1. Mixed Methods Research in Practice: Communication about Prognosis in Intensive Care Units Douglas B. White, MD, MAS Assistant Professor Division of Pulmonary and Critical Care Medicine Investigator, UCSF Program in Medical Ethics

2. Overview n Background (brief) n Aims & Study Methods n Practical Issues u Research on family members of dying patients u Training research coordinator u Data management n Methodological issues u Why mixed methods? u Why grounded theory?

3. Co-Investigators n Bernard Lo, MD Director, UCSF Program in Medical Ethics Research: Physician- patient communication; decision-making. n Ken Covinsky, MD, MPH Director, Geriatrics Research Training Program Research: determinants of prognosis in community dwelling elders; n Anita Stewart, PhD n John M. Luce, MD n Randy Curtis MD, MPH n Seth Landefeld, MD

4. An Example n Previously healthy 71-year man admitted to the ICU with a large stroke. He develops severe pneumonia w/ resp failure, sepsis and renal failure. u Aphasic, R hemiparesis u APACHE II: 35; In-hospital mortality 70% u Significant functional impairment u Patient decisionally incapacitated

5. Should life support be continued? u Surrogate decision-making u No clear “right” medical answer u Preference-sensitive decision

6. Why study communication of prognosis? 1. Patients/Families have: u A right to know autonomy & informed DM u A need to know Prognostic info affects treatment choices 2. Prognostic misunderstandings are common

7. I Shouldn't Have Had To Beg for a Prognosis With all the conflicting reports on his health, I didn't know if he was holding steady or dying. Aug. 22, 2005 issue - I was once a stalker. My victims—yes, there were several— were high on the social scale, but they were not celebrities. They were doctors.…

8. What causes misunderstandings about prognosis? Little empirical research about mechanisms n Poor MD communication skills? n No information from physicians? n Optimism bias in MD communication? n Optimism bias by families? n Lack of trust in physicians? n Low health literacy/numeracy? n Different attitudes about predicting future?

9. The Structure-Process-Outcome Paradigm: Prognosis Communication in the ICU Process of care: - # prognosis discussions - Content of discussion Outcome MD-family agreement re: prognosis Family characteristics: - literacy/numeracy - optimism - depression - prior experiences -trust in physician -Beliefs about future telling Physician characteristics: -Demographics -Skills - Attitudes

10. What causes misunderstandings about prognosis? How do surrogates arrive at an understanding of a patients’ prognosis? -what sources of information? -cultural/religious influence? -attitudes about prognostication?

11. Specific Aims Project 1 Aim 1: To determine the prevalence and predictors of misunderstandings about prognosis between physicians and family of ICU patients at high risk for death. Aim 2: To determine what factors contribute to families’ assessment of a patients’ prognosis.

12. K12 Project 1- Study Design Design: Cross sectional study Setting: 4 ICUs at UCSF (60 ICU beds) Subjects: u 175 ICU patients at high risk of death u Attending MDs u Family decision-maker(s) Measurements: u Questionnaires from MDs & family members u Chart review u Audiotaped interview with family members

13. K12 Project 1- Subjects Eligible Patients: u Lack decision-making capacity u Mechanically ventilated ≥ 3 days and ≤5 days u 40% mortality predicted mortality (APACHE II) Why study these patients?

14. K12 Project 1- Subjects Eligible family decision-maker(s): n Traditional hierarchy of surrogates is inadequate u Question to family: “Who would be involved in DM if patient couldn’t participate?” u Potential for multiple respondents per patient Physician: n Primary Attending Physician

15. Recruitment & Data Collection Strategy Daily screening n RA identifies pts intubated for 72 hours n calculates APACHE scores 1. 1 st Contact- Attending MD n Oral consent/permission to approach family n Answer prognosis questions by phone n Complete written questionnaire

16. Recruitment & Data Collection Strategy Contact with Family u 30 minute questionnaire u 20 minute semi-structured interview (audiotaped) u Conducted in private room adjacent to ICUs

