Differences in prescribed medicine availability in Primary Health Care: evidence from the Prover Project

Bueno, Maria Angélica Martins; Simões, Taynãna César; Luz, Tatiana Chama Borges

doi:10.1590/1413-81232022273.38782020

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FREE THEMES • Ciênc. saúde coletiva 27 (03) • Mar 2022 • https://doi.org/10.1590/1413-81232022273.38782020 copy

Differences in prescribed medicine availability in Primary Health Care: evidence from the Prover Project

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This is a cross-sectional study on the availability of prescribed medicines in Primary Health Care (PHC), with a probabilistic sample of 1,221 users of public pharmacies in a health pole municipality in Minas Gerais, in 2017. Medicine availability indicators were estimated, and a hierarchical logistic regression was performed, according to the behavioral model of health service use. Only 39.3% of patients received all medicines in the prescribed quantities. The most and the least available medicines were, respectively, those for the digestive system/metabolism, and for blood and hematopoietic organs. Full availability of the prescribed treatment was associated with higher schooling (≥ 8 years OR: 1.7; 95% CI: 1.3-2.4); proximity to the pharmacy (≤15 min OR: 1.7; 95% CI: 1.2-2.3); absence of out-of-pocket expenditure on medicines (OR: 2.2; 95% CI: 1.7-2.9), and a smaller number of prescription drugs (≤ 2 OR: 3.2; 95% CI: 2.3-4.4; 3/4 OR: 1.6; 95% CI: 1.2-2.1). These results showed differences in medicine availability within the Brazilian Unified Health System (SUS), and highlighted the need to reorganize the dispensing services network and pharmaceutical procurement planning, as well as to develop public policies to protect the vulnerable population.

Key words:
Primary health care; Pharmaceutical services; Prescriptions; Provision; Medicines

Anatomical group (1^st ATC level) and Therapeutic subgroup (2^nd ATC level)	Prescribed		Available
	n^a	%^b	n^c	%^d
Cardiovascular System (C)	1972	48.8	1432	72.6
Hypolipemiants (C10)	383	9.5	350	91.4
Beta blockers (C07)	240	5.9	183	76.3
Calcium channel blockers (C08)	169	4.2	119	70.4
Diuretics (C03)	495	12.3	344	69.5
Agents that act on the renin-angiotensin system (C09)	585	14.5	384	65.6
Cardiac stimulants/Cardiotonics/Glycosides (C01)	33	0.8	19	57.6
Anti-hypertensives (C02)	67	1.7	33	49.2
Digestive System and Metabolism (A)	669	16.6	536	80.1
Antacids/Antiulcers/Antiflatulents (A02)	263	6.5	252	95.8
Vitamins (A11)	28	0.7	23	82.1
Antidiabetic drugs (A10)	376	9.3	261	69.4
Mineral supplements (A12)	2	0.1	0	0
Central Nervous System (N)	566	14.0	327	57.8
Antiparkinsonian drugs (N04)	17	0.4	15	88.2
Analgesics (N02)	34	0.8	27	79.4
Psychoanaleptics (N06)	163	4.0	125	76.7
Psycholeptics (N05)	158	3.9	88	55.7
Antiepileptics (N03)	194	4.8	72	37.1
Blood and hematopoietic organs (B)	344	8.5	193	56.1
Antithrombotics (B01)	323	8.0	182	56.3
Antianemics (B03)	21	0.5	11	52.4
Hormones for systemic use (H)	158	3.9	113	71.5
Thyroid treatment (H03)	139	3.4	102	73.4
Corticosteroids for systemic use (H02)	19	0.5	11	57.9
Others (D-G-J-M-P-R-S)	330	8.2	217	65.7
Total	4039	100.0	2818	69.8

Variables	n (%)^a	Full treatment availability
Variables	n (%)^a	Prevalence (%)	OR^b (IC 95%)	p-value^b
Sex
Male	414 (34.9)	38.6	Ref.	-
Female	772 (65.1)	39.6	1.0 (0.8-1.3)	0.739
Age
60 years or older	650 (54.8)	36.9	Ref.	-
18-59 years	536 (45.2)	42.2	1.2 (1.0-1.6)	0.066*
Skin color
Non-White	608 (53.3)	38.7	Ref.	-
White	533 (46.7)	39.6	1.0 (0.8-1.3)	0.747
Schooling
0-3 years	262 (22.2)	33.6	Ref.	-
4-7 years	469 (39.8)	35.4	1.1 (0.8-1.5)	0.623
8 years or more	448 (38.0)	46.7	1.7 (1.3-2.4)	0.001*
Marital Status
Single/Divorced/Widowed/	505 (42.7)	37.0	Ref.	-
Married/Common-Law Partner	678 (57.3)	41.0	1.2 (0.9-1.5)	0.167*

