Serious complications are common during the intensive care of postoperative cardiac surgery patients.1 Some of these complications may be influenced by communication during the process of handover of care from the operating room to the intensive care unit (ICU) team.1–3 Failure to transfer essential information during ad hoc transfer of care is common.1,3–14 A structured transfer of care process may reduce the rate of communication errors and perioperative complications.6 The aviation, nuclear, and oil industries have been compared with the medical industry in which transfer of information is crucial and errors can have devastating consequences.6,15,16 A standardized, easy to follow and train protocol may help facilitate effective communication and teamwork. Few earlier studies have demonstrated outcome improvements after standardized handover processes in select populations. Agarwal et al4 reported a reduction in complications and an increase in early extubations along with staff satisfaction and improved quality of data transfer in more than 1000 pediatric cardiac surgical patients.
We therefore hypothesized that a collaborative, comprehensive, structured handover of care from the intraoperative team to the ICU team would be associated with a decrease in a specific set of postoperative complications in adult cardiac surgery patients. We tested this hypothesis by developing and introducing a comprehensive multidisciplinary transfer of care process and then measuring patient outcomes before and after the intervention using a linkage between 2 care databases: an Anesthesia Information Management System (AIMS) and a critical care complication registry database (CRD).
Production pressures, stress related to complicated cases, increased workload, distractions, communication issues, and poor standardization can all lead to increased time needed for handover and poor handover quality.1,2,5,8,17 Therefore, we also assessed the time taken to accomplish transfer of care before and after our intervention.
We hypothesized that the time needed for handover would not add a substantial burden to the process.
The IRB at Oregon Health & Science University approved this study and waived the requirement for written informed consent for this database review. The setting was a cardiac surgical ICU in an academic quaternary care facility. Inspired by provider concerns about patient safety following ad hoc transfer of care, a team of intraoperative nurses, critical care nurses, anesthesiologists, intensivists, and cardiac surgeons developed a structured process for transfer of care. Each subgroup identified specific barriers to continuous excellent care, and interventions were designed to circumvent these barriers. A scripted handover template that could be readily taught and used by members of the handover teams was developed during multiple multidisciplinary meetings, with discussion and thought as to the most important data and information that need to be conveyed during the handover process. Having multidisciplinary input into the development of our handover process helped to ensure that we addressed the major needs of all teams involved in the complex transfer of care scenario. An ideal script limits mandatory reporting of unimportant information while simultaneously allowing flexibility to add vital unanticipated data. An example of the handover template is provided (See Supplemental Digital Content, Supplemental Material, http://links.lww.com/AA/B703).
In April 2009, we introduced the structured transfer of care process with comprehensive education of all involved teams. Specific components of the new process included use of clinical information systems to give advance warning about significant intraoperative issues starting at induction, and additional notification to the ICU team near the end of the case. We used a scripted, verbal handover process from intraoperative providers to the ICU team at the time of patient arrival, including verbal acknowledgement using closed-loop communication of the formal transfer of care (“My patient is now your patient,” “Our patient”).
Anesthesia transport and report time was defined as the total time elapsed between 2 time markers recorded in the AIMS for every case. “Patient out of room” is recorded immediately before pushing the bed out of the room and “anesthesia end” is recorded at the conclusion of provider handover in the ICU, at the bedside.
Postoperative data including information on intensive care complications were obtained from our own CRD, in use since 2007. This CRD records complications, length of stay, age, date of birth, sex, name, medical record number, surgeon, surgery type, and date of surgery. It is housed on a physically and electronically secure server and is used daily for rounding and weekly for morbidity and mortality conferences. The daily use includes updating patient information including complications. Every patient who is admitted to the ICU is entered into the database, and if the patient suffers a complication of care, this is recorded with both categorical and narrative data. Use of relational database architecture to store these data allows rapid analysis for trainees, as well as long-term quantification and retrospective analysis. Because this database was intended for quality improvement, and not for research, we performed 2 analyses of the quality of data in the CRD. First, we manually verified through audit of all cases that demographic information was identical in both the CRD (hand-entered at the time of ICU admission) and the AIMS (demographic information hand-entered at the time of surgical scheduling) with the AIMS data considered to be the “gold standard,” because AIMS records all operative cases. To assess the quality of complication registry in the CRD, we performed a mortality verification analysis to ensure accuracy with respect to at least one verifiable serious complication. We verified all deaths recorded during the study period in the CRD against a list of all in-ICU deaths recorded in the hospital clinical information system during the same period.
