Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review
Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published liter...
Saved in:
| Published in | PloS one Vol. 14; no. 1; p. e0198736 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
31.01.2019
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0198736 |
Cover
| Abstract | Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.
We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.
We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.
In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. |
|---|---|
| AbstractList | BackgroundPopulation-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.MethodsWe searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.ResultsWe identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.ConclusionsIn many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity. We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism. In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. Background Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose. Methods We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity. Results We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56–90% in hospital datasets, 53–87% in prescription datasets, 81–90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36–88% in hospital datasets, 40–74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15–73% in single datasets for PD and 43–63% in single datasets for parkinsonism. Conclusions In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose. We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity. We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism. In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. Background Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose. Methods We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity. Results We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56–90% in hospital datasets, 53–87% in prescription datasets, 81–90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36–88% in hospital datasets, 40–74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15–73% in single datasets for PD and 43–63% in single datasets for parkinsonism. Conclusions In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.BACKGROUNDPopulation-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.METHODSWe searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.RESULTSWe identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity.CONCLUSIONSIn many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity. |
| Audience | Academic |
| Author | Harding, Zoe Wilkinson, Tim Breen, David P. Rannikmäe, Kristiina Sudlow, Cathie L. M. Horrocks, Sophie Ly, Amanda Stevenson, Anna Schnier, Christian |
| AuthorAffiliation | 6 Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, Scotland 2 Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom 5 Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, United Kingdom 4 Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom 3 Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom Liverpool John Moores University, UNITED KINGDOM 1 College of Medicine & Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom |
| AuthorAffiliation_xml | – name: Liverpool John Moores University, UNITED KINGDOM – name: 3 Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom – name: 4 Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom – name: 2 Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom – name: 5 Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, United Kingdom – name: 6 Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, Scotland – name: 1 College of Medicine & Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom |
| Author_xml | – sequence: 1 givenname: Zoe surname: Harding fullname: Harding, Zoe – sequence: 2 givenname: Tim orcidid: 0000-0001-8952-0982 surname: Wilkinson fullname: Wilkinson, Tim – sequence: 3 givenname: Anna orcidid: 0000-0002-0435-3562 surname: Stevenson fullname: Stevenson, Anna – sequence: 4 givenname: Sophie surname: Horrocks fullname: Horrocks, Sophie – sequence: 5 givenname: Amanda surname: Ly fullname: Ly, Amanda – sequence: 6 givenname: Christian surname: Schnier fullname: Schnier, Christian – sequence: 7 givenname: David P. surname: Breen fullname: Breen, David P. – sequence: 8 givenname: Kristiina surname: Rannikmäe fullname: Rannikmäe, Kristiina – sequence: 9 givenname: Cathie L. M. surname: Sudlow fullname: Sudlow, Cathie L. M. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30703084$$D View this record in MEDLINE/PubMed |
| BookMark | eNqNk9tq3DAQhk1JaQ7tG5TWUOjhYrc62JKdi8ISelgIpPR0K2R5vKtUlraSnXTfvnJ2N6xDKMEXNqNvfs38Mz5ODqyzkCTPMZpiyvH7S9d7K810FcNThMuCU_YoOcIlJRNGED3Y-z5MjkO4RCinBWNPkkOKOKKoyI6Sfl6D7XSz1naRfpX-t7bB2TchrXUAGSCVtk5Xu7gObapiNKR9GBK86zttwaxT5YwB1UGdLkGabqmkh7SWnTxNZ2lYhw5a2WmVerjScP00edxIE-DZ9n2S_Pz08cfZl8n5xef52ex8olhJuklFMCsQZ02uyoJUDaJVXWdlmZeElzUhwElBc8g4bnCVZ6gCymhTc0RYZBShJ8nLje7KuCC2jgVBMM8I5wVikZhviNrJS7HyupV-LZzU4ibg_EJIHws3IEoMDaO8yBBrMiqraG6FEeakAiIJrqJWvtHq7Uqur6Uxt4IYiWFouxLEMDSxHVrM-7Ctsq9aqFUciJdmVMz4xOqlWLgrwWielWwQeLsV8O5PD6ETrQ4KjJEWXH_Tb5kVOM8G9NUd9H5XttRCxsa1bVy8Vw2iYpZzXMbVyYpITe-h4lNDq1XssNExPkp4N0qITAd_u4XsQxDz798ezl78GrOv99jNAgZn4m46G8bgi32nby3e_Q8RyDaA8i4ED81DJ3h6J03pTg7XR0e0-X_yPyBBMuc |
| CitedBy_id | crossref_primary_10_3389_fnagi_2021_826213 crossref_primary_10_1186_s12911_021_01556_0 crossref_primary_10_1080_09593985_2019_1615678 crossref_primary_10_1371_journal_pone_0246342 crossref_primary_10_1212_WNL_0000000000201627 crossref_primary_10_1111_ene_16000 crossref_primary_10_1212_WNL_0000000000012601 crossref_primary_10_1186_s13023_021_01699_3 crossref_primary_10_1212_NE9_0000000000200200 crossref_primary_10_1016_j_prdoa_2020_100061 crossref_primary_10_1111_dom_15943 crossref_primary_10_1080_09553002_2023_2267640 crossref_primary_10_3389_fdgth_2023_1149154 crossref_primary_10_1016_j_envres_2023_115944 crossref_primary_10_1002_mds_30075 crossref_primary_10_1002_mds_29682 crossref_primary_10_1016_j_jns_2024_122891 crossref_primary_10_2147_CLEP_S381289 crossref_primary_10_1111_ene_15782 crossref_primary_10_1002_mds_27933 crossref_primary_10_1007_s00415_024_12280_w crossref_primary_10_1016_j_parkreldis_2023_105764 crossref_primary_10_3233_JPD_240098 crossref_primary_10_1007_s00228_020_02847_7 crossref_primary_10_1016_j_jamda_2023_04_004 |
| Cites_doi | 10.1212/WNL.0000000000000641 10.1136/jnnp.55.3.181 10.1034/j.1600-0404.2001.00191.x 10.1136/jnnp-2013-305277 10.1159/000365590 10.2105/AJPH.82.2.243 10.1016/j.jalz.2018.02.016 10.1159/000336356 10.1002/mdc3.12185 10.1136/jnnp.73.5.529 10.1093/ageing/28.2.99 10.1212/WNL.57.8.1497 10.1016/j.jns.2014.08.048 10.1136/bmj.b2535 10.1001/jamaneurol.2013.114 10.1016/S0895-4356(02)00409-2 10.1159/000381857 10.1212/WNL.52.6.1214 10.1186/2046-4053-4-1 10.7326/0003-4819-155-8-201110180-00009 10.1212/WNL.53.3.521 10.1002/mds.22829 10.1002/mds.20907 10.1186/s13063-017-2394-5 10.1371/journal.pmed.1001779 10.1371/journal.pmed.1001885 10.1093/ageing/afy068 10.1002/mds.21353 10.1002/mdc3.12318 10.1002/mus.22195 10.1093/brain/awf080 10.1007/s10654-014-9890-7 10.1002/mds.27360 10.1002/mds.20479 10.1093/jamia/ocv130 10.1016/j.jclinepi.2011.09.002 10.1016/S0140-6736(15)61124-2 10.1371/journal.pone.0172639 10.1002/mds.22283 10.1002/mds.870130305 10.1002/mds.10537 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2019 Public Library of Science 2019 Harding et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2019 Harding et al 2019 Harding et al |
| Copyright_xml | – notice: COPYRIGHT 2019 Public Library of Science – notice: 2019 Harding et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2019 Harding et al 2019 Harding et al |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM IOV ISR 3V. 7QG 7QL 7QO 7RV 7SN 7SS 7T5 7TG 7TM 7U9 7X2 7X7 7XB 88E 8AO 8C1 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI C1K CCPQU D1I DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. KB. KB0 KL. L6V LK8 M0K M0S M1P M7N M7P M7S NAPCQ P5Z P62 P64 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY RC3 7X8 5PM ADTOC UNPAY DOA |
| DOI | 10.1371/journal.pone.0198736 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Gale in Context. Opposing Viewpoints Gale In Context: Science ProQuest Central (Corporate) Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Nursing & Allied Health Database Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Meteorological & Geoastrophysical Abstracts Nucleic Acids Abstracts Virology and AIDS Abstracts Agricultural Science Collection Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest Pharma Collection Public Health Database Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Journals ProQuest Hospital Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central Advanced Technologies & Computer Science Collection Agricultural & Environmental Science Collection ProQuest Central Essentials Biological Science Collection ProQuest Central Technology Collection Natural Science Collection Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Materials Science Collection ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Materials Science Database Nursing & Allied Health Database (Alumni Edition) Meteorological & Geoastrophysical Abstracts - Academic ProQuest Engineering Collection Biological Sciences Agricultural Science Database Health & Medical Collection (Alumni Edition) Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Engineering Database Nursing & Allied Health Premium Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Environmental Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection Environmental Science Collection Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) Unpaywall for CDI: Periodical Content Unpaywall DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Agricultural Science Database Publicly Available Content Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials Nucleic Acids Abstracts SciTech Premium Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Meteorological & Geoastrophysical Abstracts Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database Virology and AIDS Abstracts ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Agricultural Science Collection ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database Ecology Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Environmental Science Collection Entomology Abstracts Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Environmental Science Database ProQuest Nursing & Allied Health Source (Alumni) Engineering Research Database ProQuest One Academic Meteorological & Geoastrophysical Abstracts - Academic ProQuest One Academic (New) Technology Collection Technology Research Database ProQuest One Academic Middle East (New) Materials Science Collection ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central ProQuest Health & Medical Research Collection Genetics Abstracts ProQuest Engineering Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Agricultural & Environmental Science Collection AIDS and Cancer Research Abstracts Materials Science Database ProQuest Materials Science Collection ProQuest Public Health ProQuest Nursing & Allied Health Source ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Animal Behavior Abstracts Materials Science & Engineering Collection Immunology Abstracts ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | Agricultural Science Database MEDLINE MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 4 dbid: UNPAY name: Unpaywall url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/ sourceTypes: Open Access Repository – sequence: 5 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) Veterinary Medicine |
| DocumentTitleAlternate | Parkinson's disease and parkinsonism in routine health data |
| EISSN | 1932-6203 |
| ExternalDocumentID | 2174277806 oai_doaj_org_article_91ef6378406f43ab932b10172be2a21b 10.1371/journal.pone.0198736 PMC6354966 A571908448 30703084 10_1371_journal_pone_0198736 |
| Genre | Meta-Analysis Research Support, Non-U.S. Gov't Systematic Review Journal Article |
| GeographicLocations | United Kingdom--UK Scotland |
| GeographicLocations_xml | – name: United Kingdom--UK – name: Scotland |
| GrantInformation_xml | – fundername: Medical Research Council grantid: MR/S004130/1 – fundername: Medical Research Council grantid: MR/L023784/2 – fundername: Medical Research Council grantid: MR/L023784/1 – fundername: Medical Research Council grantid: MR/P001823/1 – fundername: ; – fundername: ; grantid: MR/P001823/1 – fundername: ; grantid: Rowling Scholarship |
| GroupedDBID | --- 123 29O 2WC 53G 5VS 7RV 7X2 7X7 7XC 88E 8AO 8C1 8CJ 8FE 8FG 8FH 8FI 8FJ A8Z AAFWJ AAUCC AAWOE AAYXX ABDBF ABIVO ABJCF ABUWG ACGFO ACIHN ACIWK ACPRK ACUHS ADBBV AEAQA AENEX AEUYN AFKRA AFPKN AFRAH AHMBA ALMA_UNASSIGNED_HOLDINGS AOIJS APEBS ARAPS ATCPS BAWUL BBNVY BCNDV BENPR BGLVJ BHPHI BKEYQ BPHCQ BVXVI BWKFM CCPQU CITATION CS3 D1I D1J D1K DIK DU5 E3Z EAP EAS EBD EMOBN ESTFP ESX EX3 F5P FPL FYUFA GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE IAO IEA IGS IHR IHW INH INR IOV IPY ISE ISR ITC K6- KB. KQ8 L6V LK5 LK8 M0K M1P M48 M7P M7R M7S M~E NAPCQ O5R O5S OK1 OVT P2P P62 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PTHSS PUEGO PV9 PYCSY RNS RPM RZL SV3 TR2 UKHRP WOQ WOW ~02 ~KM ADRAZ ALIPV CGR CUY CVF ECM EIF IPNFZ NPM RIG BBORY 3V. 7QG 7QL 7QO 7SN 7SS 7T5 7TG 7TM 7U9 7XB 8FD 8FK AZQEC C1K DWQXO FR3 GNUQQ H94 K9. KL. M7N P64 PKEHL PQEST PQUKI PRINS RC3 7X8 5PM ADTOC UNPAY AAPBV ABPTK |
| ID | FETCH-LOGICAL-c692t-b2168076f5c982bf03bdd49959279d22e72835e471f1b540be363fd7026959c23 |
| IEDL.DBID | M48 |
| ISSN | 1932-6203 |
| IngestDate | Sun Nov 05 00:20:58 EDT 2023 Fri Oct 03 12:52:42 EDT 2025 Sun Oct 26 03:51:55 EDT 2025 Tue Sep 30 16:48:46 EDT 2025 Wed Oct 01 13:04:57 EDT 2025 Tue Oct 07 07:19:36 EDT 2025 Mon Oct 20 21:51:43 EDT 2025 Mon Oct 20 16:48:08 EDT 2025 Thu Oct 16 15:06:08 EDT 2025 Thu Oct 16 14:48:39 EDT 2025 Thu May 22 21:21:27 EDT 2025 Mon Jul 21 05:36:09 EDT 2025 Wed Oct 01 04:38:22 EDT 2025 Thu Apr 24 23:03:20 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| License | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. cc-by Creative Commons Attribution License |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c692t-b2168076f5c982bf03bdd49959279d22e72835e471f1b540be363fd7026959c23 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-3 ObjectType-Evidence Based Healthcare-1 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 Competing Interests: The authors have declared that no competing interests exist. ZH and TW are joint first authors |
| ORCID | 0000-0002-0435-3562 0000-0001-8952-0982 |
| OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.1371/journal.pone.0198736 |
| PMID | 30703084 |
| PQID | 2174277806 |
| PQPubID | 1436336 |
| PageCount | e0198736 |
