Supplementary Appendix

Transcription

1 Supplementary Appendix This appendix has been provided by the authors to give readers additional information about their work. Supplement to: White DB, Angus DC, Shields A-M, et al. A randomized trial of a family-support intervention in intensive care units. N Engl J Med 2018;378: DOI: /NEJMoa

2 SUPPLEMENTARY MATERIALS FOR: A Randomized Trial of a Family Support Intervention Delivered by the Interprofessional Clinical Team in Intensive Care Units Table of Contents: Pages List of Investigators 1 Table S1. Costs to Deploy the Intervention 2 Figure S1. Stepped Wedge Allocation of Trial Patients and Surrogates 3 Table S2: Characteristics of enrolled patients and surrogates 4 Table S3. Comparison of characteristics of patients whose surrogate completed versus did not consent to 6-month interview Figure S2a-j. Sensitivity analyses: intervention effects across time and within individual centers Exploratory analysis of survival time through 6-month follow-up 17 Table S4a-c. Effect of the PARTNER intervention on HADS subscale scores 18 Table S5. Main Study Outcome Measures Treated as Categorical Variables 19 Table S6. Effect of PARTNER Intervention on surrogates psychological distress stratified by whether the patient survived the index hospitalization 20 Trial Registration and Designation as Quality Improvement Project 21 Schedule of PARTNER Program 12-Hour Communication Skills Training PARTNER Question Prompt List 24 Comparison of PARTNER intervention and SUPPORT intervention 25 0

3 List of Investigators Douglas B. White, MD, MAS 1 Derek C. Angus, MD, MPH, FRCP 2 Anne-Marie Shields, MSN, RN 1 Praewpannarai Buddadhumaruk, MS, RN 1 Caroline Pidro, BS 2 Cindy Paner, RN, MSN 3 Elizabeth Chaitin, MSW, MA, DHCE 9 Chung-Chou H. Chang, PhD 2,4 Francis Pike, PhD 5 Lisa Weissfeld, PhD 6 Jeremy M. Kahn, MD, MS 2 Joseph M. Darby, MD 7 Amy Kowinsky, RD, LDN 3 Susan Martin RN, MSN 3 Robert M. Arnold, MD 8,9 On behalf of the Pairing Re-engineered Intensive Care Teams with Nurse-driven Emotional Support and Relationship building (PARTNER) Investigators 1 Program on Ethics and Decision Making, The Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 2 The CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 3 The Wolff Center at UPMC, UPMC Health System, Pittsburgh, PA, USA 4 Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 5 Eli Lilly and Company, Indianapolis, IN, USA 6 Statistics Collaborative; 1625 Massachusetts Ave. NW; Suite 600; Washington DC Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 8 Department of General Internal Medicine, Section of Palliative Care and Medical Ethics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA 9 Palliative and Supportive Institute, UPMC Health System, Pittsburgh, PA, USA Funding Source: UPMC Innovation Award; The Greenwall Foundation Trial Registration Number: NCT Address for correspondence: Douglas B. White, MD, MAS Program on Ethics and Decision Making in Critical Illness Department of Critical Care Medicine University of Pittsburgh School of Medicine 3550 Terrace St, Scaife Hall, Room 608 Pittsburgh, PA whitedb@upmc.edu 1

4 TABLE S1. Costs to Deploy the Intervention 12-hour communication skills training course for staff nurses at each site. Ten daily site visits by QI specialist at beginning of intervention phase at each site (4 hours each). Description of Expenses Hourly wages for nurses being trained, time of 2 medical actors, 1 instructor, and QI implementation specialist; printed training materials, facility rental, and meals for all attendees. Hourly wage of QI implementation specialist; parking and travel expenses. Cost (in U.S.D) $23, $11, Weekly site visits by QI implementation specialist throughout intervention phase at each site (4 hours each). Hourly wage of QI implementation specialist; parking and travel expenses. $58, TOTAL COST $92, Costs per patient who received the $ intervention (N=547) 2

