Suggested Resources The resources provided here are optional. You may use other resources of your choice to prepare for this assessment; however, you will need to ensure that they are appropriate, credible, and valid. The MHA-FP5064 Health Care Information Systems Analysis and Design for Administrators Library Guide can help direct your research, and the Supplemental Resources and Research Resources, both linked from the left navigation menu in your courseroom, provide additional resources to help support you. The Role of Informatics in Health Care The following articles address the increasingly important role of informatics, which may provide useful insight when examining the data needs of an organization. · Centers for Medicare & Medicaid Services. (2017). Data and program reports. Retrieved from https://www.cms.gov/regulations-and-guidance/legislation/ehrincentiveprograms/dataandreports.html . The Web page provides access to Medicare and Medicaid Electronic Health Records Incentive Program payment and registration data contained in various reports. · Chen, M., Lukyanenko, R., & Tremblay, M. C. (2017). Information quality challenges in shared healthcare decision making. Journal of Data and Information Quality (JDIQ), 9(1), 1–3. . Discusses the challenges for patients in making sense of the enormous volume of health information made available through current information and communications technologies and how the quality of that information affects shared decision-making between patients and providers. · Crawford, M. (2014). Making data smart. Journal of AHIMA, 85(2), 24–27, 28. . Discusses applied informatics and how it can be used to derive useful information from big data, as health care becomes a data-driven industry. · Dinov, I. D. (2016). Methodological challenges and analytic opportunities for modeling and interpreting big healthcare data. GigaScience, 5(1), 1–15. . Discusses the challenges of big data analysis and addresses the need for technology and education in creating valuable knowledge assets from big data. · Hegwer, L. R. (2014). Digging deeper into data. Healthcare Financial Management, 68(2), 80–84. . Discusses the role of data analysts in improving the financial and clinical performance of health care organizations. 2 Running Head: Organizational Data needs 2 Organizational Data needs Organization Data Needs Capella UniversityAssignment 2 Internal data sources can include data systems, for example, a radiology data system, medical library data, or the patient finance and billing system. Internal data sources also include EHR data systems such as the demographics, medical history of patients and disease records, medication and allergies records, laboratory test results, personal patient statistics such as gender age, weight and billing information (Porter et al, 2018). External data sources include data from Centres for Medicare and Medicaid Services (CMS), benchmarking data from other hospitals are ex.

1. Suggested Resources
The resources provided here are optional. You may use other
resources of your choice to prepare for this assessment;
however, you will need to ensure that they are appropriate,
credible, and valid. The MHA-FP5064 Health Care Information
Systems Analysis and Design for Administrators Library
Guide can help direct your research, and the Supplemental
Resources and Research Resources, both linked from the left
navigation menu in your courseroom, provide additional
resources to help support you.
The Role of Informatics in Health Care
The following articles address the increasingly important role of
informatics, which may provide useful insight when examining
the data needs of an organization.
· Centers for Medicare & Medicaid Services. (2017). Data and
program reports. Retrieved from
https://www.cms.gov/regulations-and-
guidance/legislation/ehrincentiveprograms/dataandreports.html
. The Web page provides access to Medicare and Medicaid
Electronic Health Records Incentive Program payment and
registration data contained in various reports.
· Chen, M., Lukyanenko, R., & Tremblay, M. C.
(2017). Information quality challenges in shared healthcare
decision making. Journal of Data and Information Quality
(JDIQ), 9(1), 1–3.
. Discusses the challenges for patients in making sense of the
enormous volume of health information made available through
current information and communications technologies and how
the quality of that information affects shared decision-making
between patients and providers.
· Crawford, M. (2014). Making data smart. Journal of AHIMA,
85(2), 24–27, 28.
. Discusses applied informatics and how it can be used to derive
useful information from big data, as health care becomes a data-

2. driven industry.
· Dinov, I. D. (2016). Methodological challenges and analytic
opportunities for modeling and interpreting big healthcare
data. GigaScience, 5(1), 1–15.
. Discusses the challenges of big data analysis and addresses the
need for technology and education in creating valuable
knowledge assets from big data.
· Hegwer, L. R. (2014). Digging deeper into data. Healthcare
Financial Management, 68(2), 80–84.
. Discusses the role of data analysts in improving the financial
and clinical performance of health care organizations.
2
Running Head: Organizational Data needs
2
Organizational Data needs
Organization Data Needs Capella UniversityAssignment 2
Internal data sources can include data systems, for example, a
radiology data system, medical library data, or the patient

