Download Data Systems in EMS

Document related concepts

Data model wikipedia , lookup

Database wikipedia , lookup

Data center wikipedia , lookup

Operational transformation wikipedia , lookup

Data analysis wikipedia , lookup

Expense and cost recovery system (ECRS) wikipedia , lookup

Entity–attribute–value model wikipedia , lookup

Computer security wikipedia , lookup

Clusterpoint wikipedia , lookup

3D optical data storage wikipedia , lookup

Information privacy law wikipedia , lookup

Business intelligence wikipedia , lookup

Relational model wikipedia , lookup

Open data in the United Kingdom wikipedia , lookup

Data vault modeling wikipedia , lookup

Database model wikipedia , lookup

Transcript
NCAEMSA Winter Conference 2004
Wednesday February 18, 2004
Data Systems and Issues
William E. Ott, MS, Paramedic
CPCS Technologies
www . cpcstech . com
Integrated System
Data
transformation
and scrubbing
EMS
Medical
Examiner
Data
Warehouse
Law
Enforcement Hospitals
Data
Reporting
Medical
Direction
Mobility – PAN, LAN, WAN
802.11b
Local Area
Bluetooth Network wLAN
Personal Area
Network (PAN)
LAN
<1Mbs
• Access
Workgroup
•Synchronization
Switches
•10 Meters
<11Mbs
• Access
•“hot spots”
•LAN equivalent
Wide Area
Network (WAN)
Wireless
Bridge
GPS
9.6 Kbit/s <2Mbs
• mCommerce
• SMS
• Internet access
• e-Mail
• Document transfer
• Web browsing • Low/high quality video
• Voice
EMS as Information Workers
• What is involved?
– Electronic patient records
– CAD data pre and post response
– GIS data pre and post response
– System performance data
– Application of performance data to the
continuing education program
– Personnel data
– System / Vehicle data
– Facility/Event preplan data
Threats to Information Systems
•
•
•
•
•
•
•
•
Malicious abuse
Denial of Service and related attacks
Virus, Worm, and Trojan attacks
Outside Hacker attacks
Theft of service
Theft of information
Poorly trained IT staff
Not staying current with system patches,
antivirus definitions, etc..
• Not performing proper system maintenance
• Poor or no backup and contingency plans
Threats to Productivity
• Spam
– wastes resources
– wastes time
– offensive, dangerous
• Popup ads
– wastes resources
– annoying
• Malicious use of resources
– wastes bandwidth, storage
– violates law and privacy
Threats to Privacy / Confidentiality
•
•
•
•
•
•
•
•
•
•
No security plan
No security training or awareness
Smart or Meta Tags in shared documents
Social Engineering
Unencrypted network
Unencrypted e-mail
No firewall
No antivirus system
Rogue wireless
PDAs connecting to network and servers
Some Security Options
•
•
•
•
•
•
•
•
•
•
Virtual Private Networking (VPN)
Active AntiVirus Screening
Stateful packet inspection Firewalling
Proxy servers
Opt-in e-mail
Database encryption
E-mail encryption
Network / PC security policies
Two Factor User Authentication
Aggressive Audit logging and review
Sources of Threats
• Employees
– Unintentional - acting in good faith
– Intentional - disgruntled or unhappy staff
– Software errors
• Environment
– Equipment failure
– Fire, flood, earthquake
Comprehensive Security Policy
• The policy must address:
– Physical Security
– Computer hardware and software
inventory
– Personnel screening and selection
– Ongoing education
– Access and control procedures
Comprehensive Security Policy
• Must also address:
– Procedures for release of information
– Disposal of data
– Data backup and recovery
– Contingency planning
– Sanctions for noncompliance
– Periodic review
Costs of Security
• Reduced access to information.
• Increased time and effort to access
information.
• Hardware and software to implement
security.
• Staff time to implement and maintain
