Download Integrated Clinical Information Systems for Traditional and Non-traditional Users

ROSENBERG I Clinical Info Systems
INTEGRATED CLINICAL INFORMATION SYSTEMS
FOR TRADITIONAL AND NON-TRADITIONAL USERS
Martin J. Rosenberg, PhD,
MAJARO lNFOSYSTEMS, INC.
been a part of the drug development process. We call
a computer system for the collection, retrieval, and
analysis of clinical trial information, a Clinical
Information System or CIS. The current concept of a
Clinical Information System is shown in Figure 1.
Physicians who conduct clinical trials of new drugs
transmit the raw data to the sponsor on case report
forms (CRFs) which are then entered into a database
management system (DBMS). The data from the
DBMS is transferred to a data analysis package for
statistical analysis and computer generation of tables
and graphs which are then incorporated into reports
which become part of the NDA Although no standard
DBMS has emerged in the U.S. pharmaceutical
industry, SAS has long been the standard software used
for statistical analysis, report generation, and
production of summary tables and graphs.
ABSTRACT
Increasingly, pharmaceutical companies are attempting
to enhance productivity by expanding the scope of
their clinical information systems to embrace nontraditional users such as: investigators, in-house
clinical staff, and FDA reviewers. As these systems
become commonplace, companies are confronted with
the prospect of having up to five different computer
systems, each with incompatible data structures: a
remote data entry system; a database management
system for traditional data entry; a clinical data review
system for use by in-house clinical staff; a statistical
analysis system; and a computer assisted NDA review
system (CANDA).
This paper describes the emerging features of SAS
software, including Version 6 enhancements such as
screen control language, host windowing environments, multi-vendor architecture, multiple engine
architecture, indexing, PROC ACCESS, and PROC
SQL; and explores their role as a connectivity tool in
constructing remote data entry, CANDA, and clinical
data review systems in order to develop an integrated
approach to clinical information systems.
DBMS
I
STATISTICAL
ANALYSIS
I
CLINICAL INFORMATION SYSTEMS
AUTOMATED
TABLE AND GRAPH
GENERATION
Before a new drug can be introduced into the marketplace, pharmaceutical firms must undertake a research
process which can frequently take five or more years.
The company collects information about the safety of
the drug in both animals and humans; its efficacy in
the diseases to be treated; the stability of the drug
(how long it can remain on the shelf without
degrading); the pharmacokinetics of the drug, i.e., how
it is metabolized in humans; and the ability of the
company to manufacture the drug in production
quantities.
Figure 1: Current CIS
In an effort to better manage the volume of
information and to reduce the length of time required
to introduce a drug in the United States, the Food and
Drug Administration, in conjunction with the pharmaceutical industry, has been experimenting with ways of
using computer technology to facilitate the NDA
review process. Such a computer system is called a
As can be imagined from the magnitude of information
that must be collected, computer systems have long
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ROSENBERG I Clinical Info Systems
Computer Assisted NDA Review system or CANDA.
Participants in the CANDA experiments have reported
that similar systems would be of use not only by FDA
reviewers, but by the medical staff of pharmaceutical
corporations. We designate systems for use by medical
staff to monitor ongoing clinical trials, Clinical Data
Review Systems. Simultaneously, there has been much
interest in computer systems that permit the
investigator to enter data and the sponsor to remotely
monitor the trial. The intent of such systems is to
collect more timely and accurate information. We call
such systems Remote Data Entry and Monitoring
systems or RED EM.
computer assisted NDA review system (CANDA).
The introduction of separate, incompatible systems
could adversely impact productivity. Companies must
maintain duplicate databases for each structure (with
the attendant risk of inconsistencies between the
databases) and must either train the staff in the
operation of multiple systems or maintain separate
staffs for each technology.
Consequently, it would be desirable to integrate these
five functions. Since SAS software is already in
common use throughout the pharmaceutical industry,
this paper explores the emerging capabilities of SAS
and the role they can play in producing the integrated
CIS of tomorrow. The remainder of this paper
explores the use of the current Version 5.18 release of
SAS on mainframes and the emerging features of
Versions 6.03 and 6.06.
With the introduction of these three new classes of
users (investigators, in-house medical staff, and FDA
reviewers) future clinical information systems will
resemble Figure 2. Not every study will require all the
facilities of the future CIS's. In particular, REDEM is
likely to be used in selected studies only. However,
pharmaceutical firms will increasingly expect to have
these capabilities at their disposal. As such systems
become commonplace, companies will be confronted
with the prospect of having up to five different
computer systems, each with incompatible data
structures: a remote data entry and monitoring system;
a database management system for traditional data
entry; a clinical data review system for use by in-house
clinical staff; a statistical analysis system; and a
CLINACCESS™
CLINACCESS Version 5 is a Clinical Data Review
System designed for use by medical monitors, clinical
research associates, managers and other nontraditional users on the clinical staff. Written using
Version 5.18 SAS/AF software, CLINACCESS has the
following capabilities: single or double-key data entry;
viewing and querying of data; graphics; descriptive
statistics; and report generation. CLINACCESS features
an extensive context sensitive help system and an online tutorial to aid the new or infrequent user.
REMOTE DATA ENTRY
AND MONITORING
Use by investigators
Figure 3 shows the main CLINAccess menu. Users
select one of the options by entering its number on the
"Select Option" line and pressing enter. The Database
Administrator is additionally permitted to structure
new datasets, paint data entry screens, and manage
study libraries. A key feature of CLINACCESS is its
data dictionary which is called the Clinical Questions
Catalog (CQC). The Clinical Questions Catalog
ensures uniformity of variables across studies, facilitating the pooling of information. The CQC also
simplifies the study definition process. To create a new
dataset, the Database Administrator simply places an
X in the selection field for any variable which is to be
included in the new dataset. All the standard variable
attributes (format, informat, label, type, and length)
are automatically defined. To provide flexibility while
enforcing standardization, the label, informal, and
I
DBMS
I
STATISTICAL
ANALYSIS
I
AUTOMATED
TABLE AND GRAPH
GENERATION
CLINICAL DATA
REVIEW
Use by in-house
medical staff
I
CANDA
Use by FDA Reviewers
Figure 2: Future CIS
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ROSENBERG I Clinical Info Systems
nAc c e s s
C
(tm)
Select Option ===>
+--------------------
SELECT AN OPTION
--------------------+
5 Descriptive statist;cs
Enter data
6 Written reports
2 View a dataset
3
Rearrange data
7
Learn to use ClinAccess
4
Graphics
8
Exit Cl inAccess
+----------------------------------------------------------+
PF1
HELP
Level 1 (Main Menu>
ENTER
to select
Figure 3: The CuNAccEss Main Menu
4, the user specifies the study and dataset for the
report. If the user is unsure of the dataset, he or she
can check a box and a list of available datasets appears
(Figure 5). In Figure 6, the user selects whether all
variables are to be displayed in the report or only
selected variables.
format may be customized to the study, while the
name, type, and length of the variable are fixed.
CuNACCEss's strength is the ease with which data can
be accessed and manipulated. For example, Figures 48 illustrate the process of creating a report. In Figure
DATA LIST REPORT
C011111and ===>
+--·---------------
STUDY AND DATASET NAME
-----------------+
5274
studY
x_
Check (X) here and press enter to see a
list of datasets for the above study.
PF1
HELP
PF6
CANCEL
PF3
CONTINUE
Figure 4: Selecting a Study and Dataset
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ROSENBERG I Clinical Info Systems
DATA LIST REPORT
Conmand ===>
+··············· ··· STUDY AND DATASET NAME ················· +
S274
study
---------------- ---· List of Members In SAS Library------- ---------·
COnllland ===>
Libname: S274
MASTER
_KEYS
LAB
ADV_RX
CCMED
Figure 5: A List of Datasets is Displayed
In this case the user has decided to select which
variables will be included in the report. Note also that
CLINACCESS has selected the variables ID and WEEK
for automatic display. These variables will be used to
clarify the report. In Figure 7, the user selects which
variables will appear in the report by placing an X next
DATA LIST REPORT
C011111and ===>
I
I
to each variable to be included. To print sums in the
report, the user additionally checks the sum column.