3. finance and billing system. Internal data sources also include
EHR data systems such as the demographics, medical history of
patients and disease records, medication and allergies records,
laboratory test results, personal patient statistics such as gender
age, weight and billing information (Porter et al, 2018).
External data sources include data from Centres for Medicare
and Medicaid Services (CMS), benchmarking data from other
hospitals are external data used to improve the performance of
the facility. The audit of the stock of Vila Health data systems
by the Working Groups included an appraisal of basic data holes
and needs that presently exist. The Department should
coordinate concentration and consideration in pushing ahead to
address these and different needs, keeping in mind the
following external data: health status results, protection
inclusion rates, access, and quality pointers, medicinal services
consumptions and population health status measures.
Other external data include; results form monitoring the conduct
of States, health plans, management systems, suppliers, and
shoppers with regards to ACA. The health status and health
services variations of a vulnerable population, for example,
racial and ethnic population, people with handicaps, country
population, and the LGBT population. State and network-level
strategy and general health data.
To address such needs Vila Health data systems should be
progressively receptive to strategy needs as far as practicality,
adaptability, granularity, and the ability to screen change after
some time. Likewise, thought of non-customary data sources,
for example, those accessible in the business segment will
address a few data needs (Porter et al, 2018). Changes in the
sufficiency of social insurance establishments and workforce to
address issues. Social determinants of health and the changing
idea of population health past the medicinal services
conveyance system.
On account of a healthcare data system, data collected could be
explicit to requesting or administering, inclusive of the date,
time and term, sedate structure, dose, course, recurrence, and

4. any uncommon guidelines. To encourage the electronic sharing
of data, wordings, for example, the National Drug Code (NDC)
and RxNorm are used and ought to be characterized in the data
lexicon. The NDC contains data on the manufacturer, the size of
the bundle, the measurement plan and on the off chance that it
is conventional versus brand. RxNORM is kept up by the
National Library of Medicine and gives names and one of a kind
identifier to clinical medications.
Surely, every datum source is one of a kind in its own particular
manner. Being sure about the area of the data, understanding its
procedures of assortment, the management, and connection to
every one of your contributing sources will enable you to
develop a situation of trust, worth, and effectiveness.
Health services systems keep on creating skills for catching,
dispersing, and making a move on data from external sources.
The procedure to decide how to make such data important is in
its earliest stages, however its capability to substantially
improve the nature of care, increment persistent fulfillment
while bringing down expenses is extraordinary.
Collecting data into an EDW from internal, dissimilar, clinical,
authoritative, and money related systems is the main basic
advance to distinguish open doors for quality improvement and
cost reserve funds. As the change to esteem-based consideration
keeps on picking up force, the achievement will be dictated by
how viably external data is included into the EDW.
Conglomerating external and internal data empower pioneers to
effectively supervise and oversee current agreements. It enables
the whole group to secretly plan to convey esteem-based
consideration later on.
Investigating section data has consistently been a piece of
medicinal services as clinics Endeavor to address the issues of
patients in the networks they serve. The development of shared
responsibility understandings set up money related motivating
forces for organizations to convey top-notch, tolerant focused
consideration at lower costs.
Social insurance organizations are extremely excited about

5. benchmarking. Most clinics and health systems buy into some
sort of benchmarking administration. These administrations
convey fixed arrangements of reports to supporters which, when
joined in the EDW, can enable organizations to direct their very
own exhibition benchmarking.
Numerous health services organizations are entering, or are
wanting to enter, into some sort of in risk agreement, for
example, a packaged instalment program, a Medicare Advantage
plan, or an ACO. Effectively coordinating external and internal
cases data empowers pioneers to regulate these agreements all
the more adequately. Data from CMS and business payers speak
to the most widely recognized sort of outside data right now
consolidated by health systems into their EDW.
Coordinating cases data isn't without its difficulties. Guarantee
data collections regularly slack the conveyance of care by in
any event 60 days. Some case data collections are de-
distinguished, constraining the bits of knowledge gathered from
them.
Expanding the helpfulness of cases data frequently requires
coordinating the patient on each guarantee with a patient in the
EHR utilizing an ace patient record. At times, there may not be
an appropriate coordinating innovation previously conveyed.
The steady venture required to coordinate case data into the
EDW is vital, even crucial, to achieve accomplishment in risk-
based agreements.
The fundamental difficulties with stacking benchmarking data
are anonymization and the total idea of benchmarking data.
Anonymization implies benchmarking administrations regularly
don't send data for a specific, named emergency clinic. The data
gave is to "a network medical clinic with between 200-300
beds."
Benchmarking data is generally not as adjusted as clinical or
case data. Rather than getting data containing the individual
pneumonia readmissions rates for 17 explicit clinics, the reports
give the normal pneumonia readmissions rate for a gathering of
17 mysterious emergency clinics.