security system.
Physical Security
• Control access to servers and network
equipment.
• Locate workstations in secure area, not
easily accessible to the public.
• Provide surge protection and
uninterruptible power supplies.
• Provide fire alarms and fire suppression
equipment.
Hardware Security
• Hardware should be dependable.
• Non-proprietary to allow for easy repair and
replacement.
• Critical systems should be mirrored and spare
parts available for likely to fail components.
• Routine maintenance and tuning should be done.
Have a service contract in place!
• Maintain accurate and up to date inventory.
Software Security
• Applications should be chosen with security in
mind.
• Should have the capability of encryption for data
storage and communication.
• System security software:
– Firewall
– Intrusion detection
– Anti-virus
– Disk defragmenter
• Maintain accurate and up to date inventory.
Access control
• Protect critical resources by limiting access
to authorized and authenticated users.
• Specify:
– who can access the information,
– how it can be accessed,
– when it can be accessed, and
– under what conditions it can be accessed
What Are Potential Disasters?
 External
• Storms (hurricanes, tornados, floods, hail…)
• Accidents (planes, trains, automobiles, hazardous
mat.)
• Regional Outages (power, communications…)
• Violence (civil unrest, terrorist acts, bioterrorism…)
 Internal
• Hardware Failures (servers, data stores, cyber
attacks..)
• Accidents (fires, water leaks, electrical…)
• Violence (disgruntled employee, corp. sabotage…)
Contingency Planning
• Plan for interruption of service.
• Have alternate plan for data capture and
retrieval. (Paper?)
• Have adequate security for alternate plan.
Data Backup and Recovery
•
•
•
•
One of the most crucial components!
Most likely component to be ignored.
Practice data recovery!
Use data protection schemes such as
mirroring, RAID.
• Large agencies should consider
hot sites.
Disposal of Data
• Discarded computer parts and peripherals
should be dependably erased or destroyed.
• Removable media should be accounted for.
• Hardcopy printed from computerized
records should be controlled.
System Components
Control
Mechanism
Input
Output
Transformation
Four Parallel Systems
•
•
•
•
User system
Data system
Software system
Hardware system
User
Data
Software
Hardware
Input
• Automatic data
capture
• User Assisted
– Optical Mark
Reader (OMR)
– Optical Character
Reader (OCR)
– Keyboard
– Voice recognition
Control
Mechanism
Input
Output
Transformation
Transformation
• Data is collected and
analyzed
• Aggregation
• Analysis
• Validation
Control
Mechanism
Input
Output
Transformation
Output
• Reporting
– Ad hoc
– Exception reports
– Aggregate
• Publishing
– Web-based
Control
Mechanism
Input
Output
Transformation
Control Mechanism
•
•
•
•
Quality improvement
Education
Administrative policies
Medical protocols
Control
Mechanism
Input
Output
Transformation
Systems Architecture
•
•
•
•
•
Stand-alone
Peer network
Mainframe-terminal
Client-server
Terminal-server
Stand Alone
• Each computer functions alone.
• No connection with any other
computers.
• Easy to maintain.
• File transfer by “sneaker net”
only.
Peer Network
• Computers connected to each
other.
• Limited to file and print
sharing.
• Connected via local area
network.
• Share of data weakens
security.
• No central control.
Mainframe-Terminal
• May be mini-computer or mainframe.
• Commonly referred to as legacy
system.
• “Dumb” terminals.
• All activity on main computer.
• Connected with cable.
• Normally not GUI based application.
• Not conducive to ad hoc queries and
reporting.
Client-Server
• Client are fully functional
computers.
