Grading rubric must be followed!
Instructions:
Create an Excel spreadsheet that defines data elements and formats that support enterprise information management and data integration. Write a data discovery report (4-5 pages) that identifies data quality issues and recommends strategies for addressing and preventing them.
Health care organizations are constantly challenged to assess data quality procedures. Data entered into information systems often contains redundant data elements, disparate data, and inconsistent definitions. Health care technology, such as an EHR system, helps to improve data quality; however, it cannot completely eliminate data quality challenges.
Data can be organized to identify trends, transforming raw data into useful information. Data discovery is a detection process that involves searching for trends, patterns, or specific items in a particular data set. It can also include identifying potential data quality issues and leveraging data mining techniques. Data discovery’s goal is to analyze data from different perspectives, summarize it, and use it to meet organizational needs.
In this assessment, you will investigate potential data quality issues that pose a risk to Independence Medical Center and then propose recommendations to address these issues.
DEMONSTRATION OF PROFICIENCY
By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:
Competency 1: Manage data from multiple sources.Use various strategies to maintain clean data from multiple sources.Describe data quality issues when using multiple sources.Competency 3: Analyze the impacts of data warehousing.Explain data formatting issues when using and storing data from multiple sources.Competency 4: Analyze effects of database design and architecture in integrating and using various data sources.Create a spreadsheet describing data elements and formats supporting enterprise information management and data integration.Competency 5: Communicate professionally in a health care environment.Create clear, well-organized, professional documents that are generally free of errors in grammar, punctuation, and spelling.Follow APA formatting and style guidelines for citations and references.
PREPARATION
Do the following to prepare to successfully complete Assessment 2 on data discovery:
Analyze
Independence Medical Center’s Core Data Sets [XLSX]
. Be sure to analyze all the tabs in the spreadsheet.
INSTRUCTIONS
For this second assessment, continue on in your role as Independence Medical Center’s privacy and security manager. Your boss, the CIO, is impressed with the work you did in recommending a DMGP framework for Independence Medical Center. (This is the work you completed in Assessment 1.) As is often the case in health care administration, good work is rewarded with more work. Various departments at Independence Medical Center have brought potential data quality issues to the CIO’s attention.
As a result, you have a new task. Your boss wants you to conduct an investigation into potential data quality issues that could pose risks to the organization. You will evaluate Independence Medical Center’s core data sets from multiple data sources. After identifying the potential data quality issues, your boss has asked you to prepare a data discovery report in which you propose recommendations to help resolve the data quality issues you identified. As part of this process you will also create a spreadsheet that defines Independence Medical Center’s data elements and formats.
This assessment consists of two parts.
Part 1: Spreadsheet
Based on your analysis of Independence Medical Center’s data sources, systems, and noted recommendations, create a spreadsheet to define data elements and formats. Do this in the Recommendations tab included in the Independence Medical Center’s Core Data Sets [XLSX] spreadsheet. Be sure to create your spreadsheet according to recommended data collection practices and formats that support enterprise information management and data integration.
Part 2: Data Discovery Report
Write a 4–5 page data discovery report that identifies potential issues related to enterprise information management and data integration based on all of the following:
Your boss has asked you to include all of the following headings in your data discovery report and to answer all of the questions underneath each heading:
Best Practices for Clean Data When Using Multiple Sources (1/2 page).What are the best practices for maintaining clean data when using multiple sources?Data Quality Issues When Using Multiple Sources (1 page).What data quality issues in general do organizations face when using multiple sources?What specific data quality issues appear in Independence Medical Center’s core data sets?Data Formatting Issues Related to Integration When Using and Storing Data from Multiple Sources (1 page).What data formatting issues related to integration in general do organizations encounter when using and storing data from multiple sources?What specific data formatting issues appear in Independence Medical Center’s core data sets?Recommendations for Data Sources, Systems, and Core Data Set Items (1 page).What are your top 3–5 recommendations for Independence Medical Center’s data sources, systems, and items to be included in its core data set? Be sure to include the rationale behind your recommendations.Conclusion (1 to 2 paragraphs).What are the 3–5 key pieces of information you want your CIO to remember from your data discovery report?
