General information Viacom, Inc. is an American media .docx

General information
Viacom, Inc. is an American media corporation that
mainly deals with cinema and cable television. At the moment,
market statistics place the company at sixth position in
broadcasting and cable companies based on revenue (Stempel,
2012). The company history traces its operations in the 1950s
when CBS Corporation (CBS) instituted a department that could
handle the syndication of various television programs it offered.
The current version of its business came into place in 2005 after
breaking off from CBS Corp. It is now comprised of multiple
networks such as Viacom Media Networks, Paramount Pictures,
and BET Networks. By the help of this brands, the company can
reach more than 700 million subscribers in more than 160
nations (Sweeney, 2008). The major stake control of the
company is Sumner Redstone together with CBS via its National
Amusements, Inc. Reporting of its operations and results is
done by the help of two major operating divisions; Filmed
Entertainment and Media Networks. The following unit
comprises 73% of the company revenues in the fiscal year 2014,
while the former fill the other part the balance by the various
businesses such as theatrical, home theater, and television
licensing (Fixmer, 2008).
Environmental analysis
Political
According to Rainey, (2016) together with the reviews
from Glassdoor, (2010) it is evidence that Viacom is
experiencing more of internal politics rather than politics from
the state. Rainey, (2016) reports that management groups from
various department rival due to downsizing activities by the top
management. Also, there is the issue of firing the most
experienced personnel to have other cheaper workforce options,
that is, new staff, to ensure they pay less for compensation. The
management fails to offers 'transferable skills' platform as it

says due to political influence that tend to deny the workforce
the needed support. Employees are therefore forced to learn
from an unforgiving curve unless they are very skilled. The
company needs to start giving some clear goals from the word
go to its staff more so on-job training. The management should
understand that the high turnover may be coming at the expense
of a damaging work culture. Most importantly, they should
communicate with its workforce whenever there is an abrupt
staffing change that seeks to ensure they encourage stability in
the company structure.
Technological
Being a media and entertainment company, Viacom has
employed a vast number of technologies and modern ones to
keep up with the completion. This technology has ensured that
its media networks are reaching it's multi-million worldwide
subscribers. Being the oldest film studio in America, it has
tested various techniques for many centuries to create many of
the most loved motion pictures and turn it into a major world
producer and supplier of filmed entertainment.
By the help of television and digital media technologies,
the company and its brands are now connecting with kids,
youths and adults as it assist them to develop original and
genuine content for the different audience groups. Also, Viacom
Media Networks forms the largest collection of ad-supported
cable networks in the country by audience share.
Social
Being a big company, Viacom has established itself as a
dominant force to reckon. Viacommunity, Viacom's corporate
social responsibility (CSR) unit has been doing a lot to leverage
the power of it's' brands to shift actions to more socially
inclined matters.
The unit partners with local and national agencies,
institutions, foundations, community groups, and corporations,
to address an extensive collection of issues and causes that

range from sustainability, HIV/AIDS to gender parity issues.
The company is the industry leader in handling complex
problems by transforming moments into movements. Every year,
Viacom have an international day of service where they invite
members of its workforce to give back to the societies in which
they operate and live. Additionally, the company has another
impressive move where it has committed itself to foster social
and environmental justice on a yearly basis by the help of
dynamic programming, wide-ranging actions as well as the
promotion of the current community programs (Glassdoor,
2010). Viacom's networks encompass various cultural audience
and workforce groups of all ages, races, backgrounds, sexual
status and genders. It is due to this reasons that the firm has
been devoted to celebrating diversity and advocate for
recognition and inclusion in ensuring each has a voice.
Legal
In 2015, the Paramount and VM Network units together
with legal affairs department restructured to ensure that legal
expertise is transferred across all business departments to give
lawyers a wider exposure and ensure that their expertise is more
widely deployed across the studio and television networks.
Currently, departmental task forces are focusing on wide-
ranging issues such as managing outside counsel, litigation,
diversity, automation, competition law and the art and craft of
the deal. The company is now automating most of its
workflows, such as payment of bills and tracking of deals and
deal terms and also launching online department portals to
rationalize daily connections that are becoming a model of the
organization (Spangler, 2016).
Porter analysis
Threat of entry
Among the most notable features that characterize a
competitive advantage are the barriers to entry into an industry.
A higher threat of entry is when the industry is too expensive
for new businesses to make entrants due to high barriers (Shaw,
2016). On the other hand, when the industry has reduced and

non-expensive barriers, then it becomes cheaper for a new
business to enter the market.
For the case of Viacom, high capital requirements are
meaning that a company needs to spend quite a hefty amount of
money to be in a position to compete in the market; this factor
affects Viacom positively. The mass media industry has a high
learning curve making new firms spend time and money to study
the market before they are well equipped to make entrants hence
a positive impact of Viacom competition. Also, economies of
scale help are one factor that helps organizations to lower their
cost when they produce the next unit of output as it will cost
less. When new firms enter the mass media industry, they will
incur the high cost of production since they have few customers
and hence smaller economies of scale. With Viacom boasting of
millions of subscribers and a vast scale of production, this
factor impact on it positively as it puts potential entrants away.
Having a weak distribution network translate to a more
expensive means of moving goods around while some
goods/services never reach the end customer. Viacom has built a
strong distribution network that positively affects it comparing
to new firms (Shaw, 2016).
Bargaining power of suppliers
For any company, cost saving is reliant on cuts of
purchasing price on the materials delivered by the suppliers.
Nevertheless, whether there is cost saving cost is essentially
dependent on the power of suppliers. If the firm is made to
purchase from a single or limited supplier base, then the
supplier (s) have bigger power during the negotiation of prices
(Hose, 2013).
In the mass media industry, there is a high level of
competition between suppliers which reduces the prices to
producers such as Viacom. Also, the availability of a diverse
number of substitute inputs makes sure that the suppliers have a
lesser bargaining power over producers as a result of the
competition between the substitutes with the competition
positively impacting on Viacom.

Bargaining power of buyers
A buyer often engages the seller in a price negotiation
especially when they purchase in large quantities and from a
smaller sized entity. A bigger company has many customers
which eventually increase its bargaining power as compared to
small companies who rely on few customers for survival (Shaw,
2016).
Viacom has a broad spectrum of customers and
distributors hence have a little dependence on either. This
ensures that the distributors have less bargaining power on its
products and services while customers lack bargaining leverage.
Also, its customers appear to cherish the company's products
making them pay more for these products and hence positively
impacting on its bargaining power. When there are large
numbers of customers, no one customer tends to have
bargaining leverage.
Threat of substitute products
This factor is often overlooked since issues of direct
competition are observed and monitored differently. However,
the potential new products/services may come to a surprise to
the existing businesses. Viacom is in an industry where
competitors produce different products and services, making it
difficult for customers to find comparable product or services
that will satisfy their needs. Also, there is a limited number of
substitutes making it difficult for customers to find other
products/services that meet their needs.
Rivalry among established firms
Having established local rivals is a key driver to the
formation and sustenance of a competitive environment. Rivalry
can be intensive when there is an increase in new entrants, a
high fixed cost of winning profit, and selling products and
services at the same. Few competitors translate to fewer entities
competing in the same market and resources which positively
impact on Viacom.
Description of product/service strategy
Viacom produces and distributes motion pictures, television

programming, as well as entertainment content using some of
the well-known and household entertainment brands. Their
strategic focus is on its audience to ensure they provide the
entertainment the consumers wants to experience, when and how
they want to experience it (Rainey, 2016). The major
components of their strategy include:
1. Enhancing and expanding their brands globally by creating
and acquiring new programming and channels, popular motion
pictures and other entertainment forms like video game
offerings.
2. To strengthen their relationships with their advertisers,
cable, online, satellite, and mobile partners, to work in
togetherness and come up with better ways of serving their
audience groups.
3. The keep on expanding and monetizing the online and
mobile entertainment platforms.
4. To rationalize their motion picture segment by the type
and some films produced, placing a focus particularly on
franchise properties and associated marketing strategies to
capitalize on global production, distribution, and digital
opportunities.
5. Come up with a continued operational discipline
throughout the business to ensure there is a generation of
efficiencies and effectiveness in executing their strategies.
In connection with the above efforts, Viacom intends to foster a
diverse and creative culture that will enable them to continue
developing unique and innovative content for the audiences to
maintain their position as market leaders.
Pricing strategy
Any business must make a decision on the type of pricing
strategy to use when selling its product and services. Prices are
set for various reasons, among them is to defend the business in
an established market or from new entrants, to advance its
market share within the current market, to make entrants into a
new market, etc. Viacom pricing strategy is engrossed on the
mere goal of maximizing its profitability for the goods and

services it offers the market. Pricing is there a critical
component in the theory of marketing strategy mix. Price assist
the consumers in viewing the standards of a firm based on the
price tag they place on their products hence contributing to the
creation of an exceptional reputation in that market. The
decision of the business on the price of its products as well as
the pricing strategies affect the decision of the consumers on
whether or not to make purchases (Hose, 2013).
Viacom slightly employs predatory pricing strategy
which intends to aggressively drive out competitors from the
market by capturing more market share and attaining high
economies of scale to ensure their product offerings, as well as
costs, are at the minimal hence making it difficult for competing
firms to catch compete in the market (Fixmer, 2008). Also,
being a dominant force in the market, it has widely adopted
price leadership where it's leading the way in determining
prices due to the limited competition. This strategy is focused
on generating a particular rate of return on its investments.
Advertising and promotion strategy
Advertising strategies are aimed at selling product and as
a communication means between the company and the
consumer. Such strategies intend to give consumers the
information they need to make a purchasing decision. On the
other hand, promotional strategies aim to harness an interaction
between the company and the consumers so that the company
can increase its sales by attracting more customers (Hose,
2013).
Viacom has embraced the vast number of advertising
strategies ranging from Print (e.g. newspaper), Audio (e.g.
radio), video (e.g. YouTube channel), World Wide Web (e.g.
click ad), direct mail and outdoor advertisements (e.g.
billboards). In a new development, Viacom announced a deal
that involves an advertising firm, where Viacom will be given
accessibility to Roku's audience data to allow the firm to offer
targeted advertising to its different audience groups. This deal
seeks to be a long-term advertising strategy that will help

