A nursing information system (NIS) is defined as integrating nursing science, computer science, and information science to manage and communicate patient data, information, and knowledge to support nursing practice. The purpose of a NIS is to create usable patient data, process information to support management functions, assist in patient care decisions, and formulate nursing care plans. A NIS has advantages like easy access to data, time savings, and quality checks, but also disadvantages like threats to data security and overdependence on technology.

1. NURSING
INFORMATION
SYSTEM

2. INTRODUCTION
• Health sector is consumer oriented.
• Advancement of information technology enhances
nursing care.
• Combination of nursing science, computer science,
communication technology.

3. DEFINITION of NIS
A specialty that integrates nursing, science,
computer science & information science to
manage & communicate data, information &
knowledge in nursing practice.

4. PURPOSE
• To create pertinent patient data in usable form.
• To process information to support managerial
functions.
• To assist in taking the operating decisions.
• To provide a framework to take patient care
decisions.
• To formulate nursing care plan for families &
patients.

5. COMPONENTS
NIS
Inform
ation
science
Analyti
cal
science
Compu
ter
science
DATA
INFORMATION
KNOWLEDGE
WISDOM
IDENTIFY
DEFINE
MANAGE
COMMUNICATE

6. ADVANTAGES
• Easy accessibility of data.
• Time saving
• Quality check.
• Cost consuming.
• Aids in policy making.
• Ensure quality based care.
• Easy & quick storage.

7. DISADVANTAGES
• Threat to data security.
• Over dependency on technology.
• Special skills.
• Accidental loss of data.
• Problems of adjustability.

8. TYPES OF DATA
Administrative
data
Electronic
Health
Records
Clinical Data
Insurance
Claim Data
Patient
surveys

9. DATA ANALYSIS
• Analysis refers to the act of computation,
categorization, comparison, manipulation.
• Depending on ability to measure the attribute &
group them according to certain criteria.
• Making the conceptual definition to operational
definition.
• Setting criteria to group data.

10. DATA ANALYSIS
HEALTH
DATA
DATA
COLLECTION
ANALYSIS
OF DATA
OUTCOME

11. EVALUATION OF DATA
• Comparison
• Inference
• Projection
• Conclusion
• Can be presented as narrative, table, graphical
presentation.

12. STEPS
Problem
Identification
Identification
of data
Planning for
analysis
Extracting
& Loading
Data
Checking &
preparation
of data
analysis
Analyzing &
interpreting
data
Dissemin
ation of
new
knowledg
e
Applying
knowledge
in Decision
Making

13. APPLICATION
• Diagnosis & Treatment
• Disease control
• Performance appraisal
• Track on health status of population