Note: You know that the CIO has a reputation for asking a lot of questions about how someone came to his or her conclusions. Be sure to include references to current, scholarly, and/or authoritative sources throughout your data discovery report.
Event
Patient
Patient
Middle
Patient
Number Number First Name Initial Last Name Date of Birth Billing Address
1
2
3
4
5
6
7
8
9
10
11
12
123
124
342
444
222
443
154
123
271
345
432
142
End of Worksheet
Mary
Patty
Sue
Mike
Tom
Nick
Dwayne
Mary
Matt
Michelle
Mikkella
Bonnie
N
P
S
M
T
R
S
N
H
G
F
S
Martin
Pepper
Smith
Miller
Tupper
Nicholson
Sampson
Martin
Nillick
Meyer
Biggs
Beaner
1/21/1953
5/16/1969
5/21/1969
12/3/1966
2/15/1972
1/15/1974
4/21/1952
6/30/1954
12/21/1959
8/17/1959
2/6/1965
4/13/1941
333 3rd st
44 So 4th Ave
555 City Street
6 So 6th St
343 My Street
232 23rd St
19 W Nettie Ave
333 3rd St
16 So 6th St
12 Princess Lane
3434 So 9th Ave
345 SE 5th
City
Newark
St. Peters
Newark
Little Town
Little Town
St. Peters
Newark
Little Town
Newark
St. Peters
Little Town
State/
Postal
Province Code
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
Phone
Number
Email Address
55445
55444
33344
22334
22334
33443
34543
333-333-3333
444-444-4444
(555)555-5555
545-555-5444
545-555-5333
(333)222-3333
565-331-3234
marysmail@mail.com
pattysmail@mail.com
suesmail@mail.com
mikesmail@mail.com
tomsmail@mail.com
nicksmail@mail.com
dwaynesmail@mail.com
22334
54323
34542
34221
342-5643
999-333-4444
(999)222-3332
233-444-2222
mattsmail@mail.com
michellesmail@mail.com
mikkellasmail@mail.com
bonniesmail@mail.com
Date
of Visit
Physician
Name
2/2/2007
2/3/2007
2/3/2007
2/4/2007
2/4/2007
2/4/2007
2/6/2007
2/6/2007
2/6/2007
2/6/2007
2/7/2007
2/7/2007
James Jones
John Jabor
Jack Jeffen
Jim Jones
John Jabor
Jack Jeffen
Jones, James
John Jabor
Johns Cousin
Miller, Peter MD
Paul Jabor
Dr. Jeffen
Patient
Number
MNM22
RRA33
NRD33
SSS34
RRA33
DDW
MMM33
NRN8
DSS2
MNM22
MHN3
MGM32
BSB43
Patient
Patient
Middle Date
Last Name First Name Initial of Visit
Martin
Adams
Dunn
Smith
Adams
Wilson
Miller
Nicholson
Sampson
Martin
Nillick
Meyer
Beaner
End of Worksheet
Mary
Richard
Nora
Sue
Richard
Dawn
Mike
Nick
Dwayne
Mary
Matt
Michelle
Bonnie
N
R
NULL
S
NULL
D
M
R
S
N
H
G
S
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
NULL
Ordering
Physician
NULL
Sally Sandy
Dr. Ben Biman
Jack Jeffen
Sandy, Sally MD
Bill Biman
NULL
Jack Jeffen
James Jones
John Jabor
Johns Cousin
Peter Miller
Dr. Jeffen
Test
Visit
Ordered Cost
Strep
CBC
Strep
Staph
Urinalysis
Chem12
CBC
Urinalysis
Protime
Staph
CBC
Urinalysis
Chem12
59
45
59
59
20
45
45
20
34
59
45
20
45
Materials
Cost
34
34
34
34
25
49
34
34
34
34
34
25
49
Name
Group
Status
Davis, Drew MD
Jack Jeffen
James Jones
John Jabor
Nancy Nelson
Paul Jabor
Miller, P.
