Management of pharmaceutical services in the Brazilian primary health care

Gerlack, Letícia Farias; Karnikowski, Margô Gomes de Oliveira; Areda, Camila Alves; Galato, Dayani; Oliveira, Aline Gomes de; Álvares, Juliana; Leite, Silvana Nair; Costa, Ediná Alves; Guibu, Ione Aquemi; Soeiro, Orlando Mario; Costa, Karen Sarmento; Guerra Junior, Augusto Afonso; Acurcio, Francisco de Assis

doi:10.11606/S1518-8787.2017051007063

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Original Articles • Rev. Saúde Pública 51 (suppl 2) • 2017 • https://doi.org/10.11606/S1518-8787.2017051007063 linkcopy

Management of pharmaceutical services in the Brazilian primary health care

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

OBJECTIVE To identify limiting factors in the management of pharmaceutical services in the primary health care provided by the Brazilian Unified Health System (SUS).

METHODS This study was based on the data from the Pesquisa Nacional sobre Acesso, Utilização e Promoção do Uso Racional de Medicamentos no Brasil (PNAUM – National Survey on Access, Use and Promotion of Rational Use of Medicines), and it was conducted by interviews with professionals responsible for pharmaceutical services in Brazilian cities, in 2015. To identify the management limiting factors, we considered the organizational, operational, and sustainability indicators of the management. For the analyses, we included the weights and structure of analysis plan for complex samples. The results were expressed by frequencies and measures of central tendency with 95% confidence interval, considering the Brazilian geographic regions.

RESULTS We identified the following limiting factors: lack of pharmaceutical services in the Municipal Health Secretariat organization chart (24%) and in the health plan (18%); lack of participation of managers in the Health Board and the absence of reference to this topic in the agenda of meetings (58.4%); lack of financial autonomy (61.5%) and lack of knowledge on the available values (81.7%); lack of adoption of operational procedures (about 50%) for selection, scheduling, and acquisition; and the fact that most professionals evaluate the organization of pharmaceutical services as good and great (58.8%), despite the worrisome indicators.

CONCLUSIONS Pharmaceutical services management is currently supported by a legal and political framework that should guide and contribute to improve the pharmaceutical services in the Brazilian Unified Health System primary health care. However, there is a mismatch between the goals established by these guidelines and what is actually happening.

Pharmaceutical Services, organization & administration; Primary Health Care; Health Management; Health Services Research; National Drug Policy; Unified Health System

Indicator	North	Northeast	Midwest	Southeast	South	Brazil	p

	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)
PS in the organizational chart of the Municipal Health Secretariat/FD (n = 504)	62 (63.8) (53.3–73.1)	76 (78.3) (67.9–86.1)	76 (75.1) (65.4–82.7)	84 (80.0) (70.7–86.9)	78 (72.0) (62.5–79.9)	376 (76.0) (71.4–80.1)	0.343
PS in the City/District Health Plan (n = 504)	72 (74.2) (64.1–82.2)	88 (92.3) (84.0–96.5)	77 (76.1) (66.5–83.6)	81 (74.9) (65.2–82.6)	91 (83.1) (74.5–89.2)	409 (82.0) (77.9–85.5)	0.001
Cities/FD with PTC (n = 503)	14 (10.7) (6.0–18.3)	16 (9.5) (4.8–18.0)	16 (13.6) (8.2–21.9)	19 (13.3) (7.8–21.7)	23 (15.6) (9.8–23.9)	88 (12.5) (9.5–16.3)	0.628
Meeting of the PTC with minimum regularity every six months in Cities/FD (n = 105)	8 (40.4) (19.6–65.3)	13 (62.4) (30.7–86.2)	8 (38.9) (18.7–63.9)	13 (57.3) (32.4–79.0)	15 (43.8) (24.5–65.2)	57 (51.5) (38.8–63.9)	0.934
Cities/FD that have list of medicines (n = 495)	69 (70.6) (60.3–79.1)	85 (90.8) (81.8–95.6)	81 (82.9) (73.7–89.2)	89 (86.9) (78.3–92.4)	91 (82.0) (73.2–88.4)	415 (85.3) (81.4–88.5)	0.077
Cities/FD with update of the list of medicines at least annually (n = 419)	56 (82.9) (71.8–90.3)	69 (83.8) (73.3–90.7)	65 (83.1) (73.5–89.7)	72 (81.2) (71.1–88.3)	66 (73.1) (62.6–81.5)	328 (80.4) (75.6–84.5)	0.333
Cities with permanent commission of exclusive bidding for the acquisition of medicines	34 (37.2) (27.9–47.7)	26 (30.1) (20.9–41.3)	43 (44.8) (35.1–55.0)	39 (35.7) (26.6–45.9)	40 (35.0) (26.4–44.8)	182 (34.8) (30.0–39.9)	0.574

