for what purpose and reasons do doctors use the internet: a systematic review

i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16

journa l homepage: www. int l .e lsev ierhea l th .com/ journa ls / i jmi

Review

For what purpose and reasons do doctors use the Internet:A systematic review

Ken Masters ∗

Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

a r t i c l e i n f o

Article history:

Received 17 February 2006

Received in revised form

16 October 2006

Accepted 16 October 2006

Keywords:

Internet

World Wide Web (WWW)

Email

Doctors

Physicians

a b s t r a c t

Objectives: To determine doctors’ reasons for using the Internet, and the factors that influ-

ence their usage.

Data sources: A systematic review of 38 studies, from 1994 to 2004, describing surveys of

doctors’ Internet usage.

Results: All of the studies were in the developed world, primarily in North America. Approx-

imately 60–70% of doctors have access to the Internet, but in several studies access is more

than 90%. Access is steadily increasing. Most Internet activity focuses on email and search-

ing in journals and databases, but there is a very wide range of activities. Professional email

with colleagues and patients is low, but increasing. The major factors discouraging usage

are time, workload and cost, while too much information, liability issues and lack of skills

also feature as discouraging factors. Factors encouraging use are unclear, but overall patient

satisfaction and belief in improved service delivery, time saving and demand from patients

are factors. There is a trend that males use the Internet more than females, young more than

old, and specialists more than generalists, but these differences are not across the board,

and show variations between studies.

Conclusion: In spite of the limitations, it is clear that doctors are highly connected to the

Internet, and their professional usage is increasing. Factors encouraging and discouraging

usage are more complex than simple connectivity. Usage differences between demographic

groups do exist, but are equalising. More and consistent research is required in this

area.

© 2006 Elsevier Ireland Ltd. All rights reserved.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Contents

1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.1. Inclusion and exclusion criteria . . . . . . . . . . . . . . . . . . .
2.2. Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2.3. Data extraction and study appraisal . . . . . . . . . . . . . . . . . . . .2.4. Quality of studies and validation of data . . . . . . . . . . . . . . .
∗ Tel.: +27 21 406 6507; fax: +27 21 406 6244.E-mail address: [email protected].

1386-5056/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights resdoi:10.1016/j.ijmedinf.2006.10.002

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

erved.

mailto:[email protected]

dx.doi.org/10.1016/j.ijmedinf.2006.10.002

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i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16 5

3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.1. Quality of Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.2. Representation of countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.3. Access to and use of the Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.4. Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.5. Factors discouraging Internet usage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.6. Factors encouraging Internet usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.7. Correlations of usage with demographics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.1. Weaknesses of this review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.2. Theoretical approaches to technology adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.3. Uses of the Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.4. Factors affecting usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.4.1. Ease of use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.4.2. Patient–doctor relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

4.5. Demographic indicators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134.6. Developing countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

. Introduction

n 1994, the first World Wide Web (WWW) Conference was heldt CERN, Geneva. Although the Internet had existed for someime, the “Web,” with its system of easily accessible pages andyperlinks, transformed the Internet from a tool requiring aigh degree of technical ability to one requiring little morehan the ability to double-click an icon.

The value of the Web to health had long been recognisedy the Web’s chief architect, Tim Berners-Lee [1], and, by 2001,Pew report indicated that 52 million Americans had used theeb to obtain health or medical information [2].The potential of the Internet (including email, discussion

roups, blogs and wikis) has not been ignored by Health Pro-essionals, but it is a fast-evolving technology. There is a need,s Coiera pointed out as early as 1995, to ensure that the focusf the information technology use is not on the technology,ut on solving clinical problems [3].

Ten years later, we ask the question: for what reasons dooctors use the Internet? Behind that question are two sub-uestions: (1) what are the activities performed by doctors onhe Internet, and (2) what are the factors that encourage andiscourage doctors’ use of the Internet? These are importantuestions to answer, as they have a bearing on health pol-

cy, continuing professional development, interactions amongealth professionals, and between health professionals andheir patients.

Over the past 10 years, many studies have been conductedo assess the use of the Internet by doctors. The studies haveanged widely in their scope and approach. Some have focusedn a single university or clinic, others were national and even

nternational. They usually involved a postal or telephonicuestionnaire. There is, however, no single agreed-upon for-

There is a need, then, to attempt a review of the studies,in which common themes and ideas are extracted in orderto answer the question: for what reasons do doctors use theInternet? This study is a systematic review of literature, andaims at answering that question.

2. Methods

2.1. Inclusion and exclusion criteria

Inclusion and exclusion criteria for studies were establishedbeforehand in a protocol. Studies would be included if theywere surveys of doctors in any country, examining their use ofthe Internet, including email, dealing with the main questionor its sub-questions, published from January 1994 to Novem-ber 2004. 1994 was chosen because of the WWW conference,and also because studies earlier than 1994 would give ref-erences no longer relevant to the current technology. Eitherboth of the sub-questions had to be examined, or at leastone in detail. The search was limited to studies publishedin English.

