Analytics Teams
- Shelter Length of Stay and Where People Go (Team 1)
Is there a difference in clients leaving shelter for stable housing on own based on the following lengths of stay: 13 days and under; 14-21 days, 22 days or longer? Complete for CWES, YWCA, and combined data. Can Kuhn and Culhane’s (1998) shelter use patterns of “transitional” and “episodic” be replicated in each shelter’s data (not combined)?
B.Optimal Outcome.What are the intake characteristics of clients who leave with the optimal outcome? Is there a difference in services received and referrals completed for optimal vs. other discharges? The answers to these questions will hopefully inform additional supports, capacities or staff training we can complete to better support optimal outcomes for all clients accessing the shelter. Complete for CWES, YWCA, and combined data.
- Client Characteristics; Length of Stay and Optimal Outcome (Team 2)
B.The length of stay is longer at the YWCA than at the CWES Shelter. How much of the difference in length of stay is accounted for by the intake factors (ie. differences in client need).
- Helpline (Team 3)
B. Helpline Services. Are there different services and referrals provided based on the following groupings of the helpline data:
- Inside Calgary vs. outside Calgary. – Shelter intake
- Male vs. female callers
- Impact of Economic Downturn & Fundraising (Team 4)
B.Fundraising Data analytics – Describe the giving characteristics by type of donor. Do patterns emerge (clusters) of gifts? Givers?
- Natural Language Processing Team:
Natural Language Processing of outcome survey data:
- What changes did you make as a result of this program?
- What did you like about the program?
- What would you improve about this program?
- Geographic Visualization Team:
B. Donor mapping – visualization of geographic location associated with each donor by type of donor, type of donation, donations over time, and total donations.
Data for Good – Calgary Women’s Emergency Shelter Datathon
Analytics Teams 1
- Shelter Length of Stay and Where People Go (Team 1)
A. Length of Stay
What factors are correlated to a client staying shorter/longer than 21 days? Are outcomes better1 for clients staying longer than 21 days? Is there a difference in clients leaving shelter for stable housing on own based on the following lengths of stay: 13 days and under; 14-21 days, 22 days or longer? Complete for CWES, YWCA, and combined data.
For each shelter dataset (CWES and YWCA) a unique ID is assigned to each individual, subsequent entries into shelter are recorded using the same unique ID. Kuhn and Culhane (1998) applied cluster analysis to create a typology of homelessness, including transitionally, episodically, and chronically homeless (see data dictionary for definitions) for homeless shelter users. We know there are no “chronic” users of individual shelters, however, can shelter use patterns of transitional and episodic be replicated in the individual shelter data?
Note: Kuhn and Culhane’s work as well as the work of the Calgary Homeless Foundation was analysis completed on an entire system of care comprising multiple shelters with a unique identifier used to track individuals across multiple shelters. In comparison, the current analysis will be limited to individual shelter access and will underestimate the population who would have longer and more frequent stays, ie. episodic and chronic shelter users.
B. Optimal outcome[1]
What are the intake characteristics of clients who leave with the optimal outcome? Is there a difference in services received and referrals completed for optimal vs. other discharges? The answers to these questions will hopefully inform additional supports, capacities or staff training we can complete to better support optimal outcomes for all clients accessing the shelter. Complete for CWES, YWCA, and combined data.
Alberta Women Shelters Dataset OverviewIntake Factors/ Characteristics
-Education
-Employment
-Income Sources (type and number)
-Marital status
-Citizenship
-Cultural Background
-English preferred language
-Length of time in Canada
-Type of Housing
-Living Arrangement prior to shelter entry
-Region/ province of residence
-Pregnancy/ # dependent children
-Abuser Security Concerns / Charges
-Police Service prior to intake
-Physical injury
-Abused By
-Physical Health/ Addiction / Mental Health (individually and co-morbid)– compared to average length of stay / Discharge Report Factors*(expected to be more closely related to date than other characteristics - ?)
-Type of Services Provided
-Referrals Provided
Outcome Factors
-Reason Client left program & Detail
-Living arrangements after discharge
-Type of housing after discharge & Detail
Resources: “Global Shelter Data Count” - located in “FVandA and CWES Stats” folder; 2015/16 ACWS Annual Report; “Agency Dataset by program”
- Client Characteristics; Length of Stay and Optimal Outcome (Team 2)
Purpose: One of the goals of the CWES Strategic Plan is to “Develop responsive programs and support services aimed at preventing and ending family violence and abuse with diverse and marginalized populations.” Does our data provide an indication of where to start this goal?
A.Does citizenship status; cultural background; length of time in Canada; or region/ province prior to intake impact services recorded, length of stay, and optimal outcome*? If there are differences, are they explained by other intake factors?
If time allows, complete for other demographic factors.
B. The length of stay is longer at the YWCA than at the CWES Shelter. How much of the difference in length of stay is accounted for by the intake factors (ie. differences in client need).
Resources: 2014-15 CWES Outcomes presentation (Shelter Program); 2015/16 CWES Outcomes Spreadsheet (Shelter Program) - both located in “FVandA and CWES Stats” folder
- Helpline
A. When are we busy?
Is there a busy time of the year? Time of the day?Time of the week? What patterns emerge from the helpline call data, are there specific patterns for different types of calls?
Resource: “CWES Helpline Calls Analysis – April 2016”; “CWES Helpline Calls Analysis”;
B. Helpline Services
Are there different services and referrals provided based on the following groupings of the helpline data:
- Inside Calgary vs. outside Calgary. – Shelter intake
- Male vs. female callers
- Professional vs. victim vs. informal supporter
- Impact of Economic Downturn & Fundraising (Team 4)
A. What is / was the impact of the economic downturn on demand for CWES Services, Response (services provided), and support for CWES (donations)?
