Christopher S Parshuram MBChB DPhil. moral distress, deepersonalization & uncertainty in the ICU ·yep· staff physician Department of Critical Care Medicine senior scientist Child Health Evaluative Sciences Program. The Research Institute.Hospital for Sick Children. director Centre for Safety Research. professor Interdepartmental Division of Critical Care Medicine & Departments of Pediatrics & Health Policy, Management and Evaluation. faculty Patient Safety Centre, Faculty of Medicine, University of Toronto, Canada. Caring for Staff and Families. Friday 9 Nov 15:50-16:10
Transcript
Christopher S Parshuram MBChB DPhil.
moral distress, deepersonalization & uncertainty in the ICU ·yep·staff physician Department of Critical Care Medicine senior scientist Child Health Evaluative Sciences Program. The Research Institute.Hospital for Sick Children. director Centre for Safety Research. professor Interdepartmental Division of Critical Care Medicine & Departments of Pediatrics & Health Policy, Management and Evaluation. faculty Patient Safety Centre, Faculty of Medicine, University of Toronto, Canada.
Caring for Staff and Families. Friday 9 Nov 15:50-16:10
Christopher S Parshuram MB.ChB. D.Phil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
Ontario, Canada.
disclosuresNamed inventor: Patent Bedside Paediatric Early Warning System. Owner the Hospital for Sick Children.Shares: Bedside Clinical Systems - a clinical decision support company in part owned by the Hospital for Sick Children.
Fan of MASH
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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perception vs. reality > important for interventions & nature of the construct
what is being measured stress / distress correlations with burnout & uncertainty
a personal goal zero distress NE no stress
correlates with meaningful outcomes professional effectiveness
(moral) (dis)stress: idea
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
\
n engl j med
349;12
www.nejm.org september
18, 2003
determinants of ventilator withdrawal
1125
tion Score; the need for inotropes, vasopressors, ordialysis; the physician’s prediction of the patient’slikelihood of survival in the ICU and the hospital(less than 10 percent, 10 to 40 percent, 41 to 60 per-cent, or greater than 60 percent); the physician’sprediction of the patient’s functional and cognitivestatus one month after hospital discharge (will notleave the hospital, will be severely limited, will besomewhat limited, or will be totally independent);and the physician’s perception of the patient’s pref-erences about the use of life support. All the inde-pendent variables were included in the multivariatemodel. Using this model, we identified 300 patientsat relatively high risk for withdrawal of the ventila-tor or death, with a threshold sensitivity of 68.6 per-cent and a specificity of 83.6 percent, a predictedprobability of 0.64, and an area under the receiver-operating-characteristic curve of 0.85. Among these300 patients, 88 (29.3 percent) were successfullyweaned, 105 (35.0 percent) died while receivingmechanical ventilation, and 107 (35.7 percent) hadthe ventilator withdrawn.
For these 300 patients, we conducted Cox pro-portional-hazards regression analysis to identify thedeterminants of physician-initiated withdrawal of
the ventilator. Data on patients who were weanedfrom mechanical ventilation or who died while re-ceiving mechanical ventilation were censored. Theindependent variables were the same base-line fac-tors used in the logistic model, in addition to thenumber of chronic diseases. Other daily variableswere considered in the week preceding withdrawalof mechanical ventilation or death, including indica-tors of the severity of illness (Multiple Organ Dys-function Score, ability to participate in decisions,use of inotropes or vasopressors, and use of hemo-dialysis), factors based on the physician’s clinicaljudgment (prediction of the likelihood of the pa-tient’s survival in the ICU and the hospital — exclud-ing predictions made within 48 hours before thewithdrawal of the ventilator, death, or successfulweaning, prediction of the patient’s functional andcognitive status one month after hospital discharge,and perception of the patient’s preferences about theuse of life support), and geographic factors (center,city, and country). We analyzed each factor in aunivariate model, and we included all factors withP values of less than 0.10 in a multivariate regres-sion, using backward stepwise elimination. We alsotested for two-way interactions and tested the in-
Figure 1. Outcomes among Patients Receiving Mechanical Ventilation Who Were Expected to Remain in the Intensive Care Unit (ICU) for at Least 72 Hours.
Of 851 enrolled patients, 539 were weaned from the ventilator. Of 146 patients who died while receiving mechanical ven-tilation and 166 who had mechanical ventilation withdrawn, 53 and 72 patients had inotropes or vasopressors with-drawn, respectively (P<0.001), and 8 and 18 patients underwent withdrawal of dialysis, respectively (P=0.01). The number of patients who died in the hospital includes the number who died in the ICU.
146 Died while receivingventilation (17.2%)
146 Died in the ICU(100%)
166 Had the ventilatorwithdrawn (19.5%)
145 Died in the ICU(87.3%)
160 Died inthe hospital
(96.4%)
6 Weredischarged
(3.6%)
851 Patients enrolled
539 Were weaned fromthe ventilator (63.3%)
13 Died in the ICU (2.4%)
57 Died in the hospital
(10.6%)
482 Weredischarged
(89.4%)
The New England Journal of Medicine Downloaded from nejm.org on November 5, 2018. For personal use only. No other uses without permission.