To reduce bias, the following types of studies were alsoexcluded: studies of power users only, or users of a particularsite, or of one aspect only (such as Evidence-Based Medicine),and studies that were analyses of other broad surveys such asthe AMA Studies of Physicians’ use of the Web. An exceptionto the one aspect exclusion was the study of email. In addition,because the broad studies were large and comprehensive, theoriginal studies would be obtained. Fig. 1 below gives a dia-grammatical illustration of the exclusion process, with moredetails of the types of studies that were excluded.

at, design or methodology for surveys of Internet usage.ven where studies have been repeated from year to year, thenstrument has been changed, making chronological compar-sons and trends difficult to determine.

2.2. Search strategy

The following search strategy was conducted from 9 to 13December 2004:

6 i n t e r n a t i o n a l j o u r n a l o f m e d i c a

Fig. 1 – Diagram showing path of document selection.

• Through EBSCOHost: Academic Search Premier, MEDLINE,ERIC, Health Source—Consumer Edition, Clinical Pharma-cology, American Humanities Index;

• Independently: PubMed, Web of Science, Medscape, MDConsult, African HealthLine, MagNet.

The broad range of databases was chosen because surveysof this type might be referenced in non-academic databases.African HealthLine was included because the database mighthave African surveys not published in American or Europeanjournals.

The search terms were: (“Internet” OR “World Wide Web”OR “WWW” OR “email” OR “email”) AND (“health” or “doc-tor” or “physician”) AND (“survey” OR “review”). Early pilotsearches on these terms indicated that a large number ofresults would be returned, as the Internet and email are usedso broadly, and the noise/information ratio would be high.

2.3. Data extraction and study appraisal

The following data were sought: date of study, date of publica-tion, setting and subjects, response rate, method of collection,types and rates of Internet access, specific uses of the Inter-net, interaction with patients through the Internet, and factorsencouraging or discouraging Internet usage.

The data were placed into a Microsoft Excel spreadsheet.Variables were arranged in columns. In some studies, datawere given as raw figures; in others, data were expressed aspercentages of the respondents. As a result, the missing itemswere calculated from the given data.

Because of the variability of the survey instruments, datafor all variables had not been captured by every study. Theresults tables below indicate the number of studies reflectingdata for each variable. For numbers of participants involvedin each category, the minimum, maximum and median was
calculated from the percentages. Overall mean was calculatedby expressing the total number of participants involved in anactivity as a percentage of the total number of participantswhose studies gave data for that activity.
l i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16

2.4. Quality of studies and validation of data

Studies were evaluated according to the criteria in Ref. [4].As these criteria focus on diseases, slight modifications weremade to the criteria:

• Given that surveys of physicians usually have a responserate of 50–55% [5,6], the adequate response rate was takenat 50%. (Because [4] uses percentages rather than absoluterate, this has been retained.)

• The valid and repeatable disease definition was modifiedto “valid study definition”—for this criterion, the definitionand objectives of the study had to be clearly stated.

• Information on non-respondents was enlarged to include adiscussion on the extent to which the study could be gen-eralised.

• Observer bias was enlarged to include a declaration of affil-iations, grant sources, etc.

This paper forms part of a larger study undertaken for ahigher degree. For this reason, the supervisor did not performa second extraction of data, but was able to verify that criteriawere valid, and were met by all the studies in accordance withTable 2.

3. Results

The initial search returned 19,393 abstracts. Further screeningwas conducted. Fig. 1 shows the screening refinement processin the path to the final article selection.

Thirty-five publications on 38 studies were finally cho-sen. In the final analysis, because two questions werebeing addressed, it would have been preferable if all arti-cles had addressed both questions. In reality, however,this would have been very limiting, because often the fac-tors encouraging or discouraging use were not addresseddirectly.

Table 1 shows the final list of studies to be included in thisreview.

In addition, background information on the Canadian Med-ical Association (CMA) studies was taken from [42–48].

3.1. Quality of Studies

As outlined above, the studies were analysed for qualityagainst the criteria in Ref. [4]. Table 2 summarises the results.

It is noteworthy that only three articles [22,24,35] met all thecriteria. This does not necessarily mean that the other articlesare invalid, but certainly points to a need for an industry stan-dard, as all the criteria, apart from response rate, are easilywithin the control of researchers.

Most studies that did not have adequate sampling meth-ods had used a convenience sample. These authors, however,pointed out weaknesses and differences between their sampleand the general population.

The reason for the lack of information for the CMA arti-
cles is that they were published purely as tables of data, withlittle or no contextual information. All authors of journal arti-cles were careful to point out the aims of the study, and alsoensured that bias and authors’ affiliations were identified.