| ParticipantIDs | plos_journals_2174277806 doaj_primary_oai_doaj_org_article_91ef6378406f43ab932b10172be2a21b unpaywall_primary_10_1371_journal_pone_0198736 pubmedcentral_primary_oai_pubmedcentral_nih_gov_6354966 proquest_miscellaneous_2179481546 proquest_journals_2174277806 gale_infotracmisc_A571908448 gale_infotracacademiconefile_A571908448 gale_incontextgauss_ISR_A571908448 gale_incontextgauss_IOV_A571908448 gale_healthsolutions_A571908448 pubmed_primary_30703084 crossref_primary_10_1371_journal_pone_0198736 crossref_citationtrail_10_1371_journal_pone_0198736 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2019-01-31 |
| PublicationDateYYYYMMDD | 2019-01-31 |
| PublicationDate_xml | – month: 01 year: 2019 text: 2019-01-31 day: 31 |
| PublicationDecade | 2010 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: San Francisco – name: San Francisco, CA USA |
| PublicationTitle | PloS one |
| PublicationTitleAlternate | PLoS One |
| PublicationYear | 2019 |
| Publisher | Public Library of Science Public Library of Science (PLoS) |
| Publisher_xml | – name: Public Library of Science – name: Public Library of Science (PLoS) |
| References | R Woodfield (ref14) 2015; 10 D Moher (ref19) 2009; 339 AE Lang (ref1) 2018; 33 A Chiò (ref46) 1998; 13 NR Szumski (ref28) 2009; 24 AL Feldman (ref24) 2012; 38 PF Whiting (ref22) 2011; 155 A Chiò (ref43) 2002; 55 M Brandt-Christensen (ref45) 2006; 21 A Schrag (ref48) 2002; 73 S. Jaffe (ref4) 2015; 385 AJ Hughes (ref12) 2001; 57 K Swarztrauber (ref27) 2005; 20 M Kestenbaum (ref26) 2015; 2 T Thacker (ref36) 2016; 3 (ref3) 2014; 29 AJ Hughes (ref11) 1992; 55 D White (ref31) 2007; 22 MK Beyer (ref38) 2001; 103 T Wilkinson (ref17) 2018; 14 JH Bower (ref34) 1999; 52 J Meara (ref33) 1999; 28 CH Adler (ref10) 2014; 83 P-A Fall (ref39) 2003; 18 EI Benchimol (ref5) 2015; 12 CH Williams-Gray (ref40) 2013; 84 J Benito-León (ref37) 2014; 347 KA Mc Cord (ref6) 2018; 19 L Gao (ref15) 2018; 47 V Gallo (ref25) 2015; 15 C Sudlow (ref2) 2015; 12 J Chubak (ref16) 2012; 65 T Ostbye (ref42) 1999; 53 DE Stickler (ref44) 2011; 44 (ref7) 1992 AJ Hughes (ref13) 2002; 125 S Horrocks (ref18) 2017; 12 W-Q Wei (ref29) 2016; 23 ref8 D Moher (ref20) 2015; 4 A Stevenson (ref21) 2016 L Wermuth (ref30) 2015; 2015 ref9 R Savica (ref35) 2013; 70 EJ Newman (ref47) 2009; 24 ES Fisher (ref41) 1992; 82 DA Butt (ref23) 2014; 43 MA Hernán (ref32) 2004; 251 |
| References_xml | – volume: 83 start-page: 406 year: 2014 ident: ref10 article-title: Low clinical diagnostic accuracy of early vs advanced Parkinson disease: clinicopathologic study publication-title: Neurology doi: 10.1212/WNL.0000000000000641 – volume: 55 start-page: 181 year: 1992 ident: ref11 article-title: Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases publication-title: J Neurol Neurosurg Psychiatr doi: 10.1136/jnnp.55.3.181 – volume: 103 start-page: 7 year: 2001 ident: ref38 article-title: Causes of death in a community-based study of Parkinson’s disease publication-title: Acta Neurol Scand doi: 10.1034/j.1600-0404.2001.00191.x – volume: 84 start-page: 1258 year: 2013 ident: ref40 article-title: The CamPaIGN study of Parkinson’s disease: 10-year outlook in an incident population-based cohort publication-title: J Neurol Neurosurg Psychiatr doi: 10.1136/jnnp-2013-305277 – volume: 43 start-page: 28 year: 2014 ident: ref23 article-title: A validation study of administrative data algorithms to identify patients with Parkinsonism with prevalence and incidence trends publication-title: Neuroepidemiology doi: 10.1159/000365590 – volume: 82 start-page: 243 year: 1992 ident: ref41 article-title: The accuracy of Medicare’s hospital claims data: progress has been made, but problems remain publication-title: Am J Public Health doi: 10.2105/AJPH.82.2.243 – volume: 14 start-page: 1038 year: 2018 ident: ref17 article-title: Identifying dementia cases with routinely collected health data: A systematic review publication-title: Alzheimers Dement doi: 10.1016/j.jalz.2018.02.016 – volume: 38 start-page: 186 year: 2012 ident: ref24 article-title: Accuracy and sensitivity of Parkinsonian disorder diagnoses in two Swedish national health registers publication-title: Neuroepidemiology doi: 10.1159/000336356 – volume: 2 start-page: 384 year: 2015 ident: ref26 article-title: Estimating the Proportion of Essential Tremor and Parkinson’s Disease Patients Undergoing Deep Brain Stimulation Surgery: Five-Year Data From Columbia University Medical Center (2009–2014) publication-title: Mov Disord Clin Pract doi: 10.1002/mdc3.12185 – volume: 73 start-page: 529 year: 2002 ident: ref48 article-title: How valid is the clinical diagnosis of Parkinson’s disease in the community? publication-title: J Neurol Neurosurg Psychiatr doi: 10.1136/jnnp.73.5.529 – volume: 28 start-page: 99 year: 1999 ident: ref33 article-title: Accuracy of diagnosis in patients with presumed Parkinson’s disease publication-title: Age Ageing doi: 10.1093/ageing/28.2.99 – volume: 57 start-page: 1497 year: 2001 ident: ref12 article-title: Improved accuracy of clinical diagnosis of Lewy body Parkinson’s disease publication-title: Neurology doi: 10.1212/WNL.57.8.1497 – volume: 347 start-page: 188 year: 2014 ident: ref37 article-title: Under-reporting of Parkinson’s disease on death certificates: a population-based study (NEDICES) publication-title: J Neurol Sci doi: 10.1016/j.jns.2014.08.048 – volume: 339 start-page: b2535 year: 2009 ident: ref19 article-title: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement publication-title: BMJ doi: 10.1136/bmj.b2535 – ident: ref9 – volume: 70 start-page: 859 year: 2013 ident: ref35 article-title: Incidence and pathology of synucleinopathies and tauopathies related to parkinsonism publication-title: JAMA Neurol doi: 10.1001/jamaneurol.2013.114 – volume: 55 start-page: 723 year: 2002 ident: ref43 article-title: Validity of hospital morbidity records for amyotrophic lateral sclerosis. A population-based study publication-title: J Clin Epidemiol doi: 10.1016/S0895-4356(02)00409-2 – volume: 15 start-page: 331 year: 2015 ident: ref25 article-title: Parkinson’s Disease Case Ascertainment in the EPIC Cohort: The NeuroEPIC4PD Study publication-title: Neurodegener Dis doi: 10.1159/000381857 – volume: 52 start-page: 1214 year: 1999 ident: ref34 article-title: Incidence and distribution of parkinsonism in Olmsted County, Minnesota, 1976–1990 publication-title: Neurology doi: 10.1212/WNL.52.6.1214 – year: 2016 ident: ref21 article-title: The accuracy of electronic health datasets in identifying Parkinson’s disease cases: a systematic review publication-title: The accuracy of electronic health datasets in identifying Parkinson’s disease cases: a systematic review – volume: 4 start-page: 1 year: 2015 ident: ref20 article-title: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement publication-title: Syst Rev doi: 10.1186/2046-4053-4-1 – volume: 2015 start-page: 781479 year: 2015 ident: ref30 article-title: Medical Record Review to Differentiate between Idiopathic Parkinson’s Disease and Parkinsonism: A Danish Record Linkage Study with 10 Years of Follow-Up publication-title: Parkinsons Dis – volume: 10 year: 2015 ident: ref14 article-title: Accuracy of Electronic Health Record Data for Identifying Stroke Cases in Large-Scale Epidemiological Studies: A Systematic Review from the UK Biobank Stroke Outcomes Group publication-title: PLoS One – volume: 155 start-page: 529 year: 2011 ident: ref22 article-title: QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies publication-title: Ann Intern Med doi: 10.7326/0003-4819-155-8-201110180-00009 – volume: 251 start-page: vII14 issue: Suppl 7 year: 2004 ident: ref32 article-title: A prospective study of alcoholism and the risk of Parkinson’s disease publication-title: J Neurol – volume: 53 start-page: 521 year: 1999 ident: ref42 article-title: Mortality in elderly Canadians with and without dementia: a 5-year follow-up publication-title: Neurology doi: 10.1212/WNL.53.3.521 – volume: 24 start-page: 2379 year: 2009 ident: ref47 article-title: Accuracy of Parkinson’s disease diagnosis in 610 general practice patients in the West of Scotland publication-title: Mov Disord doi: 10.1002/mds.22829 – volume: 21 start-page: 1221 year: 2006 ident: ref45 article-title: Use of antiparkinsonian drugs in Denmark: results from a nationwide pharmacoepidemiological study publication-title: Mov Disord doi: 10.1002/mds.20907 – volume: 19 start-page: 29 year: 2018 ident: ref6 article-title: Routinely collected data for randomized trials: promises, barriers, and implications publication-title: Trials doi: 10.1186/s13063-017-2394-5 – volume: 12 start-page: e1001779 year: 2015 ident: ref2 article-title: UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age publication-title: PLoS Med doi: 10.1371/journal.pmed.1001779 – volume: 12 start-page: e1001885 year: 2015 ident: ref5 article-title: The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement publication-title: PLOS Med doi: 10.1371/journal.pmed.1001885 – volume: 47 start-page: 589 year: 2018 ident: ref15 article-title: Accuracy of death certification of dementia in population-based samples of older people: analysis over time publication-title: Age Ageing doi: 10.1093/ageing/afy068 – volume: 22 start-page: 915 year: 2007 ident: ref31 article-title: Identifying incident cases of parkinsonism among veterans using a tertiary medical center publication-title: Mov Disord doi: 10.1002/mds.21353 – volume: 3 start-page: 507 year: 2016 ident: ref36 article-title: Utility of electronic medical record for recruitment in clinical research: from rare to common disease publication-title: Mov Disord Clin Pract doi: 10.1002/mdc3.12318 – volume: 44 start-page: 814 year: 2011 ident: ref44 article-title: Validity of hospital discharge data for identifying cases of amyotrophic lateral sclerosis publication-title: Muscle Nerve doi: 10.1002/mus.22195 – volume: 125 start-page: 861 year: 2002 ident: ref13 article-title: The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service publication-title: Brain doi: 10.1093/brain/awf080 – volume: 29 start-page: 371 year: 2014 ident: ref3 article-title: The German National Cohort: aims, study design and organization publication-title: Eur J Epidemiol doi: 10.1007/s10654-014-9890-7 – volume: 33 start-page: 660 year: 2018 ident: ref1 article-title: Disease Modification in Parkinson’s Disease: Current Approaches, Challenges, and Future Considerations publication-title: Movement Disorders doi: 10.1002/mds.27360 – volume: 20 start-page: 964 year: 2005 ident: ref27 article-title: Identifying and distinguishing cases of parkinsonism and Parkinson’s disease using ICD-9 CM codes and pharmacy data publication-title: Mov Disord doi: 10.1002/mds.20479 – volume: 23 start-page: e20 year: 2016 ident: ref29 article-title: Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance publication-title: J Am Med Inform Assoc doi: 10.1093/jamia/ocv130 – year: 1992 ident: ref7 article-title: The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines – volume: 65 start-page: 343 year: 2012 ident: ref16 article-title: Tradeoffs between accuracy measures for electronic health care data algorithms publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2011.09.002 – volume: 385 start-page: 2448 year: 2015 ident: ref4 article-title: Planning for US Precision Medicine Initiative underway publication-title: The Lancet doi: 10.1016/S0140-6736(15)61124-2 – ident: ref8 – volume: 12 start-page: e0172639 year: 2017 ident: ref18 article-title: Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review publication-title: PLoS ONE doi: 10.1371/journal.pone.0172639 – volume: 24 start-page: 51 year: 2009 ident: ref28 article-title: Optimizing algorithms to identify Parkinson’s disease cases within an administrative database publication-title: Mov Disord doi: 10.1002/mds.22283 – volume: 13 start-page: 400 year: 1998 ident: ref46 article-title: Prevalence of Parkinson’s disease in Northwestern Italy: comparison of tracer methodology and clinical ascertainment of cases publication-title: Mov Disord doi: 10.1002/mds.870130305 – volume: 18 start-page: 1312 year: 2003 ident: ref39 article-title: Survival time, mortality, and cause of death in elderly patients with Parkinson’s disease: a 9-year follow-up publication-title: Mov Disord doi: 10.1002/mds.10537 |
| SSID | ssj0053866 |
| Score | 2.4282002 |
| SecondaryResourceType | review_article |
| Snippet | Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in... Background Population-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant... We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference... Background Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant... BackgroundPopulation-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant... Background Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant... |
| SourceID | plos doaj unpaywall pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | e0198736 |
| SubjectTerms | Accuracy Algorithms Amyotrophic lateral sclerosis Analysis Basal ganglia Biology and Life Sciences Brain diseases Brain research Central nervous system diseases Database industry Databases, Factual Datasets Dementia Diagnostic systems Drugs Electronic Health Records Female Health care Health informatics Health sciences Hospitals Humans Information management Male Medical care quality Medical diagnosis Medical literature Medical records Medicine and Health Sciences Mortality Movement disorders Neurodegenerative diseases Neurology Parkinson disease Parkinson Disease - epidemiology Parkinson's disease Parkinsonism People and places Population Population studies Primary Health Care Prospective Studies Sensitivity Studies Systematic review Veterinary medicine |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwELbQXuCCKK8GFjAIqXBIm9iJ7XBbEFVBAiSgqLfIdpy20pJdNbtC_ffM2N60EZXaA1f7y0qZl2c2M58JeW14acvcFKlpijItjGWpzkuVtqYyjdDOav9nzpev4uCw-HxUHl266gt7wgI9cBDcXpW7VnAJdYhoC64N5BsGzYgZxzTLDUbfTFWbYirEYPBiIeKgHJf5XtTL7nLRud0M62xPyXxxEHm-_iEqT5bzRX9Vyvlv5-TtdbfU53_0fH7pWNq_R-7GfJLOwntskVuuu0-2osf29E2klX77gKzDTK6fa6I47OznvnZ6Gr_RUN01dLlZP-1_UwurPcXO-GN6tgAL7dz8nKLlQJR0DT0ZescoNpq-ozN6QQxNw1DMQ3K4__Hnh4M0XrqQWlGxVWpYLlQmRVvaSjHTZtw0TYGsZExWDWNOIkObgzOtzQ2ke8ZxwdtGQi0HGMv4IzLpQMzbhBouhM40Fw3khcoohSN_KmONtq1rszwhfKOB2kZGcrwYY177z2wSKpMgxBr1Vke9JSQdnloGRo5r8O9RuQMW-bT9AlhZHa2svs7KEvICTaMOgh2iQj0rJWRUCmrchLzyCOTU6LBp51iv-77-9O3XDUA_vo9AOxHULkAcVsdBCXgn5OoaIacjJEQGO9reRkPeSKWvsfxkUqoMhDLdGPfV2y-HbfxRbMTr3GLtMZ7fpwDM4-ALg2TD8aGKhMiRl4xEP97pTk88pTmkvQUU3gnZHfzpRsp98j-U-5TcgTQY2wYhI5mSyeps7Z5Bqrkyz31U-QsbjX3d priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db9MwELdG9wAvEysfCwwwCGnwkC5xEidFQqhDmwbSChps2ltkO043qSShaYX233PnOCkRE-zVvkTKffkuvvsdIa9lEKnIl6ErszByQ6mYK_wocXM5lhkXWgnzM-dkyo_Pws8X0cUGmba9MFhW2fpE46izUuE_8n0MnVkcJx7_UP10cWoU3q62IzSEHa2QvTcQY3fIJkNkrAHZPDicfj1tfTNYN-e2gS6I_X0rr1FVFnrkYf5toJrXB5TB8e-89aCal_VNoejfFZV3V0Ulrn-J-fyP4-roPtmycSadNIqxTTZ0MSTb1pJr-sbCTb8dkuE5VsSYtlx6Ym_aH5BV08FruqAotkabLrG9mtobHSqKjFbt-lX9gypYrSnW0c_oogR9LvT8mqKegU_VGb3sKs0olqW-oxO6hpGmTQvNQ3J2dPj947FrRzS4io_Z0pXM54kX8zxS44TJ3AtkloWIYcbiccaYjhHPTcMJmPsSgkOpAx7kWQyZH9AoFjwigwKYv0OoDDgXngh4BlFkIpMEGwQTj2VC5Tr3fIcErVxSZfHLcYzGPDWXcjHkMQ1rU5RmaqXpELd7qmrwO_5Df4Ai72gRfdsslItZao05Hfs650EMuTHPw0BIiIElujYmNRPMlw55gQqTNoztfEg6iWKIvxLIiB3yylAgAkeBJT4zsarr9NOX81sQfTvtEe1ZorwEdihh2yrgmxDZq0e526MEP6J62zuo3i1X6nRtcfBkq_I3b7_stvGlWLZX6HJlaAwaUAg0jxsL6TjbHDZJ6JC4Zzs91vd3iqtLA4AOQXIIabpDRp2V3Uq4T_79HU_JPQiHsXwQIpNdMlguVvoZhJxL-dz6kd-EL4Q5 priority: 102 providerName: ProQuest – databaseName: Unpaywall dbid: UNPAY link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Nb9QwELXK9gAXoHx1YQGDEIVD0sROnITbgqgKEgUBRe0BRbbjtBVLdtVshMqB386M4wQCRZQDt5U9tjbP4_FMPPNCyAPFYx2HKvJUEcVepDTzZBinXqkyVQhptLQvc17tiO3d6OVevLdCPna1MA5BiBFn89re5OOPeWU2HZKbyFfU3p76IU_CboS_ACE_wBiai4eWcQjfjC2xAOkcWRUxuOojsrq782a63940M0-wgLtyuj_NNDiuLKt_b7tH-M9Oc0x_z68831QLefJFzmY_HV5bl8i37rHbnJVPfrNUvv76CyPkf8PlMrno3F46bWdZIyumukLWnGGp6SPHfv34Kmna0mFbfkWxJtuWp23U1F0lUVkVdNG1H9WfqYbWmmIC_wE9nsNGqszshKKCgzE3BT3sU9wo5sM-oVP6g7-atrU718ju1vP3z7Y9920IT4uMLT3FQpEGiShjnaVMlQFXRREheRpLsoIxkyCRnIGjtwwVeKXKcMHLIoGQE2Q049fJqAJk1glVXAgZSC4KcF9TlaZYmZgGrJC6NGUQjgnvVCDXjjgdv98xy-1tYAIBVAtijlDnDuox8fpRi5Y45C_yT1G7elmk_bYNsNa5W-M8C00peAJBuSgjLhUosUKbypRhkoVqTO6ibuYtsL3xyqdxAo5fCqH4mNy3Ekj9UWFu0YFs6jp_8frDGYTevR0IbTihcg5waOnqOeCZUBUHkpOBJBgwPeheR13uUKlzjJJZkqQBgDLpdtfp3ff6bpwU8wUrM2-sjKUhikDmRrsZe2TbUy6NxiQZbNMB9MOe6ujQMq-Ddx5lAub0-w19psW9-a8DbpEL4JljJiM4SRMyWh435jZ4v0t1x9mw72_Ktfo priority: 102 providerName: Unpaywall |
| Title | Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/30703084 https://www.proquest.com/docview/2174277806 https://www.proquest.com/docview/2179481546 https://pubmed.ncbi.nlm.nih.gov/PMC6354966 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0198736&type=printable https://doaj.org/article/91ef6378406f43ab932b10172be2a21b http://dx.doi.org/10.1371/journal.pone.0198736 |
| UnpaywallVersion | publishedVersion |
| Volume | 14 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVFSB databaseName: Free Full-Text Journals in Chemistry customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: HH5 dateStart: 20060101 isFulltext: true titleUrlDefault: http://abc-chemistry.org/ providerName: ABC ChemistRy – providerCode: PRVAFT databaseName: Open Access Digital Library customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: KQ8 dateStart: 20060101 isFulltext: true titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html providerName: Colorado Alliance of Research Libraries – providerCode: PRVAFT databaseName: Open Access Digital Library customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: KQ8 dateStart: 20061001 isFulltext: true titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html providerName: Colorado Alliance of Research Libraries – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: DOA dateStart: 20060101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVEBS databaseName: Academic Search Ultimate - eBooks customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: ABDBF dateStart: 20080101 isFulltext: true titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn providerName: EBSCOhost – providerCode: PRVEBS databaseName: EBSCOhost Food Science Source customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: A8Z dateStart: 20080101 isFulltext: true titleUrlDefault: https://search.ebscohost.com/login.aspx?authtype=ip,uid&profile=ehost&defaultdb=fsr providerName: EBSCOhost – providerCode: PRVBFR databaseName: Free Medical Journals customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: DIK dateStart: 20060101 isFulltext: true titleUrlDefault: http://www.freemedicaljournals.com providerName: Flying Publisher – providerCode: PRVFQY databaseName: GFMER Free Medical Journals customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: GX1 dateStart: 20060101 isFulltext: true titleUrlDefault: http://www.gfmer.ch/Medical_journals/Free_medical.php providerName: Geneva Foundation for Medical Education and Research – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M~E dateStart: 20060101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVAQN databaseName: PubMed Central customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: RPM dateStart: 20060101 isFulltext: true titleUrlDefault: https://www.ncbi.nlm.nih.gov/pmc/ providerName: National Library of Medicine – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 7X7 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest One Academic customDbUrl: http://www.proquest.com/pqcentral?accountid=15518 eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: BENPR dateStart: 20061201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Public Health Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 8C1 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/publichealth providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Technology