Accessing and Sharing Electronic Personal Health Data

Maria Karampela

, Soﬁa Ouhbi

2,3

and Minna Isomursu

Digital Design Department, IT University of Copenhagen, Copenhagen, Denmark

Dept. of Computer Science & Software Engineering, CIT, UAE University, Al Ain, U.A.E.

TICLab, FIL, International University of Rabat, Rabat, Morocco

Keywords:

Personal Health Data, Accessibility, Sharing, Connected Health, Design.

Abstract:

An increasing attention has been given to personal health data (PHD) research over the last years. The rise

of researchers’ interest could be attributed to the increasing amount of PHD that are stored across various

databases, as a result of individuals’ rapidly-evolving digital life. Accessing and sharing PHD is essential to

create personalized health services and to involve patients in the design process of these services. This paper

conducts a survey of literature to present an overview of literature about accessing and sharing of PHD. This

study aims to identify limitations in research and propose future directions. Sixteen studies were selected from

various bibliographic databases and were classiﬁed according to three criteria: research type, empirical type

and contribution type. The results provide a preliminary review with respect to access and sharing of PHD,

addressing a need for more research about PHD accessibility and for solution proposals for both topics.

1 INTRODUCTION

The development of information and communication

technologies (ICT) and their adoption in everyday

life, has resulted in a growing amount of personal

data that are stored across different digital platforms

(Karampela et al., 2018a; Carroll and Richardson,

2017). ICT has changed the way the organizations

and companies handle data and have been seen to hold

the potential to increase the value and quality in pro-

vision of healthcare services (Raghupathi and Raghu-

pathi, 2014). Healthcare industry undergoes a trans-

formation moving towards models that aim to exploit

electronic medical records EMRs and personal health

records PHRs to create more personalized interven-

tions for patients (Lee et al., 2017).

Electronic Health Records EHRs are records for

patients’ medical data such as medication and med-

ical history or laboratory tests. EHRs are adminis-

trated by healthcare professionals and organizations

(Ouhbi et al., 2017). In contrast to EHRs, PHRs are

records that consist of health and wellness data related

to the care of users and managed by them across their

life span. The adoption of PHRs has various potential

beneﬁts. In fact, PHRs allow users/patients to access

their health information and have been seen to pro-

mote self-management of diseases (Tang et al., 2006).

Besides EHRs and PHRs, mobile PHRs (mPHRs) so-

lutions have also emerged to facilitate the manage-

ment of health information, especially useful in cases

of patients with chronic conditions. mPHRs allow

users to access and manage their health information

through their smartphones and give them the pos-

sibility to make appropriate data available to those

who need it (Ouhbi et al., 2015). Uniﬁed health-

care systems such as systems that combine EHR and

mPHR are considered to be a powerful tool that could

facilitate seamless communication between patients

and clinicians, leading to faster and informed deci-

sions, that are especially valuable in patients with

chronic conditions such as diabetes (Chang et al.,

2010; Richardson et al., 2017).

The potential of utilization of PHD towards the

creation of more personalized healthcare systems has

been discussed in literature (Pagliari et al., 2007;

Wilcox et al., 2009; Wilcox et al., 2010). Previous

studies have recognized the vital role of personaliza-

tion features in the design of future healthcare ap-

plications as components that could facilitate doctor-

patient interaction (Larkin and Kelliher, 2011). For

example, the addition of free-text annotation ﬁelds

to enable storage of personal information of patients

to EHR, could provide doctors with essential context

pertinent to diagnosis of diseases (Larkin and Kelli-

her, 2011). Apart from that, the addition of design

components to include patients’ personal information

in electronic healthcare systems has been proposed

as a step towards the improvement of quality of care

182

Karampela, M., Ouhbi, S. and Isomursu, M.

Accessing and Sharing Electronic Personal Health Data.

DOI: 10.5220/0007247301820189

In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), pages 182-189

ISBN: 978-989-758-353-7

that potentially could also contribute to cost reduction

(Zhou et al., 2010).

