Supplementary Health Data with ANS

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Overview

The ANS (Agencia Nacional de Saude Suplementar) is Brazil’s regulatory agency for private/supplementary health insurance (planos de saude). Its open data portal provides data on beneficiaries, consumer complaints, and operator financial statements.

Feature	Details
Source	HTTP CSV/ZIP (dadosabertos.ans.gov.br)
Data types	3 (beneficiaries, complaints, financial)
Beneficiaries	Monthly, per-UF (Apr 2019–present)
Complaints	Annual, national (2011–present)
Financial	Quarterly (2007–present)
Operators	Snapshot registry (separate function)

Data types

Code	Name	Granularity	Availability
beneficiaries	Beneficiarios	Monthly, per-UF	Apr 2019–2025
complaints	Demandas NIP	Annual, national	2011–2026
financial	Demonstracoes contabeis	Quarterly	2007–2025

Getting started

library(healthbR)
library(dplyr)

Check available years

# beneficiaries (default)
ans_years()

# complaints
ans_years(type = "complaints")

# financial statements
ans_years(type = "financial")

Module information

ans_info()

Beneficiaries

Beneficiary data provides consolidated counts of health plan enrollees broken down by operator, municipality, sex, age group, plan type, and more. Each file covers one state (UF) and one month.

Basic download

# Acre, December 2023
ac <- ans_data(year = 2023, month = 12, uf = "AC")
ac

Multiple months and states

# first quarter 2024, two states
ne <- ans_data(year = 2024, month = 1:3, uf = c("CE", "PE"))

# full year (month = NULL downloads all 12 months)
ac_2023 <- ans_data(year = 2023, uf = "AC")

Selecting variables

ans_data(
  year = 2023, month = 12, uf = "AC",
  vars = c("CD_OPERADORA", "SG_UF", "TP_SEXO",
           "DE_FAIXA_ETARIA", "QT_BENEFICIARIO_ATIVO")
)

Key variables

Variable	Description
ID_CMPT_MOVEL	Reference period (YYYY-MM)
CD_OPERADORA	Operator code at ANS
NM_RAZAO_SOCIAL	Operator name
SG_UF	State abbreviation
CD_MUNICIPIO	Municipality (IBGE code)
TP_SEXO	Sex (M/F)
DE_FAIXA_ETARIA	Age group
DE_CONTRATACAO_PLANO	Contract type (Individual, Coletivo Empresarial, etc.)
DE_SEGMENTACAO_PLANO	Plan segment (Ambulatorial, Hospitalar, etc.)
COBERTURA_ASSIST_PLAN	Coverage type (Medico-hospitalar, Odontologica)
TIPO_VINCULO	Beneficiary link (Titular, Dependente)
QT_BENEFICIARIO_ATIVO	Active beneficiary count

Consumer complaints (NIP)

Consumer complaints data covers demands filed through ANS’s NIP (Notificacao de Intermediacao Preliminar) system. Files are national (not per-UF) and annual.

# complaints filed in 2022
nip <- ans_data(year = 2022, type = "complaints")
nip

# multiple years
nip_multi <- ans_data(year = 2020:2023, type = "complaints")

Key variables

Variable	Description
NUMERO_DA_DEMANDA	Complaint number
ABERTURA_DA_DEMANDA	Filing date
ASSUNTO	Subject
REGISTRO_OPERADORA	Operator registration
NOME_OPERADORA	Operator name
TIPO_DE_PLANO_CONTRATADO	Contract type
SEXO	Sex (M/F)
ESTADO_DO_BENEFICIARIO	Beneficiary state
CLASSIFICACAO_DA_NIP	NIP classification
NATUREZA_DA_NIP	NIP nature
SITUACAO_DA_NIP	NIP status

Financial statements

Quarterly financial statements (demonstracoes contabeis) for all health plan operators.

# Q1 2023
fin_q1 <- ans_data(year = 2023, type = "financial", quarter = 1)

# all 4 quarters of 2023
fin_2023 <- ans_data(year = 2023, type = "financial")

# specific quarters
fin_q12 <- ans_data(year = 2023, type = "financial", quarter = 1:2)

Key variables

Variable	Description
DATA	Reference date
REG_ANS	Operator registration
CD_CONTA_CONTABIL	Accounting code
DESCRICAO	Account description
VL_SALDO_INICIAL	Opening balance (R\() \| \| VL_SALDO_FINAL \| Closing balance (R\))

Operator registry

The operator registry is a separate snapshot (not time-series), so it uses its own function:

