OJHAS Vol. 10, Issue 4:
|Clinical Decision Support System for Oncologist: Perception, Expectations
Rajesh Kumar Sinha, Associate Professor, Department of Health Information Management, Manipal College of Allied Health Sciences,
Manohara M Pai, Associate Director, Innovation Center, Professor, Information and Communication Technology, Manipal Institute of Technology,
MS Vidyasagar, Professor and Head, Department of Radiotherapy and Oncology,
Sirdhi Saibaba Cancer Hospital and Research Center,
BM Vadhiraja, Associate Professor, Department of Radiotherapy and Oncology, Sirdhi Saibaba Cancer Hospital and Research Center,
Manipal University, Manipal - 576 104, Karnataka, India.
Dr. Manohara M Pai,
Address for Correspondence
Associate Director, Innovation Center,
Professor, Information and Communication Technology,
Manipal Institute of Technology,
Manipal University, Manipal - 576 104,
Sinha RK, Pai MM, Vidyasagar MS, Vadhiraja BM. Clinical Decision Support System for Oncologist: Perception, Expectations
and Implementation. Online J Health Allied Scs.
Submitted: Oct 13,
2011; Accepted: Jan 4, 2011; Published: Jan 15, 2011
Clinical Decision Support System is an integral application in modern
healthcare practice to assist the clinicians with patient information
and domain knowledge during patient care. Purpose:
Assessment of perception and Identification of expectation are the prerequisite
for the implementation of Clinical Decision Support System (CDSS).
Methodology: A descriptive study was conducted among the 100 Oncologists
of cancer hospitals and research centers of Southern India. A validated
survey questionnaire related to the perception and expectation towards
CDSS was provided to the participants and asked them to mark their response
on a 5-Point Likert Scale i.e. from Strongly Agree to Strongly Disagree.
The time motion study was also conducted to understand the issues related
to the access of patient information and domain knowledge. Result:
The Oncologist perception towards CDSS was found to be significant where
the Oncologists felt that the implementation of CDSS will decrease the
cost of healthcare and increase the productivity of the hospital. The
Oncologists expected that the system should have the features to automatically
capture the clinical knowledge, practice guidelines and updates related
to cancer care. The time motion study revealed that the Oncologists
spend their maximum time in documentation & retrieval of patient
information during patient care and evaluation because they largely
depend on printed text. A web enabled CDSS is developed, implemented,
and tested against the requirement of the Oncologists where the system
was found to be highly acceptable by the Oncologists. Conclusion:
The expectations of the end users should be fulfilled to make the CDSS
more acceptable and sustainable as the similar result had been observed
and found in the present research.
Perception; Expectation; Clinical Decision Support System; Oncology; Oncologist
and prevention is considered to be an integral and challenging task
for the healthcare professionals and hospital setup. The objective of
cancer control and prevention is to reduce the incidence, mortality
and morbidity of care and further improve the quality of life of the
patient suffering from cancer. To achieve this it is largely dependent
on the clinician’s ability to make quality decision in formulating
the diagnosis based on information gathered from the patient and other
and Communication Technology is always looked upon by healthcare as
a tool for improving the accessibility of patient information and domain
knowledge to improve the clinical outcome of the cancer patient.
technologies have the potential to facilitate or enhance communication
and exchange of information between the cancer patients and the care
providers with an ultimate aim to enhance the benefits to stakeholders,
most importantly the patient. These technologies are acknowledged as
a supportive tool to save time and money, increase convenience and choice,
obtain timely information, and improve decision making during patient
support systems (CDSS) is an important application of Information and
Communication Technology to assist the clinicians in gathering patient
information and clinical knowledge related to the respective domain
for making diagnostic and therapeutic decision. The system also supports
in clinical coding and documentation, authorization of procedure, referral,
clinical diagnosis, treatment plan process, condition-specific guidelines,
and promoting the use of best practices. It has the potential to
minimize practice variation and improve patient care and create a marked
surface throughout the healthcare industry. It also assists in management
of various other activities such as referral, diagnosis, classification
and staging, treatment and follow-up of the patient specific to neoplastic
disease. The system also provides continuous monitoring of patient treatment.