Viacom to build its brand name and increase its sales over time
(Lynch, 2016).
Also, the company has employed various promotional
strategies such as Branded Promotional Gifts, After-Sale
Customer Surveys, Causes and Charity through Viacommunity
initiatives, Mail Order Marketing and Social media. All this has
assisted the company in promoting its product and service while
positioning it in a favorable light. More specifically, Viacom
has widely used the available social media platforms to promote
its products. In recent developments,Viacom's' marketing and
creative content unit has struck a deal with a technological
startup firm, Canvs to empower its social media marketing.
Canvs categorize social media comments into more than fifty
emotional classes and use a four million words and phrases
dictionary that is inputted into millennial slang and social
media short-hand (Spangler, 2016).
Distribution and logistics
Distribution and Logistics ensure that the storage and
allocation of goods are organized and that the right products
and services reach the intended destination on time and within
budget. Also, the unit ensures that issues of transportation,
warehousing, stock control, and flow of goods are well
monitored. Viacom has understood and integrated its entire
supply chain so that it can easily coordinate different affiliated
entities effectively and communicate with its suppliers and
distributors in an efficient manner.
Ad/Website/Social Media for product/service
Advertising being one of its product offerings, Viacom
has taken steps to offer advertisers a guarantee for the impact
the social media can give them. Using a program called
Echograph, Viacom will give clients the reach to data regarding
influencers, age, engagement, and gender as well as the
popularity of hashtag, etc. Echograph comes to back Viacom
Velocity, an integrated customized content unit that was
previously announced by the company that comes up with
branded content campaigns to be distributed across the various

networks it runs.
This means that Ads placed by Viacom will have its
viewers retweeting them and also adding their emotions while
gifting and sharing with friends, something which is not easy to
quantify at the moment. The ultimate goal for Viacom is to
move quickly and turn predictive on its social media platforms.
With the program at its early stages, the company is yet to give
out any formalized plans for what will take place in the case it
fails to meet the guarantees (Poggi, 2014).
In a different development, Viacom data scientists and
marketers are working hard to isolate the strong connection
between marketing and analytics and how it can use Ad and
social media data in a better way to meet its business goals.
Viacom has shared how the company is leveraging data to
stimulate growth and how its marketing unit is employing
advanced data products in the market.
Also, the previously discussed Viacom Velocity program
is a full unit that is dedicated to branded content. The unit is
working closely with the marketing department in the different
networks contained in Viacom portfolio. The main content part
of this division, creative solutions, aims to serve as a
knowledge base of new ideas while the other part intends to
work with the existing talent (Thielman, 2014).
Analysis of major competitors
Media Networks
Viacom media networks mainly compete with many
distributed cable networks, networks and digital distributors and
broadcast television. The media networks rival for advertising
revenue share with other broadcast and cable television
networks, other mediums like websites, social media, apps,
online platforms, print and radio programming (Sweeney, 2008).
Each and every programming offering faces competition for
audience share with respective competitors that target the same
group.
Filmed Entertainment
Viacom Filmed Entertainment sector competes for audience

share on motion pictures as well as other entertainment content
released by major studios, film producers, and entertainment
and consumer spending openings. The competitive position of
the company is primarily dependent on the quantity and quality
of the produced films, the distributed films as well as the
marketing success and public reaction. The company also
compete for the best talent to fill positions of producers,
directors, actors, writers, and even film scripts which are very
important to the success of the company (Spangler, 2016).
Competitors
In the two main segments that Viacom operates, some of its
competitors include; CBS Corporation, Time Warner Inc., Time
Warner Cable Inc., and Comcast Corp, Time Warner Cable Inc.,
Scripps Networks Interactive, Inc., Discovery Communications,
Inc., Walt Disney Co, Cablevision Systems Corp, and Twenty-
first Century Fox, Inc.
Market Share
Despite the deteriorating revenue, Viacom Inc. has an
increasing market share in the segments it operates as shown in
the table below:
Viacom and competitors market share and revenue figures
Company
Total Revenue
Market Share
Viacom Inc.
36.16 %
4.55 %
Cbs Corporation
49 %
6.18 %
Time Warner Inc.
15.76 %
4.93 %
Time Warner Cable Inc.
4.96 %

1.03 %
Comcast Corp
3.03 %
2.26 %
Scripps Networks Interactive, Inc.
69.32 %
1.93 %
Discovery Communications, Inc.
52.93 %
3.16 %
Walt Disney Co
16.08 %
8.17 %
Cablevision Systems Corp
2.18 %
0.14 %
Twenty-first Century Fox, Inc.
26.41 %
6.46 %
Graham Holdings Co
8.81 %
0.3 %
Source: (CSIM, 2016)
Company SWOT
Strengths
Entertainment Brands
Viacom has quite some network and film lines that meets
needs of consumers from different demographics. Event after
struggling in the market and capitalizing its content in the midst
of a changing consumer taste, the company has advanced on
upstarts and is poised to be the next mass media conglomerate.
After adding Pixar, Lucas film, and Marvel Studios, the
company has bolstered its position in the mass media market
(Harrington, 2015).
Weaknesses
Reliance on Cable Television

Similar to its competitors, Viacom is being challenged
by defies in cable programming sector. It younger audiences is
now shifting to other costs effective alternatives such as Netflix
and Hulu to enjoy similar programming and other media
platforms such as YouTube is continuing to pressure these old
guard media firms to streamline their strategies. Viacom is the
hardest hit with Media Networks unit being the biggest part of
its business. Viacom reported a $785 million write-down linked
to low ratings on most of its programs such as "Entourage" and
"CSI," leading to mass employee layoffs, consolidation of some
of its media units and a delay in the authorization of the $20
billion share repurchase.
Original Content
Viacom is struggling to come up with new television
franchises since the former CEO Mr. Freston left as he was the
one approving, South Park, The Real World, and SpongeBob
Square pants. The different networks are not able to come up
with other major entertainment franchise that can stimulate
ratings (Harrington, 2015).
Opportunities
International Growth
With the current shift of spending the domestic pay-tv
landscape with technology, there is a major growth potential to
be witnessed on an international scale. Viacom management has
shown its interest to increase its global presence by supporting
top-line growth over the years. The mushrooming media
markets in India and Africa are the primary target for a long-
term growth opportunity with the United Kingdom being the
next region of the firm's international expansion.
Digital Media
Viacom has shown that it will continue to develop its digital
media services to match the viewing trends. As depicted by its
platform agnostic strategic plan, Viacom has sought business
relationship from various non-Nielsen data firms. Some
researchers, like Rentrak, gather and sell data derived from
different platforms, and may, therefore, need help from Viacom

to offer services in matching advertisers with viewers, which
will auger well for the future of its digital media plans
(Harrington, 2015).
Threats
Cable Bundle coming to an end
In 2015, firms operating in the pay-tv market were forced
to deal with issues of poor ratings. In the beginning, the held to
the belief that a major migration is still years away. However,
after a series of substandard profits reports, most of them
including Viacom have compelled to reconsider this case as it
may be the end of the cable bundle.
Executive Succession
Sumner Redstone still has the voting power in the
company as so is the case with CBS. Corp. Lately, now aged 92
and absent from the public eye. The once most vocal defender
and advocate in the industry, the absence of Mr. Redstone are
stirring up increased uncertainty concerning the aging tycoon's
succession issue (Harrington, 2015).
Company Financial Analysis
Comparing the results of Viacom sales to that of its
competitors, the company has reported an increase in Total
Revenue in the second quarter of 2016 by 1.6 % with most of its
competitors experiencing reductions in revenues in the same
quarter. Also, with net margin standing at 14.16 % Viacom has
achieved higher profitability in the industry (CSIM, 2016). The
table below shows this and other financial insights.
Viacom Inc. and Competitors Financial Data
COMPANY NAME
REVENUE
NET INCOME
NET MARGIN
CASH FLOW
Viacom Inc.
12,397.00
1,493.00
14.16 %

-1,078.00
Graham Holdings Co
2,091.07
-80.03
9.73 %
-618.99
Scripps Networks Interactive, Inc.
3,337.52
939.53
26.14 %
-954.89
Cablevision Systems Corp
6,535.73
225.16
5.75 %
70.52
Discovery Communications, Inc.
6,472.00
1,193.00
24.3 %
-47.00
News Corp
8,292.00
250.00
4.9 %
0.00
Cbs Corporation
14,303.00
1,583.00
12.87 %
-144.00
Time Warner Cable Inc.
29,888.00
1,859.00
7.98 %
590.00

