Stimulation programs for pediatric drug research – do children really benefit?

Most drugs that are currently prescribed in pediatrics have not been tested in children. Pediatric drug studies are stimulated in the USA by the pediatric exclusivity provision under the Food and Drug Administration Modernization Act (FDAMA) that grants patent extensions when pediatric labeling is provided. We investigated the effectiveness of these programs in stimulating drug research in children, thereby increasing the evidence for safe and effective drug use in the pediatric population. All drugs granted pediatric exclusivity under the FDAMA were analyzed by studying the relevant summaries of medical and clinical pharmacology reviews of the pediatric studies or, if these were unavailable, the labeling information as provided by the manufacturer. A systematic search of the literature was performed to identify drug utilization patterns in children. From July 1998 to August 2006, 135 drug entities were granted pediatric exclusivity. Most frequent drug groups were anti-depressants and mood stabilizers, ACE inhibitors, lipid-lowering preparations, HIV antivirals, and non-steroidal anti-inflammatory and anti-rheumatic drugs. The distribution of the different drugs closely matched the distribution of these drugs over the adult market, and not the drug utilization by children.
Introduction
Most drugs prescribed in pediatrics have not been tested in children. A recent review demonstrates that up to 80% of prescriptions for children in hospital and in general practice are either unlicensed (without a license for children) or used off-label (outside the product license) [15]. Of commercially available drugs in Europe, only 35% are authorized for use in children [4]. Although there are reasons why children do not often participate in clinical trials, including ethical, scientific and commercial considerations [2, 25], it is considered unacceptable to treat children with drugs that have not been studied properly.
In 1997, the Food and Drug Administration (FDA) and the Congress introduced the Food and Drug Administration Modernization Act (FDAMA), and this was followed by the Best Pharmaceuticals for Children Act. Closely linked to this legislation is the Pediatric Rule (1998), which requires the industry to perform research in the pediatric population. In the European Union (EU), final legislation on this topic has been approved and will come into effect at the beginning of 2007.
In both continents, the measures taken to address the problems broadly follow the same pattern. The first incentive is aimed at new medicines and intended for products covered by a patent or a supplementary protection certificate (SPC). For these drugs, a 6-month extension of market exclusivity is granted if a pediatric study is performed. The second incentive has the objective of increasing the knowledge on drugs that are no longer patent protected. In order to obtain the data necessary to establish safety, quality and efficacy specifically in children, either funding for the studies (USA) or market exclusivity (a so-called Pediatric Use Marketing Authorization—PUMA) can be given. Central to the second incentive is that experts are involved in determining for which drugs the greatest medical need exists and in ensuring that these drugs will be given priority. In the USA, the FDA plays this central role, and in the EU, a Pediatric Committee will be established within the European Medicines Agency (EMEA) which will be given a similar role.
The EU Commission apparently follows the approach in the USA with regard to patent-protected drugs because, according to the EU Commission, “the pediatric exclusivity provision has been extremely successful in the USA in stimulating the development of medicinal products for pediatric use” [1].
At the brink of implementing new programs (EU) or decisions on continuation of existing programs (USA), we questioned what the influence of the pediatric exclusivity regulation has been on pediatric drug development. We evaluated the drugs that are granted pediatric exclusivity in the USA by studying research that has been performed as a consequence of the exclusivity provision, and by comparing the drugs granted pediatric exclusivity with medicines actually used by children.
Materials and methods
The drugs granted pediatric exclusivity since the introduction of the FDAMA in July 1998 until August 2006 were retrieved from the FDA website [17]. All drugs were classified into subgroups according to the Anatomical Therapeutical Classification (ATC) system of the European Pharmaceutical Marketing Research Association. The data submitted to the FDA that resulted in granting the exclusivity were examined. For each drug, the publicly available summaries of medical and clinical pharmacology reviews of the pediatric studies were scrutinized. These summaries contain information on the pediatric research performed to obtain pediatric exclusivity. If these summaries were unavailable, the labeling information of the drug with pediatric exclusivity was studied to retrieve information about the pediatric studies performed. Each drug label contains a pediatrics section stating whether the drug is tested in children and, if so, information on the performed studies is given [6, 17, 26]. Data were extracted about the type of study, number and age of participants, whether long-term follow-up (defined as >1 year with specific attention for long term effects on growth and development) was undertaken and whether the study led to a pediatric indication being included on the label. Participants were divided into pediatric age categories according to the International Conference on Harmonization (ICH) guidelines: neonates (birth–27 days), infants (28 days–23 months), children (2–11 years) and adolescents (12–18 years).
To obtain data about drug use in children, recently published surveys of drug prescribing in hospitals and general practice were reviewed by a systematic search of the literature on drugs used by children. Details on the literature search and selection criteria are provided in box 1. Drug use in adults was assessed by using the sales figures from public databases and publications thereof [7, 8]. The data were categorized according to the ATC system as mentioned above.
Literature search and selection strategy
Step 1: literature searches of the PubMed and Embase bibliographic databases for papers published in English between 1990 and July 2005 combining the following search terms (keywords and appropriate medical subject headings):
Child, preschool (or) child (or) infant (or) infant, newborn (or) adolescent (or) pediatric (or) paediatric (or) paediatrics.Pharmaceutical preparations (or) drugs, non-prescription (or) drugs, generic (or) drug, therapy (or) prescriptions, drug (or) medicine (or) medication.Drug utilization (or) pharmacoepidemiology (or) drug utilization review.
Step 2: the references contained in articles identified in step 1 were examined to identify further relevant studies.
Step 3: based on the titles and abstracts of the papers, we next identified and then located full-text copies of 35 potentially relevant studies for closer examination.
Step 4: selection of articles by two independent reviewers (I.B., R.S.), using the following selection criteria:
Study performed in the industrialized world, defined as in Europe, North America, Australia and New Zealand.Study population of children from 0 to at least 14 years, to include all age groups (neonates, infants, children and adolescents).Sufficient information in the paper about drug utilization to classify 90% of the drugs in an ATC drug groups.Avoidance of selection bias by exclusion of voluntary surveys.
Step 5: inclusion of nine papers meeting all selection criteria.
Results
Pediatric exclusivity provision
According to the FDA, 135 drugs (130 active moieties) were granted pediatric exclusivity from July 1998 to August 2006. Most frequent drug groups were central nervous system drugs (19%), such as anti-depressants and psycholeptics, cardiovascular drugs (16%), mainly ACE inhibitors and lipid-lowering preparations, systemic anti-infectives (12%), among which largely HIV antivirals, cytostatics (11%), and alimentary tract medication (12%), among which proton pump inhibitors and oral antihyperglycemic medication (Table 1).
Table 1Active moieties granted pediatric exclusivity according to ATC groupDrug categoryNumber of drugs (% of total)Most frequent drug classesNumber of drugsCentral nervous system24 (19%)Anti-depressants8Psychostimulants, agents used for ADHD and nootropics4Anti-epileptics3General anaesthetics3Anti-migraine preparations2Cardiovascular system21 (16%)ACE inhibitors, plain6HMG-CoA reductase inhibitors5Beta-blocking agents4Alimentary tract and metabolism16 (12%)Drugs for peptic ulcer and gastro-oesophageal reflux disease5Oral blood glucose lowering drugs4Anti-infectives for systemic use15 (12%)Direct acting antivirals10Antibacterials for systemic use4Antineoplastic and immunomodulating agents14 (11%)Other antineoplastic agents5Antimetabolites3Alkylating agents2Musculo-skeletal system7 (5%)Anti-inflammatory and anti-rheumatic products, non-steroids6Drugs affecting bone structure and mineralization1Respiratory system10 (8%)Antihistamines for systemic use4Drugs for obstructive airway disease3Decongestants and other nasal preparations for topical use2Sensory organs10 (8%)Antiglaucoma preparations and miotics4Decongestants and anti-allergics3Dermatologicals6 (5%)Corticosteroids, potent (group 3)3Genito-urinary system and sex-hormones3 (3%)Other urologicals, including antispasmodics2Blood and blood forming organs2 (2%)Anti-thrombotic agents1Systemic hormonal preparations1 (1%)Hypothalamic hormones1Parasitology1 (1%)Anti-malarials1Total130 (100%)
From 118 drugs (91%), information about studies performed in children to obtain pediatric exclusivity could be retrieved from the FDA summaries of medical and clinical pharmacology reviews (n = 61) of the pediatric studies or the prescribing information as provided by the manufacturer (n = 57). No information could be found on 12 of the drug entities, mainly including over the counter drugs. The product label of 13 drugs merely stated that safety and/or efficacy in the pediatric population had not been established. For the remaining 105 drugs, in total, 326 studies were performed for the approval of pediatric exclusivity. At least 40,075 pediatric patients participated in these 326 studies (the number of participants was not noted for 27 of these studies). In the majority of the applications, children over a wide age range were included. Information on the age of participants was not provided for 54 of the 326 studies. Children participated in 224 of the remaining 272 studies (82%), adolescents in 177 (65%), infants were included in 105 (39%) of the trials, and neonates in 38 trials (14%). Only 1 (0.4%) study included preterm infants. The objective of most (62%) of the 326 studies was to determine the safety and efficacy of a drug. Pharmacokinetics and/or pharmacodynamics were studied in 147 (45%) trials, efficacy-only in 13 (4%) and safety-only in 38 (12%). From the 299 studies in which information about the number of participants was given, on average 134 children participated per study. This varied from 8 children in a safety and efficacy study of a HIV antiviral in neonates, to 994 children participating in a safety database of an antibiotic. Long-term (>1 year) follow-up was either done or planned for 25 (21%) of the 118 drugs.
For 42% of the drugs granted pediatric exclusivity and for which information was available (50 out of 118), the information obtained from the pediatric studies led to an approved pediatric indication.
