J Med Syst (2013) 37:9990 DOI 10.1007/s10916-013-9990-z

ORIGINAL PAPER

Free Web-based Personal Health Records: An Analysis of Functionality José Luis Fernández-Alemán & Carlos Luis Seva-Llor & Ambrosio Toval & Sofia Ouhbi & Luis Fernández-Luque

Received: 29 July 2013 / Accepted: 8 October 2013 / Published online: 13 November 2013 # European Union 2013

Abstract This paper analyzes and assesses the functionality of free Web-based PHRs as regards health information, user actions and connection with other tools. A systematic literature review in Medline, ACM Digital Library, IEEE Digital Library and ScienceDirect was used to select 19 free Webbased PHRs from the 47 PHRs identified. The results show that none of the PHRs selected met 100 % of the 28 functions presented in this paper. Two free Web-based PHRs target a particular public. Around 90 % of the PHRs identified allow users throughout the world to create their own profiles without any geographical restrictions. Only half of the PHRs selected provide physicians with user actions. Few PHRs can connect with other tools. There was considerable variability in the types of data included in free Web-based PHRs. Functionality may have implications for PHR use and adoption, particularly as regards patients with chronic illnesses or disabilities. Support for standard medical document formats and protocols are required to enable data to be exchanged with other stakeholders in the health care domain. The results of our study may assist users in selecting the PHR that best fits their needs, since no significant connection exists between the number of functions of the PHRs identified and their popularity.

Keywords Personal Health Records . Review . Functionality . Patients J. L. Fernández-Alemán : C. L. Seva-Llor : A. Toval : S. Ouhbi Department of Informatics and Systems, Faculty of Computer Science, University of Murcia, Murcia, Spain L. Fernández-Luque Northern Research Institute, Tromsø, Norway J. L. Fernández-Alemán (*) Faculty of Computer Science, Campus de Espinardo – University of Murcia, 30080Espinardo, Murcia, Spain e-mail: [email protected]

Introduction Accurate medical information is critical for doctors and particularly for patients. Although patients in many countries are able to obtain copies of their official health records from their healthcare providers, the maintenance and the preservation of health information are often difficult tasks [1]. Not every patient can provide his/her doctor with his/her health history and nor do all physicians have enough time to collect their patients’ health information [2]. The lack of a robust health information infrastructure is clearly manifested when physicians need to deal with natural or other disasters that affect the public’s health, such as a hurricane, an avian flu pandemic, or a bioterrorism attack [3]. An attempt has been made to mitigate this problem through the adoption of electronic health records (EHRs) and personal health records (PHRs), which have been actively promoted by health care professionals. In EHRs, authorized clinicians in more than one health care organization can create and manage an individual’s health-related information, while PHRs are patient controlled tools which allow patients to access health data anytime and anywhere using a computer device. PHRs allow health activities to be tracked and supported throughout a patient’s entire life experience [4], and are not limited to a single organization or a single health care provider [5]. Healthcare organizations are increasingly using online PHRs to provide patients with access to their clinical information [6, 7], the estimated number of people in the USA with access to PHR systems being 70 million [8]. PHRs should provide a broad range of functions that are easy to use [8–10] and understand [11], with adaptive interfaces that allow for variations in computer literacy [12]. However, not all PHRs are endowed with the same functionality and applications. The aim of our paper is therefore to study the functionality of free Web-based PHRs. Of the various PHR support technologies available, we have focused our attention on Web-based PHR

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systems since they have certain benefits with regard to the use of the Internet [7]. Moreover, free PHRs can be used by anyone and are the easiest to access. The main contribution of this paper is the analysis, assessment and comparison of 19 free Web-based PHRs, which were identified through the use of a systematic literature review. In order to better understand the current state of the market as regards free Web-based PHRs, our study shows the features and functions they have, the degree of functional similarity among them and the extent to which their functionality and popularity vary. To the best of our knowledge, no previous studies have evaluated the connection between the number of functions of PHRs and their popularity. The capabilities and limitations of the PHRs studied have been used to establish challenges and future directions in emerging innovative research for PHRs, such as interaction with mobile devices and intelligent technology to recommend self-care activities and monitor users. The remainder of this paper is organized as follows. The “Background and significance” section provides an overview of related work and addresses the motivations behind this research. The “Methodology” section describes the protocol used in the systematic literature review employed for PHR selection and provides the comparative framework used to evaluate the free Web-based PHRs selected. The “Results” section presents the evaluation of 19 free Web-based PHRs, based on 28 functions analyzed concerning health information, user actions and connection with other tools. In the “Discussion” section the article analyzes the characteristics found in the free Web-based PHRs selected, compares them with other studies, and explores the limitations of the present study. This section also identifies needs and trends in PHR system functionality. Finally, the “Conclusions” section outlines some concluding remarks and discusses future work.