Nevertheless, barriers such as security and pri-

vacy concerns discourage individuals to exploit this

potential in spite of the fact that medical data are un-

der the umbrella of constitutional laws (Srinivasan,

2006; Sahama et al., 2013). In the USA, the cur-

rent legislation concerning the protection of medical

data is regulated by Health Insurance Portability and

Accountability Act (HIPAA) since 1996, while in Eu-

rope the enforcement of the new General Data Protec-

tion Regulation (GDPR) on May 2018, aims to protect

processing of personal data and to establish security

standards for the distribution of data (Carri

on et al.,

2011; GDPR, 2016). According to the new GDPR

people will have the right to demand and obtain elec-

tronic copies of health data from data controllers at no

cost, while data sharing will be more transparent in

terms of access control and protection of anonymity

(GDPR, 2016).

Many international organizations are working on

the standardization of e-health applications, particu-

larly EHRs applications (ISO/TR 20514:2005) (iso,

b) and PHRs applications (ISO/TR 14292:2012) (iso,

a), to address the need for common frames of refer-

ences. Among the well-know international organiza-

tions that work on e-health standardizations: Clini-

cal and Laboratory Standards Institute (CLSI) (Cls,

2018), International Telecommunication Union (ITU-

T/ITU-D2) (Itu, 2018), e-health Standardization Co-

ordination Group (eHSCG) (eHS, 2018) and Interna-

tional Organization for Standardizations (ISO) Tech-

nical Committee (TC) on health informatics (ISO/TC

215) (Iso, 2018). Their effort demonstrates a contin-

uous demand for establishment of internationally ac-

cepted standards for the electronic exchange of medi-

cal information including personal health data (PHD).

PHD management is a research topic that has at-

tracted the interest of researchers and practitioners

from various disciplines, such as engineers, computer

scientists and medical professionals (Puustj

arvi and

Puustj

arvi, 2016; Alyami et al., 2017; Agboola et al.,

2017). Various aspects of PHD have been studied and

discussed so far, such as mobile-based solutions for

integration of PHD to healthcare system, PHD man-

agement using meta-data and cloud-computing for

seamless access and sharing of data among medical

professionals, as well as access control and security

of PHD in cloud-computing (Aboelfotoh et al., 2014;

Alyami et al., 2017; Li et al., 2010). While privacy

and security solutions have also been a subject of dis-

cussions (Se

nor et al., 2012; Ishikawa et al., 2007),

many studies have been focused on evaluation of ac-

cessing and sharing of PHD.

To the best of our knowledge, no previous stud-

ies have reported and mapped accessing and shar-

ing of PHD. Thus, the present paper aims to give

an overview of the published research in this topic

identifying research gaps and stressing directions for

future research. To select candidate studies for this

survey of literature, a bibliographic search was con-

ducted in databases such as IEEE Digital Library and

ACM Digital Library. The selected papers have been

classiﬁed afterwards according to their research types,

empirical types and contribution types. This paper is

based on a previous study on PHD (Karampela et al.,

2018b).

The remainder of the paper is organized as fol-

lows. Section 2 outlines the research method that was

used. Section 3 presents the articles that included

in the study and classiﬁcation results. Section 4 dis-

cusses the main ﬁndings of the study. Finally, Section

5 presents the conclusions and future work.

2 METHOD

This study has been undertaken as a survey of litera-

ture of the articles that address the topics of accessing

and sharing of PHD.

2.1 Review and Protocol

Quality reporting guidelines in this paper, speciﬁed by

the Preferred Reporting Items for Systematic reviews

and Meta-Analysis (PRISMA) group (Liberati et al.,

2009), were followed. Before beginning the search

for studies and the data extraction, a review protocol

was developed in which each step was described, in-

cluding eligibility criteria.

2.2 Eligibility Criteria

The following inclusion criteria (IC) were used:

IC The studies that address PHD.

The studies that met at least one of the following ex-

clusion criteria (EC) were excluded:

EC1 Papers whose subject is non-digital health data.

EC2 Papers that are focusing on other aspects of

PHD such as data management and interoperabil-

ity.

