Pre-implementation adaptation of primary care cancer prevention clinical decision support in a predominantly rural healthcare system
Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and scr...
Saved in:
Published in | BMC medical informatics and decision making Vol. 20; no. 1; p. 117 |
---|---|
Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
BioMed Central Ltd
23.06.2020
BioMed Central BMC |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes.
In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR.
Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements.
Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems.
NCT02986230. |
---|---|
AbstractList | BACKGROUNDCancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. METHODSIn a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. RESULTSBased on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. CONCLUSIONSPre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. TRIAL REGISTRATIONNCT02986230. Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. Methods In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Results Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Conclusions Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. Trial registration NCT02986230. Keywords: Cancer prevention and screening, Clinical decision support, Consolidated Framework for Implementation Research, Pre-implementation adaptation, Primary care, Shared decision-making tools Abstract Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients’ cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system’s goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. Methods In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Results Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Conclusions Pre-implementation changes to CDS may help meet healthcare systems’ evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. Trial registration NCT02986230 . Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. NCT02986230. Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients’ cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system’s goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. Methods In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Results Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Conclusions Pre-implementation changes to CDS may help meet healthcare systems’ evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. Trial registration NCT02986230. Abstract Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients’ cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system’s goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. Methods In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Results Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics , Inner Setting , and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Conclusions Pre-implementation changes to CDS may help meet healthcare systems’ evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. Trial registration NCT02986230 . Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. |
ArticleNumber | 117 |
Audience | Academic |
Author | Bianco, Joseph A Elliott, Thomas E O'Connor, Patrick J Truitt, Anjali R Walton, Kayla M Sperl-Hillen, JoAnn M Allen, Clayton I Harry, Melissa L Ekstrom, Heidi L Saman, Daniel M |