Sally Sandy
Samuel Smart
Research Staff
Physicians
Physicians
Physicians
Research Staff
Physicians
Physicians
Physicians
Physicians
Staff Researcher
Contractor
Contractor
Staff Physician
Contractor
Staff Physician
Staff Physician
Contractor
Contractor
End of Worksheet
Radiology
Event Number
Patient
Patient
Middle
Patient
Radiology ID First Name Name Last Name
1
2
3
4
5
6
End of Worksheet
123RA
348RA
342RA
444RA
213RA
155RA
Mary
Nora
Sue
Mike
Bonnie
Dwayne
Nora
Rose
Ann
Miles
Sue
Martin
Dunn
Smith
Miller
Beaner
Sampson
Patient
Address
Visit
Date
333 3rd st
12 So 12th St
555 City Street
60 S 6th Strt
NKA
19 W Nettie Ave
2/3/2007
2/3/2007
2/4/2007
2/4/2007
2/4/2007
2/5/2007
Film
Type
Reason
for Visit
CXR
CXR
L Hip
R elbow
L knee
Brain Scan
Pneumonia
Influzenza
R/O Fracture
Tennis Pro
Miniscus tear
R/O thrombosis
Visit Materials
Charge Charge
200
200
300
400
300
1600
345
456
234
434
545
2300
Data Element
Example: Patient Last Name
End of Worksheet
Definition
Legal last name of the patient
Format
Text – 30 characters
Source System
EMR registration screen
Running Head: FRAMEWORK FOR DATA MANAGEMENT & GOVERNANCE PLAN
1
Enterprise Information Management
Enterprise information management structures, describes, and governs information assets.
Enterprise information uses a variety of technologies, disciplines, processes and practices in
order to manage the data within an organization (Hausmann, Williams, Hardy, & Schubert,
2014). Some examples of enterprise information management systems are the enterprise content
management system and the business management process. The enterprise content management
system handles the flow of information including capturing, storing, and achieving information.
The business process system handles analyzing, measuring, and optimizing the business in
relation to information management (van der Lans & van Til, 2013).
Data Governance
Data governance is the availability, integrity, usability, and security of data. Data
governance deals with the provision of policies, guidelines, and processes regarding management
of all data within the health care industry (Korhonen, Melleri, Hiekkanen, & Helenius, 2018).
Additionally, governance is responsible for scheduling updates and the distribution of authority
and guidelines. Regarding the distribution of authority of guidelines, this means that an
organization can institute guidelines involving data including how it is collected, stored,
accessed, and used. Data governance is vital to an enterprise because it ensures the availability,
security, and integrity of data. This allows for improved policies, guidelines, and quality
(Korhonen, Melleri, Hiekkanen, & Helenius, 2018).
Data Governance vs. Data Management
FRAMEWORK FOR DATA MANAGEMENT & GOVERNANCE PLAN
2
Data governance and data management are important components of the enterprise
information management system. Data governance creates and supervises the overall policies in.
In contrast, data management handles the day-to-day operations. For example, with backup
policies, data governance would handle setting up the policies whereas data management would
be responsible for ensuring that the policies are performed correctly and on time (Ladley, 2012).
Another example deals with data security plans. Data governance would include and handle a
review and analysis regarding security whereas data management would be responsible for
coordinating and implementing the process (Ladley, 2012). Data governance tends to include
authoritative roles in contrast to data management that handles day-to-day operations.
Framework for DMGP
Independence Medical Center needs a structure that includes strategic approaches
regarding technology, communication, stakeholders, and functions. The issue with the current
system is that it lacks a strong governing body. Steering committees are an appropriate solution
to this issue. Another issue is that data is handled manually. This causes the system to be
inefficient and time consuming. If Independence Medical Center sets up technology to take over
some of those duties, it would allow the system to run more efficiently. Some technology options
could be metadata repository, data integration techniques, and lifecycle tools.
The structure for Independence Medical Center should be a centralized governance and
decentralized execution structure. There are a few different advantages to this structure. One
advantage is that a steering committee will be added and in charge of data integration. This
steering committee will include people with experience involving different collection techniques.
Another advantage is that this structure would require the addition of a communication system.