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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12-20% mortality (adult)2-4% mortality (paediatric)locked units
conflict & ‘characters’21% ketonuria, routine ASDburnout moral and morale distress
the certain ICU
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
\
230 parents of children who died structured interview 1m after death
chart cause of death correctly identified by: 54% of mothers 40% of fathers & parents were more often correct if shorter ICU stay
perception
www.ajcconline.org AJCC AMERICAN JOURNAL OF CRITICAL CARE, May 2016, Volume 25, No. 3 235
Background More than 55 000 children die annually in the United States, most in neonatal and pediatric intensive care units. Because of the stress and emotional turmoil of the deaths, the children’s parents have difficulty com-prehending information.Objectives To compare parents’ reports and hospital chart data on cause of death and examine agreement on cause of death according to parents’ sex, race, participation in end-of-life decisions, and discussion with physicians; deceased child’s age; unit of care (neonatal or pediatric); and hospital and intensive care unit lengths of stay.Methods A descriptive, correlational design was used with a structured interview of parents 1 month after the death and review of hospital chart data. Parents whose children died in intensive care were recruited from 4 South Florida hospitals and from Florida Department of Health death records. Results Among 230 parents, 54% of mothers and 40% of fathers agreed with the chart cause of death. Agreement did not differ significantly for mothers or fathers by race/ethnicity, participation in end-of-life decisions, discussions with physicians, or mean length of hospital stay. Agree-ment was better for mothers when the stay in the inten-sive care unit was the shortest. Fathers’ agreement with chart data was best when the deceased was an infant and death was in the pediatric intensive care unit. Conclusions Death of a child is a time of high stress when parents’ concentration, hearing, and information process-ing are diminished. Many parents have misconceptions about the cause of the death 1 month after the death. (American Journal of Critical Care. 2016;25:235-242)
CAUSE OF DEATH OF INFANTS AND CHILDREN IN THE INTENSIVE CARE UNIT: PARENTS’ RECALL VS
CHART REVIEWBy Dorothy Brooten, RN, PhD, JoAnne M. Youngblut, RN, PhD, Carmen Caicedo, RN, PhD, Lynn Seagrave, RN, BSN, G. Patricia Cantwell, MD, and Balagangadhar Totapally, MD
by AACN on November 3, 2018http://ajcc.aacnjournals.org/Downloaded from
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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best interest of the patient pain & suffering | analgesia & sedation
financial considerations independent payment | indirect use of healthcare resource
on Gard The United Kingdom Sets Limitson Experimental TreatmentsThe Case of Charlie Gard
ThecaseofCharlieGard in London, England, hasbeenthe focus of international attention, generating polar-izedviewsabout theuseofexperimental treatments.Ononesideare thosewhohold thatpatients shouldbeabletopurchasewhatever treatments theydesireandcanaf-ford; on the other are thosewhomaintain that govern-ments must play a regulatory role in protecting pa-tients fromharmandthatunproventherapiesmustmeeta threshold of scientific validity before they are of-fered, regardless of the ability of the patient to pay.
Charlie Gard is an 11-month-old boy who, accord-ing to court records, “suffers from a rare inherited mi-tochondrial disease called infantile onset encephalo-myopathicmitochondrial DNA depletion syndrome.”1,2
During the several months he has been hospitalized atGreatOrmondStreetHospital his conditionhas steadilydeteriorated, and he is now dependent on life supportandmechanicalventilation.Hisphysiciansbelievehehasno reasonable remaining treatment options, and theyhaverecommendedpalliativecareandwithdrawalof theventilator. Charlie’s parents, however, are asking that
he be transported to the United States, where an un-named US physician has offered to treat Charlie withnucleosides, an experimental treatment that has beenusedona fewchildrenwitha less severe formof thedis-ease caused by a different mutation. The parents haveraisedmore than$1.6million in contributions to fundhistransport and treatment.3
Several experts in various specialties, including pe-diatric intensive care, neurology, andmitochondrial dis-eases, have argued against treating Charlie with thistherapy, pointing out that the treatment has not beentriedonhumansorevenanimalswith themutationcaus-ing Charlie’s disease.1 The US physician acknowledgedinhis testimony thathis recommendationwas theoreti-cal andbasedonvery limitedevidence fromarelatedbutless severeconditioncausedbyadifferentmutation.Af-ter reviewing the records, the physician noted that thedamage to Charlie’s brainwasmore severe than he hadthought. He said that the chances of meaningful brainrecoverywould be small, which he agreed he could notdistinguish fromvanishingly small. He conceded that to
a large extent, if not entirely, the brain damage was ir-reversible. Nevertheless, he concluded that if Charliewere in theUnited States, hewould treat him if thepar-ents so desired and could pay for it: “I would just like tooffer what we can. It is unlikely to work, but the alter-native is that he will pass away.”1
