Lessons from the pandemic on the value of research infrastructure View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-04-01

AUTHORS

Laurence S. J. Roope, Paolo Candio, Vasiliki Kiparoglou, Helen McShane, Raymond Duch, Philip M. Clarke

ABSTRACT

The COVID-19 pandemic has shed a spotlight on the resilience of healthcare systems, and their ability to cope efficiently and effectively with unexpected crises. If we are to learn one economic lesson from the pandemic, arguably it is the perils of an overfocus on short-term allocative efficiency at the price of lack of capacity to deal with uncertain future challenges. In normal times, building spare capacity with 'option value' into health systems may seem inefficient, the costs potentially exceeding the benefits. Yet the fatal weakness of not doing so is that this can leave health systems highly constrained when dealing with unexpected, but ultimately inevitable, shocks-such as the COVID-19 pandemic. In this article, we argue that the pandemic has highlighted the potentially enormous option value of biomedical research infrastructure. We illustrate this with reference to COVID-19 response work supported by the United Kingdom National Institute for Health Research Oxford Biomedical Research Centre. As the world deals with the fallout from the most serious economic crisis since the Great Depression, pressure will soon come to review government expenditure, including research funding. Developing a framework to fully account for option value, and understanding the public appetite to pay for it, should allow us to be better prepared for the next emerging problem. More... »

PAGES

54

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12961-021-00704-2

DOI

http://dx.doi.org/10.1186/s12961-021-00704-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1136840975

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33794906


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/16", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Studies in Human Society", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1605", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Policy and Administration", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biomedical Research", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "COVID-19", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Research Support as Topic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "SARS-CoV-2", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "State Medicine", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "United Kingdom", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK", 
          "id": "http://www.grid.ac/institutes/grid.8348.7", 
          "name": [
            "Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF UK", 
            "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Roope", 
        "givenName": "Laurence S. J.", 
        "id": "sg:person.011523647557.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011523647557.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK", 
          "id": "http://www.grid.ac/institutes/grid.8348.7", 
          "name": [
            "Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF UK", 
            "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Candio", 
        "givenName": "Paolo", 
        "id": "sg:person.016331653263.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016331653263.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK", 
          "id": "http://www.grid.ac/institutes/grid.4991.5", 
          "name": [
            "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK", 
            "Nuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kiparoglou", 
        "givenName": "Vasiliki", 
        "id": "sg:person.01302707706.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302707706.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nuffield Department of Medicine, University of Oxford, Oxford, UK", 
          "id": "http://www.grid.ac/institutes/grid.4991.5", 
          "name": [
            "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK", 
            "Nuffield Department of Medicine, University of Oxford, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "McShane", 
        "givenName": "Helen", 
        "id": "sg:person.01334755643.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334755643.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nuffield College, University of Oxford, Oxford, UK", 
          "id": "http://www.grid.ac/institutes/grid.4991.5", 
          "name": [
            "Nuffield College, University of Oxford, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Duch", 
        "givenName": "Raymond", 
        "id": "sg:person.012371157111.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012371157111.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC Australia", 
          "id": "http://www.grid.ac/institutes/grid.1008.9", 
          "name": [
            "Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF UK", 