5 Figure S1. Stepped Wedge Allocation of Trial Patients and Surrogates Study ICU Step 0 Step 1 Step 2 Step 3 Step 4 Step 5 Total 1 65 Patients enrolled 52 Surrogates agreed to follow-up 36 Completed follow up Patients enrolled 103 Surrogates agreed to follow-up 65 Completed follow up Patients enrolled 168 Surrogates agreed to follow-up 127 Completed follow up Patients enrolled 197 Surrogates agreed to follow-up 158 Completed follow up 208 Patients enrolled 159 Surrogates agreed to follow-up 119 Completed follow up 106 Patients enrolled a 75 Surrogates agreed to follow-up 53 Completed follow up 114 Patients enrolled 108 Surrogates agreed to follow-up 72 Completed follow up 67 Patients enrolled b 41 Surrogates agreed to follow-up 28 Completed follow up 273 Patients enrolled 211 Surrogates agreed to follow-up 155 Completed follow up 242 Patients enrolled 178 Surrogates agreed to follow-up 118 Completed follow up 337 Patients enrolled 276 Surrogates agreed to follow-up 199 Completed follow up 322 Patients enrolled 238 Surrogates agreed to follow-up 186 Completed follow up Patients enrolled 157 Surrogates agreed to follow-up 115 Completed follow up White shading= usual care; Blue shading = intervention a Last patient enrolled on 7/1/2014 because this ICU was closed by the hospital administration. b ICU decreased in size from 28 beds to 20 beds on 7/1/ Patients enrolled 46 Surrogates agreed to follow-up 36 Completed follow up 246 Patients enrolled 203 Surrogates agreed to follow-up 151 Completed follow up TOTAL 1420 Patients enrolled 1106 Surrogates agreed to follow-up 809 Completed follow up 3

6 Table S2: Characteristics of enrolled patients and surrogates Patient Characteristic Control (n=873) Intervention (n=547) p-value a Age, mean (SD) 63.3 (15.5) 67.5 (14.9) <0.001 Female, count (%) 405 (46.4) 290 (53.0) 0.02 Race, count (%) White Black Hispanic Other Not documented Primary Diagnosis, count (%) Cardiovascular Pulmonary GI Toxicology Infection/Sepsis Neurological Oncological Other Admission source, count (%) Direct Emergency Other hospital Skilled nursing facility 708 (81.1) 64 (7.3) 2 (0.2) 9 (1.0) 90 (10.3) 36 (4.1) 138 (15.9) 94 (10.8) 38 (4.4) 212 (24.4) 173 (19.9) 59 (6.8) 118 (13.6) 224 (25.7) 549 (62.9) 100 (11.5) (83.9) 43 (7.9) 0 4 (0.7) 41 (7.5) 33 (6.0) 107 (19.6) 49 (9.0) 18 (3.3) 159 (29.1) 106 (19.4) 18 (3.3) 56 (10.3) 50 (9.1) 422 (77.2) 73 (13.4) 2 (0.4) 0.30 <0.01 <0.001 Modified SAP II score, mean (SD) 49.4 (12.0) 51.0 (11.8) 0.02 Elixhauser comorbidity index (count; range 0-29), mean (SD) 5.1 (2.5) 5.8 (2.4) <0.001 On mechanical ventilation during hospitalization, count (%) 759 (86.9) 479 (87.6) 0.73 Surrogate Characteristic Control (n=677) Intervention (n=429) p-value Age, mean (SD) 56.4 (13.6) 57.1 (13.7) 0.46 Female, count (%) 480 (70.9) 284 (66.2) 0.06 Race, count (%) White Black Hispanic Asian Multiethnic Not documented Relationship to Patient Spouse/partner Parent Child Sibling Other relative Other relationship Not documented a From Student s t-test or Pearson's chi-squared test 559 (82.6) 37 (5.5) 5 (0.7) 6 (0.9) 3 (0.4) 67 (9.9) 295 (43.6) 63 (9.3) 197 (29.1) 81 (12.0) 18 (2.7) 20 (3.0) 3 (0.4) 383 (89.3) 36 (8.4) 0 (0) 2 (0.5) 2 (0.5) 6 (1.4) 161 (37.5) 28 (6.5) 163 (38.0) 53 (12.4) 12 (2.8) 9 (2.1) 3 (0.7)