The case has been heard by 3 courts in the UnitedKingdom(theHighCourt,1 theCourtofAppeal,4 and theSupreme Court5) as well as the European Court of Hu-man Rights.6 All of the courts have affirmed the initialruling that palliative care andwithdrawal of life supportare in Charlie’s best interest. In an unusual develop-ment,however,bothPopeFrancisandPresidentDonaldTrumphaveexpressed support for theparents, and theVaticanhasoffered to acceptCharlie “for the time itwilltake for him to live.”7
At least 3 issues are involved in this case that are atthe core of many of the worldwide debates regardinghealth care delivery: the best interest of the patient,financial considerations, and scientific validity. First,the judge in the trial court explained that the law re-
quiredhim tobasehis decision solely onwhat he deemed to be the child’s bestinterest.1 Based on testimony from thephysicians, the judge ruled that contin-ued treatmentwould causeCharlie painand suffering and that, in the absenceofa realistic chance of benefit, continuedtreatmentwouldnot be inCharlie’s bestinterest.1 The problem with this deci-
sion is 2-fold. First, this decision depends on an objec-tive opinion about a subjective phenomenon, namelypain and suffering. Although the clinicians caring forthis child apparently believe that he is experiencingpain and discomfort, his parents disagree and have saidthat they would not be insisting on continued treat-ment if they thought that he was. In addition, medicaltreatments in the intensive care unit are almost alwaysassociated with some degree of discomfort, but inten-sive care unit clinicians arewell trained and equipped toeffectively manage these symptoms. If pain and suffer-ing were the only issue, then an alternative to treat-ment withdrawal would be to use a standard regimenof analgesia and sedation.
Second is the question of whether health care is acommodity thatshouldbedistributedbasedonthepref-erences of patients and their ability to pay, or is a com-munal resource that governmentshaveanobligation toregulate in accord with principles of distributive jus-tice. Advocates of the former view are outraged at theefforts of the hospital to block the parents’ request for
The sad and tragic story of Charlie Gardis a window into several of the deep andfundamental debates that are roilingthe governance of health care deliveryboth domestically and abroad.
Downloaded From: http://jamanetwork.com/ by Roxanne Kirsch on 07/21/2017
... parental vs. medical + legal perception
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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‘everything it takes’
> expectation
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
\
n engl j med
349;12
www.nejm.org september
18, 2003
determinants of ventilator withdrawal
1125
tion Score; the need for inotropes, vasopressors, ordialysis; the physician’s prediction of the patient’slikelihood of survival in the ICU and the hospital(less than 10 percent, 10 to 40 percent, 41 to 60 per-cent, or greater than 60 percent); the physician’sprediction of the patient’s functional and cognitivestatus one month after hospital discharge (will notleave the hospital, will be severely limited, will besomewhat limited, or will be totally independent);and the physician’s perception of the patient’s pref-erences about the use of life support. All the inde-pendent variables were included in the multivariatemodel. Using this model, we identified 300 patientsat relatively high risk for withdrawal of the ventila-tor or death, with a threshold sensitivity of 68.6 per-cent and a specificity of 83.6 percent, a predictedprobability of 0.64, and an area under the receiver-operating-characteristic curve of 0.85. Among these300 patients, 88 (29.3 percent) were successfullyweaned, 105 (35.0 percent) died while receivingmechanical ventilation, and 107 (35.7 percent) hadthe ventilator withdrawn.
For these 300 patients, we conducted Cox pro-portional-hazards regression analysis to identify thedeterminants of physician-initiated withdrawal of
the ventilator. Data on patients who were weanedfrom mechanical ventilation or who died while re-ceiving mechanical ventilation were censored. Theindependent variables were the same base-line fac-tors used in the logistic model, in addition to thenumber of chronic diseases. Other daily variableswere considered in the week preceding withdrawalof mechanical ventilation or death, including indica-tors of the severity of illness (Multiple Organ Dys-function Score, ability to participate in decisions,use of inotropes or vasopressors, and use of hemo-dialysis), factors based on the physician’s clinicaljudgment (prediction of the likelihood of the pa-tient’s survival in the ICU and the hospital — exclud-ing predictions made within 48 hours before thewithdrawal of the ventilator, death, or successfulweaning, prediction of the patient’s functional andcognitive status one month after hospital discharge,and perception of the patient’s preferences about theuse of life support), and geographic factors (center,city, and country). We analyzed each factor in aunivariate model, and we included all factors withP values of less than 0.10 in a multivariate regres-sion, using backward stepwise elimination. We alsotested for two-way interactions and tested the in-
Figure 1. Outcomes among Patients Receiving Mechanical Ventilation Who Were Expected to Remain in the Intensive Care Unit (ICU) for at Least 72 Hours.