B. Fundraising Data analytics – Describe the giving characteristics by type of donor. Do patterns emerge (clusters) of gifts? Givers?
Resources: “CWES – Call Volume, Type of Violence, and Danger Assessment”; “CWES Helpline Calls Analysis – April 2016” “Emergency Shelter – Analysis of Housing Referrals and Outcomes Oct 27, 2016”; “Shelter and the Economy Oct 27, 2016”; “CPS – DV Stats Projections”; and “Sample DPA Report” for metrics
- Natural Language Processing Team:
For All Clinical Programs
Natural Language Processing of outcome survey(Anonymous data in SPSS) data:
- What changes did you make as a result of this program?
- What did you like about the program?
- What would you improve about this program?
Resources: Qualitative Analysis summaries for Healthy Relationships and Shelter
- Geographic Visualization Team:
A. Domestic Violence and Client Mapping – Where is domestic violence reported to the police (Homefront Data). Where does CWES record high lethality (Danger Assessment[2] Data)? How do the two maps compare? Where are the gaps? Where do CWES clients report having lived prior to entering services? Is there a difference between Community Services Clients; All Shelter Clients; CWES Shelter Clients; and YWCA Shelter Clients?
B. Donor mapping – visualization of type of donation, donations over time, total donations.
Resources: “Danger Assessment Full Report” Executive Summary for historic information; City of Calgary Community Profile Data
Key Terms and Definitions
CWES / Calgary Women’s Emergency ShelterYWCA / Young Women’s Christian Association
Sheriff King / Domestic Violence Shelter, program of YWCA
Emergency Shelter / Can refer to a Homeless Shelter or Domestic Violence Women’s Shelter. The Domestic Violence Shelter has a targeted length of stay of 21 days.
Second Stage Shelter / Available to women leaving a Domestic Violence Emergency Shelter. Can stay between six months to one year.
Brenda Stratford / Second Stage Shelter
Discovery House / Second Stage Shelter; also organization offering several domestic violence programs
Sonshine / Second Stage Shelter
Professional - Helpline / CWES Employee
Child and Family Services Authority
Community resource centre
Counselling agency
Emergency DV Shelter
Financial assistance
Housing Services
Immigrant serving agency
Lawyer/Legal Aid
Medical/Health
Police/RCMP
Second stage DV Shelter
Victim – Helpline / Self
Current CWES client
Informal Supporter - Helpline / Community member
Friend or family
ACWS / Alberta Council of Women’s Shelters – provincial advocacy group representing members of Alberta’s women’s shelters.
Danger Assessment / The Danger Assessment tool was originally developed in 1985 to empower women at risk with information that reduced the likelihood of further exposure to her risk of femicide. It consists of a Calendar to assist in recall and 20 weighted questions designed to measure risk in an abusive relationship.” (Cairns and Hoffart, 2009, p. 1). Sample of the tool is provided in the report.
Better/ Optimal Outcome / Better Outcome/ Optimal Outcome is defined as client chooses to leave and completed program; living in stable housing; and living on own or with friends and family, second stage. This definition was created for data analysis. Based on previous research (Cairns and Hoffart, 2009), this is the preferred outcome for between 86% and 90% of shelter clients. The optimal outcome is individual and defined by each client. The data collected in this dataset does not account for preferred client outcome.
CHF / Calgary Homeless Foundation
CAEH / Canadian Alliance to End Homelessness
Transitionally Homeless / “The transitionally homeless population consists of those who generallyenter the shelter system for only one stay and for a short period...They are forced to spend a short time in a homeless shelter before making a transition into a more stable housing arrangement, and in most cases they do not return to homelessness. Over time, persons in this cluster are expected to account for the majority of persons experiencing homelessness, given their higher rate of turnover (Burt, 1994; Culhane et al., 1994; Culhane & Kuhn, in press). Such a client's shelter utilization profile would be characterized by one or very few homelessness episodes of less than a few weeks or months total.” (Kuhn and Culhane, 1998, pp. 210-211)
For transitionally homeless, a Calgary Homeless Foundation presentation reported the average number of stays at 1.88 and the total number of days as 38.84.
Episodically Homeless / “The episodically homeless population comprise those who frequently shuttle in and out of homelessness… These clients are likely to account for relatively fewer of the homeless over time than their transitionally homeless counterparts (Culhane & Kuhn, in review). Their homeless shelter utilization profile would consist of many episodes of shelter usage (even using a criterion of shelter exit of 30 days out of the system) with varying lengths of stay each time, but they are unlikely to accumulate more than a few months total of shelter use” (Kuhn and Culhane, 1998, p. 211)
For episodically homeless, a Calgary Homeless Foundation presentation reported the average number of stays as 10.27 and the total number of days as 253.22.
Chronically Homeless / “These are people who are likely to be entrenched in the shelter system, and for whom shelters are more like long-term housing than an emergency arrangement…Their stay profile would be characterized by fewer episodes of homeless shelter use than the episodicgroup, but each episode is likely to last much longer, and, in some cases, may last many years” (Kuhn and Culhane, 1998, pp. 211-212).
We do not expect to observe any clients meeting these characteristics.
For Chronically homeless, a Calgary Homeless Foundation presentation reported the average number of stays as 4.2 and the total number of days as 1548.76.
[1] Better/Optimal Outcome Defined in data dictionary below.
[2]“The Danger Assessment is defined in the Data Dictionary below.