Intensivist Staffing: Evolving Challenges and Solutions

Patient Outcomes and Unit Composition With Transition to a High-Intensity ICU Staffing Model: A Before-and-After Study

Provider staffing models for ICUs are generally based on pragmatic necessities and historical norms at individual institutions. A better understanding of the role that provider staffing models play in determining patient outcomes and optimizing use of ICU resources is needed.

OBJECTIVES

To explore the impact of transitioning from a low- to high-intensity intensivist staffing model on patient outcomes and unit composition.

DESIGN SETTING AND PARTICIPANTS

This was a prospective observational before-and-after study of adult ICU patients admitted to a single community hospital ICU before (October 2016-May 2017) and after (June 2017-November 2017) the transition to a high-intensity ICU staffing model.

MAIN OUTCOMES AND MEASURES

The primary outcome was 30-day all-cause mortality. Secondary outcomes included in-hospital mortality, ICU length of stay (LOS), and unit composition characteristics including type (e.g., medical, surgical) and purpose (ICU-specific intervention vs close monitoring only) of admission.

RESULTS

For the primary outcome, 1,219 subjects were included (779 low-intensity, 440 high-intensity). In multivariable analysis, the transition to a high-intensity staffing model was not associated with a decrease in 30-day (odds ratio [OR], 0.90; 95% CI, 0.61-1.34; p = 0.62) or in-hospital (OR, 0.89; 95% CI, 0.57-1.38; p = 0.60) mortality, nor ICU LOS. However, the proportion of patients admitted to the ICU without an ICU-specific need did decrease under the high-intensity staffing model (27.2% low-intensity to 17.5% high-intensity; p < 0.001).

CONCLUSIONS AND RELEVANCE

Multivariable analysis showed no association between transition to a high-intensity ICU staffing model and mortality or LOS outcomes; however, the proportion of patients admitted without an ICU-specific need decreased under the high-intensity model. Further research is needed to determine whether a high-intensity staffing model may lead to more efficient ICU bed usage.

Characteristics of Pulmonary Critical Care Medicine and Pulmonary Medicine Applicants and Fellowships

Background: Little is known about historical and recent application trends for pulmonary critical care medicine (PCCM) or pulmonary medicine (PM) fellowship programs. Describing trends in and characteristics of PCCM and PM applications, applicants, and fellowship programs can help program directors and medical educators understand trainees’ interest in and application patterns for these fellowship programs.

Objective: The objective of this study was to use National Residency Match Program data to assess recent trends in PCCM and PM fellowship applications and compare characteristics of applicants and fellowship programs.

Methods: In 2019, we used National Residency Match Program data to evaluate applicant ranking and matching in PCCM and PM fellowship programs and to compare applicant and fellowship program characteristics.

Results: From 2008 through 2019, the majority of applicants (59.1%) matched into PCCM were graduates of U.S. allopathic or osteopathic medical schools, whereas 87% of PM fellows were non-U.S. graduates. PCCM was the preferred specialty for 90.8% of matched applicants versus only 31.6% of matched PM applicants (P < 0.001). The match rate for PCCM applicants was 67.2% versus 23.8% for PM applicants (P < 0.001). Of PCCM applicants, 36.6% matched into their top choice versus 10.8% of PM applicants (P < 0.001). There are far fewer PM fellowship positions (n = 23) and programs (n = 12) than PCCM positions (n = 450) and programs (n = 131). The mean fill rates from the 2004 through 2016 appointment years are 94.1% in PCCM and 97.4% in PM (P = 0.009).

Conclusion: PCCM is a prevailing specialty choice over PM among residency graduates, with matched applicants more likely to list PCCM than PM as their preferred specialty. Further exploration into applicants’ interest in critical care compared with PM may prove beneficial in guiding applicants to programs that will best meet their career goals.

Quantification of critical care medicine: An ICU survey

BACKGROUND

The shortage in intensivist workforce has been long recognized but no solution has been identified. Meanwhile, fellowships in pulmonary and critical care medicine (PCCM) are expanding, other critical care medicine (CCM) programs are contracting. No explanation exists for this contradictory trend, although understanding contributory factors may lead to a solution for the shortage. The fundamental difference between PCCM and other CCM programs lies in the residency training of trainees. We tested the hypothesis that the nature of CCM practice determines its attractiveness to potential candidates.

METHODS

A questionnaire-based survey was administered recording all daily activities in four different kinds of ICUs at two teaching hospitals one was public, and one was private. Activities were categorized into conventional CCM, respiratory, medical, and surgical interventions.

RESULTS

The average daily census was 17.6 ± 6.6. Across two MICU, one trauma/surgical and one cardiothoracic ICU the average daily activity ranged from 152 to 203 of these CCM formed 27%-36%, respiratory 10%-13%, medical 43%-59%, and surgical 1%-15%. The combination of medical and respiratory interventions represented >50% of daily activities among all the ICUs.

