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Original Research: Critical Care |

Physician Staffing Models Impact the Timing of Decisions to Limit Life Support in the ICUICU Physician Staffing Impact on End-of-Life Care FREE TO VIEW

Michael E. Wilson, MD; Ramez Samirat, MD; Murat Yilmaz, MD; Ognjen Gajic, MD, FCCP; Vivek N. Iyer, MD, MPH
Author and Funding Information

From the Department of Internal Medicine (Dr Wilson), Divisions of Pulmonary and Critical Care Medicine (Drs Gajic and Iyer), Department of Internal Medicine, Mayo Clinic, Rochester, MN; Department of Internal Medicine (Dr Samirat), University of Miami Jackson Memorial Hospital, Miami, FL; and the Department of Anesthesiology and Intensive Care (Dr Yilmaz), Akdeniz University, Antalya, Turkey.

Correspondence to: Vivek N. Iyer, MD, MPH, Pulmonary and Critical Care Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: iyer.vivek@mayo.edu


Funding/Support: Financial support for this study was provided by the Mayo Clinic and Mayo Foundation.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2013;143(3):656-663. doi:10.1378/chest.12-1173
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Background:  A growing trend is the implementation of 24-h attending physician coverage in the ICU. Our aim was to measure the impact of 24-h, in-house, attending intensivist coverage on the quality of end-of-life care and the timing of end-of-life decision-making.

Methods:  A retrospective cohort study was conducted of all ICU deaths 6 months before and 6 months after the implementation of mandatory 24-h attending intensivist coverage in a medical ICU. Data relevant to end-of-life care per established consensus recommendations were abstracted from the medical record.

Results:  The following changes were observed after implementation of 24-h intensivist coverage: Time from ICU admission to decision to withdraw mechanical ventilation and time to decision to change to do-not-resuscitate code status both were shortened by 2 days (both P = .03). Quality measures, such as increased family presence around time of death (P = .01) also improved. Other findings, which did not reach statistical significance, included the following: Time to family conference was shortened by 2 days (P = .09), time to decision to limit any life support was shortened by 1 day (P = .08), time to death was shortened by 2 days (P = .08), and intubations against patient wishes decreased (from three to none; P = .12).

Conclusions:  The implementation of mandatory 24-h, in-house, attending intensivist coverage was associated with earlier decision-making across a number of domains related to end-of-life care. Positive trends were noted in quality of end-of-life care as reflected in the presence of family at the time of death.

Decisions to withdraw or withhold life support are routinely made in the ICU when patients, surrogate decision-makers, and the health-care team transition from curative to comfort care.1 The two most important factors influencing such decisions are patient preferences and patient prognosis.2,3 Numerous additional patient-, provider-, and surrogate-related factors impact such decisions and create significant variability in decision-making.46 In an era when up to 20% of all adults die in the ICU and one-third of all health-care dollars in the United States are used in the last year of life, understanding how decisions to limit life support are made and implementing strategies to improve decision-making have been the subjects of continued research.1,710

Additionally, there has been a growing trend and recommendations toward the use of continuous, 24-h, intensivist staffing of ICUs.11 This is typically accomplished by alternating daytime and nighttime intensivist shifts. The impact of adding continuous, attending intensivist coverage in the ICU has been associated with improvement in a number of patient outcomes including decreased hospital length of stay; decreased ICU complication rate; increased staff satisfaction; improvement in a number of evidence-based care processes, such as ventilator bundle compliance; and decreased mortality rates in some care settings.1214

In this single-center study, we sought to measure the impact of intensivist staffing models on decisions to limit life support in the ICU. We hypothesized that the continuous (24-h) presence of an attending intensivist would be associated with improved care at the end of life and improved end-of-life decision-making.

In this retrospective study, we compared the quality of end-of-life care and timing of decisions to limit life support before and after the introduction of a mandatory 24-h presence of an attending intensivist. The Mayo Clinic Institutional Review Board approved the study protocol (IRB Study No. 215005).

We examined the medical records of all patients in the medical ICU who died 6 months before and 6 months after the staffing intervention, which occurred on January 3, 2006, in a single, tertiary care, academic teaching hospital in Rochester, Minnesota. There were 85 deaths in the first study period (before the staffing change) and 65 deaths in the second study period (after the staffing change). No patients met any exclusion criteria, and all patients or their authorized surrogates gave research consent.