2.3 Identiﬁcation of Studies

To identify the studies to be included in this study, a

search has been conducted in January 2018 in the fol-

lowing sources: IEEEXplore, ACM Digital Library,

Accessing and Sharing Electronic Personal Health Data

183

Springer Link, and Science Direct (Karampela et al.,

2018b). Google scholar was also selected to seek

grey literature in the ﬁeld such as white papers and

technical reports. The search string used to perform

the search in the digital libraries selected was the fol-

lowing: “Personal’”AND “health” AND “data” AND

(“electronic*” OR “Digital”). The selection of this

search string is in alignment with the scope of the

study, as authors wanted to limit the search results to

data instead of systems and applications. The search

was limited to the title, abstract and keywords of the

studies. There was no time frame speciﬁed for the

literature search.

A total of 16 studies were selected from 246 pa-

pers identiﬁed. Fig. 1 shows the process of the studies

selection. 5 studies were selected for PHD accessibil-

ity and 11 studies for PHD sharing.

Figure 1: PRISMA Flow Diagram. Acronyms: Inclusion criteria

(IC) and exclusion criteria (EC).

2.4 Analysis and Synthesis Method

The papers selected have been classiﬁed with respect

of their research type, empirical type and contribution

type (Karampela et al., 2018b).

A research type can be classiﬁed as:

• Solution proposal: include studies that proposed

solutions either new or extensions of an existing

approach.

• Evaluation research: the proposed approaches are

implemented in practice and evaluation is being

performed.

• Opinion paper: these type of papers present a per-

sonal opinion pertinent to a solution.

• Other, e.g. Review.

An empirical study could use one of the following

empirical methodologies:

• Case study: a study that examines an approach in

real-life context.

• Experiment: the evaluation of the approach is per-

formed under controlled conditions.

• Survey: a query to collect qualitative information,

e.g. questionnaire.

• History-based evaluation or other: the evaluation

of approaches is based on previous results.

If the paper is not empirically evaluated then it is clas-

siﬁed as theory.

The type of contribution could be:

• Method: a regular and systematic means of ac-

complishing PHD.

• Model: a representation of a system that allows

investigations through a hierarchical structure.

• Framework: a real or conceptual structure in-

tended to serve as a support or guide for PHD.

• Process: a series of actions, or functions leading

to a result and performing operations on data.

• Tool-based technique: a technique based on a

software tool to accomplish PHD tasks.

• Guidelines, or other.

The data was tabulated in an Excel Sheet for both

quantitative and quality assessment.

3 RESULTS

3.1 Classiﬁcation Results

This section presents the analysis of the results and

the map created by combining different facets. The

overall result is presented in Table 1.

Fig. 2 shows that there is a discontinuity in the

publication trend of PHD accessibility and sharing

and also that the interest in both topic has started a

decade ago.

Figure 2: Publication trend.

Fig. 3 presents the publication channels that have

identiﬁed in PHD accessibility and sharing literature.

80% of the selected studies about PHD accessibility

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184

Table 1: Classiﬁcation results.

Topic Reference Publication

channel

Publication year Research type Empirical type Contribution

type

PHD Accessibility (Wu et al., 2011) Conference 2011 Solution proposal Experiment Method

(Gladwin, 2012) Journal 2012 Opinion paper Theory Guidelines

(Van Gorp and Comuzzi, 2014) Journal 2012 Evaluation research Experiment Tool

(Sulthana and Habeeba, 2014) Journal 2014 Review Theory Method

(Greenberg et al., 2017) Journal 2017 Evaluation research Survey Tool

PHD Sharing (Frost and Massagli, 2008) Journal 2008 Evaluation research Other Tool

(Weitzman et al., 2010) Journal 2010 Evaluation research Survey Model

(Capozzi and Lanzola, 2011) Conference 2011 Solution proposal Experiment Framework