Of 851 enrolled patients, 539 were weaned from the ventilator. Of 146 patients who died while receiving mechanical ven-tilation and 166 who had mechanical ventilation withdrawn, 53 and 72 patients had inotropes or vasopressors with-drawn, respectively (P<0.001), and 8 and 18 patients underwent withdrawal of dialysis, respectively (P=0.01). The number of patients who died in the hospital includes the number who died in the ICU.
146 Died while receivingventilation (17.2%)
146 Died in the ICU(100%)
166 Had the ventilatorwithdrawn (19.5%)
145 Died in the ICU(87.3%)
160 Died inthe hospital
(96.4%)
6 Weredischarged
(3.6%)
851 Patients enrolled
539 Were weaned fromthe ventilator (63.3%)
13 Died in the ICU (2.4%)
57 Died in the hospital
(10.6%)
482 Weredischarged
(89.4%)
The New England Journal of Medicine Downloaded from nejm.org on November 5, 2018. For personal use only. No other uses without permission.
Withdrawal of Mechanical Ventilation in Anticipation of Death in the Intensive Care Unit
Deborah Cook, M.D., Graeme Rocker, D.M., John Marshall, M.D., Peter Sjokvist, M.D., Peter Dodek, M.D., Lauren Griffith, M.Sc., Andreas Freitag, M.D., Joseph Varon, M.D., Christine Bradley, M.D., Mitchell Levy, M.D., Simon Finfer, M.D.,
Cindy Hamielec, M.D., Joseph McMullin, M.D., Bruce Weaver, B.Sc., Stephen Walter, Ph.D., and Gordon Guyatt, M.D., for the Level of Care Study
Investigators and the Canadian Critical Care Trials Group
From the Departments of Medicine (D.C.,A.F., C.B., C.H., J.M.) and Clinical Epidemi-ology and Biostatistics (D.C., L.G., B.W.,S.W., G.G.), McMaster University, Hamil-ton, Ont., Canada; the Department of Med-icine, Dalhousie University, Halifax, N.S.,Canada (G.R.); the Department of Surgery,University of Toronto, Toronto (J.M.); theDepartment of Anesthesia and IntensiveCare, Huddinge University, Stockholm, Swe-den (P.S.); the Program of Critical CareMedicine, University of British Columbia,Vancouver, B.C., Canada (P.D.); the Depart-ment of Medicine, Baylor College of Medi-cine, Houston (J.V.); the Department ofMedicine, Brown University, Providence,R.I. (M.L.); and the Intensive Therapy Unit,Royal North Shore Hospital, University ofSydney, Sydney, Australia (S.F.).
In critically ill patients who are receiving mechanical ventilation, the factors associatedwith physicians’ decisions to withdraw ventilation in anticipation of death are unclear.The objective of this study was to examine the clinical determinants that were associatedwith the withdrawal of mechanical ventilation.
methods
We studied adults who were receiving mechanical ventilation in 15 intensive care units,recording base-line physiological characteristics, daily Multiple Organ DysfunctionScores, the patient’s decision-making ability, the type of life support administered, theuse of do-not-resuscitate orders, the physician’s prediction of the patient’s status, andthe physician’s perceptions of the patient’s preferences about the use of life support. Weexamined the relation between these factors and withdrawal of mechanical ventilation,using Cox proportional-hazards regression analysis.
results
Of 851 patients who were receiving mechanical ventilation, 539 (63.3 percent) weresuccessfully weaned, 146 (17.2 percent) died while receiving mechanical ventilation,and 166 (19.5 percent) had mechanical ventilation withdrawn. The need for inotropes orvasopressors was associated with withdrawal of the ventilator (hazard ratio, 1.78; 95 per-cent confidence interval, 1.20 to 2.66; P=0.004), as were the physician’s prediction thatthe patient’s likelihood of survival in the intensive care unit was less than 10 percent (haz-ard ratio, 3.49; 95 percent confidence interval, 1.39 to 8.79; P=0.002), the physician’sprediction that future cognitive function would be severely impaired (hazard ratio, 2.51;95 percent confidence interval, 1.28 to 4.94; P=0.04), and the physician’s perception thatthe patient did not want life support used (hazard ratio, 4.19; 95 percent confidence in-terval, 2.57 to 6.81; P<0.001).
conclusions
Rather than age or the severity of the illness and organ dysfunction, the strongest de-terminants of the withdrawal of ventilation in critically ill patients were the physician’sperception that the patient preferred not to use life support, the physician’s predictionsof a low likelihood of survival in the intensive care unit and a high likelihood of poorcognitive function, and the use of inotropes or vasopressors.
abstract
The New England Journal of Medicine Downloaded from nejm.org on November 5, 2018. For personal use only. No other uses without permission.