Twenty-first Century Fox, Inc.
27,326.00
3,016.00
9.12 %
0.00
Time Warner Inc.
27,903.00
4,056.00
13.68 %
-626.00
Comcast Corp
78,023.00
8,727.00
10.9 %
-679.00
General Electric Company
116,615.00
11,821.00
8.37 %
-42,039.00
APROX. MARKET
333,183.32
35,082.66
10.53 %
-45,526.36
Source: (CSIM, 2016)
Future Trends
Once a dominant force in Hollywood, Viacom-owned
Paramount, is currently enduring hard times due to stiff
completion from firms like 20th Century Fox and Disney's
Buena Vista (Lynch, 2016). However, going into the future, this
situation will drive the management of Paramount parent
Viacom, to pick up strategies that are deployed on struggling
businesses so that they reduce the exposure and raise profit
margins to offset its down debt .
With the impending digital explosion as the traditional

media conglomerates brace for the ultimate impact and badly
looking for survival strategies, the media businesses will
scramble to escape the disaster and enter the digital code
(Harrington, 2015). Viacom, which has been under scrutiny by
researchers at Wall Street and by the press due to the current
failures have started embracing the creative and technological
hurdles already, and the impending disruption may find it much
prepared to be among the companies that will survive.
Currently, Viacom argues that despite the struggling
networks, its brands is still dominant among the young
audiences (Yu, 2016). Going into the future, consumers will
stop using the cable bundles entirely, or shift to other skinny
bundles as they seek content. However, the young viewer's
group will remain hungry as it is harder for them to drop pay-tv
for other substitutes such as Netflix hence assuring Viacom
survival in the future.
Recommendations for the future
Based on its weakness, Viacom should develop its strategies
based on this weak points while embracing the growth
opportunities to ensure that it reclaim its position as the
industry leader. Some of the recommendations are as follows:
1. Viacom should reduce its reliance on cable television and
diverse its offerings to newer forms to ensure that it taps its
audiences who are now shifting to other cost effective
alternatives.
2. Viacom should invest in training and incubation of talents
to make sure that it handles its current problem of creating new
original television franchises such as South Park, The Real
World, and SpongeBob Square pants.
3. With the current shift of ending the national pay-tv
landscape with technology, Viacom should start embracing
international growth potential by venturing into mushrooming
media markets such as India and Africa.
4. Viacom should place more emphasis on developing digital
media content to match the viewing trends.
Conclusion

Viacom is evidently a dominant force in the mass media
and advertising market owing to its past success stories and
current wide subscriptions. However, most of its networks have
been faced with significant challenges that need to be addressed
to secure the future of the company. The current revolutions
such as the changing consumer preferences will continue being
a challenge due to the high investment in the old forms of
content delivery. Altogether, the experience, connections,
customer base and constrained industry will serve the company
well in its strategies of reclaiming its lost glory.
References
CSIM. (2016). Viacom Inc. Competitiveness. Retrieved from
CSI Market:
http://csimarket.com/stocks/compet_glance.php?code=VIA
Fixmer, A. (2008). Viacom May Pull Channels Off Time Warner
Cable in Contract Spat. London: Bloomberg.
Glassdoor. (2010). Viacom Reviews. Retrieved from Glassdoor:
https://www.glassdoor.com/Reviews/Employee-Review-Viacom-
RVW579175.htm
Harrington, R. (2015). Viacom, Inc.: A Short SWOT Analysis.
Retrieved from Value Line:
http://www.valueline.com/Stocks/Highlights/Viacom,_Inc___A_
Short_SWOT_Analysis.aspx#.WBNfyeB97IV
Hose, C. (2013). Promotional and advertising Strategies.
Retrieved from Small Businesses:
http://smallbusiness.chron.com/top-ten-promotional-strategies-

10193.html
Lynch, J. (2016). Viacom Strikes Advertising Deal with Roku as
Its TV Ad Revenue Falls. Retrieved from AdWeek:
http://www.adweek.com/news/television/viacom-strikes-
advertising-deal-roku-its-tv-ad-revenue-falls-171122
Poggi, J. (2014). Viacom Looks to Set Social Media Guarantees.
Retrieved from Advertising Age (Adage):
http://adage.com/article/media/viacom-set-social-media-
guarantees/292571/
Rainey, J. L. (2016). Viacom Finally Announces Philippe
Dauman Ouster, Thomas Dooley Promotion. Variety.
Shaw, L. (2016). Viacom Board Said to Plan Strategic Review.
Retrieved from Bloomberg:
http://www.bloomberg.com/news/articles/2016-09-07/viacom-
board-said-to-plan-all-day-strategy-review-hire-advisers
Spangler, T. (2016). Viacom to Track Emotional Responses to
Social Ads, Content. Retrieved from Variety Editions:
http://variety.com/2016/digital/news/viacom-canvs-emotional-
social-media-ads-1201687790/
Stempel, J., & Adegoke, Y. (2012). Viacom wins reversal in
landmark YouTube case. Reuters.
Sweeney, M. (2008). Google and Viacom reach a deal over
YouTube user data. London: The Guardian.
Thielman, S. (2014). Viacom Is Creating a Full Division
Devoted to Branded Content. Retrieved from Ad Week:
http://www.adweek.com/news/television/viacom-creating-full-
division-devoted-branded-content-155115
Yu, R. (2016). Viacom's future is as murky as management
turmoil. Retrieved from USA Today:
http://www.usatoday.com/story/money/2016/06/26/viacoms-
future-murky-management-turmoil/86349716/
Week Twelve: The Survey Says: Conducting a Descriptive

Research Study “Barriers to Accepting Health Information
Technologies”
Introduction: With the rapid transformation of the U.S. health
care industry,
today’s HIM (including health care managers) professional
requires an advanced
level of skill sets and training. This includes the basic ability to
conduct health
care research and analysis raw data in order to derive
meaningful information.
Conduct a descriptive research study on the assigned topic
“Barriers to Accepting
Health Information Technologies”.
Deliverables: The final product to submit at the conclusion of
week twelve (12), is
a six (6) to seven (7) page summary of your Descriptive
Research Study that
includes the following:
-
o Given the assigned research topic “Barriers to Accepting
Health
Information Technologies”, identify your independent and

dependent
study variable(s)
-
o State your hypothesis
Participants-
o Part I. Survey Design
ypothesis in the previous
steps, design a ten (10) question survey as it relates to the
assigned research topic “Barriers to Accepting Health
Information Technologies”. The survey must consist of a mix of
opened-ended and closed-ended questions
Determine your sample size
soliciting participants
o Part II. Creating a Cover Letter
following:
Purpose/Need of the study

and the plan to ensure the confidentiality, privacy and
security of the collected data
discarding the collected data
p Four: Obtaining UMUC’s Human Research Project
Notification &
Human Subjects Protection Approval
o By week eleven (11) submit your completed UMUC’s Human
Research
Project Notification & Human Subjects Protection Form to the
board
for final approval (In this case: Your Professor)

o FYI: UMUC’s Human Research Project Notification & Human
Subjects
Protection Form is an alternative to the Institutional Review
Board
(IRB) Application
o Submit a copy of your final draft in week twelve (12)
[Important Note in Regards to Steps One & Two- For the
running course
project, you are asked to identify variables in step one and
formulate a
hypothesis in step two. Note, you will not submit your work for
step one and
step two until you make the required submission for step three.
Please see
below for pointers on approaching step one and step two]
References & Resources
UMUC’s The Human Research Project Notification & Human
Subjects Protection
Form:
http://www.umuc.edu/policies/researchpolicies/research13026.c
fm
Sample Descriptive

Study:
http://library.ahima.org/xpedio/groups/public/documents/ahima/
bok1_023
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Creating an Descriptive Research Study Course Project
“Barriers to Accepting
Health Information Technologies”
Pointers for Completing Steps One & Step Two
For the running course project, “Barriers to Accepting Health
Information Technologies”, you are asked
to identify variables in step one and formulate a hypothesis in
step two. Note, you will not submit your
work for step one and step two until you make the required
submission for step three. Please see below
for pointers on approaching step one and step two:

Step One: Identifying the Variables
The instructions state, “Given the assigned research topic
“Barriers to Accepting Health Information
Technologies”, identify your independent and dependent study
variable(s).”
Please review page 44-45 of the Layman and Watzlaf text for
definitions of variables. Also refer to the
following links:
http://nces.ed.gov/nceskids/help/user_guide/graph/variables.asp
An example of an independent variable may be age or drug type
(e.g. a drug may be categorized as a
study drug or a placebo).
A dependent variable is believed to change based on the
independent variable. For example, weight
might be a dependent variable that changes based on a person’s
age. In the example of drug type, heart
burn could be a dependent variable. Heartburn may decrease if
the study drug is taken.
You may also want to do some further research on your own to
learn more about variables and variable

relationships. Variables may be numerical or categorical.
For this assignment, use the title “Barriers to Accepting Health
Information Technologies” to identify
independent and dependent variables that should be investigated
in the research survey that you will
create. Consider what types of relationships may occur between
these variables. You will produce
survey questions that further investigate these relationships.
Step Two: Formulate the Hypothesis
The instructions state, “State your hypothesis.”
Please refer to pages 251 – 253 of the Horton text and pages
207 – 209 of the Layman and Watzlaf text
for basic information on hypotheses. Also refer to the following
link:
http://nces.ed.gov/nceskids/help/user_guide/graph/variables.asp
http://www.psychologyandsociety.com/variables.html
http://socialresearchmethods.net/kb/hypothes.php
After you have a clear research topic in mind, have identified
independent and dependent variables, and
have considered relationships between these variables, you will

want to make a statement of what you
predict that relationship will be.
For example, based on the literature, I believe that weight
increases with age. Now I can convert this
statement into a hypothesis. My hypothesis is, “Weight
increases with age.” Since this is what I believe
to be true, this is called the alternative hypothesis, denoted H1.
The null hypothesis, denoted H0, is
what a researcher would actually test. A null hypothesis is
always going to support a status quo or
indicate that there is no difference or no relationship. For my
example, H0: “Weight change is
independent of age.”
Here are some generalized way of presenting your null (H0) and
alternative (H1) hypotheses.
If you are comparing categorical data,
If you are testing against a set value,

For this assignment, use your predicted relationship between the
independent and dependent variables
that you identified in step one to create a null and alternative
hypothesis.
Step Three: Designing A Research Survey & Soliciting
Participants
· Step Three: Designing A Research Survey & Soliciting
Participants-
· Part I. Survey Design
· Having identified the variables and hypothesis in the previous
steps, design a ten (10) question survey as it relates to the
assigned research topic “Barriers to Accepting Health
Information Technologies”. The survey must consist of a mix of
opened-ended and closed-ended questions
· Determine your sample size
· Discuss how you plan to pilot test the survey before soliciting
participants
· Part II. Creating a Cover Letter
· Create a one (1) page cover letter that discusses the following:
· An overview of the topic/study
· Purpose/Need of the study
· State the hypothesis
· The Expected Benefits
· Official Request for Participation
· Identify and explain any associated participant risk(s) and the
plan to ensure the confidentiality, privacy and security of the
collected data
· The Deadline to complete the survey
· The Data Retention Schedule and the process of discarding the

collected data
· Reference and Include an Appendix with Your Survey
· Closing Remarks (along with your contact information)
Health Informatics Research Methods:
Principles and Practice
Part 2: Chapters 3-8
Survey Research
Chapter 3
Overview of Survey ResearchChoose a topic of studyFormulate
criteria to develop questions about that topicCan explore a
disease, community, organization, culture, health information
system or software etc.Random sample of subjects chosen to
answer the questions in a standardized format
Overview of Survey ResearchDevelop the questionnaireDevelop
the cover letter that explains the study and directions for
completing the questionnairePretest the questionnaire for
validity and reliabilityDisseminate the survey via email, mail,
Web, fax or use the survey during interviews