(Weitzman et al., 2012) Journal 2012 Evaluation research Survey Model

(Pickard and Swan, 2014) Symposium 2014 Solution proposal Survey Framework

(Pickard, 2014) Conference 2014 Evaluation research Survey Method

(Vahidhunnisha et al., 2014) Journal 2014 Solution proposal Theory Framework

(Bietz et al., 2015) Journal 2015 Evaluation research Survey Method

(Ssembatya and Kayem, 2015) Workshop 2015 Solution proposal Experiment Framework

(Chen et al., 2016) Journal 2016 Evaluation research Survey Method

(Spencer et al., 2016) Journal 2016 Evaluation research Survey Method

are published in journals while 20% are published in

conferences. 64% of the studies selected about PHD

sharing are published in journals, 18% in conferences,

9% in symposia and 9% in workshops.

Figure 3: Publication channels.

Fig. 4 presents the research types identiﬁed in

PHD accessibility and PHD sharing literature. The

majority of the studies selected are evaluation re-

search, followed by solution proposals.

Figure 4: Research types of the selected studies.

Fig. 5 presents the empirical types identiﬁed in

both PHD accessibility and sharing selected studies.

The majority of selected studies about PHD sharing

are empirically evaluated using surveys or question-

naires, while studies about accessibility have mainly

conducted experiments to empirically evaluate their

contributions.

Figure 5: Empirical types of the selected studies.

Fig. 6 presents the contribution types identiﬁed

in both PHD accessibility and PHD sharing selected

studies. Three types were identiﬁed in PHD acces-

sibility: guidelines, tools and methods. While four

types are identiﬁed in PHD sharing: frameworks,

methods, models, and tools.

3.2 Solutions for PHD Accessibility and

Sharing

Wu et al. (Wu et al., 2011) have proposed a method-

ology based on categorized architecture for accessing

PHRs. The suggested privilege management mecha-

nism allows users to adopt their own privilege scope

and access only the required data. The authors argue

that their contribution enhances the privacy security

Accessing and Sharing Electronic Personal Health Data

185

Figure 6: Contribution types of the selected studies.

level but may have an impact on disease statistics and

management of major infectious diseases.

Pickard and Swan (Pickard and Swan, 2014) have

presented a framework to increase PHD sharing based

on “trust, motivation, community, and informed con-

sent”. They have built their contribution on the results

of an online survey that has demonstrated a strong

willingness to share PHD for research purposes in the

population surveyed. Capozzi and Lanzola (Capozzi

and Lanzola, 2011) have proposed a synchronization

framework for speeding up the implementation of per-

sonal health services (PHSs). PHS refers to devices

made available by the combination of ICT, microelec-

tronics and nanosciences.

Vahidhunnisha et al. (Vahidhunnisha et al., 2014)

have proposed a framework to improve the privacy

in sharing PHD in the cloud and to establish patient-

centric privacy control over their own PHRs. This

framework is based on attribute based encryption

(ABE), which is a one to one encryption technique

that can be applied to protect PHRs and EHRs. Ssem-

batya and Kayem (Ssembatya and Kayem, 2015) have

also based their contribution on encryption. They

have proposed an access control framework supported

by identity-based encryption for a secure mPHR sys-

tem to share PHD in a secure and efﬁcient way.

4 DISCUSSION

4.1 Main Findings

This study has conducted a survey of literature con-

cerning accessibility and sharing of PHD. PHD is

an interdisciplinary research area with contributions

to various disciplines (Larkin and Kelliher, 2011; Li

et al., 2014; Mendelson, 2017; Wilcox et al., 2010).

The aim of the study was to provide researchers with

an overview of the available literature in order to iden-

tify limitations in the present published literature. Ac-

cessibility and sharing of PHD are research topics that

have implications to future design of healthcare sys-

tems. Our study points out that research within these

topics is still in its infancy.

The interest in PHD accessibility and sharing

started since the end of the last decade. This recent

interest and the discontinuity in the publication trend

may seem reasonable and could be explained by the

fact that both topics started to emerge with the use of

EHRs, PHRs and digital health.

The majority of papers were published in journals.