6 of the 166 patients undergoing withdrawal of mechanical ventilation survived to hospital discharge [aka physicians can’t tell]
160 (96.4%) didn’t. [you decide]
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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(dis)stress construct
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
\
we are the ‘champions’...
comparison...Study Country Sample RR population mean MDS-R
Dryden-Palmer
2017 Can 1325 ~70% Paediatric ICUNeonatal ICU
8790
Larson+ ‘2014’ Can 218 89% Paediatric ICUNeonatal ICU
102102
Dodek 2016 Can 1390 48% Adult ICU RNAdult ICU MD
8357
Trotochaud 2015 US 869 37% Paed Ward RNPaed Ward MD
6347
Whitehead 2014 US 592 22% Adult ICUPaediatric ward
8957
Karanikola 2013 Italy 566 90% Adult ICU RN 88
Hamric 2012 US 206 48% Adult ICU RNAdult ICU MD
9263
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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the most distressing...
best interest / prolongation of death / passive continuationpoor communucation & false hope
4 www.pccmjournal.org XXX 2017 • Volume XX • Number XXX
items on the scale’s overall reliability. Data were analyzed using STATA version 12.1 (StataCorp, College Station, TX).
RESULTSSite and Sample A total of 219 completed surveys were returned, for a response rate of 89%. Ten were excluded from analysis based on prede-termined exclusion criteria; four respondents had less than 3 months of ICU experience and six had completed the survey
twice. We excluded three surveys with more than three miss-ing MDS-R data points. Of the remaining 206 surveys, 144 were from PICU (14 physicians, 110 nurses, 18 RTs, and two physiotherapists) and 62 were from NICU (six physicians, 49 nurses, and seven RTs). The presence of missing data points was unrelated to profession (three physicians, 18 nurses, and four RTs). Due to the small number of physiotherapists in the sample, they were excluded from analyses examining differ-ences between professions.
Figure 1. Ranked Moral Distress Scale (MDS) items according to factor. Box and whisker plots of each of the 21 items from the Revised MDS (MDS-R), ordered from highest to lowest scoring and broken down into item-specific mean frequency and intensity subscores. Different shadings correspond to the major factor evoking moral distress in each situation. Numbers along the x-axis correspond to MDS-R items ranked in Table 6.
TABLE 2. Situations Reported as Most Morally Distressing by Profession
Situations
Physicians Nurses Respiratory Therapists
Rank
MDS-R Item Score, Median
(IQR) Rank
MDS-R Item Score, Median
(IQR) Rank
MDS-R Item Score, Median
(IQR)
Follow the family’s wishes to continue life support even though I believe that it is not in the best interest of the child.
1 6 (5–10.5) 1 9 (8–12) 1 9 (9–12)
Initiate extensive life-saving actions when I think that they only prolong death.
5 6 (3–8.5) 2 9 (6–12) 2 9 (8–12)
Continue to participate in care for a hopelessly ill child who is being sustained on a ventilator, when no one will make a decision to withdraw support.
3 6 (2–12) 3 8 (4–12) 4 9 (6–12)
Witness diminished patient care quality due to poor team communication.
2 6 (3.5–10.5) 5 6 (3–9) 3 9 (6–12)
Witness healthcare providers giving “false hope” to parents.
6 6 (2.5–8.5) 4 6 (4–9) 6 6 (3–9)
IQR = interquartile range, MDS-R = Revised Moral Distress Scale.Top five highest scoring items from the MDS-R in the overall sample, ranked by profession. Ranks represent the item’s rank out of the scale’s 21 items, within each profession.
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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‘mental anguish as a result of being con-scious of a morally appropriate action, which despite every effort cannot be per-formed owing to organizational or other constraints.” Schulter 2008“the experience of being seriously compromised as a moral agent in practicing in accordance with accepted professional values and standards. .......It is a relational experience shaped by multiple contexts, in-cluding the socio-political and cultural context of the workplace environment”.
moral distress...
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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“when professionals cannot carry out what they believe to be ethically appropri-ate actions because of internal or external constraints.” “experiences of frustration and failure arising from an individual’s struggles to fulfill their moral obligations to patients, families, and the public” Austin 2012
moral distress
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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an ‘experience-based’ construct 1592 registered nurses, 4 nations meta-analysis of nine studies ‘ethical competence’
systematic review: ‘conformist practice’ Goethals et al 2010 ‘The core problem for both doctors and nurses was witnessing suffering, which engendered a moral obligation to reduce that suffering. Uncertainty about the best course of action for the patient and family was a source of moral distress’ Oberle2001
moral accuracy
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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meaning ?
what does MDS(R) mean ? validity, important difference ? ideal ?
Moral Distress Self Report
Yes
No
5
4
3
2
1
<35
35 40 45 50 55 60 65 70 75 80 85 90 95 100
105
110
115
120
125
130
135
140
145
150
155
160
165
170
175
180
strongly agree
strongly disagree
I would say work causes me significant moral distress ...
MDS (R) score
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
Pediatric Critical Care Medicine www.pccmjournal.org S81
for compassion fatigue are limited. In a review of the available compassion fatigue and burnout literature, van Mol et al (5) found that 7.3% of PICU clinicians and 40% of ICU nurses scored high for compassion fatigue on the Professional Quality of Care questionnaire.
The mutable nature of PICU clinician stress opens up opportunity where interventions may facilitate adaptive clini-cian responses thus improving resilience and mitigating other adverse consequences of workplace stressors (1). In contrast to the negatively framed states of moral distress, burnout, and compassion fatigue, resilience may be viewed as enabling healthcare professionals to effectively respond to stressors while optimizing opportunities for personal growth. Resilience is the ability of a person to manifest adaptive coping strategies that are matched to the situation while minimizing stress or distress, or to create personal meaning when circumstances are painful, overwhelming, or unreasonable (23). Resilience exists on a continuum, and resilient individuals are more efficient at resisting work-related stressors that can lead to moral distress, burnout, and depression, thus enabling them to continue to provide high-quality patient care.
We believe that the stressors present in PICU can cre-ate either virtuous and productive or destructive spirals. Virtuous spirals can create individual and team level resilience
that may be enabled by well-selected proactive interven-tions. Destructive spirals may reduce professional effec-tiveness and personal well-being of clinicians and may be “managed” by responsive strategies (4). Resilience in healthcare has been viewed as a process rather than a trait and thus may be cultivated and attained. Cultivating resil-ience is the goal of interven-tions that promote clinician well-being such that stress responses are maintained in the adaptive zone (2, 24).
ACQUIRING AND MAINTAINING CLINICIAN WELL-BEINGInterventions to promote and maintain clinician compe-tence and well-being may be understood as proactive or responsive in nature (Table 1). Responsive interventions are deployed to mitigate adverse consequences after “events,” challenging situations, or
other crises have occurred, whereas proactive interventions are implemented beforehand and intended to increase resilience of the frontline staff for managing future stressors. Here, we focus on stressors related to EOL care. The healthcare community has long recognized the importance of educating practitioners about EOL care (25). The interventions we describe in the con-text of EOL care can also assist when facing other stress-pro-voking phenomena such as difficult disclosures or disrupted relationships and include the domains of self-awareness and care, preparatory and relational skills, empathic presence, and the team approach (26).
PROACTIVE WELL-BEING INTERVENTIONSProactive interventions address self-awareness, self-care, situ-ational awareness, and build competence and confidence in one’s skills to provide EOL care (4). Personal initiatives for sustaining clinician wellness include self-care (e.g., exer-cise, rest, nutrition), self-awareness (e.g., reflective practices, mindfulness, journaling), cultivating emotional wellness (pet therapy) and a spiritual life, valuing relationships, and seek-ing self-education and conscious recognition of the degree of uncertainty inherent in the job (35). Studies of mindfulness interventions have shown decreased depression and anxiety and demonstrated higher empathy measures in mindfulness
Figure 1. The figure describes day-to-day levels of stress in ICU clinicians. Individual level of stress may change overtime and fluctuate between zones reflecting changes in the work environment and in individual disposition. Each black line represents an individual clinician. Shown are examples of some of the possible alter-nate trajectories of provider experience of stress. Dynamic factors such as past stressors, the prevailing work culture, available resources, and resilience of the individual healthcare clinician will affect the day-to-day level of stress and the responses to stressors at different times. Three zones identify differing responses to workplace stressors (behavioral, psychologic, and emotional). Workplace stressors are routinely encountered in pediatric critical care and should elicit responses from clinicians. Ideally, these responses are adaptive and timely actions that resolve (or mitigate) the course of stress (green zone). Underactive responses to workplace stressors (orange zone) may signal disengagement, emotional exhaustion, or withdrawal and may reflect burnout or com-passion fatigue. Overactive responses (red zone) could point toward hypersensitivity, anxiety, and disequilibrium and may reflect moral distress and risks for job departure. Both the overactive and underactive zones reflect conditions of potentially detrimental levels of stress.
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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“It's better to burn out than to fade away.” N Young
I C Uburnout
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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cross-sectional, 198 French ICUs 978 physician respondents, 38% trainees (fellows, interns) 59+/- 12 hours worked / week 24% symptoms of depression 46.5% high degree of burnout
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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higher MBI scoresindependently associated : 1 female sex 2 the number of night shifts per month 3 a longer period of time from the last nonworking week, 4 night shift before the survey (the cause or as done more often?)5 conflict with another colleague intensivist (the cause or effect?)6 conflict with (a) nurse (the cause or effect?)& Protective: relationship quality with chief nurses & nurses
& NOT severity of illness of patient factors, or worked hours.
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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burnout47% French Intensivists Embriaco 2007
30% Paediatric Intensivists Levi 2004
14% Paediatric Intensivists Fields 2005
33% French ICU Nurses Poncet 2007
historical levels ~ versus population level more recent levels higher ...