Table 1 – Studies, showing, author, year of publication, year of study, respondents’ information, methods

Author Year ofpublication

Year ofstudy

Location, subjects, full samplesize/(eligible)/respondents,

response ratea

Method

AMA [American medicalassociation] [7]

2002 2001 USA, AMA Physician Masterfile,excluding physicians over 70 andresidents, 7518/977 = 13%

Random; telephone

AMA 2001 2000 USA, AMA Physician Masterfile,6,244/1001 = 16%

Random; telephone

AMA 2000 1999 USA, AMA Physician Masterfile,15,000/1084 = 7%

Random until 400 interviews withWeb user completed; telephone

AMA 1998 1997 USA, AMA Physician Masterfile,????/1950

Random; telephone

Andrews et al. [8] 2004 ???? USA: primary care practitioners inKentucky Ambulatory Network (KAN),116/59 = 51%

Full population; postal

Audet, A.-M. [9] 2004 2003 USA, Physicians, 3598/1837 = 53% Random/postalBell et al. [10] 2003 2001 USA, Orange County, all primary care

paediatric physician that contract toCalOptima, 307 (offices)/(141)/140(offices) = 46%


Bennet et al. [11] 2004 2002-3 USA, Physicians, all specialities asdefined by AMA, ????/3,347 = N/A

Random blocks until 3200 reached;fax

Carney et al. [12] 2004 ???? USA, New Hampshire, DartmouthMedical School: preceptors who taughtstudents September 1998–April 2001,178/129 = 73%


Casebeer et al. [13] 2002 ???? USA, Physicians of all specialities inactive community practice,????/2,200 = N/A

Random until 2 200 reached; fax

Chew et al. [51] 2004 2002 USA, All members of AAFP in anorth-east metropolitan area; familyphysicians, 98/58 = 59%


CMA [Canadian MedicalAssociation] [14]

1998 1998 Canada, all physicians, 7693/3385 = 44% Random; postal

CMA [15] 1999 1999 Canada, all physicians, 7723/3128 = 41% Random; postalCMA [16] 2000 2000 Canada, all physicians, 8000/2806 = 35% Random; postalCMA [17] 2001 2001 Canada, all physicians, 7756/3246 = 42% Random; postalCMA [18] 2002 2002 Canada, all physicians, 7700/2882 = 34% Random; postalCMA [19] 2003 2003 Canada, all physicians, 7922/2251 = 28% Random/postalEberhart-Phillips et al.

[20]2000 1998 New Zealand, all GPs in

Otago/Southland region known to Deptof General Practice, Dunedin School ofMedicine. 259/168 = 65%

Full population; -ostal

Flanagan et al. [21] 2003 2002 Germany, France, Sweden, 50% GPs,50% specialists. ???/606 (254, 251,101) = N/A

Random; (telephone?) interviews

Gaster et al. [22] 2003 2000-1 USA, All physicians in outpatients at Uof Washington and affiliatedcommunity-based primary care clinics.295/(283)/249 = 88%


Given et al. [23] 2002 2001 USA, practicing physicians,23,492/1200 = 5.7%

“Representative”; telephone

Gjersvik et al. [24] 2002 2001 UK, Sweden, Norway: members of thedermatological societies,1,291/653 = 51%


Hobbs et al. [25] 2003 2002 USA, Primary care physicians inPartners HealthCare System, Boston,Massachusetts. 94/71 = 76%


Kalsman and Acosta [26] 2000 ???? USA, Rural provider in Wyoming,Montana and Idaho. 481/250 (57%)

????; postal

Kleiner et al. [27] 2002 ???? USA, “participating offices”, Pediatricphysicians (SP and GPs) in their offices;????/37 = N/A

???? ; F2F interview

8 i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16

Table 1 (Continued )

Author Year ofpublication

Year ofstudy

Location, subjects, full samplesize/(eligible)/respondents,

response ratea

Method

Koller et al. [28] 2001 2000 German-speaking Switzerland, 2009primary care physicians,2009/(1103)/ = 1085 = 54%

Random; postal

Kwon and Xie [29] 2003 ???? USA, physicians and other medicalpractitioners in the St Louis, Missourimetropolitan area, 1800/445 = 25%

????; postal

Lacher et al. [30] 2000 1998 USA, members of American College ofPhysicians–American Society ofInternal Medicine; 45 206/9466 = 21%


Lorenzo and Mira [31] 2004 2003 Spain, doctors in clinical units of eightpublic hospitals. 901/302 = 34%

Full population (of selectedhospitals); postal?

Miller et al. [32] 2004 2001 USA, Mostly solo/small group specialistphysicians, 23,492/1200 = 5.7%

National stratified random;telephone

Moffat et al. [33] 2001 1999 UK (Scotland, Lothian): all GPs in theLothian Health Primary Care mailinglist; 546/306 = 56%


Moyer et al. [34] 2002 1999 USA, Primary care physicians at twouniversity-based primary-care clinics;132/126 = 95%

Full population; F2F delivery ofquestionnaire

Murray et al. [35] 2003 2000-1 USA, National, based on AMAdatabase; 2000/1050 = 53%

Random; cross-sectional; postal?