Author_xml | – sequence: 1 givenname: Melissa L surname: Harry fullname: Harry, Melissa L organization: Essentia Health, Essentia Institute of Rural Health, 6AV-2, 502 East Second Street, Duluth, MN, 55805, USA – sequence: 2 givenname: Daniel M orcidid: 0000-0002-8372-4615 surname: Saman fullname: Saman, Daniel M email: Daniel.Saman@EssentiaHealth.org organization: Essentia Health, Essentia Institute of Rural Health, 6AV-2, 502 East Second Street, Duluth, MN, 55805, USA. Daniel.Saman@EssentiaHealth.org – sequence: 3 givenname: Anjali R surname: Truitt fullname: Truitt, Anjali R organization: HealthPartners Institute, 3311 E. Old Shakopee Road, Bloomington, MN, 55425, USA – sequence: 4 givenname: Clayton I surname: Allen fullname: Allen, Clayton I organization: Essentia Health, Essentia Institute of Rural Health, 6AV-2, 502 East Second Street, Duluth, MN, 55805, USA – sequence: 5 givenname: Kayla M surname: Walton fullname: Walton, Kayla M organization: Essentia Health, Essentia Institute of Rural Health, 6AV-2, 502 East Second Street, Duluth, MN, 55805, USA – sequence: 6 givenname: Patrick J surname: O'Connor fullname: O'Connor, Patrick J organization: HealthPartners Institute, 3311 E. Old Shakopee Road, Bloomington, MN, 55425, USA – sequence: 7 givenname: Heidi L surname: Ekstrom fullname: Ekstrom, Heidi L organization: HealthPartners Institute, 3311 E. Old Shakopee Road, Bloomington, MN, 55425, USA – sequence: 8 givenname: JoAnn M surname: Sperl-Hillen fullname: Sperl-Hillen, JoAnn M organization: HealthPartners Institute, 3311 E. Old Shakopee Road, Bloomington, MN, 55425, USA – sequence: 9 givenname: Joseph A surname: Bianco fullname: Bianco, Joseph A organization: Essentia Health - Ely Clinic, 300 W Conan Street, Ely, MN, 55731, USA – sequence: 10 givenname: Thomas E surname: Elliott fullname: Elliott, Thomas E organization: HealthPartners Institute, 3311 E. Old Shakopee Road, Bloomington, MN, 55425, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32576202$$D View this record in MEDLINE/PubMed |
BookMark | eNptksuL1TAUxouMOA_9B1xIwY2bjnmn3QjD4GNgQBe6Dmke9-bSJjVpB-7eP9xzH45zRQppOP3OL_lOv8vqLKboquo1RtcYt-J9waTDuEEENQhjKpr2WXWBmSSN6Jg8e7I_ry5L2SCEZUv5i-qcEi4FQeSi-vUtuyaM0-BGF2c9hxRrbfV03CZfTzmMOm9ro7ODJRqXoeYeQL5TmCHEYPRQW2dC2VXKMk0pz3UA0k5p0xiijvOwrfOSQbl2epjXe17ZltmNL6vnXg_FvTq-r6ofnz5-v_3S3H_9fHd7c98YLujctEx6xDqvBQIrXHjMLWI9p51HlnFCJEJcOE5N23rje8JMZwXxWtoedX1Pr6q7A9cmvVFHYyrpoPaFlFdK5zmYwSnmONOt6RCzHesk6jtAwimsl8YYbYH14cCaln501sA4wNsJ9PRLDGu1Sg9KUgy35AB4dwTk9HNxZVZjKMYNg44uLUURhkVHpSQUpG__kW7SkiOMClSESYpayf-qVhoMhOgTnGt2UHUjCPxvxjkB1fV_VPBYNwYDAfMB6icN5NBgciolO__oESO1y6E65FBBDtU-h6qFpjdPp_PY8id49Dc0udw8 |
CitedBy_id | crossref_primary_10_1200_OP_23_00482 crossref_primary_10_1186_s12913_021_06551_9 crossref_primary_10_3389_frhs_2024_1326777 crossref_primary_10_1186_s12913_021_07421_0 crossref_primary_10_1080_21645515_2022_2040933 crossref_primary_10_1177_0272989X221082083 crossref_primary_10_1007_s10865_023_00400_2 crossref_primary_10_1186_s12911_022_02032_z crossref_primary_10_2196_32577 |