Physician Staffing Intervention

A description of our medical ICU and staffing intervention has previously been published.12,13 The study was conducted in a 24-bed medical ICU with an average daily admission rate of seven patients and an average midnight census of 16 patients. Before the change in staffing model, two ICU teams, each led by an attending intensivist formally trained in critical care medicine, provided care during the daytime with alternate admission days and nighttime coverage. Although one ICU fellow and two internal medicine residents provided continuous, in-house, nighttime coverage, attending intensivists on call were available by pager from home and were expected to come to the ICU on demand within 15 to 30 min of being called. The on-call attending intensivist communicated with the in-house critical care fellow via pager and telephone, and decisions regarding the need to see a specific patient before the next morning were based on the severity of illness and the comfort of the house staff in managing the situation. Other factors, such as total ICU acuity and activity, could also influence the nocturnal in-house presence of the attending critical care specialist. Before the intervention, the number of times the attending intensivist would have to come in at night was highly variable and very dependent on ICU occupancy and disease acuity. A rough estimate would be around two to three times per week during the nighttime hours.

The new staffing model was introduced on January 3, 2006, and consisted of an additional, night-shift, attending intensivist who was present in-house in the ICU to attend to all patient care needs between 7:00 PM and 7:00 AM. The nighttime intensivist functioned in a manner similar to the daytime attending intensivist, including the performance of independent physical examinations, critical care resuscitation, review of the medical database, review of the plan of care, supervision of all invasive procedures, and trainee education. The duration and content of nighttime rounds was left to the discretion of the individual intensivist, but typically involved formal nighttime rounds with the resident/fellow team and the ICU charge nurse. The schedule of the night-shift attending critical care intensivist consisted of three, four, or seven consecutive, 12-h, night shifts as chosen by the individual intensivist. For each 12-h night shift covered, the attending intensivist was given a compensatory day off free from all medical duties. In addition to attending to new admissions, the nighttime intensivist, along with the critical care team (residents and fellow), would also undertake regular bedside rounds on all patients in the ICU to monitor progress and make necessary changes in the plan of care. Multidisciplinary ICU rounds also occurred every morning during both periods and were staffed by the daytime intensivist, who came in at 7:00 AM. Standardized order sets were available for short- and long-term sedation, ventilator management, electrolyte replacement, and sepsis management. No other major practice-model interventions occurred during the study period.

Outcome Variables

Quality of end-of-life care was measured according to previously published consensus recommendations.15,16 Four main domains were studied: patient- and family-centered decision-making, communication, spiritual support, and symptom management. The timing of the following events in decision-making to limit life support was also measured: family conference, code status change to do-not-resuscitate (DNR), decision to withdraw and/or withhold life support, documentation of comfort care orders, and death. Both before and after the intervention, data regarding timing of end-of-life events were abstracted from the medical record for dates and times of specific orders. There were no changes in the manner of recording or abstracting data between the two study time periods.

Statistical Analysis

Paired Student t tests, Wilcoxon rank-sum test, and χ2 test were used as appropriate for univariate comparisons before and after the staffing intervention. Statistical analysis was performed with JMP software version 9.0.1 (SAS Institute Inc) and reviewed by a statistician.

Of 150 eligible deaths, 85 occurred before the staffing intervention and 65 occurred after the staffing intervention. Table 1 shows the demographic characteristics of all patients. There were no significant differences in severity of illness or other baseline characteristics before and after the intervention.

Table Graphic Jump Location
Table 1 —Comparison of Demographic Characteristics 6 mo Before and 6 mo After the Staffing-Model Intervention

Data given as No. (%) unless otherwise indicated. APACHE = Acute Physiology and Chronic Health Evaluation; DNR = do not resuscitate; IQR = interquartile range.

Table 2 shows the mode of death. In both study periods, documentation showed that 18 patients (12%) died after unsuccessful CPR, 18 patients (12%) died in the setting of full support without terminal CPR, and 105 patients (70%) died after a decision to withdraw and/or withhold life support. For nine patients (6%), the mode of death was unclear from the medical record. There were no significant differences in the mode of death before and after the physician-staffing intervention.

Table Graphic Jump Location
Table 2 —Withdrawal or Withholding of Life Support

Data given as No. (%) unless otherwise indicated. NPPV = noninvasive positive-pressure ventilation; TPN = total parenteral nutrition.

Table 3 shows the timing of specific decisions regarding limiting life support. After the study intervention, the time from ICU admission and decision to withdraw mechanical ventilation was shortened by 2 days (P = .03) and time to decision to change to a DNR code status was shortened by 2 days (P = .03). Trends toward quicker family conferences and decisions to withdraw/withhold any life support were also noted but did not reach statistical significance. For the 105 patients (70%) for whom life support was limited, the median time to death was 4 days before the intervention and 2 days after the intervention; this finding was not statistically significant (P = .08) (Table 3). For all 150 patients who were studied, the median ICU length of stay was 2 days for both study periods (Table 1). In a cohort of patients, all of whom died in the ICU, the ICU length of stay should equal the time to death. The reason why the time to death reported in Table 3 was the same (2 days) as or longer (4 days) than the ICU length of stay (2 days) was because the 30% of patients in whom life support was not withdrawn and/or withheld had shorter ICU stays.