The 130 active moieties granted pediatric exclusivity were categorized according to the ATC system. The results are shown in Table 1.
Drug utilization by children and adults
The search strategy retrieved nine papers addressing drug utilization in children (Table 2). The data were summarized by calculating a weighted average for each drug category with weights proportional to the number of prescriptions (Table 3). Drugs most often used by children are respiratory drugs, anti-infectives for systemic use and dermatologicals.
Table 2Characteristics of included studies on pediatric drug utilizationAuthor (year)SettingPopulation sizeAge range (y)Number of prescriptionsNiclasen [14] (1995)Pharmacy dispensing records in-and outpatients1,7040–145,876Rokstad [21] (1997)Prescriptions of general practitionersa0–198,215Thrane [28] (1999)Pharmacoepidemiological prescription database outpatients48,0910–15154,189Schirmb [24] (2000)Pharmacy dispensing records outpatients15,0010–16373,925Lewis [12] (2001)Prescriptions pediatric outpatients12,6280–1633,140Pandolfini [16] (2002)Prescriptions general pediatric hospitals1,3250–144,265Schirm [23] (2003)Pharmacy dispensing records outpatients18,9430–1666,222Ufer [30] (2003)Pharmacy dispensing records outpatients357,7840–16644,817Sanz [22] (2004)Prescriptions outpatients by GPs and pediatricians12,2640–1427,486a Not statedb Not included in weighted average due to presentation of data in paper (percentage of children using a drug category).Table 3Drug utilization pattern in childrenDrug category% of prescriptionsFrequent used drug classesRespiratory system30 %Drugs for obstructive airway diseaseNasal preparationsCough and cold preparationsAntihistamines for systemic useGeneral anti-infectives, systemic28%Antibacterials for systemic useDermatologicals12%Antifungals for dermatological useEmollients and protectivesCorticosteroids, dermatological preparationsSensory organs7%OphtalmologicalsOtologicalsCentral nervous system4%Analgesics/ antipyreticsPsychostimulants, agents used for ADHD and nootropicsAnti-epilepticsHormones3%Corticosteroids, for systemic useBlood and blood forming organs3%Vitamin KAlimentary tract and metabolism2%Drugs for peptic ulcer and gastro-oesophageal reflux diseaseInsulins and analoguesMusculo-skeletal system2%Anti-inflammatory and anti-rheumatic products, non-steroidsGenito-urinary system and sex-hormones2%Hormonal contraceptives for systemic useCardiovascular system1%DiureticsOther<1%Total105% (exceeds 100% due to rounding)
The pattern of drug use in adults based on sales over the last 12 months to May 2005 (Table 4) shows that drugs used for central nervous system, cardiovascular, alimentary tract and metabolism disorders make up over 50% of the market.
Table 4Drug utilization patterns in adults, according to the drug sales in North America over the period May 2004–May 2005Drug categoryAdult prescriptionsCentral nervous system23%Cardiovascular system19%Alimentary tract and metabolism14%Respiratory system9%General anti-infectives, systemic8%Musculo-skeletal system6%Genito-urinary system and sex-hormones6%Other2%Antineoplastic and immunomodulating agents4%Dermatologicals3%Blood and blood forming organs3%Sensory organs2%Total100%
Discussion
The introduction of the pediatric exclusivity laws in the USA has led to pediatric drug trials for 135 drugs tested in the past eight years. Over 300 studies were performed with over 40,000 pediatric patients participating. Based on these data, the FDA claims “the pediatric exclusivity provision has done more to generate clinical studies and useful prescribing information for the pediatric population than any other regulatory or legislative process to date” [20]. The EU Commission and other policy makers see a rapid adaptation of similar legislation in Europe essential to boost pediatric drug research in the EU as soon as possible [1, 3, 19]. Although it is true that more pediatric studies have been done, we question the content of the research.
A major discrepancy is apparent between the drug prescription pattern in children and the drugs granted pediatric exclusivity. The majority of drugs granted pediatric exclusivity are rarely used by children, and drugs that are frequently used by children are underrepresented in the pediatric studies to obtain exclusivity. This difference is not accounted for by the licensing status of the used drugs. For instance, in general practice, 37% of the prescriptions of respiratory drugs are still used in an unlicensed or off-label manner [27]. This suggests that the pediatric studies did not address the real needs in pediatric drug development. Whilst the pediatric exclusivity scheme has stimulated pediatric research quantitatively, the nature of the scheme has led to priorities for the type of research that are largely driven by the adult market for medicines rather than by the needs of the pediatric population. An important built-in motive in the stimulation program for performing pediatric studies is the financial benefit gained from the exclusivity provision. The drugs granted pediatric exclusivity include 5 out of the “Top 10” prescription drugs with the highest sales figures in North America in 2005: atorvastatin (Lipitor), simvastatin (Zocor), omeprazole (Nexium), lansoprazol (Prevacid), and sertraline (Zoloft). Sales of these 5 drugs amounted to $24.1 billion US in 2005 [9]. Extension of the SPC on the basis of pediatric exclusivity has also been granted to other adult best-selling drugs, such as pravastatine, enalapril, metformin, amlodipine, paroxetine, fluoxetine, and rofecoxib (currently withdrawn). It is thus clear that the patent extension has an enormous financial benefit for the pharmaceutical companies, which easily outweighs the cost of the average pediatric trial [1]. This is not only the case for best-selling drugs but also for drugs with a smaller market share. A Tufts University report indicates that an estimated $35 million US in undiscounted profits per drug can be earned by obtaining pediatric exclusivity based on median 2004 sales for all pediatric exclusivity drugs after accounting for costs and market protection extensions [29]. Although the increased profit was intended by the legislator, we doubt if the other intention, which aimed at providing data to reduce the volume of drugs taken by children that are off-label or unlicensed, has also been met.
Our approach to define essential drugs for children by volume and by number of children that need a certain medicine is incomplete, as indications and severity of the conditions for which the drug is prescribed also play an important role [10]. Secondly, the method employed in our literature search may have introduced some bias toward outpatient drug consumption, thus underestimating the use of, for example, anesthetic or cardiovascular drugs. Clearly, hypertension or lipid disorders occur in children, and knowledge about these drugs in this population is important. However, these conditions are certainly not major causes of morbidity, and subsequent drug use in children and the research priorities lie elsewehere.
Furthermore, there are specific issues in pediatric clinical pharmacology that have remained unaddressed by the current product-related approach. First, the age distribution of the children participating in the trials does not reflect the actual medical needs. Drug use in children follows a pattern, with a relatively high percentage of children using a prescription drug in the first year of life [24] while the proportion of off-label and unlicensed drug use is highest (∼90%) in the vulnerable group of neonatal ICU patients [5]. These data are not reflected in the participation in the trials to obtain pediatric exclusivity, with neonates and infants being included in, respectively, 14 and 39% of the study groups. In fact, it is surprising to see that the majority of applications included children of a wide age range, thereby ignoring the delineation of age groups as defined in the ICH guidelines. This is problematic, as in the pediatric population significant age-related differences may exist in the pharmacokinetics and the effects of drugs [11]. Secondly, the effects of drugs (that are intended for chronic use) on development and maturation of children are largely unknown, but this issue has hardly been addressed. Third, off-label drugs are hardly or not studied. Only ten drugs in this category are under consideration for study by pharmaceutical companies (FDA website). From these ten drugs, six already have been refused by industry for studying, and have been referred to the National Institutes of Health to obtain the necessary information for rational use in pediatric populations. These clinical trials are at the moment awaiting funding [13, 18]. Surprisingly, in the same Tufts study that reports on a profit of $35 million US per drug granted exclusivity, it is also suggested that the current incentives for studying non-patent protected drugs are too low [29].
Finally, methodological research has remained underfunded by this approach. Any expansion of research will require specialized techniques that allow samples and data to be obtained in children with minimal discomfort and risk. For instance, most pharmacokinetic assays require an amount of blood that is too large for the average neonate, so highly sensitive assays need to be developed. Accurate assessment of drug effects on neuro-development and behavior also require further development, independently of studies with particular compounds.
The recently approved EU guidelines contain differences from the USA that may remedy some of the deficiencies indicated. It contains a section for the stimulation of off-patent drugs that can be granted a special label (PUMA), and data protection if data necessary to establish safety, quality and efficacy in children are submitted. The ‘Medicines Investigation for the Children of Europe’ program, funded by the EU, will be created to stimulate research of off-patent drugs. The proposed establishment of a Pediatric Committee, operating within the European Medicines Agency, will guard study of significant drugs for children and avoid unnecessary studies, provide free advice to industry, and stimulate long-term pharmacovigilance. It will also play a role in the implementation of the requirement for industry to submit data they already hold on use of their medicines in children. New drugs will not be granted Marketing Authorisation unless the need for pediatric research has been waived by the Pediatric Committee, or deferral of initiation or completion of an already approved Pediatric Investigation Plan has been agreed to by this committee. In addition, an EU network of investigators and trial centers will be formed [1]. Although elements of this network are now beginning to form, their funding is unclear and certainly not at the level provided to the patent holders by a patent extension. Also, it is not immediately clear why the EU measures will deliver, when this was not achieved with the formation of Pediatric Pharmacology Research Units and the oversight of research priorities by the FDA in the USA.
In conclusion, the schemes implemented in the US generated new knowledge and led to the rapid development of an infrastructure to carry out pediatric drug trials. Although these are certainly positive developments, we do believe that the findings of this survey warrant additional efforts to stimulate research on drugs used more frequently by children, and generally applicable methodological research, as at least the short-term effect of these initiatives seems to have drawn the focus of industry-sponsored research to the most profitable part of the market. The funding of the research we propose should not be problematic. The pediatric exclusivity schemes generate a flow of public money to the sponsoring drug companies because generic replacement and price reductions are postponed. There is no particular reason why these public funds could not be at least partly applied in an alternative manner.