Cites_doi | 10.1007/s11892-012-0350-z 10.1177/0272989X10378701 10.1093/jamia/ocv177 10.15585/mmwr.mm6549a5 10.1377/hlthaff.2010.0129 10.1093/jamia/ocy085 10.7314/APJCP.2013.14.3.1999 10.1186/s12875-018-0797-3 10.1093/jnci/81.24.1879 10.1002/cncr.20512 10.1001/jamainternmed.2014.1319 10.5888/pcd12.150300 10.1186/1471-2296-14-27 10.1186/s13012-018-0772-3 10.1016/j.evalprogplan.2016.09.003 10.1186/1748-5908-4-50 10.1111/j.1369-7625.2010.00613.x 10.1056/NEJMp1900808 10.1186/s12913-019-4326-4 10.1370/afm.1196 10.1016/j.pec.2010.07.025 10.1002/14651858.CD001431.pub5 10.1056/NEJMp1109283 10.1177/0272989X15587676 10.1136/qshc.2008.027649 10.1370/afm.1713 10.1016/j.jbi.2017.12.005 10.1370/afm.1768 10.1197/jamia.M1370 |
ContentType | Journal Article |
Copyright | COPYRIGHT 2020 BioMed Central Ltd. 2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Author(s) 2020 |
Copyright_xml | – notice: COPYRIGHT 2020 BioMed Central Ltd. – notice: 2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: The Author(s) 2020 |
DBID | CGR CUY CVF ECM EIF NPM AAYXX CITATION 3V. 7QO 7SC 7X7 7XB 88C 88E 8AL 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABUWG AFKRA ARAPS AZQEC BBNVY BENPR BGLVJ BHPHI CCPQU DWQXO FR3 FYUFA GHDGH GNUQQ HCIFZ JQ2 K7- K9. L7M LK8 L~C L~D M0N M0S M0T M1P M7P P5Z P62 P64 PIMPY PQEST PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
DOI | 10.1186/s12911-020-01136-8 |
DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed CrossRef ProQuest Central (Corporate) Biotechnology Research Abstracts Computer and Information Systems Abstracts Health & Medical Complete (ProQuest Database) ProQuest Central (purchase pre-March 2016) Healthcare Administration Database (Alumni) Medical Database (Alumni Edition) Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni Edition) ProQuest Central UK/Ireland Advanced Technologies & Aerospace Collection ProQuest Central Essentials Biological Science Collection AUTh Library subscriptions: ProQuest Central Technology Collection ProQuest Natural Science Collection ProQuest One Community College ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection (Proquest) (PQ_SDU_P3) ProQuest Computer Science Collection Computer Science Database ProQuest Health & Medical Complete (Alumni) Advanced Technologies Database with Aerospace Biological Sciences Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Computing Database Health & Medical Collection (Alumni Edition) Healthcare Administration Database PML(ProQuest Medical Library) Biological Science Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Publicly Available Content Database ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) Directory of Open Access Journals |
DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) CrossRef Publicly Available Content Database Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection ProQuest Health & Medical Complete (Alumni) Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Natural Science Collection ProQuest Central China ProQuest Central Health Research Premium Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Biological Science Collection Advanced Technologies Database with Aerospace ProQuest Medical Library (Alumni) Advanced Technologies & Aerospace Collection ProQuest Computing ProQuest Biological Science Collection ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Health Management ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest Health Management (Alumni Edition) Engineering Research Database ProQuest One Academic ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic MEDLINE Publicly Available Content Database CrossRef |