Indicator	North	Northeast	Midwest	Southeast	South	Brazil	p

	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)
Cities with accountability of the expenses with PS made on the CMS of the city (n = 323)	38 (56.0) (43.6–67.7)	32 (63.9) (48.7–76.8)	41 (63.6) (50.6–74.3)	40 (61.1) (48.5–72.4)	46 (65.4) (53.0–76.0)	197 (62.6) (56.1–68.7)	0.670
Cities where the manager of PS takes part in the CMS (n = 410)	39 (44.5) (34.2–55.4)	25 (38.1) (26.4–51.5)	41 (51.2) (39.9–62.3)	37 (41.9) (31.7–52.9)	36 (40.6) (30.5–51.5)	178 (41.6) (36.1–47.4)	0.854
Cities where the CMS decides on issues concerning PS (n = 420)	51 (58.2) (47.2–68.4)	43 (59.3) (46.5–71.0)	58 (70.2) (59.1–79.4)	54 (60.2) (49.3–70.1)	55 (61.5) (50.7–71.3)	261 (60.9) (55.2–66.3)	0.632
Cities that have mechanisms to receive criticism and suggestions from users about PS (n = 506)	35 (38.8) (29.2–49.3)	26 (24.3) (16.1–34.8)	34 (33.0) (24.3–42.9)	38 (35.8) (26.8–45.9)	43 (37.4) (28.5–47.2)	176 (32.7) (28.1–37.7)	0.566
Cities that have mechanisms to receive criticisms and suggestions from the health workers about PS (n = 420)	25 (28.8) (20.1–39.6)	18 (23.8) (14.7–36.2)	34 (41.1) (30.7–52.3)	33 (35.5) (25.9–46.4)	34 (36.5) (26.9–47.3)	144 (32.4) (27.4–37.9)	0.434