Despite the increasing interest in accessing and shar-

ing of PHD over the last decade, we only found 16

studies that discuss access and sharing of PHD (5 ac-

cess, 11 sharing). Regarding access of PHD only one

solution proposal was found, which addresses the lack

of research in this area.

The contribution types of the selected papers point

out a lack of guidelines and tools in both research ar-

eas. Thus, more research is needed to towards this

direction. The majority of papers concerning sharing

PHD were surveys (models, frameworks), suggesting

that more experiments are needed. In both research

areas no case study has been conducted so far, reveal-

ing that there is a lack of user validation on the pro-

posed solutions in real settings.

Although many studies have addressed patients

with chronic conditions as the user group that could

beneﬁt the most from accessing and sharing of PHD

(DuBenske et al., 2010; Kim et al., 2013), only one

paper (Greenberg et al., 2017) of the selected stud-

ies has evaluated a tool using data from patients with

chronic conditions.

4.2 Implications

The ﬁndings of this study have implications for re-

searchers who intend to conduct studies pertinent to

EHR or in general within PHD subject. In addition,

this research is relevant to practitioners who are work-

ing in connected health and would like to have an

overview on the existent studies on PHD accessibil-

ity and sharing. We believe that this study can be a

benchmark for future endeavors towards new research

in the areas of accessing and sharing PHD, as we have

attempted to point out the speciﬁc research types and

empirical types in need of further research. We invite

researchers to direct their research efforts to the sug-

gested areas in order to improve the quality and quan-

tity of research and to offer new perspectives evolving

users more actively in the validation process of the

identiﬁed approaches.

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186

4.3 Limitations

This study may have several limitations, such as:

• The search was limited only to the title, abstract

and keywords of the papers which may have omit-

ted candidate studies. However, if a paper’s main

focus is PHD then the PHD terms should appear at

least in the abstract and keywords which alleviate

the risk of omitting relevant studies.

• Other classiﬁcation criteria may have been rele-

vant to extract further information from the se-

lected studies. However, the main aim of this pa-

per is to give an overview of PHD literature and

the criteria used ﬁt this purpose.

• PHD literature was studied mainly in this paper

through the engineering and computing lens, for

this reason the search for papers was conducted in

the databases listed in Section 2.3. Although bib-

liographic search was conducted in Science and

Engineering databases excluding therefore med-

ical libraries such as PubMed, we could argue

that the inclusion of Google Scholar, which is a

generic database alleviates the risk of omission of

relevant studies.

5 CONCLUSIONS

This paper provides an overview of existing research

pertinent to PHD accessibility and sharing. We clas-

siﬁed the selected papers according to their research

type, empirical type and contribution type and then

we described in brief the papers included in our study.

What we identiﬁed is a need for more research about

PHD accessibility and for solution proposals for both

topics. Although research about accessing and shar-

ing of PHD is still in its infancy, the emergence of

connected health solutions (Ouhbi et al., 2018; Car-

roll et al., 2016) and adoption of wearables technolo-

gies could increase scientiﬁc interest to this topic in

the future. For future work, we intend to propose a

solution for PHD accessibility and sharing with which

to assist connected health systems designers.

REFERENCES

ISO/TR 14292:2012 Health Informatics - Personal Health

Records Deﬁnition, scope and context.

ISO/TR 20514:2005 Health Informatics - Electronic Health

Record Deﬁnition, scope and context.

(Sep 2018). CLSI. URL: https://goo.gl/gCXNd5.

(Sep 2018). eHSCG. URL: https://goo.gl/pb3k1u.

(Sep 2018). ISO/TC 215. URL: https://goo.gl/hywkdn.

(Sep 2018). ITU-T. URL: https://goo.gl/ebiptt.

Aboelfotoh, M. H., Martin, P., and Hassanein, H. S. (2014).

A mobile-based architecture for integrating personal

health record data. In 2014 IEEE 16th Interna-

tional Conference on e-Health Networking, Appli-

cations and Services (Healthcom), pages 269–274.

IEEE.