7 Table S3. Comparison of characteristics of patients whose surrogate completed versus did not consent to 6-month interview Patient characteristics Did not complete 6 month followup (n=611) Completed 6 month follow up (n=809) p-value a Total Age, mean (SD) 64.9 (15.2) 64.9 (15.6) (15.4) Female, No. (%) 309 (50.6) 386 (47.7) (48.9) Race, No. (%) White Black Hispanic Other Not documented Primary Diagnosis, count (%) Cardiovascular Pulmonary GI Toxicology Infection/Sepsis Neurological Oncological Other Not documented Admission source, No. (%) Direct Emergency Other hospital SNF 538 (81.0) 66 (9.9) 1 (0.2) 8 (1.2) 51 (7.7) 28 (4.6) 102 (16.7) 61 (10.0) 27 (4.4) 174 (28.5) 115 (18.8) 35 (5.7) 66 (10.8) 3 (0.5) 674 (83.3) 48 (5.9) 1 (0.1) 5 (0.6) 81 (10.0) 41 (5.1) 143 (17.7) 82 (10.1) 29 (3.6) 197 (24.4) 164 (20.3) 42 (5.2) 108 (13.4) 3 (0.4) (82.3) 114 (7.7) 2 (0.1) 13 (0.9) 132 (9.0) 69 (4.9) 245 (17.3) 143 (10.1) 56 (3.9) 371 (26.1) 279 (19.7) 77 (5.4) 174 (12.3) 6 (0.4) 109 (17.8) 422 (69.1) 80 (13.1) (20.4) 549 (67.9) 93 (11.5) 2 (0.3) (19.3) 971 (68.4) 173 (12.2) 2 (0.1) Modified SAP II score, mean (SD) 50.2 (12.1) 49.8 (11.8) (11.9) Elixhauser comorbidity index score (0-29), mean (SD) 5.5 (2.6) 5.3 (2.5) (2.5) Received mechanical ventilation during the hospitalization, No. (%) 526 (86.1) 712 (88.0) (87.1) a From Student s t-test or Pearson's chi-squared test 5

8 Figure S2a-h. Sensitivity analyses: intervention effects across time and within individual centers We conducted post-hoc sensitivity analyses to assess the robustness of the main findings, following recommendations for such analyses in stepped wedge randomized controlled trials (Davey C, et al. Analysis and reporting of stepped wedge randomized controlled trials: synthesis and critical appraisal of published studies, 2010 to Trials 2015; 16:358). First, we assessed whether the effects of the intervention were consistent over time during the study period. Second, we assessed whether the effects of the intervention were consistent across sites. Overall, these exploratory analyses support the robustness of the findings across individual sites and individual time steps. We used two approaches to assess for heterogeneity of treatment effect over time. First, we assessed for interactions between treatment and the fixed effect for time. To check for interactions between treatment and time, we included a variable for time step (time step=0 to time step=5) and an interaction variable between this time step and PARTNER intervention in the multivariable linear regression models, adjusted for the same variable listed in Table 2. Second, we reran the multivariable regression models stratified by time, then plotted the treatment effect across time to allow for visual comparison. For this analysis, we used the same multivariable linear regression models in Table 2 but restricted the analyzing cohort to those enrolled between time 0 to the end of time step t (where t=1, 2, 3, or 4). Therefore, we obtained a total of 4 stratified models for each outcome. We used two approaches to assess for heterogeneity of treatment effect across individual ICUs. First, we assessed for interactions between treatment and the ICU fixed effect. To check for interactions between treatment and ICU fixed effect we included a variable for site and interaction variable between PARTNER intervention and site into the multivariable linear regression models, adjusted for the same variable listed in Table 2. Second, we refit the multivariable regression models stratified by ICUs, then plotted the treatment effect in individual ICUs to allow for visual comparison. To refit the models stratified by ICU, we used the same multivariable linear regression models in Table 2 but restricted the analyzing cohort to each site. Therefore, we obtained a total of 5 stratified models for each outcome. 6