# active operators
active <- ans_operators()

# cancelled operators
cancelled <- ans_operators(status = "cancelled")

# both combined
all_ops <- ans_operators(status = "all")

Key variables

Variable	Description
REGISTRO_OPERADORA	ANS registration number
CNPJ	Tax ID
Razao_Social	Legal name
Nome_Fantasia	Trade name
Modalidade	Modality (Medicina de Grupo, Cooperativa, etc.)
UF	State
Data_Registro_ANS	ANS registration date

Exploring variables

# beneficiaries variables (default)
ans_variables()

# complaints variables
ans_variables(type = "complaints")

# financial variables
ans_variables(type = "financial")

# search across variables
ans_variables(search = "operadora")
ans_variables(search = "beneficiario")

Example: beneficiaries by state and plan type

# December 2023, all states
ben <- ans_data(year = 2023, month = 12)

# active beneficiaries by state and coverage type
ben |>
  group_by(SG_UF, COBERTURA_ASSIST_PLAN) |>
  summarize(
    total = sum(as.integer(QT_BENEFICIARIO_ATIVO), na.rm = TRUE),
    .groups = "drop"
  ) |>
  arrange(desc(total))

Example: complaints by subject and operator

nip <- ans_data(year = 2023, type = "complaints")

# top complaint subjects
nip |>
  count(ASSUNTO, sort = TRUE) |>
  head(10)

# operators with most complaints
nip |>
  count(NOME_OPERADORA, sort = TRUE) |>
  head(10)

Example: operator financial health

# Q4 2023 financial data
fin <- ans_data(year = 2023, type = "financial", quarter = 4)

# join with operator registry for names
ops <- ans_operators()

fin |>
  filter(grepl("^41", CD_CONTA_CONTABIL)) |>  # revenue accounts
  group_by(REG_ANS) |>
  summarize(
    revenue = sum(as.numeric(VL_SALDO_FINAL), na.rm = TRUE),
    .groups = "drop"
  ) |>
  left_join(
    ops |> select(REGISTRO_OPERADORA, Razao_Social),
    by = c("REG_ANS" = "REGISTRO_OPERADORA")
  ) |>
  arrange(desc(revenue)) |>
  head(10)

Example: combining ANS with SUS data

ANS beneficiary counts complement SUS data by showing private coverage:

# private coverage (ANS)
ben <- ans_data(year = 2023, month = 12,
                vars = c("SG_UF", "QT_BENEFICIARIO_ATIVO"))

private_by_uf <- ben |>
  group_by(SG_UF) |>
  summarize(
    private_beneficiaries = sum(as.integer(QT_BENEFICIARIO_ATIVO), na.rm = TRUE),
    .groups = "drop"
  )

# total population (Census 2022)
pop <- censo_populacao(year = 2022, territorial_level = "state")

# private coverage rate
# private_by_uf |>
#   left_join(pop, by = ...) |>
#   mutate(coverage_pct = (private_beneficiaries / population) * 100) |>
#   arrange(desc(coverage_pct))

Parameter routing

ans_data() routes parameters based on the type:

Parameter	beneficiaries	complaints	financial
`year`	required	required	required
`month`	optional (1–12)	ignored	ignored
`uf`	optional (27 UFs + XX)	ignored	ignored
`quarter`	ignored	ignored	optional (1–4)
`vars`	optional	optional	optional

Unused parameters emit a warning but do not cause errors.

Lazy evaluation

With the arrow package installed, data is cached in Parquet format and can be queried lazily:

# lazy query (requires arrow)
lazy_ben <- ans_data(year = 2023, uf = "AC", lazy = TRUE)
lazy_ben |>
  filter(month == 12L, TP_SEXO == "F") |>
  select(CD_OPERADORA, DE_FAIXA_ETARIA, QT_BENEFICIARIO_ATIVO) |>
  collect()

Cache management

Downloaded data is cached locally for faster future access:

# check cache status
ans_cache_status()

# clear cache if needed
ans_clear_cache()

Differences from DATASUS modules

Feature	ANS	DATASUS modules
Data source	HTTP CSV/ZIP	FTP .dbc/.DBF files
Column names	MixedCase (from CSV)	UPPERCASE
`parse` parameter	Not available	Available
`dictionary()`	Not available	Available
`quarter` parameter	Financial data	Not used
Operator registry	`ans_operators()`	Not applicable

Additional resources

ANS open data portal (dadosabertos.ans.gov.br)
ANS official website (www.gov.br/ans/pt-br)
ANS Tabnet (www.ans.gov.br/anstabnet)
Census vignette for population denominators

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.