Variables	n (%)^a	Full treatment availability
Variables	n (%)^a	Prevalence (%)	OR^b (IC 95%)	p-value^b
Personal monthly income^c
< 1 MW	321 (27.5)	41.4	Ref.	-
1 MW	446 (38.1)	36.6	0.8 (0.6-1.1)	0.171*
>1MW	402 (34.4)	40.3	0.9 (0.7-1.3)	0.758
Health insurance coverage
Yes	856 (72.2)	38.3	Ref.	-
No	330 (27.8)	41.8	1.2 (0.9-1.5)	0.269
Travel time to the pharmacy
>30 min	303 (25.6)	32.0	Ref.	-
15-30 min	435 (36.8)	37.5	1.3 (0.9-1.7)	0.127*
< 15 min	444 (37.6)	46.0	1.8 (1.3-2.4)	0.000*
Out-of-pocket expenditure on medicines in the past three months
Yes	906 (76.5)	34.6	Ref.	-
No	278 (23.5)	54.7	2.3 (1.7-3.0)	0.000*

Variables	n (%)^a	Full treatment availability
Variables	n (%)^a	Prevalence (%)	OR ^b (IC 95%)	p-value^b
Number of medicines prescribed in the past 15 days
5 or more	583 (49.2)	29.2	Ref.	-
3-4	356 (30.0)	40.7	1.7 (1.3-2.2)	0.000*
1-2	247 (20.8)	61.1	3.8 (2.8-5.2)	0.000*
Self-Perception of Health
Fair/Bad/Very Bad	675 (57.7)	35.7	Ref.	-
Very Good/Good	495 (42.3)	45.1	1.5 (1.2-1.9)	0.001*
Health conditions as diagnosed by the physician
Three or more	497 (41.9)	29.0	Ref.	-
Up to two	689 (58.1)	46.7	2.2 (1.7-2.7)	0.000*
Physical activity practice
No	669 (56.5)	38.0	Ref.	-
Yes	516 (43.5)	41.1	1.1 (0.9-1.4)	0.276
Recent alcohol use
Yes	248 (20.9)	41.9	Ref.	-
No	936 (79.1)	38.5	0.9 (0.7-1.2)	0.319
Currently smoking
Yes	143 (12.1)	35.7	Ref.	-
No	1042 (87.9)		1.2 (0.8-1.7)	0.340

Variables	Model 1		Model 2		Model 3
Variables	OR (95% CI)	p- value	OR (95% CI)	p- value	OR (95% CI)	p- value
Predisposing Factors
Schooling
0-3 years	Ref.		Ref.		Ref.
4-7 years	1.1 (0.8-1.5)	0.623	1.1 (0.8-1.6)	0.472	1.1 (0.8-1.5)	0.615
8 years or more	1.7 (1.3-2.4)	0.001*	1.7 (1.2-2.3)	0.002*	1.6 (1.1-2.2)	0.008*
Enabling Factors
Travel time to the pharmacy
>30 min	-	-	Ref.		Ref.
15-30 min	-	-	1.3 (0.9-1.7)	0.148	1.2 (0.9-1.7)	0.283
< 15 min	-	-	1.7 (1.2-2.3)	0.001*	1.6 (1.2-2.2)	0.004*
Out-of-pocket expenditure on medicines in the past three months
Yes	-	-	Ref.		Ref.
No	-	-	2.2 (1.7-2.9)	0.000*	1.8 (1.4-2.4)	0.000*
Need Factors
Number of medicines pre-scribed in the past 15 days
5 or more	-	-	-	-	Ref.
3-4	-	-	-	-	1.6 (1.2-2.1)	0.002*
1-2	-	-	-	-	3.2 (2.3-4.4)	0.000*
Akaike’s Criterion	1569.063			1522.264		1476.294

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[1] Collaborations

MAM Bueno and TCB Luz contributed equally to the study design, data analysis, interpretation and manuscript drafting. TCB Luz was responsible for funding acquisition and Prover Project coordination. TC Simões contributed with the data analysis.