Background and significance PHRs have undergone an important growth over the last few years. While a list of 27 publicly available PHRs were identified in 2000 [13], there are currently more than 200 PHR products in the marketplace [14, 15]. The American Health Information Management Association (AHIMA) maintains a Web site called MyPhr that which provides information on around 80 PHR products [16]. The most highly recognized types of PHRs in ISO’s “selfcontained” EHR category are Web-based and USB-based PHRs [2]. Most Web-based PHRs are free to consumers, while the objective of paid versions is principally to offer special formats, such as CDs, flash drives, bracelets, or wallet cards [14]. Providing a free service for patients has been recognized as a key success factor for PHR adoption [17]. Nevertheless, several surveys have reported that there are

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other factors which account for the disparities in the use of PHR: age [18–20], gender [21], income [22], educational background [12, 19], baseline Internet access [12, 18, 19, 23], and race [12]. When a PHR is connected with an EHR system or another institutional database, offering patients access to parts of their electronic health records, it is termed as a tethered PHR. In contrast, a PHR which does not link to healthcare providers and requires that individuals directly enter their health data into the PHR, is termed as an untethered PHR. According to a study of 117 PHRs [14], 54 % of PHRs are freestanding products (non-tethered) and 11 % provide both standalone and integrated versions. This study found that the majority of PHRs operate on a web-based platform, and fewer than half are available for use with mobile devices. Nevertheless, the most comprehensive PHRs are linked to the user’s official medical health records, with information entered by both clinician and patient [24]. A promising approach with which to implement tethered PHRs is the use of the CCR/CCD standards [15]. It is likely that the pervasive adoption and use of PHRs will increase when consumers seek access to their health records by using tethered PHRs across the medical care spectrum. Note that one of the most successful examples of a PHR implementation project is Kaiser Permanente’s HealthConnect [25, 26], with an impressive rate of adoption of 28 %. This PHR is built upon a high-quality, care-related integrated information system. PHRs developed as extensions of EHRs within particular health systems have higher rates of endorsement than standalone PHRs that do not automatically provide consumers with access to health data [27]. As demonstrated by the lessons learned in Google Health, the mere availability of an application to store data is not a sufficient condition to ensure widespread adoption [28]. An exhaustive analysis conducted by the Center for Information Technology Leadership (CITL) in 2008 found that the benefits and value of PHRs would appear to be allied with the types of functions they supported [29]. The features of PHRs have a direct impact on users and providers. For example, PHRs can provide a means of patient-physician communication and the issuing of repeat prescriptions online, without the necessity of visiting the care office or telephone contacts [30]. Avoiding repetitive processes reduces clinics’ workload volume and gives staff members more time to concentrate on serving patients [31], while patients save time and money. Many other benefits can be found in the use of PHRs [32]: they reduce the risk of medical errors [33], improve patient safety [34], prevent the unnecessary repetition of medical tests and procedures [3], facilitate continuity of care [35], promote collaborative tracking [36], improve patient-physician communication [37, 38], provide asynchronous communication [3], improve information transfers and hospital efficiency [39], support prevention

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campaigns [40], and contain the rising pharmaceutical bill and chronic disease management costs [3]. According to several studies [20, 27, 41], the most popular functions of PHR systems are access to laboratory and radiology results, patient-provider clinical messaging and the issuing of repeat prescriptions. The functionality of the PHR systems are important determinants of uptake and use [2, 42]. To date, few studies have been conducted to examine the functionality of PHRs. Sunyaev et al. [43] identified a list of 25 features that are necessary for a successful PHR implementation. These features were grouped into patient information (5 features), personal control (3 features) and additional services (17 features). The application of this evaluation framework was illustrated by comparing two PHRs: Microsoft HealthVault and Google Health. These authors found functionality gaps in both PHR providers. The functions of full-profile search, secure messaging, quality comparisons of clinicians and institutions and presenting information in different languages were not included in the PHRs studied. Al-Ubaydli [44] presented a how-to guide to the use of PHRs from a clinicians’ perspective. This author briefly describes the main functions of Microsoft HealthVault and Google Health. In 2002, Matthew and Kevin [45] presented a research paper concerning an evaluation of the functionality and utility of 11 Web-based PHRs. These authors found that the incomplete functionality and the data entry, validation, and information display methods used by PHRs limited their ability to serve as adequate representations of medical information. Maloney and Wright [2] carried out an analysis of the features and functionality of 13 commercially available USB-based PHRs. The USB based PHRs analyzed appeared to have important deficiencies. No PHR had all eight features analyzed (export and import data, images, summary print out, emergency entry, teaching material available, username and password, Mac-compatible), and only two of the devices contained seven of the eight features. The functionality, privacy, and security of the devices were variable and rarely complete. A total of 58 features grouped in six domains (Structured Data, Document Formats, Data Protection and Security, Services, Interface and Interfaces/Data Exchange) of 48 WebBased PHRs were analyzed through the use of publicly available information, the exploratory use of test accounts and the usage of a questionnaire sent to the vendors [46]. The results of the study showed that PHRs only implemented basic features, with a limited use of existing medical standards for the storage and communication of their data. However, the authors did not include data regarding the specific PHRs used in the survey. An evaluation of features and functionality of standalone mobile PHRs for iOS, BlackBerry, and Android was recently performed [47]. The product characteristics, data elements

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contained in the PHR, application technical features, and marketing tactics of nineteen mobile PHR applications were analyzed. None of the mobile PHRs included all the attributes evaluated.

