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Segment Winner
Konfidence
2yr Trend
N/A
Average Segment Score83.5
50
95.9
Schedule360 Employee Scheduling and Labor Management
100
Culture
A+
Loyalty
A+
Operations
A
Product
A
Relationship
A+
Value
A+
2
Konfidence
2yr Trend
N/A
90.5
ShiftWizard
Culture
A
Loyalty
A
Operations
B+
Product
A-
Relationship
A-
Value
A-
3
Konfidence
2yr Trend
88.4
Change Healthcare ANSOS Staff Scheduling
Culture
A-
Loyalty
B+
Operations
B+
Product
B+
Relationship
A-
Value
A
4
Konfidence
2yr Trend
84.3
Virence Health Centricity Staffing and Scheduling (API)
Culture
B-
Loyalty
A
Operations
B
Product
B
Relationship
B
Value
C+
5
Konfidence
2yr Trend
80.5
Kronos Workforce Scheduler
Culture
B-
Loyalty
B+
Operations
C
Product
B-
Relationship
B-
Value
C
6
Konfidence
2yr Trend
73.6
Virence Health Centricity ShiftSelect (API)
Culture
C
Loyalty
C+
Operations
C+
Product
C
Relationship
D+
Value
C+
7
Konfidence
2yr Trend
66.5
Cerner Clairvia
Software 81.2
Culture
F
Loyalty
D+
Operations
C-
Product
D+
Relationship
D+
Value
C
Solutions Not Ranked
Component [C], Not Primary [NP], Regional [R] or Limited Market Share [MS]
*Does not meet minimum KLAS Konfidence level.
Trend does not include the Best KLAS score
Want more insights into this segment?
More information about Scheduling - Nurse and Staff is available via the following KLAS products:
Past Scheduling - Nurse and Staff Awards
Konfidence
Konfidence level
Konfidence Level Description
Products must have at least 30 live organizations participating for software and at least 15 live organizations for professional services. Exception to this is Transcription Services (30).
Products must have at least 20 live organizations participating for software and at least 10 live organizations for professional services. Exception to this is Transcription Services (20).
Products must have at least 15 live organizations participating for software and at least 6 live organizations for professional services. Exception to this is Transcription Services
-
The Konfidence level on this product rating is low. These results are for early trend detection. As more performance data is received, the result is likely to have a wide variance.
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