• Server may host applications.
• File sharing and printing normally
done through server.
• Connected via local or wide area
network.
• May be very secure.
• High cost of multiple client
workstations (purchase and
maintenance)
Terminal-Server
• New technology.
• Multiple “dumb” terminals
connected to server.
• Applications, printing, file storage
are on server.
• Connected via local or wide area
network.
• Centrally maintained software.
• Low-cost network terminal.
Clustering
• Multiple servers.
• Servers are joined and share
processing.
• Service is maintained with
failure of single server.
• Highly dependable with little
down-time.
Database Systems
Schema
• Pronounced SKEE-mah.
• The organization or structure for a
database.
• Often used to refer to a graphical depiction
of the database structure.
Data Components
•
•
•
•
Database
Tables
Records
Columns
Tables
Table Name
Column Names
Patient
PatientID
Address
City
State
ZipCode
Age
DOB
Primary Key
Table
• A collection of
similar data
organized in
columns and rows
(records).
• Concept similar to
a spreadsheet.
Table
Patient Table
PatientID
ORA4567
ORB1111
ORA1234
ORB5678
City
Danville
Orlando
Bithlo
Taft
Column
State
VA
FL
FL
FL
DOB
11/11/54
08/26/17
05/03/38
01/01/74
Row
(Record)
Column
• Each column is
a data element.
• The storage
format for each
column is defined
• Column names
are listed at the
top
Column
Name
Patient Table
PatientID
ORA4567
ORB1111
ORA1234
ORB5678
City
Danville
Orlando
Bithlo
Taft
Column
Data
State
VA
FL
FL
FL
DOB
11/11/54
08/26/17
05/03/38
01/01/74
Data Element
• Data elements
have different
types
• All data in a
column will be
of the same
type.
Patient Table
PatientID
ORA4567
ORB1111
ORA1234
ORB5678
City
Danville
Orlando
Bithlo
Taft
Column
Data
State
VA
FL
FL
FL
DOB
11/11/54
08/26/17
05/03/38
01/01/74
Data Element Types
• Character or text
• Numerical
– Integer
– Fixed
– Real
•
•
•
•
Date (time)
Binary or raw
Memo or long
Link
Data Elements
• Each field has a type.
• The length of the field is set for character
fields.
• Most other fields can expand to
accommodate more data.
Data Elements
• Beware! – Not all fields containing numbers
should be number fields.
• Numbers that are not used in any
arithmetic should be in character fields.
• Examples are Social Security numbers,
telephone numbers and any other
identification number.
Database Front-End
• Front-end: the interface that the user sees to
input and manipulate data.
• Front-ends are usually built using some
programming language such as:
– PowerBuilder
– Visual Basic
– Java
– Delphi
• Usually connect to some relational database.
Database Back-end
• Back-end: the relational database used to
store and manipulate the data.
• Relational database management (RDBM)
Relational Database
• A collection of data items organized as a
set of tables (like spreadsheets).
• Tables may be linked to form new tables.
• Has rows and columns to show the
relationships between items.
• Tree-like structure.
Flat File Database
• Stores information in single file.
• Does not allow a one-to-many relationship.
• Limits the amount of data that may be input
per record.
Desktop DB vs. RDBMS
• Desktop include:
– Access
– Approach
– Filemaker Pro
– FoxPro
• All processing occurs on
the standalone.
• Intended for smaller
databases.
• Front-end included.
• RDBMS include:
– Oracle
– Informix
– DB2
– MS SQL
• Processing occurs on the
server.
• Has tools for larger
databases.
• Requires front-end
programming.
One-to-Many Relationship
One IncidentMany Patients
Incident
Patient
Patient
Patient
Event
Event
Event
Event
Event
Event
Event
Event
Event
Event
Event
Event
One-to-Many Relationship
One PatientMany Events
Patient
