Recommendations amp Observations Part One Todays Presenters Steve Eastwood 211 Arizona Community Information and Referral Services Phoenix Arizona Dave Erlandson United Way 211Ceridian Minneapolis Minnesota ID: 749962
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Slide1
Resource Database Assembly: Resource Database Quality Recommendations & Observations
Part OneSlide2
Today’s Presenters
Steve Eastwood
2-1-1 Arizona, Community Information and Referral Services, Phoenix, Arizona
Dave
Erlandson
United Way 211/Ceridian, Minneapolis, Minnesota
Polly McDaniel
Institute for Human Services, 2-1-1 HELPLINE, Bath, New YorkSlide3
How We Got Here2013 AIRS Conference sessions in
Portland
Common thread emerged in discussions about best practices, potential metrics, staffing models, etc.
Opened the group to volunteers via the AIRS Networker Open Forum in June, 2013
Put together a new survey for resource work (last one was in 2008)Slide4
How We Got Here
2014
AIRS Conference sessions in
Atlanta
Discussions
of the group this
past year
+ Feedback
today (Atlanta conference)
=
Recommendations for
Staffing
Metrics
Database update percentage requirements
Published white paper supported by AIRS
Compilation of the field’s recommendations and resulting Database Quality MeasuresSlide5
Objectives
Database Quality
Metrics
Staff Performance Metrics
Program MetricsSlide6
Database Quality Metrics
Accuracy
Completeness
Consistency
TimelinessSlide7
Database Quality MetricsAccuracy
According to the Basic Principles of I&R (also known as the I&R Bill of Rights) and AIRS Standard 10, an I&R service maintains accurate information. Accuracy is measured by reviewing the original request submitted against the entry into the resource database.
We recommend that resource staff maintain a 95% accuracy rating for the entries they have updated. A resource department should have in place a procedure to measure this metric at least annually.Slide8
Database Quality MetricsCompleteness
AIRS Standard 8 identifies the data elements that are required and recommended for each organizational record within a resource database. Completeness is measured by the level of completeness for every required field in the database for each record updated annually (and for which data exists).
We recommend that resource staff maintain a 95% completeness rating for the entries they have updated. A resource department should have in place a procedure to measure this metric at least annually
.Slide9
Database Quality MetricsConsistency
Create a database style guide and apply it
consistently
Develop standard description narratives such
as
“Provides food boxes for individuals and families in need.”
“Offers one-time electric bill payment assistance.”
Review and/or audit records for consistency of style and
indexing
Set standards for measuring
consistencySlide10
Database Quality MetricsTimeliness
Set standards for entering changes or new information within a certain time
frame
Average time allowed for adding new info should be at least twice the average time allowed for updating an existing record to allow for research and data entry
process
Review timeliness through
documentation
We recommend maintaining a 95% timeliness
ratingSlide11
Database Quality MetricsComments
What have you done?
What is working, what isn’t?
Other questions?Slide12
Staff Performance Metrics
Records per FTE
Time to Reply
Time to Enter UpdatesSlide13
Staff Performance MetricsRecords Per FTE
This metric supports AIRS Standard 12
The number that was often cited was 650 – 800; however this was unsatisfactory since it was seemingly taken from thin air
Last year the number suggested was 500, which was based off of a limited set of complexity data
Realistic but challenging expectations are
key
Keep in mind outside factors: time off, those pesky updates that just go beyond any reasonable time expectation, skill of staff,
etc
CRS Task AnalysisSlide14
Staff Performance MetricsRecords Per FTE
Complexity plays an important role for this particular metric; however aspects of complexity may need some work (we’ll talk about that in session 2)
Those issues aside we may be nearing a point where we can measure this, with complexity taken into account, and come up with a national average
We’ll need to gather some data
Average database records (total)
Average database complexity (per complexity category)
Average time to complete an annual update (per category)Slide15
Staff Performance MetricsTime to Reply
Set standards for staff to acknowledge requests for database updates or
additions
This includes responding to providers, the general public, I&R staff,
etc…
Should meet standard at least 90% of the
timeSlide16
Staff Performance MetricsTime to Enter Updates
Set standards for how quickly updates and new information should be entered once
received
Should meet standard at least 90% of the
timeSlide17
Staff Performance MetricsComments
What have you done?
What is working, what isn’t?
Other questions?Slide18
Putting Metrics to Work
Polly –
Data Quality Procedure, Includes establishing quarterly monitoring
Performance Development Review Policy
Dave –
Created
a scoring sheet for monthly reviewsSlide19
Putting Metrics to WorkComments
What have you done?
What is working, what isn’t?
Other questions?Slide20
Hope to see you back for the second sessionSlide21
Resource Database Assembly: Resource Database Quality Recommendations & Observations
Part TwoSlide22
Today’s Presenters
Steve Eastwood
2-1-1 Arizona, Community Information and Referral Services, Phoenix, Arizona
Dave
Erlandson
United Way 211/Ceridian, Minneapolis, Minnesota
Polly McDaniel
Institute for Human Services, 2-1-1 HELPLINE, Bath, New YorkSlide23
Objectives
Program Metrics
Policies and Procedures
Inclusion/Exclusion Issues
Defining a Record
Nature of a Resource Database
Resource Department Customer Service Survey
Annual Completion Rate
Record Complexity Slide24
Program MetricsPolicies and Procedures
Taxonomy
Usage Policy (AIRS Standard 9, Quality Indicator 2; AIRS Standard 10, Quality Indicator 11)
The Taxonomy Usage Policy should also discuss Target Term usage or a separate Target Usage Policy should exist (AIRS Standard 10, Quality Indicator 11)
Database Maintenance Procedure (AIRS Standard 10 and 12)
Style Guide/Format Policy (AIRS Standard 10, Quality Indicator 4)
Inclusion/Exclusion
Policy (AIRS Standard 7)Slide25
Program MetricsInclusion/Exclusion Issues
Standard 7, but goes beyond
Sets the amount of maintenance work that an I&R must accomplish year to
year
What should go into a review?
