Simulation-based operations testing in new neonatal healthcare environments.

In situ simulations, those conducted in the actual clinical environment, confer a high level of contextual fidelity and have been applied to the operations testing of new healthcare environments (HCE) to identify potential threats to patient, family and staff safety. By conducting simulation-based operations testing, these latent safety threats (LSTs) - which are weaknesses in communications, human factors, system process and technologies, and the way they are linked together - can be identified and corrected prior to moving patients into the new HCE. Simulation-based operations testing has extended to the neonatal HCE, as neonatal intensive care units (NICUs) transition from open-bay to single-family room design. In this section, we define LSTs, review simulation-based operations testing in new neonatal and perinatal HCEs, review challenges associated with conducting simulation-based operations testing, and briefly review pre-construction simulation-based user-centered design of new HCEs.

Qualitative analysis of latent safety threats uncovered by in situ simulation-based operations testing before moving into a single-family-room neonatal intensive care unit.

OBJECTIVES: We aimed to identify: (a) latent safety threats (LSTs) in a new neonatal intensive care unit (NICU) through simulation-based pre-occupancy operations testing, and (b) LSTs that remained unresolved 1-year post-occupancy. STUDY DESIGN: In this qualitative study, 111 healthcare professionals participated in patient care simulations and debriefings in a new NICU. Debriefing transcripts were inductively analyzed to characterize LSTs. Unresolved LSTs were identified 1 year after NICU occupancy. RESULTS: Thematic saturation was attained after analysis of nine debriefings. Four major themes affecting staff function and patient safety emerged from 305 threats: relay of information, workplace design, patient care processes, and patient family and staff focus. One-year post occupancy, 29 (9%) LSTs remained unresolved. CONCLUSION: Team debriefings of simulated patient events uncover LSTs that can largely be resolved before transitioning patient care into a new NICU. Understanding how LSTs interact provides a platform to develop viable strategies to mitigate patient safety risks.

Necrotizing Enterocolitis and Spontaneous Intestinal Perforation: A Spatiotemporal Case Cluster Analysis.

OBJECTIVE: To expand existing statistical methods to identify clusters of necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) cases in the neonatal intensive care unit. METHODS: In an academic, tertiary referral center, possible NEC or SIP clusters were identified using a binomial distribution scan test. The incidence-density rate (IDR) was calculated as the number of cases per 1,000 patient-days during each possible cluster and compared with the baseline IDR. A structured chart review compared cluster and noncluster cases. Spatial clustering analyzed the physical distribution of cases using the Grimson Test. Repeat analysis included only SIP cases. RESULT: The initial scan identified 3 suspected temporal clusters. IDR comparison confirmed only 1 cluster. Analysis of SIP only cases revealed similar results. Physical proximity was not a significant factor. Chart review of the SIP and NEC cases revealed significant increases during the confirmed cluster of small for gestational age infant births and indomethacin treatment. Chart review of the SIP only cases in the confirmed cluster revealed no significant differences. CONCLUSION: Statistical methods distinguish whether suspected case clusters represent a significant increase in baseline incidence. True clusters warrant detailed investigation including spatial analysis and chart review. This approach may have application in other disease processes and populations.

Sustained Improvement in Neonatal Intensive Care Unit Safety Attitudes After Teamwork Training.

OBJECTIVES: This study aimed to measure safety attitudes in the neonatal intensive care unit (NICU) before and serially after a compulsory, multidisciplinary teamwork and communication training initiative and novel sustainment program. METHODS: Training was administered to NICU staff and subsequent sustainment efforts were directed at enculturating core principles over the following year. A modified Agency for Healthcare Research and Quality Survey on Patient Safety Culture was administered before as well as 3 and 12 months after training. Longitudinal survey results were compared with the national Agency for Healthcare Research and Quality survey data. RESULTS: Ninety-six percent of 350 NICU staff were trained over 2 months. Survey response rates were 84%, 71%, and 83% before, at 3 months, and at 12 months after training, respectively. Items with sustained improvement pertained to staff empowerment and patient hand-offs. The proportion of participants who agreed with the statement, "Staff feel free to question the decisions or actions of those with more authority" increased from 55% to 76% and 83% at 3 and 12 months, respectively (P < 0.0001). The proportion of participants who disagreed with the statement, "Things 'fall between the cracks' when transferring patients from one unit to another" increased from 36% to 48% and 52% at 3 and 12 months, respectively (P < 0.01). The only significant decline was for the statement, "We are actively doing things to improve patient safety." The proportion of respondents who agreed dropped from 93% to 83% at 3 months (P = 0.02). CONCLUSIONS: A novel sustainment program after teamwork and communication training measurably improved most staff safety attitudes over 1 year.