Methodology Systematic review and protocol The search for free Web-based PHRs performed in this research has been addressed through the use of an SLR (Systematic Literature Review) which used formal methods to ensure that the search and retrieval process was accurate and impartial. The quality reporting guidelines set out by the Preferred Reporting Items for Systematic reviews and MetaAnalysis (PRISMA) group [48] are followed in this paper. The objective of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. Before beginning the search for literature and the data extraction, a review protocol was developed in which each step of the systematic review was described, including eligibility criteria. Eligibility criteria and sources Two inclusion criteria (IC) were used: PHRs with Web-based format (IC1) and free PHRs (IC2). The following sources were selected to perform the SLR: Medline, ACM Digital Library, IEEE Digital Library and ScienceDirect. The myPHR Website was also an information source for our research. This Website contains information related to the use and the construction of PHRs, and was created by the American Health Information Management Association (AHIMA) to help individuals become better managers of their personal health information. PHRs selection The PHR selection was organized as follows. First, the following search string: (PHR or “PHR providers” or “PHR Website”) was used to search for publications in electronic databases related to health and computer science. The articles selected were then explored in order to discover the names of Web-based PHRs. A search for PHRs in the myPHR Website was also performed to identify additional tools. Eligibility criteria IC1 and IC2 were applied to the PHRs found. Finally, an exploration of each of the PHR Websites selected took place in order to identify and analyze their functionality. The above activities were carried out independently by two authors. Any discrepancies were resolved by the rest of the team. A total of 19 PHRs were selected from 47 PHRs found in our search. Some PHRs were discarded since they

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did not meet criteria IC1 and IC2. Figure 1 shows the PHR selection process. Data collection process There is little consensus as to what information should be included in a typical PHR. The categories and functions were chosen by conducting a preliminary evaluation of the PHRs and identifying common elements that could form the basis for a comparison. This analysis was supplemented by a review of recommendations of the American Medical Informatics Association’s College of Medical Informatics [49, 50] and other research papers [2, 3, 45, 47, 51, 52]. A template was designed with the data that should be extracted. Each PHR was assessed by two authors of this paper in order to explore their functionality as regards information collection, information sharing and exchange, and information self-management [8]. The Cohen’s Kappa coefficient was used to calculate the interrater agreement between the two researchers in their evaluation. The Kappa coefficient was 0.91 which, according to Landis and Koch [53], indicates an almost perfect agreement between the two assessments. PHR characteristics A list of six characteristics were extracted and evaluated from the free Web-based PHRs selected: target audience, languages in which the PHRs are provided, geographical limitations, authentication methods, health advice and alarm systems. The target audience was evaluated because some PHRs provide their services for a certain kind of public, e.g. the military or diabetics. The number of languages supported by the PHR reflects international access to the PHR Website.

Geographical limitation was evaluated because some PHRs provide their services only in a specific geographical area, e.g. the USA. The authentication method is an important characteristic as it reflects the level of security provided by the PHR. This could be via the popular authentication method login/ password or a two-factor authentication which requires the use of at least two of the following authentication factors: something the user knows, something the user has, and something the user is. Health advice brings added value to the PHR as it could help the user to improve his/her way of life. Finally, the alarm system is a characteristic which can be used by different functions. For example, it reminds users of their appointments with doctors or medication time, or notifies them in the case of non compatibility between pharmacological treatments. We found that users can enter their personal contact information in any PHR. This information typically includes a current home address, phone number, and e-mail address. Functional categorization The data elements included in the PHR were identified and analyzed. The data collected were tabulated to show three data categories: health information, user actions and connection with. The “Health information” category has 11 functions: allergies, diabetes information/glucose level, blood pressure, blood group, weight, height, immunizations, medication, family history, social history (e.g. smoking status, alcohol history) and emergency contact. The “User actions” category includes 11 functions: information sharing, import information, export information, add, modify, remove, and grant access. These last four actions were evaluated for both patient and physician. The “Connection with” category contains 6 functions:

Fig. 1 PRISMA Flow Diagram PHRs identified through database searching

Additional PHRs identified through myPHR Website

PHRs after duplicates removed (n=47)

PHRs assessed for eligibility 1 (n=45)

PHRs excluded, not met IC1 (n=2)

PHRs assessed for eligibility 2 (n=19)

PHRs excluded, not met IC2 (n=26)

PHRs included in quantitative synthesis (n=19)

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healthcare providers (i.e. EHR systems), health devices, other PHRs, third-party applications, social networks, and laboratories that may be connected with PHRs.

Results Table 1 presents the characteristics of the PHRs selected. All of them provide password-protected access to their Websites. One PHR targets patients that have diabetes and another PHR restricts its services to veterans and their relatives. Three Websites propose their services in another language than English, which is Spanish, and only two PHRs have geographical restrictions for adhesion. 68 % and 63 % of the free Websites selected provide patients with health advice and alarm system functionality, respectively. Functionality was highly variable within and between the different PHRs. Only tw o PHRs, Dr. I-N et and myHealthFolders, contained all the health information functions included in our evaluation (Table 2). None of the PHRs incorporated all the user action (Table 3) and connection (Table 4) functions identified in our template. Most of the PHRs allow patients to enter their allergy information (89 %) and offer users the possibility of storing medication lists (94 %). The high coverage of these data elements by free Web-based PHRs makes them a de-facto common feature of a typical PHR. In contrast, the least covered data elements among free Web-based PHRs were connection with other health devices (11 %) and with laboratories (5 %), thus making these functions a differentiating characteristic. Classification summary Figure 2 presents the classification result of the PHRs selected based on the total score of the quality evaluation (QE). The QE score was obtained by adding one point for each function that was satisfied by the free Web-based PHRs. Microsoft Health Vault comes first in the PHR ranking as it provides the user with 82 % of the functions assessed. HealthyCircles and my MediConnect offer the user 79 % of the functions evaluated. 42 % of the Websites meet less than the half of the 28 function requirements presented in this paper. My HealtheVet and dLife come last in the ranking of the PHRs with 9 and 8 functions, respectively.