pediatrics
patents
clinical trials
pharmaceutical preparations
licensure


Value of assessment of tricuspid annulus: real-time three-dimensional echocardiography and magnetic resonance imaging

Aim To detect the accuracy of real-time three-dimensional echocardiography (RT3DE) and two-dimensional echocardiography (2DE) for tricuspid annulus (TA) assessment compared with magnetic resonance imaging (MRI).
Introduction
Evaluation of tricuspid annulus (TA) continues to be a major problem in the surgical decision-making process due to its complex three-dimensional shape [1–3]. Accurate assessment of TA has many values in clinical application. For example, the decision of tricuspid valve repair may change due to discrepancy between pre-operative measurement of TA diameter (TAD) by two-dimensional transthoracic (or transesophageal) echocardiography (2DE) and direct surgical visualization [4]. Several studies described a strong correlation between TA motion and right ventricular (RV) function [5–8]. Analysis of TA velocity by tissue Doppler imaging has been found useful for RV functional assessment [9, 10]. In these studies, the assessment of TA motion relied on 2DE, M-mode and tissue Doppler recording. Since Real-time three-dimensional echocardiography (RT3DE) has become available for clinical practice, it is now possible to examine the TV more completely [11]. This study aimed to use RT3DE in evaluation of TA morphology, size and cyclic changes during the cardiac cycle. It also aimed to correlate TA function with RV function that was assessed by magnetic resonance imaging (MRI).
Subjects and methods
The study included 30 patients (mean age 34 ± 13 years, 60% were males) who were scheduled for routine MRI examination for evaluation of right ventricular function (10 patients with congenital heart disease, five with chronic pulmonary disease, five with multivalvular affection, and 10 normals). 2DE and RT3DE were performed at the same day of MRI examination after their informed consent for assessment of TA. The inclusion criteria for selection were good 2D image quality, sinus rhythm and mild to moderate tricuspid regurgitation.
MRI studies were performed with a 1.5 T MRI (General Electric, Milwaukee WI; Signa 1.5 T MRI) equipped with a four-element torso coil. A cardiac-triggered, steady-state, free-precession sequence (FIESTA; temporal resolution and repetition time of echo of 3.5 and 1.3 ms, respectively, flip angle of 45 degrees) was used for quantitative analysis. 10 cine short axis slices were acquired (slice thickness 10 mm, gap 0 mm) during a breath-hold period. Additional imaging parameters were a field of view of 320–380 mm and a matrix of 160 × 128. These series of high quality images encompassing the right ventricle (RV) produced a three-dimensional data set with sharp edge between the blood pool and myocardium. Quantitative analysis was performed using standardized software (MassPlus, Medis Inc., Leiden, NL). By this software, manual tracing was done for TA and RV endocardial border on all images (end-diastolic and end-systolic). The following measures were obtained at end-diastolic and end-systolic frame: (1) TA area (TAAMRI), (2) TADMRI, (3) RV volume, (4) RV ejection fraction (RV-EF) was calculated as (RV end-diastolic volume- RV end-systolic volume/RV end-diastolic volume) × 100%, (5) TA fractional shortening (TAFSMRI) defined as (end-diastolic TADMRI–end-systolic TADMRI)/end-diastolic TADMRI × 100% and (6) TA fractional area changes (TAFACMRI) defined as (end-diastolic TAAMRI–end-systolic TAAMRI)/end-diastolic TAAMRI × 100%.
2DE was done with a Sonos 7500 ultrasound system attached to a S3 transducer (Philips, Best, The Netherlands). The TV was imaged from apical 4-chamber view with the patient in the left lateral decubitus position. The following measures were obtained: (1) TAD2D was defined as the distance between the insertion sites of septal and anterior TV leaflets and obtained at an end-diastolic and end-systolic still frame and (2) TA fraction shortening (TAFS2D) defined as (end-diastolic TAD2D–end-systolic TAD2D)/end-diastolic TAD2D × 100%
RT3DE was done with the same ultrasound system attached to X4 matrix array transducer capable of providing real-time B-mode images. A full volume 3D data set was collected within approximately 5–10 s of breath holding in full volume mode from an apical window. The 3D data set was transferred for off-line analysis with TomTec software (Unterschleissheim, Munich, Germany). Data were stored digitally and subsequently evaluated by two blinded observers (AMA, OIIS). Data analysis of 3D images was based on a 2D approach relying on images obtained initially from the apical view. The TA was sliced between two narrow lines to exclude other tissues on the 2D image leading to clarification of annulus by a 3D image. TA was viewed and traced manually from the atrial aspect and once this is completed the surface area was automatically calculated and could be visualized from different points of views. Manual modification was made to correct any inconsistence. The following RT3DE variables were obtained from both an end-diastolic and end-systolic still frame: (1) TA area (TAA3D), and (2) TAD3D defined as the widest TAD (see Fig. 1), Subsequently, TAFS3D and TA fractional area changes (TAFAC3D) (%) were calculated by the same formula used in 2DE.
Fig. 1Tricuspid annulus oval shape as seen by graphic representation (A), real-time three-dimensional echocardiography (B), magnetic resonance imaging (C), and tricuspid annulus with 2 lines inside, the larger is the TAD by real-time three-dimensional echocardiography and the smaller is the TAD by two-dimensional echocardiography with large difference in measurements
Statistical analysis
All data obtained by MRI, 2DE and RT3DE are presented as mean ± SD. A paired t-test and was performed for comparing means of variables. The level of significance was set to P < 0.05. A SPSS statistical package was used (SPSS, version 12.1, SPSS Inc, Chicago). Pearson’s coefficient was used for correlation between RT3DE and MRI data. Interobserver agreement for RT3DE measurements was assessed according to the Bland and Altman principle [12].
Results
Acquisition of RT3DE data was performed in all patients in a reasonable time (approximately 1 min for acquisition and 5 min for data analysis). The TA was clearly delineated in all patients. An oval-shaped TA (not circular) was visualized by RT3DE and MRI (Fig. 1). TAD3D was obtained with very good interobserver agreement (mean difference −0.4 ± 1.5 mm, agreement −3.4–2.6). There was a good correlation between TADMRI and TAD3D (R = 0.75, P = 0.001), while TAD2D was fairly correlated with TAD3D and TADMRI (R = 0.5, P = 0.01 for both). There were no significant differences between RT3DE and MRI in TAD, TAA, TAFS, and TAFAC measurements, while TAD2D and TAFS2D were significantly underestimated (P < 0.001) (Table 1). TAFS2D was not correlated with RV-EF, while TAFS3D and TAFAC3D were fairly correlated with RV-EF (r = 0.49, P = 0.01, and r = 0.47, P = 0.02 respectively).
Table 1Comparison between measurements of TA size and function by 2DE, RT3DE and MRI2DERT3DEMRIEnd-diastolic TAD (mm)33.0 ± 8.5 43.2 ± 10.044.1 ± 9.2End-diastolic TAA (mm2)—-1835 ± 4251869 ± 392End-systolic TAD (mm)27.0 ± 7.832.0 ± 8.732.5 ± 8.2End-systolic TAA (mm2)—1120 ± 3071137 ± 288TAFS (%) 18.7 ± 4.026.3 ± 5.926.7 ± 5.7TAFAC (%)—39.3 ± 4.939.5 ± 4.7TAD: Tricuspid annular diameter, TAA: Tricuspid annular area, TAFS: Tricuspid annulus fractional shortening and TAFAC: tricuspid annular fractional area change
Discussion
In the present study, the morphological and functional aspects of TA were assessed by MRI and RT3DE. The main findings of our study are (1) TA shape was not circular but oval, (2) TAD measurement by RT3DE is more accurate than by 2DE, and (3) TA function was fairly correlated with RV function.
TAD measurements have an important role in the TV surgical decision-making process not only for the selection of patients undergoing surgery, but also the type of surgical technique (valve plication or ring placement) [13–15]. Although 2DE is helpful to assess TV function and to detect TR severity it has important limitations in describing TV morphological details, such as TAD [14, 15]. RT3DE may yield more detailed anatomical description of TA morphology and function [16, 17]. In the present study, the TA was visualized well in all subjects allowing even measurements of its area. This is in accordance with Schnabel et al. [11] who reported well or at least sufficient TA visualization in over 90% of patients. The measurements of TAD by RT3DE and MRI showed good correlation without significant difference between both techniques. When TAD2D measurements were compared with the TAD3D and TADMRI measurements, 2D measurements were significantly underestimated. Analysis of TA motion by M-mode, 2DE and tissue Doppler imaging has been studied as a feasible marker for RV function reflecting the longitudinal RV shortening and lengthening. All these analyses described the physiological behaviour of TA plane systolic motion towards the apex along the RV long axis [5–10]. The TA plane systolic displacement is not influenced by its complex structure and asymmetrical shape [18] In the present study TA circumferential and horizontal motion along the RV short axis was assessed by RT3DE. TA motion along the RV short axis, which was fairly correlated with RV function that was assessed by MRI as a standard method for assessing RV ejection fraction. Fair and not good correlation may be explained by the meridional motion of the muscles and other structures of the RV inflow region. Furthermore, the myocytes are disposed longitudinally in the inflow region and more sensitive to meridional stress [19]. Despite this fair correlation, the summation of TA motion along both RV long and short axes increases the accuracy and correlation values for estimation of RV function [20].
Study limitation
The main limitation of this study is that RT3DE images more critically depend on image quality than 2DE images and the value of RT3DE should be assessed in a more non-selected (image quality). Due to the high cost of MRI, a small number of patients were included.