Nylenna and Aasland[37]

2000 1998 Norway, active physicians;1646/1276 = 78%

Random; postal

Nylenna and Aasland[37]

2000b 1998 Norway, active physicians;1646/1276 = 78%

Random; postal

Poensgen and Larsson[38]

2001 2000? Sweden and Germany, ????/250 = N/A ???; interviews and focus groups

Stille et al. [39] 2003 2001 USA (New England), AAP and/orpediatric generalists and specialists,900/(860)/412 = 45%

Random plus hand-searchingpostal

van Knoop et al. [40] 2003 2001, 2002 USA, physicians who spent more than20 h per week caring for patients.????/>400 = N/A

Random; telephone

Wilson [41] 1999 ???? UK (Glasgow), GPs; 300/160 (54%) Random; postal

ipanhed. Nnalys

a Calculated from number of “eligible,” (returned uncompleted) particrespondents were contacted until a specific number had been reac

b This is a different aspect of the same study as Ref. [36]. For meta-a

3.2. Representation of countries

Because we are attempting to examine a global picture, andbecause Internet infrastructure varies internationally, thestudies were grouped according to the region in which theyhad been conducted. These results are reflected in Table 3.For purposes of context, the percentage of doctors reportingInternet access is also given and compared to the nationalaverage percentages as given by the International Telecom-munications Union (ITU) [49,50].

Even considering the high Internet penetration in thesecountries, the number of doctors connected to the Internetappears to be high and growing. Given that these numberscover 10 years, and that the 2002 Internet penetration for theUSA was 55%, and Sweden had the world’s highest at 57%, thenumbers for doctors are well above the norm.

3.3. Access to and use of the Internet

On average, some 60–70% of physicians have access to theInternet, although there are several studies [11,23,25,33,40,51]

ts, if the study makes this distinction. Number in italics indicate thato indication of the total number contacted.

is purposes, they are taken as one.

that place this figure above 90%. Those studies that wererepeated by organisations (such as the American MedicalAssociation (AMA) [7], Canadian Medical Association (CMA)[14–19] and the Boston Consulting Group (BCG) [38,40]), almostalways found an increase in access over time.

On the specific use of the Internet, the studies offeredrespondents a wide range of activities from which to choose.Table 4 shows doctors’ most common methods of access toand activities on the Internet.

Key: for the following tables:

• Studies: number of studies having data for this item.• N: total number of respondents in these studies.• Num: numerator: total number of respondents involved in

this activity.• %: numerator/N expressed as a percentage.• Minimum, maximum and median of individual studies’ per-

centage.

There is generally a strong and increasing use of activesearching in journals and databases, although other activitiesalso frequently feature. Email with colleagues and patients is


Table 2 – Survey quality Criteria, based on [4]

Author Targetpop

Samplemethods

Samplesize

Responserate

Non-respond/generalisability

Definitions/objectives

Bias/affiliations

AMA [7] X X XAndrews et al. [8] X X X X XAudet, A.-M. [9] X X X X X XBell et al. [10] X X X X X XBennet et al. [11] X X X X X XCarney et al. [12] X X X X X XCasebeer et al. [13] X X X X XChew et al. [51] X X X X XCMA (1998) [14] X X XCMA (1999) [15] X X XCMA (2000) [16] X X XCMA (2001) [17] X X XCMA (2002) [18] X X XCMA (2003) [19] X X XE-Phillips et al. [20] X X X X X XFlanagan et al. [21] X X X XGaster et al. [22] X X X X X X XGiven/Miller X X X X XGjersvik et al. [24] X X X X X X XHobbs et al. [25] X X X X XKalsman X X X X X XKleiner et al. [27] X X XKoller et al. [28] X X X X XKwon and Xie [29] X X X XLacher et al. [30] X X X X XLorenzo and Mira [31] X X X X XMoffat et al. [33] X X X X X XMoyer et al. [34] X X X X X XMurray et al. [35] X X X X X X XNylenna X X X X X XPoensgen X X XStille et al. [39] X X X X X X

gor(

van Knoop et al. [40] X XWilson [41] X X

An “X” indicates that the criterion has been met.

enerally very low, but there is a trend showing an increasever time. Within some studies, however, there was a strongesistance to ever using email with patients (e.g. [8] (42%), [27]79%), [12]). In many of the studies where email with patients

Table 3 – Geographical spread of studies, showing country, numstudies, percentage of doctors who had access to the Internet, a

Countries Studies Respon

Total Minimum

United States 23 26 111 37Canada 6 17 698 2251UK 2 466 160UK/Sweden/Norway 1 653Sweden/Germany 1 250Germany/France/Sweden 1 606Norway 1b 1 276Spain 1 1 302Switzerland 1 1 085New Zealand 1 168

Total 38 48 615

a This is actual users. Those with access is not known.b Two papers, but one study.

