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Quality Assurance Program. Pre-Conference. Quality Assurance Pre-Conference. FSA Assessment Case Study. “ Coming together is a beginning; Keeping together is progress; Working together is success” - Henry Ford. Session Objectives.

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quality assurance pre conference

Quality Assurance Pre-Conference

FSA AssessmentCase Study

slide3
“Coming together is a beginning;

Keeping together is progress;

Working together is success”

- Henry Ford

session objectives
Session Objectives
  • Experience the Value of an FSA Assessment Activity and the Management Enhancement Form
  • Learn the importance of team workto resolve a finding.
instruction
Instruction

Work with your table to discuss the Management Enhancement/Action Plan.

If other stakeholders are needed to assist in the resolution of your plan, assign a team member to discuss issue(s) with appropriate stakeholders:Financial Aid Office, Business Office, Student, Senior Management or Computer Center

lessons learned
Lessons Learned
  • Don’t Assume
  • FSA Assessment Activities and the Management Enhancementare valuable tools
  • Team Work – is a necessity
session objectives1
Session Objectives
  • Learn where to locate the FSA Assessments
  • Review FSA Assessment Highlights
  • Introduce Policies and Procedures Component
  • Learn FSA Assessment requirements for QA schools
where to find the fsa assessments
Where to find the FSA Assessments

Web address:We recommend that you save it as a favorite

http://ifap.ed.gov/qahome/fsaassessment.html. 

Or

IFAP.ed.gov

fsa assessment highlights
FSA Assessment Highlights
  • This Chart: Ways to use the assessments
  • Policies and Procedures: Ensure you are meeting minimum requirements
  • Management Enhancement: How to track your progress
policies and procedures
Beginner, Intermediate and Advanced Users

Minimum Requirements

Regulations

Demo: Go live to the FSA Assessment

Policies and Procedures
qa program requirements for the fsa assessments
QA Program Requirements for the FSA Assessments
  • Complete two assessments or activities
  • Notify QA Regional Representative of the two assessments
  • If applicable, complete the Management Enhancement Form
session objectives2
Session Objectives
  • Complete a Team Building Exercise
  • Learn the value of a team
  • Access Team Building Resources
team building web site
Team Building Web Site

http://www.teambuildinginc.com/tps/002.htm

mission accomplished
Mission Accomplished
  • Completed a team building exercise
  • Learned the value of a team
  • Found Team Building Website
qa program pre conference

QA Program Pre-Conference

The Detail

on

Data Analysis

David Rhodes

Anne Tuccillo

slide23

“Statistics are like a bikini. What they reveal is suggestive, but what they conceal is vital.”

Aaron Levenstein

session objectives3
Session Objectives
  • Share program-wide analyses
  • Share institutional profiles
  • Go over your analysis requirements for 2008-09 and 2009-10
  • Remind schools about verification status codes in COD
session objectives cont d
Session Objectives (Cont’d)
  • Introduce a new “EFC Impact Analysis” standard report
  • Preview a new shared report
  • Provide tips on applying and sharing results
analysis of 2006 07 sample data
Analysis of 2006-07 Sample Data
  • 132 schools
  • Average enrollment was 20,105
  • Disbursed 11% of all Pell Grants in 2006-07
  • 62,958 individual ISIR records
schools by sector
Schools by Sector

Analysisof Quality Assurance Program Sample Data: 2006–07

verification status by sector
Verification Status by Sector

Analysisof Quality Assurance Program Sample Data: 2006–07

classifying the effect of verification on eligibility
Classifying the Effect of Verification on Eligibility
  • No change—EFC and Pell Grant Award remained the same
  • Major decrease—Pell Grant decreased or EFC increased at least 400
  • Major increase—Pell Grant increased or EFC decreased at least 400
classifying the effect of verification on eligibility cont d
Classifying the Effect of Verification on Eligibility (Cont’d)
  • Minor decrease—EFC increased less than 400 and Pell Grant remained the same
  • Minor increase—EFC decreased less than 400 and Pell Grant remained the same
change in eligibility by sector
Change in Eligibility by Sector

Analysisof Quality Assurance Program Sample Data: 2006–07

irs and other isir data
IRS and Other ISIR Data
  • To what degree are the corrections uncovered by verification limited to the fields addressed by a potential IRS match – adjusted gross income and taxes paid?
  • What portion of the changes in aid eligibility captured by current federal verification worksheets are due to adjusted gross income and U.S. taxes paid data?
types of change observed
Types of Change Observed

Analysisof Quality Assurance Program Sample Data: 2006–07

share of estimated change to efc
Share of Estimated Change to EFC

Analysisof Quality Assurance Program Sample Data: 2006–07

implications of 2006 07 analysis
Implications of 2006-07 Analysis
  • Neither school nor CPS verification was efficient; this was especially true for the most eligible aid applicants
  • CPS may want to consider expanding verification among records initially ineligible for Pell Grants
  • An IRS match involving only adjusted gross income and taxes paid will not replace the full “value” of the current verification worksheets
alternating focus of qa analysis
Random Sample 2006-07 & 2008-09

Representative of all potential changes in your aid population

Question of the year: Who are you missing?

School Selected 2007-08 & 2009-10

Changes your verification detected

Question of the year: Who are you verifying unnecessarily?

