CalFresh Data Dashboard: What does it say?

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1 CalFresh Data Dashboard: What does it say? This document will review the CalFresh Data Dashboard and provide guidelines on how to work with the data. This document should help you to: 1) Identify and interpret the data. 2) Put the data in context (compared to other counties and statewide averages.) 3) Identify policies and practices that may impact that data. Getting Started How to make the spreadsheet work The CalFresh Program County Data Dashboard can be found at-- Click on the link that says Data Dashboard, to download the Excel spreadsheet. Open the spreadsheet and at the top, click on the link that says Enable Editing. Next, click in the blue bar that says Click to Select County/Statewide from menu. You will see a small grey arrow appear at the end of the blue box. Click the arrow, scroll down and select your County. Repeat this process in the second blue bar and select the county which you would like to use for comparison. For best results, select a county with similar demographics to your County. To select the state of California, select Statewide at the top of the drop down bar. Understanding your County Establishing a comparison baseline What is the complexion of our County as compared to another County? --Three starting data points for the purposes of comparison are found under County/State Demographics. Find Total Populations and then the total population as broken out by Elderly and Children. Are the numbers for both counties reasonably similar in size, if not, you may want to select an alternate county for the sake of comparison. In our example, comparing Sacramento and Alameda, these numbers are reasonably similar for both counties. What has been the trend in participation in the CalFresh Program? It is important to note here that the data provided on the spreadsheet for the data points CalFresh Persons is a snapshot of those in the program at a given point in time. The quarterly numbers are a snapshot of the last month of the quarter and the annual numbers are a snapshot of the month of July.

2 --To determine the quarterly trends, under CalFresh Caseload (note that this category is at the top of the sheet) use the data fields CalFresh Households and CalFresh Persons Have the numbers increased or decreased from the Jul/Sept 2012 to the Oct/Dec 2012 timeframes (keep in mind that this data point if for the last month in each quarter). In our example for Sacramento, it has increased. --To determine how things have changed since the same time last year, compare Oct/Dec 2012 to Oct/Dec 2011 (keep in mind that this data point is a snapshot of the month of July). In our Sacramento example, this number has also increased quite a bit, a 7.1% increase in Households and a 5.4% increase in Persons. So we have established that there has been an increase in program participation from one quarter to the next and for the same period in the previous year. (It is important to keep in mind when considering these data points, that since they are for single months, there could be some variance due to monthly fluctuations in the numbers) Why has there been an increase or decrease in program participation? --One reason could be a change in the general population. Are there more people in the County, have the demographics shifted towards an older population or an increase in children? Could the change in the population be a factor in the participation levels over time? Was a new program implemented that could have been a contributing factor? Go to the County/State Demographics section of the spreadsheet. --Look at the % change in population from In our example, we see that while the total population in Sacramento has only changed by 1%, and while the number of children in the County stayed relatively flat, the elderly population has increased by 4%. Could the aging population in the county be a contributing factor to the increase in participation? --Could unemployment be a factor in participation levels? --In the Sacramento example, unemployment rates for the timeframe decreased. Decreased unemployment would suggest that employment was not a factor in the increase in Program participation. --Could language be a factor? Look at Language other than English Spoken at Home. For Sacramento, we see that the number of people who fall into this category has been increasing over the past two years. --Were there new programs that might have increased outreach and therefore participation, could that be a factor? --Are more people eligible for the program than in previous time frames? Let us investigate this further. What percentage of the estimated eligible population is participating in the Program? It is important to note here that the data provided on the spreadsheet for the data points CalFresh Persons is a snapshot of those in the program at a given point in time. The quarterly numbers are a snapshot of the last month of the quarter and the annual numbers are a snapshot of the month of July. --Find the data points under Potential CalFresh Eligibles Adjusted CalFresh Eligibles. In our Sacramento example, those eligible for the program have increased each year. --In 2012, it was estimated that 281,327 Persons were eligible. --Look under CalFresh Caseload Demographics under Persons and see that in 2012 (this is a snapshot of the July numbers), there were 204,104 Persons in the program, or a participation level of 72.5% To determine if participation amongst eligible individuals is increasing or decreasing, review the same two data points for the previous year, 2011.