Ensemble-based methods for forecasting census in hospital units.

BACKGROUND: The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. METHODS: In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. RESULTS: Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. CONCLUSIONS: Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts.

A medical simulation-based educational intervention for emergency medicine residents in neonatal resuscitation.

OBJECTIVES: The objective was to determine if a medical simulation-based neonatal resuscitation educational intervention is a more effective teaching method than the current emergency medicine (EM) curriculum at one 4-year EM residency program. METHODS: A prospective, randomized study of second-, third-, and fourth-year EM residents was performed. Of 36 potential subjects, 27 residents were enrolled. Each resident was assessed at baseline and after the intervention using 1) a questionnaire to evaluate confidence in leading adult, pediatric, and neonatal resuscitation and prior neonatal resuscitation experience and 2) a neonatal resuscitation simulation scenario in which each participant was the code leader to evaluate knowledge and skills. Assessments were digitally recorded and reviewed independently by two Neonatal Resuscitation Program (NRP) instructors using a validated neonatal resuscitation scoring tool. Controls (15 participants) received the current EM curriculum. The intervention group (12 participants) experienced an educational session, which incorporated didactics, skills station, and medical simulation about neonatal resuscitation. Outcomes measured included changes in overall neonatal resuscitation score, number of critical actions, time to initial steps of neonatal resuscitation, and changes in confidence level leading neonatal resuscitation. RESULTS: Baseline neonatal resuscitation scores were similar for the control and intervention groups. At the final assessment, the intervention group's neonatal resuscitation score improved (p = 0.016) and the control group's score did not. The intervention group performed 2.31 more critical actions overall and the time to achieve warming (p = 0.0002), drying (p < 0.0001), tactile stimulation (p = 0.002), and placing a hat on the patient (p <0.0001) were also improved compared to controls. At the baseline assessment, 80% of the control group and 75% of the intervention group reported being "not at all confident" in leading neonatal resuscitation. At the final assessment, the proportion of residents who were "not at all confident" leading neonatal resuscitation decreased to 35% in the intervention group compared to 67% of the control group. The majority of the intervention group (65%) reported an increased level of confidence in leading neonatal resuscitation. CONCLUSIONS: Medical simulation can be an effective tool to assess the knowledge and skills of EM residents in neonatal resuscitation. Our simulation-based educational intervention significantly improved EM residents' knowledge and performance of the critical initial steps in neonatal resuscitation. A medical simulation-based educational intervention may be used to improve EM residents' knowledge and performance with neonatal resuscitation.

Transportable enhanced simulation technologies for pre-implementation limited operations testing: neonatal intensive care unit.

INTRODUCTION: Transition of a Neonatal Intensive Care Unit (NICU) to a new physical plant incurs many challenges. These are amplified when the culture of care is changing from traditional cohort-based care to the single-family room model. Altered healthcare delivery systems can be tested in situ with TESTPILOT: Transportable Enhanced Simulation Technologies for Pre-Implementation Limited Operations Testing. The aims of the study included promoting translation of existing processes and identifying staff orientation material. We hypothesized that (1) numerous process gaps would be discovered and resolved, and (2) participants would feel better prepared. METHODS: A functional neonatal intensive care unit was modeled before its opening. Scenarios were developed, volunteers recruited, and rooms supplied with equipment. Participants performed usual duties in two 30-minute in situ simulations followed by facilitated debriefings. As latent safety hazards were identified, they were corrected and retested in subsequent simulations. Staff was surveyed for perceived preparedness. RESULTS: Ninety-six multidisciplinary participants identified 164 latent safety hazards in verbal and written communication, facilities, supplies, staffing, and training, 93% of which were resolved at transition. Staff preparedness varied but showed improving communication, workflow patterns, and awareness of equipment and supply locations. The majority stated that this simulation experience changed their practice. CONCLUSIONS: Simulation is very effective for identifying process gaps before major institutional change. TESTPILOT generated iterative workflow enhancements and staff orientation toward improving patient care at transition and beyond. The extensive coordination required to implement such large-scale simulations is well worth the benefit for systems refinement and patient safety.

Testing with simulation before a big move at Women & Infants Hospital.

Simulation can identify process gaps prior to major institutional change. NICU staff found simulation very beneficial for facilities orientation; the majority of providers considered patient safety enhanced by scenario-based training. TESTPILOT identified problems that could not have been identified by committees. This information improved processes and was used to tailor staff training workshops, all of which led to better preparedness and patient safety. The impact has been recognized as so beneficial that we are now collaborating with the Rhode Island Hospital Medical Simulation Center to build a simulation facility at Women & Infants Hospital.