FRAMEWORK FOR DATA MANAGEMENT & GOVERNANCE PLAN
This system allows the various data users within the organization to communicate more
effectively.
Conclusion
As outlined above, the primary goal of this data management and governance plan is to
add a steering committee and increase the amount of technology used in order to create a more
efficient system. The creation of a steering committee allows for a strong governing body to be
put in place. The increase in technology allows for a decrease in time consuming manual work.
Diagram
3
FRAMEWORK FOR DATA MANAGEMENT & GOVERNANCE PLAN
4
References
Hausmann, V., Williams, S. P., Hardy, C. A., & Schubert, P. (2014). Enterprose Information
Management Readiness: A Survey of Current Issues, Challenges, and Strategy. Procedia
Technology.
Korhonen, J. J., Melleri, I., Hiekkanen, K., & Helenius, M. (2018). Designing Data Governance
Structure: An Organizational Perspective. GSTF Journal on Computing (JoC).
Ladley, J. (2012). Data Governance: How to Design, Deploy, and Sustain an Effective Data
Governance Program. Waltham, MA: Elsevier.
van der Lans, A., & van Til, P. (2013). Enterprise Information Management (EIM). Springer,
NY.
CRITERIA
NON-PERFORMANCE
BASIC
Use various strategies to
maintain clean data from
multiple sources
Does not use various
strategies to maintain clean
data from multiple sources
Attempts to use various
strategies to maintain clean
data from multiple sources:
however, omissions and/or
errors exist
PROFICIENT
Uses various strategies to
maintain clean data from
multiple sources
DISTINGUISHED
Uses various strategies to
maintain clean data from
multiple sources. Narrative
includes multiple examples
and references to current,
scholarly, and/or
authoritative sources
Describe data quality issues
when using multiple sources.
Does not describe data
quality issues when using
multiple sources
Attempts to describe data
quality issues when using
multiple sources, however,
omissions and/or errors
exist
Describes data quality
issues when using multiple
sources.
Explain data formatting issues
when using and storing data
from multiple sources
Does not explain data
formatting issues when
using and storing data from
multiple sources
Attempts to explain data
formatting issues when
using and storing data from
multiple sources. However,
omissions and/or errors
exist
Explains data formatting
issues when using and
storing data from multiple
sources
Describes data quality
issues when using multiple
sources. Description
includes multiples
examples and references to
current scholarly, and/or
authoritative sources
Explains data formatting
issues when using and
storing data from multiple
sources. Explanation
includes multiple examples
and references to current,
scholarly, and/or
authoritative sources
Creates a
spreadsheet describing
industry-approved best
practices for data elements
and formats that support
enterprise information
management and data
integration
Create a spreadsheet describing Does not create a
data elements and formats spreadsheet describing
data elements and formats
supporting enterprise information supporting enterprise
management and data
information management
integration
and data integration
Creates a
spreadsheet describing
data elements and formats
supporting enterprise
information management
and data integration
Create clear, well-organized,
professional documents that are
generally free of errors in
grammar, punctuation, and
spelling
Does not create documents
that are clear, well
organized, professional,
and generally free of errors
in grammar, punctuation,
and spelling
Attempts to create a
spreadsheet describing
data elements and formats
supporting enterprise
information management
and data integration
However, omissions and/or
errors exist
Attempts to create
documents that are clear.
well organized,
professional, and generally
free of errors in grammar
punctuation, and spelling
However, lapses
omissions, and/or errors
exist
Attempts to follow APA
style and formatting
guidelines for citations and
references, however,
omissions and/or errors
exist
Creates clear, well-
organized, professional
documents that are
generally free of errors in
grammar, punctuation, and
spelling
Creates clear, well-
organized, professional,
and error-free documents.
Documents contain multiple
examples and references to
current, scholarly, and/or
authoritative sources
Follow APA style and formatting
guidelines for citations and
references
Does not follow APA style
and formatting guidelines
for citations and
references
Follows APA style and
formatting guidelines for
citations and references
Follows APA style and
formatting guidelines for
citations and references
without omissions and/or
errors