Indicators	North	Northeast	Midwest	Southeast	South	Brazil	p

	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)
Educational level of the manager (n = 504)							0.015
Up to high school	6 (6.8) (3.1–14.4)	2 (2.6) (0.6–9.8)	6 (6.2) (2.8–13.3)	3 (3.1) (1.0–9.3)	4 (4.0) (1.5–10.1)	21 (3.7) (2.2–6.1)
Higher education degree	78 (83.3) (74.1–9.7)	66 (71.3) (60.4–80.3)	72 (74.0) (64.4–81.8)	83 (80.9) (71.8–87.6)	68 (60.3) (50.5–69.4)	367 (72.9) (68.2–77.2)
Specialization	11 (9.9) (5.3–17.9)	26 (36.1) (17.5–36.9)	22 (19.7) (13.0–28.8)	19 (16.0) (9.9–24.7)	38 (35.7) (27.0–45.6)	116 (23.4) (19.3–28.0)
% of cities that offer qualification or training for professionals of PS (n = 418)	9 (10.1) (5.2–18.8)	8 (11.6) (5.6–22.4)	11 (14.6) (8.3–24.6)	11 (13.3) (7.5–22.6)	11 (9.2) (4.7–17.4)	50 (11.7) (8.5–16.0)	0.800
Cities with SOP for: (n = 491)
Selection of medicines	42 (45.9) (35.6–56.6)	46 (48.8) (37.7–60.0)	50 (51.5) (41.4–61.4)	60 (56.5) (46.3–66.1)	52 (45.9) (36.4–55.7)	250 (50.6) (45.3–55.8)	0.564
Scheduling	40 (45.0) (34.6–55.8)	50 (56.1) (44.7–67.0)	53 (53.0) (43.0–62.9)	68 (64.6) (54.4–73.7)	48 (43.2) (33.8–53.1)	259 (54.7) (49.5–59.9)	0.038
Acquisition	47 (52.6) (41.9–63.1)	52 (58.8) (47.3–69.4)	52 (52.8) (42.7–62.6)	69 (66.7) (56.5–75.5)	55 (49.4) (39.7–59.1)	275 (58.2) (52.9–63.2)	0.078
Cities where the pharmacist makes the technical specification of medicines to be purchased (n = 505)	77 (80.4) (70.9–87.4)	78 (83.1) (73.1–89.9)	90 (90.4) (82.7–94.9)	91 (89.3) (81.4–94.1)	96 (88.0) (80.1–93.0)	432 (86.6) (82.6–89.7)	0.352
Cities where there is purchase of medicines in local pharmacies (n = 499)							< 0.001
Always	4 (4.5) (1.7–11.4)	2 (2.6) (0.6–9.9)	16 (17.0) (10.6–26.0)	11 (11.7) (6.6–20.1)	12 (12.0) (6.9–20.0)	45 (9.0) (6.5–12.3)
Repeatedly	4 (4.5) (1.7–11.4)	4 (4.0) (1.3–11.5)	7 (7.4) (3.6–14.8)	4 (4.3) (1.6–10.9)	13 (13.0) (7.7–21.1)	32 (6.5) (4.4–9.4)
Sometimes	14 (15.9) (9.5–24.8)	19 (21.0) (13.3–31.6)	35 (36.3) (27.3–46.5)	31 (31.1) (22.5–41.2)	35 (32.2) (23.8–42.0)	134 (27.6) (23.3–32.5)
Rarely	25 (27.2) (18.9–37.3)	15 (14.6) (8.3–24.3)	17 (17.2) (10.9–26.3)	22 (20.5) (13.5–29.9)	19 (18.1) (11.7–26.9)	98 (18.4) (14.8–22.8)
Never	41 (40.9) (31.2–51.3)	43 (46.1) (35.3–57.2)	20 (18.8) (12.2–27.9)	30 (28.0) (19.9–38.0)	26 (20.8) (14.0–29.8)	160 (31.9) (27.2–36.9)
Cities where the ratio of the average percentage of expired medicines by the total number of acquisitions is up to 5% (n = 489)	77 (84.1) (75.1–90.3)	66 (73.9) (62.8–82.7)	80 (83.3) (74.5–89.5)	86 (85.5) (76.5–91.4)	91 (83.0) (74.3–89.2)	400 (81.3) (76.7–85.1)	0.472
Cities where the Secretariat has legal advice to answer lawsuits (n = 322)	37 (83.2) (67.9–92.1)	49 (84.8) (70.2–93.0)	62 (85.3) (74.8–92.0)	61 (80.4) (69.0–88.3)	61 (80.5) (69.2–88.3)	270 (82.1) (76.5–86.7)	0.855
Cities where the coordination of PS has autonomy for managing the financial resources destined to PS (n = 504)	53 (57.0) (46.6–66.9)	39 (43.4) (32.9–54.5)	44 (44.9) (35.3–55.0)	35 (32.7) (24.0–42.7)	36 (31.7) (23.3–41.4)	207 (38.5) (33.6–43.6)	0.079
Cities that received resources from the State or Federal Government for structuring PS in the primary health care in the past year (reforms, construction, among others) (n = 499)	23 (23.3) (15.7–33.1)	37 (44.3) (33.5–55.7)	23 (23.6) (16.1–33.2)	35 (34.6) (25.8–44.7)	27 (25.8) (18.2–35.2)	145 (33.5) (28.7–38.7)	0.066
Cities that spent resources in structuring PS in the past year (n = 501)	35 (34.2) (25.2–44.5)	50 (54.5) (43.3–65.1)	44 (45.9) (36.1–56.0)	35 (32.4) (23.7–42.5)	56 (50.2) (40.6–59.9)	220 (44.3) (39.3–49.5)	0.015
Managers who did not know which was the total expenditure of the city with PS in the past year (n = 501)	77 (85.2) (76.0–91.2)	67 (76.8) (65.9–85.0)	84 (88.5) (80.5–93.5)	79 (85.6) (77.0–91.7)	82 (79.0) (69.8–86.0)	389 (81.7) (77.2–85.5)	0.213
Managers who consider that the list of medicines adopted by the city meets the population demands (n = 501)							0.349
Completely	16 (24.6) (15.6–36.5)	24 (27.2) (18.1–38.7)	25 (29.3) (20.4–40.1)	32 (34.6) (25.1–45.5)	27 (27.8) (19.2–38.2)	124 (29.7) (24.7–35.1)
Partially	55 (75.4) (63.5–84.4)	63 (72.8) (61.3–81.9)	59 (70.7) (59.9–79.6)	59 (65.4) (54.5–74.9)	65 (71.1) (60.5–79.7)	301 (70.1) (64.6–75.0)
Evaluation of PS organization in the city/FD by the manager (n = 420)							0.852
Great	8 (9.8) (5.0–18.5)	4 (5.0) (1.6–14.3)	7 (9.3) (4.5–18.3)	7 (8.4) (4.0–16.6)	6 (7.1) (3.2–15.1)	32 (7.4) (4.9–10.9)
Good	38 (42.0) (31.9–52.9)	39 (56.4) (43.8–68.3)	42 (54.8) (43.5–65.6)	44 (48.2) (37.7–58.9)	48 (52.1) (41.4–62.5)	211 (51.4) (45.7–57.0)
Regular	32 (38.3) (28.4–49.3)	22 (30.0) (19.8–42.6)	25 (29.2) (20.1–40.3)	32 (36.1) (26.5–46.9)	25 (28.7) (20.0–39.3)	136 (32.3) (27.3–37.9)

Indicators	North	Northeast	Midwest	Southeast	South	Brazil	p

	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)	n (%) (95%CI)
Cities with some mechanism for the registration of technical complaint and notification of adverse events of medicines (n = 417)	19 (22.2) (14.5–32.5)	15 (15.9) (8.6–27.5)	19 (24.6) (16.1–35.6)	21 (22.9) (15.1–33.2)	23 (23.1) (15.3–33.2)	97 (21.1) (16.9–26.1)	0.212
Cities with records of expired medicines (n = 497)	77 (79.6) (69.9–86.7)	72 (75.9) (64.9–84.3)	84 (85.9) (77.4–91.6)	85 (81.7) (72.4–88.3)	94 (86.0) (77.8–91.5)	412 (81.2) (76.7–85.0)	0.119
Cities with computerized system for PS management (n = 501)	41 (40.1) (30.5–50.5)	60 (61.2) (50.0–71.4)	54 (53.5) (43.5–63.3)	81 (78.7) (69.2–85.8)	95 (87.9) (79.9–93.0)	331 (70.6) (65.9–74.9)	< 0.001
Cities with monitoring of the medicine storage conditions (n = 497)
Temperature	71 (72.0) (61.8–80.3)	82 (88.0) (78.4–93.7)	81 (82.0) (72.8–88.5)	82 (79.4) (69.9–86.5)	94 (85.1) (76.7–90.8)	410 (82.9) (78.6–86.4)	0.101
Moisture	58 (57.4) (47.0–67.2)	73 (77.2) (66.4–85.4)	72 (72.4) (62.5–80.5)	68 (65.3) (55.1–74.3)	75 (66.3) (56.6–74.9)	346 (69.0) (64.0–73.5)	0.229
Cleaning	84 (86.6) (77.7–92.2)	85 (93.3) (84.8–97.2)	90 (92.3) (84.9–96.2)	97 (94.6) (87.6–97.8)	103 (94.0) (87.3–97.3)	459 (93.2) (90.2–95.4)	0.363
Protection from insects	74 (76.2) (66.3–83.9)	80 (87.8) (78.3–93.5)	83 (84.9) (76.1–90.8)	88 (84.9) (76.0–90.9)	97 (88.1) (80.1–93.1)	422 (85.8) (81.8–89.0)	0.183
Cities in which the computerized system includes the items: (n = 336)
Acquisition	32 (79.0) (63.0–89.3)	48 (79.1) (65.5–88.3)	46 (84.3) (71.6–92.0)	73 (87.1) (77.7–92.9)	79 (84.0) (74.8–90.3)	278 (83.7) (78.6–87.8)	0.837
Financial control and execution	27 (69.2) (52.9–81.8)	39 (69.8) (55.5–81.1)	36 (67.7) (53.8–79.0)	53 (64.0) (52.8–73.8)	60 (63.6) (53.2–73.0)	215 (65.8) (59.7–71.4)	0.723
Inventory storage and control	35 (87.4) (72.7–94.8)	55 (91.7) (79.9–96.8)	54 (100) (100–100)	75 (88.4) (79.2–93.9)	85 (88.6) (80.1–93.8)	304 (90.0) (85.5–93.2)
Delivery of medicines to the user	29 (70.6) (54.1–83.1)	48 (77.2) (63.4–86.9)	48 (89.7) (78.1–95.5)	80 (94.8) (87.1–98.0)	93 (97.7) (91.3–99.4)	298 (89.8) (85.4–93.0)	0.036
Cities where the computerized system is networked with the UBS (n = 331)	14 (29.6) (17.6–45.1)	26 (33.2) (21.9–46.1)	34 (57.4) (44.0–69.8)	39 (44.3) (33.7–55.5)	59 (62.9) (52.4–72.3)	172 (46.6) (40.7–52.6)	0.009
Cities where the computerized system has user registration – Patient Record (n = 336)	8 (22.4) (11.6–38.8)	20 (37.2) (24.8–51.4)	25 (46.1) (33.0–59.7)	51 (62.6) (51.4–72.6)	57 (58.9) (48.3–68.7)	161 (52.4) (46.3–58.4)	0.004

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Faculdade de Saúde Pública da Universidade de São Paulo Avenida Dr. Arnaldo, 715, 01246-904 São Paulo SP Brazil, Tel./Fax: +55 11 3061-7985 - São Paulo - SP - Brazil
E-mail: revsp@usp.br

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[TFN1] PS: Pharmaceutical Services; FD: Federal District; PTC: Pharmacy and Therapeutics Committee.

[TFN2] Source: PNAUM Services – Brazil, 2015.