9 Magnitude of effect size on QOC Figure S2a. Effect of PARTNER intervention across time on Quality of Communication (QOC) score with 95% CI Overall effect End of time step t size Summary of findings in S2a. After adjusting for patient s age, race, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, and admission source, the intervention significantly improved surrogates perceptions of the quality of communication (QOC scale; β=6.39 (95% CI 2.57 to 10.20; p=0.001). Overall, there was no difference across time in the QOC score; the interaction between treatment and time fixed effect was not statistically significant (p=0.08). Visual inspection of the effect over time revealed that there was a positive effect in all time steps. 7

10 Magnitude of effect size on PPPC Figure S2b. Effect of PARTNER intervention across time on the patient- and familycenteredness of care score (with 95% CI) Overall effect size End of time step t Summary of findings in S2b. After adjusting for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, admission source, surrogate s age and gender, the PARTNER intervention improved surrogates perceptions of the patient- and familycenteredness of care (β (95% CI to -0.04; p=0.006). Overall, there was no difference across time in the PPPC score; the interaction between treatment and time fixed effect was not statistically significant (p= 0.77). Visual inspection of the figure displaying stratification by time revealed that there was a similar effect of the PARTNER intervention on surrogates perceptions of the patient- and family-centeredness of care in all time steps. 8

11 Magnitude of effect size on HADS Figure S2c. Adjusted estimated effect of PARTNER intervention across time on total HADS score with 95% CI Overall effect size End of time step t Summary of findings in Figure S2c: Overall, there was no significant difference between groups in the HADS score (β (95% CI to 0.99; p=0.62) after adjusting for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. There was no difference across time in the HADS score; the interaction between treatment and time fixed effect was not statistically significant (p=0.10). Visual inspection of the figure displaying stratification by time revealed that there was a similar effect of the PARTNER intervention on surrogates HADS scores in all time steps. 9

12 Magnitude of effect size on IES Figure S2d. Adjusted estimated effect of PARTNER intervention across time on IES score with 95% CI Overall effect size End of time step t Summary of findings in S2d. Overall there was no significant effect of the intervention on surrogates post-traumatic stress symptoms, measured with the IES, after adjusting for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient (β: 0.90 (95% CI to 3.47; p=0.49). There was no difference across time in the IES score; the interaction between treatment and time fixed effect was not statistically significant (p= 0.97). Visual inspection of the figure displaying stratification by time revealed that there was a similar effect of the PARTNER intervention on surrogates IES score in all time steps. 10

13 Magnitude of effect size on ICU LOS among decedents Figure S2e. Adjusted estimated effect of PARTNER intervention across time on ICU length of stay (LOS) among in-hospital decedents (IRR with 95% CI) Overall effect size End of time step t Summary of findings in S2e. Overall there was no difference across time in ICU LOS among decedents (IRR 0.64; 95% CI 0.52 to 0.78; p<0.001). The interaction between treatment and time fixed effect was not statistically significant (p=0.516). Stratification by time step showed no significant change in the intervention s effect on ICU LOS across time. 11

14 Magnitude of effect size on QOC Figure S2f. Adjusted estimated effect of PARTNER intervention by site on QOC score (with 95% CI) ICU1 ICU2 ICU3 ICU4 ICU5 Overall effect size Site Summary of findings in S2f. After adjusting for patient s age, race, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, and admission source, the intervention significantly improved surrogates perceptions of the quality of communication (QOC scale), β 6.39 (95% CI 2.57 to 10.20; p=0.001). There was no significant heterogeneity of treatment effect across sites as evidenced by the non-significance of the interactions between treatment and ICU fixed effect (p= Visual inspection of the figure displaying site-specific estimates of effect size reveals all ICUs with similar effects. 12

