local CSCom only for diarrhea/malnutrition, malaria, vaccinable disease, respiratory disease 2. Healthworker visits: monitor health, teach symptoms, and guide use of formal care – e.g. accompany to clinic – based on IMCI standards when care is required Fall 2013: 10-week follow-up survey I Formal consultations: 514 CSCom, 67 other (private); average cost of USD 5-10 I Symptom records
  14. 14. Symptom Data Symptoms recorded and relative frequency: Mean SD Mean SD Number,of,days: 59.94 (9.37) 17.94 (15.89) Percentage,where,each,symptom,is,present: Convulsions,,fits,,or,spasms 0.09% 0.34% Lethargic,or,unconscious 1.39% 3.96% Unable,to,drink,or,breastfeed 0.34% 1.10% Vomiting,everything 1.14% 4.79% Coughing 11.15% 33.05% Difficulty,breathing 1.63% 4.40% >,3,loose,stools 2.24% 7.07% Blood,in,the,stool 0.20% 0.58% Sunken,eyes 0.62% 1.99% Unusually,hot,skin 8.42% 31.44% Other:,rash,,spots,,or,itch 0.89% 2.96% Other:,cold,symptoms 18.30% 51.52% Other:,ear,ache 0.30% 1.05% Other:,wound,,injury,,or,burn 1.27% 3.94% Other,symptoms 1.42% 5.39% Total,observed, days,per,child Illness,days,per, child
  15. 15. Data: Spells and Need for Care Spell: contiguous period of symptoms, ending with doctor visit or recovery. Policymaker preference: I Unicef/W.H.O.’s Integrated Management of Childhood Illness (IMCI) Classify symptom days in the spell as “early” for care or “care required” I Example: I Diarrhea < 5 days: home remedies I Diarrhea with blood in the stool: immediate care (dysentery)
  16. 16. Results
  17. 17. Outcomes: Unconditional Utilization I Subsidies I decrease CSCOM visit costs by 70% (2964 to 893 CFA on average) I increase formal demand by 317% per child (from 0.18 to 0.57 visits) I Healthworkers I have little average demand effects.
  18. 18. Outcomes: Over- and Underuse early care required early care required early care required early care required 374 407 327 463 368 430 353 438 % with a consultation 3% 11% 2% 10% 6%** 31%*** 8%*** 27%*** Significance levels: *** 1%, ** 5%, * 10%, t-test on mean difference from control. # spells that did/did not enter "care required" Control Healthworker Free care HW & FC I Control and HW only groups: I Rampant underuse, no overuse I Subsidies I remaining underuse of at least 69% of “care required” spells I Healthworkers have no clear effects I Proportion of consultations that are overuse constant at about 16%.
  19. 19. Day by day probability of care seeking 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 >7 Probability of Formal Care Spell Day Control Early Care required 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 >7 Probability of Formal Care Spell Day Healthworkers only Early Care required 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 >7 Probability of Formal Care Spell Day Subsidy only Early Care required 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 >7 Probability of Formal Care Spell Day Subsidy and Healthworkers Early Care required
  20. 20. Demand for Care: Interpretation and Applications
  21. 21. Implications for Overuse and Underuse 1. Overuse: I Near zero probability of care-seeking on “early” days I No additional reduction by healthworkers I Subsidies have only small effect on demand on early days 2. Underuse: I Subsidies increase care-seeking, but to at most 14% daily probability I Healthworkers decrease use by 37% (10% significance) Implications: I Parents can discern “early” days I Substantial underuse even with subsidies I Healthworkers increase underuse, as predicted when parents have high cost threshold Cost/benefit is the binding constraint; information not the main barrier
  22. 22. Predicting Care Seeking For Other Disease Environments I Care-seeking probabilities based on symptoms: allow out-of-sample predictions I Here: use hemorrhagic fever spell descriptions to code set of typical symptom spells I Predict proportion without care for each spell day Model 1, group HWFC Model 1: each day classified as early/care-required according to C-IMCI. Model 2, group HWFC Model 4: Indicators for disease com diseases (i.e. generalized fever, ma 0.5 0.6 0.7 0.8 0.9 1 1 2 3 4 5 6 7 8 9 10 Ebola: pred. proportion without formal care (Model 1: early/care-required) Model 1, group C Model 1, group FC Model 1, group HW Model 1, group HWFC Ebola: pred. proportio (Model 3: C-IMC 0.5 0.6 0.7 0.8 0.9 1 1 2 3 4 5 Ebola: pred. proportio (Model 4: day-t Model 4, group C Model 4, group HW Ebola: pred. proportion without formal care (Model 2: symptom-specific early/care-req.) Result: in an (undetected/unexpected) Ebola outbreak, subsidies would lead to 20-30% higher use of formal care by day 5.
  23. 23. Other Results Health Outcome Effects of subsidies: I Average illness spell length reduced by 0.8 days – recall, only 30% receive a visit! I Mothers self-report significantly less worried about their children; 20% of days instead of 29% of days
  24. 24. Conclusion
  25. 25. Summary of Results I Open the black box of healthcare demand, estimate timing of care conditional on illness incidence I Results encouraging for opponents of user fees: I Families recognize need for care I Overuse and moral hazard not a primary concern I Unintended consequences of (only) providing information
  26. 26. Policy Relevance I Immediate policy impact: I Changes to the programs of our cooperating partner Mali Health I Focus on subsidies, re-focus health workers onto prevention I Many open questions: I How were care-seeking guidelines formulated? I Should we trust parents’ observations, but not their decisions? How? I Can we get more data, and how to use it? I Broader lessons for child poverty and healthcare access I Urban healthcare is different I Access 6= use; parents as gatekeepers of children’s use of resources I Non-monetary costs of care are important: mutiple dimensions of scarcity
  27. 27. Thank you!
  28. 28. Treatment Groups: Attrition Control Healthworker Free care HW & FC All Original Sample 463 433 451 417 1764 Not Found at Baseline 26 24 19 12 81 Moved Post-Baseline 34 23 35 23 115 Died Post-Baseline 0 1 3 1 5 Refused Post-Baseline 0 0 0 1 1 Unexplained Absence 4 6 5 3 18 2013 Sample 399 379 389 377 1544 Total Attrition 13.8% 12.5% 13.7% 9.6% 12.5% Attrition Post Baseline 8.7% 7.3% 10.0% 6.9% 8.3% Go back

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