Agboola, S., Golas, S., Fischer, N., Nikolova-Simons, M.,

op den Buijs, J., Schertzer, L., Kvedar, J., and Jeth-

wani, K. (2017). Healthcare utilization in older pa-

tients using personal emergency response systems: an

analysis of electronic health records and medical alert

data. BMC health services research, 17(1):282.

Alyami, M. A., Almotairi, M., Aikins, L., Yataco, A. R.,

and Song, Y.-T. (2017). Managing personal health

records using meta-data and cloud storage. In 2017

IEEE/ACIS 16th International Conference on Com-

puter and Information Science (ICIS), pages 265–271.

IEEE.

Bietz, M. J., Bloss, C. S., Calvert, S., Godino, J. G., Gre-

gory, J., Claffey, M. P., Sheehan, J., and Patrick,

K. (2015). Opportunities and challenges in the use

of personal health data for health research. Jour-

nal of the American Medical Informatics Association,

23(e1):e42–e48.

Capozzi, D. and Lanzola, G. (2011). A data synchroniza-

tion framework for personal health systems. In Inter-

national Conference on Wireless Mobile Communica-

tion and Healthcare, pages 300–304. Springer.

Carri

on, I., Fern

andez-Alem

an, J. L., and Toval, A. (2011).

Usable privacy and security in personal health records.

In IFIP Conference on Human-Computer Interaction,

pages 36–43. Springer.

Carroll, N. and Richardson, I. (2017). A disciplined inno-

vation approach to health technology solutions. Pro-

ceedings of the 10th HealthInf Conference, page 389.

Carroll, N., Travers, M., and Richardson, I. (2016). Eval-

uating multiple perspectives of a connected health

ecosystem. In HEALTHINF.

Chang, I.-C., Hsiao, S.-J., Hsu, H.-M., and Chen, T.-H.

(2010). Building mPHR to assist diabetics in self-

healthcare management. In 7th International Con-

ference on Service Systems and Service Management,

ICSSSM, pages 1–5. IEEE.

Chen, J., Bauman, A., and Allman-Farinelli, M. (2016).

A study to determine the most popular lifestyle

smartphone applications and willingness of the pub-

lic to share their personal data for health research.

Telemedicine and e-Health, 22(8):655–665.

DuBenske, L. L., Gustafson, D. H., Shaw, B. R., and Cleary,

J. F. (2010). Web-based cancer communication and

decision making systems: connecting patients, care-

givers, and clinicians for improved health outcomes.

Medical Decision Making, 30(6):732–744.

Frost, J. H. and Massagli, M. P. (2008). Social uses of

personal health information within patientslikeme, an

online patient community: what can happen when pa-

tients have access to one another’s data. Journal of

Medical Internet Research, 10(3).

Accessing and Sharing Electronic Personal Health Data

187

GDPR (2016). Regulation (EU) 2016/679 of the european

parliament and of the council of 27 april 2016 on the

protection of natural persons with regard to the pro-

cessing of personal data and on the free movement of

such data, and repealing directive 95/46. Ofﬁcial Jour-

nal of the European Union (OJ), 59:1–88.

Gladwin, J. (2012). Patients welcome access to online

health records: Jacqui gladwin argues that giving peo-

ple the right to see their personal medical data beneﬁts

them and the healthcare professionals involved. Pri-

mary Health Care, 22(5):10–10.

Greenberg, A. J., Falisi, A. L., Rutten, L. J. F., Chou,

W.-Y. S., Patel, V., Moser, R. P., and Hesse, B. W.

(2017). Access to electronic personal health records

among patients with multiple chronic conditions: A

secondary data analysis. Journal of Medical Internet

Research, 19(6):e188.

Ishikawa, K., Ohmichi, H., Umesato, Y., Terasaki, H.,

Tsukuma, H., Iwata, N., Tanaka, T., Kawamura, A.,

Sakata, K., Sainohara, T., et al. (2007). The guideline

of the personal health data structure to secure safety

healthcare: The balance between use and protection

to satisfy the patients’ needs. international journal of

Medical Informatics, 76(5-6):412–418.

Karampela, M., Grundstrom, C., and Isomursu, M. (2018a).