15 Magnitude of effect size on PPPC Figure S2g. Adjusted estimated effect of PARTNER intervention on PPPC score with 95% CI by site ICU1 ICU2 ICU3 ICU4 ICU5 Overall effect size Site Summary of findings in S2g. After adjusting for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, admission source, surrogate s age and gender, the PARTNER intervention improved surrogates perceptions of the patient- and familycenteredness of care (β (95% CI to -0.04; p=0.006). The treatment effect was consistent across sites as evidenced by the non-significance of the interactions between treatment and ICU fixed effect (p=0.14). Visual inspection of the figure displaying site-specific estimates of effect size reveals all ICUs showed improvements in the patient- and familycenteredness of care in the ICU (i.e., reduced scores on the scale). 13

16 Magnitude of effect size on HADS Figure S2h. Adjusted estimated effect of PARTNER intervention by site on total HADS score with 95% CI ICU1 ICU2 ICU3 ICU4 ICU5 Overall effect size Site Summary of findings in Figure S2h: Overall, there was no significant difference between groups in the HADS score (β (95% CI to 0.99; p=0.62). While site effect was not statistically significant (p=0.62), the interaction between treatment and ICU fixed effect was statistically significant (p=0.04). Running an analysis stratified by ICU revealed that one ICU differed from the other 4 ICUs in terms of detecting a significant improvement in HADS scores (β -3.91; 95% CI to -0.20; p=0.04), whereas the was no significant heterogeneity across the other ICUs. Of note, the one ICU that drove the positive heterogeneity test had the fewest patients in the control arm (n=34) raising questions about the stability of the estimate of the treatment effect in the control arm. 14

17 Magnitude of effect size on IES Figure S2i. Adjusted estimated effect of PARTNER intervention on IES score with 95% CI by site ICU1 ICU2 ICU3 ICU4 ICU5 Overall effect size Site Summary of findings in S2i. Overall there was no significant effect of the intervention on surrogates post-traumatic stress symptoms, measured with the IES, after adjusting for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, primary diagnosis, admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient (β: 0.90 (95% CI to 3.47; p=0.49). There was not a significant interaction between treatment and ICU fixed effect (p= 0.077). On visual inspection of the sitespecific effects in Figure S8d, the 95% CI of the effect size overlapped across all 6 ICUs. 15

18 Effect size on ICU LOS among decedents (IRR) Figure S2j. Adjusted effect of PARTNER intervention by site on ICU length of stay (LOS) among in-hospital decedents (IRR with 95% CI) ICU1 ICU2 ICU3 ICU4 ICU5 Overall effect size Site Summary of findings in S2j: The overall effect of PARTNER intervention on ICU LOS among decedents adjusted for site is IRR 0.64 (95% CI 0.52 to 0.78; p<0.001). The interaction between treatment and ICU fixed effect was not statistically significant (p=0.238). Running an analysis stratified by ICU revealed that the intervention decreased ICU LOS across all sites. 16

19 Exploratory analysis of survival time through 6-month follow-up Approach and findings: To assess whether the intervention affected survival time over 6-month follow-up, we conducted an exploratory analysis using Gray s semiparametric survival regression model, adjusting for time, ICU site, age, having mechanical ventilation, modified SAPS III score, and primary diagnosis. We assessed the proportional hazards (PH) assumption for each covariate using Gray s test (1992). We treated covariates that violated the PH assumption as time-varying. We treated all other covariates as constant in the model. ICU was treated as a fixed effect. The covariates that significantly violated the PH assumption were treatment, time, ICU, age, and primary diagnosis. In the final adjusted model, there was no statistically significant effect on duration of survival within the 6-months of combined inpatient and outpatient follow up (HR=1.25, 95% CI: ; p-value=0.09). These findings are consistent with the main outcome analysis of 6-month survival, which found no statistically significant difference in the proportion of patients alive at 6 months. Reference Gray, RJ (1992). Flexible methods for analyzing survival data using splines, with application to breast cancer prognosis. Journal of the American Statistical Association, 87,