We used custom-developed software written in Python (Python.org Amsterdam, the Netherlands) to match each intraoperative record by demographic and date information with its respective postoperative CRD record. The resulting data set was manually verified for accuracy of matching before analysis.
Complications were prospectively defined as part of the CRD design, resulting in a list of 26 possible complications (Table 1). Preventable and serious complications (Table 2) were defined by a group of cardiac surgical intensivists before data analysis, using a collaborative process and broad categorical definitions. The consensus for “preventable” complications was for those that were most clearly defined and thought to be reduced by an improvement in the handover process. Complications defined as “preventable” were so chosen if it was believed that transfer of operative or preoperative information at the time of handover could significantly decrease the probability of the complication. For example, iatrogenic pneumothorax was included as a preventable complication because we believe this could be prevented by leaving the chest tubes on suction if a significant air leak was noted during surgery, or if there remained concern about possible lung injury during central line placement. Complications were defined as “serious” if they inevitably or nearly inevitably were associated with new organ failure. Our goal was to identify complications that were clearly defined and have a reduced incidence by an improved transfer of care process. Complications such as acute renal failure and myocardial infarction were more difficult to define in our database and not thought to have a major reduction by improving transfer of care by consensus. The primary outcome is whether a patient had a preventable complication during the study period. All records in the CRD during the period of analysis were reviewed for completeness. Complications were defined as occurring within 24 hours if they were recorded as having taken place on postoperative day 0 or 1.
Baseline and outcome data were analyzed using Stata 13.0 (StataCorp, College Station, TX). Complications were categorized based on type, severity, and timing (within 24 or 48 hours of admission or later). For the available demographic information, means and SDs were calculated for continuous variables (age and length of stay in the ICU) and proportions were calculated for the categorical variable (sex) for patients in the preintervention and postintervention periods. Demographic variables were compared between the preintervention and postintervention time period using a 2-tailed t test for continuous variables and a χ2 test for categorical variables. Univariable logistic regression models were built for the outcomes of preventable complications, preventable complications in the first 24 hours after surgery, and preventable complications in the first 48 hours after surgery. For each of the 3 models, potential confounding variables were added to the multivariable model and assessed for statistical significance (P < .05). Those that were statistically significant and those determined a priori to be important to the outcome were retained. Bonferroni correction for multiple comparisons was used to infer statistical significance with P < .017 (0.05/3) considered statistically significant.
There were no ethical conflicts identified for this study because the aim of the intervention was quality improvement. The authors have all disclosed no conflicts of interest.
We analyzed preintervention and postintervention data over a 3-year period in this retrospective cohort study. We included all adult patients (n = 1127, 550 before and 577 after the intervention) who underwent cardiac surgery at Oregon Health and Science University during the study period (October 1, 2007, to September 30, 2010, 18 months before and after the intervention). We excluded patients who had serious complications in the ICU before their first operation (n = 44), who were under the age of 18 (n = 8), or who had unrecoverable missing data for points of analysis (sex n = 10, age n = 9). There were a total of 71 patients excluded from analysis. Data were collected from 2 primary sources: intraoperative data were retrieved from the institutional source (AIMS), and ICU course data were retrieved from a locally developed, preexisting CRD. Concordance between the AIMS and the CRD regarding demographic information for these admissions was >99%. All deaths of study patients, which were recorded in the hospital clinical information system, were also recorded in the CRD, for a concordance of 100%.