trends in healthcare showed the necessity for innovative and dependable
clinical information systems with decision support capabilities for
quality decision making in healthcare delivery system. But before the
implementation of such system, it is required to understand the clinician’s
opinion as the acceptability of any such information system in the healthcare
set-up largely depends on the positive attitude of the clinicians to
use it for quality decision making in patient care.[7-11]
To make the system more acceptable and sustainable in the healthcare
delivery, clinician’s needs and expectation towards the clinical decision
support system must be assessed and considered. This helps in
choosing the appropriate content and tool for the development of the
system [12-14] and creates a feeling of ownership among the end
Design: A descriptive
method of research was used for the study. John W Creswell  describes
the descriptive method of research where the researcher gathers information
based on the present existing condition. The method is used to define
the nature of the situation, as it exists at the time of study and to
explore the causes of a particular phenomenon. In this study, the descriptive
method was employed to identify the perception and expectation of Oncologists
towards clinical decision support system using a tested tool by recruiting
and selecting oncologists during the time of research. The aim of this
research is to design and develop a customized decision support system
for oncology where this method helped to obtain first hand data for
deriving the rationale and sound conclusions and recommendations.
Setting: The participants
were selected from 12 different Cancer Hospitals and Research Centers
of Southern India.
Size: In order to
determine the level of awareness and utilization of cancer information
system, perception and expectation from decision support system, 100
oncologists were asked to participate. A purposive sampling method was
adopted where the three states i.e. Karnataka, Kerala and Tamil-Nadu
were included in the study. In these three states, 12 hospitals were
considered for selecting the Oncologists based on the availability and
convenience and also as per the qualification of the Oncologist.
Criteria: To obtain pertinent
information, certain inclusion criteria were drawn. The participants
with MD and 5 years of working experience in the oncology set-up qualified
for the study. This qualification ensured that the participants understood
the role of information support services in their practice and be able
to give appropriate feedback in this regard. The participants who were
not willing to participate in the study were excluded.
Data Collection Tool: In order to
collect the data from the Oncologists, a validated and pre tested questionnaire
was used. The questionnaire was prepared and validated by experts from
the field of Oncology, and Health Information Management. The
questionnaire consisted of three sections: Demographic Details;
Perception towards Clinical Decision Support System and Expectation
from Clinical Decision Support System. To understand the oncologists
perception towards the clinical decision support system
8 parameters were included where the oncologists were asked to mark
in a scale from 1 to 5 (Strongly Agree to Strongly Disagree).
The oncologists were asked to rate their expectation from the proposed
system in terms of quality decision making, coding, documentation and
patient care. These expectations were captured using a checklist consisting
of 14 components related to the above parameters. The oncologists were
asked to respond by marking their response in a scale from 5 to 1
(Strongly Agree to Strongly Disagree). The oncologists were
first briefed about the study and after obtaining an informed consent
they were included in the study.
workflow has also been observed to determine the total time for capturing
and disseminating the patient information to the oncologists and also
the issues related to the accessibility of clinical knowledge. The oncologists
were also asked to list out the areas of improvement in terms of information
support service in their practice.
and implemented, the CDSS is demonstrated among the Oncologist and their
feedback was collected to understand their acceptance level.
Methods of Data Collection: The questionnaire
was administered to the Oncologists after taking the consent from the
concerned hospital authorities. The Oncologists were first briefed about
the research and its objectives and the purpose of survey. An informed
consent was obtained from the Oncologists for being the part of the
study where the data was collected by distributing the questionnaire
among those who responded. During the process of data collection, the
workflow pattern and total time taken with respect to the documentation,
retrieval and access of patient information and clinical knowledge were
also noted down. The user acceptance test was also conducted to determine
the acceptance of the CDSS.
Statistical Analysis: Statistical
Package of Social Sciences (SPSS) 16.0 version was used to analyze the
data. Chi square test was done and P<0.05 was considered significant.
The average time for capturing and dissemination of patient information
to the end users were also calculated to understand the issues related
to the access and availability of information and clinical knowledge
and to suggest the better CDSS for improving the information support
to Develop Clinical Decision Support System: A CDSS was
developed with 3-layer application with User Interface, Business Logic
layer and Data layer. Data access layer is incorporated using ADO.NET
to communicate with database. The software platform used to developed
the CDSS was MS SQL 2005 and the Web Server i.e. IIS to serve
the users request from their browsers like Mozilla Firefox, Internet
Explorer etc. to access the system and its content. The end users operating
system can be any version of Windows, Linux or any other which supports
TCP/IP protocols. The communication interfaces is a local area network
connected to local hosting server.
the Oncologists: A total of
100 oncologists from 12 cancer hospitals and research centers of Southern
India, participated in the study. The majority of the Oncologists (71%)
were found to be male (Table 1).