X XX X X

was used, it was generally used with only a small group (e.g.[22]).

On the value of the Internet, a mean of 51% (10 studies,n = 6619) found the Internet useful or extremely useful for find-

ber of studies, and total number of respondents in thosend the National averages for countries in those studies

dents Doctorsinternet (%)

Nationalinternet (%)

Maximum Median

9466 400 63 553385 3005 63 51306 233 88 42

77 42/57/5047 57/4162a 41/31/5748 5098 1675 3572 48


Table 4 – Access to and use of the Internet

Studies n Num % Minimum Maximum Median

Categories of accessHave Internet access (unspecified) 32 45,821 30,599 67 20 100 75Have Internet access from work 21 24,823 16,103 65 11 100 72Have Internet access from home 15 20,336 13,110 64 24 90 55Have email account 8 13,325 10,947 82 60 92 77

ActivitiesUse Internet (unspecified) 18 23,898 15,261 64 20 98 69At least weekly use of the Internet 10 16,844 8,650 51 19 75 51Use email to consult with colleagues 13 20,601 4,954 24 13 60 28Use email with patients 15 11,581 2,536 22 12 72 23

Specific activities (in order of decreasing number of studies)Accessing online journals 15 15,995 8,315 52 13 71 46Search for/attend. CME courses/meets 15 20,479 6,183 30 10 56 31Professional association updates 14 25,375 6,957 27 12 57 26Bibliographic info/medline 13 19,415 9,266 48 4 67 37Drug and dosage information 9 11,904 4,441 37 11 66 40Patient education/orientation sites 9 13,121 3,168 24 6 33 22Getting/storing lab results 9 11,096 2,264 20 3 59 17Financial activities 7 14,193 4,786 34 11 45 35Filing insurance claims 7 8,813 1,072 12 1 75 9Travel information 6 5,760 2,235 39 14 67 53

43

Literature searching 4 6,997Search for patient-specific information 4 6,934

ing medical information. In the five studies where more than50% of the respondents found the Internet useful, 89% hadan email account (as opposed to the 82% mean). Surprisingly,however, in these five studies, Internet access was lower thanthe mean: Internet access: 64% versus 67%; access from work:58% versus 65%; access from home: 38% versus 64%. This pointis considered further in Section 4.

3.4. Patients

Apart from interaction with patients via email, the Internetalso affects the face-to-face interaction. Increasingly, doctorsare reporting patients’ bringing Internet material to the con-sulting room. 89% of the doctors reported this, although onlya small percentage of their patients are bringing material. Toa far lesser extent, doctors are referring patients to Internetsites. The figures for interaction are reflected in Table 5.

3.5. Factors discouraging Internet usage

Mention has been made of the variability of the study designs.This variability was particularly evident in the questions

Table 5 – Interaction with patients

Access Studies n Nu

Patients have discussed with themmaterial found on the Internet

9 10,169 9,0

Frequently or sometimes referpatients to Web sitesa

6 11,349 2,2

a Includes 2,003,001 (n = 105) where 35% responded, but the frequency is n

,874 70 25 89 69,044 44 29 63 50

regarding the factors discouraging and encouraging usage.Many studies asked all participants, others did not ask atall, and others asked only those who were not using theInternet; some used “yes” and “no” options, other used alikert scale, and others allowed participants to select onlythe single most important factor discouraging or encouragingusage. The designers’ options ranged across at least 38 pos-sible factors discouraging usage and 26 factors encouragingusage.

This summary in Table 6 of factors discouraging use listsonly those factors interrogated by at least three studies. Italso distinguishes between answers from all respondents andanswers from those not using the Internet.

This table indicates the complexity of the factors affect-ing (encouraging or discouraging) doctors’ use of the Internet.Firstly, connectivity is not the most important issue; otherissues are at stake. In fact, [27] shows that while specialists hadgreater access to email than generalists, 79% of both groups
did not wish to use email with patients.
Also mentioned as obstacles were slow download times,navigation difficulties, specific information not available, notbeing aware of good or valuable sites, lack of reimbursement,

m % Minimum Maximum Median

45 89 50 98 90

85 20 13 66 25

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no resources, no need, lack of access, software incompatibili-ties, lost productivity, language barriers, lack of standards, andlack of trust of web sites.

The small number of studies examining each item makesconfident statements difficult, but it is obvious that time,workload, cost and too much or confusing information are bar-riers. Concerns about privacy and liability are primarily in thearea of email with colleagues and patients. Lack of skills playsa role, particularly amongst non-users.