3 In 2011, it was estimated that 253,216 people were eligible. --In 2011, there were 195,423 Person participants. This suggests approximately a 77.1% participation level amongst those who were eligible for the Program. What we have discovered, is that year over year, amongst the entire eligible population, participation rates have dropped. So what we have been able to determine by the previous exercises --the pool of eligible participants has increased from 2011 to that while participation in the program increased over the last two quarters in 2012, a smaller percentage of those eligible participated in 2012 vs there has been a population shift in the County towards a higher number of elderly --there has been an increase in the number of people who speak a language other than English at home --unemployment does not appear to be a factor in the quarterly change Next steps --Given the data points above, consider the following --it s likely that participation increased because there were more eligible Persons, however, could there have been other factors such as new programs that were put into place that could have had an impact? --with the increase in the elderly population, should outreach efforts be increased in that area? --with a trend towards more people who speak a language other than English, should additional multilingual outreach be conducted? --as a percentage of those eligible, fewer people are in the program, why do you think that might be? What could be changed to increase the percent of those participating to the 2011 level? How are we similar or different to other like counties and the State as a whole? Comparing basic demographics between two counties As an example, we will compare Sacramento and Alameda. In this example, we see that the Total Population and Percent of State are reasonably similar in size for the purposes of comparison. --We need to do a little outside work to compare the complexion of each population. When we do, we see that in 2012, the elderly made up roughly 16% of the overall population in Sacramento and in Alameda, it is roughly the same, about 16%. --In Sacramento, in 2012 we see there is a slightly higher population of children 25% of the overall population, while in Alameda, children make up 22% of the overall population. --When we look at Language Other than English Spoken at Home, we see that while in Sacramento the total number of those who speak a language other than English at home is less than Alameda overall, in Sacramento the number of those who speak another language at home has been increasing each year, while in Alameda, that number has been dropping. --In comparing unemployment rates, we see that while unemployment has been decreasing each year in both counties, Sacramento has a higher unemployed rate of 10.6% to Alameda s 9% --So we have established that Sacramento has a higher population of children, is experiencing an increase in those who speak a language other than English at home and has a higher level of unemployment than Alameda.

4 Comparing Overall Participation Levels It is important to note here that the data provided on the spreadsheet for the data points CalFresh Persons is a snapshot of those in the program at a given point in time. The quarterly numbers are a snapshot of the last month of the quarter and the annual numbers are a snapshot of the month of July. --When we look at CalFresh Persons participation levels for specific timeframes, we see that there was a slight increase in participation for the July/Sept 2012 to the Oct/Dec 2012 period in Sacramento as compared to Alameda. Sacramento had a person participation increase of 1.4, while Alameda had a 1% increase in the same time frame. (Bear in mind that these rates reflect Participation in a single month and there could be some variance due to the natural fluctuation in the numbers from one month to the next.) --Comparing on a quarter over quarter basis, we see that when we compare Oct/Dec 2012 to the same period in the previous year, Oct/Dec 2011, (this is a snapshot of the month of December) that Sacramento had a Persons participation increase of 5.4% while Alameda had a Persons participation increase of 3.7% --Let s look at the next data point for comparing participation, what percentage of those eligible participated in the program. We already know that in Sacramento in 2011, 77.1% of the eligible population was participating in the program and in % of those eligible participated (Based upon a snapshot of the month of July). When we look at the same data points for Alameda, we see that of those eligible 75.65% participated in 2011 and 81.5% in There was a substantial year over year increase in Alameda. Perhaps the reason we didn t see as large an increase in participation in the second half of 2012 for Alameda as Sacramento is because Alameda is already serving a larger portion of the population, or, could there be other reasons? Now it s time to hypothesize on why the difference in participation levels between the counties. --Why is there a higher participation among the eligible in Alameda than Sacramento? Do they have more staffing, different outreach programs, easier access? What might account for the difference? --We ve calculated that there are more children in Sacramento, could that be a factor? --What other factors could be in play here? --Are the participation rates in Alameda an anomaly? Let s investigate by looking at State averages. How does my County compare to the State? --When we look at the participation rates of those eligible for the State, we see that in California there are 5,772,912 eligible persons and 4,074,650 participating in 2012, a participation rate of approximately 70.5%. In 2011, there was a State participation rate of 68.5%. So, while Sacramento s eligible participation is higher than the State average, the State average did increase from 2011 to 2012, while Sacramento s participation level decreased in that timeframe. At this point, you may want to look at three or four additional peer counties. How do you compare? Are your participation rates quarterly, annually and as a percentage of those eligible roughly the same as other similar sized counties, much better, or not quite as high?

5 Investigating other contributing factors to participation rates Let us look at data points related to the initial application process. The next data point that we are going to examine is Timeliness. Under the CalFresh Caseload locate Timeliness 30 days. When we look at Sacramento, we see that the percentage of cases meeting the 30 day requirement increased slightly from Jul/Sept 2012 to Oct/Dec 2012 from 98% to 98.8%. There has also been an increase in Timeliness quarter over quarter with the Oct/Dec 2011 rate being 96.1 and the same quarter in 2012 as 98.8%. How does this compare to our peer county Alameda and Statewide? Jul/Sept 2012 Oct/Dec Sacramento 98% 98.5% --Alameda 90.9% 91.5% --California 97.8% 97.5% Oct/Dec 2011 Oct/Dec Sacramento 96.1% 98.8% --Alameda 90.1% 91.5% --California 96.7% 97.5% Both counties have seen slight increases in Timeliness in both time frames, however, Sacramento is out performing its peer county and the State in Timeliness. This is a good opportunity to consider what Sacramento may be doing that has resulted in such a high Timeliness rate. Are there programs that could be adopted by other counties? What activities or actions might account for the Timeliness rate and how might those activities be rolled out to other regions? How do the counties compare on Timeliness-Expedited which can be found at the top of the sheet under CalFresh Caseload Jul/Sept 2012 Oct/Dec Sacramento 98.5% 97.4% --Alameda 87.7% 85.5% --California 94.2% 93.9% Oct/Dec 2011 Oct/Dec Sacramento 86.6% 97.4% --Alameda 87.1% 85.5% --California 92.3% 93.9% While there was a slight drop in Sacramento s Timeliness--Expedited in the last two quarters of 2012, we see that overall Sacramento is still outperforming on Timeliness--Expedited as compared to its peer county and the State. We also see that Sacramento had a significant increase in Timeliness--Expedited from 2011 to What could account for this change? What happened or changed in 2012 that could have contributed to such a significant up tick? Could that activity, program, change, be adopted by other counties.

