1. Standardizing Patient Race, Ethnicity and Language Data Collection: Key Decision Points October 1, 2010 Memphis, TN Aligning Forces for Quality National Program Office

2. 2 Standardizing R/E/L data collection: Key decision points  What is standardized data collection?  Where are data collected?  Who needs to be engaged?  What IT system modifications need to be made?  How will registration processes change?  How will changes be communicated to patients and staff?  How will staff be trained?

3. 3 Components of standardized R/E/L data collection Standardized categories across the organization Patient self-reports race, ethnicity and language – No more “eyeballing” the patient – Data is collected from all patients Telling the patient why we are collecting his/her race, ethnicity and language

4. 4 Where are data collected? When scheduling/registering an office visit – Face-to-face – Written registration forms – Telephone Upon admission or registration at the hospital – Face-to-face – Telephone registration All points of entry (inpatient, outpatient, emergency department, cardiac catheterization lab, etc.) “Downstream effect” – Registries and other databases Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009http://www.hretdisparities.org/

5. 5 Who needs to be engaged? Senior Leadership Information Technology staff Registration/Admissions staff Quality Improvement Interpreter Services Clinicians Patient Advocacy/Diversity Team Community Relations/Marketing Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009http://www.hretdisparities.org/

6. 6 When does everyone need to be engaged? Your timeline should reflect the work that needs to be done Get early support and buy-in – Ask for input on the changes – Will minimize resistance to change Share information often – Continue to build support – Keep dialogue going

7. 7 What registration system modifications need to be made? Will you need add data fields to accommodate new categories? – Will you use granular categories? – Can patients choose more than one race? What is your system’s capacity to add a field? – Can the change be made ‘in-house’ and house-wide? – What departments need to be involved to make changes to the system? – Is there a need to create combined R/E categories? Will these fields be hard stops?

8. 8 Other IT system modifications Does your registration system link with other IT systems (e.g., clinical systems, disease registries)? Will registration systems from different points of entry ‘talk to one another’? How will the data be stored? – What to do with old data? – How long will new data stay in the system?

9. 9 How will patient registration process change? How will registration staff ask the questions? Will scripts be used? In which order will the questions be asked? How might registration of patients by phone be the same/different than in-person?

10. 10 How will patients be informed about the new questions? Most patients believe health care providers should collect race and ethnicity data Letting your patients know that it is about improving quality helps everyone’s comfort level

11. 11 Letting your patients know: Putting it into practice Wall Posters Can be displayed in: Registration areas Waiting rooms

12. 12 How will staff be trained? Who needs to be trained? Who will provide training? How will the training be implemented? – Role-playing? Handouts/scripts? Screen content? Will data be monitored after the training? How will you monitor data? – Will feedback be given? – Will registrars see how data is used?

13. 13 Anticipating staff concerns Patients will get angry It’s illegal Patients will get angry We don’t need to collect this information Patients will get angry I’m uncomfortable asking these questions Patients will get angry It will take too much time Patients will get angry

14. 14 Address staff concerns by providing: Training sessions and focus groups where staff can ask questions An explanation of why the organization is doing this and how patients may benefit Feedback on how the process is going Guidance in solving problems or refining the process as needed Findings from the R/E/L data and how the data have been used to analyze and improve care