The economic burden of unsafe abortion for women and households in Zambia

Tiziana Leone, LSE

Ernestina Coast, LSE

Divya Parmar, City University

Bellington Vwalika, UTH Lusaka

Safe Unsafe

Background

• Although abortion is legal, unsafe abortion is still high in Zambia

• Stigma and barriers to access mean that women still use illegal and unsafe clandestine providers

• Limited evidence globally on economic consequences of seeking an unsafe abortion compared to a safe abortion

• Studies often fail to account for indirect costs (e.g. loss of wages, transport, accommodation), actions taken in order to find money or for the costs for friends and family

Unsafe abortion…

• a large health risk for women because of inadequate skills of the providers, unsanitary environments, and hazardous techniques

• increase the rate of complications (e.g.: severe bleeding, abdominal and genital injury) or death

• can lead to further complications (e.g.: haemorrhage, sepsis, genital perforation)

• might need complex tertiary care which is only available at referral public hospitals with the capacity for surgery, blood transfusion, and intensive care

A relatively liberal abortion law in Zambia

• Abortion is legally permitted:

⁻ To save the life of a woman

⁻ To preserve physical health

⁻ To preserve mental health

⁻ Foetal impairment

⁻ Socio-economic and welfare of existing children can be taken into account

Gestational age limits apply

Estimates of abortion for Zambia

Annual

estimate

Total induced abortions 114,279

• Unsafe 108,264

& require post-abortion care 45,471

• Safe 6,015

Aims and objectives

• Estimate and compare the costs of safe

abortion and post-abortion care (PAC)

following an unsafe abortion for women and

their households

• Analyse the impact of different pathways to termination of pregnancy on economic burdens and their determinants

Primary Data

• 112 interviews with women

– Enough statistical power level of confidence 95% and a margin of error at 5% given a response level of 80% (87% response level achieved)

• For each woman medical records linked

• Data collected January-December 2013 for all women identified as having undergone either a safe abortion or having received PAC following an unsafe abortion in the study hospital in Lusaka and discharged Monday to Friday (08:00-16:00 and 06:00-17:00)

• Interviews conducted privately with women following treatment and prior to discharge

Research instrument

• Available from: http://www.abortionresearchconsortium.org/

• Covered:

– socio-demographic background

– direct service costs (e.g.: fees per procedure or

intervention)

– indirect costs (e.g.: travel, food, loss of productivity)

– resources used to pay costs (e.g.: credit, asset sale,

borrowing, loss of wages)

– household assets used to calculate the wealth asset

Methods strengths and innovations

• Costs included all attempts and actions prior to arriving at hospital

• Medical notes used to validate individual reports of direct hospital costs

• Qualitative and quantitative data collected simultaneously

Methods for costing Total patient costs =

Direct medical costs (e.g. pregnancy test costs, charges paid by women for un/safe abortion, fees)

+ Indirect nonmedical costs (e.g. childcare, travel, accommodation, informal payments)

+ Productivity losses (e.g. time away from work/loss of income for woman and people involved, including housework)

Linear regression of individual costing controlling for medical procedures (e.g. medical abortion vs manual vacuum aspiration) and socio-economic determinants

Pathways to study hospital in our sample

%

N=112

Safe abortion at hospital 59.8

PAC after unsafe abortion:

[Medical abortion self-initiated]

[Other method e.g.: overdose, insert foreign object]

41.2

[14.7]

[25.5]

Percentage of women by age and un/safe abortion

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

14-19 20-24 25-29 30-34 35+

Safe

Unsafe

Percentage of women by un/safe abortion and wealth

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

poorest below average average above average wealthiest

Safe

Unsafe

First attempt

Includes 2 ambiguous

cases

No information

about 3 (7%)

1 attempts third

unsafe attempt

112

women

34 (89%) go to

hospital

Second attempt

Government hospital

4 make a 2nd unsafe attempt

71 (63%) report going

straight to hospital

11 (15%)

receive referral

2 (50%)

receive referral

38 attempt an unsafe abortion 4 seek an

alternative

unsafe method

22 (65%)

receive referral

41(37%) visit

different providers

What happens before arriving at hospital?

Breakdown of costs incurred by women (US$)

Safe abortion

Unsafe abortion +

PAC

Direct pre-hospital

2.6 5.8

Indirect pre-hospital

4.7 17.7

Direct at hospital 6.5 4.9

Indirect at hospital

38.3 35.5

Total costs 52.0 64.0

• Medical abortion = $33

• PAC following a failed

abortion = $88

• Average minimum monthly salary for a domestic worker is $100 Gross

• $12 is the equivalent of 3 day’s work

Costs for women by un/safe abortion and wealth quintile

Determinants of costs

Cost

Age

Parity NS

Wealth

Procedure PAC>ToP

Education NS

Ward (High vs low cost) NS

Main activity Business owners pay more

What determines the costs that women incur?

• Inadequate decentralisation of ToP services

– Referrals from district clinics to tertiary hospital means further economic burden for women

• Treating the consequences of an unsafe abortion costs up to 70% more for women than a safe medical abortion

• Indirect payments account for the largest part of the burden

• Costs increase with wealth: women asked to pay more according to their visible wealth status

• More than half had to ask relatives and friends for money adding further burden on the wider household

Limitations

• Only one site but most of abortion care done there at

the time the data were collected

• Costs accounted for up to the time of the interview but

could be more costs post-hospital (transport back

home included in our calculations)

• School days missed costs not included

• Costs underestimated due to the lack of data for more

serious complications and those women that die

Future work

• This study has looked at the overall experience

– By costing directly the expenses occurred at the last leg of the journey we would miss a big chunk of burden that the whole experience is for women. Need to assess uncertainty beyond CIs (e.g.: Monte Carlo simulation/sensitivity analysis)

• More in depth study on more serious cases which might have been missed by our study and account for underrepresentation with cost unit weighting

More information

http://zambiatop.wordpress.com/

https://twitter.com/ZambiaToP

@ZambiaToP