Discussion PHR characteristics Only one of the PHRs targets a specific disease: diabetes. This is one of the chronic diseases that cause a high number of deaths every year. According to the World Health Organization (WHO)

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[73], 346 million people worldwide had diabetes in 2012, and an estimated 3.4 million people died as a result of high blood sugar [74] in 2010. A higher adoption rate of PHRs focused on a specific patient disease is to be expected in coming years since people with disabilities and chronic conditions, and caregivers for the elderly, tend to be those most interested in PHRs [24, 50, 75]. The number of people aged 60 and over is expected to increase from 605 million to 2 billion between 2000 and 2050 [76]. The elderly population will therefore be a potential market for PHRs, but accessibility and usability issues must be addressed. Moreover, the multiple comorbidities in older adults require a holistic approach towards health and wellness. All of the free Web-based PHRs reviewed support the English language. It is not surprising to find that Spanish is the second language proposed by three PHRs since Spanish is the third most widely-spoken language in the world, after English and Mandarin, and is the official language in twentyone countries. Supporting new languages from overpopulated countries in emerging economies, specifically China, will provide great opportunities and expectations for higher user adoption rates. According to a recent survey conducted in 12 countries [77], 31 % of health care consumers in China maintain a PHR as opposed to 11 % in the USA or 5 % in the UK. The best PHR according to our ranking in Fig. 2 restricts adhesion to citizens in only the USA, Canada, the UK and Germany. Microsoft expects to extend access to its current UK-based HealthVault service to users throughout Europe, once the unique regulatory and privacy needs of each country have been defined. My HealtheVet also restricts its services solely to USA veterans, their relatives and caregivers, since this PHR only targets the US military community. The authentication method proposed by all of the PHRs selected was login/password which is the least expensive authentication method to use but is very weak and susceptible to attacks. Data security and privacy are major concerns for PHRs [78, 79]. While most PHRs can be password protected, a second authentication method (e.g. out-of-band authentication or challenge response) could be used to enhance their security. Strong authentication could be achieved by means of digital certificates on smart cards and USB tokens, thus requiring users to carry hardware with them wherever they go. The users of Microsoft’s HealthVault can log in to their PHR accounts via their OpenID accounts, many of which offer a second authentication factor through the use of physical USB keys. More sophisticated methods such as biometric factors specific to the user involve high deployment costs and additional hardware costs [80]. In line with other studies [2, 46] that have examined the provision of additional medical information on health related topics, two thirds of the PHRs analyzed provide their users with advice. A PHR can include information on healthy lifestyles concerning diet, exercise, smoking, weight loss,

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Table 1 PHR characteristics PHR

Target audience

Languages

Geographical limitation Authentication

Health advise

Alarm system

dLife [54] Dr. I-Net [55] EMRySTICK [56] HealthCompanion [57]

Diabetics Anyone Anyone Anyone

English English English English, Spanish

No No No No

login/password login/password login/password login/password

Yes Yes Yes Yes

No No No Yes

HealthyCircles [58] Juniper Health [59] MedsFile.com [60] Microsoft Health Vault [61] My Doclopedia PHR [62] My HealtheVet [63]

Anyone Anyone Anyone Anyone

English English English English, Spanish

login/password login/password login/password login/password OpenID account login/password login/password

Yes Yes No Yes

Yes Yes No Yes

English English

No No No USA, Canada, UK, Germany No USA

No Yes

Yes Yes

English English English English English English English, Spanish English

No No No No No No No No

login/password login/password login/password login/password login/password login/password login/password login/password

Yes Yes No No Yes Yes No Yes

Yes Yes No No Yes Yes Yes Yes

English

No

login/password

No

No

Anyone Veterans, active duty Service members myHealthFolders [64] Anyone myMediConnect [65] Anyone NoMoreClipBoard [66] Anyone PatientPower [67] Anyone PatientsLikeMe [68] Anyone RememberItNow! [69] Anyone Telemedical.com [70] Anyone WebMD Health Manager Anyone [71] ZebraHealth [72] Anyone

and working habits [50]. These PHRs mainly differ as regards how this information is presented to the user [46]. Several studies reported changes in patients’ health situations as the result of a change in behavior (exercise, diet, and habits related to stress) after using a PHR [81–83]. The main concern regarding health advice in a PHR is usability [82, 83]. Lifestyle advice should be provided using data obtained in an easy and user-friendly manner. Health information Allergies, diabetes and blood pressure are the most well known chronic diseases. 84 % of the PHRs store information about allergies, and around half of the PHRs selected store information about diabetes and blood pressure. Allergy data is very well supported by most PHRs, which confirms findings from previous studies [2, 46]. In contrast, more free web based PHRs should support diabetes and blood pressure information since these two diseases are the direct or indirect cause of death for millions of people throughout the world. These functions, in addition to information concerning blood group, immunizations and medications, could be very useful for physicians in emergency situations. In this kind of situations, only 68 % of the PHRs selected provide the

user with emergency contact. This data contrasts with previous studies in which 58 % of 11 web based PHRs [45], 71 % of 48 web based PHRs [46], 52 % of 19 mobile PHRs [47] and 92 % of 13 USB-based PHRs [2] included an emergency entry. This is an important feature which permits the appropriate healthcare professionals (previously authorized by the user) to access users’ data. Patients with chronic illnesses or disabilities [75] are particularly interested in an emergency entry. Some PHRs, such as Microsoft HealthVault, allow users to select what information will be shared and with whom in the case of an emergency. In other PHRs, emergency login information is printed on a card, a bracelet or necklace, or gained via phone or fax. Nevertheless, emergency access increases the risk of data breaches. Some national laws assume implicit patient consent in an emergency situation [84] which does not guarantee the privacy of patients’ data. The majority of the PHRs selected (79 %) provide users with the possibility of entering their family health history. There is variability among previous findings, in which 67 % of the 48 web based PHRs [46], 47 % of the 19 mobile PHRs [47], and 69 % of the 13 USB-based PHRs [2] included family history. This is an important risk factor for both common chronic diseases and genetic disorders. Recognizing patterns of familial disease can