3.6. Factors encouraging Internet usage

When dealing with factors encouraging the use of the Internetand email, survey design consistency was particularly lack-ing. In four studies (n = 1494), however, 94% of physician emailusers said that it increased patient satisfaction. Other factorswere mentioned, but in too few studies to be realistically takeninto account. Nevertheless, they are listed here if they werementioned in two studies where a mean of at least 40% of thedoctors who used email with patients, listed these as encour-aging factors: improves overall efficiency, delivers better care,enhances medical practice, saves the practice money, assistswith time-saving and management, and because of demandfrom patients. In addition, in two studies, reimbursement wasmentioned as a factor that would encourage email communi-cation between doctors and patients.

3.7. Correlations of usage with demographics

Some studies reported on the relationship between usage anddemographic factors. A correlation was accepted if the studiesdetermined one. In the case of the CMA tables, correlationswere determined statistically.

Table 7 summarises the results where at least three studiesgave data on a particular variable.

In addition, however, one study ([7] n = 977) indicated a neg-ative correlation on practice size, and one study ([13], n = 2200)indicated a negative correlation on generalists versus special-ists.

Common wisdom, perhaps based on the male/female ratioin Information Technology fields, would lead one to believethat males use the Internet far more than females. While thestudies show a slight tendency towards this, it is by no meansclear-cut, with seven studies showing low or no correlationwhatsoever. [36] show greater usage by males, but males andfemales have equal access. It is true, however, that no studiesindicate a significant reverse correlation.

There is also still a strong correlation between age andusage, with the younger doctors using the Internet more.Again, however, 6 of the 21 studies show no correlation. Indeed[7] shows that this difference is decreasing.

4. Discussion

4.1. Weaknesses of this review

Perhaps the single greatest weakness of this review is theinconsistency in the methods, instruments and terminologyused in the surveys. This has been discussed above. A uni-versally accepted survey form could be extremely useful for


Table 7 – Correlations of demographics

Factor (less/more) No or low correlations Medium or high correlations

Studies n Studies n

Gender (F/M) 7 5,479 12 34,219Age (old/young) 6 2,842 15 34,790Gen/spec 5 2,713 8 19,947Rural/urban 6a 17,698 1 2,200

71
Practice size (small/large) 1
a These are all the Canadian studies.

future reviews. This would allow for comparisons and trendsto be more easily identified.

A second weakness, obvious from Table 3, is the geograph-ical inequality of the studies. There is a dominance of NorthAmerican studies, and all but one of the studies are fromthe Northern Hemisphere. All the countries fall into a groupdefined by the ITU as “high income” with an average 2002Internet penetration of 44.5%. In contrast, Africa’s figure is1.2%, with South Africa the highest at 6.8%. Not a single studywas from a developing country. For this reason, the meanaccess cannot be taken as a global picture, but chiefly a pictureof the developed world.

The third weakness is that the amount of Internet usageis changing rapidly, so measurements from older studies mayhave reduced accuracy. The impact is not always grave, how-ever, for some older studies (e.g. [30]) show Internet accessfigures equal to or above the mean.

In spite of these weaknesses, there is value to be drawnfrom this study.

4.2. Theoretical approaches to technology adoption

Before we discuss these studies in more detail, however,we should look briefly at some theoretical considerations.Although this review is not the place to examine theories ontechnology adoption in detail, there is value to be gained fromhaving a context in which to view these results. Everett Rogers’Diffusion of Innovations (DoI) [52] and Fred Davis’ Technol-ogy Adoption Model (TAM) [53,54] point to various factors thatimpact upon the adoption of new technologies.

Rogers’ Diffusion of Innovations considers “the process bywhich (1) an innovation (2) is communicated through certainchannels (3) over time (4) among the members of a socialsystem” [52,55]. In considering the innovation, Rogers looksparticularly at five characteristics of the innovation that deter-mine its rate of adoption. These are: relative advantage (theextent to which the new innovation is perceived as advanta-geous over the old method); compatibility (the extent to whichthe new innovation is compatible with the current norms andpractises of the individual); complexity (the measurement ofeffort required to understand and use the new innovation); tri-alabilty (the extent to which the individual can experiment or“play” with the new innovation); and observability (the extentto which individuals can see the value of the innovation in
others) [52].
Rogers summarises the impact of these by arguing that“innovations that are perceived by individuals as havinggreater relative advantage, compatibility, trialability, observ-

2 3,037

ability, and less complexity will be adopted more rapidly thanother innovations” [55].

Davis’ original Technology Adoption Model concentrateson two aspects of technology: perceived usefulness (“thedegree to which a person believes that using a particularsystem would enhance his or her job performance”) and per-ceived ease of use (“the degree to which a person believes thatusing a particular system would be free of effort”) [53,54]. Alater extension of TAM by Venkatesh and Davis, called TAM2[56] introduced a measure of social influence. More recently, in2003, Venkatesh, Davis and colleagues created a “Unified The-ory of Acceptance and Use of Technology” (UTAUT) [57], which“posits three direct determinants of Intention to use (perfor-mance expectancy, effort expectancy, and social influence)and two direct determinants of usage behavior (intention andfacilitating conditions)” [57].