Personal health data: Access and perceived value in

denmark. In 2018 40th Annual International Confer-

ence of the IEEE Engineering in Medicine and Biol-

ogy Society (EMBC), pages 4081–4084. IEEE.

Karampela, M., Ouhbi, S., and Isomursu, M. (2018b). Per-

sonal health data: A systematic mapping study. Inter-

national journal of medical informatics, 118:86–98.

Kim, S. C., Shah, D. V., Namkoong, K., McTavish, F. M.,

and Gustafson, D. H. (2013). Predictors of online

health information seeking among women with breast

cancer: the role of social support perception and emo-

tional well-being. Journal of Computer-Mediated

Communication, 18(2):212–232.

Larkin, K. and Kelliher, A. (2011). Designing ﬂexible

EMR systems for recording and summarizing doctor-

patient interactions. In CHI’11 Extended Abstracts on

Human Factors in Computing Systems, pages 1609–

1614. ACM.

Lee, J., Kim, J. G. B., Jin, M., Ahn, K., Kim, B., Kim, S.,

and Kim, J. (2017). Beneﬁcial effects of two types of

personal health record services connected with elec-

tronic medical records within the hospital setting.

CIN: Computers, Informatics, Nursing, 35(11):574–

581.

Li, M., Yu, S., Ren, K., and Lou, W. (2010). Securing

personal health records in cloud computing: Patient-

centric and ﬁne-grained data access control in multi-

owner settings. In International conference on secu-

rity and privacy in communication systems, pages 89–

106. Springer.

Li, Y., Guo, L., Wu, C., Lee, C.-H., and Guo, Y. (2014).

Building a cloud-based platform for personal health

sensor data management. In Biomedical and Health

Informatics (BHI), 2014 IEEE-EMBS International

Conference on, pages 223–226. IEEE.

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C.,

Gøtzsche, P. C., Ioannidis, J. P., Clarke, M., Dev-

ereaux, P., Kleijnen, J., and Moher, D. (2009). The

PRISMA statement for reporting systematic reviews

and meta-analyses of studies that evaluate health care

interventions: explanation and elaboration. Annals of

Internal Medicine, 151(4):W65.

Mendelson, D. (2017). Legal protections for personal health

information in the age of Big Data-a proposal for

regulatory framework. Ethics, Medicine and Public

Health, 3(1):37–55.

Ouhbi, S., Fern

andez-Alem

an, J. L., Carrillo-de Gea, J. M.,

Toval, A., and Idri, A. (2017). E-health internation-

alization requirements for audit purposes. Computer

methods and programs in biomedicine, 144:49–60.

Ouhbi, S., Fern

andez-Alem

an, J. L., Toval, A., Rivera Pozo,

J., and Idri, A. (2018). Sustainability requirements for

connected health applications. Journal of Software:

Evolution and Process, 30(7):e1922.

Ouhbi, S., Idri, A., Fern

andez-Alem

an, J. L., and Toval, A.

(2015). Mobile personal health records for cardiovas-

cular patients. In Third World Conference on Complex

Systems, WCCS, pages 1–6. IEEE.

Pagliari, C., Detmer, D., and Singleton, P. (2007). Potential

of electronic personal health records. BMJ: British

Medical Journal, 335(7615):330.

Pickard, K. T. (2014). Exploring markets of data for per-

sonal health information. In 2014 IEEE International

Conference on Data Mining Workshop, ICDMW,

pages 477–480. IEEE.

Pickard, K. T. and Swan, M. (2014). Big desire to share big

health data: A shift in consumer attitudes toward per-

sonal health information. In 2014 AAAI Spring Sym-

posium Series, pages 2168–7161.

Puustj

arvi, J. and Puustj

arvi, L. (2016). Managing frag-

mented personal data: Going beyond the limits of

personal health records. In Proceedings of the In-

ternational Joint Conference on Biomedical Engi-

neering Systems and Technologies, pages 145–150.

SCITEPRESS-Science and Technology Publications,

Lda.