6. An organization needs a significant level of investigative
mastery in customer and family unit data to comprehend,
convey, and make a move on the data form these data sources.
To take care of explicit issues, numerous organizations utilize
experts to help them in this procedure. A chosen few, enormous
organizations, with critical examination abilities and committed
key arranging assets, will think that its advantageous to do take
this kind of investigation on themselves.
One incredible procedure to support the utility of data is to
include data from at least two sources. This can be practiced,
for instance, by connecting two overviews, connecting reviews
with managerial data, connecting authoritative data with clinical
data, and other data linkages.
Strategies for meeting the data needs may include fitting the
message—Communication intended for an individual dependent
on data from the person., focusing on the message to crowd
portions—Communication intended for subgroups dependent on
bunch enrolment or qualities, for example, age, sexual
orientation or sex, race, social foundation, language, and other
"psychographic" attributes, for example, an individual's frames
of mind about specific topic, utilizing accounts—
Communication conveyed as a story, tribute, or diversion
training.
Custom fitted correspondence conveyed by means of print or the
Internet is more compelling than nontailored correspondence in
expanding data and evolving conduct. Impact sizes can change
depending on the length of follow-up, factors customized, sort
of conduct, populations considered, and the number of
intercession contacts.
Story types of correspondence increment data preparing and
increment the influence of messages; individuals become
shipped into a circumstance that can upgrade feelings, frames of
mind, and practices. While thinking about dissemination
methodologies, instructive effort and scholastic specifying are
the most reliably successful mediations.

7. References
Bundled Payments for Care Improvement Initiative Fact Sheet.
(2014), January 30, from Centers for Medicare & Medicaid
Services website, https://www.cms.gov/newsroom/fact-
sheets/bundled-payments-care-improvement-initiative-fact-sheet
Porter A, Potts H, Mason S, Morgan H, Morrison Z, Rees N,
Shaw D, Siriwardena N, Snooks H, Williams V (2018). The
digital ambulance: Electronic patient clinical records in
prehospital emergency care. BMJ Open, 8(Suppl 1): A26-7
NEMSIS - National EMS Information System". nemsis.org.
Archived from the original on 8 June 2017. Retrieved 31 May
2017.
1/11/2020 Capella University Scoring Guide Tool
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MHA-FP5064
u02a1 - Using Data for Decision Making
Learner: Monna , Joseph
OVERALL COMMENTS
Mona

8. I reviewed your second attempt and still have concerns about
the lack of academic support and how geneal the
analysis is. I am still not seeing enough clarity. Most statements
are not specific to the topic and just general
statements about data. I need to see a high level analysis and
explanation of data types specific to the Vila health
setting and supported by academic references.
You are not following APA - please review APA format
resources and examples. See my comments in the rubric
RUBRICS
1/11/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 2/8
CRITERIA 1
Describe the types of internal data available within a health care
system.
COMPETENCY
Apply data classification and management techniques to
decision making as a health care administrator.
NON_PERFORMANCE: Does not list broad categories of data
available within a health care system.

9. BASIC: Lists broad categories of data available within a health
care system.
PROFICIENT: Describes the types of internal data available
within a health care system.
DISTINGUISHED:
Describes the types of internal data available within a health
care system needed to support high-level
decision making. Identifies areas of uncertainty and information
gaps detrimental to effective decision
making.
Comments:
Both external and internal data were listed but the explanation
was very broad. You are not talking about
EHR data. Patient data, workflow and satisfaction data the helps
the organization
(16%)
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CRITERIA 2
Describe the types of external data available within a health
care system.