17. 0% chance of survival 100% chance of survival 1.What do you think are the chances that the patient will survive this hospitalization if the current treatment plan is continued? Place a mark on the line… 0% chance of survival 100% chance of survival Outcome Measure- Prognostic Discordance

18. 0% chance of survival 100% chance of survival 1.What do you think the doctor thinks are the chances that the patient will survive this hospitalization if the current treatment plan is continued? Place a mark on the line… Outcome Measure- Prognostic Discordance

19. Measurements- Physician Predictors u Demographics (age, gender, race) u Specialty u Self-rated skill: Communicating prognosis to family End of life communication skills u Attitudes about: Prognostication Involving family in decision-making

20. Measurements- Family Predictors u Literacy u Numeracy u Desire for information u Preferred Role in DM u Depression u Locus of Control u Dispositional Optimism u Prior EOL DM experience

21. Statistical Plan- Phase 1 Overarching goal: To identify factors associated with overly optimistic prognostic estimates by family. Approach: multivariate analysis u logistic regression or linear regression u mixed effects modeling (2 levels of clustering) u include factors with p≤0.20 on bivariate

22. Aim 2: To determine what factors contribute to families’ assessment of a patients’ prognosis. n Semistructured interviews with family n RA shows family the recorded prognostic estimate and asks: 1) “What has made you think this is your loved ones’ chance of surviving?” -follow up probes 2) “I notice this is your prognostic estimate, but that this is what you think the MD thinks the prognosis is. Can you tell me why they’re different?”

23. Aim 2: To determine what factors contribute to families’ assessment of a patient’s prognosis. Analysis: -transcription by trained qualitative transcriptionist -multidisciplinary coding team -Grounded theory approach to inductively develop a conceptual framework -multiple investigator meetings -Member checking

24. Expectations- Project 1 1. Quantitative determination of predictors of discordance 2. Qualitative understanding of how family members make an assessment of patient’s prognosis. 3. Reasons that family hold systematically different view of prognosis than physician.

25. K12 Project 2: Audiotaped Discussions about Prognosis

26. Specific Aims Project 2 Aim 3: To determine how physicians communicate with surrogates of ICU patients about prognosis. Aim 4: To identify communication strategies that are associated with physician-family concordance about prognosis.

27. Qualitative Data Analysis: Coding Strategy Development of framework: u Inductive process  Grounded Theory approach u Develop categories of prognosis Preliminary framework: u 5 investigators analyzed prognostic statements from same 5 conferences  each developed framework u Multiple investigator meetings  developed consensus regarding framework

28. Sample coding “I’m really concerned about your father’s future. His chances of surviving this hospitalization are poor. When I say that, I mean maybe 80% of people in your Dad’s situation don’t survive. Even if he did survive, his quality of life would be poor.” General Survival QOL

29. K12 Study Design- Project 2 Design: (Nested) cross-sectional study Subjects: u N=60 subset of the 175 physician-family pairs from Project 1 Measurements: u Audiotaped MD-family discussion u Questionnaires from MDs & family members u Outcome: understanding of prognosis after discussion

30. Recruitment Daily screening n By RA  bedside nurse: “Is a family meeting planned for today?” 1. 1 st Contact- Attending MD* n Oral consent/permission to approach family n Consent from MD and all family *probable clustering

31. Data Collection Strategy Before MD-Family Meeting nFamily prognostic estimate Audiotape the meeting After MD-Family Meeting nMD prognostic estimate nFamily prognostic estimate nFamily satisfaction with communication

32. Outcome Measure- Discordance Score Family PessimisticFamily Optimistic -100-90-80-70-60-50-40-30-20-10102030405060708090100 No Discordance

33. Data Analysis Possible Predictors u number/type prognostic statements u Language used to communicate risk u MD behaviors (assessing desire for prog info and understanding) u Family behaviors (questions, explicit statement of prognosis, disagreement) u Family satisfaction w/ communication