Conclusions
RT3DE helps in accurate assessment of TA comparable to MRI, while 2DE could not be relied on due to underestimation. This may have important implications in the TV surgical decision-making processes. RT3DE analysis of TA function could be used as a marker of RV function.


What Is eHealth (4): A Scoping Exercise to Map the Field

Background Lack of consensus on the meaning of eHealth has led to uncertainty among academics, policymakers, providers and consumers. This project was commissioned in light of the rising profile of eHealth on the international policy agenda and the emerging UK National Programme for Information Technology (now called Connecting for Health) and related developments in the UK National Health Service.
Introduction
The application of information and communications technology (ICT) in health care has grown exponentially over the last 15 years and its potential to improve effectiveness and efficiency has been recognized by governments worldwide [1]. National strategies aimed at developing health information infrastructures and “infostructures” are emerging across North America, Australia, Europe and elsewhere [2-5]. These are united by a vision to improve the safety, quality and efficiency of patient care by enabling access to electronic health records and by supporting clinical practice, service management, research and policy though availability of appropriate evidence and data. In addition, these strategies emphasize the importance of standards and policies for ensuring interoperability and data security, and many incorporate a commitment to facilitate consumer empowerment and patient self-care through provision of electronic information and/or telemedicine facilities. In the United Kingdom, these principles are reflected in the National Information Strategy for Health and are being addressed via the UK National Programme for Information Technology (NPfIT, now called Connecting for Health) and related initiatives [6,7].
While such initiatives have been taking place, the focus of health care information technology (IT) has been changing, from an emphasis on hardware, systems architectures and databases, to innovative uses of technology for facilitating communication and decision making, coupled with a growing recognition of the importance of human and organizational factors. At the same time, Internet technologies have become increasingly pervasive. In parallel, the language of health care IT has been changing, and references to the concept of eHealth have proliferated in international health policy, management and research arenas. Despite the clear interest in and apparent marketability of eHealth, it was not evident, at the time this research was commissioned, what exactly was meant by the term. It had been variously used as a synonym for health informatics, telemedicine, consumer health informatics and e-business, as well as more specific technological applications, but no consensus existed on its conceptual scope and it was unclear whether it indeed represented a new concept, or simply a linguistic change. An international call for definitions of eHealth posted in 2001 failed to generate any published responses and the call was updated in June 2004, suggesting that this is still a grey area [8,9].
In view of these uncertainties, it was considered important by the UK National Health Service (NHS) Research and Development Programme to define eHealth and to assess its scope and value for the future of health care, in particular to synthesize the available evidence relating to its potential impact, likely trajectory, and implications for service development and organization. The current paper reports descriptive work to profile and define the field, which was conducted independently of, but complements, the systematic review of definitions of eHealth provided elsewhere in this volume [10]. This work produced a framework for locating evidence on the effectiveness, promise and challenges of eHealth, as well as recommendations for future research, which are reported elsewhere [11].
Potential areas of eHealth considered at the outset of the project are shown in Table 1. This was derived by group discussion among the research team, utilizing team members' a priori knowledge of topics and issues in medical informatics (drawing on backgrounds in health care research, practice, policy, and computing), key eHealth discussion papers, and the results of a preliminary Medline search suggesting that eHealth is closer to the emerging area of health informatics than to medical informatics as a whole. While it was established that eHealth is about the use of information technology to facilitate patient and citizen health care or service delivery, rather than technology per se, uncertainty remained about what specific topics or issues, among those shown, fall within the scope of, or have relevance to, the concept.
It was recognized that in order to fully explore the area, multiple sources of information would need to be examined. While identifying the scope of eHealth research was a crucial objective, the published research literature presents a filtered record of activity and thinking and, given the fast-moving pace of the field and its importance beyond academia, nonresearch sources are likely to yield rich information about the current status of eHealth and future trends. For this reason we conducted two parallel, large scale reviews—one focusing on the medical and related scientific literature and the other drawing on alternative sources available via the World Wide Web, including independent scoping exercises (of which there have been several), policy documents and technology reports. The results of these exercises were converged in order to derive a conceptual map and are considered together in this report.
Table 1
Potential eHealth areas and issues considered at the outset of the project
What
issues currently dominate eHealth?
What is going on in eHealth?
What emerging technologies are likely to impact on health care?
How does research inform eHealth?
How do developments in eHealth inform research?
Professional Clinical Informatics- Decision aids for practitioners (eg, prompts, reminders, care pathways, guidelines)- Clinical management tools (eg, electronic health records [EHRs/EPRs], audit tools)- Educational aids (guidelines, medical teaching)- Electronic clinical communications tools (eg, e-referral, e-booking, e-discharge correspondence, clinical email/second opinion, laboratory test requesting/results reporting, e-shared care)- Electronic networks (NHS-Net and disease-specific clinical networking systems)- Discipline/disease-specific tools (eg, diabetes informatics)- Telemedicine applications (for interprofessional communication, patient communication and remote consultation)- Subfields eg, nursing & primary care informatics)
Electronic Patient/Health Records (EPR, EHR)- Electronic medical records. Record linkage. The Universal Patient Indicator. Databases and population registers.- Achieving multiprofessional access. Technical and ethical issues.- Data protection/security issues- Patient access and control- Integration with other services (eg, social work, police)- Clinical coding issues (terminologies, etc) Healthcare Business Management- Billing and tracking systems- Audit & quality assessment systems
Consumer Health Informatics- Decision aids for patients facing difficult choices (eg, genetic screening)- Information on the web and/or digital TV (public information and educational tools for specific clinical groups)- Clinician-patient communication tools:1. Remote: Clinical email and web-based messaging systems for consultation, disease monitoring, service-oriented tasks (eg, appointment booking, prescription reordering).2. Proximal: Shared decision making tools, informed consent aids3. Mixed: On-line screening tools (eg, for depression) and therapeutic interventions (eg, cognitive behaviour therapy)- Access and equity issues (data protection issues, the Digital Divide)- Quality issues for health information on the net- “virtual” health communities
New Technologies- Satellite communications (eg, for remote medicine )- Wireless networks (eg, within hospitals, across geographical areas)- Palmtop technologies (for information, for records)- New mobile telephones- Digital TV (for disseminating health information & communicating with patients)- The WWW and it's applications for health (issues: quality control, confidentiality, access) NHS-Direct etc.- Virtual reality (eg, remote/transcontinental surgery)- Nanotechnology- Intersection of bioinformatics and health informatics.
Research Input- Development -Need for user involvement in product conception, design and testing. Iterative development. Needs assessment, accessibility and usability research. Multi-faceted expertise required.- Implementation – Understanding people and organizational factors eg, system acceptability, resistance to change etc. Use of tailored implementation strategies.- Innovative methods for mapping functional and technology needs eg, place of systems in the organization - Knowledge management, systems approaches, communication networks models, organizational development to map pathways.- EvaluationFormative, as above, also:Outcome assessment to establish impact of new systems on clinical outcomes, processes and costs. )
Research Outcomes- Potential of electronic databases such as population registers for epidemiological research.- Research into the impact or use of informatics tools suggests appropriate and cost-effective priorities for policymakers.- Areas of cross-over (eg, bioinformatics)
Methods
Assessing the Taxonomic Structure of Research Databases and the Presence of eHealth
In the formative stage of the project, we explored the subject taxonomies, or thesauri, of multiple databases of abstracts in order to identify high-level subject headings which could be used to profile the volume and content of the medical informatics literature and to construct searches for pertinent evidence. In the case of Medline the thesaurus containing a hierarchical controlled vocabulary is referred to as Medical Subject Headings, or MeSH (see below). As part of this we sought to assess whether eHealth was explicitly represented within these thesauri. A further objective was to determine the ontological structure of the databases in relation to medical informatics and eHealth and the implied relationships between alternative subfields.
The databases examined were Medline (PubMed), the Cumulative Index of Nursing and Allied Health Literature (CINAHL), the Science Citation Index (SCI), the Social Science Citation Index (SSCI), the Cochrane Library Database (including Dare, Central, NHS Economic Evaluation Database [NHS EED], Health Technology Assessment [HTA] database, NHS EED bibliographic) and Index to Scientific and Technical Proceedings (ISTP, now known as ISI proceedings), all of which predate the targeted search period.
Exploring the Composition of the Medical Informatics Literature Using the Existing MeSH Thesaurus
MeSH has been developed (and is constantly updated by) the US National Library of Medicine. It consists of sets of terms naming descriptors in a hierarchical structure that permits searching at various levels of specificity. At the most general level of the hierarchical structure are very broad headings such as Anatomy or Information Science. More specific headings are found at more narrow levels of the eleven-level hierarchy, such as Ankle or Medical Informatics. There are 22568 descriptors in MeSH.
Historical trends in the literature indexed by the individual Medline MeSH terms subsumed within the broad Medical Informatics category were assessed for the period 1987 to 2003, and part way through 2004. Individual MeSH definitions were examined to assess the range and nature of the topics covered and to clarify which are most clearly related to common conceptions of eHealth (eg, specific applications of information technology (IT) to health care versus technical issues). The number of publications in Medline was profiled by year, as was the type of publication, subject to the limitations of the Medline categorization scheme (Randomized Controlled Trial/Controlled Trial/Meta-analysis/Review). In addition, the MesH tree was compared with an expert-derived taxonomy from the International Medical Informatics Association (IMIA) in order to assess its coverage of key areas and its merits as a means of identifying appropriate literature.
Using eHealth as a Search Term
Applying eHealth as free-text search term to multiple databases offered a “grounded” method of defining the field, as represented in the research literature. In order to identify publications specificially relating to eHealth and to place the concept within the wider medical informatics literature, all the databases described previously were searched for the presence of the word eHealth or its variants in the title or abstract for the period January 1, 1997 to December 31, 2003 (search string: Ehealth OR e-health OR e*health). Results were organized to show the number of articles arising each year, the journals in which they appeared, and the range of topics covered.