Overview of Survey ResearchResearcher must choose the best
medium to disseminate surveyOverall goal of survey research is
to collect the most appropriate and accurate data that will
answer the questions pertaining to the research topic.
Survey CreationUse/Adapt Existing SurveysHealth Information
National Trends Survey (HINTS)Created a population-based
survey that tracked trends in the use of communication
technologies as a source of cancer information
Survey CreationUse/adapt existing surveys cont’dNational
Center for Health StatisticsNational Health Interview Survey
(NHIS)National Ambulatory Medical Care Survey
(NAMCS)Health Assessment QuestionnaireAdapt several
different questionnaires into one

New Survey DevelopmentNeed to consider the following
items:ContentAudienceMediumSample or survey entire
populationStatistics to be generated
Advisory CommitteeFocus group of experts in survey design
and the topic under studyAssist in phrasing the questionsMay
also seek assistance from organizations/departments which
provide assistance and guidance in survey design, development,
and analysis of resultsInclusion criteria
Types of QuestionsOpen-ended (unstructured or
qualitative)Close-ended (structured or
quantitative)Scales:Nominal OrdinalIntervalRatio
Pilot Test SurveyPilot test survey on a small group of

respondentsThe sample should reflect the true sample of
respondentsProvide accurate simulation of administration of
survey questionnaireReview all comments and discuss with
advisory boardIncorporate into final survey
Test Survey for ValidityFace Validity
Criterion-related validity
Construct validity
Content validity
Examines how survey looks
Accuracy of intended
survey
Agreement between theoretical concept and survey
Survey captures the information intended to measure
Test Survey for ReliabilityReliability or consistency of
surveyReliability Coefficient : Cronbach’s AlphaMeasures
whether survey has internal consistency—Do all variables
measure the same concept?Should be measured on an interval or
ratio scaleNormally distributedReliability Coefficients close to
1.00 have very high internal consistency or reliabilityTest-

Retest for ReliabilityMeasures whether survey is consistent
over time or when given multiple timesCorrelation coefficient
between the relationship between two total scores given two
different timesThose coefficients close to 1.00 show strong
reliability.
Factor Analysis in Refining SurveySometimes researchers need
to refine the number of questions used in a survey.Factor
analysis is a statistical technique in which a large number of
variables are summarized and reduced down to a smaller number
based on similar relationships among those variables.
AudienceNeed to know your audience so that questions on the
survey can be built so that they are able to answer themUse
clear, unambiguous terms Do not use terms that are unclear,
such as “not sure”Pilot test the survey to capture terms that
should not be included in the original development of the
survey
Framing of QuestionsOrder of questions is
importantDemographic data is usually first, followed by more
broad or general questions, followed by more specific questions
with ranked or ordinal type responses or open-ended type
questionsProvide a checklist of possible responsesHIPAA
Privacy Rule Implementation Study by Firouzan
IncentivesConsider whether incentives should be provided to

individuals who complete the surveySome incentives may
influence responses so be careful when choosing the type of
incentiveResearcher should decide if it is necessary and what
type of incentive should be used if any
Confidential ReponsesDiscuss how the individual’s responses
will be kept confidential in the cover letter or
instructionsInstitutional Review Board (IRB) will also need to
see how information collected will be kept
confidentialExamples: individual non-identifying number and
password can be part of the URL in a Web-based survey, no
identifying information linked with survey, separate database
used to collect demographic information but not linked to
responsesAll information reported in presentations and
published material should be reported in aggregate form
LimitationsEvery study design has limitationsSurvey research
design includes the following limitations:Inaccurate responses
due to:Not understanding the question or instructionsNot having
appropriate time to complete the surveyNot able to recall past
experiences to answer the questionToo long and respondents
may tire May exaggerate responses to questions—i.e. salary
Reduce Limitations ByAsk questions that: are unambiguousDo
not require extensive recollectionJog the respondent’s memory
with pictures, graph, table etc.Provide ranges to choose from
especially if the question is more sensitive in nature

Type/MediumWeb-basedEmailMailFaxGroup
Web-based SurveysAdvantages:Reduced cost when compared to
paperLittle or no data entryEase of data analysisUse of pop-up
instructions and drop-down boxesAbility to present questions in
random order(Gunn, 2002)
Web-based SurveysDisadvantagesMissing respondents who do
not have a computer or access to InternetIncreased up front time
in the development of the questionnaireHire a person with skills
in Web-based survey design and developmentDifficult making
changes to survey once on the WebRespondents more reluctant
to provide responses over Internet due to lack of confidence in
privacy and security
Other Types of SurveysMail—Still used effectively in health
informatics especially when surveying physicians, nurses and
other health care providersEmail—very similar to Web-based
surveys but time to develop may not be as extensive, however,
automatic response to database is limitedFax---Similar to mail
surveys and can be used so that one captures all possible
respondentsGroup---Paper survey made available to participants
at a conference, retirement community, physician practice etc.
Examples of Survey Research in Health InformaticsEHR/ASTM
study by Watzlaf et al, 2004 used all types of surveys (Web-
based, mail, fax, group) with the major focus being Web-based.
Intent was to increase response rate using all types of

medium.Criswell et al, 2002 used mail surveys to determine if
physicians in family practice residency programs used PDAs
Examples of Survey Research in Health InformaticsMurff et al,
2001 used mail surveys for physicians to determine their
satisfaction with using two different CPOE systems. Used the
Questionnaire for User Interface Satisfaction (QUIS).Patel et al,
2005 used both survey and face-to-face interviews to collect
pre-and post-course data on students enrolled in the Woods
Hole Course in Medical Informatics. Interviews were used to
supplement the survey questions.
Examples of Survey Research in Health InformaticsCouper et
al, 2007 used both mail surveys and phone interviews to collect
data on weight management and also were interested in which
method produced a better response rate. Results: phone
interview (59% response rate) and mail (55% response rate).
Distribution of SurveyResearcher should determine HOW the
survey will be distributedEmail or phone each of the
respondents selected to participate and explain the purpose of
the study and their roleAsk if they are willing to
participateDetermine the best way to send the survey and obtain
contact information for themAssure respondent that their
answers will be kept confidential and that only aggregate data
will be used when reporting results

Distribution of SurveyDiscuss the cover letter contentDiscuss
incentives if they are usedOnce the respondent agrees to
participate, contact them via email, mail, fax, etc. and provide a
copy of the cover letter and survey.Make sure that the deadline
date to return the survey is bolded in the cover letter (See
Appendix 3C for sample of Cover Letter)After 2 weeks with no
response, send Follow-up letter and reiterate the importance of
study and the need for their participation. (See Appendix 3E
for sample of Follow-Up Letter)
Sample and Sample SizeMost survey research is performed on a
sampleCensus survey includes the entire populationIf a sample
is chosen, make sure that it includes an accurate representation
of the population under study. In this way, the characteristics
of the sample participants are similar to the population
characteristics.
Sampling MethodsStratified Random Sampling—separate the
population by certain characteristics such as physician
specialty, nursing units, DRGs, and then choose the
sampleSystematic Random Sampling---draw the sample from a
list of items such as diagnoses, I9 codes, or discharges and
select every nth case
Sampling MethodsCluster Sampling—separate first into a city
block, randomly choose residences and then sample everyone
within that residenceConvenience Sampling—not random, can
generate quick results but the results should not be generalized
to the population. Example: When one surveys everyone in a
specific HIT department to determine their knowledge of HL7

Sample Size CalculationRefer to Table 3.5 and pages 68 and 69
for an Example of the Sample Size Calculation for the EHR
study by Watzlaf et al, 2004.
Response RateVery important in survey researchEven a low
response rate may prove beneficial if it is in an area or topic
that has not been researched in depth before
Response RatesMethods used to increase response rates
include:Follow up letters, emails, phone calls, faxDo not be
overly annoyingInclude the title of the research study, when the
survey questionnaire was sent, the importance of the study, and
how important the respondent’s reply is to the research
studyReiterate how data will be kept confidentialExplain any
incentivesAttach survey again –do not make the respondent look
for previous survey sent
Statistical Analysis of Survey Study DataUsually quite
simpleFrequencies and percentagesCorrelation
coefficieintsTests of significanceConfidence IntervalsOpen-
ended questions should be analyzed using content analysis
Examples of Statistical Analysis of Survey Study DataSee
Tables 3.6 – 3.12 for a simple data display for the EHR study by
Watzlaf et al, 2004.