Gender Wise distribution|
A mixed variation was observed
in terms of the age of Oncologists where 41% of them were in the age
interval of 36-40 followed by 20% under 41-45 age group, 18% under 31-35
group and 13% in 51-55 age group. Only 2 Oncologists were in the age
group of 56-60 (Figure.1). Thus a relatively younger generation of oncologists,
mostly below 40 (61%) were found in most of the hospitals.
Age-wise Distribution of Oncologists
represents the designation-wise distribution of the Oncologists. Of
the total, 37 Oncologists were consultants followed by 27 Associate
Professors and 15 Assistant Professors whereas Additional Professor
and Professors constituted only of 11 and 10 respectively. This is attributed
to the fact that the majority of the oncologists were below the age
of 40 and the designations in most of the hospitals in India are based
on the years of teaching and/or practice.
Designation and Department Wise Distribution
The majority of the
Oncologists (41%) had 5 – 10 years of experience, 37% under 11 – 15 years,
whereas, 22% of the Oncologists reported to have more than 16 year of experience
in patient care and teaching (Figure 2).
Figure 2: Distribution
of Oncologists based on years of experience
Opinion of Oncologists on Clinical
Decision Support System: The opinions of end users are required in easy and
practical implementation of clinical decision support system in practice.
who completed the survey offered diverse opinion about the clinical
decision support system in healthcare practice. Table 3
summarizes the response of the oncologist towards clinical decision
support system (CDSS). A total of 93% of the Oncologists were found
to agree on the fact that the implementation of CDSS will increase the
productivity of the hospital. This is attributed to the fact that most
of the oncologists were found to be aware about the benefits of clinical
decision support system. A systematic review conducted by Amit et al
; and Kensaku et al also revealed that most of the CDSS
improved the clinician performance and resulted in better patient outcome.
Opinion on Clinical Decision Support System
of Decision Support System will:
the productivity of hospitals
hassles for clinical staff
|Do a job
better than the people
hospital costs in the long run
work for people
job functions of non-medical personnel
the doctors control over medical practice
unavoidable in healthcare practice
SA= Strongly Agree, A= Agree, N= No Opinion, SD = Strongly Disagree,
A mixed response
had been observed when the oncologists were asked whether the implementation
of CDSS will create hassles in their work, 42% of the Oncologists were
found to disagree whereas 32% of them showed no opinion but only 26%
of them agreed. When probed further, the clinicians felt that the CDSS may
create hassles initially but at a later stage will definitely improve their
workflow as well as their performance.
Out of total,
63% of the Oncologists believed and agreed that CDSS can do the job
better whereas 25% did not have any opinion and 12% disagreed to it
and expressed that the system cannot replace a human being.
whether they feel that the decision Support System will reduce the cost in the
long run, 74% of the Oncologists agreed, 12% disagreed and 14% of them did not
opine. When the Oncologists were asked whether the clinical decision support
system will help in reducing the workload, 66% had positive opinion, whereas 18%
disagreed, and 16% were found to have no opinion in this regard. It was evident
from the study by Troy et al felt that the clinical decision support system had
significantly decreased the clinicians prescription cost and improved their
A good percentage
of the Oncologists i.e. 29% were found to have no opinion on how the
clinical decision support system will upgrade the job function of non-medical
personnel where as 60% of them showed their agreement with this fact.
When the Oncologists were asked whether the implementation of clinical decision
support system will reduce their control over medical practice, 79% of the total
Oncologists showed their disagreement and commented that the machine cannot
replace the humans where the life of the patient is at risk whereas 10% did not
have any opinion but 11% of them agreed with the same.
to the query whether CDSS will help in making quality decision during patient
care, 81% of them agreed whereas 11% disagreed and 8% did not have any opinion
The study conducted
by S. Trent Rosenbloom et al. was evident that the clinicians were satisfied
with the computer provided order entry and reported that their efficiency in
terms of quality patient care, order entry has been improved. They also
commented that the decision support system is also assisting them in medical
show that the Oncologists with clinical experience of 5-15 years were
more interested in implementing CDSS in their day to day practice whereas
the Oncologists with 16-25 years of clinical experience were not very
much sure and confident on how CDSS will support them in their oncology
practice. This can be attributed to the fact that the younger oncologists
are more technology savvy and understand the benefits from it fully,
whereas the older generations still have certain trepidations. This
behavior can also be seen in the study conducted by Helena Veronen where the
younger physicians looked more enthusiastic towards the implementation of the
use of the system in their practice where criticism was mostly presented by the
Expectation from Clinical Decision
Support System: Expectations
of the end users and their needs have to be identified before designing
and developing any information technology (IT) applications.[21,22]
The same was conducted among the oncologists to understand their expectation
from the CDSS.
regard to Clinical Decision Making: Clinical decision making during the
patient encounter always depends on the availability of complete and accurate
patient information and domain knowledge to the healthcare professionals.