Profiling the Literature From Wider Web-Based Sources
Mixed methods were used to (a) identify current commentary and analysis relating to the emergence, nature, scope and potential of eHealth, and (b) locate evidence and opinions on general trends in technology and technology adoption with direct or indirect relevance to eHealth now or in the future. Relevant terms (including e health, e-health, ehealth, healthcare information technology and healthcare computing) were applied, singly and in combinations, to the Google search engine, which indexes over 8 billion URLs and ranks results by relevance and link popularity. In addition, websites previously identified as being likely to contain information relevant to eHealth were visited directly and scrutinized for pertinent information. In some cases, this was guided by the results of preliminary Google searches or by following up leads suggested in documents found earlier on, while in others it was guided by the existing knowledge of team members. As the searches were predominantly opportunistic and iterative in nature, it is inappropriate to try to document them exhaustively; however, the following types of information were targeted:
previous exercises to map, scope or define eHealth;
white papers, technical reports, predictions and early research reports on aspects of technology in health care, eHealth related policy, evaluation and trends, from the United Kingdom, Europe and beyond;
funding programmes for eHealth- and/or health-and-technology - focused research and development;
relevant articles from computing and information science-focused academic publications;
eHealth and health technology-focused websites, web logs and online journals, online ehealth news feeds, email discussion groups and email newsletters;
online sources with a focus on human-computer interaction, usability and accessibility, with specific attention on health care issues;
technology-oriented news websites profiling general and health-related trends and developments;
online studies, reports and statistical surveys relating to general technology take-up; consumer purchasing trends; attitudes and strategies of consumers and clinicians towards adoption of technology in general and for health care-focused tasks in particular; evaluation of the effectiveness of technological innovation, in the health care sector and beyond.
Given the increasing online availability of refereed academic literature there was inevitably some overlap between the information identified by the two searches.
Aggregating and Analyzing Definitions of eHealth
Scientific abstracts identified using the key word search were examined in order to assess the presence of definitions. While hand searching of full text articles was not a primary objective, this was done where easy Web-based access to this information was available. In the case of Web-based reports or commentary the definition was extracted from the page in which it appeared or was quoted. In both cases the initial extraction was performed by one research fellow and the results checked for inclusion eligibility by a second investigator. Our aim was not to perform an exhaustive and systematic review of definitions (because of time constraints) but to aggregate those appearing most easily and commonly in the research and wider arenas, as a means of supplementing our wider scoping study. The aggregated definitions were then analyzed thematically in order to assess the applications, stakeholders, contexts and theoretical perspectives targeted, so that the heterogeneity of conceptualizations could be determined. They were also considered with reference to the perspectives of the defining individual or organization and associated clarifications within the source document.
Results
Assessing the Taxonomic Structure of Research Databases and the Presence of eHealth
Of the databases of scientific abstracts consulted, only Medline has a comprehensive hierarchical taxonomy of descriptors for the broad field of medical informatics. This part of the MeSH tree is shown in Figure 1. Medical informatics is also represented on CINAHL; however the subtree is relatively shallow and undifferentiated, forming only a small branch of the higher Information Science category, with many potentially relevant areas subsumed within other branches.
That eHealth has yet to be explicitly included among these thesauri, indicates the relative youth of the topic and the lack of an agreed conceptual definition. The literature relevant to eHealth is thus distributed among a range of existing MeSH fields.
The Medline MeSH structure for Medical Informatics contains 3 main subbranches: Public Health Informatics, Medical Informatics Computing, and Medical Informatics Applications. Examining the definitions of these and their lower order MeSH descriptors indicates that the Medical Informatics Applications tree encompasses the greatest number of component categories relevant to eHealth, taken broadly as the use of information and communication technologies to facilitate health care. For example, it subsumes the lower-order categories of Decision Making, Computer Assisted (which subsumes Computer Assisted Therapy and Diagnosis, among others); Information Systems (electronic information systems, networks, clinical decision support) and Information Storage and Retrieval (databases, laboratory information systems, etc). In contrast, Medical Informatics Computing is mainly characterized by an emphasis on systems and hardware, although it does contain MeSH descriptors relevant to eHealth — most importantly Internet, which may appear in eHealth publications as a specific technology or an application of technology. Public Health Informatics is concerned with the application of information and computer sciences to public health practice, research, and learning. Although this potentially encompasses eHealth-relevant research (for example, use of information and communications technologies for population health surveillance), the term was only recently introduced and has yet to contain any subcodes, limiting its usefulness at the present time. While the broader taxonomic categories each have their own character, there is clearly overlap between them. For example, decision support systems appear within both Medical Informatics Applications and Medical Informatics Computing, and electronic databases are a common feature in medical informatics applications, as well as representing a type of system.
Comparison of the MeSH tree with an expert-derived conceptual map endorsed by the International Medical Informatics Association (IMIA) revealed interesting differences in terms of the breadth of included concepts and their structural relationships (Table 2) [12]. For example, human and organizational factors appear to be underrepresented within Medline, while applications for consumers do not have a specific MeSH term (however, the IMIA taxonomy also appears to underrepresent consumer issues). This reflects the historical evolution of the MeSH hierarchy, which has been added to as the need arose by elaborating upon existing structures. Nonetheless, all the main areas apparently relevant to eHealth were encompassed by the MeSH tree and we are confident that using it as the basis of our search enabled the majority of pertinent literature to be identified.
Figure 1Hierarchy of MeSH descriptors found below the Medical Informatics descriptor in the MeSH tree
Table 2
Medical informatics scientific content map endorsed by the International Medical Informatics Association (IMIA) [12]
Applied Technology
Information Technology Infrastructure
Data-Infrastructure Related
Applications and Products
Human-Organizational
Education and Knowledge
Algorithms
Bioinformatics
Biosignal processing
Boolean logic
Cryptology
Human genome related
Human interfaces
Image processing
Mathematical models in medicine
Pattern recognition
Archival-repository systems for medical records- EPR-CPR-EMR
Authentication
Chip cards in health care
Distributed systems
Health professional workstation
Interfaces
Knowledge based systems
Networks
Neural networks
Pen based
Security
Speech recognition
Standards
Systems architecture
Telehealth
User interfaces
Classification
Coding systems
Concept representation-preservation
Data acquisition-data capture
Data analysis-extraction tools
Data entry
Data policies
Data protection
Database design
Indexing
Syntax
Language representation
Lexicons
Linguistics
Modeling
Nomenclatures
Standards
Terminology-vocabulary
Thesaurus tools
Biostatistics
Clinical trials
Computer-supported surgery
Decision support
Diagnosis related
Disease management
EPR-CPR-EMR
Epidemiological research Hosp IS
Event-based systems
Evidence based guidelines
Expert systems
Health services research
Health Information Systems management
Knowledge-based systems
Laboratory data
Image processing
Operations/resource management
Outcomes research and measurement
Quality management
Patient identification
Patient monitoring
Minimum data sets
Supply chain
Telematics
Telemedicine
Assessment
Compliance
Cognitive tasks
Collaboration
Communication
Economics of IT
Ethics
Implementation-deployment
Diffusion of IT
Evaluation
Human Factors
Legal issues, implementing national laws
Management
Managing change
Needs assessment
Organizational redesign processes
Organizational transformation
Planning
Policy issues
Privacy
Project management
Security
Strategic plans
Unique identifiers
User-computer interface
Bibliographic
Cognitive learning
Computer aided instruction
Computer-supported training
Consumer education
Continuing education
Digital libraries
E-Business
Health/medical informatics education
Information management- dissemination
Knowledge bases
Knowledge management
Learning models
Online/distance education
Clinical Disciplines: Anesthesia, Behavioral, Cardio/Thoracic, Cardiovascular, Dentistry, Dermatology, Emergency Medicine, Environmental Health, Gastroenterology, Human Genetics, Internal Medicine, Neurosurgery, Nursing, Obstetrics & Gynecology, Ophthalmology, Orthopedics, Pathology, Pediatrics, Pharmacy, Primary Care, Psychiatry, Radiology, Surgery, Urology
Exploring the Composition of the Medical Informatics Literature Using Existing Taxonomic Systems
Figure 2 describes trends in the volume and nature of the literature indexed by the Medical Informatics MeSH descriptor (note that searching for MeSH terms in PubMed automatically includes the more specific MeSH terms in a search). There has been a steady growth in the volume of medical informatics research literature. The annual number of publications increased from 1987 to 2003 five-fold.
Figure 2Number of publications over time indexed with the MeSH descriptor Medical Informatics
Publications indexed with MeSH keywords from each of the 3 main medical informatics MeSH subtrees (medical informatics computing, medical informatics applications, public health informatics) all follow this steady upwards trend, as do most narrower MeSH (eg, Information Systems; Therapy, Computer Assisted). However, the frequency of publications concerned with Clinical Laboratory Information Systems (Figure 3), appears to be decreasing, while research concerned with computer-assisted diagnosis increased rapidly in 2003 (Figure 4).
A breakdown of Medical Informatics MeSH, including definition, year of introduction, number and type of publications is supplied in Multimedia Appendix 1.
Figure 3Number of publications over time indexed with the MeSH descriptor Clinical Laboratory Information Systems
Figure 4Number of publications over time indexed with the MeSH descriptor Diagnosis, Computer Assisted
Using eHealth as a Search Term
As mentioned previously, there are currently no MeSH or equivalent coding categories in any of the databases searched which explicitly incorporate the term eHealth or its variants in their thesauri. This suggests that articles making reference to eHealth are being absorbed within existing classification schemes, such as Medline's Medical Informatics taxonomy.
