See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research article
Habibollah Pirnejad
Urmia University of Medical Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9284-5702
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background Electronic personal health records (ePHRs) are defined as electronic applications through which individuals can access, manage, and share health information in a private, secure, and confidential environment. Existing evidence shows their benefits in improving outcomes, especially for chronic disease patients. However, their use has not been as widespread as expected partly due to barriers faced in their adoption and use. We aimed to identify the types of barriers to a patient, provider, and caregiver adoption/use of ePHRs and to analyze their extent in chronic disease care.
Methods A systematic search in Medline, PubMed, Science Direct, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, and the Institute of Electrical and Electronics Engineers (IEEE) database was performed to find original studies assessing barriers to ePHR adoption/use in chronic care until the end of 2018. Two researchers independently screened and extracted data. We used the PHR adoption model and the Unified Theory of Acceptance and Use of Technology to analyze the results. The Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of evidence in the included studies.
Results Sixty publications met our inclusion criteria. Issues found hindering ePHR adoption/use in chronic disease care were associated with demographic factors (e.g., patient age and gender) along with key variables related to health status, computer literacy, preferences for direct communication, and patient’s strategy for coping with a chronic condition; as well as factors related to medical practice/environment (e.g., providers’ lack of interest or resistance to adopting ePHRs due to workload, lack of reimbursement, and lack of user training); technological (e.g., concerns over privacy and security, interoperability with electronic health record systems, and lack of customized features for chronic conditions); and chronic disease characteristics (e.g., multiplicities of co-morbid conditions, settings, and providers involved in chronic care).
Conclusions ePHRs can be meaningfully used in chronic disease care if they are implemented as a component of comprehensive care models specifically developed for this care. Our results provide insight into hurdles and barriers mitigating ePHR adoption/use in chronic disease care. A deeper understating of the interplay between these barriers will provide opportunities that can lead to an enhanced ePHR adoption/use.
Keywords
personal health records, systematic reviews, ePHR, self-care, chronic diseases
Figure 1
This is a list of supplementary files associated with this preprint. Click to download.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Editorial decision: Accept
On 19 Jun, 2020
Editor assigned
On 18 Jun, 2020
Submission checks complete
On 17 Jun, 2020
Editor invited
On 17 Jun, 2020
Version 3
Posted 16 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 17 Jun, 2020
Editor assigned
On 15 Jun, 2020
Submission checks complete
On 14 Jun, 2020
Editor invited
On 14 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 01 Jun, 2020
Reviewers invited
Invitations sent on 20 May, 2020
Editor assigned
On 11 May, 2020
Editor invited
On 10 May, 2020
Submission checks complete
On 28 Jan, 2020
No comments provided
Editorial decision: Major revision
On 22 Apr, 2020
Review #2 received
Received 21 Apr, 2020
Reviewer #2 agreed
On 16 Apr, 2020
Review #1 received
Received 26 Feb, 2020
Reviewer #1 agreed
On 22 Feb, 2020
Reviewers invited
Invitations sent on 19 Feb, 2020
Editor assigned
On 03 Feb, 2020
Submission checks complete
On 28 Jan, 2020
Editor invited
On 28 Jan, 2020
First submitted
On 23 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
Learn more about our company.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Habibollah Pirnejad
Urmia University of Medical Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9284-5702
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Editorial decision: Accept
On 19 Jun, 2020
Editor assigned
On 18 Jun, 2020
Submission checks complete
On 17 Jun, 2020
Editor invited
On 17 Jun, 2020
Version 3
Posted 16 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 17 Jun, 2020
Editor assigned
On 15 Jun, 2020
Submission checks complete
On 14 Jun, 2020
Editor invited
On 14 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 01 Jun, 2020
Reviewers invited
Invitations sent on 20 May, 2020
Editor assigned
On 11 May, 2020
Editor invited
On 10 May, 2020
Submission checks complete
On 28 Jan, 2020
No comments provided
Editorial decision: Major revision
On 22 Apr, 2020
Review #2 received
Received 21 Apr, 2020
Reviewer #2 agreed
On 16 Apr, 2020
Review #1 received
Received 26 Feb, 2020
Reviewer #1 agreed
On 22 Feb, 2020
Reviewers invited
Invitations sent on 19 Feb, 2020
Editor assigned
On 03 Feb, 2020
Submission checks complete
On 28 Jan, 2020
Editor invited
On 28 Jan, 2020
First submitted
On 23 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Medical Informatics and Decision Making.
Background Electronic personal health records (ePHRs) are defined as electronic applications through which individuals can access, manage, and share health information in a private, secure, and confidential environment. Existing evidence shows their benefits in improving outcomes, especially for chronic disease patients. However, their use has not been as widespread as expected partly due to barriers faced in their adoption and use. We aimed to identify the types of barriers to a patient, provider, and caregiver adoption/use of ePHRs and to analyze their extent in chronic disease care.
Methods A systematic search in Medline, PubMed, Science Direct, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, and the Institute of Electrical and Electronics Engineers (IEEE) database was performed to find original studies assessing barriers to ePHR adoption/use in chronic care until the end of 2018. Two researchers independently screened and extracted data. We used the PHR adoption model and the Unified Theory of Acceptance and Use of Technology to analyze the results. The Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of evidence in the included studies.
Results Sixty publications met our inclusion criteria. Issues found hindering ePHR adoption/use in chronic disease care were associated with demographic factors (e.g., patient age and gender) along with key variables related to health status, computer literacy, preferences for direct communication, and patient’s strategy for coping with a chronic condition; as well as factors related to medical practice/environment (e.g., providers’ lack of interest or resistance to adopting ePHRs due to workload, lack of reimbursement, and lack of user training); technological (e.g., concerns over privacy and security, interoperability with electronic health record systems, and lack of customized features for chronic conditions); and chronic disease characteristics (e.g., multiplicities of co-morbid conditions, settings, and providers involved in chronic care).
Conclusions ePHRs can be meaningfully used in chronic disease care if they are implemented as a component of comprehensive care models specifically developed for this care. Our results provide insight into hurdles and barriers mitigating ePHR adoption/use in chronic disease care. A deeper understating of the interplay between these barriers will provide opportunities that can lead to an enhanced ePHR adoption/use.
Figure 1
This is a list of supplementary files associated with this preprint. Click to download.
Loading...