It is not the position of this paper to argue for DoI, TAM orUTAUT, but they are raised here so that they might shed lighton some of the results and add to the discussion to follow.

4.3. Uses of the Internet

From Table 5, there is little surprising in the specific activi-ties of doctors on the Internet. Apart from email, they appearto be using the Internet as a large library. Some other activi-ties mentioned in the studies (too few instances to be listed inthe results) support this: PubMed, WebMD, Physicians Online,Medscape, MDConsult also feature as popular websites. Thispursuit and value of clinical information is borne out by resultsof other studies of doctors’ use of online evidence [58–60],although several studies also indicate that the use of systemssuch as Cochrane is still low [61,62].

The high rate of Internet usage amongst doctors comparedto their national norms is not entirely surprising, and is pre-dicted by Rogers’ DoI and earlier studies [52] which point to acorrelation between education levels and adoption and usagerates of new innovations and technologies.

4.4. Factors affecting usage

4.4.1. Ease of useObviously, connectivity is a pre-requisite for usage, but theusage figures in Table 6 indicate that connectivity does notautomatically lead to usage. In most of these countries, Inter-
net access is widespread. Yet, the impact of obstacles suchas time, workload and effort, cost, confusion, and concerns ofliability and confidentiality illustrates that the path to greaterand effective use of the Internet is not merely the supply of

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nfrastructure. This is certainly supported by the theories ofoI [51,52,55,63–65] and TAM [53,54,66–70] which emphasiseompatibility, usefulness and ease of use as factors affectingdoption of technology; the obstacles mentioned here impactirectly on the ease with which the Internet can be integrated

nto medical practice without disruption, and the degree tohich its value can be demonstrated. This is also consistentith barriers identified in other studies of doctors’ accessingnline materials [71–73].

Although lack of skills features low on the list of barri-rs (Table 6), in any activity, there is a natural relationshipetween skills and the effort and time taken to perform a task.t is reasonable to argue that an increase in skills would leado information being found more easily, thereby reducing thempact of effort and time (and confusion), and perhaps evenost. This appears to be borne out by at least one study [11],here 59% of the doctors were confident or very confident in

heir searching skills and also reported a high level of usage.he impact of skills on doctors’ online activities has also been

ound in other studies [71,73].We need to be reminded, however, that, while the results

ection showed a correlation between perceived usefulnessnd number of email accounts, there was also a negative cor-elation between perceived usefulness and Internet access.his may be due to many factors, including a naivety amongston-users about the value of Internet. Further studies in per-eptions of usefulness between users and non-users would beble to clarify this issue.

Accompanying legal and security support will furtherncourage usage. This is especially true when discussingmail interaction with patients. Given that email is the mostommon activity on the Internet, and that some 82% of theoctors have email accounts, the fact that less than 25% of doc-ors use it professionally is telling. The importance of legal andecurity issues has been found in other studies [73,74] also,nd are also the factors affecting compatibility as determinedy DoI.

.4.2. Patient–doctor relationshiphe Internet is obviously directly affecting the patient–doctorelationship. The high percentage (89%) of doctors reportingatients’ bringing Internet information to the consultation

s interesting, especially when compared to the much lowerercentage of doctors searching for patient-specific informa-ion on the Internet (44%) or referring their patients to webites (20%). While some of this might be explained by thereater medical expertise of the doctors, it would be usefulo ascertain how much is determined by the identified barri-rs. Nevertheless, patients’ use of the Internet is impacting onhe relationship, and not always positively, especially whenatients attempt some self-medication before consultation

75]. Other researchers, however, have argued that this shoulde embraced by doctors, as part of the “patient as partner”cenario, and that doctors can use this opportunity to guideatients to web sites and other Internet resources [76–83].

Also encouraging is the fact that, even though the number
f doctors searching patient-oriented sites is low (24%), theMA studies show this to be rapidly increasing.
Patient–doctor email interaction affects the relationship,s has been found in other studies [84]. For the most part,

i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16 13

it appears that the patients’ satisfaction with the medi-cal experience is raised, as is evidenced by the fact thatpatient-demand is becoming a factor [13,40,84,85] and cer-tainly that some doctors are reporting similar favourableexperiences [8,29,34,84]. On the horizon, though, is the prob-lem of reimbursement—it is only logical that, if patients beginto see email communication as a substitute for visiting thedoctor, and the doctors’ workload increases [86–88], then someform of reimbursement will need to be considered.

Indeed, DoI, TAM and UTAUT all note that compatibilitywith existing norms and practices is important for a technol-ogy to be integrated, and that the obstacles of legality, securityand negative impact on the patient–doctor relationship willhave to be removed if the Internet is to be effectively used bydoctors.