Raghupathi, W. and Raghupathi, V. (2014). Big data an-

alytics in healthcare: promise and potential. Health

information science and systems, 2(1):3.

Richardson, I., AbuBaker, A., O’Connor, P., O’Mahony, J.,

and O’Leary, P. (2017). Sink or swim: Connected

health software-grasping the innovation opportunities

by mitigating risk. In HEALTHINF, pages 213–221.

Sahama, T., Simpson, L., and Lane, B. (2013). Security

and privacy in ehealth: Is it possible? In 2013 IEEE

15th International Conference on e-Health Network-

ing, Applications & Services (Healthcom), pages 249–

253. IEEE.

nor, I. C., Alem

an, J. L. F., and Toval, A. (2012). Personal

health records: New means to safely handle health

data? Computer, 45(11):27–33.

Spencer, K., Sanders, C., Whitley, E. A., Lund, D., Kaye,

J., and Dixon, W. G. (2016). Patient perspectives on

sharing anonymized personal health data using a digi-

tal system for dynamic consent and research feedback:

HEALTHINF 2019 - 12th International Conference on Health Informatics

188

a qualitative study. Journal of Medical Internet Re-

search, 18(4).

Srinivasan, A. (2006). Keeping online personal records

private: security and privacy considerations for web-

based phr systems. Journal of AHIMA, 77(1):62–3.

Ssembatya, R. and Kayem, A. V. (2015). Secure and efﬁ-

cient mobile personal health data sharing in resource

constrained environments. In IEEE 29th Interna-

tional Conference on Advanced Information Network-

ing and Applications Workshops, WAINA, pages 411–

416. IEEE.

Sulthana, M. Z. and Habeeba, S. (2014). Assurance of pa-

tient control towards personal health data. Interna-

tional Journal Of Advanced Research In Engineering

And Science, 2:1660–1664.

Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., and

Sands, D. Z. (2006). Personal health records: deﬁni-

tions, beneﬁts, and strategies for overcoming barriers

to adoption. Journal of the American Medical Infor-

matics Association, 13(2):121–126.

Vahidhunnisha, J., Balasubramaniam, T., et al. (2014). Im-

proving privacy in sharing of personal health data stor-

age on cloud. IJITR, 2(3):940–944.

Van Gorp, P. and Comuzzi, M. (2014). Lifelong personal

health data and application software via virtual ma-

chines in the cloud. IEEE journal of biomedical and

health informatics, 18(1):36–45.

Weitzman, E. R., Kaci, L., and Mandl, K. D. (2010). Shar-

ing medical data for health research: the early per-

sonal health record experience. Journal of Medical

Internet Research, 12(2).

Weitzman, E. R., Kelemen, S., Kaci, L., and Mandl, K. D.

(2012). Willingness to share personal health record

data for care improvement and public health: a sur-

vey of experienced personal health record users. BMC

Medical Informatics and Decision Making, 12(1):39.

Wilcox, L., Lu, J., Lai, J., Feiner, S., and Jordan, D. (2009).

Activenotes: computer-assisted creation of patient

progress notes. In CHI’09 Extended Abstracts on

Human Factors in Computing Systems, pages 3323–

3328. ACM.

Wilcox, L., Morris, D., Tan, D., and Gatewood, J. (2010).

Designing patient-centric information displays for

hospitals. In Proceedings of the SIGCHI Confer-

ence on Human Factors in Computing Systems, pages

2123–2132. ACM.

Wu, S.-W., Cheng, P.-H., Chiang, W.-C., Lin, J.-K., and

Lai, J.-S. (2011). Categorized level management agent

with forest-based data structures for accessing per-

sonal health records. In IEEE Region 10 Conference

TENCON, pages 1207–1211. IEEE.

Zhou, X., Ackerman, M. S., and Zheng, K. (2010). Doctors

and psychosocial information: records and reuse in

inpatient care. In Proceedings of the SIGCHI Confer-

ence on Human Factors in Computing Systems, pages

1767–1776. ACM.

Accessing and Sharing Electronic Personal Health Data

189