Baseline characteristics are shown in Table 3. Patients in the postintervention group were significantly younger (60.91 ± 15.33) compared with patients in the preintervention group (63.38 ± 14.10; P = .0055). There were significantly more ventricular assist device implantations in the after-intervention group (10 vs 51; P < .001). There was no overall difference in total cardiopulmonary bypass times between the 2 groups.
There were 1127 total postoperative cardiac surgery admissions during the study period: 550 before and 577 after the intervention. There were 384 complications during the study period: 166 before and 198 after the intervention (P = .154). There were 29 preventable complications before the intervention, and 11 preventable complications after the intervention (P = .023) (Table 4). There was no statistically significant difference in serious complications before (61) or after the intervention (55) (Table 5).
In the univariable logistic regression, the postintervention group was overall less likely to suffer from a preventable complication (odds ratio [OR] 0.35; 98.3% confidence interval [CI], 0.15–0.82; P = .003). There was no statistically significant difference between the preintervention and postintervention groups looking at only preventable complications occurring in the first 24 hours after surgery (OR 0.39; 98.3% CI, 0.13–1.14; P = .035) or the first 48 hours after surgery (OR 0.39; 98.3% CI, 0.14–1.09; P = .028).
When adjusted for age and sex, the postintervention group was less likely to have a preventable complication compared with the preintervention group (OR adjusted [adj] 0.35; 98.3% CI, 0.15–0.84; P = .004). Preventable complications occurring in the first 24 hours after surgery (OR adj 0.39; 98.3% CI, 0.13–1.15; P = .037) and preventable complications occurring 48 hours after surgery (OR adj 0.40; 98.3% CI, 0.14–1.10; P = .031) remained nonstatistically significant in the adjusted models (Table 6).
In a subset of 1085 patients (432 preintervention and 653 postintervention) with complete data on out-of-operating room time and anesthesia end time, anesthesiologist transfer of care time was 17.77 ± 9.19 minutes before the intervention and 19.21 ± 9.59 minutes after the intervention; P= .0132.
The main finding of this investigation is that following introduction of a collaborative, comprehensive transfer of care process from the operating room to the ICU, patients suffered fewer preventable complications. We used novel methodology to generate these data: linkage between an AIMS and an ICU complication registry with custom software.
Our intervention was motivated by desire to improve patient safety. We hypothesized that collaborative, comprehensive transfer of care would reduce complications. There was no difference in total number of complications between the groups during the study period. Accordingly, we found that, compared with before the intervention, postintervention patients were less likely to suffer a preventable complication within 24 and 48 hours after cardiac surgery. The OR for this effect was similar across all 3 time periods at approximately 0.4. Older patients were less likely to benefit from our intervention than younger patients (OR 0.7; CI, 0.2–2.3 for 65+ year olds versus 0.4; CI, 0.04–2.2 for patients 45–54 years old). This suggests that comprehensive transfer of care may be associated with greater benefit to younger patients, who may have fewer comorbidities, or who may simply be vulnerable to early complications for a shorter period of time.
Although time to transfer of care was increased in the postintervention group, the increment of 2 minutes was small and would be unlikely to significantly affect operating room flow. Since the comprehensive process we introduced was designed to deliver all significant information with regularity, it is possible that the increased time to transfer care is part of the explanation for the improvement in patient outcome. During this study period, there was no change in patient transport or anesthesiology documentation, which could potentially confound our results. An increased transfer of care time has not been shown in other studies.3,6,7,18 We suggest that anesthesiologists and the ICU teams are more likely to adapt a transfer of care process such as ours if it does not greatly increase workload while improving communication and patient outcome.