6 What have we been able to determine by the previous exercises? When we compare Sacramento to its peer county Alameda, Timeliness does not appear to be the factor that is causing the lower participation rate in Sacramento. As we ve seen, Sacramento is out performing Alameda on Timeliness. Again, this is a good place to consider if this is an anomaly or a trend by comparing Sacramento s Timeliness to a few additional peer counties. The final data point that we are going to consider related to the initial application process is the Active Error Rate. Locate this data point towards the top of the sheet. Jul/Sept 2012 Oct/Dec Sacramento 2.5% 0.4% --Alameda 1.6% 4.6% --California 3.6% 3.2% Oct/Dec 2011 Oct/Dec Sacramento 5.3% 0.4% --Alameda 1.4% 4.6% --California 3.7% 3.2% Again, we see that Sacramento is outperforming its peer and the State. We also see that Alameda has had a somewhat significant increase in the Active Error Rate particularly in the Jul to Dec 2012 timeframe. What could have caused such a significant change? Has it been resolved? What could be done to improve the Error Rate? What are other counties doing? What have we been able to determine by the previous exercises We have learned that Sacramento is performing very well during the initial application process with above average Timeliness and a very low Error Rate. While this provides an excellent opportunity for other counties to investigate Sacramento s programs as related to the application process, it does not explain why Sacramento s participation levels are lower than those of its peer Alameda. Considering the Churn factor Towards the top of the sheet, locate Total Churn and Recertification Churn. When we look at 30 day Reapplication Churn and 90 Day Reapplication Churn for Sacramento and Alameda, we see that the percentages are comparable and that the trend for both counties for the July/Sept 2012 quarter to the Oct/Dec 2012 is a slight increase. We also see that this trend holds true when we compare Sacramento to the State. Again, this is a good place to ask Why? Why did churn rates increase at the end of 2012? What changed? When we compare on a year over year basis, we see a downward trend in churn for both counties with comparable percentages. When we look at the State, we see similar downward trends. So, Sacramento is more or less in alignment with its peer and the State as a whole. If we saw significant difference in trends, for example, Sacramento s churn rate was up as compared to its peer or the State s rate which was down, it would warrant further investigation and discussion. Likewise, if we discovered the trends were the same, both with an uptick, but the percentage of the uptick was significantly different from one county to the next, than this too might warrant further investigation.

7 Let us go through the same process for Recertification Churn. When we look at 30 day Scheduled Recertifications and 90 day Scheduled Recertifications for the last two quarters of 2012, we see that again the numbers are reasonably comparable and the trends are the same, flat or a slight uptick in churn for both counties. As compared to the State, we see that the State trend for the same time period is going down. Why? Have other counties put in more aggressive programs so that there are fewer Recertifications? Is it just that the State had a much higher overall Recertification level than our two counties, so they had more opportunity to reduce Recertification churn. This would be another good place to compare Sacramento to a few other peer counties to see how the numbers compare. Are other peer counties like Sacramento with similar numbers of Recertifications and trends, or, are they more like the State. Where does Sacramento really stand in the broader picture? Finally, lets us look at Recertification Churn from one year to the next. Here we see that the two counties diverge, Sacramento has a downtick in both 30 and 90 day Recertifications while Alameda has an uptick? Let s look at which trend most closely mimics the State. When we examine the same data point for the State, we see that California was more like Alameda with an uptick in both 30 and 90 day Recertifications. Why is it different in Sacramento? This is an area worth exploring and determining if certain efforts in Sacramento can be duplicated elsewhere to lower Recertification churn. In Closing By completing the above analysis, you have been able to learn more about how your county performs against other counties and the State, as well as how to understand and interpret disparate data points. We have seen that Sacramento has a lower participation level against its peer, but that it excels in Timeliness and Churn as compared to its selected peer county and the State. What other factors could be contributing to Sacramento s lower participation rates? Could it be related to the increase in their elderly population and/or a larger population of children overall both groups which may be challenged with the application process? Could it be due to the increase in those who speak a language other than English at home perhaps also challenged by the application process? What hypotheses can you form? Are there other data points you could consider that could support your hypothesis? If you expand Sacramento s peer group and compare it to 3 or 4 other like counties, do you find that the trends stay the same. Where do they differ? As you have seen, while there is a certain science to data collection and presentation, interpretation of data can be a bit of an art. The key is to compare your county against your peers and question the differences. As a consumer of the data, form hypotheses on why the differences may exist and test those hypotheses. Discuss the variances with your peer counties to uncover what underlying factors may be contributing to the differences. Using the data to identify differences will provide you numerous opportunities to have a dialogue with peer counties!