a10.2 collecting using and evaluating_bennett, abuayyash and laplante
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Disclosure of Commercial Support CFPC Conflict of Interest
Presenter Disclosure Presenter: Bennett-AbuAyyash, Caroline and LaPlante, Nancy Relationships with commercial interests: • Grants/Research Support: None • Speakers Bureau/Honoraria: None • Consulting Fees: None • Other: None
Collecting, Using, and Evaluating Patient Demographic Data
Caroline Bennett-AbuAyyash Nancy LaPlante Prevent More to Treat Less: Public Health and Primary Health Care Together 4 June 2014
Today’s objectives
1. Enhance skills to collect personal demographic information from patients/clients
2. Learn key approaches for evaluating demographic data quality
3. Explore how patient/client demographic data can be applied toward health equity
Workshop Design: Evidence-based Approach
• Knowledge and skills in this workshop are research-based and validated through: – “Measuring Health Equity in TC LHIN Hospitals” – “Community Health Centre Socio-Demographic
Data Collection Pilot” • Both initiatives adopted 8 demographic questions:
Language Born in Canada
Race/ Ethnicity Disability
Gender Sexual
Orientation Income # ppl this income
supports
Objective: Enhance skills to collect personal demographic
information from patients/clients
Defining Health Equity
Equity in health care refers to ensuring quality care and best outcomes regardless of race, religion, language, income or any other individual characteristic
Quality care is…
Timely, Effective, Efficient, Person-centred, Safe, EQUITABLE
Demographic Data for ‘tracking health equity’
• Track and identify who we serve • Assess fit between needs and available services • Promote health equity:
– Embed as a quality indicator – Identify inequities & plan interventions – Provide patient-focused care
Data Collection Process
1. Approaching client with questions – Be mindful of barriers around language and literacy
2. Remember to refer to resources available such as: – Staff Asking Aid – Poster – Pamphlet – Laminated questions with numbered options – Glossary of term
Ready to Talk About…
• WHY: Purpose of demographic data collection
“Find out who we serve”
“Plan and deliver tailored care”
“Best outcomes for all”
• WHY: Purpose of demographic data collection • WHO: Who can see the data
– Explain who this information (or pieces of it) will be visible to
– Explain that if shared for research, it will only be done by grouping all patient information together and taking out any pieces that would identify them i.e. it can’t be traced back to a single individual
Ready to Talk About…
• WHY: Purpose of demographic data collection • WHO: Who can see the data • Options around (not) responding and (not) participating
– Voluntary – Prefer not to answer – Do not know
Ready to Talk About…
When we know who you are, we can serve your unique needs
better
This will take a few minutes. It’s
completely voluntary, so you can choose
‘prefer not to answer’ to any of questions.
Only visible to those taking care
of you while you’re here
Useful illustrations
WHY
WHO
PARTICIPATION
14
What did you see happening?
How do you evaluate the interaction with the patient?
What did the interviewer specifically say or do that encouraged the patient to answer the questions?
Illustration: Best Practices
15
Time for Practice! • Review resources • Pair up, one person plays patient then switch roles • 3 Minutes to ask all questions • Please review Practice Exercise sheet
Provide Feedback
How well is the question explained? What was done well? Can anything be improved? What advice do you have?
Objective: Explore key approaches for evaluating
demographic data quality
The First Next Step: Data Quality
• What is “quality data”? Assessment or examination of the ability to use data for its intended purpose in a given context
• Why assess data quality?
Data Information Decisions
CIHI Data Quality Framework
Usability
Comparability Accuracy
Relevance
Timeliness
Data Quality
• Coverage• Capture and Collection• Unit Non-Response• Item Non-Response• Measurement Error• Edit and Imputation• Processing and Estimation
• Data dictionary Standards• Standardization• Linkage• Equivalency• Historical Comparability
• Adaptability• Value
• Accessibility• Documentation• Interpretability
• Data Currency at the Time of Release• Documentation Currency
Data Quality Indicators
• Participation Rates – Percentage of clients who consent
• Item Response Rates – Percentage of “meaningful responses”
• Feedback: Staff & Clients
Data Quality Indicators
• Participation Rates – Percentage of patients who consent
• Item Response Rates – Percentage of “meaningful responses”
All responses, including ‘Do not know’, ‘Prefer not to answer’ and ‘Other’ can be a rich source of information.