When duplicates across databases were discarded we identified a total of 392 publications which explicitly referred to eHealth in the title, abstract, or journal title. Of these, most were represented in Medline. Appearing only in the Medline database were 283 (72%) articles, 54 (14%) only on the CINAHL database, and 55 (14%) only on the SCI, SSCI and ISTP databases.
Figure 5 illustrates trends in the volume of eHealth publications appearing across databases over time. This shows that the term did not start to be used in the research literature until 2000. References to eHealth showed a dramatic rise in 2000 to 2001 and, despite a small dip in 2002 a general upward trend persists. Note that we also retrieved publications from the Journal of Telemedicine and E-health which were picked up due to the journal name, not necessarily because they dealt with eHealth.
Figure 5Number of publications found using the search term eHealth (or variants) in 5 research databases by year.
In Which Journals Do Publications Using the Term eHealth Appear?
In our study, publications containing the term eHealth were found in 154 different journals. A research fellow classified these by type, using a scheme agreed by the research team. The number of articles appearing within each journal were documented. Of the 387 publications found across multiple databases (after eliminating 5 that were clearly irrelevant), 77 appeared in clinical journals, 61 in health-services - related journals, 7 in finance-related journals, 4 in legal journals, 3 in journals related to medical education, and 28 in other journals not easily categorized. The journal titles with the most articles containing the term eHealth (n=9 for each journal) were the Journal of Medical Internet Research, Managed Care Interface, and Journal of AHIMA / American Health Information Management Association. The majority of publications were IT-related (207): however, among these, 116 articles were published in the Journal of Telemedicine and E-health, which were mainly picked up due to the journal name: only 4 articles actually contained the term eHealthin the abstract or title. Further details are provided in Table 3 and a detailed breakdown of journal titles is given in Multimedia Appendix 2.
Table 3
Topical areas of journal titles containing articles using the term eHealth
Main Topic Area
More Specific Topics
Number of Publications (%)
Information Technology
Telemedicine
124* (32%)
Medical Informatics
35 (9%)
Internet
23 (6%)
Medical Computing
6 (1.5%)
Biotechnology
2 (0.5%)
Others
17 (4 %)
Sub total
207 (53%)
Clinical
Specialist Medical
30 (8%)
Generalist Medical
16 (4%)
Nursing
13 (3%)
Others
18 (4%)
Sub total
77 (19%)
Health Services
Management
30 (8%)
Case Management
16 (4%)
Others
15 (4%)
Sub total
61 (16%)
Finance
Sub total
7 (2%)
Legal
Sub total
4 (1.5%)
Education
Sub total
3 (1.5%)
Others
Sub total
28 (7%)
Total
387 (100%)
* Of the 124 publications listed under telemedicine, 116 articles were published in the Journal of Telemedicine and E-health, of which only 4 articles actually contained the term e-health
What Topics are Covered in the Literature Using the Term eHealth?
In our study, in order to identify the topics dealt with in papers explicitly referring to eHealth, article titles and abstracts were examined by a research fellow and classified using narrative descriptors. This indicated that the most common topics are related to telemedicine (25% of publications) or the Internet (13%), while some (6%) are concerned with issues such as the scope of eHealth, future trends, or progress and challenges in the field. Note that this view is possibly biased towards the telemedicine field, as all articles published in the Journal of Telemedicine and E-health were retrieved, even if they did not mention eHealth specifically. Other topics are distributed across a range of diffuse areas such as antiterrorism and medical errors, none of which is represented by more than 4 papers (hence relevant percentages have not been calculated). A heuristic summary is provided in Figure 6, which highlights the key topics and subtopics identified. These results are based on preliminary analysis; further validation work is underway.
Figure 6Map of topics in published articles using the term eHealth
Definitions of eHealth
We identified 36 definitions of eHealth [13-52] appearing in published scientific abstracts and Web-based information sources (Table 4). As stated previously, our aim was not to perform an exhaustive and systematic review of definitions (which would have necessitated hand searching of full-text articles and reference lists), but to aggregate the most salient and easily accessible examples. Since many research databases are Internet accessible, there was some overlap between the definitions obtained by the two methods; however, they did yield largely unique results. In total, 36 definitions were identified. Definitions 1 to 15 were accessed via the research literature and 16 to 36 via the independent online searches, while 1, 5, 6, 7, 15 and 28 emerged from both searches.
Definitions were analyzed thematically in order to highlight specific technologies, applications or stakeholders referred to, and other theoretical concepts addressed, as detailed in Table 4. Analysis was initially performed by one investigator and the results checked by two others, thereby establishing agreement.
Our analysis suggests that there is significant variability in the scope and focus of existing definitions of eHealth both within the research literature and relevant sources on the World Wide Web. In terms of its functional scope, most definitions conceptualize eHealth as a broad range of medical informatics applications for facilitating the management and delivery of health care. Purported applications include dissemination of health-related information, storage and exchange of clinical data, interprofessional communication, computer-based support, patient-provider interaction and service delivery, education, health service management, health communities, and telemedicine, among others. A few narrow the concept down to specific applications, such as telemedicine or e-business, but these are the exceptions. While the range of applications is broad, a general theme relates to communication. One example is “E-health is connectivity; it is transactional; it is clinical. It is informational, interactive and interventional.”[43]
The majority of definitions (n=24) specify the use of networked information and communications technologies, primarily the Internet, and digital data, thus differentiating eHealth from the broader field of medical informatics, which incorporates “harder” technologies, such as scanning equipment, and bioinformatics research which tends to take place in isolation and is less directly applicable to health care service delivery. It is acknowledged that the Internet “…has the reach, the infrastructure, and the acceptance to achieve widespread change” [17] and it is envisaged that “Internet technology may rank with antibiotics, genetics and computers as among the most important changes for medical care delivery.”[16] Only 1 definition makes specific reference to harder technologies such as nanotechnology, robotics and laboratory tools [27], although another refers to Internet-compatible ICTs such as digital TV [40]. Of the 36 definitions identified, a sizable proportion make reference to telemedicine or telecare, either explicitly (7 examples) or in terms commonly used to describe these areas, such as delivery of care over distances. In most cases this is presented as part of a wider sphere of applications, although the definition from NHS Wales clearly identifies eHealth with telemedicine and telecare [45]. We identified 6 definitions that make explicit reference to business or e-business, although others contain related ideas such as the online trading of goods and services. In the majority of cases, such commercial applications are presented as merely one expression of eHealth.
In terms of the stakeholders considered to be the users or targets of eHealth, many definitions emphasize applications for providers and organizations–particularly those stressing electronic data exchange for clinical and administrative purposes. Others emphasize provision of information, education and services to consumers, including patients and “citizens”, with a small number clearly identifying eHealth with consumer health informatics [14, 46, 50]. Nevertheless the majority appear to encompass applications for all stakeholder groups, whether specified or implied by the breadth of the definition.
There is also variation in the degree to which alternative definitions consider wider theoretical issues, such as the influence of eHealth on society or on professional behaviour. Several highlight the changing cultural environment of health care; particularly growing patient empowerment (access to information and ability to use it), and point to the potential of eHealth to facilitate doctor-patient communication, partnership and shared decision making. Others emphasize the changes required to ensure that eHealth reaches its full potential, recognising that it requires new ways of working and attitudes and must take account of human and organizational influences affecting technology adoption and change. More broadly, eHealth is said to require a fundamental rethinking of health care processes and a commitment for networked global thinking to improve health care [22]. Overall, the definitions suggest a general excitement and optimism about the potential of this rapidly evolving field to improve health care processes and patient outcomes, and many clearly identify projected benefits such as improved clinical decision making, efficiency and safety.
Table 4
Definitions of eHealth identified from searching databases of scientific abstracts and wider Web-based information sources
Definition
Source
Date
Technologies Specified
Applications Specified
Stakeholder Focus
(and Other Concepts)
1) “e-Health is a consumer-centred model of health care where stakeholders collaborate, utilizing ICTs, including Internet technologies to manage health, arrange, deliver and account for care, and manage the health care system”
Alvarez [13], based on Ontario Hospital e-health Council [14]
2002(2002)
ICTs including Internet
General: manage health, arrange, deliver and account for care, and manage the health care system
Consumer centered but also emphasizes collaboration with providers
2) “Healthcare delivery is being transformed by advances in e-health and by the empowered, computer-literate public. Ready to become partners in their own health and to take advantage of online processes, health portals, and physician web pages and e-mail, this new breed of consumer is slowly redefining the physician/patient relationship. Such changes can effect positive results like improved clinical decision-making, increased efficiency, and strengthened communication between physicians and patients.”
Ball and Lillis [15]
2001
Internetonline processes, health portals, physician en-pages, email.
General: healthcare delivery
Consumers (Change. Citizen empowerment. Physician/patient relationship/ communication. Improved clinical decision making, efficiency)
3) “The "e-health" era is nothing less than the digital transformation of the practice of medicine, as well as the business side of the health industry…. The Internet is the next frontier of health care. Health care consumers are flooding into cyberspace, and an Internet-based industry of health information providers is springing up to serve them. Internet technology may rank with antibiotics, genetics, and computers as among the most important changes for medical care delivery.”
Coile [16]
2000
Internet
The practice of medicine as well as the business side of the health industry
Consumers and providers(Change. New frontiers. Transformation of medical practice.)
4) “E-health—any electronic exchange of healthcare data or information across organizations—reflects an industry in transition…. The Internet clearly drives the development and adoption of e-health applications; standing alone, it has the reach, the infrastructure, and the acceptance to achieve widespread change.”
DeLuca and Enmark [17]
2000
Internet
Electronic exchange of healthcare data or information across organizations
Not specified. Implies focus on professional & organizational levels(Change)
5) "a new term needed to describe the combined use of electronic communication and information technology in the health sector... the use in the health sector of digital data - transmitted, stored and retrieved electronically - for clinical, educational and administrative purposes, both at the local site and at distance"
Della Mea [18], based on Mitchell [19]
2001[1999]
Combined use of electronic communication in and IT in the health sector. Digital data transfer
Transmission of digital data locally and across distances, for clinical, educational and administrative purposes
Professionals and organizations
6) “e-health is the use of emerging information and communication technology, especially the Internet, to improve or enable health and healthcare.”
