Augmenting Communication and Decision Making in the Intensive Care Unit with a Cardiopulmonary Resuscitation Video Decision Support Tool: A Temporal Intervention Study

McCannon, Jessica; O’Donnell, Walter J.; Thompson, B. Taylor; El‐Jawahri, Areej; Chang, Yuchiao; Ananian, Lillian; Bajwa, Ednan K.; Currier, Paul F.; Parikh, Mihir; Temel, Jennifer S.; Cooper, Zara; Wiener, Renda Soylemez; Volandes, Angelo E.

doi:10.1089/jpm.2012.0215

Cited by 48 publications

(41 citation statements)

References 21 publications

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“…A few videos of this sort with demonstrated efficacy already exist (McCannon et al 2012;Volandes et al 2007), and interactive checklists, simulations, and virtual worlds could be developed with online links to advance-directive forms or advance-care planning programs or for use within hospitals when decision-making demands are imminent.…”

Section: Policy Implicationsmentioning

confidence: 99%

Do Advance Directives Direct?

Shapiro

2015

Journal of Health Politics, Policy and Law

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Resolution of long-standing debates about the role and impact of advance directives - living wills and powers of attorney for health care - has been hampered by a dearth of appropriate data, in particular data that compare the process and outcomes of end-of-life decision making on behalf of patients with and without advance directives. Drawing on a large ethnographic study of patients in two intensive care units in a large urban teaching hospital, this article compares aspects of the medical decision-making process and outcomes by advance-directive status. Controlling for demographic characteristics and severity of illness, the study finds few significant differences between patients without advance directives and those who claim to have them. Surprisingly, these few differences hold only for those whose directives are in their hospital chart. There are no significant differences between those with no directive and those claiming to have a copy at home or elsewhere. The article considers the implications if directives seemingly must be in hand to show even modest effects. Do advance directives direct? The intensive care unit data provide far more support for the growing body of literature that casts doubt on their impact than studies that promote the use of them.

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Section: Policy Implicationsmentioning

confidence: 99%

Do Advance Directives Direct?

Shapiro

2015

Journal of Health Politics, Policy and Law

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“…7,12,13,14,15 Previous efforts to improve surrogate decision making have largely been directed towards improving surrogates’ understanding of medical facts and the cognitive quality of their decisions. 16,17,18,19 or towards improving the accuracy of their substituted judgments. 20,21 These studies have had negligible success.…”

mentioning

confidence: 99%

The Trial of Ascertaining Individual Preferences for Loved Ones' Role in End-of-Life Decisions (TAILORED) Study: A Randomized Controlled Trial to Improve Surrogate Decision Making

Sulmasy

Hughes

Yenokyan

et al. 2017

Journal of Pain and Symptom Management

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Context Patients with terminal illnesses often require surrogate decision makers. Prior research has demonstrated high surrogate stress, and that despite standards promoting substituted judgment, most patients do not want their surrogates to make pure substituted judgments for them. It is not known how best to help loved ones fulfill the surrogate role. Objectives To test the effectiveness of an intervention to help surrogate decision makers. Methods 166 patients (41% with ALS and 59% with gastrointestinal cancers) and their surrogates at 2 university medical centers were randomized to an intensive nurse-directed discussion of the end of life Decision Control Preferences of the patient (TAILORED) or a discussion of nutrition (CONTROL); 163 completed baseline interviews and underwent the intervention. Results Twelve patients died during follow-up and 137 dyads completed the study. Post-intervention, using all available data, TAILORED patients and surrogates became more likely to endorse mutual surrogate decision making, i.e., a balance of their own wishes and what the surrogate thinks best (Adjusted odds compared with baseline for patients = 1.78, p = .04; Adjusted odds for surrogates = 2.05, p = .03). CONTROL patients became 40% less likely to endorse mutual surrogate decision making (p = 0.08) while CONTROL surrogates did not change significantly from baseline (adjusted odds = 1.44, p = .28). Stress levels decreased for TAILORED surrogates (Impact of Events Scale = 23.1±14.6 baseline, 20.8±15.3 f/u, p= 0.046), but not for CONTROL (p = .85), and post-intervention stress was lower for TAILORED than CONTROL (p = .04). Surrogate confidence was uniformly high at baseline and did not change. Caregiver burden (Zarit) increased from 12.5±6.5 to 14.7±8.1 for TAILORED (p <.01) while not changing for CONTROL, yet satisfaction with involvement in decision making was higher at follow-up for TAILORED than for CONTROL (71% vs. 52%, p = .03). Conclusion TAILORED patients and surrogates who completed the study adopted a more mutual decision making style, balancing their own wishes with what the surrogate thinks would be best for them. Surrogates reported less stress and more satisfaction. Confidence was high at baseline and did not change. There was a modest increase in caregiver burden. These findings suggest that interventions like TAILORED might positively impact surrogate decision making.