Collection customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 8FG dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/technologycollection1 providerName: ProQuest – providerCode: PRVFZP databaseName: Scholars Portal Journals: Open Access customDbUrl: eissn: 1932-6203 dateEnd: 20250930 omitProxy: true ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M48 dateStart: 20061201 isFulltext: true titleUrlDefault: http://journals.scholarsportal.info providerName: Scholars Portal |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db9MwELe2ToK9IMbXAqUYhDR4SJU4iZ0gIdRNGwNpZRoUlafITpxuUklL0wr633PnfEBEJ_aSB_tcNee781189ztCXiovSAJX-bZK_cD2VcJs6QahnalIpVzqRJqPOWdDfjryP46D8Rape7ZWDCw2hnbYT2q0mPZ__Vi_A4V_a7o2CLde1J_Pct13MIr2-DbZgbMqwmYOZ35zrwDazXlVQHfdyl1yq9SD0G-dVQbSvzHcnfl0VmzySv9Nrry9yudy_VNOp3-dXCd3yZ3K5aSDUkb2yJbO75G9SqkL-qpCnn59n6zKsl1T-kSxHtqUhh0UtLrGoTJP6bwevyq-0wRGC4rJ8xO6mIEQ53q6pihcYEh1Si-b9DKKuahv6ID-wY6mZd3MAzI6Of5ydGpXfRnshEdsaSvm8tARPAuSKGQqczyVpj4ClzERpYxpgSBuGo69zFXgESrtcS9LBYR7QJMw7yHp5MDxfUKVx7l0pMdTcB1DFYZYFRg6LJVJpjPHtYhX70CcVKDl2DtjGpubOAHBS8nEGLcwrrbQInazal6CdvyH_hA3t6FFyG0zMFtM4kqD48jVGfcEBMQ88z2pwPFVaM-Y0kwyV1nkGYpGXDK2MRzxIBDgdIUQBlvkhaFA2I0c83omclUU8YdPX29A9PmiRXRQEWUzYEciq1oKeCeE82pRdluUYDyS1vQ-CnLNlSLGCJUJETrAlG4t3JunnzfT-KOYq5fr2crQGAggH2gelbrQcLbWLIuIlpa0WN-eya8uDeo5eMY-xOYW6Tf6dKPNfXztn3hCdsH9xXRB8ES6pLNcrPRTcDGXqke2xVjAMzxy8Xnyvkd2Do-H5xc989GmZ6wKjI2G54NvvwG8LYKa |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELem8jBeECsfKwxmEGjwkC5xEidFQqh8TC1bhwTb1LdgJ043qSSlaTX1n-Jv5M5xUiIm2Mte7Uuk3J1_vovvfibkhXT92HekZ8nE8y1PxswSjh9aqezJhAsVC_0zZ3TMB6fe57E_3iC_ql4YLKusMFEDdZLH-I98H0NnFgShzd_Nflp4axSerlZXaJRucahWl5CyFW-HH8G-Lxk7-HTyYWCZWwWsmPfYwpLM4SFk76kf90ImU9uVSeIh7RYLegljKkAKMgWgnToS4hmpXO6mSQDJCsjESHQAkH_LcwFLYP0E4zrBA-zg3LTnuYGzb7yhO8sz1bUxu9dE0OvtT98SUO8Frdk0L64KdP-u19xcZjOxuhTT6R-b4cFdcsdEsbRfut0W2VBZm2wZnCjoK0Nm_bpN2mdYb6ObfunInOPfI8uyP1j3WFFsvNY9aHsFNedFVGQJnVXjF8UPGsNoQbFKf0LnOayWTE1XFL0YEFsl9LyuY6NY9PqG9umapJqWDTr3yemNmOoBaWWg_G1Cpcu5sIXLE4hRQxmG2H4Y2iwRcapS2-kQt7JLFBt2dLykYxrpI78AsqRStRFaMzLW7BCrfmpWsoP8R_49mryWRW5vPZDPJ5GBiqjnqJS7AWTePPVcISHClgicTCommCM7ZBcdJioVWyNU1PcDiO5CyLc75LmWQH6PDAuIJmJZFNHwy9k1hL59bQjtGaE0B3XEwjRtwDchb1hDcqchCSgVN6a30b0rrRTRej3Dk5XLXz39rJ7Gl2JRYKbypZbRXEMeyDwsV0it2XIrC70OCRprp6H65kx2ca7p1SEE93oc3tmtV9m1jPvo39-xSzYHJ6Oj6Gh4fPiY3IbAGwsVIQbaIa3FfKmeQHC7kE81olDy_aYh7Dc3_bhI |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3fb9MwELamIgEviJUfKwxmEGjwkLZxEidBQqgwqpWxgYBNfQt24nSTSlKaVlP_Nf467hwnJWKCvezVvkTK3fnzXXz3mZBn0vFiz5auJRPXs1wZM0vYXmClMpQJFyoW-mfO4RHfP3Y_jL3xBvlV9cJgWWWFiRqokzzGf-Q9DJ2Z7wd93ktNWcTnveGb2U8Lb5DCk9bqOo3SRQ7U6hzSt-L1aA9s_Zyx4ftv7_Ytc8OAFfOQLSzJbB5AJp96cRgwmfYdmSQuUnAxP0wYUz7SkSkA8NSWENtI5XAnTXxIXEAmRtIDgP9rvuOEWE7oj-tkD3CEc9Oq5_h2z3hGd5ZnqtvHTF-TQq-3Qn1jQL0vtGbTvLgo6P27dvPGMpuJ1bmYTv_YGIe3yS0T0dJB6YKbZENlbbJpMKOgLwyx9cs2aZ9g7Y1uAKaH5kz_DlmWvcK634piE7buR9stqDk7oiJL6KwaPyt-0BhGC4oV-xM6z2HlZGq6oujRgN4qoad1TRvFAthXdEDXhNW0bNa5S46vxFT3SCsD5W8RKh3ORV84PIF4NZBBgK2IQZ8lIk5V2rc7xKnsEsWGKR0v7JhG-vjPh4ypVG2E1oyMNTvEqp-alUwh_5F_iyavZZHnWw_k80lkYCMKbZVyx4csnKeuIyRE2xJBlEnFBLNlh-ygw0SlYmu0igaeD5FeALl3hzzVEsj1keGqmYhlUUSjTyeXEPr6pSG0a4TSHNQRC9PAAd-EHGINye2GJCBW3JjeQveutFJE67UNT1Yuf_H0k3oaX4oFgpnKl1pG8w65IHO_XCG1ZsttLXA7xG-snYbqmzPZ2ammWodw3A05vLNbr7JLGffBv79jh1wH8Io-jo4OHpKbEINjzSKEQ9uktZgv1SOIcxfysQYUSr5fNYL9BjeevIs |
| linkToUnpaywall | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Nb9QwELXK9gAXoHx1YQGDEIVD0sROnITbgqgKEgUBRe0BRbbjtBVLdtVshMqB386M4wQCRZQDt5U9tjbP4_FMPPNCyAPFYx2HKvJUEcVepDTzZBinXqkyVQhptLQvc17tiO3d6OVevLdCPna1MA5BiBFn89re5OOPeWU2HZKbyFfU3p76IU_CboS_ACE_wBiai4eWcQjfjC2xAOkcWRUxuOojsrq782a63940M0-wgLtyuj_NNDiuLKt_b7tH-M9Oc0x_z68831QLefJFzmY_HV5bl8i37rHbnJVPfrNUvv76CyPkf8PlMrno3F46bWdZIyumukLWnGGp6SPHfv34Kmna0mFbfkWxJtuWp23U1F0lUVkVdNG1H9WfqYbWmmIC_wE9nsNGqszshKKCgzE3BT3sU9wo5sM-oVP6g7-atrU718ju1vP3z7Y9920IT4uMLT3FQpEGiShjnaVMlQFXRREheRpLsoIxkyCRnIGjtwwVeKXKcMHLIoGQE2Q049fJqAJk1glVXAgZSC4KcF9TlaZYmZgGrJC6NGUQjgnvVCDXjjgdv98xy-1tYAIBVAtijlDnDuox8fpRi5Y45C_yT1G7elmk_bYNsNa5W-M8C00peAJBuSgjLhUosUKbypRhkoVqTO6ibuYtsL3xyqdxAo5fCqH4mNy3Ekj9UWFu0YFs6jp_8frDGYTevR0IbTihcg5waOnqOeCZUBUHkpOBJBgwPeheR13uUKlzjJJZkqQBgDLpdtfp3ff6bpwU8wUrM2-sjKUhikDmRrsZe2TbUy6NxiQZbNMB9MOe6ujQMq-Ddx5lAub0-w19psW9-a8DbpEL4JljJiM4SRMyWh435jZ4v0t1x9mw72_Ktfo |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Identifying+Parkinson%27s+disease+and+parkinsonism+cases+using+routinely+collected+healthcare+data%3A+A+systematic+review&rft.jtitle=PloS+one&rft.au=Harding%2C+Zoe&rft.au=Wilkinson%2C+Tim&rft.au=Stevenson%2C+Anna&rft.au=Horrocks%2C+Sophie&rft.date=2019-01-31&rft.eissn=1932-6203&rft.volume=14&rft.issue=1&rft.spage=e0198736&rft_id=info:doi/10.1371%2Fjournal.pone.0198736&rft_id=info%3Apmid%2F30703084&rft.externalDocID=30703084 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1932-6203&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1932-6203&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1932-6203&client=summon |