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Table 2 Health information functions PHR

Allergies Diabetes Blood Blood pressure group

Weight Height ImmuMedication Family nizations history

Social history

Emergency Total % contact

dLife Dr. I-Net EMRySTICK HealthCompanion

N Y Y Y

Y Y N Y

N Y N Y

N Y Y N

N Y N Y

N Y N Y

N Y Y Y

Y Y Y Y

N Y N Y

N Y N Y

N Y N N

2 11 4 9

18 % 100 % 36 % 82 %

HealthyCircles Juniper Health MedsFile.com Microsoft Health Vault My Doclopedia PHR My HealtheVet myHealthFolders myMediConnect NoMoreClipBoard PatientPower PatientsLikeMe RememberItNow! Telemedical.com WebMD Health Manager ZebraHealth Total %

Y Y Y Y

N Y N Y

Y Y N Y

Y Y Y N

Y Y Y Y

Y N Y Y

Y N Y Y

Y Y Y Y

Y Y Y Y

Y Y N N

Y N Y Y

10 8 8 9

91 73 73 82

Y

Y

N

N

N

N

N

Y

Y

Y

N

5

45 %

Y Y Y Y Y N Y Y Y

N Y Y N N N Y Y N

N Y Y N N Y Y N N

Y Y Y Y Y N Y N Y

N Y Y Y N Y Y Y N

N Y Y Y N N Y Y N

Y Y N Y N N N Y Y

Y Y Y Y Y N Y Y Y

Y Y Y Y Y N Y Y N

N Y Y Y N Y N Y N

Y Y Y Y Y N Y Y Y

6 11 10 9 5 3 9 9 5

55 % 100 % 91 % 82 % 45 % 27 % 82 % 82 % 45 %

Y 17 89 %

N 10 53 %

N 9 47 %

Y 13 68 %

Y 13 68 %

Y 11 58 %

Y 12 63 %

Y 18 94 %

Y 15 79 %

N 10 53 %

Y 13 68 %

8 -

73 % -

help to identify preventive interventions, including genetic testing technologies [85]. Hospitals do not normally have a history of sharing information which encompasses all family members, so this function is a significant contribution to the patient’s continuity of care. Nevertheless, a good agreement among family members must be assumed in order not to contradict the confidentiality of personal health information [86]. Around half the PHRs provide users with the possibility of storing their social history. The provision of this function is lower still in other PHR formats, since only 5 % of the 19 mobile PHRs [47], and 23 % of the 13 USB-based PHRs [2] incorporate social history. This area should be improved as social history, like smoking or drinking habits, is a critical issue that helps doctors to provide a diagnosis [87]. This information could also be exploited by the PHR to present users with personalized health advice. User actions PHR interoperability is a significant challenge as regards achieving the exchange of clinical data. Around half the PHRs

% % % %

allow users to export data (53 %) and share their information (47 %), as opposed to 42 % of the 19 mobile PHRs [47], and 46 % of the 13 USB-based PHRs [2]. The percentage of PHRs that allow users to import data is the same as that of the 19 mobile PHRs (26 %) [47], and slightly less than 38 % of the 13 USB-based PHRs [2]. Different formats are chosen to extract or import data: proprietary binary format, proprietary XML format, PDF, txt, Continuity of Care Document (CCD) [88] and Continuity of Care Record (CCR) [89] format. PHRs should export data to and import data from other systems in a standardized manner [3], and a broad agreement on standard data formats is therefore required [90]. Two proposals whose intention is to foster the interoperability of clinical data and support the continuity of care are the CCD and the CCR. However, these standards were implemented in only a few PHRs. This weak penetration contributes to the theory that most providers avoid the implementation of medical standards in their PHRs owing to complexity [46]. All the PHRs selected give patients the right to modify, add and remove information, but only half of them provide physicians with these functions. We believe that this

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Table 3 User actions functions User

Patient

Physician

PHR

Share data

Import data

Export data

Add

Modify Remove Grant access

Add

Modify Remove Grant access

dLife

Y

N

Y

Y

Y

Y

N

N

N

N

N

5

45 %

Dr. I-Net EMRySTICK HealthCompanion HealthyCircles Juniper Health MedsFile.com Microsoft Health Vault My Doclopedia PHR My HealtheVet myHealthFolders myMediConnect