Alternating Focus of QA Analysis
2007 08 school verified data
2007-08: School Verified Data
  • 141 schools with ISIR data
  • 141,484 individual ISIR records
  • 134 schools supplied a description of their verification criteria
    • 124 of these had 2007-08 ISIR data
    • 119 of these had 2006-07 ISIR data
the number of verification criteria at qa program schools
The Number of Verification Criteria at QA Program Schools

Analysisof Quality Assurance Program Data: 2007–08

the relationship between the number of criteria and verification outcomes
The Relationship between the Number of Criteria and Verification Outcomes

Analysisof Quality Assurance Program Data: 2007–08 & 2006-07

top 10 data fields used in qa schools verification criteria
Top 10 Data Fields Used in QA Schools’ Verification Criteria

Analysisof Quality Assurance Program Data: 2007-08

observed relationships between school using indicated data field and verification outcomes
Observed Relationships Between School Using Indicated Data Field and Verification Outcomes

Analysisof Quality Assurance Program Data: 2007-08 & 2006-07

observed relationship between school using indicated data field and verification outcomes
Observed Relationship Between School Using Indicated Data Field and Verification Outcomes

Analysisof Quality Assurance Program Data: 2007-08 & 2006-07

common strategies for selecting students for verification
Common Strategies for Selecting Students for Verification

Analysisof Quality Assurance Program Data: 2007-08

observed relationship between school using common strategy and verification outcomes
Observed Relationship Between School Using Common Strategy and Verification Outcomes

Analysisof Quality Assurance Program Data: 2007-08 & 2006-07

less common strategies
Less Common Strategies

Analysisof Quality Assurance Program Data: 2007-08

apply 2007 08 findings to your analysis
Fields to consider using in your criteria

EFC

Student filed tax return? *

Father’s income from work *

Mother’s income from work *

Student’s income from work

Strategies to consider using in your criteria

Specific values *

Greater than

Less than *

Range

Apply 2007-08 findings to your analysis

* Associated with reduced ability to prevent Pell under-awards

implications of 2007 08 analysis
Implications of 2007-08 Analysis
  • Generalizations about Quality Assurance School verification are very hard to make
  • Roughly half of participating schools use non-ISIR information when selecting students for verification
  • School criteria often reduce “unnecessary” verification
  • The cost of this efficiency seems to paid solely by the reduced capacity to correct Pell under-awards; the tendency to prevent Pell over-awards was not affected
institutional profiles 2007 08
Institutional Profiles 2007-08
  • Pell improper payments prevented by your school’s verification efforts
  • Program-wide averages provided for context
example 2007 08 profile
Example 2007-08 Profile

Analysisof Quality Assurance Program Data: 2007–08

profiles differs from year to year
Profiles Differs from Year to Year
  • 2007-08 provide data of improper payments PREVENTED by school verification
  • 2006-07 provided data on estimated levels of POTENTIAL improper payments in a school’s applicant population
qa schools must use these verification status codes
QA Schools Must use these Verification Status Codes
  • V VERIFIED by the school.
  • S Selected by CPS but NOT verified because the ISIR record did not meet the school verification criteria
  • W Selected by the school and the Pell was disbursed without documentation.
  • BLANK Not selected
tracking your w codes
Tracking your W Codes
  • Access the Verification Tracking Report in COD
verification status report
Verification Status Report

To retrieve the report via a Data Request:

  • Log into the COD web site, select the Batch option from the top tool bar
  • Select Grant Data Requests, select New Request; from the Report Type dropdown box, select Verification Status Report
verification status report cont d
Verification Status Report-Cont’d
  • Make the appropriate selections for Award Year, Request Type and Data Type, and click the submit buttonThis process will produce a report with current data from COD. Remember, if there is no student for whom a code is missing, the file will be sent but the results will be blank.
efc impact analysis report
EFC Impact Analysis Report
  • What’s here?
    • Graph or table with counts of changes to any and the five most commonly changed critical ISIR fields by initial EFC value range
  • How can you use it?
    • Determine if changes to ISIR fields are concentrated in an initial EFC range
    • Target verification or outreach efforts
tips for applying analysis
Tips for Applying Analysis
  • KISS
    • Know
    • Integrate
    • Summarize
    • Sell
  • Telling quotations
slide68

Last night somebody broke into my apartment and replaced everything with exact duplicates …. When I pointed this out to my roommate he said, “Do I know you?”

Steven Wright

slide69
Know
  • What you do
  • What has changed
  • Remember what you don’t know
slide70

In essence, science is a perpetual search for an intelligent and integrated comprehension of the world we live in

Cornelius Bernardus Van Neil

integrate
Integrate
  • Current practices
  • Possible practices
  • Previous analysis
  • Other’s analysis
slide72

Summarize:

“I have made this [letter] longer, because I did have not had the time to make it shorter.”

Blaise Pascal

summarize
Summarize
  • For your audience
  • For you
slide74

Between two products equal in price, function and quality, the better looking will out sell the other.

Raymond Loewy

slide75
Sell
  • Data driven decisions
    • Identify how to improve
    • Recertify the status quo
  • Document the value of your efforts
    • Improper payments
    • Outreach efforts
    • Accurate aid awards
questions
Questions

Questions

contact us
Contact Us

Questions

Regional Representatives:

Regions 1, 2, 5 (CT, IN, IL, MA, ME, MI, MN, NH, NJ, NY, OH, RI, VT and WI)Holly Langer-Evans | Holly.Langer-Evans@ed.gov

Regions 3 and 4 (AL, DC, DE, FL, GA, KY, MD, MS, NC, PA, SC, TN, VA and WV)Anne Tuccillo | Anne.Tuccillo@ed.gov

Regions 6 and 7 (AR, IA, KS, LA, MO, NE, NM, OK, and TX)Anne Tuccillo | Anne.Tuccillo@ed.gov

Regions 8, 9, 10 (AK, AZ, CA, CO, HI, ID, MT, ND, NV, OR, SD, UT, WY and WA)Michael Cagle | Michael.Cagle@ed.gov

Program Director:Barbara Mroz | Barbara.Mroz@ed.gov

Program Analysts:David Rhodes | David.Rhodes@ed.govWarren Farr | Warren.Farr@ed.gov