Eng [20], based on Eng [21]
2004[2001]
Emerging ICTs, especially the Internet
General: To improve or enable health and health care
Not specified but implies consumers and providers
7) “e-health is an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology.”
Eysenbach [22]
2001
Broad definition encompassing many aspects of health informatics but focusing on the Internet and related technologies
Delivery of health services and information
Not specified. Implies consumers and providers.(“a state of mind, a way of thinking, an attitude and commitment for networked, global thinking to improve healthcare…”)
8) “Many of the major forces of change impacting health care today have technological underpinnings, and many of the less desirable impacts may have technological solutions. Two related technological forces are transacting business, online (e-business) and delivering health care online (e-health).”
Ellis and Schonfeld [23]
2001
Internet
General: Delivering healthcare
“Delivering” implies focus on professionals(Change.Relationship between eHealth and eBusiness)
9) “ehealth includes use of the internet or other electronic media to disseminate health related information or services.”
Gustafson and Wyatt [24]
2004
Internet or other electronic media
Dissemination of health related information or services
Implies consumers
10) “As a special expression of e-business in the health service the sphere of e-health has developed in recent years which increasingly manifests itself in the internet via health portals. Next to the transmitting of medical contents, the offer of community functions and the trading with goods from the medical sector, these health portals now increasingly provide advisory services for citizens by medical experts.”
Khorrami [25]
2002
Increasingly manifests itself in the Internet via health portals.
e-businessHeath advice. Information exchange. Community functions. Advisory services for citizens
ConsumersHealthcare organizations
11) “e-Health (use of interactive communication and information technologies to engage in health-related activities) includes not only telehealth-related media and telecommunications but also a wide array of consumer and healthcare provider activities that use the Internet.”
Maddox [26]
2002
Interactive ICT, telehealth, internet etc
General: health-related activities
Consumer and healthcare provider
12) “ …technologies with practical applications that have the potential to improve both quality of and access to healthcare….Telemedicine, Health Information Systems, Databases, Genomics, Biotechnology, eLearning, Continuing Professional Development, Nanotechnology, Drug Treatment Technologies, Decision Making Tools, Diagnostic Aids, eLibraries, Laboratory tools, and Robotics are all innovative or 'disruptive' technologies that promise a better health for our children.”
McConnell [27]
2002
Wide range of digital technologies
Wide range of informatics applications that may contribute to improved quality of and access to healthcare
Providers and patients(Quality. Access. “Disruptive technologies”)
13) “e-Health offers the rich potential of supplementing traditional delivery of services and channels of communication in ways that extend the healthcare organization's ability to meet the needs of its patients. Benefits include enhanced access to information and resources, empowerment of patients to make informed healthcare decisions, streamlined organizational processes and transactions, and improved quality, value, and patient satisfaction.”
Nazi [28]
2003
Not specified
Delivery of services Communication. Access to information and resources.
Patients (empowerment, satisfaction)Organization (efficiency and quality)
14) “the use of the Internet for health purposes”
Provost et al [29]
2003
Internet
General: “Health purposes”
Any
15) "a means of applying new low cost electronic technologies, such as 'web enabled' transactions, advanced networks and new design approaches, to healthcare delivery. In practice, it implies not only the application of new technologies, but also a fundamental re-thinking of healthcare processes based on using electronic communication and computer-based support at all levels and for all functions both within the healthcare service itself and in its dealings with outside suppliers. eHealth is a term which implies a way of working rather than a specific technology or application".
Richardson [30], based on Silicon Bridge [31]
2003 [2001]
InternetNew low-cost electronic technologies such as ”web enabled” transactions and advanced networks”
General: “Healthcare delivery” Electronic communication and computer-based support at all levels and for all functions
‘Healthcare delivery [and] processes' implies organizational/ professional level(“…a way of working”)
16) “The healthcare industry's component of business over the internet.”
Blutt [32]
2001
Internet
Business
Implies organizations
17) "The application of the Internet and other related technologies in the healthcare industry to improve the access, efficiency, effectiveness, and quality of clinical and business processes utilized by healthcare organizations, practitioners, patients, and consumers to improve the health status of patients."
Broderick and Smaltz [33]
2003
Internet and related technologies
Improvement of access, efficiency, effectiveness and quality of clinical and business processes
Organizations, practitioners, patients, consumers
18) “eHealth includes the development, application and implementation of technology to improve effectiveness in healthcare. But it also includes getting it out there wherever it's needed in the service and making it happen across the service. It includes the use of telemedicine and clinical systems used for diagnosis and care pathways. We also apply the term to the policies and protocols that assure the confidentiality and security of sensitive data. Most of all it includes those aspects that support major change of working practice - training, support and Organisational Development.”
Chisholm [34]
2003
Technology
TelemedicineClinical systems for diagnosis and care pathwaysPolicies and protocols
Not specified, but implies organizational/professional focus (Importance of organizational and professional behaviour change recognized. Also confidentiality and security issues.)
19) “…using Information and Communications Technologies to ensure the right treatment to each patient, specialised to each individual's context and situation, and to deliver healthcare where patients and providers need not be in the same place at the same time.
CSIRO [35]
Un-dated
ICTs
Delivery of personalized patient care. Telemedicine implied
Not specified. Implies provider focus but also interaction with patients
20) "Put simply, e-health is a wide-ranging area of social policy that uses new media technologies to deliver both new and existing health outcomes. In the UK, it incorporates everything from NHS Direct online to Internet pharmacies to webcast operations involving consultants in another country…At the moment, the main focus of e-health is on patient empowerment and self-care. As the area develops, e-health could expand to include online long-term disease management, personalised health checks, and more efficient primary care services due to informed patients accessing the healthcare system at the most appropriate point."
GJW Government Relations Ltd [36]
2000
New media technologies
On-line health informationLong-term disease management and patient self-careTelemedicine
Patients and professionals(Patients emphasized)
21) “something to do with computers, people, and health”(Centre for Global e-Health Innovation, 2003)
Gustafson [37]
2003
Computers in general
Very broad – computers, people and health
Implies all stakeholders
22) “the application of information and communication technologies (ICT) across the whole range of functions which, one way or another, affect the health of citizens and patients.”
European Commission [38]
2003
ICTs
Broad – the whole range of functions which, in one way or another, affect the health of citizens and patients
All stakeholders. Providers, patients, citizens.
23) “the emerging world of e-health can be defined as the application of information, communication and video technologies to the delivery of timely, professional and safe healthcare.”
European Health Telematics Association [39]
2004
ICT and video technologies
Broad – delivery of timely, professional and safe care
Not specified. Implies professional perspective.
24) “the use of emerging interactive technologies (i.e., Internet, interactive TV, interactive voice response systems, kiosks, personal digital assistants, CD-ROMs, DVD-ROMs) to enable health improvement and health care services. For this Initiative, these technologies should focus primarily on health behavior change and chronic disease management for consumers/patients.”
Health e-Technol-ogies Initiative [40]
2002
Emerging interactive technologies (Internet, interactive TV, interactive voice response systems, kiosks, personal digital assistants, CD-ROMs, DVD)
Enabling health improvement and health care services,chronic disease management, health behaviour change
Consumers, patients
25) “the use of ICT to support and improve healthcare”
Hoving et al [41]
2002
ICT
General: support and improve health care
Not specified.
26) "eHealth means taking the most recent developments in computer and networking technology, and applying it to the problems facing the healthcare community in all its forms - eHealth is the endeavour to produce reliable, easy-to-use, highly-automated, accurate systems, so that health care professionals can spend less time and resources on finalising the paperwork, and more time doing what they do best - taking care of people's health!"
IBA eHealth [42]
Un-dated
Recent developments in computer and networking technology
General: Applying it to the problems facing the healthcare community in all its formsSpecific: administrative and clinical information to improve efficiency
Professionals(improved efficiency)
27) “The "e" is for electronic. Placed before the word health, it implies all things transmitted and technological in health care, which help improve the flow of information and the process of health care delivery. "E" networks integrate isolated towers of information and create new knowledge through the creation of relational databases. The spectrum of "E" is broad and goes beyond the use of a computer as a box on the desktop. It includes wireless communication using hand-held devices and the storage and function by the microchip which is revolutionizing health care, as it is inserted into everything we use to diagnose, treat, record, sort, analyze, and conclude. It also incorporates electronic forms of care delivery, such as telemedicine, providing health care over a distance, communicating by sound and image transmission. E-health is connectivity; it is transactional; it is clinical. It is informational, interactive and interventional.”
Marcus and Fabius [43]
Un-dated
Electronic networks, relational databases. Wireless communication.
All things transmitted and technological in health care, which help improve the flow of information and the process of health care deliveryElectronic care delivery (telemedicine)Sound and image transmission
Not specifiedConnectivity; communication, interactivity, intervention
28) "the health services organisation and societal approach to health and health services which result from the introduction of, and increasing access to, new digital technologies: including the Internet, other computerised networks and tele- or distant health care facilitated by new digital technologies".
NHS SDO Programme [44]
2002
New digital technologies InternetOther computerized networks Telemedicine
Health service organization“Societal functions”
OrganizationsSociety (citizens)
29) “More commonly known as “eHealth”, the headings of Telemedicine and Telecare are themselves subsumed under the framework category of "health informatics", which basically means the delivery of healthcare and medical knowledge through the application of advanced information and computer technologies.”
NHS Wales [45]
2003
Advanced information and computer technologies
Telemedicine and Telecare.