Y Y Y Y N Y N

Y Y Y N N Y N

Y Y Y Y N Y N

Y Y Y Y Y Y Y

Y Y Y Y Y Y Y

Y Y Y Y Y Y Y

Y N N Y N N Y

N N N Y N N Y

N N N Y N N Y

N N N Y N N Y

Y N N N N N Y

8 6 6 9 3 6 8

73 55 55 82 27 55 73

% % % % % % %

N N N N

N N N N

Y N N N

Y Y Y Y

Y Y Y Y

Y Y Y Y

Y N Y Y

Y N Y Y

Y N Y Y

Y N Y Y

Y N Y Y

9 3 8 8

82 27 73 73

% % % %

N N Y N Y N

N Y N N N N

Y Y N N N Y

Y Y Y Y Y Y

Y Y Y Y Y Y

Y Y Y Y Y Y

Y N Y Y Y Y

Y N Y Y Y Y

Y N Y Y Y Y

Y N Y Y Y Y

Y N Y Y Y Y

9 5 9 8 9 9

82 45 82 73 82 82

% % % % % %

Y 9 47 %

N 5 26 %

N 10 53 %

Y Y 19 19 100 % 100 %

Y 19 100 %

N 11 58 %

N N 10 10 53 % 53 %

N 10 53 %

N 10 53 %

4 -

36 % -

NoMoreClipBoard PatientPower PatientsLikeMe RememberItNow! Telemedical.com WebMD Health Manager ZebraHealth Total %

aspect should be improved. Knowing that patients are reviewing their diagnoses and medications may act as a stimulus for the clinicians to maintain accurate information [91]. Nevertheless, some physicians have expressed their concerns that the information stored in PHRs might be incomplete, out of date or less accurate if patients do not know what exactly is included [23, 92]. Some PHRs such as Microsoft’s Health Vault even allow the patient to alter professionally sourced information [93]. The root of this problem resides in low health literacy [94, 95]. Some studies provide insights into this problem by evaluating the accuracy of the information provided by patients [96, 97] and developing a classification scheme of comprehension errors [98]. Another related concern is the amounts of irrelevant information that a patient may send to a doctor. Overwhelmed clinicians cannot deal with critical health information. This issue could be addressed by flagging the information provided by patients as included or altered, and using a standard to specify what data can be collected and exchanged among different PHR systems and between PHR and EHR systems.

Total %

Connection with other tools The inability to share information across organizations is one of the main barriers to PHR adoption by patients [99]. A few PHRs are connected with EHR systems (32 %) and other PHRs (26 %). Connection with health devices (only 11 %) is an emerging field that needs to be further explored by developers in the future. Health devices such as blood glucose monitors, blood pressure monitors, body weight monitoring and management systems can collect and manage a large quantity of data, thus supporting physicians in their decision-making processes. Connection with EHRs, PHRs and particularly health devices is rarely supported by the PHRs reviewed, principally owing to the lack of interoperability among these systems [100]. Standardized messaging structures (e.g., HL7) or medical vocabularies (e.g., SNOMED, ICD10) can push the tethering of PHRs with EHRs, PHRs, or consumer medical devices (e.g., import/export data from a Glucometer) [47]. Moreover, entities controlling EHRs (e.g., hospitals and practices) should commit to making data electronically available to patients, which continues to be an important barrier [90].

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Table 4 PHR connection with other tools PHR

EHRs Health Other PHRs devices

Third-party applications

Social networks

Laboratories Total %

dLife

N

N

N

N

N

1

17 %

Dr. I-Net EMRySTICK HealthCompanion HealthyCircles

Y N N N

N N N N

N N N HealthVault

N N N N

1 0 1 3

17 % 0% 17 % 50 %

Juniper Health MedsFile.com Microsoft Health Vault

N N Y

N N Y

N N Y

N N N Neighborhood Nurse, AMA Adult Tool, Midwest Heart Specialists. N N More than 100 applications

Facebook, Twitter, YouTube N N Facebook and LinkedIn LinkedIn, Facebook, Twitter, Google+

N N Y

1 0 6

17 % 0% 100 %

My Doclopedia PHR My HealtheVet myHealthFolders myMediConnect

N N N Y

N N N Y

N N N HealthVault

N N N N

0 0 0 4

0% 0% 0% 67 %

NoMoreClipBoard

Y

N

N

N

3

50 %

PatientPower PatientsLikeMe

N N

N N

My Medicare, HealthVault N N

N N N WellNess Tracker, eRadiology Room Pain Management with ReliefInsite N N

Facebook, Twitter N Facebook, Windows Live, Twitter N N N N

N N

0 1

0% 17 %

RememberItNow!

N

N

N

N

N

1

17 %

N

3

50 %

N N 1 5%

1 0 -

17 % 0% -% -

Telemedical.com

Y

N

HealthVault

Hill Physicians

N Twitter, Facebook, Wikipedia, YouTube, Flickr Facebook, Twitter, LinkedIn, Youtube N

WebMD Health Manager ZebraHealth Total %

Y N 6 32 %

N N 2 11 %

N N 5 26 %

N N 5 26 %

N N 7 37 %

authored by clinicians [98]. Only Microsoft Health Vault can be connected with laboratories. With the aim of keeping records in a PHR up to date, patient input may act as a conduit

At the present time, there is no consensus as to whether a PHR should be connected with an EHR, but it is expected that in the future most PHRs will provide access to documents

12

10

25

23 (82%) 22 (79%)22 (79%) 21 (75%) 20 (71%) 20 (71%) 19 (68%) 18 (64%)

20

14 (50%)

8

14 (50%)

14 (50%)

13 (46%)

6

12 12 (43%) (43%)

15

12 (43%) 10 (36%) 10 (36%) 9 (32%)