The information also contributed in updating knowledge as well as planning for
the therapy and care.
All the oncologists
were found to agree with the fact that clinical decision support system should
have the provision to provide various clinical knowledge and treatment
guidelines to the end user in quality decision making. About 74% of the
Oncologists showed their agreement but 22% were not sure about the role of
clinical decision support system with respect to the etiological diagnosis and
therapy. Out of total, 92% of the Oncologists wanted features where the proposed
system will support them in updating the clinical knowledge for planning the
treatment and care (Table 4).
Expectations with regard to Clinical Decision Making
CDSS should help in quality
decision making by:
Providing various clinical knowledge and guidelines
Answering questions concerning medical knowledge
Correlating patient condition with clinical knowledge
Finding etiological diagnosis and therapy goal easier
Updating the knowledge of healthcare team by providing reviews of scientific
literature and current updates
SA= Strongly Agree, A= Agree, N= No Opinion, SD = Strongly Disagree,
regard to Documentation and Statistics of Patient Information: The
healthcare professionals always expect that the information system if
implemented in their practice should reduce their time in medical documentation
and clinical coding and increase their time for patient care and evaluation.
In this study,
the Oncologists were asked about their expectation from the proposed system in
terms of medical documentation, clinical coding, statistic and recording of
investigation results. The responses were as follows:
Classification of Disease-10thVersion (ICD-10) and International
Classification of Disease in Oncology (ICD-O) helps the healthcare professionals
as well as the hospital to standardize the recording and reporting requirement
and helping them in making quality decision. In view to this, 95% of the
Oncologists expected to have an automated clinical coding and documentation
features in the proposed system.
majority of the Oncologists i.e. 99% felt that the system should have the
features in generating variety of statistical result for reporting and research.
All the Oncologists agreed to have certain features where they can easily
interact with each other using the same system and receive the investigation as
well as therapy result without any delay (Table 5).
Expectation with regard in Documentation Patient Information & Statistics
Decision Support System should:
in clinical coding and documentation
|Generate a variety of
statistical analysis and presentation
results of a test or investigation easier
Strongly Agree, A= Agree, N= No Opinion, SD = Strongly Disagree, D=Disagree
regard to Patient Care: Clinical Decision Support System assists the
healthcare professionals in achieving the best patient outcome and maximum
patient satisfaction by reducing the cost of healthcare, improving the clinical
outcome, instant information retrieval and reducing the waiting time of the
patient. The healthcare professionals also get benefited with this in
promoting evidence based medicine.
In view to
this, 91% of the Oncologists agreed that the system should have an automated
feature to instantly access the patient’s identification, clinical and
investigation details. They also commented that the automation of this process
will secure the patient data from misplacing, missing or any incident of loss
and will directly contribute in reducing the cost of healthcare.
About 93% of
the Oncologists felt that the system should have certain features to assist them
in retrieving complete, accurate and adequate patient information and domain
knowledge related to cancer for improving the clinical outcome of the patient.
Oncologists wish to have selective retrieval of patient information and domain
knowledge. They also felt that the system should satisfy their day to day
reporting activities such as administrative, clinical and reporting to
National Cancer Registry Office. They felt the need of such system in getting
access to all the patient information and the status of the patient during
medicine is the use of current medical knowledge and patient’s clinical evidence
to make quality decision during patient’s treatment. In this view, 90% of the
respondents expected to have this feature into the system but 10% of them were
not sure whether the system will really assist them in improving the evidence
based medicine. (Table 6)
Table 6: Expectation
with regards to Patient Care
Decision Support System should:
the cost of healthcare
|Help in improving the
clinical outcome of patients
|Make seeking specific
information from patient records
|Help in better
reporting and follow-up of adverse events
based healthcare practice
Agree, A= Agree, N= No Opinion, SD = Strongly Disagree, D=Disagree
All the respondents
agreed to the fact that this kind of system should be implemented in
all the hospitals and should have the provision where the decision taken
by the clinician based on the knowledge provided by the system should
automatically get saved into the system for future reference. (Table 7)
Overall opinion on Clinical Decision Support System|
|Do you think
that the CDSS should be implemented and practiced in all healthcare
facilities for quality decision making and quality healthcare?
