Type: Package
Title: Portuguese 'NHS' Hospitals
Version: 0.1.0
Description: A data set of the Portuguese 'NHS' hospitals.
License: CC0
URL: https://github.com/nhs-pt/hospitals
BugReports: https://github.com/nhs-pt/hospitals/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
Imports: magrittr, stringr, tibble
Depends: R (≥ 2.10)
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-11-25 12:00:01 UTC; rmagno
Author: Ramiro Magno ORCID iD [aut, cre], CINTESIS [cph, fnd]
Maintainer: Ramiro Magno <ramiro.magno@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-26 08:20:02 UTC

hospitals: Portuguese 'NHS' Hospitals

Description

A data set of the Portuguese 'NHS' hospitals.

Author(s)

Maintainer: Ramiro Magno ramiro.magno@gmail.com (ORCID)

Other contributors:

See Also

Useful links:

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

lhs

A value or the magrittr placeholder.

rhs

A function call using the magrittr semantics.

Value

The result of calling 'rhs(lhs)'.

Get hospital attribute

Description

get_hospital_attribute retrieves one of the variables of hospitals as indicated in x. Hospitals in x can be specified by the: (i) hospital identifier, (ii) acronym, or the (iii) shortened or (iv) full version of the hospital name.

Usage

get_hospital_attribute(x, key = "hospital_id", value = "hospital_short_name")

Arguments

x

A character vector of values that refer to hospitals, can be either the hospital identifier (e.g. "h0003"), its acronym (e.g. "HB"), the shortened name ("H de Braga") or the full name ("Hospital de Braga, EPE"). Indicate how x should be interpreted with the parameter key.

key

A string indicating the type of values in x: "hospital_id", "hospital_acronym", "hospital_short_name" or "hospital_full_name".

value

A string indicating the hospital attribute to be returned, can be any of the columns of hospitals.

Value

A character vector of hospital attributes.

Examples

# Get the short name of a hospital
# (same as get_hospital_attribute('h0001', value = 'hospital_short_name'))
get_hospital_attribute('h0001')

# Or get instead the full name
get_hospital_attribute('h0001', value = 'hospital_full_name')

# Map the hospital short name to its full name
get_hospital_attribute('IPO de Lisboa', key = 'hospital_short_name', value = 'hospital_full_name')

Portuguese NHS hospitals

Description

A dataset of the Portuguese National Health Service hospitals.

Usage

hospitals

Format

A data frame with 16 variables:

hospital_id

A surrogate identifier created by this R package to identify unambiguously each hospital institution.

hospital_acronym

The acronym or initialism of the hospital name.

hospital_legal_status

Legal entity status: either an administrative public sector (SPA) entity, a corporate public entity (EPE) or a public-private partnership (PPP) entity. The legal status of SPA and EPE entities can be found in Decree-law 18/2017. For information about the legal status of the PPP entities see Decree-law 23/2020. The Portuguese government may also establish contracts with hospitals owned by social enterprises, namely Private Institutions of Social Solidarity (IPSS). In this case, these hospitals become effectively part of the National Health Service. There are three types of contracts that can be established with IPSS which are regulated by the Decree-law 138/2013: Management Agreement (IPSS-MA), Cooperative Agreement (IPSS-CA) and Convention (IPSS-CN).

hospital_integration

The integration level of the hospital institution: a single hospital unit ('H'); Centro Hospitalar ('CH'), comprising two or more individual Hospital units (a case of horizontal integration); and Unidade Local de Saúde ('ULS'), comprising both Hospital entities and primary care health centres (a case of vertical integration).

hospital_group

One of the groups defined by Ordinance 82/2014: I, II, III, IV-a, IV-b or IV-c. This classification is based on the hospital catchment area and the scope of medical specialities provided. Broadly speaking, group I includes local hospitals, group II corresponds to regional hospitals, and group III to central hospitals. Group IV corresponds to specialised hospitals: IV-a, oncology institutes; IV-b, physical medicine and rehabilitation hospitals; and IV-c, psychiatry and mental health hospitals.