20 Table S4a. Effect of the PARTNER intervention on HADS subscale scores Control (n=501) Intervention (n=308) Unadjusted p-value a Intervention effect (95% CI) 7.1 (4.7) 6.7 (4.3) 0.21 β c (-0.99 to 0.50) 4.9 (4.4) 5.0 (4.3) 0.91 β c HADS anxiety subscale (range 0-21), mean (SD) HADS depression subscale (range 0-21), mean (SD) (-0.80 to 0.60) a From Student s t-test b Adjusted for site, patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, and admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. c β=linear regression coefficient. Results from adjusted linear regression model. Adjusted p-value b Table S4b. Effect of the PARTNER intervention on HADS subscale categories: normal, borderline abnormal, and abnormal. HADS anxiety subscale category 0-7 Normal 8-10 Borderline abnormal Abnormal HADS depression subscale category 0-7 Normal 8-10 Borderline abnormal Abnormal Control (n=501) 285 (58.2) 91 (18.6) 114 (23.3) 373 (76.1) 53 (10.8) 64 (13.1) Intervention (n=308) 182 (59.3) 70 (22.8) 55 (17.9) 233 (75.9) 37 (12.1) 37 (12.1) Unadjusted p-value a Intervention effect (95% CI) 0.12 OR 0.93 c (0.67 to 1.30) 0.82 OR 0.89 c (0.59 to 1.33) a From Student s t-test b Adjusted for site, patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, and admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. c OR=odds ratio. Results from adjusted ordinal logistic regression model. Adjusted p-value b Table S4c. Effect of the PARTNER intervention on HADS subscale binary categories: normal vs abnormal HADS anxiety subscale, count, (%) 0-10 Normal Abnormal HADS depression subscale, count, (%) 0-10 Normal Abnormal Control (n=501) 376 (76.7) 114 (23.3) 426 (86.9) 64 (13.1) Intervention (n=308) 252 (82.1) 55 (17.9) 270 (88.0) 37 (12.1) Unadjusted p-value a Intervention effect (95% CI) 0.07 OR 0.73 c (0.48 to 1.13) 0.68 OR 0.73 c (0.43 to 1.25) a From Student s t-test b Adjusted for site, patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, and admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. c OR= odds ratio. Results from adjusted logistic regression model. Adjusted p-value b

21 Table S5. Main Study Outcome Measures Treated as Categorical Variables Control (n=501) Intervention (n=308) a Unadjusted p-value Intervention effect (95% CI) Adjusted p-value b Surrogates Psychological Symptom Burden c Hospital Anxiety and Depression Scale category; No. (%) Normal (0-14) Borderline abnormal (15-21) Abnormal (22-42) Refused HADS assessment Impact of Events Scale category, No. (%) No concern (0 score<24) Partial PTSD (24 score<33) Probable PTSD (33 score<37) PTSD (37 score 88) Refuse IES assessment 333 (66.5) 80 (16.0) 77 (15.4) 11 (2.2) 316 (63.1) 73 (14.6) 17 (3.4) 79 (15.8) 16 (3.2) 206 (66.9) 62 (20.1) 39 (12.7) 1 (0.3) 190 (61.7) 40 (13.0) 22 (7.1) 53 (17.2) 3 (1.0) 0.06 OR 0.96 d,e (0.67 to 1.37) 0.04 OR 1.29 e ( ) Communication and Decision Making Outcomes Quality of Communication Scale OR (30.5) 126 (41.0) f,g score 80, No. (%) (1.17 to 2.30) Patient- and family-centeredness, No. (%) 3<score 4 38 (7.6) 14 (4.6) OR 2.03 <0.001 e,h 2<score (27.9) 50 (16.2) (1.41 to 2.93) 1 score (62.7) 244 (79.2) Refused assessment 9 (1.8) 0 (0) a From Pearson's chi-squared test b All models were adjusted for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, and admission source. c Additional covariates included in the model: patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. d Additional covariates included in the model: site e OR=odds ratio. Results from ordinal logistic regression modeling. f Additional covariates included in the model: patient s race (black vs. non-black) g OR=odds ratio. Results from logistic regression modeling. h Additional covariates included in the model: surrogate s age and gender <