Table Graphic Jump Location
Table 3 —Number of Days Between ICU Admission and Decision-Making to Limit Life Support in Those Patients in Whom Life Support Was Limited

Data given as median (IQR) unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Two-sided Student t test.

Quality measures of end-of-life care abstracted from the medical record are shown in Table 4.1719 At the time of ICU admission, a minority of patients had a living will (31%) or durable power of attorney for health care (23%) scanned into the electronic medical record. Family members were present at 131 of 150 deaths (88%), and this increased from 82% to 95% (P = .01) after the staffing intervention. It was documented that 71% of patients received spiritual support. Sixty-seven percent of patients had comfort care orders placed prior to death and 25% of patients had successful or unsuccessful CPR in the 24 h prior to death. There was > 90% documentation of pain, shortness of breath, and agitation assessments. Documentation of pain assessment was present in 99% of patients before the staffing intervention and 94% of patients after the staffing intervention (P = .04). In the 24 h prior to death, pain was present in 29 patients (19%), shortness of breath was present in 108 patients (72%), and agitation was present in 13 patients (9%). Continuous analgesia and sedation were used in 76% and 50% of patients, respectively. Before the staffing intervention, three unresponsive patients were intubated against their known wishes, whereas no such incident occurred after the staffing intervention (P = .12).

Table Graphic Jump Location
Table 4 —Quality Measures of Death Using the Electronic Medical Record

Data given as No. (%) unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Pain was defined as either a pain rating of ≥3 on a 0-10 numeric pain intensity scale or a Face, Legs, Activity, Cry, and Consolability (FLACC) score ≥5.17

b 

Shortness of breath was defined as subjective nursing assessment of shortness of breath.

c 

Agitation was defined as a Richmond Agitation-Sedation Scale score ≥+2.18

d 

Confusion was defined as Confusion Assessment Method for the ICU positive.19

This single-center study suggests that the key steps in decisions to limit life support occurred earlier with the continuous (24-h) presence of an attending intensivist. These steps included earlier decisions to withdraw mechanical ventilation and changing to DNR code status. Quality end-of-life measures, such as increased family presence around time of death, also improved after the staffing change.

There are several possible explanations for the observed efficiency in decision-making after the staffing intervention. One reason may be that physician communication with surrogate decision-makers occurred earlier in the ICU course and in a more effective manner. Patients and families often seek an in-charge physician/physician leader when discussing end-of-life care issues, and direct communication with the attending physician rather than with housestaff or nurses is viewed positively by patients and family members.20 Although not statistically significant, there was a trend toward increased documentation of physician communication with surrogate decision-makers in the first 24 h of ICU admission before and after the intervention (66%-77%, P = .14) (Table 4). Other studies have similarly shown that communication strategies lead to quicker and better decision-making to limit life support.9,2126 Additionally, there is a growing body of evidence that resident physicians may lack the skills and training necessary to have effective conversations about life support decisions.2729 Leading an effective discussion with the patient and family about complex end-of-life issues requires skill and experience.30 Thus, the presence of an experienced attending intensivist overnight is a likely explanation for quicker and improved family communication, support, and decision-making. Another reason might be related to the fact that the night intensivist performed a number of critical care services overnight (documentation, billing, invasive procedures, etc.). This likely “unloaded” the daytime intensivist, thus allowing that physician to focus more on the patient/family and end-of-life care issues that do often require considerable time and personnel resources.

In addition to quicker decision-making, this study also indicates that documentation of two domains of quality of end-of-life care showed modest, clinically relevant improvement after the staffing intervention: increased family presence at patient death (from 82% to 95%, P = .01) and decreased rate of intubation against stated patient preferences (from three instances to none, P = .12). Although not statistically significant, we feel that reduction of unwanted intubations from three to none is a clinically notable finding and may have been the result of intensivist intervention. Improvements in family presence and adherence to patients’ life support preferences again may be attributable to improved communication and decision-making by an experienced intensivist.

The other markers of quality of end-of-life care that were measured did not show improvement after the addition of a nighttime attending intensivist. In our institution, many of these markers of quality, such as documentation of pain, agitation, dyspnea, and so forth, are the responsibility of nursing staff. Other markers of quality of care are routinely offered to patients and families regardless of physician presence (eg, spiritual support). Similarly, other markers of quality, such as presence of a living will or durable power of attorney for health care in the medical chart, are usually not directly affected by the ICU medical team during acute critical illness. Thus, the addition of an experienced attending intensivist overnight may not directly influence these markers of quality currently measurable in the medical chart.