Data Quality Indicators
• Participation Rates – Percentage of patients who consent
• Item Response Rates – Percentage of “meaningful responses”
• Qualitative Feedback: From staff & patients
Data Quality: Sources of Errors Type of error Data Quality
Dimension Affected Potential source
Data Collection Data Entry/Storage High rate of non-participation, where patient opts out of the 8 questions
Relevance Accuracy: Completeness Usability
• Client not asked the questions • Client asked but doesn’t want to
participate
Data not entered Not entered consistently and therefore not usable nor valuable for planning
Low item response rates (e.g. low response rates for Gender)
Comparability Accuracy: Completeness Relevance
• Client not asked the question; staff need to understand the importance of these questions
• Client does not understand the item
Data not entered Data not accurate and therefore not comparable over time
Answer/response fails to capture information about client
Accuracy: Coverage , Measurement Error
• The question is not clear • Translation is incorrect
Data incorrectly entered
Not all clients are included Relevance • Staff do not use data, so they do not understand its value
N/A
Information cannot be accessed for use
Usability: Accessibility Timeliness
• Information not collected at right time nor updated on a regular basis
• Information is not available to the centre for use
Data stored in inaccessible space Data not current
Strategies for improving data quality • Consistent monitoring • Engage department(s)/program(s) • Follow up training • USE THE DATA!
Wrap up: Data Quality Checklist
Have protocols for gathering data on participation rates
Have channels for receiving staff and patient feedback
Have plans for consistent monitoring
Reflective Group Exercise
Discuss with the person next to you: • What is the biggest issue that may (or currently
does) affect demographic data quality in your organization?
• What are some strategies to address it? Time: 5 minutes
Objective: Understand how patient/client demographic
data can be applied toward health equity
Demographic Data Use: Profiling Patients/Clients
0%
10%
20%
30%
40%
50%
60%
70%
Income Distribution
Caribbean 32%
Black 24%
African 15%
Latin American 11%
South Asian 6%
Hispanic 4%
Top 5 Client Ethnicities
*Source: Tharao, W. (2013, September). Beyond Reporting: Using Data to Achieve Health Equity. Presented at Measuring Health Equity: Digging into the Data Symposium in Toronto, ON.
Demographic Data Use: Profiling Patients/Clients
BLACK CARIBBEAN
Sexual Disorders
4.0%
Substance Related
Disorders19.2%
Other Problems
6.1%Childhood Disorders
3.3%
Anxiety Disorder
5.9%
Unknown15.3%
Psychotic Disorders
28.3%
Developmental
Disorders2.1%
Mood Disorders
15.9%
SOUTH ASIAN
Anxiety Disorder
9.1%
Psychotic Disorders
16.0%
Other Problems
15.7%
Unknown14.7%
Substance Related
Disorders15.1%Sexual
Disorders5.3%
Mood Disorders
24.1%
Primary Diagnosis FY 2012-2013
*Source: Agic, B. (2013, September). Equity-Driven Service Planning and Delivery. Presented at Measuring Health Equity: Digging into the Data Symposium in Toronto, ON.
Community Health Centres Equity data Example…
Community Health Centres Equity data Example…
Beyond Reporting: Using Demographic Data to Make Linkages
Health Equity
- Cancer screening - Pre-natal programs - Diabetes management
- ED visits - Birth weight - Cancer survival - Re-admission rate - Drug dosage
- Referrals - Adherence to protocols
Access to Services
Health Outcomes
Healthcare Delivery
Using Demographic Data for Awareness and Education
Reflective Group Exercise
Discuss with the person next to you: • What can demographic data use look like in your
organization? • What would you expect to find? Time: 5 minutes
Wrap-up: Looking at the Big Picture
Health Equity
Planning Collecting
Data
Identifying Inequities Reporting
Additional Resources: • Mount Sinai Hospital & TC LHIN
website on demographic data collection www.torontohealthequity.ca
• HRET Disparities Toolkit http://www.hretdisparities.org/
• Robert Wood Johnson
Foundation http://www.rwjf.org/
THANK YOU!
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