Admissions due to ambulatory care-sensitive conditions (ACSC): an analysis based on socio-demographic characteristics, Brazil and regions, 2010 to 2019

Santos, Filipe Malta dos; Macieira, César; Machado, Antônio Thomaz Gonzaga da Matta; Borde, Elis Mina Seraya; Santos, Alaneir Fátima dos

doi:10.1590/1980-549720220012

Acessibilidade / Reportar erro

Brasil

Revista Brasileira de Epidemiologia

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Original Article • Rev. bras. Epidemiol. 25 • 2022 • https://doi.org/10.1590/1980-549720220012 copy

Admissions due to ambulatory care-sensitive conditions (ACSC): an analysis based on socio-demographic characteristics, Brazil and regions, 2010 to 2019

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT:

Objective:

To analyze the temporal trend of hospital admissions due to Ambulatory Care-Sensitive Conditions (ACSC) in Brazil per sex, region, cause and age group, from 2010 to 2019.

Methods:

This is an ecological study based on the temporal trend of ACSC rates. Standardized rates were analyzed in a simple linear regression and a generalized linear model (GLM) Gamma. The percentage change was also checked over three periods: 2010–2014, 2015–2019 and 2010–2019.

Results:

There was a reduction in hospital admission rates between 2010 and 2019 for Brazil: 124.3/10,000 inhab. to 88.2/10,000 inhab. among women (-29.0%) and 119.0/10,000 inhab. to 88.2/10,000 inhab. (-25.9%) among men in all regions. The decrease was more prominent between 2010–2014 (-17.7%) and (-17.8%) than between 2015–2019 (-.2%) and (-5.9%) for females and males, respectively. The milder decline in the period from 2015 to 2019 was more noticeable among age groups 0–4y and 5–19y in all regions. As for the causes, most ICD-10 diseases had a downward trend, the more expressive ones being gastroenteritis (-60%); however, an increase was seen in cerebrovascular diseases among women (11.2%) and men (17.1%), and angina (15% %) and skin infections (56.1%) among men.

Conclusion:

There was a significant drop in ACSC rates in the period analyzed, especially for age groups 0-4y and 5-19y. The rates had a milder drop from 2015 to 2019, a period of austerity and economic crisis.

Keywords:
Primary health care; Quality of health care; Hospitalizations; Family health

Region	Sex	2010	2014	2015	2019	Coefficient	p	R²	Variation 2010–19	Variation 2010–2014	Variation 2014–2019
Brazil	F	124.34	102.30	97.17	88.22	-3.92	<0.01	0.94	-29.06	-17.73	-9.21
Brazil	M	119.02	97.74	93.79	88.24	-3.34	<0.01	0.90	-25.86	-17.88	-5.92
Midwest	F	159.44	114.35	106.05	94.28	-7.06	<0.01	0.91	-40.87	-28.28	-11.10
Midwest	M	137.33	102.17	96.57	88.96	-5.28	<0.01	0.90	-35.22	-25.60	-7.87
Northeast	F	141.27	113.71	108.65	95.97	-4.93	<0.01	0.93	-32.07	-19.51	-11.67
Northeast	M	128.57	105.62	101.74	94.91	-3.64	<0.01	0.89	-26.18	-17.85	-6.71
North	F	178.97	148.34	129.37	117.70	-7.06	<0.01	0.93	-34.23	-17.11	-9.02
North	M	147.59	124.15	111.04	101.95	-5.35	<0.01	0.94	-30.92	-15.88	-8.18
Southeast	F	91.02	78.39	75.99	70.65	-2.30	<0.01	0.93	-22.37	-13.87	-7.03
Southeast	M	96.21	80.98	78.92	75.34	-2.37	<0.01	0.89	-21.70	-15.83	-4.54
South	F	142.10	119.39	115.50	104.39	-3.65	<0.01	0.91	-26.54	-15.98	-9.62
South	M	135.45	110.87	108.27	102.55	-3.11	<0.01	0.83	-24.29	-18.15	-5.28