Our study has several limitations. This is a single-center study from a tertiary care, academic medical center and the findings of this study may not generalize to other geographic regions and practice settings. The implementation of physician staffing-model changes in other institutions with different models of ICU care delivery may have a different impact on end-of-life decision-making. Additionally, there is significant variability in end-of-life decision-making based on country, region of country, religion, and family involvement.4 Traditionally, patient autonomy is considered to be very important in the United States and Canada, whereas some European and Asian countries tend to be more paternalistic in end-of-life decision-making.31,32 An additional source of variability likely lies at the level of the practice patterns of the individual intensivist concerning end-of-life care and the time allocated to it vs other ICU commitments. This variability, however, likely did not change between the two study periods given that the same intensivists staffed the ICU during both periods. Being a retrospective study, it is possible that other variables could have influenced outcomes, although no other major changes were made during the study period in terms of nurse staffing or change in practice model in the ICU. In addition, the ability of the medical record to capture the quality of end-of-life care is somewhat limited. Of the seven accepted end-of-life care domains measurable from the medical chart, only partial assessment of four domains was possible in this study.16 Documentation, especially in physician admission and progress notes, of life-support decision-making and the quality of end-of-life care is suboptimal. This finding has been noted before,3335 and highlights the need to improve documentation of such practices for clinical and research purposes.36,37 Another limitation of our study is that we did not measure satisfaction with end-of-life care delivery among members of the critical care team or resource utilization. While faster decision-making to limit life support has been used as a measure for higher quality decision-making,10 other measures of high-quality decisions, such as decision anxiety, decision accuracy, and decision regret, were unable to be measured in this retrospective study.38 Another limitation is the use of multiple comparisons, which likely increased the likelihood of a type 1 error.

Strengths of our study include the closed nature of our ICU (both before and after the study intervention) with the intensivist having complete and primary responsibility for the patient. A closed ICU during both time periods eliminated a potential source of confounding and variation.39 No other staffing or data-recording changes besides the study intervention occurred during the study period. Specifically, the nurse-patient ratio, which has been associated with end-of-life decision variability,40 remained the same during the study period. An additional strength of our study includes the comprehensive use of electronic medical records, including electronic availability of physician notes, patient code status, and nursing documentation.

Considerable emphasis is being placed on the creation of accountable care organizations and high-value health-care enterprises.41 The ICU accounts for a majority of health-care expenditures in the hospital setting and also accounts for a large proportion of hospital-based deaths.1,42 Almost 28% of health-care expenditures occur in the last year of life.7,8 In this changing paradigm of accountability and high-value care, special emphasis needs to be placed on further understanding care delivery at the end-of-life.43

The introduction of mandatory, 24-h ICU coverage by an attending intensivist was associated with earlier decision-making to withdraw mechanical ventilation and change to DNR orders as well as improved quality of death as evidenced by increased family presence. Other metrics such as time to family conference, time to decision to limit any life support, time to death, and intubations against patient wishes showed positive trends, but did not reach statistical significance. Further research and better training of all critical care providers in discussing preferences for life-support interventions are needed to optimize end-of-life care and prevent negative consequences of both prolonged dying and premature death.

Author contributions: Drs Wilson and Iyer had full access to all of the data and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Wilson: contributed to the study design, data and statistical analysis, and manuscript preparation and served as principal author.

Dr Samirat: contributed to study design, data analysis, and manuscript revision.

Dr Yilmaz: contributed to study design, data analysis, and manuscript revision.

Dr Gajic: contributed to the study design, data analysis, and manuscript preparation.

Dr Iyer: contributed to the study design, data and statistical analysis, and manuscript preparation.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The sponsors had no role in the design of the study, collection and analysis of the data, or preparation of the manuscript.

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Figures

Tables

Table Graphic Jump Location
Table 1 —Comparison of Demographic Characteristics 6 mo Before and 6 mo After the Staffing-Model Intervention

Data given as No. (%) unless otherwise indicated. APACHE = Acute Physiology and Chronic Health Evaluation; DNR = do not resuscitate; IQR = interquartile range.

Table Graphic Jump Location
Table 2 —Withdrawal or Withholding of Life Support

Data given as No. (%) unless otherwise indicated. NPPV = noninvasive positive-pressure ventilation; TPN = total parenteral nutrition.

Table Graphic Jump Location
Table 3 —Number of Days Between ICU Admission and Decision-Making to Limit Life Support in Those Patients in Whom Life Support Was Limited

Data given as median (IQR) unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Two-sided Student t test.

Table Graphic Jump Location
Table 4 —Quality Measures of Death Using the Electronic Medical Record

Data given as No. (%) unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Pain was defined as either a pain rating of ≥3 on a 0-10 numeric pain intensity scale or a Face, Legs, Activity, Cry, and Consolability (FLACC) score ≥5.17

b 

Shortness of breath was defined as subjective nursing assessment of shortness of breath.

c 

Agitation was defined as a Richmond Agitation-Sedation Scale score ≥+2.18

d 

Confusion was defined as Confusion Assessment Method for the ICU positive.19

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