SummaryDevelopment of survey instrumentNew survey or adapt
existing oneAddress the following areas:ContentAudienceHow
Administered (Type/Medium)Sample or PopulationType of
Statistics
SummaryChoose advisory committee of experts to review the
surveyDetermine the different types of questions and response
types or scalesPilot Test the surveyFeedback reviewed with
Advisory CommitteeMake changes based on the pilot survey
SummaryValidity and Reliability TestingCronbach’s alphaTest-
Retest Factor AnalysisOther issues to considerIncentivesHow to
maintain confidentialityMinimize bias or error Increase
response rate through follow-upAppropriate statistical analysis
Health Informatics Research Methods:
Principles and Practice
Chapter 4

Outline of DiscussionObservingWhy do Observational
ResearchNon-ParticipantNaturalisticSimulation—UsabilityCase
StudyFocused InterviewInformal ConversationalStandardized
Open-EndedGeneral Interview GuideFocus GroupParticipant
ObservationEthnographyContent Analysis
ObservingTake a minute to observe something near you. It can
be anything on your desk, in your office or home.Look at its
color, shape, function, age, etc.Jot down some information
about it. Let’s discuss
IntroductionQualitative
researchPerceptionsInteractionsFeelingsAttitudesDepth
Why choose Observational Research?New topicTransitional
programBackground for larger studyRobust, rich
dataObservation, field interviews, medical record reviews,
ethnographic methods, combination of all
Attention ToObservation siteTime periodWhat will be
observedHow it will be recordedWho will conduct the
observationHow data will be analyzedHow results will be
disseminated

Non-Participant ObservationNon-Participant Observation
Observes actions of study participants with limited interference.
Example: Observing how employees react to a new
documentation software system
Three types: Naturalistic observation, simulation observation,
case study
Naturalistic ObservationObserving behaviors or actions that
occur naturally in the environmentUseful to see if study
participants are following a procedure, rule, law,
policyParticipants should not know what the researcher is
observing or when in order to simulate the “normal”
environment.
Naturalistic Observation Example
We examined the reasons for underutilization of the cancer
registry
Informal discussions with physiciansNaturalistic observations
of cancer registrySemi-structured interviews with physicians
and nursesCompile data to enhance the new cancer registry
software system
Can anyone think of another example of naturalistic observation
in HIM?
Simulation ObservationNaturalistic observation conducted in
environment created for participantsHackett, Parmanto et al,
2007 dissertation research observed individuals with visual
disabilities using different websites chosen for the participants.
Goal is to see if the transcoder is effective in improving

websites for individuals with visual disabilities. Usability
study---different tasks developed
Usability StudiesHow fast can the learner use the PHR system
(Ease of learning)?How fast can the learner accomplish the
tasks? (Efficiency of use)? How effectively can the user learn
the PHR system upon several different uses?
(Memorability)How often do errors occur, how serious and what
do users do to manage the error? (Error frequency and
severity)How much does the user like using the system?
(Subjective Satisfaction)
(Hackett et al, 2007, Dissertation Research, An Exploration into
Two
Solution
s to Propagating Web Accessibility for Blind Computer Users)
Case StudyNon-participant observationIndividual, group,
institutional case studyCollects demographic, disease, religious,
social, cultural, technological system and software, community
etc.Field notes, tape recordings, video, images, etc.

Examples Case StudyWho can provide an example of an
individual, group or institutional case study?
How does the case study differ from the ethnographic analysis?
Focused InterviewInformal conversational
Standardized open-ended
General Interview guide
Informal ConversationalNo set questions developed, moves
forward based on what the study participant would like to
discuss
Example: What is the meaning of living with dementia while in
a nursing facility? Other examples in HIM?
Standardized Open-EndedSpecific questions are used to

interview the study participants
Example: Used to study automated coding software and the
potential to decrease fraud and abuse---See examples
Examples of Standardized Open-EndedAutomated Coding
Study:Government:What problems do you foresee in relation to
fraud and abuse when the Electronic Health Record (EHR) is
used?Are you aware of incorrect coding or abuse detected with
Natural Language Processing (NLP)? If you are familiar with
the approach of the NLP, was it a rules-based approach or data-
driven approach? Please describe.
Examples of Standardized Open-EndedVendorWhat type of
automated coding system do you provide?When was your first
installation of the automated coding system? How many
installations (users/clients) do you have and in what
settings?What is the average installation and training time?

Examples of Standardized Open-EndedUserWhat is the level of
accuracy on coding and billing?How is the automated coding
system used with the EHR?How is the automated coding system
used within the coding and billing process?What are the anti-
fraud features available and how do they link to the automated
coding system?
Other Examples—Standardized Open-EndedOther examples of
how the standardized open-ended interview could be used in
HIM?
General Interview GuideOutline of issues is used to conduct the
informal interview
Examples: Medical schools used the general interview guide to
reassess team based learning. Other examples in HIM?
Focus GroupA focus group is a group of subjects, usually
experts in the particular area of study, who are brought together
to discuss a specific topic.

Example: Focus group of experts used in evaluating ICD-10-CM
and its effectiveness in capturing public health related
diseases—See example
Example of Website Tables – Alzheimer’s progression
Step 1
Step 2
Step 3
Questions
1.After review of the public health diagnoses reportable list, are
there any diagnoses that should be added, deleted or changed?
If so, please explain.
2.Do the hypotheses and explanations that relate to the coding
of the reportable diagnoses provide enough information so that
changes to the coding system can be made? If not, please
specify which sections need further detail.
3.Do the ranked scale data and explanations related to
differences in the ICD-10-CM and ICD-9-CM coding systems

make sense? Do you need additional information to clarify any
cases? If so, which ones.
4.Based on the information provided to you, what
recommendations do you have to improve the ICD-10-CM for
public health reporting?
Focus GroupOther ways focus group can be used in HIM
Participant ObservationObserver part of environment being
observedWill true feelings etc. be observed when participant is
also observer?
Example of Participant ObservationHofler et al, 2005 HIPAA
compliance
EthnographyDelving into a particular culture or organization in

great detail in order to learn everything there is to know about
them and to develop new hypotheses.
EthnographyNot objectiveIncludes opinions of researcherNo
two ethnographers will examine a specific culture or
organization the same wayFocuses on people, culture, life
Field NotesBrief notes written at field siteDescription
(everything researcher can remember about the event such as a
meeting, encounter etc.)Analysis (linking step 1 & 2 to research
questions)Personal viewpoints
(Hall, 2007)
EthnographyCan include both qualitative and quantitative
approachesParticipative and non-participative methodsWith
participative: extensive field notesOpen-ended and unstructured
interviewsDocuments pertinent to setting

Ethnography--Cyclical
Develop
Tentative
Hypotheses
Review
Literature
Collect Data
Analyze Data
Revise tentative hypotheses
Create new hypothesis
Day in the LifeLet’s discuss our ethnographic examples

Ethnography QuestionsWhat parts of the ethnography did you
find the most difficult to collect and why?Do you think the
ethnographic method is a good way to collect research data?
Why or why not?Do you think the ethnographic method is the
best method to use when collecting observational research data
related to health care and health informatics? Why or why not?
Analysis of DataContent AnalysisExamine textual data to detect
recurrent terms and emerging themes reflective of culture or
facilityExamplesAutomated coding study
Constant Comparative MethodGrounded TheoryComparing
incidents applicable to each categoryIntegrating
categoriesDefine the theoryWriting the theory
Example--CCMTang, 2007—Patients with Colorectal
CancerOpen analysis of interviewsTranscripts read and words
reflected respondents’ ideas and thoughts labeledPatterns
derived from actual wordingCategorizations developed from

interpretation and grouping of codes Words with similar
meaning grouped into categories for further analysisGrouping
categories developedAll information reflected back to theory or
objectives of study
Software
Content AnalysisCount word frequenciesCategory
frequenciesCluster analysis—groups together words used in
similar contextsCo-word citation—examines occurrence of pairs
of wordsMay be expensive and require training
SummaryNon-Participant Observation: Observes actions of
study participants with limited interference. Example:
Observing how employees react to a new documentation
software systemParticipant Observation: Researcher is a part of
the environment he or she is observing Example: Used to assess
how well employees in health care facilities abide by HIPAA

SummaryNaturalistic: One example of non-participant
observation in which behaviors and events are recorded as they
occur naturally in the normal environment Example: naturalistic
observations conducted to determine whether the cancer registry
is underutilizedSimulation: Observing participants in an
environment that has been created for them rather than their
normal environment Example: observing individuals with visual
disabilities use different websites to determine if the websites
are accessible.
Summary
Case Study: Non-participant observation when the researcher
wants to thoroughly assess an individual, group, or institution.
Individual: Record and collect as much information as possible
about a particular individual as they progress through a certain
disease, procedure, treatment, cultural or system change.
Example: individual patient is followed and evaluated to
determine how they use an assistive technology device.
Group: Very similar to individual case study except that
interviews or observations are conducted on a group of
individuals

Example: Assessing the moral reasoning skills of medical
students using ethical issues.
Institutional: Observing a particular health care institution or
facility to determine how it conducts a particular process,
system or procedure.
Example: Department of Veterans Affairs health care system
used the institutional case study method to describe how their
electronic health record system is used in home-based primary
care programs
SummaryFocused Interview: Interview used in observational or
qualitative research in to collect in-depth, rich, robust
information. Focus group: Group of subjects, usually experts in
the particular area of study, who are brought together to discuss
a specific topic.Example: Focus group of experts used in
evaluating ICD-10-CM and its effectiveness in capturing public
health related diseases.Informal conversational: No set
questions developed, moves forward based on what the study
participant would like to discussExample: What is the meaning
of living with dementia while in a nursing facility?Standardized
open-ended: Specific questions used to interview the study
participants.Example: Used to study automated coding software

and the potential to decrease fraud and abuseGeneral interview
guide: Outline of issues used to conduct the informal interview
Example: Medical schools used the general interview guide to
reassess team based learning.
SummaryEthnography: Delving into a particular culture or
organization in great detail in order to learn everything there is
to know about them and to develop new hypotheses.Example:
Used to assess interactions between physicians and patients
when using the EHR.
Questions
Experimental and
Quasi-Experimental Research
Chapter 5

ExperimentBegin with a hypothesisTest itRefine hypothesisTest
againReach conclusionsTry to establish cause and effect
Experimental ResearchMost powerful when trying to establish
cause and effectExpose participants to different interventionsIn
order to compare the result of these interventions with the
outcome
Independent VariableThe intervention or factor you wish to
measure in order to determine if it will have an effect on the
outcome or disease under study.Examples: medications, diet,
exercise, education, health information system
Dependent VariableThe outcome, end point or disease under
studyExamples include: survival time for patients with cancer,
reduction of pressure sores in patients using specific type of
wheelchair, decrease in the number of adverse events in health
care facilities using a CPOE