            "National Institute for Health Research Oxford Biomedical Research Centre\u2013John Radcliffe Hospital, Oxford, UK", 
            "Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Clarke", 
        "givenName": "Philip M.", 
        "id": "sg:person.0734456474.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734456474.38"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/d41586-020-01824-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1128530700", 
          "https://doi.org/10.1038/d41586-020-01824-5"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2021-04-01", 
    "datePublishedReg": "2021-04-01", 
    "description": "The COVID-19 pandemic has shed a spotlight on the resilience of healthcare systems, and their ability to cope efficiently and effectively with unexpected crises. If we are to learn one economic lesson from the pandemic, arguably it is the perils of an overfocus on short-term allocative efficiency at the price of lack of capacity to deal with uncertain future challenges. In normal times, building spare capacity with 'option value' into health systems may seem inefficient, the costs potentially exceeding the benefits. Yet the fatal weakness of not doing so is that this can leave health systems highly constrained when dealing with unexpected, but ultimately inevitable, shocks-such as the COVID-19 pandemic. In this article, we argue that the pandemic has highlighted the potentially enormous option value of biomedical research infrastructure. We illustrate this with reference to COVID-19 response work supported by the United Kingdom National Institute for Health Research Oxford Biomedical Research Centre. As the world deals with the fallout from the most serious economic crisis since the Great Depression, pressure will soon come to review government expenditure, including research funding. Developing a framework to fully account for option value, and understanding the public appetite to pay for it, should allow us to be better prepared for the next emerging problem.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s12961-021-00704-2", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.9250297", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.7147391", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1032049", 
        "issn": [
          "1478-4505"
        ], 
        "name": "Health Research Policy and Systems", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "19"
      }
    ], 
    "keywords": [
      "option value", 
      "serious economic crisis", 
      "allocative efficiency", 
      "government expenditure", 
      "economic crisis", 
      "economics lessons", 
      "Great Depression", 
      "normal times", 
      "unexpected crises", 
      "COVID-19 pandemic", 
      "spare capacity", 
      "health system", 
      "crisis", 
      "United Kingdom's National Institute", 
      "research funding", 
      "prices", 
      "expenditure", 
      "fatal weakness", 
      "infrastructure", 
      "funding", 
      "lessons", 
      "cost", 
      "research infrastructure", 
      "healthcare system", 
      "pandemic", 
      "benefits", 
      "framework", 
      "values", 
      "perils", 
      "article", 
      "public appetite", 
      "world", 
      "future challenges", 
      "resilience", 
      "spotlight", 
      "efficiency", 
      "weakness", 
      "fallout", 
      "capacity", 
      "lack", 
      "problem", 
      "system", 
      "National Institute", 
      "challenges", 
      "appetite", 
      "Research Center", 
      "reference", 
      "Institute", 
      "Biomedical Research Centre", 
      "time", 
      "ability", 
      "work", 
      "pressure", 
      "center", 
      "depression", 
      "biomedical research infrastructure", 
      "overfocus", 
      "response work", 
      "Health Research (NIHR) Oxford Biomedical Research Centre", 
      "short-term allocative efficiency", 
      "price of lack", 
      "uncertain future challenges", 
      "enormous option value", 
      "COVID-19 response work", 
      "Kingdom National Institute", 
      "Research Oxford Biomedical Research Centre", 
      "Oxford Biomedical Research Centre"
    ], 
    "name": "Lessons from the pandemic on the value of research infrastructure", 
    "pagination": "54", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1136840975"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12961-021-00704-2"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33794906"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12961-021-00704-2", 
      "https://app.dimensions.ai/details/publication/pub.1136840975"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T19:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_888.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s12961-021-00704-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12961-021-00704-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12961-021-00704-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12961-021-00704-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12961-021-00704-2'