|Do you think
the CDSS should have the provision to automatically store the decisions
made as a case base, which can be referred to later during a similar
Assessment of Existing Workflow Pattern: Figure 3 represents
the conventional workflow pattern in the hospital for patient care and
evaluation where the easy and instant access of patient information
and clinical knowledge play a vital role and also influence the process
Conventional Flow of Information for Patient Care
of workflow pattern and feedback received from the oncologists reveals
that they spend maximum time in accessing patient information during
the follow-up. It takes longer time in retrieving and sending from the
medical records from medical records department to the OPD. This results in
increased waiting time of the patient who requires immediate attention.
interpretations were drawn by assessing the existing workflow in the
hospital with the estimated workflow using clinical decision support
Comparative list of conventional workflow pattern with CDSS
With CDSS (Electronic)|
of patient data – Request sent to MRD
||10 Min. (Avg.):
As the patient information record manually on paper.
||Records are electronically
documented into the system that is available instantly in any location.|
|Time to reach
the medical records from MRD to OPD
||20 Min. (Avg.):
Records are sent through the messenger boy to the respective unit.
||Instant access of patient
information by the oncologist at their respective OPD.
the patient information onto the medical records.
||Manual entry of the patient
data increases the clinician time for documentation.
||Menu driven entry decreases
the oncologist’s time in documenting the patient information.
of patient investigation result
||20 Min. (Avg.):
Manual entry of patient investigation result and reporting on paper
||Instant access of up-to-date
investigation result at the oncologists desktop |
recent clinical knowledge
||Through text book or internet
Issue: Difficult to
search the instant and accurate knowledge related to oncology.
|Instant access of clinical
knowledge as the rules or algorithm will automatically filter and rank
the online and offline latest evidence related to the respective domain.
recent domain knowledge, practice guidelines and protocols were also
found to be the major issues where maximum Oncologists use Google as
a search engine but it provides the information without any ranking
and filter. On comparison, it is felt that the implementation of CDSS will
definitely improve the information support service in the hospital in this
regard (Table 8).
Implementation Details: Based on the
result receive from the survey, a web enabled clinical decision support
system model is developed and implemented. The model consist of Patient
Database to capture the demographic and clinical events occur in
care of a cancer patient with automated ICD-Oncology-3rd
Version and AJCC TNM-Staging ; Knowledge Base to create a warehouse of knowledge
related to oncology domain; Search Engine to search domain knowledge based on
two criteria such as the latest evidence and review article; Case base to create
a user profile to store all the transaction details of the end user and
Statistical Analysis to generate various statistics related to patient care. The
ultimate aim of the system is to completely support the oncologist in accessing
patient information and clinical knowledge for quality decision making in
patient care and evaluation.
given by the Oncologists were mainly related to the strengthening of
the knowledge base where they suggested various text materials in terms
of textbooks, journals, practice guidelines and websites related to
oncology practice and the same were incorporated into the knowledge
base of the CDSS.
Module of Clinical Decision Support System
The model is
tested against the requirement and expectation of Oncologists identified
during the survey. The CDSS is demonstrated to the Oncologists where
the result revealed that the Oncologists were highly satisfied with
the user interface and felt that the system is friendly, supportive,
logical, consistent, helpful and easy to use. The Oncologists also felt
that implementing OncoSys would be wise for them and hospital. The Oncologists
intended to use the system in case of doubt during patient care and evaluation.
with the existing workflow pattern the Oncologists felt that the OncoSys
can greatly reduce their time in access and management of patient information.
They agreed on the fact that the statistical analysis module will contribute
in generating variety of statistical data for health research, conducting
various cancer control and prevention programs and also for National
Cancer Registry reporting. The Oncologists felt the system will help
in enhancing their productivity and also will contribute greatly to
the evidence-based practice. All Oncologists felt that the system has
all the features to support them in quality decision making and should
be implemented in all the hospitals for quality decision making in patient
care and evaluation.
The study concludes
that the oncologist had positive opinion in implementing the clinical
decision support system in their practice. The majority of the Oncologists
felt that the implementation of clinical decision support system will
decrease the hospital cost in the long run, reduce the work load in
terms of documentation and reporting, upgrade the job functions of non-medical
personnel, do the job better than people and it is unavoidable in healthcare
practice. The clinicians only disagreed to the fact that implementation
of clinical decision support system will reduce their control over medical
practice. There was an awareness that CDSS will only assist in decision making
and is not a replacement for the clinicians.
felt that the CDSS will support them in easy documentation, statistical
analysis and also assist them in improving the clinical outcome of the
patient. The oncologists’ major concern was to reduce their time in
accessing patient information and clinical knowledge and they felt that
the developed CDSS will definitely support them in doing so. All the
Oncologists felt that the implementation of the system will increase
the productivity of the hospital and it should be implemented in all
- Maserat E. Information
communication technology: new approach for rural cancer care improvement.
Asian Pac J Cancer Prev. 2008 Oct-Dec; [Cited 2011 January 08]; 9(4):811-814.
- Clinical Decision
Making. Encyclopedia Britannica. [Cited 2011 January 10] Available from:
- Van Den Brink JL et al. An information system to support the care for head and neck cancer
patients. Support Care Cancer. 2003 Jul; [Cited 2011 January 23];11(7):452-9. Epub 2003 Apr 18. Available from:
- Human Papillomavirus
and Related Cancer, Summary Report 2010 WHO/ICO. [Cited 2011 January
23]; Available from URL:
- Decision Support
System. Open Clinical Knowledge Management for Medical Care. [Cited
2011 February 11]; Available from URL.
- Wong HJ, Legnini MW, Whitmore HH.
Diffusion of decision support systems in healthcare: Are we there yet?
Journal of Healthcare Management 2000;45
[Cited 2011 January 08]:240–249.
Available from: http://www.ncbi.nlm.nih.gov/pubmed/11067416
- Badran IG.
Knowledge, attitude and practice the three pillars of excellence and
wisdom: a place in the medical profession. Eastern Mediterranean Health
- Lindenauer et al.
Physician Characteristics, attitude and use of computer order entry.
Journal of Hospital Medicine. July-August 2006;1(4):221-230. DOI: 10.1002/jhm.106
- Al-Hajjaj MS, Bamgboye EA. Attitude and Opinion of medical staff towards computers.
Computers in Biology and Medicine. 1992;22(4):221-226. doi:10.1016/0010-4825(92)90061-Q
- Liaw ST, Pearce CM, Chondros P, McGrath BP, Piggford L,
Jones K. Doctors' perceptions and attitudes to prescribing within
the Authority Prescribing System. MJA 2003;178(5):203-206.
- Young DW. Doctors Attitude to
Computer Based Clinical Information System. Methods of Information in
- Doormaal JE et al. Computerized Physician Order Entry System: Expectation
and Experiences of users. Journal of Evaluation of Clinical Practice.
August 2010;16(4):738-743. DOI: 10.1111/j.1365-2753.2009.01187.x
- Clark C. Doctors
Need Decision Support in Ordering Imaging Diagnostics. IMGMA Medical
Group Management Association, July 28, 2010.
- Carroll C et al.
Involving Users in the design and usability evaluation of a clinical
decision support system. Computer Methods Programs Biomed. Aug 2002;69(2):123-135
- Creswell JW. Research design: Qualitative and quantitative approaches.
Thousand Oaks, CA: SAGE Publications. 1994
- Garg AX et al.
Effects of Computerized Clinical Decision Support Systems on Practitioner
Performance and Patient Outcomes. JAMA. 2005;293(10):1223-1238.
- Kawamoto K, Houlihan CA, Balas EA, Lobach
DF. Improving clinical practice using clinical decision
support system: A Systematic Review of trials to identify features critical
to success. BMJ 2005;330:765.
et al. Impact of an Evidence-Based Computerized Decision Support
System on Primary Care Prescription Costs. Annals of Family Physician.
10.1370/afm.233. Available at
- Rosenbloom ST
Clinicians’ perceptions of clinical decision support integrated into
computerized provider order entry. International Journal of Medical
et al. What may help or hinder the implementation of computerized decision
support systems (CDSSs): a focus group study with physicians. Family
Practice 2008;25(3):162-167. Available at URL.
- Farzandipour M, Sadoughi F,
Meidani Z. Hospital Information Systems User Needs Analysis: A Vendor Survey.
Journal of Health Informatics in Developing Countries. Available at
- Rossos PG,
Abrams H, Wu R, Bray P. Active Physician Participation
Key to Smooth MOE/MAR Rollout. Healthcare Quarterly, 2006;10(Sp):58-64.