22 Table S6. Effect of PARTNER Intervention on surrogates psychological distress stratified by whether the patient survived the index hospitalization Patient survived hospitalization PARTNER Intervention Adjusted effect (95% CI) p-value a Patient died in-hospital PARTNER Intervention effect (95% CI) Adjusted p-value a Surrogates Psychological Outcomes (n=568) (n=241) HADS (range 0-42) b β (-1.71 to 1.47) c 0.88 β (-3.94 to 1.26) c 0.31 IES (range 0-88) β 0.65 (-2.31 to 3.61) c 0.67 β 0.37 (-4.90 to 5.64) c 0.89 a Adjusted for patient s age, modified SAPS III, Elixhauser index, mechanical ventilation usage, admission source, patient s vital status up to 6-month post-discharge, surrogate s gender and relationship to the patient. b Additional covariates included in the model: site c β=linear regression coefficient. Results from adjusted linear regression model. 20

23 Trial Registration and Designation as Quality Improvement Project The University of Pittsburgh Institutional Review Board, the UPMC Quality Improvement Committee, and the leadership of participating ICUs approved the project. The deployment of the intervention was judged to be a quality improvement project because its primary purpose was to increase the implementation of behaviors recommended in professional society practice statements (e.g., provision of emotional support and timely conduct of interdisciplinary family meetings). All surrogates of eligible patients were informed of the quality improvement project by clinical staff. The long-term follow up of surrogates was judged to be research; therefore, surrogates provided informed consent for participation. Due to an administrative error by the research team regarding whether quality improvement projects could be registered on clinicaltrials.gov, trial registration was finalized after subject enrollment commenced. The timeline was as follows: 1. UPMC approved the study protocol on June 18, 2012 (one month before the trial was started). This institutional review concluded that the project was a quality improvement project and therefore would not be issued an IRB approval number. 2. Before the first patient was enrolled the study coordinator attempted to register the trial on the clinical trials registration site (clinicaltrials.gov). However, when she encountered the portion of the registration process that requests the IRB approval number, she interpreted the instructions on the website to mean that she could not formally submit the application without an IRB approval and therefore did not finalize the registration. 3. Due to a miscommunication, the study PI believed that the outcome was that the research coordinator had indeed certified the registration and only needed to go back to update the site once we secured an IRB approval number. 4. Because the project was deemed QI by the institution and was approved to begin, subject enrollment proceeded. 5. In order to be able to add an IRB number to the trial registration site, we requested that the IRB review the project as human subjects research. We were eventually permitted to submit an IRB application which, after several iterations, was approved on 2/26/2013. Only the long-term follow up of surrogates was judged to be research requiring consent. 6. On April 19, 2013, the research coordinator entered the IRB approval number and finalized the submission on the clinical trials registration website. 21