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: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 1472-6947 |
EndPage | 117 |
ExternalDocumentID | oai_doaj_org_article_4e54a8c904d94970b98fc0d44b7cccad A627624552 10_1186_s12911_020_01136_8 32576202 |
Genre | Randomized Controlled Trial Journal Article Research Support, N.I.H., Extramural |
GeographicLocations | United States |
GeographicLocations_xml | – name: United States |
GrantInformation_xml | – fundername: NCI NIH HHS grantid: R01 CA193396 – fundername: ; grantid: R01CA193396 |
GroupedDBID | --- -A0 0R~ 23N 2WC 3V. 53G 5VS 6J9 6PF 7X7 88E 8FE 8FG 8FH 8FI 8FJ AAFWJ AAJSJ AAKPC AAWTL ABDBF ABUWG ACGFO ACGFS ACIWK ACPRK ACRMQ ADBBV ADINQ ADUKV AENEX AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS AQUVI ARAPS AZQEC BAPOH BAWUL BBNVY BCNDV BENPR BFQNJ BGLVJ BHPHI BMC BPHCQ BVXVI C24 C6C CCPQU CGR CS3 CUY CVF DIK DU5 DWQXO E3Z EAD EAP EAS EBD EBLON EBS ECM EIF EMB EMK EMOBN ESX F5P FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HMCUK HYE IAO IHR INH INR ITC K6V K7- KQ8 LK8 M0N M0T M1P M48 M7P M~E NPM O5R O5S OK1 P2P P62 PGMZT PIMPY PQQKQ PROAC PSQYO RBZ RNS ROL RPM RSV SMD SOJ SV3 TR2 TUS UKHRP W2D WOQ WOW XSB AAYXX CITATION ABVAZ AFGXO AFNRJ 7QO 7SC 7XB 8AL 8FD 8FK FR3 JQ2 K9. L7M L~C L~D P64 PQEST PQUKI PRINS Q9U 7X8 5PM |
ID | FETCH-LOGICAL-c563t-847f049fa6000156f15d04b539f0d452270056e53c88fcfb24c9d62fa7db09bb3 |
IEDL.DBID | RPM |
ISSN | 1472-6947 |
IngestDate | Tue Oct 22 15:15:31 EDT 2024 Tue Sep 17 21:14:35 EDT 2024 Fri Aug 16 01:33:01 EDT 2024 Thu Oct 10 22:08:06 EDT 2024 Fri Feb 23 00:05:45 EST 2024 Fri Feb 02 04:18:22 EST 2024 Thu Sep 12 16:49:59 EDT 2024 Sat Sep 28 08:20:54 EDT 2024 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Keywords | Shared decision-making tools Consolidated Framework for Implementation Research Clinical decision support Pre-implementation adaptation Cancer prevention and screening Primary care |
Language | English |
License | Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c563t-847f049fa6000156f15d04b539f0d452270056e53c88fcfb24c9d62fa7db09bb3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-News-3 content type line 23 |
ORCID | 0000-0002-8372-4615 |
OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310565/ |
PMID | 32576202 |
PQID | 2424730875 |
PQPubID | 42572 |
PageCount | 1 |
ParticipantIDs | doaj_primary_oai_doaj_org_article_4e54a8c904d94970b98fc0d44b7cccad pubmedcentral_primary_oai_pubmedcentral_nih_gov_7310565 proquest_miscellaneous_2416937723 proquest_journals_2424730875 gale_infotracmisc_A627624552 gale_infotracacademiconefile_A627624552 crossref_primary_10_1186_s12911_020_01136_8 pubmed_primary_32576202 |
PublicationCentury | 2000 |
PublicationDate | 2020-06-23 |
PublicationDateYYYYMMDD | 2020-06-23 |
PublicationDate_xml | – month: 06 year: 2020 text: 2020-06-23 day: 23 |
PublicationDecade | 2020 |
PublicationPlace | England |
PublicationPlace_xml | – name: England – name: London |
PublicationTitle | BMC medical informatics and decision making |
PublicationTitleAlternate | BMC Med Inform Decis Mak |
PublicationYear | 2020 |
Publisher | BioMed Central Ltd BioMed Central BMC |
Publisher_xml | – name: BioMed Central Ltd – name: BioMed Central – name: BMC |
References | 1136_CR16 1136_CR38 1136_CR17 1136_CR39 1136_CR18 1136_CR19 1136_CR30 1136_CR31 1136_CR10 1136_CR32 1136_CR11 1136_CR33 1136_CR12 1136_CR34 1136_CR13 1136_CR35 1136_CR14 1136_CR36 1136_CR15 1136_CR37 1136_CR27 1136_CR28 1136_CR29 1136_CR2 1136_CR1 1136_CR40 1136_CR41 1136_CR9 1136_CR20 1136_CR42 1136_CR8 1136_CR21 1136_CR43 1136_CR7 1136_CR22 1136_CR44 1136_CR6 1136_CR23 1136_CR45 1136_CR5 1136_CR24 1136_CR46 1136_CR4 1136_CR25 1136_CR3 1136_CR26 |
References_xml | – ident: 1136_CR39 – ident: 1136_CR41 doi: 10.1007/s11892-012-0350-z – ident: 1136_CR5 doi: 10.1177/0272989X10378701 – ident: 1136_CR14 – ident: 1136_CR46 doi: 10.1093/jamia/ocv177 – ident: 1136_CR16 – ident: 1136_CR38 doi: 10.15585/mmwr.mm6549a5 – ident: 1136_CR20 doi: 10.1377/hlthaff.2010.0129 – ident: 1136_CR37 – ident: 1136_CR42 doi: 10.1093/jamia/ocy085 – ident: 1136_CR2 doi: 10.7314/APJCP.2013.14.3.1999 – ident: 1136_CR28 doi: 10.1186/s12875-018-0797-3 – ident: 1136_CR35 – ident: 1136_CR29 doi: 10.1093/jnci/81.24.1879 – ident: 1136_CR33 – ident: 1136_CR12 – ident: 1136_CR31 – ident: 1136_CR9 doi: 10.1002/cncr.20512 – ident: 1136_CR10 – ident: 1136_CR18 doi: 10.1001/jamainternmed.2014.1319 – ident: 1136_CR27 doi: 10.5888/pcd12.150300 – ident: 1136_CR21 doi: 10.1186/1471-2296-14-27 – ident: 1136_CR1 – ident: 1136_CR45 doi: 10.1186/s13012-018-0772-3 – ident: 1136_CR25 doi: 10.1016/j.evalprogplan.2016.09.003 – ident: 1136_CR26 doi: 10.1186/1748-5908-4-50 – ident: 1136_CR8 doi: 10.1111/j.1369-7625.2010.00613.x – ident: 1136_CR24 doi: 10.1056/NEJMp1900808 – ident: 1136_CR15 doi: 10.1186/s12913-019-4326-4 – ident: 1136_CR36 – ident: 1136_CR3 – ident: 1136_CR40 doi: 10.1370/afm.1196 – ident: 1136_CR6 doi: 10.1016/j.pec.2010.07.025 – ident: 1136_CR13 doi: 10.1002/14651858.CD001431.pub5 – ident: 1136_CR19 – ident: 1136_CR32 – ident: 1136_CR34 – ident: 1136_CR30 – ident: 1136_CR11 – ident: 1136_CR7 doi: 10.1056/NEJMp1109283 – ident: 1136_CR4 doi: 10.1177/0272989X15587676 – ident: 1136_CR23 doi: 10.1136/qshc.2008.027649 – ident: 1136_CR17 doi: 10.1370/afm.1713 – ident: 1136_CR43 doi: 10.1016/j.jbi.2017.12.005 – ident: 1136_CR22 doi: 10.1370/afm.1768 – ident: 1136_CR44 doi: 10.1197/jamia.M1370 |
SSID | ssj0017835 |
Score | 2.3477168 |
Snippet | Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute... Abstract Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along... Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with... BACKGROUNDCancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with... Abstract Background Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along... |
SourceID | doaj pubmedcentral proquest gale crossref pubmed |
SourceType | Open Website Open Access Repository Aggregation Database Index Database |
StartPage | 117 |
SubjectTerms | Algorithms Cancer Cancer prevention Cancer prevention and screening Cancer research Cancer screening Cardiovascular diseases Clinical decision making Clinical decision support Clinics Consolidated Framework for Implementation Research Content analysis Decision making Decision support systems Decision Support Systems, Clinical Delivery of Health Care Design Disease prevention Electronic health records Electronic medical records Health care Health problems Health risks Humans Intervention Leadership Medical records Medical screening Meetings Neoplasms Patients Pre-implementation adaptation Prevention Primary care Primary Health Care Qualitative analysis Qualitative Research Risk management Shared decision-making tools United States |