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“…The mean age of patients was 54 ± 17 years old, and 40% were female. Median (IQR) duration of mechanical ventilation was 22 (17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) days. Hospital mortality was 29%, and one-year mortality was 45%.…”

Section: Model Developmentmentioning

confidence: 99%

“…Over twenty years ago, the SUPPORT trial failed to show an impact of providing objective prognostic information to clinicians, perhaps because clinicians did not share the information in 80% of cases 38 . Yet, when incorporated into formal decision aids, data from prognostic models can facilitate the presentation of objective prognostic information to surrogates, reduce decisional conflict, reduce use of low value health care, and better align choice with values [21][22][23] . Preliminary studies incorporating the ProVent model in an innovative decision aid to inform surrogate decision makers of PMV patients indicate that significant discordance in expectations of outcome between clinicians and decision-makers can be minimized 39 .…”

mentioning

confidence: 99%

“…If compelling prognostic data were available sooner for the patient whose goals of care are known, these decisions might be made more easily and earlier in the course of illness [21][22][23] . Building on our previous work, we hypothesized that a simple mortality prediction model constructed from factors clinically available by day 14 in the course of mechanical ventilation could discriminate between PMV patients at high and low risk of death at one year.…”

mentioning

confidence: 99%

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Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation

Hough

Caldwell

Cox

et al. 2016

Survey of Anesthesiology

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Objectives-The existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation.Study Design-Multi-center retrospective cohort study.Patients-Adult patients receiving at least 14 days of mechanical ventilation at 5 medical centers (development cohort) or enrolled in the ARDS Network FACTT trial (validation cohort). HHS Public Access Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptMeasurements and Main Results-Predictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with one-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver-operator characteristic curve (AUC).491 patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and non-trauma admission. The AUC for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old, and categorized platelet count at 100 × 10 9 /L, and had similar discrimination as the ProVent 14 model in both cohorts.Conclusion-Using clinical variables available on day 14 of mechanical ventilation, the ProVent14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within one year. KeywordsProlonged mechanical ventilation; outcomes; prognosis; critical care; communication; multiple organ failure; decision makingFor an increasing number of patients, critical illness or injury is neither self-limited nor imminently fatal 1 . As survival from life-threatening illness improves, pre-existing disease and newly-acquired organ dysfunction may conspire against recovery, leaving patients dependent on life supporting therapies for extended time periods. This syndrome, termed "chronic critical illness", is commonly typified by persistent respiratory failure that requires prolonged mechanical ventilation (PMV). Long-term mortality is high, approaching rates of 40% to 60% at one-year in inclusive cohorts [2][3][4][5][6][7][8][9][10] . Patients have a very high symptom burden during the weeks of prolonged ventilation 11,12 and chances of living at home with functional independence at the end of the year are as low as 10% 9,13 .Most PMV patients are unable to participate in thei...

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Augmenting Communication and Decision Making in the Intensive Care Unit with a Cardiopulmonary Resuscitation Video Decision Support Tool: A Temporal Intervention Study

Cited by 48 publications

References 21 publications

Do Advance Directives Direct?

Do Advance Directives Direct?

The Trial of Ascertaining Individual Preferences for Loved Ones' Role in End-of-Life Decisions (TAILORED) Study: A Randomized Controlled Trial to Improve Surrogate Decision Making

Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation

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