Hospital admissions for ACSC among males
Age group	Region	2010	2014	2015	2019	β Coefficient	2010–2019 (%)	2010–2014 (%)	2015–2019 (%)
0-4 years	Brazil^* * generalized linear gamma model was used, not linear regression;	345.6	268.7	251.2	253.0	-0.03^† † p<0.01 of the coefficient.	-26.8	-22.2	0.7
	Midwest	365.1	258.9	243.3	266.6	-10.64^† † p<0.01 of the coefficient.	-27	-29.1	9.6
	Northeast^* * generalized linear gamma model was used, not linear regression;	409.4	313.6	287.4	288.8	-0.03^† † p<0.01 of the coefficient.	-29.5	-23.4	0.5
	North	465.7	357.6	317.6	305.8	-16.47^† † p<0.01 of the coefficient.	-34.3	-23.2	-3.7
	Southeast^* * generalized linear gamma model was used, not linear regression;	259.1	215	208.7	212	-0.02^† † p<0.01 of the coefficient.	-18.2	-17	1.6
	South^* * generalized linear gamma model was used, not linear regression;	330.5	260.5	247.6	247.1	-0.03^† † p<0.01 of the coefficient.	-25.2	-21.2	-0.2
5-19 years	Brazil	51.9	41.9	39.1	37.7	-1.46^† † p<0.01 of the coefficient.	-27.4	-19.4	-3.6
	Midwest	59.5	42.1	39.7	40.9	-1.92^† † p<0.01 of the coefficient.	-31.3	-29.3	3
	Northeast^* * generalized linear gamma model was used, not linear regression;	67.2	54.1	49.7	48.5	-0.03^† † p<0.01 of the coefficient.	-27.7	-19.5	-2.4
	North	73.0	59.8	50.6	45.8	-3.11^† † p<0.01 of the coefficient.	-37.3	-18.1	-9.5
	Southeast	34.1	28.7	28.1	27	-0.73^† † p<0.01 of the coefficient.	-20.6	-15.6	-3.6
	South^* * generalized linear gamma model was used, not linear regression;	48.2	37.1	36.9	35.6	-0.03^† † p<0.01 of the coefficient.	-26.1	-22.9	-3.5
20-59 years	Brazil	70.9	59.0	56.8	52.7	-2.1^† † p<0.01 of the coefficient.	-25.6	-16.7	-7.2
	Midwest	80.1	60.4	57.1	50.2	-3.36^† † p<0.01 of the coefficient.	-37.3	-24.5	-12
	Northeast	75.6	62.2	60.6	54.1	-2.54^† † p<0.01 of the coefficient.	-28.4	-17.7	-10.7
	North	88.1	73.2	65.1	59.3	-3.39^† † p<0.01 of the coefficient.	-32.7	-17	-9
	Southeast	60.2	51.2	49.4	47.2	-1.61^† † p<0.01 of the coefficient.	-21.6	-14.8	-4.5
	South	80.0	67.6	66.9	64.0	-1.47^† † p<0.01 of the coefficient.	-20.1	-15.5	-4.4
60-79 years	Brazil	420.4	354.2	347.2	315.3	-11.81^† † p<0.01 of the coefficient.	-25	-15.7	-9.2
	Midwest	522.9	399.8	379.5	318.6	-22.16^† † p<0.01 of the coefficient.	-39.1	-23.6	-16.1
	Northeast	401.9	350.3	351.4	320.2	-9.88^† † p<0.01 of the coefficient.	-20.3	-12.8	-8.9
	North	467.2	430.2	396.1	357.3	-14.82^† † p<0.01 of the coefficient.	-23.5	-7.9	-9.8
	Southeast	359.7	301.5	297.3	273.0	-10^† † p<0.01 of the coefficient.	-24.1	-16.2	-8.2
	South	560.8	460.6	448.2	409.2	-14.69^† † p<0.01 of the coefficient.	-27	-17.9	-8.7

Hospital admissions for ACSC among females
Age Group	Região	2010	2014	2015	2019	β Coefficient	2010–2019 (%)	2010–2014 (%)	2015–2019 (%)
0-4 years	Brazil^* * generalized linear gamma model was used, not linear regression;	308.6	244.5	227.4	229.1	-0.03^† † p<0.01 of the coefficient.	-25.8	-20.8	0.7
	Midwest	335	242.6	223.5	237.9	-9.91^† † p<0.01 of the coefficient.	-29	-27.6	6.4
	Northeast^* * generalized linear gamma model was used, not linear regression;	364.1	283.7	259.4	262.9	-0.03^† † p<0.01 of the coefficient.	-27.8	-22.1	1.3
	North	433.8	326.6	286	279.8	-15.3^† † p<0.01 of the coefficient.	-35.5	-24.7	-2.2
	Southeast^* * generalized linear gamma model was used, not linear regression;	229.3	196.5	190.4	193.7	-3.16^† † p<0.01 of the coefficient.	-15.5	-14.3	1.7
	South^* * generalized linear gamma model was used, not linear regression;	282.3	232.5	221.3	215.5	-0.03^† † p<0.01 of the coefficient.	-23.7	-17.7	-2.6
5-19 years	Brazil	65.5	59.4	55.7	51.3	-1.5^† † p<0.01 of the coefficient.	-21.7	-9.3	-7.9
	Midwest	81.5	67.4	60.9	56.4	-2.78^† † p<0.01 of the coefficient.	-30.7	-17.3	-7.4
	Northeast	78.2	68.2	63.4	59.6	-1.82^† † p<0.01 of the coefficient.	-23.8	-12.8	-6
	North	96.7	85.4	74.6	68.8	-3.13^† † p<0.01 of the coefficient.	-28.9	-11.6	-7.8
	Southeast	43.7	42.8	41.7	37.6	-0.72^† † p<0.01 of the coefficient.	-13.9	-2	-9.8
	South	66.4	61.7	60.4	54.8	-1.12^† † p<0.01 of the coefficient.	-17.5	-7	-9.3
20-59 years	Brazil	87.2	72.1	68.7	61.9	-2.83^† † p<0.01 of the coefficient.	-29	-17.3	-10
	Midwest	112.1	81.8	76.2	65.8	-5.13^† † p<0.01 of the coefficient.	-41.2	-27	-13.6
	Northeast	99.3	78.7	75.8	65	-3.88^† † p<0.01 of the coefficient.	-34.6	-20.7	-14.2
	North	138.4	113.2	97.7	88.6	-5.73^† † p<0.01 of the coefficient.	-36	-18.3	-9.4
	Southeast	62.6	54.2	52.7	49.1	-1.6^† † p<0.01 of the coefficient.	-21.7	-13.4	-6.9
	South	99.8	85.9	83.7	76.4	-2.17^† † p<0.01 of the coefficient.	-23.4	-13.9	-8.7
60-79 years	Brazil	348.7	279.1	268.4	230.6	-13.18^† † p<0.01 of the coefficient.	-33.9	-20	-14.1
	Midwest	488.9	322.8	302	248.8	-25.57^† † p<0.01 of the coefficient.	-49.1	-34	-17.6
	Northeast	378.2	305.5	300.1	246.3	-15.26^† † p<0.01 of the coefficient.	-34.9	-19.2	-17.9
	North	435.9	379.1	334.8	292.1	-18.4^† † p<0.01 of the coefficient.	-33	-13	-12.8
	Southeast	268.1	219.1	211.4	188.1	-9.15^† † p<0.01 of the coefficient.	-29.8	-18.3	-11
	South	459.5	365.6	351.6	303.7	-15.62^† † p<0.01 of the coefficient.	-33.9	-20.4	-13.6

ACSC among women	2010	2014	2015	2019	Variation 2010-2019	Variation 2010–2014	Variation 2015–2019
Infectious gastroenteritis and complications	29.06	19.36	18.39	11.75	-59.6	-33.4	-36.1
Asthma	9.87	6.50	5.75	4.08	-58.7	-34.1	-29.1
Hypertension	6.81	5.14	4.98	3.46	-49.2	-24.6	-30.6
Heart failure	13.83	11.76	11.36	9.90	-28.4	-15.0	-12.8
Diabetes mellitus	8.57	7.46	7.39	6.37	-25.7	-13.0	-13.9
Lung diseases	8.80	8.23	7.79	7.71	-12.4	-6.5	-1.1
Kidney and urinary tract infection	18.31	17.33	18.21	17.40	-5.0	-5.4	-4.5
Bacterial pneumonia	7.80	6.75	6.88	7.64	-2.1	-13.5	11.1
Angina	4.53	4.76	5.04	4.58	1.1	5.0	-9.1
Cerebrovascular diseases	9.00	9.23	9.45	10.00	11.2	2.6	5.9

ACSC among men	2010	2014	2015	2019	Variation 2010–2019	Variation 2010–2014	Variation 2015–2019
Asthma	10.07	5.77	5.70	3.89	-61.3	-42.7	-31.7
Infectious gastroenteritis and complications	28.04	17.66	14.38	11.09	-60.4	-37.0	-22.8
Heart failure	14.91	12.24	11.98	10.79	-27.7	-17.9	-10.0
Lung diseases	11.23	9.62	9.89	9.45	-15.8	-14.3	-4.5
Diabetes mellitus	6.70	6.39	6.44	6.70	-0.01	-4.8	4.1
Bacterial pneumonia	9.06	7.91	7.75	9.14	0.9	-12.7	17.9
Kidney and urinary tract infection	8.75	8.61	8.76	9.41	7.5	-1.7	7.4
Angina	6.29	7.34	7.15	7.24	15.0	16.7	1.3
Cerebrovascular diseases	10.13	10.68	11.02	11.86	17.1	5.4	7.6
Infection of the skin and subcutaneous tissue	5.24	6.44	6.80	8.18	56.1	22.8	20.4

Associação Brasileira de Saúde Coletiva Av. Dr. Arnaldo, 715 - 2º andar - sl. 3 - Cerqueira César, 01246-904 São Paulo SP Brasil , Tel./FAX: +55 11 3085-5411 - São Paulo - SP - Brazil
E-mail: revbrepi@usp.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] Corresponding author: Filipe Malta dos Santos. Avenida Professor Alfredo Balena, 190 – 7° andar, sala 711, Santa Efigênia, CEP: 30130-100, Belo Horizonte (MG), Brasil. E-mail: filipe.malta@hotmail.com