Figure 8 shows the finished report. The data is
automatically displayed by identil)'ing variables, in this
case the patient ID and the week of the visit.
+--------------- ---------------- ---------------- -------------+
I
I
STUDY AND DATASET NAME: S274.LAB
+······------· VARIABLES AUTOMATICALLY DISPLAYED ············+
ID
WEEK
+··············· · OTHER VARIABLES TO DISPLAY ----············+
Choose one:
__ Display all other variables in the dataset.
X_ Select other variables to display from a List.
+··············· ··----· OPTIONAL TITLES
················· ····+
I
I
+--------------- ---------------- ---------------- -------------+
PF1
HELP
PF5
variables
PF6
CANCEL
PF9
ZOOM
PF3
SUBMIT
Figure 6: The User Fills in Blanks on the
Report Program Screen
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ROSENBERG I Clinical Info Systems
Screen
Obs
Edit dataset: S274.LAB
C011111and ===>
3, ••• to specify
Type an X in the DISPLAY colU1111 or use 1, 2,
the order displayed. Use X to indicate which variables to SUM.
DESCRIPTION
TYPE
DISPLAY SUM NAME
CALCIUM NUM
X
NUM
SGOT
X
X
NUM
SGPT
X
X
GLUCOSE NUM
NUM
IRON
NUM
PHOS
NUM
BUN
-X
BILIRUBN NUM
CREATNIN NUM
ALBUMIN NUM
NUM
SODIUM
Phosphorus
Bilirubin
Creatinine
PF7
BACKWARD
PF1
HELP
PF3
SUBMIT
PF8
FORIIARD
Figure 7: Selecting Variables to Display and Sum
DATA LISTING FOR STUDY S274
DATASET IS LAB
10
101
IIEEK
0
4
8
12
16
20
BILIRUBIN
CALCIUM
0.6
0.8
0.9
0.6
0.8
0.6
9.5
9.8
10.1
10.1
9.7
9.6
1.0
0.7
1.0
0.9
0.7
0.9
0.8
9.0
9.2
9.6
9.4
9.2
9.7
9.5
101
102
N=
SGPT
13
8
12
10
12
12
13
14
14
17
15
19
··---------92
-----------67
6
N=
102
SGOT
0
4
8
12
16
20
28
17
12
11
10
13
14
11
-----------88
7
16
10
13
11
15
17
14
-----------96
April 6, 1989
Figure 8: The Completed Report
mainframes under either the MVS or VM/CMS
operating systems.
CLINACCESS is an example of the kind of applications
which can be developed using Version 5 SAS software.
CLINACCESS Version 5 is available on IBM
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ROSENBERG I Clinical Info Systems
VERSION 6 ENHANCEMENTS
opened for either data entry or browsing. The
windows can be resized or zoomed to fill the entire
screen.
The introduction of SAS/AF in Version 5 extended the
power of SAS software to the non-traditional user.
Version 6 further extends that power with greater ease
of use and the addition of many desirable features
associated with relational database management
systems (RDBMS). These enhancements combine to
transform SAS into a connectivity tool which spans
hardware and software platforms as well as databases.
Datasets can also be linked using SCL. One thorny
problem in clinical data management is to display
comments made by investigators. A solution is to
place the comments in a separate dataset. An SCL link
can take a reviewer from an observation stored in one
dataset to a comment for that observation stored in the
comment dataset.
When finished reading the
comment, a single keystroke returns the user to the
dataset he was browsing.
The Version 6 enhancements include:
Screen Control Language available in SAS/AF
and SAS/FSP software.
• Host windowing environments
PROC SQL which adds the emerging standard for
fourth generation relational database query
languages to SAS.
• PROC ACCESS and Multiple Engine
Architecture which provide transparent access to
databases such as Oracle, DB2, SQL/DS, and
Rdb/VMS.
• Multi-Vendor Architecture, which permits applications to run on multiple hardware platforms.
• Indexing of SAS datasets, which provides
interactive applications with faster access to data.