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
contributing domains: workload > exhaustion - ‘excessive volume’ mismatch vs skill control > accomplishment -limited control over resources to workreward: financial, hardwork over-looked community: degree of connection to othersfairness: persons treated equally + mutual respectvalues : ethical / other things that are important
burnout
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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reflects the stress dimension of burnout alone is insufficient
>> ineffectiveness at work >> prompts individuals to distance (DP)
exhaustion (emo)
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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“Depersonalization is an attempt to put distance between oneself and service recipients by actively ignoring the quali-ties that make them unique and engagin people.”
a consequence of ‘exhaustion’
depersonalization
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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aka Effectiveness
Arises as either [1] consequence of exhaustion and depersonalization if exhausted or depersonalized what is the acomplishment[2] in parallel with Depersonalization and Exhaustion
implied in 2001 review that each domain is needed ...
accomplishment
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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normative 33% | 33% | 33% empiric correlations all three or just one domain ?
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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Residents with High degree of burnout by MBI domain
Modest numbers of individual residents tested, non-significant, but consistent increases across domains > 2months in ICU may increase resident burnout.
Physician fatigue is common, is associated with worse physician well-being and more medical errors than for well-rested clini-
cians, and may compromise patient safety.1–3 Shorter duty hours are purported to address these concerns,4,5 but they necessitate more care transi-tions, which increases the risk of information loss.6,7 The net effect on patient safety therefore depends on the relative balance between fatigue and continuity.8–13 Currently, high-quality data to guide scheduling decisions are limited.
The complexity, acuity and therapeutic inten-sity of patients’ conditions and their care make the intensive care unit (ICU) an ideal environ-ment to evaluate the trade-offs between phys-ician fatigue and continuity. Prior randomized studies have evaluated data for interns14 or intensivists,15 rather than the residents who pro-vide most in-house overnight care in Canadian ICUs.16 We evaluated the impact of 3 com-monly used schedules5 on patient safety and resi dent well-being.
Patient safety, resident well-being and continuity of care with different resident duty schedules in the intensive care unit: a randomized trial
Christopher S. Parshuram MB ChB DPhil, Andre C.K.B. Amaral MD, Niall D. Ferguson MD MSc, G. Ross Baker PhD, Edward E. Etchells MSc MD, Virginia Flintoft BN MSc, John Granton MD, Lorelei Lingard PhD, Haresh Kirpalani BM MSc, Sangeeta Mehta MD, Harvey Moldofsky MD, Damon C. Scales MD PhD, Thomas E. Stewart MD, Andrew R. Willan PhD, Jan O. Friedrich MD DPhil; for the Canadian Critical Care Trials Group
Competing interests: None declared.
This article has been peer reviewed.
Correspondence to: Christopher Parshuram, christopher.parshuram @sickkids.ca
CMAJ 2015. DOI:10.1503 /cmaj.140752
Background: Shorter resident duty periods are increasingly mandated to improve patient safety and physician well-being. However, increases in continuity-related errors may coun-teract the purported benefits of reducing fatigue. We evaluated the effects of 3 resident schedules in the intensive care unit (ICU) on patient safety, resident well-being and continu-ity of care.
Methods: Residents in 2 university-affiliated ICUs were randomly assigned (in 2-month rotation-blocks from January to June 2009) to in-house overnight schedules of 24, 16 or 12 hours. The primary patient outcome was adverse events. The primary resident outcome was sleepiness, measured by the 7-point Stan-ford Sleepiness Scale. Secondary outcomes were patient deaths, preventable adverse events, and residents’ physical symptoms and burnout. Con tinuity of care and perceptions of ICU staff were also assessed.
Results: We evaluated 47 (96%) of 49 resi-dents, all 971 admissions, 5894 patient-days
and 452 staff surveys. We found no effect of schedule (24-, 16- or 12-h shifts) on adverse events (81.3, 76.3 and 78.2 events per 1000 patient-days, respectively; p = 0.7) or on resi-dents’ sleepiness in the daytime (mean rating 2.33, 2.61 and 2.30, respectively; p = 0.3) or at night (mean rating 3.06, 2.73 and 2.42, respectively; p = 0.2). Seven of 8 preventable adverse events occurred with the 12-hour schedule (p = 0.1). Mortality rates were similar for the 3 schedules. Residents’ somatic symp-toms were more severe and more frequent with the 24-hour schedule (p = 0.04); how-ever, burnout was similar across the groups. ICU staff rated residents’ knowledge and deci-sion-making worst with the 16-hour schedule.
Interpretation: Our findings do not support the purported advantages of shorter duty sched-ules. They also highlight the trade-offs between residents’ symptoms and multiple sec-ondary measures of patient safety. Further delineation of this emerging signal is required before widespread system change. Trial regis-tration: ClinicalTrials.gov, no. NCT00679809.
See related commentary, www.cmaj.ca/lookup/doi/10.1503/cmaj.150010
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
2 No difference between ICU schedules but low power to exclude important effect
3 ICU Environment > ICU Schedule 2 months in ICU may increase burnout for sleepiness: working at night > schedule
interpretation
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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1 baseline issue - and definitional issue 2 understand the origins of the problem3 schedule interventions limited effect.... larger scale studies needed :) aka InCURS
4 mitigate moral distress 5 individual mindfulness (trainees/ faculty)6 professional self-respect 7 fatigue risk management (org. mindfulness)
structural interventions?