hospital_short_name

An abbreviated version of the hospital name.

hospital_full_name

The name of the hospital.

hospital_region_full_name

The name of the Portuguese health region.

hospital_region_short_name

A shortened version of hospital_region_full_name.

hospital_vatin

VAT identification number (VATIN). In Portuguese, Número de Identificação de Pessoa Colectiva (NIPC).

hospital_latitude

Latitude of the location of the hospital entity expressed in decimal degrees.

hospital_longitude

Longitude of the location of the hospital entity expressed in decimal degrees.

hospital_region_colour

Colour associated with the region. These colours are assigned by this package and are provided as a convenience colour palette for plotting in R.

hospital_bh_group

One of the groups defined by the project Benchmarking of Hospitals. Source: BH | Grupos e Instituições.

hospital_bh_group_colour

Colour associated with the bh_group. These colours are assigned by this package and are provided as a convenience colour palette for plotting in R.

hospital_regex

A regular expression that can be used to identify hospitals from their names, even when the names are not exactly as in hospital_full_name.

Details

The concept of hospital here adopted is that of a legal entity providing hospital services. Depending on the organisational structure of the entity, it may be a single hospital unit (H), several hospital units that have been merged into one Hospital Centre (CH), or a merge of hospital units and health centres into the so called Unidades Locais de Saúde (ULS); the column hospital_integration indicates which case is which.

Source

The set of hospitals included in this dataset was created by manual inspection of the hospital institutions referred in https://www.sns.gov.pt/institucional/entidades-de-saude/, namely those under the sections: Serviço Nacional de Saúde—Setor Público Empresarial, Serviço Nacional de Saúde—Setor Público Administrativo, Hospitais em parceria público-privada (PPP) and Hospitais geridos pelas Misericórdias.

Here are the sources per variable (column) in the dataset:

hospital_id

Own work.

hospital_acronym

Own work.

hospital_legal_status

Obtained from https://www.sns.gov.pt/institucional/entidades-de-saude/ as the hospitals were grouped according to its legal status. In the case of the partnerships with IPSS, the information on the precise type of contract was obtained from inspection of the contracts themselves. In all cases they are Cooperative Agreements (IPSS-CA):

Hospital Luciano de Castro, Anadia

data-raw/source/Acordo_Cooperacao_Hospital_Jose_Luciano_Castro_-Anadia1.pdf

Hospital São José, Fafe

data-raw/source/Acordo_Coop_Hosp_Sao_Jose_Fafe.pdf

Hospital de São Paulo, Serpa

data-raw/source/Acordo_Cooperacao_-Hospital_Sao_Paulo_Serpa.pdf

hospital_integration

The classification in Hospital unit (H), Hospital Centre (CH) or Unidade Local de Saúde (ULS) could be easily inferred from the name of the hospitals. Hospital Centres always start with Centro Hospitalar (CH), and ULS hospitals always start with Unidade Local de Saúde (ULS). The remaining hospitals are therefore single Hospital (H) units.

hospital_group
Hospitals mentioned in Ordinance 82/2014

For the majority of the hospitals this grouping was obtained from the ordinance where these are first defined, i.e., the table annexed to Ordinance 82/2014.

Instituto de Oftalmologia Dr. Gama Pinto

The hospital Instituto de Oftalmologia Dr. Gama Pinto was not assigned to any group in the Ordinance 82/2014. But given that this hospital is exclusively specialised in ophthalmology, we have decided to assign it generically to group IV (for specialised hospitals), following the criteria given in Ordinance 82/2014.

Hospital Dr. Francisco Zagalo, Ovar

The hospital Hospital Dr. Francisco Zagalo, Ovar was not assigned to any group in the Ordinance 82/2014. It was included in group I however in a work by Luís Pereira, which we followed, see Table 15 in the Appendix 1, page 71 of data-raw/source/Pereira.Unpublished.2019.pdf.