Dose-Response Relationship
Experimental research also tries to determine a dose-response
relationship.
If a new medication has slowed the progression of cancer, will a
higher dose slow the progression even faster?
Or if a specific factor is removed from the environment it may
also decrease the progression of a certain disease.
*
Use Experimental ResearchConsider the following:
Eligibility of appropriate participants
Randomization
Ethical Issues

Quasi-Experimental ResearchSimilar to experimental research
but does not include randomization of participants.Independent
variable may not be manipulated by the researcher, and there
may be no control groupIt may be used over time with
something other than individual participants
Example of Quasi-Experimental ResearchStudy the effects of
automated coding system to determine if there is an increase in
hospital reimbursement before and after the system is
implementedStudy the cost/benefits of using an EHR before and
after its implementation. Cost/benefits of a paper-based system
is compared to the cost of an EHR in all HIM functions.
R = randomization
O = observation
X = intervention
Overview of Experimental Research DesignsStudy
DesignCharacteristicsDiagramPretest-posttest control group
methodRandomly assigned to intervention or non-intervention
(control) group

Pretests given to both groups
Posttests given to both groups after interventionR---O---X---O
R---O--- ---OSolomon four group methodTwo intervention
groups
Two control groups
Randomization used to assign to all four groups
Pretest for one pair of intervention and control groups
Same intervention used in both groups
Posttest used in all four groupsR---O---X---O
R---O--- ---O
R--- ---X---O
R--- --- ---OPosttest only control group
methodRandomization used for assignment into intervention and
control groups
No pretest given
Intervention given to one group only
Posttest given to both groupsR--- ---X---O
R--- --- ---O

Overview of Quasi-Experimental Study DesignsStudy
DesignCharacteristicsDiagramOne-shot case studySimple design
One group
Intervention
Posttest ---X---OOne group pretest-posttest methodOne group
Pretest
Intervention
PosttestO---X---OStatic group comparison methodTwo groups
Intervention
No intervention
Posttest for both groups ---X---O
--- ---O

ElementsRandomizationWhen study participants are randomly
chosen to be in the experimental, control, or comparison group
using a random method, such as probability sampling, so that
each participant has an equal chance of being selected for one
of the groups.Intervention = experimental groupNo intervention
= control groupDifferent intervention = comparison group
Example RandomizationResearcher may be interested in
determining whether individuals retain more if they do higher
levels of exercise before they learn how to use the PHR. Three
different groups of participants will be established. First group
will run for thirty minutes before sitting down in front of the
computer to learn to use their PHR, Second group will walk for
thirty minutes before learning to use the PHR, Third group will
not do any type of exercise before learning to use the PHR.
Therefore, the first group is called the experimental group, the
second is called the comparison group and the third is called the
control group and randomization will be used.

Example Randomization cont’dDevelop a list of all the study
participants and number themPick out each number and allocate
to a particular group. For example, the first number drawn will
go into the experimental group, the second number to the
control group and the third number to the comparison group and
so forth until all the numbers are drawn and participants
allocated. The goal is to have the experimental, control, or
comparison groups as similar as possible except for the
intervention under study. Randomization techniques can be
performed using statistical software programs
Comparison GroupMay be unethical to withhold a certain
intervention from one group of participants, Some experimental
research studies do not contain a control group but instead use
two comparison groups. The intervention under study is still
used but all members of the study are receiving some type of
intervention. For example, if researchers are assessing the
effect of using RHIOs to decrease the incidence of hospital-
acquired infections in four nursing facilities in a particular
region, then two of the nursing facilities will use the RHIO

based data and two of the other nursing facilities will need to
utilize some other type of database in order to minimize the
unethical consequences of not providing any type of data.
Cross-over DesignA cross-over design can also be used to
minimize the unethical effects of not providing certain types of
interventions. It includes using one group of participants as
both the experimental group and the control group. A group of
participants start out by being assigned to the experimental
group and receive this intervention for a certain period of time,
such as 6 months or a year. After they receive the intervention,
they cross-over to receiving no intervention or another
comparison intervention for another 6 months to a year.
Example Cross-over DesignMay be used when studying whether
certain types of telerehabilitation will improve the outcomes of
patients with multiple sclerosis. Patients may start out using
sensors and body monitoring and then cross-over to using a
PDA or the traditional in-house therapy monitoring in order to
monitor their functional levels after treatment. The same group
is used as the control (or comparison group) and the

experimental group.
ObservationPretest—observing the experimental and control or
comparison groups before the interventionPosttest—observing
the experimental and control or comparison groups after the
intervention
Examples ObservationBlood pressure taken before and after the
administration of medication, diet, or exerciseQuestionnaire
given to determine levels of depression before and after a
medication intervention. Observing a group of individuals
before the administration of a policy or procedure change and
then observing them again after the change has been in place for
one month. Other types of observations are not administered
before or after the intervention but during the middle of the
particular study. These observations are called midtests.
Other observations may be conducted several months or years
after the intervention ends to determine its long term impact.
Other observations may be conducted throughout the study
period as a new policy or law is implemented. These are called

time-series tests. For example, a researcher might use the time-
series test to examine the number of breaches of confidentiality
after the implementation of HIPAA. These rates could be
compared to rates before HIPAA was implemented.
Control GroupUse of the control group allows the researcher to
determine if the effect seen is really due to the intervention and
not other extraneous factors or confounding variables. In
clinical trials when medication is being tested as the
intervention, the control group is given a placebo so that they
are as similar as possible to the intervention group but not
receiving the medication under study.
TreatmentTreatments or interventions are also the independent
variable. Use of experimental medications, changes in an
individuals’ behavior such as smoking or alcohol cessation, or
changes in a particular assistive device, technology, software or
system. Should be administered in the same way for all
participants in the experimental group. For example, if physical

therapists are going to be educated and trained on-line in using
a new rehabilitation EHR system, the level (hours of training),
quality (content of the on-line education and training), and
hands-on application (amount of time using the EHR system)
should be the same for all physical therapists in the
experimental group. The control group may consist of those
physical therapists that will receive the traditional in-class
education and training. The hypothesis is that those physical
therapists trained on-line or with distance education will be the
same or better than those trained using the in-class method.
Experimental Studies
Pretest/Posttest Control Group Method
Similar to the randomized controlled trial (RCT) or clinical
trialPretest-posttest control group method provides an
intervention that may include a specific program or system
change than a medication or treatment. Participants are
randomly assigned to either the intervention (experimental) or a
non-intervention (control) group. Control/Comparison group
may receive a different intervention other than the one under

study. Pretests are given to both groups at the same time to
assess their similarities and differences. Posttests are given to
both groups to determine the effect of the intervention.
Example in Health InformaticsShegog et al, 2001---Assessing
the impact of a computer-assisted instruction (CAI) program on
factors related to asthma self-management behavior.Baseline
data collected on asthma self-management skillsChildren in
experimental group used CAI programOne week later post-test
data (assessment of asthma self-management skills and attitudes
toward CAI collected
Solomon Four-Group MethodTwo experimental groups which
both receive the intervention One group receives a pretest and
posttest while the other experimental group receives a posttest
only. Two control groups are also used in this designOne
control group receives a pre and posttest while the other group
receives the posttest only. All participants are randomly
assigned to the groups. This method controls for pretest
exposure but also requires more time, effort and cost due to the
additional groups.

Example of Solomon Four GroupAdaptation of the Solomon
four-group design was used by researchers evaluating the
effectiveness of a multi-media tutorial in the preparation of
dental students to recognize and respond to domestic violence
(Danley et al, 2004). First experimental group of dental
students was randomly assigned to take the pretest, the tutorial
(intervention), and then a posttest. The second experimental
group first took the tutorial and then the posttest. The third
group (control group) took the pretest and then the posttest.
Posttest-Only Control Group MethodParticipants are randomly
assigned to an experimental group or a control group and
posttests are the only means of observation. No pretests are
used. This is done to reduce the effect of familiarity with
exposure to a pretest. Not using a pretest eliminates the ability
to assess an improvement in scores from before the intervention
to after the intervention.

Example of Posttest-Only Control Group MethodThe
experimental posttest only control group method was used by
researchers assessing the effect of community nursing support
on clients with schizophrenia (Beebe, 2001). 24 participants
randomly assigned to control group (routine follow-up care and
informational telephone contact at 6 and 12 weeks) and
Experimental group(weekly telephone intervention plus routine
follow-up care for 3 months). All were followed for 3 months
after hospital discharge to determine the length of survival as
well as frequency and length of stay for re-hospitalizations.
Quasi-Experimental Studies
One-Shot Case StudyThis study is a simple design in which an
intervention is provided to one group which is followed forward
in time after intervention to assess the outcome (posttest). No
randomization, no control group, and no pretest is includedNo
baseline measurement to provide a comparison to the
intervention outcome.

Example of One-Shot Case StudyResearchers conducted a quasi-
experimental one shot case study to determine if an automated
two-way messaging system will help HIV-positive patients
comply with complex medication treatments (Dunbar et al,
2003). 19 HIV-positive patients enrolled and received two-way
pagers that included reminders to take all medication doses and
follow any dietary requirements. No control groupOutcome
measures consisted of the number of times participants reported
missing one or more medication doses, medication side effects,
and participant’s satisfaction level in using the messaging
system.
One-Group Pretest-Posttest Method
Similar to one-shot case study except that the pretest is used
before the intervention. No control group and no randomization.
Used when it is unethical or inappropriate to withhold the
intervention from a group of participants.
Example of One-Group Pretest-Posttest MethodResearchers

assessed the timeliness and access to healthcare services using
telemedicine in individuals aged 18 and younger in state
correctional facilities (Fox, et al, 2007). Data were collected
one year before implementation of the telemedicine program
and two years after implementation. The telemedicine
intervention consisted primarily of remote delivery of
behavioral health care services. Timeliness of care and use of
healthcare services before and after telemedicine
implementation was examined. The data was collected
primarily from medical records and other claims and
information assessment logs.
Static Group Comparison
Two groups are examined; One with the interventionOne
without the interventionPosttest is given to assess the result of
the intervention.There are no pretests and no randomization but
a control group is used.