Come to the Inclusion/Exclusion presentation “The Most Important Document You’ll Create” if the following gets you
excited
Inclusion/Exclusion
Brief literature reviews
A discussion on the nature of information in an I&R setting
Solid practices to implement in your next policy
reviewSlide26
Program MetricsDefining a Record
All the data elements that define an organization and its services, programs, and location at which the services are
deliveredSlide27Slide28
Program MetricsNature of a Resource Database
Are there complex records in the D-List?
If so, can they be re-organized into a simpler structure?
Do the A-List receive priority for establishing personal relationships with their agency contacts? Slide29
Program MetricsAnnual Update Completion Rate
100% annual completion is our Holy
Grail
85-95% annual completion is more realistic due
to
Staffing (and funding) issues
Overlap of updates
cycles
Level of provider cooperationSlide30
Program MetricsResource Department Customer Satisfaction Survey
How satisfied are you with
Anytown
I&R’s listing of your organization’s information? (Excellent – Good – Fair – Poor)
If you chose Poor or Fair, what would you like to change about the way your information is listed?
How satisfied are you with the update process?
Are you aware of our online database?
Do either you or your staff use it? (Yes occasionally – Yes often – No)
How would you rate your experience using the online database?
If you have called (our database department), how would you rate the service you received? Slide31
Program MetricsResource Department Customer Satisfaction Survey
We recommend that those agencies that completed an update within the past year be requested to complete an annual update customer service survey. A satisfaction rating of at least 90% should be
achievedSlide32
Program MetricsDatabase Record Complexity
Sue
Boes
presented on Record Complexity last year
Not all records are created
equal
There’s
a big difference between a one-service agency and a ten-service agency; the I&R world needed a better way of recognizing this
difference
The complexity formula itself is a very solid way of measuring the difference between small, medium, large, and very large records in your database, but it may need some tweaks to work well for
youSlide33
Program MetricsRecord Complexity: Basic Method
Assign points to database elements
Consider what (agency/site/service) records hold the most critical elements and what elements are a breeze
Service
vs
Service Groups? Questions of consistency
Develop a scale
Scale offered can handle everything from 1 to >41
Should the scale be modified to handle “Very Complex” records >81 points?
Determine average work hours
This is the toughest component to narrow down
Gatto
& Kelly note a time tracking sheet is essentialSlide34
Program MetricsA bit more on tracking time
Track in a similar way that lawyers would track billable hours: when you’re actively working on a record
Time is listed in tenths of an hour (6 minute increments)
Be liberal when rounding up (if a task took you 14 minutes, mark it as .3)
Create a good sample size to base your average off of (this is no small task)Slide35
Program Metrics
Basic Method 2: Electric
Boogaloo
Consider Variables:
These are some of the things we considered above, but there are also some intangibles that we need to think about as well(staff skill, agency cooperation/rapport with your I&R, local standards, AIRS best practices, etc.)
Create formula
More of implementation if everything else above is in play
Total the weighted score for each record, multiply by average time
Review possible outcomes:
Keep in mind (among other things,) an increase in weight will tip your scaleSlide36
Program MetricsOutcome Top Tips: Management Tools
Equitable work assignments amongst resource staff
With current time projections 1950 (one year FTE) hours of work can be 65 complex agencies or 780 simple agencies
Jumping back to part one for a moment, this is why it’s difficult to say Records per FTE
Time and cost projections for new initiatives
If United Way would like you to add a service to each of your school districts as a new initiative to support its education impact area, you might use complexity to see if records will be bumped to the next tier of complexity
Keep in mind, this wouldn’t necessarily be a one time cost; maintenance is recurring!Slide37
Program MetricsOutcome Top Tips: Individual Tools
Equitable work amongst your personal update cycle
162.5 (one month FTE) hours of work can be ~6 complex agencies or 65 simple agencies
So balancing out each complexity tier as a percentage each month may help keep a monthly workload relatively even
Use this as a tool to help guide update decisions
Are these three services better as one service group or should they be split up?
Are there agencies with repeated services? Agencies with coalition agreements is a big issueSlide38
Program MetricsHome Brewed Complexity
Many I&R software packages actually implemented a complexity score
Many others did not; so implementing a complexity program can be difficultSlide39
Putting Metrics to Work
Polly –
Allowed my executive director to better see the capacity and time of the work involved in resource work
Switched to dedicated resource time vs contact center responsibilities rather than merging it all together…and “getting the resource work done in between calls”
Steve –
Complexity scoring showed us that some records were over-complicated. We scaled some back to help simplify database maintenance
Standards also gave us a way to measure the effectiveness of training methods and our new trainee and gave ideas for goals for resource staff annual reviews
Dave –
Working on redistribution of work load amongst resource specialists and simplifying more complex records
Cross trained call staff to help
While using complexity has made an impact, feel scoring needs to be adjustedSlide40
Putting Metrics to WorkAction Items
Do we, collectively need to refine any of these metrics?
Is there more
work to be done
Complexity Score – refine variables, time?
FTE’s?
Other issues?Slide41
THANK YOU!!
Steve Eastwood, seastwood@cir.org
Dave
Erlandson
, david.erlandson@Ceridian.com
Polly
McDaniel, mcdanielp@ihsnet.org