Hospital Luciano de Castro, Anadia

The hospital Hospital Luciano de Castro, Anadia was not assigned to any group in the Ordinance 82/2014. It was included in group I however in a work by Luís Pereira, which we followed, see Table 15 in the Appendix 1, page 71 of data-raw/source/Pereira.Unpublished.2019.pdf.

hospital_short_name

Own work.

hospital_full_name

Obtained from https://www.sns.gov.pt/institucional/entidades-de-saude/.

hospital_region_full_name

Obtained from Decree-law 11/93.

hospital_region_short_name

Own work.

hospital_vatin

From the search engine https://codigopostal.ciberforma.pt/ and from data-raw/source/Infarmed_lista_hospitais.pdf.

hospital_latitude and hospital_longitude

By searching each hospital in Google Maps and retrieving its coordinates.

hospital_region_colour

Own work.

hospital_bh_group

The ACSS groups defined in the project Hospitals' Benchmarking were collected from these sources:

ACSS Hospitals' Benchmarking website

ACSS BH | Grupos e Instituições

Relatório de Benchmarking | hospitais EPE e PPP

Page 7 of data-raw/source/Lourenco.TechReport.2013.pdf

Termos de Referência para contratualização de cuidados desaúde no SNS para 2021

Page 25 of data-raw/source/ACSS.TechReport.2020.pdf

hospital_bh_group_colour

Own work.

hospital_regex

Own work.

Examples

hospitals

Normalise hospital names

Description

normalise tries to match provided hospital names to the Portuguese NHS hospitals, i.e. to those hospitals included in the data set hospitals, thus allowing conversion to standard hospital names. By default, it returns the shortened version of the hospital name: column hospital_short_name in hospitals. Use the return argument to return a different variable, see below for possible values.

Usage

normalise(
  nm,
  return = c("hospital_short_name", "hospital_full_name", "hospital_id",
    "hospital_acronym"),
  unmatched_as_na = TRUE
)

normalize(
  nm,
  return = c("hospital_short_name", "hospital_full_name", "hospital_id",
    "hospital_acronym"),
  unmatched_as_na = TRUE
)

Arguments

nm

A character vector of hospital names.

return

A string indicating the hospital attribute to be returned: either hospital_short_name (default), hospital_full_name, hospital_id or hospital_acronym. These hospital variables are documented in hospitals.

unmatched_as_na

A logical indicating whether unmatched hospital names are returned as NA (TRUE, the default) or as originally supplied in nm (FALSE).

Details

The method behind normalise for matching hospital names is based on an heuristic that uses a minimal set of keywords to identify the hospital. This is implemented by using regular expressions. The regular expressions are provided in data set hospitals, column hospital_regex. Moreover, the method is case insensitive and is pretty tolerant to variations in the name as long as one of the critical keywords is found in the name. Note however that the regular expressions have been designed such that matches are mutually exclusive. So the same hospital name will never match more than one hospital of the data set hospitals.

normalise is aware of deprecated hospital names, and will map those old designations to the new hospital names, e.g., Hospital do Alto Ave is correctly mapped to Hospital da Senhora da Oliveira, Guimarães, EPE.

normalise is lenient with typos associated with accented characters, so, e.g., both expressions 'Hospital de São João' and 'Hospital de Sao Joao' will correctly match to the same hospital: CHU de São João.

Value

A character vector.

Examples

# Match hospital with a single keyword
normalise('Matosinhos')

# The same, but return now the full name
normalise('Matosinhos', 'hospital_full_name')

# Get instead the hospital identifier
normalise('Matosinhos', 'hospital_id')

# Or even just the acronym (useful for labelling in plots)
normalise('Matosinhos', 'hospital_acronym')

# Find hospitals from their old names
# "Hospital do Alto Ave" is the old name for 'Hospital da Senhora da Oliveira, Guimarães, EPE'
normalise('Hospital do Alto Ave', 'hospital_full_name')

# `normalise()` is vectorised over `nm`
normalise(nm = c('medio tejo', 'oeste', 'guarda'))