Not specified.(Identified eHealth with telemedicine)
30) “The big difference between yesterday's knowledge-based patient care and that of tomorrow is a fundamental premise that patients will explore the web world with a desire to learn more about their condition, including its treatment and prognosis. This has evolved into the concept of e-health”
Podichetty and Biscup [46]
2003
Internet
Patient information and decision support
Patients(Cultural shift to patient participation/ empowerment in health care)
31) “eHealth signifies a concerted effort undertaken by some leaders in healthcare and hi-tech industries to harness the benefits available through convergence of the internet and healthcare…”
Rx2000 Institute [47]
Un-dated
Internet
None specified
Not specified. Implies organizations(Harnessing benefits of converging internet and healthcare)
32) “eHealth describes the application of information and communications technologies (ICT) across the whole range of functions that help health. It is the means to deliver responsive healthcare tailored to the needs of the citizen.”
Silber [48]
2003
ICTs
Broad – the whole range of functions that help health
Citizens (consumers, patients, public)
33) “E-health is a new term used to describe the combined use of electronic communication and information technology in the health sector OR is the use, in the health sector, of digital data-transmitted, stored and retrieved electronically-for clinical, educational and administrative purposes, both at the local site and at a distance.”
WHO [49]
Un-dated
ICTsDigital data
Clinical, educational and administrative purposes, at the local site and at a distance
Organizations/professionals
34) “Using the internet and other electronic media to disseminate or provide access to health & lifestyle information or services”
Wyatt [50]
2003
Internet and other electronic media
Access to health and lifestyle information or services
Patients, public
35) “e-Health refers to all forms of electronic healthcare delivered over the Internet, ranging from informational, educational and commercial "products" to direct services offered by professionals, non-professionals, businesses or consumers themselves. e-Health includes a wide variety of the clinical activities that have traditionally characterized telehealth, but delivered through the Internet. Simply stated, e-Health is making health care more efficient, while allowing patients and professionals to do the previously impossible.”
Wysocki [51]
2001
Internet
Delivery of informational, educational and commercial "products"Direct delivery of servicesClinical activities traditionally characterized telehealth
Professionals, consumers, businesses(Making health care more efficient, while allowing patients and professionals to do the previously impossible)
36) “E-health is a very broad term that encompasses many different activities related to the use of the Internet for healthcare. Many of these activities have focused on administrative functions such as claims processing or records storage. However, there is an increasing use of e-health related to patient and clinical care.”
American Telemed-icine Association [52]
2001
Internet
Administrative functions, patient and clinical care
Not specified. Implies organizational and professional focus(increasing use of eHealth for patient and clinical care)
Discussion
We have established that eHealth is a new term which has yet to be formally represented in bibliographic research taxonomies but is part of the wider field of medical or health informatics. The Medical Informatics MeSH tree encompasses most topics likely to be classed as eHealth and is broadly compatible with an expert-derived taxonomy endorsed by IMIA. Since eHealth cuts across a range of health informatics topics a new MeSH term may neither be necessary nor appropriate at the present time. Topics related to eHealth are distributed across all component MeSH trees within the broader field, although most are represented by the Medical Informatics Applications tree, which emphasizes functions of technologies, rather than technologies themselves, and prioritizes delivery of clinical information, care or services. The medical informatics literature has grown steadily over the last 15 years although research on some topics, such as clinical laboratory information systems, is becoming less prevalent, while that on others, such as computer-assisted diagnosis, has recently increased rapidly, reflecting a change in emphasis from systems and database architectures to supportive applications.
Research articles explicitly referring to eHealth or its variants begun to appear in 2000 and are accumulating rapidly. The majority of such articles are indexed by Medline, although others appear in alternative databases. Such articles are published in a wide range of journals, spanning information science to law, but they are most commonly represented in journals related to health care information technology and telemedicine. A vast array of topics is covered by research articles referring to eHealth, highlighting the diffuse nature of the field and the lack of an agreed conceptual definition.
Definitions of eHealth demonstrate variation in the breadth and focus of alternative conceptualizations. At the extremes these range from the highly vague and diffuse, eg, “something to do with computers, people and health” [37] to the highly specific, eg, “the healthcare industry's component of business over the internet.” [32] Nevertheless, most conceptualize eHealth as a broad range of medical informatics applications for facilitating the management and delivery of health care, including dissemination of health-related information, storage and exchange of clinical data, interprofessional communication, computer-based support, patient-provider interaction, education, health service management, health communities and telemedicine, among other functions. A general theme relates to electronic communication, which is supported by the fact that most definitions specify the use of networked digital information and communications technologies, primarily the Internet. This differentiates eHealth from its parent field of medical informatics, which encompasses fixed technologies, such as X-Ray equipment, and pure bioinformatics research. While Internet technologies represent the prevailing theme, there is sufficient reference to applications that may be enabled by other interactive ICTs to suggest caution before identifying eHealth exclusively with this medium. This is supported by the high profile of decision support as a generic topic within the health informatics literature, which may, for example, take the form of clinical decision support systems or patient decision aids available via CD-ROM. Nevertheless, rapid increases in bandwidth and desktop computing capability make it likely that most such tools will soon be accessible using digital networked systems.
Many conceptualizations of eHealth incorporate telemedicine and although most do so as part of a wider sphere of applications, some authors use the terms synonymously [45]. We suggest that the latter is more likely due to a misuse of the term than, as some have speculated, “the death of telemedicine” in favour of eHealth [19] (cited in [18]). While telemedicine is certainly a theme in the eHealth literature, and the ICTs used in this area are common to many eHealth functions, it clearly represents only one domain of the broader field. Similarly, while several definitions extend to e-business, primarily meaning online transactions between suppliers and purchasers (2% of eHealth-related articles appear in journals of finance), most of these portray it as merely one application of eHealth for service management or care delivery.
Most definitions appear to encompass applications for all stakeholder groups, although many emphasize support for providers and organizations and a few see eHealth as an application of consumer health informatics or, even narrower, as the use of “internet and other electronic media to disseminate or provide access to health & lifestyle information or services.”[50] Our review of eHealth topics in the research and Web-based literature also indicates that the concept extends across stakeholder groups, including providers, patients, citizens, organizations, managers, academics and policymakers. A tendency has been noted for an inclusive model to predominate in Europe and a narrower consumer-focused one in the USA, possibly reflecting top-down versus bottom-up health systems and cultures [53]. However our results indicate that there is currently more overlap than difference between conceptualizations emanating from either side of the Atlantic, with the inclusive view predominating (also the case for Australia). Even of those conceptualizations tending toward the consumer informatics model, most emphasize interaction with professionals rather than simply passive delivery or provision of information to citizens or patients, thus drawing in the professional stakeholder. While there may be a valid argument for narrowing eHealth down to consumer health informatics in the future, namely to circumscribe the field and thereby make it more manageable, analysis of the existing eHealth landscape suggests that the concept is currently more inclusive.
Existing conceptualizations also vary in the extent to which they consider broader issues relating to the place, function or promise of eHealth in the modern world, such as its ability to promote patient self-care and communication, and the implications of this for the doctor-patient relationship. Many see eHealth as facilitating the transition of decision making control and responsibility from the professional to the empowered consumer, consistent with conceptions of the information age flipping over the “power pyramid” of health care [54]. The human and organizational changes required to effect new ways of working and attitudes also represent a strong theme. This is reflected in the relatively large number of publications, identified by the keyword search, that are concerned with issues such as challenges to implementation, as opposed to specific technologies or applications. We therefore agree that the concept incorporates “a state-of-mind, a way of thinking, an attitude.” [22] Such human and organizational factors appear to be underrepresented in the MeSH Medical Informatics taxonomy at present, suggesting that a review may be warranted to bring it into line with expert-derived ontologies such as that endorsed by IMIA. More broadly, eHealth is said to require a fundamental rethinking of healthcare processes” [31] and a “commitment for networked global thinking to improve healthcare” [22], but there is clearly a general optimism surrounding the potential benefits of this rapidly evolving field for health care processes and patient outcomes.
Of course, definitions do not exist in isolation and the source documents for those reviewed provide further elaboration. For example, Eng provides a “5 C's model” of functions and capabilities of eHealth (content, connectivity, community, commerce, care) [21]; Eysenbach lists “10 essential E's” in eHealth (efficiency, enhancing quality of care, evidence-based, empowerment of consumers, etc) [22], and Richardson proposes a “4-pillar model” (under the headings of clinical applications, healthcare professional continuing education, public health information, and education and lifetime health plan) [30]. Yet others have attempted to define eHealth in terms of its potential role during a patient's care pathway [55] or with reference to the settings in which it may be useful [48]. Nonetheless, most authors have successfully distilled their concepts within the definitions they provide. Converging these with the other information sources documented in this report provides a fairly comprehensive overview of the concept and enables us to draw broad conclusions about its nature and scope.
In an editorial on the website, Health Informatics Europe, Ahmad Risk posed the question: “So, is this it? … Does 'eHealth' mean 'web health informatics'?”[9] Based on our results, our conclusion is largely “Yes”, or “It soon will be”, recognising that the parameters of the field currently extend to other interactive ICTs which, with increasing computing power, bandwidth and wireless capability, may rapidly be accommodated by Internet technologies. Based on our analysis of the place of eHealth within the wider informatics field and the nature of research activity and general commentary on the topic, we conclude that it is well represented by the global definitions suggested by Eng and Eysenbach early in the emergence of the field, with a minor change to the latter, as indicated below:
e-health is the use of emerging information and communications technology, especially the Internet, to improve or enable health and healthcare. [21]
e-health is an emerging field of medical informatics, referring to the organization and delivery of health services and information using the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a new way of working, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology. (adapted from Eysenbach [22])

ehealth
telemedicine
internet
medical informatics