8 (29%) 10

4 5

2

9 8 6

10 9 3

10 8 4

9 9 3

9 9 3

11 8 1

11 8 0

9 8 1

9 6 1

5 9 1

8 6 0

5 9 0

3 9 1

8 3 1

0

4 6 0

5 5 0

6 3 0

2 5 1 0

Health Information

Fig. 2 PHR classification

8 4 0

User action

Connection with

Total score

9990, Page 10 of 16

for the transmission of medical data from laboratories to PHRs. According to previous studies, 68 % of the 19 mobile PHRs [47], 61 % of the 13 USB-based PHRs [2], 48 % of the 48 web based PHRs [46] and 81 % of the 11 web based PHRs [45] allow patients to enter information about laboratory tests. However, several important issues arise from this approach. On the one hand, laboratories must release test results only to authorized persons, which depends on local, state and national government laws and regulations [90]. On the other hand, the reliability of laboratory data entered by patients with a low health literacy is too questionable [3] to be considered as an important data element for clinical decision making. Note that 26 % of the PHRs selected can be linked to thirdparty applications. Mobile phones are a particularly attractive avenue for the delivery of health interventions owing to of their widespread adoption, ubiquity, and increasingly powerful technical capabilities. Five intervention strategies have been used in phone-based health interventions [101]: (1) tracking health information, (2) involving the healthcare team, (3) leveraging social influence, (4) increasing the accessibility to health information, and (5) utilizing entertainment. Moreover, a study carried out in 2006 found that individuals were within arms’ reach of their mobiles during an average of 58 % of the time [102]. In fact, individuals spend more time with their phones than they do with their partners or even at their workplace [103]. It would therefore be possible to drastically increase the number of care points, from clinics and patient homes, to nearly any place and whenever the patient needs support [104]. Many patients, and particularly those suffering from a chronic or rare disease [105], seek interaction with other patients to compare care experiences, therapies, and lessons learned [106]. This can be achieved with chat rooms, forums, email lists, subscriptions to electronic information or social networks. Around a third of the PHRs selected are connected with a social network. The use of social networking implies privacy and security issues, particularly as regards the sharing of information related to family members. Despite the loss of privacy, the patients/users of social networks can obtain support and information from their friends which could help them to confront their health condition. Data analyses Figure 3 presents a dendrogram (a tree of clusters) of the PHRs selected based on their functions. It shows how the PHRs are related to each other. Health information, user action and connection functions were used to form the PHR functions vectors. The proximity measure selected to quantify the distances between the PHRs was the squared Euclidean distance. Average Linkage (Between Groups) was selected [107] to compute the distance between clusters. This method is a

J Med Syst (2013) 37:9990

general agglomerative hierarchical clustering procedure, which begins with every PHR being a cluster in itself. At successive steps the algorithm produces a sequence of clustering schemes in a decreasing number of clusters. The clustering scheme produced in each step results from the previous one by merging the two closest PHR clusters into one. The algorithm ends with each PHR belonging to one single cluster. The percentage of common functions for each PHR cluster obtained is calculated and presented in Fig. 3, which indicates the level of similarity at which PHRs join a cluster. For example, there are 11 % of shared functions among all the PHRs (first cluster in the hierarchy). The optimum number of clusters was obtained by cutting the dendrogram at level of similarity 16, which is to say that a line is drawn at level 16 of the similarity, represented in the xaxis of the chart. The criteria used to choose this grouping were: (1) minimize variability within PHR clusters and (2) maximize variability between PHR clusters. All the stems that intersect this line indicate a group of PHRs, thus resulting in five clusters (C1-C5). For example, the PHRs included in C1 are MedsFile.com, ZebraHealth, My HealtheVet, PatientPowerEMRySTICK, HealthCompanion, Juniper Health and dLife. C2 and C5 are groups formed of a unique PHR which represent PHRs with a singular group of functions. They have no similarities with the other clusters at level 16. C1 is the most important cluster as it joins 8 PHRs. The Websites in C1 share the presence or absence of 14 functions (50 %): medication, patient actions (4 functions), physician actions (4 functions) and connection with other tools except social networks (5 functions). In C3, two PHRs have 21 functions in common (75 %): allergies, blood pressure, weight, height, medication, user actions (3 functions), patient actions (4 functions), doctor actions (4 functions) and connection with other tools except EHRs (5 functions). Finally, C4 contains 7 PHRs which have 14 common functions (50 %): allergies, weight, height, medication, family history, emergency contact, import data, patient actions (4 functions) and doctor actions except grant access (3 functions). Data from the Alexa [108] ranking was collected and compared with the PHRs functionality ranking from our study. Figure 4 shows the Alexa ranking against the QE ranking of the 19 free Web-based PHRs. The Alexa global rank is calculated using a combination of average daily visitors to the Website over the past 3 months. The Pearson’s correlation coefficient was used to calculate the correlation between each two rankings, obtaining r =0,10, which indicates a low degree of linear dependence between the variables [109]. We therefore conclude that no significant connection exists between the number of functions of the PHRs identified and their popularity.