 

This table displays all metadata directly associated to this object as RDF triples.

221 TRIPLES      22 PREDICATES      102 URIs      91 LITERALS      14 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12961-021-00704-2 schema:about N25e6b6901e9b4c8cb45e0d6e280b1cba
2 N744289d00a75451b8cdab46a963da78b
3 N772cc130a51749959a3ec65a64ec3593
4 Nb0e24cad596042f4ab7563262e69cbbe
5 Nf2240af963f94d1ca55203aa8e583428
6 Nf5125343be8c476196f7590cab44af88
7 Nffae0f9a03b949f88c6f9ab0cb52a0e9
8 anzsrc-for:11
9 anzsrc-for:1117
10 anzsrc-for:16
11 anzsrc-for:1605
12 schema:author N6b142d7fa30e4da1881f41c491180b39
13 schema:citation sg:pub.10.1038/d41586-020-01824-5
14 schema:datePublished 2021-04-01
15 schema:datePublishedReg 2021-04-01
16 schema:description The COVID-19 pandemic has shed a spotlight on the resilience of healthcare systems, and their ability to cope efficiently and effectively with unexpected crises. If we are to learn one economic lesson from the pandemic, arguably it is the perils of an overfocus on short-term allocative efficiency at the price of lack of capacity to deal with uncertain future challenges. In normal times, building spare capacity with 'option value' into health systems may seem inefficient, the costs potentially exceeding the benefits. Yet the fatal weakness of not doing so is that this can leave health systems highly constrained when dealing with unexpected, but ultimately inevitable, shocks-such as the COVID-19 pandemic. In this article, we argue that the pandemic has highlighted the potentially enormous option value of biomedical research infrastructure. We illustrate this with reference to COVID-19 response work supported by the United Kingdom National Institute for Health Research Oxford Biomedical Research Centre. As the world deals with the fallout from the most serious economic crisis since the Great Depression, pressure will soon come to review government expenditure, including research funding. Developing a framework to fully account for option value, and understanding the public appetite to pay for it, should allow us to be better prepared for the next emerging problem.
17 schema:genre article
18 schema:inLanguage en
19 schema:isAccessibleForFree true
20 schema:isPartOf N24b519a5651143ca999c12c17dfc4f3e
21 N974815cd587f450fa3b77e5b9aec2df1
22 sg:journal.1032049
23 schema:keywords Biomedical Research Centre
24 COVID-19 pandemic
25 COVID-19 response work
26 Great Depression
27 Health Research (NIHR) Oxford Biomedical Research Centre
28 Institute
29 Kingdom National Institute
30 National Institute
31 Oxford Biomedical Research Centre
32 Research Center
33 Research Oxford Biomedical Research Centre
34 United Kingdom's National Institute
35 ability
36 allocative efficiency
37 appetite
38 article
39 benefits
40 biomedical research infrastructure
41 capacity
42 center
43 challenges
44 cost
45 crisis
46 depression
47 economic crisis
48 economics lessons
49 efficiency
50 enormous option value
51 expenditure
52 fallout
53 fatal weakness
54 framework
55 funding
56 future challenges
57 government expenditure
58 health system
59 healthcare system
60 infrastructure
61 lack
62 lessons
63 normal times
64 option value
65 overfocus
66 pandemic
67 perils
68 pressure
69 price of lack
70 prices
71 problem
72 public appetite
73 reference
74 research funding
75 research infrastructure
76 resilience
77 response work
78 serious economic crisis
79 short-term allocative efficiency
80 spare capacity
81 spotlight
82 system
83 time
84 uncertain future challenges
85 unexpected crises
86 values
87 weakness
88 work
89 world
90 schema:name Lessons from the pandemic on the value of research infrastructure
91 schema:pagination 54
92 schema:productId N0996d5a171f14ff2b35671339fa5558c
93 N8374fc339b1a435684ad526bc2589bcd
94 Ne87cff96eb194c058012017da93d4ced
95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1136840975
96 https://doi.org/10.1186/s12961-021-00704-2
97 schema:sdDatePublished 2022-01-01T19:00
98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
99 schema:sdPublisher N933d60a6ea7243d0b424e4738bf7c46b
100 schema:url https://doi.org/10.1186/s12961-021-00704-2
101 sgo:license sg:explorer/license/
102 sgo:sdDataset articles
103 rdf:type schema:ScholarlyArticle
104 N0355ab8243644d56afd646672352be52 rdf:first sg:person.01302707706.05
105 rdf:rest N32977a86f9b34de7bf7458163a82c5f9
106 N0996d5a171f14ff2b35671339fa5558c schema:name dimensions_id
107 schema:value pub.1136840975
108 rdf:type schema:PropertyValue
109 N24ab601a76164c7f97ded06c1d60e9cc rdf:first sg:person.012371157111.51
110 rdf:rest N3973d69986e04ac1bc26eab6ddcf9b87
111 N24b519a5651143ca999c12c17dfc4f3e schema:issueNumber 1
112 rdf:type schema:PublicationIssue
113 N25e6b6901e9b4c8cb45e0d6e280b1cba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name COVID-19
115 rdf:type schema:DefinedTerm
116 N32977a86f9b34de7bf7458163a82c5f9 rdf:first sg:person.01334755643.19
117 rdf:rest N24ab601a76164c7f97ded06c1d60e9cc
118 N3973d69986e04ac1bc26eab6ddcf9b87 rdf:first sg:person.0734456474.38
119 rdf:rest rdf:nil
120 N609dce2d8a2c4875b4b9cb5815ca4584 rdf:first sg:person.016331653263.56
121 rdf:rest N0355ab8243644d56afd646672352be52
122 N6b142d7fa30e4da1881f41c491180b39 rdf:first sg:person.011523647557.28
