Factors that affect the use of electronic personal health records among patients: A systematic review

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Abstract

Background

Electronic personal health records (ePHRs) are web-based tools that enable patients to access parts of their medical records and other services. In spite of the potential benefits of using ePHRs, their adoption rates remain very low. The lack of use of ePHRs among patients leads to implementation failures of these systems. Many studies have been conducted to examine the factors that influence patients’ use of ePHRs, and they need to be synthesised in a meaningful way.

Objective

The current study aimed to systematically review the evidence regarding factors that influence patients’ use of ePHRs.

Methods

The search included: 42 bibliographic databases (e.g. Medline, Embase, CINHAL, and PsycINFO), hand searching, checking reference lists of the included studies and relevant reviews, contacting experts, and searching two general web engines. Study selection, data extraction, and study quality assessment were carried out by two reviewers independently. The quality of studies was appraised using the Mixed Methods Appraisal Tool. The extracted data were synthesised narratively according to the outcome: intention to use, subjective measures of use, and objective measures of use. The identified factors were categorised into groups based on Or and Karsh’s conceptual framework.

Results

Of 5225 citations retrieved, 97 studies were relevant to this review. These studies examined more than 150 different factors: 59 related to intention to use, 52 regarding subjectively-measured use, and 105 related to objectively-measured use. The current review was able to draw definitive conclusions regarding the effect of only 18 factors. Of these, only three factors have been investigated in connection with every outcome, which are: perceived usefulness, privacy and security concerns, and internet access.

Conclusion

Of the numerous factors examined by the included studies, this review concluded the effect of 18 factors: 13 personal factors (e.g. gender, ethnicity, and income), four human-technology factors (e.g. perceived usefulness and ease of use), and one organisational factor (facilitating conditions). These factors should be taken into account by stakeholders for the successful implementation of these systems. For example, patients should be assured that the system is secure and no one can access their records without their permission in order to decrease their concerns about the privacy and security. Further, advertising campaigns should be carried out to increase patients’ awareness of the system. More studies are needed to conclude the effect of other factors. In addition, researchers should conduct more theory-based longitudinal studies for assessing factors affecting initial use and continuing use of ePHRs among patients.

Introduction

Electronic Personal Health Records (ePHRs) are secure internet-based systems that allow patients to view parts of their medical records and share them with trusted others [1]. Such systems may also provide services to patients such as messaging healthcare providers, requesting repeat prescriptions, and booking appointments [2].

Despite the potential benefits of ePHRs, their adoption rates are often very low [[2], [3], [4], [5], [6]]. For example, three American national surveys conducted by California HealthCare Foundation [7], Markle Foundation [8], and Markle Foundation [9] reported that about 7%, 3%, and 10% of adults had ever utilised ePHRs, respectively. In the United Kingdom, the adoption rate of ePHRs (i.e. HealthSpace) did not exceed 0.13% [10]. The uptake rates of ePHRs in other Europe countries (e.g. France, Denmark, Estonia, etc.) reached only around 5% [11].

The lack of use of ePHRs among patients leads to a failure of the implementation of these systems [12,13]. Identifying factors that influence patients’ use of ePHRs is crucial to increasing patients’ adoption and improving implementation success of ePHRs [4,5,14]. Many studies have investigated factors that affect patients’ use of ePHRs. To date, no meaningful synthesis of findings has been produced. Therefore, the current study aimed to systematically review the evidence regarding factors that influence patients’ use of ePHRs.

A conceptual framework used by Or and Karsh [15] in a review of consumer health information technology acceptance was used in this review as a theoretical lens to group factors. Or and Karsh adopted this framework from other frameworks developed by Holden and Karsh [16] and Karsh [17]. According to this framework, adoption of health information technologies is predicted by: (i) individual factors, which refer to sociodemographic characteristics, personality characters, and health status; (ii) human-technology interaction factors, which refer to individual’s perceptions and expectations about a technology; (iii) organisational factors, which refer to facilitating conditions provided by organisations, implementation processes, organisation’s structures, and end-user perceptions of them; (iv) social factors, which refer to the effect of other people to which a person belongs; (v) environmental factors, which refer to characteristics of the physical setting where a system is used; and (vi) task factors, which refer to the degree to which a technology influences a task and individual’s perceptions of this effect [15].

Section snippets

Methods

The systematic review followed guidelines recommended by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [18]. The protocol for this systematic review is registered at PROSPERO with the number CRD42017056050.

Search results

As shown in Fig. 1, the search process of 42 bibliographic databases and two web engines retrieved 5225 citations. After removing 1602 duplicates, 3623 unique titles and abstracts remained. Of those titles and abstracts, 3345 citations were excluded after scanning their titles and abstracts. By reading the full text of the 278 remaining citations, 85 publications were included. Nineteen additional studies were identified from others sources. In total, 104 publications were included in the

Principal findings

This review aimed to identify factors that affect patients’ use of ePHRs. We identified ninety-seven individual studies examining the effect of more than 150 different factors: 59 factors related to intention to use, 52 factors regarding subjectively-measured use, and 105 factors related to objectively-measured use. In spite of this large number of factors, the current review was able to draw definitive conclusions regarding the effect of only 18 factors. For the remaining factors, definitive

Conclusion

Of the numerous factors examined by the included studies, this review concluded the effect of 18 factors: 13 personal factors (e.g. gender, ethnicity, and income), four human-technology factors (e.g. perceived usefulness and ease of use), and one organisational factor (facilitating conditions). These factors should be taken into account by stakeholders for the successful implementation of these systems. More studies are needed to conclude the effect of other factors. In addition, researchers

Authors’ contribution

The review was conducted by AA, with guidance from and under the supervision of BMB, TF, and PG. AA drafted the manuscript, and it was revised critically for important intellectual content by all authors. All authors approved the manuscript for publication and agree to be accountable for all aspects of the work.

Conflicts of interest

The authors have no competing interests to declare.

Summary Tables

What was already known on this topic:

  • Electronic personal health records are useful tools for converting the care from physician-centred to patient-centred.

  • Adoption rates of electronic personal health records are usually very low.

  • Many studies assessed factors affecting adoption of electronic personal health records.

What this study added to our knowledge:

  • This review provides a long list of possible factors affecting patients’ use

Acknowledgements

The Authors would like to thank the research assistant Mohammad Khasawneh (MK) for his help in the screening of studies for inclusion in the review, extracting data from the included studies, and assessing the studies’ quality.

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