The comprehensive handover process requires the presence of all key team members from surgery, ICU nursing, and anesthesiology, resulting in one thorough handover addressing all team members’ input and concerns. During the transition from the operating room to the ICU, patient monitoring and important information must be safely and efficiently transferred.1,2,9,13,19,20 In some settings, handover may begin before all team members are ready.8 This also may further empower hierarchical structures, which limit benefits of a structured transfer of care process. A standardized handover process may help diminish distractions and place equal value on all team members, which may allow their questions to be answered without fear of repercussions.3,8
A checklist approach may have limited success if it does not foster teamwork and effectively convey important information.6,18 A large study of surgical safety checklists in Ontario, Canada did not show significant reductions in mortality or complications.16,21 It is important to note that our development and implementation involved training sessions, practices during implementation, and feedback. We changed how information was delivered, who was present, and what tasks were being performed during sign-out and by whom. In our institution, after verification of the monitors being transferred to the patient, with the patient in a stable/safe period for care transfer, the primary nurse responsible for the patient is able to direct full attention to care transfer while other nurses are caring for the patient during this brief time. The quality of information conveyed is also an important consideration; there could be instances where too much information is conveyed or pertinent information is not clearly transferred.9,22,23 An ideal script limits mandatory reporting of unimportant information while simultaneously allowing flexibility to add vital unanticipated data.
Our study has several limitations, inherent to retrospective observational studies. Data acquisition in the CRD is by voluntary reporting and may be subject to reporting bias. We attempted to limit the effect of this bias by testing whether patient admissions were faithfully captured and by verifying the reporting of a single highly verifiable complication: death. Near misses and errors that did not result in harm to the patient were not collected. During the implementation of the transfer of care process, there was education for the intraoperative teams and ICU teams regarding the entire process of transfer of care and the handover template. Education is an important part of implementation of a new process and may have had an effect not directly related to the handover template. This study may also be limited by an improvement in efficiency and care during the study period. Surgical advancement in technique or procedures, as well as standardized improvement in ICU care, may have had an influence on outcomes. Our study was limited to 3 years duration, without major changes in case volume (other than an increased number of ventricular assist devices in the postintervention group) or operating surgeons, making advancement in health care unlikely to influence our results. A key limitation in this study is the lack of analysis of patient comorbidities. The data set was limited and incomplete in relation to comorbidities and not carried into analysis.
There were more patients who underwent ventricular assist device placement procedures in the after intervention group. The evolution of left ventricular assist devices has increased the number of end-stage heart failure patients in the cardiac surgical ICU when, previously, these patients would be treated with optimal medical therapy.24 We feel this group of patients is at high risk for postoperative complications. Changes and advances in technology require education and familiarization to ensure patient safety.25 A standardized transfer of care process has the potential to identify educational and implementation needs for changes in technology.
We chose to measure adverse events as a measure of transfer of care efficacy; however, there may be other factors of care that can influence these events and may not be related to the handover process. We did not evaluate adherence to the comprehensive care transfer process. Adherence to a transfer of care process has not been well studied in the literature, although 1 study showed a decrease in compliance over time in a pediatric cardiac surgery population. A high satisfaction with the transfer of care process has been noted previously and is thought to be essential to adherence to a new process. Our study is also limited in this regard, although anecdotally we observed overall satisfaction of surgical, nursing, anesthesiology, and ICU team members as noted by others.3,4,6,9,12 The reduction in complications appears to remain sustained at least through the study period (Figure 1).
In this before-and-after retrospective study of 1127 postoperative cardiac surgery patients, a structured transfer of care process was associated with a reduction in preventable complications despite an increase in ventricular assist device placement procedures, and a small but statistically significant increase in anesthesiologist time to transfer care. We feel a comprehensive multidisciplinary approach to development and implementation of the transfer of care process is key to success, and further studies are necessary for validation of improved patient safety.
Name: Michael Hall, MD.
Contribution: This author is the first author and corresponding author; this author was involved in study design and data collection.
Name: Jamie Robertson, PhD.
Contribution: This author is the contributing author; this author was involved in statistical analysis.
Name: Matthias Merkel, MD, PhD.
Contribution: This author is the contributing author.
Name: Michael Aziz, MD.
Contribution: This author is the contributing author.
Name: Michael Hutchens, MD.
Contribution: This author is the senior author; this author was involved in study design, statistical analysis, and data collection.
This manuscript was handled by: Richard C. Prielipp, MD.
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