CONCLUSIONS

Quantitative description of ICU activities indicates that the majority of the ICU daily practice relies on medical and respiratory interventions, which may explain why PCCM remains popular.

The Intensive Care Unit Perspective of Becoming a Level I Trauma Center: Challenges of Strategy, Leadership, and Operations Management

The primary purpose of this narrative is to elucidate the numerous significant changes that occur at the intensive care unit (ICU) level as a medical center pursues becoming a Level I trauma center. Specifically, we will focus on the following important areas: (1) leadership and strategy issues behind the decision to move forward with becoming a trauma center; (2) preparation needed to take a highly functioning surgical ICU and align it for the inevitable changes that happen as trauma go-live occurs; (3) intensivist staffing changes; (4) roles for and training of advanced practice practitioners; (5) graduate medical education issues; (6) optimizing interactions with closely related services; (7) nursing, staffing, and training issues; (8) bed allocation issues; and (9) reconciling the advantages of a “unified adult critical care service” with the realities of the central relationship between trauma and surgical critical care.

Clinical and Economic Outcomes of Telemedicine Programs in the Intensive Care Unit: A Systematic Review and Meta-Analysis

Objective:

To evaluate the impact of telemedicine programs in intensive care unit (Tele-ICU) on ICU or hospital mortality or ICU or hospital length of stay and to summarize available data on implementation cost of Tele-ICU.

Methods:

Controlled trails or observational studies assessing outcomes of interest were identified by searching 7 electronic databases from inception to July 2016 and related journals and conference literatures between 2000 and 2016. Two reviewers independently screened searched records, extracted data, and assessed the quality of included studies. Random-effect models were applied to meta-analyses and sensitivity analysis.

Results:

Nineteen of 1035 records fulfilled the inclusion criteria. The pooled effects demonstrated that Tele-ICU programs were associated with reductions in ICU mortality (15 studies; risk ratio [RR], 0.83; 95% confidence interval [CI], 0.72 to 0.96; P = .01), hospital mortality (13 studies; RR, 0.74; 95% CIs, 0.58 to 0.96; P = .02), and ICU length of stay (9 studies; mean difference [MD], −0.63; 95% CI, −0.28 to 0.17; P = .007). However, there is no significant association between the reduction in hospital length of stay and Tele-ICU programs. Summary data concerning costs suggested approximately US$50 000 to US$100 000 per Tele-ICU bed was required to implement Tele-ICU programs for the first year. Hospital costs of US$2600 reduction to US$5600 increase per patient were estimated using Tele-ICU programs.

Conclusions:

This systematic review and meta-analysis provided limited evidence that Tele-ICU approaches may reduce the ICU and hospital mortality, shorten the ICU length of stay, but have no significant effect in hospital length of stay. Implementation of Tele-ICU programs substantially costs and its long-term cost-effectiveness is still unclear.

Simulation of a Novel Schedule for Intensivist Staffing to Improve Continuity of Patient Care and Reduce Physician Burnout

OBJECTIVE

Despite widespread adoption of in-house call for ICU attendings, there is a paucity of research on optimal scheduling of intensivists to provide continuous on-site coverage. Overnight call duties have traditionally been added onto 7 days of continuous daytime clinical service. We designed an alternative ICU staffing model to increase continuity of attending physician care for patients while also decreasing interruptions to attendings' nonclinical weeks.

DESIGN

Computer-based simulation of a 1-year schedule.

SETTING

A simulated ICU divided into two daytime teams each covered by a different attending and both covered by one overnight on-call attending.

SUBJECTS

Simulated patients were randomly admitted on different service days to assess continuity of care.

INTERVENTIONS

A "shared service schedule" was compared to a standard "7 days on schedule." For the 7 days on schedule, an attending covered a team for 7 consecutive days and off-service attendings cross-covered each night. For the shared schedule, four attendings shared the majority of daytime and nighttime service for two teams over 2 weeks, with recovery periods built into the scheduled service time.

MEASUREMENTS AND MAIN RESULTS

Continuity of care as measured by the Continuity of Attending Physician Index increased by 9% with the shared schedule. Annually, the shared service schedule was predicted to increase free weekends by 3.4 full weekends and 1.3 weekends with either Saturday or Sunday off. Full weeks without clinical obligations increased by 4 weeks. Mean time between clinical obligations increased by 5.8 days.

CONCLUSIONS

A shared service schedule is predicted to improve continuity of care while increasing free weekends and continuity of uninterrupted nonclinical weeks for attendings. Computer-based simulation allows assessment of benefits and tradeoffs of the alternative schedule without disturbing existing clinical systems.