Users’ satisfaction with the public dental service: the discovery of new patterns

Fadel, Cristina Berger; Bordin, Danielle; Santos, Celso Bilynkievycz dos; Carvalho, Deborah Ribeiro; Moimaz, Suzely Adas Saliba

doi:10.1590/1414-462X201900020008

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Sumário

Original Article • Cad. saúde colet. 27 (02) • Apr-Jun 2019 • https://doi.org/10.1590/1414-462X201900020008 copy

Users’ satisfaction with the public dental service: the discovery of new patterns

Satisfação de usuários com o serviço público odontológico: a descoberta de novos padrões

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Background

Regarding to oral health, little has been advanced on how to improve quality within dental care.

Objective

The aim of this study was to identify the demographic factors affecting the satisfaction of users of the dental public service having the value of a strategic and high consistency methodology.

Method

The Data Mining was used to a secondary database, contemplating 91 features, segmental in 9 demographic factors, 17 facets, and 5 dominions. Descriptive statistics were extracted to a demographic data and the satisfaction of the users by facets and dominions, being discovered as from Decision Trees and Association Rules.

Results

the analysis of the results showed the relation between the demographic factor 'professional occupation' and satisfaction, in all of the dominions. The occupations of general assistant and home assistant with daily wage stood out in Association Rules to represent the lower level of satisfaction compared to the facets that were worse evaluated. Also, the factor ‘health unit's name’ showed relation with most of the investigated dominions. The difference between health units was even more evident through the Association Rule.

Conclusion

The Data Mining allowed to identify complementary relations to the user's perception about the public oral health services quality, constituting a safe tool to support the management of Brazilian public health and the basis of future plans.

Keywords:
evaluation of the health service; satisfaction; dental care; data mining

Variable	Class	F	%		Variable	Class	F	%
City	1	461	50.00	100	'Intrinsic characteristics of each health unit' (graphically represented by alphabetic codes)	BF	92	9.98	100
City	2	461	50.00	100		BB	69	7.48
Model of organization of health care	UBS	280	30.37	100		D	51	5.53
Model of organization of health care	UFS	642	69.63	100		BA	41	4.45
Occupation	housewife	238	25.8	100		U	36	3.9
	home assistants	70	7.59			AC	34	3.69
	Retired	64	6.94			E	31	3.36
	Student	58	6.29			L	29	3.15
	General assistant	37	4.02			AO	25	2.7
	Janitor	28	3.04			K	24	2.6
	Unemployed	22	2.39			AR	23	2.49
	Nursing technician	15	1.63			AQ	22	2.39
	Community agent of endemic	13	1.41			Z	22	2.39
	businessman	13	1.41			X	21	2.28
	Manicure	12	1.3			AP	20	2.17
	Cook	12	1.3			AH	20	2.17
	Driver	12	1.3			J	19	2.06
	Public server	11	1.19			AY	18	1.95
	Self employed	10	1.08			R	17	1.84
	Others (< 10 registry)	309	33.5			AM	16	1.74
Gender	Feminine	741	80.37	100		G	16	1.74
Gender	Masculine	181	19.63	100		O	15	1.63
Marital status	Single	406	44.03	100		H	15	1.63
	Married	381	41.32			P	15	1.63
	Widow (er)	53	5.75			AZ	15	1.63
	Separated or divorced	47	5.10			F	14	1.52
	Stable union	28	3.04			V	14	1.52
	No answer	7	0.76			AF	13	1.41
Education	Primary school	384	41.65	100		S	13	1.41
	High school	325	35.25			C	12	1.3
	Incomplete high school	107	11.61			W	12	1.3
	Graduate	42	4.56			Y	12	1.3
	Undergraduate	24	2.60			B	10	1.08
	No answer	21	2.28			Others (< 10 registry)	116	12.6
	Illiterate	11	1.19
	Posgraduate	8	0.87
Income	216 > 421 dollars	431	46.75	100
	420>1081 dollars	298	32.32
	No answer	60	6.51
	Unemployed	56	6.07
	>216 dollars	50	5.42
	1080>2161 dollars	23	2.49
	>2160 dollars	4	0.43