Example Static Group ComparisonResearchers assessed the use
of alcohol in patients after a traumatic brain injury (TBI) based
on patients’ and relatives’ reports (Sander et al, 1997). This
study examined the validity of patients’ reports by comparing
them to relatives’ descriptions of post-injury alcohol use. In
this design, researchers use the brain injury as the intervention
and then assess via a post-injury questionnaire whether drinking
habits as perceived by the patient with the TBI and the close
relative are similar or different.
Internal and External Validity
Internally validity demonstrates that the dependent variable
(outcome measure) is only caused by the independent variable
(intervention) rather than other confounding variables. External
validity is concerned with being able to generalize the results to
other populations
(Campbell and Stanley, 1963).

Factors Affecting Internal Validity
HistoryHistory or the events happening in the course of the
experiment that could impact the results. Researcher collects
level of functioning data on hip replacement patients before
and after the use of a new physical therapy device. During the
time that this device is being used, the developer becomes ill
and unable to fully train all physical therapists in its proper use.
Therefore, the study may be affected by inadequate time in
training rather than the device itself.
MaturationMaturation and refers to the natural changes of
research subjects over time due to the length of time that they
are in the study. For example, older individuals may become
very fatigued after completing a training session on using a
computer to manage their finances. Their fatigue could then
affect their responses on the posttest.

TestingTesting is the effect created once exposed to questions
that may be on the posttest. For example, participants of a
study that is assessing whether a course module on the use of
privacy and security within the electronic health record (EHR)
improves their knowledge content of this subject, use a pretest
and posttest to assess whether there is improvement due to the
course module. However, since the students are already
exposed to the pretest and are able to think of some of the test
questions, they may change their answers on the posttest and do
better by learning from the pretest. Therefore, the use of the
pretest is what may be causing the improvement in test scores
more so than the course module on privacy and security of the
EHR.
InstrumentationInstrumentation--Changes in instruments,
interviewers, or observers may all cause changes in the results.
For example, interviewers may probe for answers more from
one individual they are interviewing more so than others, if
training is not performed consistently across all interviewers.

Statistical RegressionStatistical regression or regression toward
the mean is when extreme scores of measurement tend to move
toward the mean because they have extreme scores, not because
of the intervention under study. For example, coders who
performed poorly on the ICD-10-CM coding exam are selected
to receive training. The mean of their posttest scores will be
higher than their pretest scores because of statistical regression
not necessarily because of the ICD-10-CM training session.
SelectionSelection is when there are systematic differences in
the selection and composition of subjects in the experimental
and control groups based on knowledge or ability. For example,
one group of subjects who have viewed an instructional video
on how to give themselves insulin injections is compared to
another group which has not watched this video. No
randomization is used.

AttritionAttrition is the withdrawal of subjects from the study.
Those individuals who leave a study can be very different than
those who remain in the study and the characteristics of these
individuals can affect the results. For example, a study which
focuses on trying to reduce the number of incomplete medical
records due to incomplete nursing documentation have 15
nurses leave the experimental group and 2 nurses leave the
control group. The 15 nurses who leave the group may be very
different than those who remain in the experimental group.
Also, the difference in the numbers of nurses who leave each
group may be a problem.
Interaction
An interaction of factors or a combination of the factors

discussed above may also lead to bias in the final results.
Therefore, the researcher needs to be aware of the effect of a
combination of some of the factors discussed above and their
impact on internal validity
(Shadish and Cook, 1998, Key, 1997, Shi, 1997).
Factors that Affect External ValidityTestingSelection
biasParticipants are chosen who are frequently under medical
careVolunteersParticipants who receive compensationAll may
be different than the general population
Control for Internal and External ValidityRandomization—most
powerful to control for selection, regression to the mean,
interaction of factors, improves external validity because
subjects are not pre-selected but uses random assignmentUse of
control or comparison groups---help control for effects of
history, maturation, instrumentation, interaction of factors
(Key, 1997, Shi, 1997)

Poor Experimental ProceduresControl group exposed to part of
the interventionMultiple treatment interferenceLength of time
of treatment interventionLoss of participants
SummaryExperimental study designs are one of the most
powerful designs to use when trying to prove cause and effect.
Quasi-experimental study designs are also very effective but
tend to have many more problems with external validity since
most do not include randomization of subjects Researchers in
health informatics choose to use the quasi-experimental design
for many reasons such as ethical considerations, the difficulty
in randomization of subjects and small sample size (Harris et al,
2006).Several examples of experimental and quasi-experimental
studies and the methodology used in the health informatics and
healthcare setting demonstrate that this study design is a viable
option for health informatics research.
Epidemiological Research

Chapter 6
IntroductionEpidemiology examines patterns of disease
occurrence in human populations, and the factors that influence
these patterns in relation to time, place, and persons. Essential
tool when developing specific research methodologies in health
informatics. This chapter provides examples of epidemiological
principles to study disease and health informatics.
Types of EpidemiologyEpidemics -- what caused them and how
they could be controlled and prevented. Expanded rapidly
beyond the study of infectious diseases into the study of all
types of illnesses. Cancer epidemiology; pharmaco-
epidemiology; environmental epidemiology, nutritional
epidemiology; chronic disease epidemiology, health services
epidemiology,
Epidemiology and Health InformaticsEpidemiological principles
can be used to study any type of behavior, outcome, occurrence,

community, or healthcare system. The key is to know which
epidemiological study design to use to inspect a particular
problem. Epidemiological principles and study designs are used
to examine many of the health informatics systems and
structures that sustain the healthcare system today.
Example
Researchers (Bell et al. 2003) used a cross-sectional study to
determine whether physician offices located in high-minority
and low-income neighborhoods in southern California have
different levels of access to information technology than offices
located in lower-minority and higher-income areas.
Example cont’d
Use epidemiological principles similar to those that Snow
developed.
Researched physician offices in targeted geographic areas and
neighborhoods to determine the use of different types of health
information technology.
Even though they did not establish the cause of any particular
disease, they determined whether or not socioeconomic

demographics play a part in the use of information technology.
*
Infectious Disease Model
Gordis 2004, 16; Lilienfeld 1994, 37-38).
Host
Agent
Environment
Age, gender, race religion,
Marital status, ethnicity, genomics,
Social behaviors, anatomy & physiology
Prior illness or disease
Nutritional, chemical,
Physical, infectious
Physical Environment
Tornado, flood, hurricane, war

Occupational Environment
Infectious Disease
Chronic Disease Model
Component I
Component II
Component IV
Component III

Chronic disease model:
Example of lung disease
Smoking or
Air Pollution
Family History or Genetics
Infant respiratory infection
Poor Nutrition
Using the Epidemiological Models of Causation in Health
Informatics
Epidemiological model: Health informatics example—
Computer-assisted coding (CAC)

Host
Agent
Environment
Experience
Training
Understanding of CAC system
Computer problems
Coding errors in system
User friendly
Encoder issues
Documentation in EHR incomplete
Structured text
Free text
Artificial Intelligence
Chronic disease model:
Example of reluctance to use PHR

Privacy and Security Issues
Inaccessible systems
Unfamiliar with computers and PHR systems
Additional Time to Develop and Use
Epidemiological Study DesignsDescriptive StudyCross-
sectional or prevalence studyAnalytic StudiesRetrospective
(Case-Control) StudyProspective StudyExperimental
StudyClinical and community trial
Progression of Epidemiological Study Designs

Analytic Study Design:RetrospectiveCase-Control Prospective
StudyHistorical-Prospective Study
Experimental Study:Clinical TrialCommunity Trial
Descriptive Study Design:
Cross-SectionalPrevalence
Components of the cross-sectional or prevalence studyDescribes
health characteristic at one point or period in timeGenerates
hypothesesDetermines whether the disease or health
characteristic exists nowGenerates new ideasPerformed when
very little is known about a topicExcellent design when
studying new concepts in health informatics Leads to analytic
studies
Prevalence Rate
Below is an example of how a prevalence rate is determined:

Number of U.S. ambulatory healthcare facilities that use digital
radiology systems
Number of ambulatory care facilities in the US
where N = 1000 if expressing the rate per 1,000 facilities,
10,000 if expressing the rate per 10,000 facilities, and so forth.
X N
Sensitivity and SpecificitySensitivity and specificity rates can
be used in prevalence studies when assessing correct
measurement or correct labeling. True Positives (TP): Correctly
categorize true cases as cases (cases are individuals with the
disease or outcome) = VALID labelingFalse Negatives (FN):
Incorrectly label true cases as non-cases (non-cases are those
individuals without the disease or outcome = INVALID labeling

Sensitivity and SpecificityTrue Negatives (TN): Correctly label
non-cases as non-cases = VALID labelingFalse Positives (FP):
Incorrectly label non-cases as cases = INVALID
labelingSensitivity = Percentage of all true cases correctly
identified where TP/(TP+FN) Specificity = Percentage of all
true non-cases correctly identified where TN/(TN+FP)
(Lilienfeld and Stolley 1994)
Example of Prevalence Study
The American Hospital Association (AHA) (2007) conducted a
prevalence study by surveying AHA member hospitals to
determine their use of health information technology. Survey
instruments were sent to hospital chief executive officers
(CEOs) from all types of hospitals and from different
geographic areas across the country.
Analytic Study Designs: Case-Control (Retrospective)
Steps to follow when conducting a case-control (retrospective)
study
Step 7 Design the instrument used to collect the exposure or

risk factor data. Collect it through phone or in-person
interviews, self-report questionnaires, abstracts from existing
sources such as the EHR, cancer registry, birth certificates,
death certificates, financial records and so forth. Step 8Analyze
the data to include the appropriate statistics.Step 9Summarize
the results and determine if they support or refute the
hypothesisStep 10Publish the results
Step 1Determine the hypothesis and decide whether to use
prevalence (existing cases of disease) or incidence cases (new
cases of disease)Step 2If prevalence cases, seek out cases from
the state or hospital-based cancer registry. If incidence cases,
have health care facilities provide new cases as they are
treated.Step 3Decide who will be part of the study by using
inclusion criteria such as ICD-9-CM codes, laboratory reports,
radiology reports, medical records, and so forth, which all
validate the disease under study.Step 4Randomly select the
cases by obtaining a list of possible cases (either from the state
or hospital-based cancer registry or from a list of ICD-9-CM
codes and so forth) and use a systematic sample by choosing
every 5th case.