123 rdf:rest N609dce2d8a2c4875b4b9cb5815ca4584
124 N744289d00a75451b8cdab46a963da78b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Humans
126 rdf:type schema:DefinedTerm
127 N772cc130a51749959a3ec65a64ec3593 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name United Kingdom
129 rdf:type schema:DefinedTerm
130 N8374fc339b1a435684ad526bc2589bcd schema:name doi
131 schema:value 10.1186/s12961-021-00704-2
132 rdf:type schema:PropertyValue
133 N933d60a6ea7243d0b424e4738bf7c46b schema:name Springer Nature - SN SciGraph project
134 rdf:type schema:Organization
135 N974815cd587f450fa3b77e5b9aec2df1 schema:volumeNumber 19
136 rdf:type schema:PublicationVolume
137 Nb0e24cad596042f4ab7563262e69cbbe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name State Medicine
139 rdf:type schema:DefinedTerm
140 Ne87cff96eb194c058012017da93d4ced schema:name pubmed_id
141 schema:value 33794906
142 rdf:type schema:PropertyValue
143 Nf2240af963f94d1ca55203aa8e583428 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name SARS-CoV-2
145 rdf:type schema:DefinedTerm
146 Nf5125343be8c476196f7590cab44af88 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Research Support as Topic
148 rdf:type schema:DefinedTerm
149 Nffae0f9a03b949f88c6f9ab0cb52a0e9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Biomedical Research
151 rdf:type schema:DefinedTerm
152 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
153 schema:name Medical and Health Sciences
154 rdf:type schema:DefinedTerm
155 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
156 schema:name Public Health and Health Services
157 rdf:type schema:DefinedTerm
158 anzsrc-for:16 schema:inDefinedTermSet anzsrc-for:
159 schema:name Studies in Human Society
160 rdf:type schema:DefinedTerm
161 anzsrc-for:1605 schema:inDefinedTermSet anzsrc-for:
162 schema:name Policy and Administration
163 rdf:type schema:DefinedTerm
164 sg:grant.7147391 http://pending.schema.org/fundedItem sg:pub.10.1186/s12961-021-00704-2
165 rdf:type schema:MonetaryGrant
166 sg:grant.9250297 http://pending.schema.org/fundedItem sg:pub.10.1186/s12961-021-00704-2
167 rdf:type schema:MonetaryGrant
168 sg:journal.1032049 schema:issn 1478-4505
169 schema:name Health Research Policy and Systems
170 schema:publisher Springer Nature
171 rdf:type schema:Periodical
172 sg:person.011523647557.28 schema:affiliation grid-institutes:grid.8348.7
173 schema:familyName Roope
174 schema:givenName Laurence S. J.
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011523647557.28
176 rdf:type schema:Person
177 sg:person.012371157111.51 schema:affiliation grid-institutes:grid.4991.5
178 schema:familyName Duch
179 schema:givenName Raymond
180 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012371157111.51
181 rdf:type schema:Person
182 sg:person.01302707706.05 schema:affiliation grid-institutes:grid.4991.5
183 schema:familyName Kiparoglou
184 schema:givenName Vasiliki
185 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302707706.05
186 rdf:type schema:Person
187 sg:person.01334755643.19 schema:affiliation grid-institutes:grid.4991.5
188 schema:familyName McShane
189 schema:givenName Helen
190 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334755643.19
191 rdf:type schema:Person
192 sg:person.016331653263.56 schema:affiliation grid-institutes:grid.8348.7
193 schema:familyName Candio
194 schema:givenName Paolo
195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016331653263.56
196 rdf:type schema:Person
197 sg:person.0734456474.38 schema:affiliation grid-institutes:grid.1008.9
198 schema:familyName Clarke
199 schema:givenName Philip M.
200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734456474.38
201 rdf:type schema:Person
202 sg:pub.10.1038/d41586-020-01824-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1128530700
203 https://doi.org/10.1038/d41586-020-01824-5
204 rdf:type schema:CreativeWork
205 grid-institutes:grid.1008.9 schema:alternateName Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC Australia
206 schema:name Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC Australia
207 Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF UK
208 National Institute for Health Research Oxford Biomedical Research Centre–John Radcliffe Hospital, Oxford, UK
209 rdf:type schema:Organization
210 grid-institutes:grid.4991.5 schema:alternateName Nuffield College, University of Oxford, Oxford, UK
211 Nuffield Department of Medicine, University of Oxford, Oxford, UK
212 Nuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK
213 schema:name National Institute for Health Research Oxford Biomedical Research Centre–John Radcliffe Hospital, Oxford, UK
214 Nuffield College, University of Oxford, Oxford, UK
215 Nuffield Department of Medicine, University of Oxford, Oxford, UK
216 Nuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK
217 rdf:type schema:Organization
218 grid-institutes:grid.8348.7 schema:alternateName National Institute for Health Research Oxford Biomedical Research Centre–John Radcliffe Hospital, Oxford, UK
219 schema:name Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF UK
220 National Institute for Health Research Oxford Biomedical Research Centre–John Radcliffe Hospital, Oxford, UK
221 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...