Input			Results
Input			Objective Measures				Decision tree
Meta Attribute	Attributes Candidates to Prediction	Training and Test	Kappa	Measure F	Size of Receiver Operating Characteristic (ROC)	Correct Group Grading (%)	Number of sheets	Tree size
D1 - Organization of services	Demographic and Domains	split	0.717	0.809	0.908	81.15	1304	1350
	Demographic and Domains	vc	0.76	0.838	0.929	84.13	1304	1350
	Demographic	split	0.569	0.699	0.851	70.93	1756	1811
	Demographic	vc	0.736	0.819	0.934	82.61	1756	1811
D2 - Physical structure	Demographic and Domains	split	0.827	0.885	0.968	88.82	809	838
	Demographic and Domains	vc	0.801	0.867	0.949	86.85	809	838
	Demographic	split	0.753	0.833	0.961	84.03	1523	1566
	Demographic	vc	0.767	0.841	0.947	84.67	1523	1566
D3 - Information and Support	Demographic and Domains	split	0.708	0.801	0.902	80.51	1039	1091
	Demographic and Domains	vc	0.819	0.879	0.96	88.06	1039	1091
	Demographic	split	0.516	0.659	0.875	67.73	1782	1845
	Demographic	vc	0.746	0.826	0.933	83.28	1782	1845
D4 - Medical Care	Demographic and Domains	split	0.714	0.813	0.922	81.15	482	519
	Demographic and Domains	vc	0.829	0.886	0.948	88.7	482	519
	Demographic	split	0.58	0.725	0.879	72.2	1088	1143
	Demographic	vc	0.682	0.781	0.923	79.13	1088	1143
D5 - Relationship and Communication	Demographic and Domains	split	0.837	0.891	0.976	89.14	543	574
	Demographic and Domains	vc	0.895	0.93	0.981	93.05	543	574
	Demographic	split	0.741	0.821	0.93	82.75	1854	1897
	Demographic	vc	0.795	0.861	0.951	86.54	1854	1897

Origin Group	Classification Group			Total
Origin Group	low	medium	high	Total
low	218	6	36	260
medium	0	332	0	332
high	12	10	307	329
Measure F	0.976	0.914	0.890
ROC Size	0.997	0.974	0.968
Correct Classification of the Group				93.05%

Association Rules			Interest Measures
Demographic Factor (Antecedent)		Satisfaction (Consequent)	Lift	Conviction
Professional Ocupation	General Assistant	Low	2.73	4.93
	Home assistant with daily wage	Low	2.23	2.3
	Community agent of endemic	Medium	2.31	2.6
	Production assistant	Medium	2.24	2.27
Health Unit' ^a a To preserve the health units, their names were replaced by alphabetic codes	Health Unit A	Low	2.92	7.23
	Health Unit B	Low	2.43	2.96
	Health Unit G	Low	2.06	1.86
	Health Unit H	Low	1.99	1.81
	Health Unit I	Low	1.83	1.5
	Health Unit F	Medium	2.02	1.95
	Health Unit K	Medium	1.72	1.54
	Health Unit L	Medium	1.72	1.54
	Health Unit C	High	2.65	2.77
	Health Unit D	High	2.47	2.54
	Health Unit E	High	2.45	2.22
	Health Unit J	High	2.04	1.59

Association Rules			Interest Measures
Demographic Factor (Antecedent)		Satisfaction (Consequent)	Lift	Conviction
Professional Ocupation	Home assistant with daily wage	Low	1.87	1.59
	General Assistant	Low	1.82	1.55
	Seller	Medium	2.31	2.37
Health Unit ^a a To preserve the health units. their names were replaced by alphabetic codes	Health Unit B	Low	1.98	1.74
	Health Unit H	Low	2.13	2.07
	Health Unit L	Low	1.98	1.9
	Health Unit O	Low	2.34	2.61
	Health Unit P	Low	2.19	2.33
	Health Unit R	Low	2.03	1.96
	Health Unit N	Medium	2.31	2.37
	Health Unit Q	Medium	2.02	1.94
	Health Unit M	Medium	2.59	3.87
	Health Unit T	Medium	1.76	1.48
	Health Unit U	Medium	1.71	1.51
	Health Unit S	High	2.32	1.82
	Health Unit E	High	2.06	1.66

Instituto de Estudos em Saúde Coletiva da Universidade Federal do Rio de Janeiro Avenida Horácio Macedo, S/N, CEP: 21941-598, Tel.: (55 21) 3938 9494 - Rio de Janeiro - RJ - Brazil
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[1] Correspondence: Cristina Berger Fadel – Departamento de Odontologia, Universidade Estadual de Ponta Grossa (UEPG), Av. Gal. Carlos Cavalcanti, 4748 – Uvaranas – CEP: 84030-900 – Ponta Grossa (PR), Brasil – Email: cbfadel@gmail.com