SummonAdditionalLinks | – databaseName: Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LixQxEA6yB_Eivu11lQiCB2k2k3cfV3FZhBUPLuwtdDoJO6A9wzwO3v3hViXpYRoPXrw0Qyed6dQjVdWp-kLIO-FjpziTrQVj00plWdt7M7SwDCZjvWYpc_r6q766kV9u1e3RUV-YE1bggQvhzmVUsrdDx2ToZGeY72waWJASRoR_D3n1XagpmKr7B_g9YyqRsfp8C1YNPwVyTMJaIATvzAxltP6_1-QjozRPmDyyQJePyMPqOtKL8sqPyb04PiH3r-vm-FPy-9smtsufU0I4Upz2oV_Xn6tE1wVagmK6F1yA3xu4F2vKI52qJGmoB-_Q7X6N_jldwkjYM6xK5syPX3SDeB307pA-Rgsm9DNyc_n5-6erth6y0A5Ki10L1ilBlJB6Xcqq00IFJr0SXQIqg3dmEC00KjFYIHzyXA5d0Dz1JnjWeS-ek5NxNcaXhNoUBx1hgZAIc9jhFqpZ-CRAx1kfeGrIh4nmrk7Y5RjEalc45IBDLnPI2YZ8RLYceiIOdr4B0uGqdLh_SUdD3iNTHWorcG7oa9EBvDDiXrkLzcEaSKV4Q85mPUHLhnnzJBauavnWYWmNQUhF1ZC3h2Z8EjPXxrjaYx-Eu4EYRjTkRZGiw5QERnucweBmJl-zOc9bxuVdxgA34JaDL376P4j0ijzgWTV0y8UZOdlt9vE1uFo7_yZr1R9UGCgD priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Technology Collection dbid: 8FG link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3Ni9QwFA-6gngRv-26SgTBg4TNpEmanmQVx0VY8eDC3kLz5Q6s07Ezc9i7f7jvtWndIngpJUlLkveZ5L1fCHlTulgrwSUzYGyYVIazxlWegRpMlXGap57SZ1_16bn8cqEu8obbNodVjjqxV9Sh9bhHfoxpDBXC16n3m18Mb43C09V8hcZtcmeBSHiYKb78PJ0i4K7GmChj9PEWbBtuCAoMxVogEO_MGPWY_f9q5humaR42ecMOLR-Q-9mBpCcDxR-SW3H9iNw9y0fkj8nvb11kq59jWDjOO21Cs8mvbaKbAWCCYtAXPIDqHZTFHPhIx1xJGvL1O3S736CXTlfwJ2wZ2iF-5uqadojaQS-nIDI6IEM_IefLT98_nrJ81QLzSpc7BjYqwVohNXpIrk4LFbh0qqwTDwi6XiFmaFSlNyb55IT0ddAiNVVwvHaufEoO1u06PifUpOh1BDUhEeywxoPUauFSCZLOmyBSQd6Nc27zgG2_EjHaDhSyQCHbU8iagnxAskwtEQ27L2i7HzYLl5VRycb4mstQy7riroZOQr8lcB1waCjIWySqRZkFyvkmpx5AhxH9yp5oATZBKiUKcjRrCbLm59UjW9gs61v7lzML8nqqxi8xfm0d2z22QdAbWMmUBXk2cNE0pBLXfILDz6sZf83GPK9Zry57JPAKnHPwyA__360X5J7omV4zUR6Rg123jy_Bldq5V728_AG2-h6a priority: 102 providerName: ProQuest – databaseName: Scholars Portal Open Access Journals dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3Ni9QwFA_rCuJl8duuq0QQPEg1k6-mB5FVXBZhxIMDewtNk7gDu-3YmQH37h_ue206bnGPXkpp0pLk_V5eXvPeL4S8Ei6UijOZGzA2uVSG5ZUr6hymwVgYp1nsJT3_qk8X8suZOtsj43FHaQDXN7p2eJ7Uort4--vn1QdQ-Pe9whv9bg02C3_0cQyxmiHB7i1ym0shEfFz-XdXAf9yjIkzN743MU49h_-_M_U1UzUNo7xml07ukYO0oKTHAwLuk73QPCB35mnL_CH5_a0L-fJyDBNHOdDKV6t020a6GggnKAaBwQVQ0MGzkAIh6Zg7SX06joeutyscMLqEL2FN3w7xNBdXtEMWD3q-CyqjA1P0I7I4-fz902mejl7Ia6XFJgebFcF3iJUekq3jTHkmnRJlZB5J2AvkEA1K1MbEOjou69JrHqvCO1Y6Jx6T_aZtwlNCTQy1DjBtSCQ_LHFjtZi5KEDzWeV5zMibccxt6rDtPROj7SAhCxKyvYSsychHFMuuJrJj9w_a7odNymZlULIydcmkL2VZMFdCI6HdElAIiPUZeY1CtYgqkFxdpVQEaDCyYdljzcFGSKV4Ro4mNUH36mnxCAs7Qtdiwk2BRIsqIy93xfgmxrM1od1iHSTBAc9GZOTJgKJdlwT6gJzBx4sJviZ9npY0y_OeGbyAxTqs0A__xyA9I3d5rxo65-KI7G-6bXgOC7CNe9Fr1R99Zy83 priority: 102 providerName: Scholars Portal |
Title | Pre-implementation adaptation of primary care cancer prevention clinical decision support in a predominantly rural healthcare system |
URI | https://www.ncbi.nlm.nih.gov/pubmed/32576202 https://www.proquest.com/docview/2424730875 https://search.proquest.com/docview/2416937723 https://pubmed.ncbi.nlm.nih.gov/PMC7310565 https://doaj.org/article/4e54a8c904d94970b98fc0d44b7cccad |