10. COMPETENCY
Apply data classification and management techniques to
decision making as a health care administrator.
NON_PERFORMANCE: Does not list broad categories of data
available within a health care system.
BASIC: Lists broad categories of data available within a health
care system.
PROFICIENT: Describes the types of external data available
within a health care system.
DISTINGUISHED:
Describes the types of external data available within a health
care system needed to support high-level
decision making. Identifies areas of uncertainty and information
gaps detrimental to effective decision
making.
Comments:
Consider specific data to help improve processes at the
organization and drive deciion making such as
demographic data, public health data etc.
(14%)

11. 1/11/2020 Capella University Scoring Guide Tool
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CRITERIA 3
Propose strategies for accessing and analyzing available data.
COMPETENCY
Apply data classification and management techniques to
decision making as a health care administrator.
NON_PERFORMANCE: Does not propose strategies for
accessing and analyzing available data.
BASIC:
Proposes strategies for accessing and analyzing available data
that are insufficient or impracticable.
PROFICIENT: Proposes strategies for accessing and analyzing
available data.
DISTINGUISHED:
Proposes strategies for accessing and analyzing available data.
Provides a concise, unbiased
assessment of the advantages and disadvantages inherent in each
approach.
Comments:
Your strategy is not addressing key approaches to using HIM
data to imrprove process I need need to see

12. current trends and best practices.
(14%)
1/11/2020 Capella University Scoring Guide Tool
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CRITERIA 4
Summarize the data needs within a health care system.
COMPETENCY
Apply data classification and management techniques to
decision making as a health care administrator.
NON_PERFORMANCE: Does not summarize the data needs
within a health care system.
BASIC:
Provides a superficial summary that overlooks data needs that
decision makers must be cognizant of.
PROFICIENT: Summarizes the data needs within a health care
system.
DISTINGUISHED:
Summarizes the data needs within a health care system.
Provides a concise, accurate summary and

13. proposes suitable criteria for prioritizing data needs.
Comments:
(14%)
1/11/2020 Capella University Scoring Guide Tool
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CRITERIA 5
Propose strategies for meeting the data needs of a health care
system.
COMPETENCY
Apply data classification and management techniques to
decision making as a health care administrator.
NON_PERFORMANCE:
Does not propose strategies for meeting the data needs of a
health care system.
BASIC:
Proposes strategies for meeting the data needs of a health care
system that are insufficient or
impracticable.
PROFICIENT: Proposes strategies for meeting the data needs of
a health care system.

14. DISTINGUISHED:
Proposes strategies for meeting the data needs of a health care
system. Provides a concise, unbiased
assessment of the advantages and disadvantages inherent in each
approach.
Comments:
I am not seeing your concise, unbiased assessment of the
advantages and disadvantages inherent in
each approach supported by evidence-based literature.
(14%)
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CRITERIA 6
Propose communication strategies for disseminating strategic
information to end-users.
COMPETENCY
Communicate effectively with diverse audiences, in an
appropriate form and style, consistent with
applicable organizational, professional, and scholarly standards.

15. NON_PERFORMANCE:
Does not propose communication strategies to disseminate
information to end-users.
BASIC:
Proposes communication strategies to disseminate information
to end-users that are insufficient or
impracticable.
PROFICIENT:
Proposes communication strategies for disseminating strategic
information to end-users.
DISTINGUISHED:
Proposes communication strategies for disseminating strategic
information to end-users. Presents
sound evidence to support the contention that the proposed
strategies will be effective.
Comments:
I am not seeing enough depth on communication strategies
specific to Vila Health's setting. You needed to
present strategic information to end-users. Presents sound
evidence to support the contention that the
proposed strategies will be effectiv
(14%)

16. 1/11/2020 Capella University Scoring Guide Tool
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CRITERIA 7
Write clearly and concisely, using correct grammar, mechanics,
and APA formatting.
COMPETENCY
Communicate effectively with diverse audiences, in an
appropriate form and style, consistent with
applicable organizational, professional, and scholarly standards.
NON_PERFORMANCE:
Does not write clearly and concisely, using correct grammar,
mechanics, and APA formatting.
BASIC:
Writing is unclear and disorganized, includes errors in grammar
and mechanics that inhibit effective
communication, or contains incorrect or improperly formatted
source citations and references.
PROFICIENT: Writes clearly and concisely, using correct
grammar, mechanics, and APA formatting.
DISTINGUISHED:

17. Writes clearly and concisely. Grammar, mechanics, and APA
formatting are error-free.
Comments:
APA was not followed for references -references in APA should
be using hanging indent and headings aer
bold/centered.
(14%)