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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individual effectiveness
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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professionalpersonal
stressorsmitigation
work content
workload
environment/ culture
family
positive relationships
vacation
hobbies
staff support
supervision
reward
recognition
Individual Effects
crashes
circadian rhythm disrupt
sleep deprivation
physical symptoms
debt & exams
schedule?
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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improvement|potential
The SickKids Critical Care Program. Available records show that since 1972, we have cared for 48,626 Patients in the ICU for 277,458 days. Over the decades ICU mortality (grey) has decreased. It was 9-12% in the 70s and 80s and is 4.7% in the ‘current’ era.
Pediatric Critical Care Medicine www.pccmjournal.org S81
for compassion fatigue are limited. In a review of the available compassion fatigue and burnout literature, van Mol et al (5) found that 7.3% of PICU clinicians and 40% of ICU nurses scored high for compassion fatigue on the Professional Quality of Care questionnaire.
The mutable nature of PICU clinician stress opens up opportunity where interventions may facilitate adaptive clini-cian responses thus improving resilience and mitigating other adverse consequences of workplace stressors (1). In contrast to the negatively framed states of moral distress, burnout, and compassion fatigue, resilience may be viewed as enabling healthcare professionals to effectively respond to stressors while optimizing opportunities for personal growth. Resilience is the ability of a person to manifest adaptive coping strategies that are matched to the situation while minimizing stress or distress, or to create personal meaning when circumstances are painful, overwhelming, or unreasonable (23). Resilience exists on a continuum, and resilient individuals are more efficient at resisting work-related stressors that can lead to moral distress, burnout, and depression, thus enabling them to continue to provide high-quality patient care.
We believe that the stressors present in PICU can cre-ate either virtuous and productive or destructive spirals. Virtuous spirals can create individual and team level resilience
that may be enabled by well-selected proactive interven-tions. Destructive spirals may reduce professional effec-tiveness and personal well-being of clinicians and may be “managed” by responsive strategies (4). Resilience in healthcare has been viewed as a process rather than a trait and thus may be cultivated and attained. Cultivating resil-ience is the goal of interven-tions that promote clinician well-being such that stress responses are maintained in the adaptive zone (2, 24).
ACQUIRING AND MAINTAINING CLINICIAN WELL-BEINGInterventions to promote and maintain clinician compe-tence and well-being may be understood as proactive or responsive in nature (Table 1). Responsive interventions are deployed to mitigate adverse consequences after “events,” challenging situations, or
other crises have occurred, whereas proactive interventions are implemented beforehand and intended to increase resilience of the frontline staff for managing future stressors. Here, we focus on stressors related to EOL care. The healthcare community has long recognized the importance of educating practitioners about EOL care (25). The interventions we describe in the con-text of EOL care can also assist when facing other stress-pro-voking phenomena such as difficult disclosures or disrupted relationships and include the domains of self-awareness and care, preparatory and relational skills, empathic presence, and the team approach (26).
PROACTIVE WELL-BEING INTERVENTIONSProactive interventions address self-awareness, self-care, situ-ational awareness, and build competence and confidence in one’s skills to provide EOL care (4). Personal initiatives for sustaining clinician wellness include self-care (e.g., exer-cise, rest, nutrition), self-awareness (e.g., reflective practices, mindfulness, journaling), cultivating emotional wellness (pet therapy) and a spiritual life, valuing relationships, and seek-ing self-education and conscious recognition of the degree of uncertainty inherent in the job (35). Studies of mindfulness interventions have shown decreased depression and anxiety and demonstrated higher empathy measures in mindfulness
Figure 1. The figure describes day-to-day levels of stress in ICU clinicians. Individual level of stress may change overtime and fluctuate between zones reflecting changes in the work environment and in individual disposition. Each black line represents an individual clinician. Shown are examples of some of the possible alter-nate trajectories of provider experience of stress. Dynamic factors such as past stressors, the prevailing work culture, available resources, and resilience of the individual healthcare clinician will affect the day-to-day level of stress and the responses to stressors at different times. Three zones identify differing responses to workplace stressors (behavioral, psychologic, and emotional). Workplace stressors are routinely encountered in pediatric critical care and should elicit responses from clinicians. Ideally, these responses are adaptive and timely actions that resolve (or mitigate) the course of stress (green zone). Underactive responses to workplace stressors (orange zone) may signal disengagement, emotional exhaustion, or withdrawal and may reflect burnout or com-passion fatigue. Overactive responses (red zone) could point toward hypersensitivity, anxiety, and disequilibrium and may reflect moral distress and risks for job departure. Both the overactive and underactive zones reflect conditions of potentially detrimental levels of stress.
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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the
self
high
-5
6486 PDA respiratory quotient pneumnothorax methyliune blue
Christopher S Parshuram MBChB. DPhil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto
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thanks 6486 PDA respiratory quotient pneumnothorax methyliune blue
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