Datasets:

electricsheepafrica
/

user-fee-abolition

id int64	facility_type string	residence string	catchment_population int64	staff_count int64	has_exemption_policy int64	primary_exemption_group string	opd_visits_per_1000 int64	ipd_admissions_per_1000 int64	institutional_delivery_rate float64	u5_utilisation_change_pct float64	revenue_loss_pct float64	compensatory_funding_received int64	funding_gap_pct float64	user_fee_per_visit_usd float64	drug_stockout_rate float64	quality_score float64	staff_motivation float64	wait_time_hours float64	equity_index float64	poorest_quintile_utilisation_share float64	year int64
1	health_post	rural	4,000	3	1	emergency	647	27	0.69	41.7	0.21	0	0.21	1.32	0.16	0.59	0.38	2.3	0.54	0.13	2,021
2	dispensary	rural	1,643	2	1	under_5	720	72	0.53	22.3	0.12	1	0	1.97	0.24	0.45	0.4	0.7	0.64	0.16	2,023
3	health_post	rural	2,937	2	1	under_5	696	49	0.41	25.2	0.15	0	0.15	0.85	0.4	0.45	0.62	3.8	0.51	0.15	2,022
4	health_post	rural	1,802	2	1	hiv_tb	465	26	0.64	32.1	0.27	0	0.27	1.1	0.31	0.51	0.55	0.4	0.51	0.12	2,022
5	health_centre	urban	6,024	7	1	under_5	487	45	0.47	24.3	0.33	0	0.33	1.56	0.16	0.53	0.39	5.4	0.65	0.05	2,021
6	health_post	urban	500	6	1	pregnant_women	685	60	0.68	35.4	0.35	0	0.35	0.68	0.16	0.5	0.33	4.1	0.52	0.06	2,021
7	health_post	urban	6,493	4	1	pregnant_women	582	30	0.56	46	0.22	1	0	0.54	0.08	0.49	0.49	6.1	0.57	0.19	2,023
8	health_centre	urban	4,549	9	1	under_5	450	20	0.6	53.7	0.22	0	0.22	1.19	0.38	0.58	0.45	1.7	0.6	0.21	2,020
9	dispensary	urban	5,801	2	1	indigent	470	26	0.66	24.1	0.2	1	0	1.22	0.39	0.56	0.58	0.3	0.54	0.1	2,022
10	health_centre	rural	7,831	6	1	indigent	867	37	0.5	26.6	0.22	0	0.22	0.52	0.26	0.58	0.8	0.8	0.45	0.12	2,021
11	health_post	urban	4,911	4	1	hiv_tb	1,009	32	0.47	28.6	0.02	1	0	3.59	0.12	0.42	0.72	0.6	0.41	0.12	2,020
12	health_post	rural	2,009	2	1	under_5	426	36	0.55	33.5	0.14	0	0.14	1.84	0.27	0.59	0.51	7.3	0.46	0.15	2,020
13	health_centre	urban	9,146	4	1	emergency	692	47	0.37	43.9	0.25	0	0.25	0.75	0.28	0.56	0.46	0.5	0.52	0.15	2,023
14	health_centre	rural	6,353	5	1	pregnant_women	596	39	0.45	25	0.33	0	0.33	2.83	0.37	0.6	0.71	5.4	0.65	0.12	2,022
15	health_centre	rural	3,643	6	1	disabled	639	22	0.52	52.7	0.26	0	0.26	0.54	0.25	0.4	0.42	13.4	0.47	0.2	2,022
16	health_centre	rural	6,144	6	1	indigent	787	31	0.68	46	0.22	0	0.22	1.18	0.16	0.53	0.48	0.5	0.67	0.08	2,021
17	health_post	rural	855	6	1	hiv_tb	616	9	0.77	23.1	0.21	1	0	0.38	0.12	0.36	0.4	0.2	0.61	0.15	2,019
18	dispensary	rural	1,556	4	1	under_5	687	47	0.5	27.3	0.22	1	0	0.79	0.3	0.52	0.49	0.4	0.31	0.07	2,020
19	health_post	urban	3,998	4	1	under_5	869	41	0.48	21.1	0.05	1	0	0.81	0.33	0.76	0.33	0.2	0.43	0.16	2,023
20	health_post	urban	1,289	4	1	elderly	708	59	0.54	7.8	0.31	0	0.31	1.95	0.29	0.53	0.54	0.6	0.8	0.14	2,020
21	health_centre	rural	6,666	6	1	pregnant_women	964	56	0.46	35.2	0.16	0	0.16	1.12	0.31	0.51	0.63	1.8	0.55	0.27	2,022
22	health_post	rural	3,661	5	1	under_5	758	56	0.62	25.7	0.25	1	0	1.75	0.07	0.51	0.26	10.1	0.71	0.18	2,022
23	health_centre	rural	4,913	7	1	under_5	706	50	0.5	43.5	0.36	0	0.36	0.59	0.38	0.53	0.67	1.6	0.72	0.14	2,021
24	health_centre	urban	4,117	5	1	pregnant_women	522	14	0.48	33.7	0.18	0	0.18	0.91	0.27	0.43	0.58	1.5	0.6	0.17	2,023
25	dispensary	rural	1,885	4	1	under_5	638	45	0.59	18.5	0.29	1	0	0.91	0.18	0.62	0.52	1.2	0.54	0.15	2,022
26	health_post	rural	5,172	7	1	emergency	458	27	0.61	54.2	0.08	1	0	2.98	0.08	0.4	0.45	2.6	0.65	0.15	2,023
27	health_centre	rural	8,548	6	1	under_5	688	18	0.63	17.9	0.07	0	0.07	1.16	0.19	0.72	0.45	0.1	0.58	0.11	2,019
28	health_centre	rural	8,725	9	1	under_5	735	17	0.66	60.8	0.22	1	0	0.92	0.31	0.34	0.52	1.6	0.77	0.13	2,021
29	district_hospital	urban	12,638	19	1	pregnant_women	597	14	0.58	16.5	0.17	0	0.17	0.36	0.09	0.61	0.44	3.1	0.64	0.15	2,020
30	health_centre	rural	6,698	13	1	under_5	575	33	0.62	26.3	0.3	0	0.3	0.61	0.17	0.27	0.38	0.9	0.53	0.19	2,019
31	health_centre	rural	8,098	5	1	under_5	481	39	0.55	11.8	0.04	1	0	0.81	0.15	0.54	0.64	1.6	0.37	0.09	2,020
32	health_centre	rural	3,719	4	1	hiv_tb	675	51	0.68	5.7	0	1	0	2.04	0.15	0.33	0.51	0.5	0.77	0.16	2,023
33	dispensary	urban	1,901	5	1	emergency	721	58	0.66	41.1	0.26	1	0	0.34	0.26	0.48	0.35	6.2	0.76	0.21	2,023
34	health_post	urban	2,905	4	1	under_5	942	53	0.58	33.7	0.2	0	0.2	0.52	0.23	0.46	0.35	0.3	0.6	0.05	2,019
35	health_post	urban	4,551	3	1	indigent	859	56	0.56	11.3	0.17	0	0.17	0.89	0.19	0.58	0.44	0.3	0.59	0.12	2,022
36	health_centre	rural	5,037	11	1	elderly	466	34	0.49	16.6	0.17	1	0	3.01	0.22	0.78	0.5	1	0.54	0.14	2,021
37	health_post	rural	1,085	4	1	pregnant_women	652	45	0.63	0.9	0.27	1	0	0.42	0.24	0.56	0.42	0.2	0.39	0.12	2,021
38	health_centre	urban	3,984	12	1	under_5	852	33	0.28	4.4	0.12	0	0.12	0.78	0.25	0.51	0.63	1	0.45	0.16	2,021
39	health_centre	rural	5,705	5	1	emergency	527	45	0.65	20.7	0.3	0	0.3	2.37	0.3	0.71	0.27	0.9	0.45	0.14	2,023
40	health_post	rural	2,160	2	1	under_5	722	57	0.78	34.6	0.26	1	0	0.95	0.34	0.65	0.53	1.5	0.61	0.2	2,021
41	health_post	urban	500	3	1	hiv_tb	461	29	0.74	22.7	0.42	0	0.42	1.28	0.41	0.57	0.38	3.5	0.55	0.07	2,020
42	district_hospital	rural	12,069	15	1	pregnant_women	750	25	0.46	46.6	0.16	0	0.16	1.31	0.3	0.37	0.53	0.7	0.59	0.17	2,021
43	dispensary	rural	3,708	4	1	emergency	632	45	0.67	31.8	0.21	1	0	0.97	0.18	0.5	0.58	2.7	0.59	0.17	2,022
44	health_post	urban	500	3	1	indigent	658	35	0.54	39.3	0.23	0	0.23	1.28	0.31	0.3	0.46	2.5	0.55	0.14	2,021
45	dispensary	rural	1,499	1	1	pregnant_women	649	54	0.51	42.1	0.27	1	0	1.79	0.32	0.56	0.41	0.8	0.49	0.16	2,023
46	dispensary	rural	2,091	3	1	indigent	716	41	0.63	27.7	0.35	0	0.35	1.97	0.19	0.54	0.37	5.8	0.72	0.13	2,023
47	health_centre	rural	2,814	6	1	under_5	720	40	0.59	23.9	0.06	0	0.06	1.48	0.22	0.48	0.5	3.2	0.57	0.1	2,023
48	health_post	urban	3,489	4	1	indigent	471	50	0.42	18.1	0.33	1	0.03	2.44	0.22	0.41	0.47	0.1	0.56	0.19	2,020
49	health_post	urban	3,400	1	1	pregnant_women	611	37	0.55	56.6	0.19	1	0	0.28	0.16	0.52	0.42	0.3	0.53	0.2	2,020
50	health_post	rural	2,507	2	1	under_5	652	50	0.64	24.2	0.3	0	0.3	1.12	0.35	0.58	0.43	3.2	0.56	0.14	2,023
51	dispensary	urban	500	4	1	emergency	942	33	0.54	12.8	0.01	1	0	0.55	0.24	0.36	0.41	1.9	0.59	0.16	2,021
52	health_post	rural	3,765	1	1	under_5	598	45	0.65	27.9	0.35	1	0.05	0.86	0.33	0.78	0.74	0.8	0.44	0.21	2,019
53	health_centre	rural	6,840	4	1	pregnant_women	698	53	0.52	27.2	0.13	1	0	0.44	0.07	0.28	0.36	4	0.54	0.2	2,022
54	dispensary	urban	3,547	4	1	disabled	457	41	0.62	18.1	0.2	1	0	1.45	0.41	0.7	0.38	1.8	0.49	0.19	2,022
55	dispensary	rural	2,156	3	1	indigent	532	30	0.67	29.4	0.37	1	0.07	1.82	0.26	0.65	0.45	4.2	0.54	0.1	2,023
56	health_post	rural	5,573	4	1	under_5	913	45	0.55	47.9	0	1	0	1.61	0.26	0.58	0.34	1.4	0.79	0.18	2,020
57	health_centre	rural	1,741	10	1	elderly	246	25	0.73	-11.7	0.17	1	0	1.62	0.18	0.6	0.57	1	0.53	0.16	2,021
58	health_post	urban	1,378	2	1	pregnant_women	697	16	0.57	41.1	0.01	1	0	1.69	0.28	0.6	0.72	0.3	0.63	0.27	2,022
59	health_centre	rural	6,877	7	1	disabled	440	45	0.81	37	0.16	0	0.16	0.78	0.22	0.5	0.61	6.3	0.65	0.12	2,020
60	dispensary	urban	4,991	6	1	elderly	678	44	0.76	48.4	0	1	0	0.91	0.07	0.56	0.65	0.9	0.59	0.09	2,023
61	health_post	urban	3,424	2	1	elderly	743	18	0.72	25.1	0.18	1	0	0.71	0.32	0.58	0.58	2.2	0.61	0.12	2,022
62	dispensary	rural	5,235	1	1	pregnant_women	807	40	0.55	26.9	0.24	1	0	1.11	0.16	0.65	0.61	1.8	0.64	0.12	2,020
63	health_centre	rural	6,473	7	1	under_5	626	44	0.86	52.7	0.17	1	0	0.82	0.3	0.54	0.45	2.2	0.54	0.25	2,022
64	health_centre	rural	7,925	9	1	under_5	647	6	0.56	27.6	0.41	0	0.41	0.79	0.42	0.6	0.57	1	0.59	0.18	2,020
65	health_centre	rural	6,656	5	1	pregnant_women	702	22	0.67	12.3	0.14	1	0	2.21	0.28	0.52	0.56	1.5	0.54	0.24	2,020
66	health_centre	rural	7,791	13	1	under_5	303	49	0.65	34.6	0.3	0	0.3	3.34	0.15	0.64	0.3	3.6	0.65	0.15	2,020
67	health_post	rural	500	2	1	under_5	532	31	0.54	9.4	0.14	1	0	1.59	0.33	0.53	0.45	1	0.45	0.08	2,020
68	health_centre	rural	6,324	8	1	elderly	290	45	0.72	27.7	0.26	1	0	0.93	0.09	0.27	0.61	2.3	0.5	0.07	2,023
69	health_post	rural	3,255	3	1	emergency	641	56	0.73	8.7	0.17	1	0	1.36	0.27	0.52	0.45	2.3	0.52	0.14	2,020
70	dispensary	rural	8,328	2	1	under_5	657	51	0.72	32.9	0.31	0	0.31	2.6	0.29	0.68	0.35	2.1	0.57	0.14	2,023
71	dispensary	rural	4,447	6	1	under_5	658	38	0.72	27.3	0.13	0	0.13	2.15	0.3	0.5	0.47	0.4	0.6	0.05	2,022
72	dispensary	rural	500	3	1	pregnant_women	650	44	0.5	28.7	0.04	0	0.04	1.31	0.23	0.36	0.62	4.9	0.46	0.12	2,020
73	health_post	rural	4,956	1	1	hiv_tb	690	37	0.68	22	0.04	0	0.04	0.73	0.13	0.6	0.44	0.8	0.34	0.15	2,023
74	health_post	rural	500	4	1	hiv_tb	555	5	0.66	28.3	0.1	0	0.1	0.7	0.2	0.62	0.34	0.4	0.38	0.1	2,023
75	district_hospital	urban	10,118	21	1	indigent	635	39	0.55	8.4	0.15	1	0	0.44	0.23	0.45	0.51	1.8	0.73	0.16	2,021
76	health_post	rural	1,346	3	1	hiv_tb	543	31	0.71	39.4	0.37	0	0.37	0.54	0.26	0.41	0.41	7.2	0.42	0.08	2,021
77	district_hospital	urban	10,164	23	1	emergency	576	41	0.42	55.6	0.31	0	0.31	0.45	0.27	0.42	0.68	0.1	0.56	0.05	2,023
78	health_centre	rural	8,218	4	1	pregnant_women	601	12	0.54	25.1	0.19	0	0.19	0.77	0.25	0.6	0.46	2.4	0.56	0.05	2,023
79	health_post	rural	4,421	3	1	pregnant_women	574	49	0.69	37.3	0.17	0	0.17	1.59	0.37	0.63	0.39	1.4	0.65	0.22	2,023
80	dispensary	rural	2,614	3	1	indigent	607	62	0.47	21.2	0.2	1	0	0.41	0.12	0.31	0.5	2.3	0.5	0.17	2,020
81	health_post	urban	3,844	1	1	under_5	819	45	0.41	39.8	0.09	1	0	1.85	0.28	0.57	0.47	1.3	0.51	0.15	2,020
82	health_post	rural	500	4	1	under_5	767	61	0.53	31.5	0	0	0	0.53	0.27	0.36	0.57	0.8	0.46	0.08	2,020
83	district_hospital	urban	8,897	19	1	emergency	559	56	0.65	28	0.26	0	0.26	1.02	0.26	0.49	0.55	9.4	0.61	0.17	2,023
84	health_post	rural	1,267	3	1	emergency	337	56	0.57	12.1	0.14	0	0.14	1.68	0.32	0.34	0.45	3.5	0.71	0.07	2,023
85	health_centre	rural	4,645	7	1	pregnant_women	508	70	0.59	33.7	0.02	0	0.02	1.14	0.15	0.66	0.36	6.9	0.48	0.15	2,021
86	health_centre	urban	4,531	3	1	pregnant_women	611	35	0.59	55.4	0.07	0	0.07	0.32	0.27	0.74	0.56	0.2	0.48	0.14	2,022
87	health_post	urban	2,896	2	1	emergency	738	43	0.7	31.3	0.24	0	0.24	0.95	0.2	0.82	0.45	0.8	0.6	0.15	2,021
88	dispensary	urban	500	5	1	under_5	908	42	0.58	20.1	0.26	0	0.26	1.01	0.17	0.57	0.49	3.1	0.37	0.17	2,023
89	health_centre	rural	8,616	3	1	under_5	574	54	0.46	34.4	0.29	1	0	3.16	0.17	0.38	0.38	4.1	0.61	0.14	2,021
90	district_hospital	rural	14,317	16	1	under_5	744	32	0.36	21	0.09	0	0.09	2.81	0.28	0.6	0.46	1.6	0.67	0.14	2,023
91	health_centre	urban	3,186	3	1	under_5	644	40	0.32	16.3	0.24	1	0	0.5	0.27	0.67	0.59	8.7	0.49	0.11	2,023
92	health_post	rural	2,763	5	1	none	691	14	0.49	41.6	0.17	0	0.17	2.32	0.15	0.45	0.53	1.1	0.61	0.18	2,020
93	health_centre	rural	6,125	8	1	pregnant_women	564	46	0.71	31.5	0.43	0	0.43	1.21	0.17	0.51	0.53	0.2	0.59	0.2	2,020
94	dispensary	urban	3,288	1	1	indigent	802	34	0.6	29	0.27	1	0	0.52	0.27	0.62	0.54	3.3	0.63	0.1	2,020
95	health_centre	rural	7,158	8	1	pregnant_women	601	21	0.62	30.8	0.25	1	0	1.44	0.21	0.8	0.53	0.2	0.43	0.05	2,023
96	health_centre	rural	10,021	4	1	pregnant_women	348	37	0.58	26.8	0.12	0	0.12	0.9	0.26	0.62	0.63	6.1	0.5	0.16	2,019
97	health_centre	rural	7,959	6	1	hiv_tb	665	28	0.59	18.1	0.09	1	0	1.09	0.31	0.81	0.53	1.1	0.42	0.07	2,022
98	health_centre	urban	5,921	8	1	emergency	528	39	0.72	14.5	0.19	1	0	0.24	0.35	0.41	0.54	1	0.68	0.17	2,023
99	district_hospital	rural	11,610	18	1	under_5	615	12	0.53	36.2	0.09	1	0	1.72	0.26	0.18	0.35	0.6	0.48	0.05	2,022
100	health_centre	rural	6,553	6	1	under_5	845	33	0.72	43.9	0.46	0	0.46	0.74	0.22	0.49	0.39	0.6	0.5	0.16	2,023

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User Fee Abolition & Free Care Policies

Abstract

This synthetic dataset models health facility experiences with user fee policies across three SSA scenarios: comprehensive abolition (Uganda/Sierra Leone-like), targeted exemptions (Ghana/Kenya), and fee retention (Nigeria/DRC). Each scenario captures utilisation changes, drug stockouts, revenue loss, quality, equity, and staff motivation.

Parameterization Evidence

Parameter	Value	Source	Year
Fee removal utilisation increase	30-50%	Ridde & Morestin, Lancet	2011
Uganda OPD visits increase	+77%	McPake et al., Health Policy & Planning	2011
SSA countries with exemptions	30+	WHO AFRO	2023
Fee removal & quality concerns	Mixed	Lagarde & Palmer, Cochrane	2008

Validation

Usage

from datasets import load_dataset
ds = load_dataset("electricsheepafrica/user-fee-abolition", name="targeted_exemption")
df = ds['train'].to_pandas()

References

Ridde V & Morestin F (2011). User fee removal in Africa. Lancet. DOI: 10.1016/S0140-6736(11)60817-9
McPake B et al. (2011). Removing user fees. Health Policy & Planning 26:ii104-17
Lagarde M & Palmer N (2008). Cochrane review. DOI: 10.1002/14651858.CD007396
WHO AFRO (2023). https://www.afro.who.int

Citation

@dataset{electricsheepafrica_user_fee_2025,
  title   = {User Fee Abolition and Free Care Policies Dataset},
  author  = {Electric Sheep Africa},
  year    = {2025},
  url     = {https://huggingface.co/datasets/electricsheepafrica/user-fee-abolition},
  license = {CC-BY-4.0}
}

License

CC-BY-4.0

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