Compressed SAS datasets, which can save disk
storage space.
The other Version 6 enhancements will be available in
Version 6.06 or subsequent releases of SAS. Version
6.06 will initially be available for IBM mainframes
under MVS or VM/CMS, DEC VAX computers under
VMS, and PC compatibles under OS/2.
SCL will be substantially enhanced in Version 6.06,
including the addition of further database management functions, as well as support for host windowing
environments. These enhancements will support a
common user interface with pull down menus, dialog
boxes, and other point and shoot tools. In particular,
under the OS/2 Presentation Manager and DEC
Windows, graphical user interfaces are supported,
providing for the first time, the power of SAS software
with the ease of use of a Macintosh like interface. ·
Version 6.03 of SAS is currently available on IBM
compatible PC's under the MS-DOS operating system
and on selected HP and Sun Microsystems computers
under UNIX. This release includes Screen Control
Language (SCL), a true programming language which
generates stored object code. In SAS/AF software,
SCL is specifically designed to create interactive fullscreen applications.
In SAS/FSP software, SCL
performs sophisticated interactive edit checks during
data entry. The syntax of SCL is similar to that of the
SAS DATA step, so experienced SAS programmers
will quickly feel comfortable.
Another addition to Version 6.06 is Multiple Engine
Architecture. Multiple Engine Architecture provides
the ability to use data stored in data structures other
than a SAS dataset, for example data stored in another
database management system (DBMS). Currently,
interfaces between SAS and a DBMS are constructed
as in Figure 13. A program is used to identify the data
available in the DBMS. The user selects the variables
and/or records desired and these are extracted from the
DBMS and restructured in the form of a SAS dataset.
This extra step of extracting data from a database and
creating a SAS dataset can be a considerable obstacle
to the non-traditional user. In addition, since the data
is physically removed from the DBMS, as new data are
added or corrections are made to the DBMS, the
extracted data ceases to be current and must be reextracted.
Version 6.03 has also added useful database management features such as the ability to display information
from several datasets simultaneously. Customized
screens resembling case report forms can be developed
which display data from more than one dataset, for
example demographics and adverse events. Data entry
can now be performed either in CRF or in table view.
Additionally, in table view, multiple windows can be
Under multiple engine architecture, SAS applications
will be able to run directly against other databases. A
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ROSENBERG I Clinical Info Systems
pharmaceutical industry where companies may use
several types of computers, e.g. a corporate mainframe,
a departmental mini-computer such as a VAX, and
intelligent workstations or PC's. Because the CIS will
have a common user interface across the hardware
platforms, training costs can be minimized.
Extract Program
User Specifies Variables
PROC SQL and indexing bring to SAS two important
database management features for performing queries.
SQL is the emerging standard for relational database
query languages. The SAS implementation will permit
queries of both SAS datasets and other database
structures, through multiple engine architecture.
Indexing is a common database management feature
that can speed on-line queries. Finally, compressed
datasets will reduce storage costs.
SAS Dataset Created
Data Used by SAS Application
Figure 13: Current Extract Process
SUMMARY
new procedure, PROC ACCESS, is used by the
database administrator,
to define the mapping
between the host DBMS structure and SAS.
Thereafter, access to the DBMS is transparent to the
user. As shown in Figure 14, a SAS program that
requires data sends a request to the engine supervisor,
a portion of the SAS system. The engine supervisor
selects the appropriate software engine to read the
data, and the information is provided to the requesting
program. No SAS dataset needs to be created.
SAS Application
Requests Data
I Engine
As the role of the Clinical Information System expands
to encompass non-traditional users such as investigators, medical monitors, CRA's, and FDA reviewers,
pharmaceutical companies are faced with an
increasingly complex web of technology. In an effort to
simplify the process, we might look for ways to
integrate the various CIS processes. One way to do
this is to explore existing standards in an effort to
expand their use and leverage the investment already
made in training personnel and incorporating the
technology.
SAS software is the de facto standard in the pharmaceutical industry for performing statistical analyses and
presenting the results in graphical or tabular forms.
Once data is in machine readable form, most of the
subsequent processing is typically performed in SAS.