cont’dStep 5Choose controls from siblings or friends, who are
of similar age, gender, socioeconomic status, or from the same
hospital. Controls should be similar to the cases for all
characteristics except the disease under study. For example, if
studying melanoma, choose controls from the same hospital-
affiliated cancer registry as the case but who has another type of
cancer such as colon cancer or lung cancer. Select these
controls from a list of cancer cases identified by their ICD-9-
CM code and validate the diagnosis through pathology reports
and medical records. Also, choose controls from this list that

are similar in age by at least five years.Step 6Decide whether
matching of the cases and controls will be used on certain
variables. Matching on variables such as age, gender, race and
so forth should only be used when the researcher is certain that
there is a relationship between that variable and the dependent
variable. For example, age is always related to cancer because
as we age, our chance of developing cancer increases.
Therefore, age becomes what is called a confounding variable
because it may be the underlying factor that is leading to the
development of the cancer instead of the specific risk factor that
one is trying to prove is related. Therefore, when studying
cancers, matching should be done for age.
cont’dStep 7 Design the instrument used to collect the exposure
or risk factor data. Collect it through phone or in-person
interviews, self-report questionnaires, abstracts from existing

sources such as the EHR, cancer registry, birth certificates,
death certificates, financial records and so forth. Step 8Analyze
the data to include the appropriate statistics.Step 9Summarize
the results and determine if they support or refute the
hypothesisStep 10Publish the results

Example—Odds Ratio
The odds ratio for this example is:
AD=(200) x (100) = 20,000=4
BC (500) x (10)5,000
The value of 4 means that those individuals that use tanning
lamps are 4 times more likely to develop melanoma than those
individuals who do not use tanning lamps.
If the odds ratio for this particular example equaled 1, then it
means that the risk for melanoma is actually equal for the cases
and controls and that use of tanning lamps is not a risk factor
for melanoma. If an odds ratio is less than 1.0, this means that
the factor (the use of tanning lamps) actually decreases the risk
of disease and provides a protective effect.
Example: Case-Control Study in Health Informatics
Hippisley-Cox et al. (2005) used the case-control design to
examine the relationship between myocardial infarction (MI),
and use of non-steroidal anti-inflammatory drugs (NSAID). The
authors of this study used a research database called
QRESEARCH to examine this relationship.
Cases were patients aged 25 to 100 identified as having an acute
myocardial infarction (MI) for the first time recorded from Read

Codes (similar to SNOMED codes) during a four-year study
period.
Controls were those individuals with a diagnosis of coronary
heart disease, but without an MI, matched to each case by age,
year, gender, and physician practice.
Odds ratios were computed.
Confounding variables also were collected and controlled for,
and include smoking and comorbitities such as diabetes,
hypertension, coronary heart disease, osteoarthritis, rheumatoid
arthritis, and obesity.
Cohort (Prospective) Study DesignThis study design has two
groups of study participants: One with the exposure
(independent variable) One without the exposure (dependent
variable). Both groups are then followed forward in time to
determine if and when they develop the disease or outcome
variable under study.

Calculating the Relative Risk
The calculation for the relative risk is:
Incidence rate of the exposed group
Incidence rate of the unexposed groupThe incidence rate is:
Number of new cases of a disease over a period of time
Population at risk
where N = 1000 if expressing the rate per 1,000 people, or N =
100,000 if expressing the rate per 100,000 people and so forth.
Population at risk refers to those free of the disease at the start
of the study.
X N
Calculating the Relative Risk cont’d
The calculation for the relative risk is:Incidence Rate of
Exposed =A(A+B)Incidence Rate of Unexposed =
C(C+D)Relative Risk:[A / (A + B )]
[C / (C + D)]

Calculating the Relative Risk cont’d
The relative risk for this example is:Incidence Rate of Exposed
= 200 275Incidence Rate of Unexposed = 25325Relative
Risk:[0.727]
[0.077] = 9.4In this hypothetical example, the relative risk of
9.4 is very high for the association between use of video games
and migraine headaches, and those children who play video
games are almost nine times more likely to develop migraine
headaches than those who do not play video games.
Prospective Study Example in Health Informatics
Baxt et al. (1996) conducted a prospective study that compared
the accuracy of physicians diagnosing patients with acute
myocardial infarction (MI) to an artificial neural network.
Compared data collected by physicians when evaluating 1,070
patients who entered the emergency department of a teaching
hospital in California with anterior chest pain to the neural
network diagnosis of the same patients.
Patients were o followed over time by review of their medical

records in the outpatient department or via telephone to
determine their final diagnoses, which were validated by serum
creatine kinase levels and EKG evidence.
Experimental Study Designs in Epidemiology
Experimental research studies expose participants to different
interventions (independent variables) to compare the result of
these interventions with the outcome (dependent variables).
Two examples of experimental research studies in epidemiology
include the clinical and community trial.
Clinical Trials
Clinical trials are designed to help healthcare professionals test
new approaches to the diagnosis, treatment, or prevention of
different diseases.
Patients who are at high risk for developing these diseases are
often the ones who participate in the clinical trial.
The clinical trial is designed to test new medications (most

common) and surgical procedures, as well as new treatments or
combinations of treatments to prevent disease.
Community trials
Very similar to clinical trials but take place in a particular
community and have less control over the intervention than one
would have with the clinical trial.
The community trial’s goal is to produce changes in a specific
population within a community, organization, or association.
Participation includes all members of the community and the
intervention tends to be provided throughout the population
(Friis et al. 2004, 322-323; UPMC 2008).
Clinical and Community Trial Protocol
Rationale and background
Specific aims
Randomization
Blinding or masking
Types and duration of treatment
Number of subjects

Criteria for including and excluding participants
Outline of treatment procedures
Clinical and Community Trial Protocol
Procedures for observing and recording side effects
Informed consent
Analysis of data
Dissemination of results
Types of Clinical Trials
Treatment trials test experimental treatments, new combinations
of medicines, different types of surgery, radiation or
chemotherapy
Prevention trials aim to prevent disease in a person who has
never had the disease or to prevent it from advancing or
reoccurring.
Diagnostic trials are conducted to find better tests, procedures,
or screenings to detect a disease or condition.

Types of Clinical Trials cont’d
Screening trials examine the best method to detect diseases or
health conditions.
Quality of life trials explore methods used to improve comfort
and the quality of life for individuals with a chronic disease
Clinicaltrials.gov 2007
Phases of Clinical Trials
Phase I, II, III, or IV based on the size of the population and the
intervention being tested. The FDA provides guidelines for the
different types of clinical trials.
Phase I clinical trials usually test a new drug or treatment in a
small group of people (20-80)
Phase II clinical trials study the intervention in a larger group
of people (100-300)
Phase III the study drug or treatment is given to even larger
groups of people (1,000-3,000)
Phase IV clinical trials include studies that collect additional
information after the drug has been marketed, such as the drug’s

risks, benefits, and optimal use.
Clinical Trials in Health Informatics
Shea (1996) examined several different experimental studies
comparing computer-based clinical reminder systems to manual
reminder card-type systems in ambulatory preventive care
settings.
They found 16 different randomized controlled trials from 1975-
1994 in which computer-based clinical reminders were used for
several different preventive services such as hypertension
follow-up, influenza vaccine, pneumococcal vaccine,
mammography, fecal occult blood test, pap smear, tetanus
vaccine, dental screening, smoking assessment, dietary
assessment, and so forth.
They found that computer-generated reminders when compared
to manual reminders increased preventive practices by 77
percent.
The use of the experimental study to examine the effectiveness
of the computer-based clinical reminder system provided
thorough evaluation of this system.

Rules of Evidence for CausalityStrength of association: The
strength of the association is measured by the relative risk.(RR)
A strong RR is important, and those >2 are effective to show
causality. However, repeated findings of weak RRs may be of
equal importance if it is found in studies with reliable
methodology.Consistency of the observed association:
Confirmation of results in many different types of
epidemiological studies in different populations and different
settings. This can be seen in the study by Shea (1996) in which
upon review of 16 RCTs, found that computer-generated
reminder systems improved preventive practices over time.
Rules of Evidence for CausalitySpecificity: A one-to-one
relationship between an independent variable and a dependent
variable, or between the exposure and the disease is necessary
to add weight to causality. However, because some exposures
may lead to many different adverse outcomes, if specificity is
not found this does not mean an association is not causal.
Temporality: The independent variable must precede the
dependent variable, not follow it. For example, in order to state
that decision support systems decrease medical errors, the use

of the decision support system must precede the development of
the medical error. Sometimes this is not easy to determine. A
prospective study design can help support this rule.
Rules of Evidence for CausalityDose-response relationship: As
the dose of the independent variable is increased, it strengthens
the relationship with the dependent variable.
In epidemiology, this can be demonstrated for smoking, in
which dose and duration increase risk of disease. In health
informatics, if clinical reminder systems for colonoscopy reduce
the likelihood of developing colon cancer, increasing the use of
the clinical reminder systems for other types of cancer
screening can be assumed to also reduce the development of
cancer.
Rules of Evidence for CausalityBiological plausibility: The
relationship must make sense in relation to what is known about
it in the sciences, animal experiments, and so
forth.Experimental evidence: A well-conducted RCT may

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