4.5. Demographic indicators

As seen in Table 7, the usage rates between males and femalesare blurring, and the tendency is towards equalisation. Thisis predicted by UTAUT, which posits the possibility that, infuture, “gender differences in how each perceives informa-tion technology may disappear” [57]. Similarly, differences inusage amongst age groups are probably related to familiar-ity with computers and IT an earlier age, and therefore thesedifferences are likely to be reduced in the future [57].

Only one study showed the urban doctor using the Internetmore than the rural. It must be noted, however, that the sixstudies showing no statistical correlation were all from onecountry, Canada.

An interesting connection exists between generalists andprimary physicians as opposed to specialists. There is cer-tainly a greater tendency for specialists to use the Internetmore than generalists. On closer inspection, however, thisappears only somewhat related to the nature on the work,and closely related to cost. Cost has already been shown to bea significant factor; as [9] notes, the start-up costs are great,and this prevents many smaller general practices from goingonline. Once online, however, the situation begins to change.Ref. [22] shows that primary care doctors in the same environ-ment as the specialists use the Internet almost as much as thespecialists. Indeed, [13] shows a negative correlation, wherespecialists have used the Internet for longer than primary carephysicians, but the primary care physicians are using it morefrequently.

Similarly, the impact of practice size is unclear—whilesome studies show the larger practice using the Internet more,[7] shows that, while penetration of usage might be less in soloor two-doctor practices, these doctors spend more time on theInternet than those in group practices; more even than med-ical school doctors. Similarly, [31] shows doctors in smallerhospitals using the Internet more than doctors in larger hos-pitals.

4.6. Developing countries

Earlier, attention was drawn to the fact that the studiesfocussed on developed countries. There are, however, insightsfor developing countries; perhaps the most important con-cerns infrastructure. Although infrastructure in developing

14 i n t e r n a t i o n a l j o u r n a l o f m e d i c a

Summary pointsWhat was known before this study?

• Various studies, ranging in size and scope, examinedoctors’ use of the Internet, but there is conflictinginformation on the activities and the various factorsaffecting their usage.

• To our knowledge, no systematic synthesis of the stud-ies exists.

• As a result, there is no knowledge of a global picture.

What has this study added to the body of knowledge?

• A systematic review of 38 studies examining doctors’use of the Internet over 10 years.

• Consistently, doctors use the Internet more than theirnational averages, and their activities focus on the useof email, retrieving information from online journals,attending courses and conferences, receiving pro-fessional updates, and performing professional andadministrative functions; professional email with col-leagues and patients, however, is relatively low.

• The chief factors discouraging usage are time, work-load, cost, information-seeking problems, legal issuesand lack of skills, while the factors encouraging usageare patient satisfaction and demand, overall efficiency,and saving of time and money. Usage differencesbetween demographic groups do exist, but are equal-ising.

• Further consistently designed studies, particularly indeveloping countries are required to complete the pic-

r

technology in Southern California physician offices, J. Am.Med. Inform. Associat. 10 (2003) 484–493.

[11] N. Bennet, L. Casebeer, R. Kristfco, S. Strasser, Physicians’

ture.

countries needs to be addressed, efforts aimed at improvinginfrastructure for Internet access must be accompanied byefforts to overcome the other major obstacles. This is bothhighlighted by the theory, and demonstrated by the studies inthis review. A concentration on infrastructure only will resultin delays in doctors’ effective use of the Internet.

5. Conclusion

This systematic review has examined 38 studies of doctors’use of the Internet since the First WWW conference at CERNin 1994. Each of those studies has contributed informationto a larger picture of doctors’ Internet usage. The picture isnot complete, and the first fact highlighted by this review isthe real need for surveys and similar studies in other partsof the world. In addition, there is a need for consistency ofapproaches, so that more meaningful comparisons can bemade in future systematic reviews.

Diffusion of Innovations, Technology Adoption Model, and
the Unified Theory of Acceptance and Use of Technology havebeen used to shed some light on the results. This has allowedus to see that the most pertinent obstacles facing doctors whowish to use the Internet, such as cost, time and effort and
l i n f o r m a t i c s 7 7 ( 2 0 0 8 ) 4–16

the expertise required, are to be expected, and will need tobe addressed if the Internet is to contribute to effective healthcare delivery. They have also pointed to the possibility that theconflicting information regarding age and gender, is probablybecause of a transition period, and that equalisation will soonfollow.

The overall picture that has emerged so far, then, is one ofdoctors using the Internet far more than their national aver-ages, using email, obtaining professional information fromonline journals, attending courses and conferences, receivingprofessional updates and performing professional, adminis-trative functions. Those who have overcome the obstacles,often because of demand from their patients, have found thatit has improved overall healthcare delivery. In essence, in theshort space of time that the Internet has been easily accessi-ble through the Web, doctors have harnessed its power in boththeir personal and professional lives. All indications are thatthey will continue to do so.

Acknowledgements

I wish to thank Professor Jimmy Volmink for overall guidance,Mr. Rauf Sayed for assistance with the statistical analyses, andDr Dick Ng’ambi for additional comments.

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