Volume | 20 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3Na9swFBdtB6WXse9564IGgx2GG8eSLPnYlGZlkBLKCmEXYclSG2ickDSH3feH7z1ZDjW77SKMJRtJ7z09ffzeT4R8YcaVIs94qsDZpFyoLK2MtCkMg14qU2Q-SHp6XVzd8h9zMT8goouFCaB9axZnzcPyrFncB2zlemmHHU5sOJteSIb3xYvhITmUjHVL9Hh0gFsZXXSMKoZbcGi4C5gj_mqE7Lsn5JjhNDuPWymdMwqc_f-OzE9cUx82-cQPTV6Q53ECSc_bir4kB655RY6n8Yj8Nfkz27h0sexg4djvtKqrdXxcebpuCSYogr4gAalv4J2LwEfaxUrSOl6_Q7e7Nc7S6QL-hCXrVYufefhNN8jaQe_3IDLaMkO_IbeTy58XV2m8aiG1omCPKfgoD2sFXxVtcLUfiTrjRrDSZzWSrkvkDHWCWaW89SbntqyL3FeyNllpDHtLjppV494TqryzhYNhgiPZYYkHqXJkPANLz6o69wn51vW5jg3WYSWiCt0KS4OwdBCWVgkZo1j2JZENO7xYbe501AnNneCVsmXG65KXMjMlVBLqzUHrQEPrhHxFoWq0WZCcrWLoAVQY2a_0eZGDOnAh8oSc9kqCrdl-dqcWOtr6VmOAjURiRZGQz_ts_BLxa41b7bAMkt7ASoYl5F2rRfsmdcqYENnTr16b-zlgGIEJPBrCh__-8iM5yYNpFGnOTsnR42bnPsEs69EMwLbmElI1-T4gz8aX17ObQdixgHTKFaQ341-DYHt_AUFPLcY |
link.rule.ids | 230,315,733,786,790,870,891,2115,12083,12792,21416,24346,27955,27956,31752,31753,33406,33407,33777,33778,43343,43633,43838,53825,53827 |
linkProvider | National Library of Medicine |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3Ni9QwFA86C-pF_La6agTBg5TNpEmbnmRXdhl1Z1hkF_YWmq_dAW3HzszBu3-477XpuEXwUkqSliTvM8l7vxDyLjO-lJyJVIGxSYVULK1MYVNQg6FQJmeho_R8kc8uxJdLeRk33NYxrHLQiZ2ido3FPfIDTGMoEL5Oflz9TPHWKDxdjVdo3CZ7CLmpJmTv6Hhx9m13joD7GkOqjMoP1mDdcEuQYzDWFKF4R-aoQ-3_VzffME7jwMkblujkAbkfXUh62NP8Ibnl60fkzjwekj8mv89any5_DIHhOPO0ctUqvjaBrnqICYphX_AAurdQ5mPoIx2yJamLF_DQ9XaFfjpdwp-wpWv6CJrvv2iLuB30ehdGRnts6Cfk4uT4_NMsjZctpFbm2SYFKxVgtRCqvE-vDlPpmDAyKwNzCLteIGqol5lVKthguLCly3moCmdYaUz2lEzqpvbPCVXB29yDohAId1jiUWoxNSEDWWeV4yEhH4Y513HAuluLqFz3FNJAId1RSKuEHCFZdi0RD7sraNorHcVLCy9FpWzJhCtFWTBTQieh3wL4DnjUJeQ9ElWj1ALlbBWTD6DDiH-lD3MOVkFIyROyP2oJ0mbH1QNb6Cjta_2XNxPydleNX2IEW-2bLbZB2BtYy2QJedZz0W5IGa76OIOfFyP-Go15XFMvrzss8ALcc_DJX_y_W2_I3dn5_FSffl58fUnu8U4A8pRn-2Syabf-FThWG_M6Ss8fLhUi8Q |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lj9MwEB7BIlV74c0SWMBISBxQmjSx8zguC9Xy6KoHVlpxseIXW7FNqz4OcOaHM5M4VQO3vVRRPKls-ZsZPz5_BniTKluKJOZhgckm5KKIw0rlOsQw6PJCZbFrenpynp1d8M-X4nLvqq-GtK_VbFhfz4f17KrhVi7nOup4YtF0cpqndF-8iJbGRbfhDvpskncTdb-BQAsa3RmZIovWmNZoLTAhFtaINHgPYZDSYDvxCypdSmqU-_-Pz3sJqk-e3MtG43vwvWtHS0L5Odxu1FD__kfi8UYNvQ93_RiVnbQmD-CWrR_CYOJ34R_Bn-nKhrN5xzynrmWVqZb-ceHYstWwYMQrwx8E1grfWc-tZN1xTGb8DT9svV3SRIDN8J_I0ixais71L7YiYRB2teOpsVZ8-jFcjD9-Oz0L_W0OoRZZugkxDTqcjrgqa89vu5EwMVciLV1sSNc9J1lSK1JdFE47lXBdmixxVW5UXCqVPoGDelHbp8AKZ3VmMRJx0lMsaa82HymXYjCJK5O4AN51HSp9g2Uz2Sky2SJBIhJkgwRZBPCe-nxnSYLbzYvF6of0vSG5FbwqdBlzU_Iyj1WJlcR6cwQ2OoEJ4C0hRlJYQFjoyp9uwAqTwJY8yRLEGhciCeC4Z4nurPvFHeakDydrSWd4ctJuFAG83hXTl0SRq-1iSzakq4OTpTSAoxaiuyZ1SA8g74G31-Z-CUKyERv3EHx24y9fwWD6YSy_fjr_8hwOk8YFszBJj-Fgs9raFzim26iXjff-BQs4S_I |
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=Pre-implementation+adaptation+of+primary+care+cancer+prevention+clinical+decision+support+in+a+predominantly+rural+healthcare+system&rft.jtitle=BMC+medical+informatics+and+decision+making&rft.au=Melissa+L.+Harry&rft.au=Daniel+M.+Saman&rft.au=Anjali+R.+Truitt&rft.au=Clayton+I.+Allen&rft.date=2020-06-23&rft.pub=BMC&rft.eissn=1472-6947&rft.volume=20&rft.issue=1&rft.spage=1&rft.epage=15&rft_id=info:doi/10.1186%2Fs12911-020-01136-8&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_4e54a8c904d94970b98fc0d44b7cccad |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1472-6947&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1472-6947&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1472-6947&client=summon |