Event – IV Access
Event – O2 Admin
Event - Medication
Event - Procedure
Many-to-Many Relationship
Doctor
One PatientMany
Doctors
Doctor
Doctor
One DoctorMany
Patients
Patient
Patient
Patient
Patient
One-to-One Relationships
One Patient-One Home Address
Patient
Home Address
One Ambulance-One Defibrillator
Ambulance
Defibrillator
Keys
• A key field should be present in each table.
• Tables are related (linked) using keys.
• A key may be made of multiple combined
fields.
Primary Keys
• Primary keys are values that uniquely
identify each record within the table.
• Primary keys must always be filled in and
not duplicate any of the other values in the
table.
Foreign Keys
• Tables may contain a “foreign” key.
• Foreign keys are the primary key for a
related table.
• Multiple records may have the same
foreign key that link them to a single record
in the related table.
Table Relationship
Patient
PatientID
Name
Address
City
State
ZipCode
Age
DOB
Primary Key
Foreign Key
Same value
Links the
two tables
Treatment
PatientID
Treatment ID
Medication
Dosage
Route
Table Joins
• May create a new table, “target”,
from the source tables.
• May be temporary – called a “query”.
• May use many tables to assemble the
desired data set.
Table Join
Name
Og Oglesby
John Doe
Patient ID
OR13567
OR54321
Tables are associated
with the primary key
Patient ID Medication
OR54321 Epinephrine
OR13567 ASA
OR54321 Oxygen
OR13567 Atropine
Note: One-to-many relationship
Dosage
1.0 mg
162 mg
12 l/m
1.0 mg
Relational vs. Flat File
• Flat file databases are limited to predefined
number of data occurrences.
• Most desktop databases are
relational, however, some
applications are designed as
flat file.
Relational vs. Flat File
Flat File Database
Name
Patient ID B/P1 Time1 B/P2 Time2
Og Oglesby OR13567 110/80 13:45 116/82 13:55
Relational Database
Name
Patient ID
Og Oglesby OR13567
Patient ID B/P B/P Time
OR13567 110/80 13:45
OR13567 116/82 13:55
OR13567 120/82 14:05
Note: One-to-many relationship
Table Join
Name
Og Oglesby
John Doe
Patient ID
OR13567
OR54321
The Patient ID is the
primary key in the
patient table and the
foreign key in the
medication table
Patient ID Medication
OR54321 Epinephrine
OR13567 ASA
OR54321 Oxygen
OR13567 Atropine
Note: One-to-many relationship
Dosage
1.0 mg
162 mg
12 l/m
1.0 mg
Table Joins
Source
Source
Name
Patient ID
Og Oglesby OR13567
John Doe
OR54321
Name
Og Oglesby
Og Oglesby
John Doe
John Doe
Patient ID
OR13567
OR13567
OR54321
OR54321
Target
Patient ID Medication
Dosage
OR54321 Epinephrine 1.0
mg
OR13567 ASA
162 mg
OR54321 Oxygen
12 l/m
OR13567 Atropine 1.0 mg
Medication Dosage
ASA
162 mg
Atropine
1.0 mg
Epinephrine 1.0 mg
Oxygen
12 l/m
Table Joins
Source
Source
Name
Patient ID
Og Oglesby OR13567
John Doe
OR54321
Name
Og Oglesby
Og Oglesby
John Doe
John Doe
Patient ID
OR13567
OR13567
OR54321
OR54321
Target
Patient ID Medication
Dosage
OR54321 Epinephrine 1.0
mg
OR13567 ASA
162 mg
OR54321 Oxygen
12 l/m
OR13567 Atropine 1.0 mg
Medication Dosage
ASA
162 mg
Atropine
1.0 mg
Epinephrine 1.0 mg
Oxygen
12 l/m
Reporting
Name
Og Oglesby
Og Oglesby
John Doe
John Doe
Name
Og Oglesby
Og Oglesby
John Doe
John Doe
Patient ID
OR13567
OR13567
OR54321
OR54321
Patient ID
OR13567
OR13567
OR54321
OR54321
Medication Dosage
ASA
162 mg
Atropine
1.0 mg
Epinephrine 1.0 mg
Oxygen
12 l/m
Medication
ASA
Atropine
Epinephrine
Oxygen
Dosage
162 mg
1.0 mg
1.0 mg
12 l/m
Reporting
Name
Og Oglesby
Og Oglesby
John Doe
John Doe
Name
Og Oglesby
John Doe
Patient ID
OR13567
OR13567
OR54321
OR54321
Patient ID
OR13567
Medication
ASA
Atropine
Epinephrine
Oxygen
Medication
Dosage
162 mg
1.0 mg
1.0 mg
12 l/m
Dosage
ASA
Atropine
162 mg
1.0 mg
Epinephrine
Oxygen
1.0 mg
12 l/m
OR54321