J Med Syst (2013) 37:9990

Page 11 of 16, 9990 0

5

10

MedsFile.com 7 ZebraHealth 19 My HealtheVet 10 PatientPower 14

15

20

25

71%

92% 89%

50%

C1

EMRySTICK 3

39%

HealthCompanion 4

78%

Juniper Health 6

60%

dLife 1

C2

Dr. I-Net 2

C3

My Doclopedia PHR 9

75%

WebMD Health Manager 18

11%

myHealthFolders 11 RememberItNow! 16 NoMoreClipBoard 13

35%

89% 85%

75%

Telemedical.com 17 myMediConnect 12

64%

50%

C4

28%

Microsoft Health Vault 8 HealthyCircles 5 PatientsLikeMe 15

C5

Fig. 3 Dendrogram using average linkage (between groups)

Future direction In several recent surveys [18, 110], users have expressed an interest in potentially using Web-based PHRs. However, there is a gap between the interest in PHRs and their real usage. A key driving factor as regards adopting Web-based PHRs would appear to be the presence of a comprehensive, integrated EHR [24]. In the USA context, Blue Button [111] and Meaningful Use [112] could play an important role in addressing this issue. Blue Button is a USA government initiative to help individuals attain access to their own health information through PHRs. Data from Blue Button-enabled sites can be used to create portable medical histories with the aim of facilitating communication among health care providers, caregivers, and other related entities. In 2013, the Office of the National Coordinator for Health IT provided an implementation guide for data holders and third-party application developers to enable data parsing features and automated data exchange among Blue Button+compliant applications using structured data formats [113]. Meaningful Use is, meanwhile, a set of standards defined by the Centers for Medicare & Medicaid Services Incentive Programs, with the aim of promoting the spread of EHRs to improve health care in the USA. It is expected that patients will access self-management tools in 2016, during Stage 3 of Meaningful Use. The European Union eHealth Task Force has also released a report entitled

“Redesigning Health in Europe for 2020”, which provides a list of key recommendations on what should be done to ensure open access to healthcare data to increase the quality of life for European citizens. Another important concern is usability. According to the Technology Acceptance Model [114], perceived usefulness and perceived ease of use are instrumental in determining users’ intentions to adopt technology. However, few research papers have examined PHR usability issues [8]. Some usability barriers to PHR adoption have already been identified: difficulties in navigation [115, 116], medical language complexity [115, 117], difficulties in registration [9], error recovery [115], limited options for sharing data with clinicians [9, 27] and the amount of data available [27]. This last point is particularly important if we consider that Web-based PHRs contain a wealth of information which can be challenging to analyze. Techniques with which to summarize, filter, and present health information are currently being developed [118]. There are also research efforts to enable consumers and professionals to discover patterns of categorical events throughout multiple health records [119, 120]. The concept of an intelligent PHR has been proposed in order to improve PHRs’ capability and usability [121–123], while expert system technology, Web search technology, natural language generation technology, database trigger

9990, Page 12 of 16 Fig. 4 Comparison of functionality/Alexa rankings

J Med Syst (2013) 37:9990 20 15 10 5 0

Funconality ranking

technology, and signal processing technology are being introduced into the PHR domain to guide the search for disease information, recommend self-care activities and monitor user. Employers could be one of the markets for Web-based PHR in the future. A study conducted among 500 USA employers [124] found that 88 % of employers intended to invest in long-term solutions to keep employees healthy. Employer-sponsored PHRs can provide employees with information and action plans for health and wellness with the aim of helping employers meet their long-term objectives. Any employees’ health metrics that are analyzed must be previously de-identified to preserve the privacy of their personal health data. As equipment becomes increasingly portable and interactive, smartphones and tablets have emerged as a new potential platform for PHRs [47]. The technical capabilities of smartphones and tablets can provide patients with new functionalities and services. The fact that smartphones and tablets are so close at hand makes it possible to offer care points nearly anywhere and at any time [104]. PHRs can take advantage of all these capabilities to a greater or lesser extent. Smartphones are usually equipped with more than 10 sensors [125], hardware which can be used to collect the patient’s health data [126–128].

Limitations This study may have several limitations. The search string may not have included words that would have selected other relevant PHRs. Moreover, the relevant functions of the PHRs selected may have not been included in this study. These limitations could affect the construct and the conclusion validity of this study [129]. But as the data analysis was carried out by two researchers and reviewed by the remaining authors, the threat to conclusion validity has therefore been reduced. The threat to internal validity has been minimized as the Kappa coefficient was 0.91, which reflects a high agreement between the authors. The threat to the external validity of this

Alexa ranking

paper should be mitigated by carrying out another study on commercial Web-based PHRs.

Conclusions In 2002, the state-of-the art for PHRs could be characterized as beta releases [13]. In the light of our study, there are currently PHRs with a comprehensive set of means to enter structured data and many interesting services, particularly as regards information acquisition. The next steps involved in empowering patients might be to provide functions with explanatory texts that support users in entering data and how this information can be obtained [46]. One of the main concerns as regards facilitating widespread PHR adoption is support for standard medical document formats or protocols. The implementation of these standards is extremely important, since they enable the exchange of data with other stakeholders in the health care domain and provide a solid basis for the next generation of distributed health services [46]. In the future, when health data are portable and understandable, PHRs will probably not only survive but may even become an invaluable tool. The results of this study allow PHR users to select the PHR that best fits their needs. PHR designers may also use our findings and our selection of free Web-based PHRs as a benchmark. Our research may also help stakeholders to discover the features that exist in the current free Web-based PHRs. In future work, the authors intend to analyze the usability and internationalization issues of free Web-based PHRs. Acknowledgments This research is part of the PEGASO-PANGEA projects (TIN2009-13718-C02-02) financed by the Spanish Ministry of Science and Innovation (Spain), and the GEODAS-REQ project (TIN2012-37493-C03-02) financed by both the Spanish Ministry of Economy and Competitiveness and European FEDER funds. Conflict of Interest The authors declare that they have no conflict of interest.

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