Consequently, it is reasonable to examine whether SAS
can play an expanded role in the CIS.
r<~
I
Supervisor
I
I
I
Although initially a statistical package, much of the
recent development of SAS has been to add features
commonly associated with relational database
management systems and fourth generation languages.
Version 6 of SAS adds a number of features that are of
particular strategic importance to the pharmaceutical
industry. Version 6 offers the potential to easily port
CIS applications to other hardware platforms due to
multi-vendor architecture. A CIS might operate on
personal workstations, department VAX computers,
and enterprise wide IBM mainframes, all with a
Proper Engine I
I
Figure 14: Multiple Engine Architecture
Multi-vendor architecture refers to the ability of a SAS
program written for one computer to be used on other
computers. This is particularly important in the
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ROSENBERG I Clinical Info Systems
common user interface. The addition of PROC SQL,
indexing, data compression, and other database
management tools has the potential to make storage of
data in SAS datasets sufficiently powerful for some
companies. Other companies that require a database
management system can develop applications
independent of the particular DBMS used, due to
multiple engine architecture. The transition from one
DBMS to another or the sharing of information
between divisions that use different databases can be
enhanced.
Wallace, Emily P. (1989). Database Interfaces Under
the Version 6 Engine Architecture. Proceedings of the
Fourteenth Annual SAS Users Group International
Conference. SAS Institute Inc., cary, NC. pp. 347-349.
ACKNOWLEDGEMENTS
CLINACCESS is a trademark of MAJARO
lNFOSYS1EMS, INC., Mountain View, CA, USA
All CLINACCESS screens shown are Copyrighted (C)
1988, 1989 by MAJARO INFOSYS1EMS, INC. and are
used by permission.
This paper has explored many of the existing and
emerging features of SAS software and has shown that
it may be able to play a prominent role in developing
integrated, powerful, yet easy to use clinical
information systems for the 1990's. Many of the ideas
of this paper have already been incorporated into the
CuNACCEss™
clinical
data
review
system.
CuNACCESS is available on IBM mainframes under
MVS and VM/CMS and is currently being ported to
IBM PC compatibles under MS-DOS. Support for
other hardware platforms and operating systems is
anticipated.
SAS, SAS/AF, and SAS/FSP are the registered
trademarks of SAS Institute Inc., cary, NC.
DEC, VAX, VMS, and Rdb/VMS are trademarks of
Digital Equipment Corporation.
Macintosh is a
registered trademark of Apple Computer Inc. IBM is a
registered trademark and DB2, SQL/DS, OS/2, and
Presentation Manager are trademarks of International .
Business Machines Corporation. Oracle is a registered
trademark of Oracle Corporation. MS-DOS is a
registered trademark of Microsoft Corporation. UNIX
is a registered trademark of AT&T.
For a number of years now, we've witnessed the
evolution of SAS software into a product with greater
interactivity and data management capabilities.
Version 6 is a major step in that evolution. Companies
that start now to explore these new capabilities and
learn to exploit them, will have the potential of
realizing substantial advantages over their competitors
in terms of reducing the cost and time needed to bring
a new drug to the market.
MAJARO INFOSYS1EMS INC. provides statistical
and information management services to the
pharmaceutical, biotechnology, and food products
industries, and specializes in extending computer
technology to non-traditional users.
REFERENCES
Rosenberg, Martin J. (1988). Using the SAS System
to Facilitate Clinical Trials Research and NDA
Approval. Proceedings of the Thirteenth Annual SAS
Users Group International Conference. SAS Institute
Inc., cary, NC. pp. 550-556.
For further information regarding this paper,
please contact:
Martin J. Rosenberg, Ph.D.
MAJARO INFOSYS1EMS, INC.
99 East Middlefield Road
Suite 31
Mountain View, CA 94043
tel. (415) 961-8432
(415) 961-9260
Rosenberg, Martin J.
(1989).
An Integrated
Approach to Computer Systems for NDA Preparation
and Presentation. Proceedings of the Fourteenth Annual
SAS Users Group International Conference.
SAS
Institute Inc., cary, NC. pp. 786-792.
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