24 Schedule of PARTNER Program 12-Hour Communication Skills Training DAY 1 8:15--8:30 a.m. Registration and Breakfast 8:30--9:00 a.m. PARTNER Overview 9:00--9:30 a.m. Overview of Core Communication Skills 9:30--10:00 a.m. First Meeting with Family (Didactic/modeling) 10:00 10:45 a.m. Skills Practice I: First Meeting with Family 10:45--11:00 a.m. BREAK 11:00 11:45 a.m. Skills Practice ll: First Meeting with Family 11:45 am--12:15 p.m. LUNCH 12:15--12:30 p.m. Making Family Meetings Happen 12:30--1:00 p.m. Pre-Family Meeting (Didactic/modeling) 1:00--2:00 p.m. Skills Practice lll: Pre-Family Meeting 2:00--2:15 p.m. BREAK 2:15--2:30 p.m. Daily Check-in (Didactic/modeling) 2:30--3:00 p.m. Skills Practice lv: Daily Check-in 3:00--3:15 p.m. Taking the Skills Home 3:15--3:30 p.m. Next steps and Program Evaluation 22

25 DAY 2 8:00--8:15 a.m. Registration and Breakfast 8:15--8:30 a.m. Overview of Today - Intervention Training Day 2 --Pre Meeting with Doctors --Family Meetings --Post-Family Meeting 8:30--8:45 a.m. Review and Model Key Activities of PARTNER Program (Intervention Training Day 1) -- First Meeting with Family --Pre-Family Meeting --Daily Check-in --Making Family Meetings Happen 8:45--9:00 a.m. 9:00 9:30 a.m. Pre Meeting with Doctors -- Didactic Talk -- Role Model Skills Pre Meeting with Doctors --Skills Practice 9:30--9:45 a.m. Gently Intervening in Family Meetings -- Didactic Talk -- Role Model Skills 9:45--10:45 a.m. 10:45 a.m.--11:15 a.m. 11: :45 a.m. 11:45 12:15 p.m. 12:15 12:30 p.m. 12:30 12:45 p.m. Gently Intervening: Skills Practice --Practice Activities/Skills --Gently Intervening Skills Practice LUNCH Review and Model Skills for Post-Family Meeting --Skills Practice Documentation Q & A Program Evaluation 23

26 PARTNER Question Prompt List Questions About My Loved One It s normal for families to have questions about what is happening with their loved one s illness and treatment. Please check the questions that you would like the doctor or ICU team to answer. Disease Information What is wrong with my loved one? What treatments is my loved one receiving? Prognosis What happens to most people with the kind of illness my loved one has? My Loved One s Values How can I make sure the doctors know about my loved one s values and treatment preferences? What should my role be in making treatment decisions? Options What are the different treatment options that we should be thinking about? Milestones How can we tell if my loved one is getting better or worse? Social How do people cope with having a loved one in the ICU? How do most people discuss the stress of having someone in the ICU with their family and friends? Who can provide information about insurance and financial issues? Is there a chaplain or other spiritual support available in the hospital? What should I do if I get conflicting information from the different doctors? Please write any other questions you have for the care team: Questions the Doctor May Ask You: Have you ever made decisions for a loved one who was too sick to make decisions? What was your loved one like before this hospitalization. What does he or she do/enjoy? Has your loved one ever talked about treatment preferences and values if he or she were very sick? What role would you like to play in major medical decisions for your loved one? 24

27 Comparison of PARTNER intervention and SUPPORT intervention The SUPPORT and PARTNER interventions are conceptually and practically very different. The SUPPORT intervention was grounded in traditional decision theory (i.e., utility theory) and focused on providing clinicians accurate information about patients prognosis and preferences. 1 In contrast, the PARTNER intervention was grounded in Kahneman and Tversky s prospect theory 2, and was designed to support surrogates through the emotional and psychological complexity of making decisions for others. Second, we used methods of implementation science to intervene on ICUs culture and practices related to family support. Third, the PARTNER intervention was delivered by the interprofessional ICU team rather than by external interventionists, which may have led to more integrated and effective support of surrogates. 1. Lynn J, Arkes HR, Stevens M, et al. Rethinking fundamental assumptions: SUPPORT's implications for future reform. Study to Understand Prognoses and Preferences and Risks of Treatment. J Am Geriatr Soc 2000;48:S Kahneman, Daniel. A Perspective on Judgment and Choice: Mapping Bounded Rationality. American Pyschologist. 2003; 58: