Descripción de las herramientas de comunicación utilizadas en el área quirúrgica y la perspectiva de los instrumentadores quirúrgicos / Description of communication tools practices in the surgical area and the perspective of surgical instrumenters

La comunicación efectiva dentro de las organizaciones es uno de los factores más importantes para lograr un trabajo positivo y eficaz. Se realizó una investigación cuyo objetivo fue identificar y describir las herramientas de comunicación en el área de Quirófano Central del Hospital Italiano de Buenos Aires y las distintas perspectivas de los instrumentadores quirúrgicos respecto de su utilización. Métodos: se realizó un estudio de corte transversal con un componente de observación participativa de los medios de comunicación y una encuesta a los instrumentadores quirúrgicos de la institución. Resultados: se identificaron ocho tipos de herramientas de comunicación en el área quirúrgica. El correo electrónico (e-mail) como herramienta de comunicación es muy utilizado según los instrumentadores quirúrgicos, pero estos sugirieron otras herramientas más directas, como reuniones y capacitaciones solas o en combinación para determinados tipos de información. Conclusiones: los instrumentadores quirúrgicos utilizan una amplia gama de medios de comunicación en el área quirúrgica. La distribución de preferencias según el tipo de información indica que la elección de estos medios debería ser personalizada. (AU)

Effective communication within organizations is one of the most important factors to achieve a positive and effective work. An investigation was carried out and its objective was to identify and describe the communication tools in the surgical area of the Hospital Italiano de Buenos Aires and the different perspectives of the surgical nurses regarding its use. Methods: a cross-sectional study was carried out with a component of participative observation of the communication tools and a survey of the surgical nurses of the institution. Results: eight types of communication tools were identified in the surgical area. The implementation of email as a communication tool is widely used by surgical nurses, but they suggested other more direct tools such as meetings and training sessions alone or in combination for certain types of information. Conclusions: Surgical nurses use a wide range of communication tools in the surgical area. The distribution of preferences according to the type of information indicates that the choice of these tools should be personalized. (AU)

Analysis of operating theatre utilisation to drive efficiency and productivity improvements.

There is an urgent need in the acute health system to use resources as efficiently as possible. One such group of resources are operating theatres, which have an important impact on patient flow through a hospital. Data-driven insights into the use of operating theatres can suggest improvements to minimise wastage and improve theatre availability. In this paper, a short extract of surgical data from participating Queensland public hospitals was statistically analysed to examine the effects of session type, session specialty, scheduling the longest case first and day of the week on theatre utilisation. It was found that day-long sessions (as opposed to separate morning or afternoon sessions), mid-week sessions, certain specialties (eg. neurosurgery sessions) and not doing the longest case first were most beneficial to theatre utilisation. Awareness of these findings is important in any redesign activity aimed at improving flow performance.

Explanation for the near-constant mean time remaining in surgical cases exceeding their estimated duration, necessary for appropriate display on electronic white boards.

BACKGROUND: Consider a case that has been ongoing for longer than the scheduled duration. The anesthesiologist estimates that there is 1 hour remaining. Forty-five minutes later the case has not yet finished, and closure has not yet started. We showed previously that the mean (expected) time remaining is approximately 1 hour, not 15 minutes. The relationship is a direct mathematical consequence of the log-normal probability distributions of operating room (OR) case durations. We test the hypothesis that, with an accurate probabilistic model, until closure begins the estimated mean time remaining would be the mean time from the start of closure to OR exit. METHODS: Among the 311,940 OR cases in a 7-year time series from 1 hospital, there were 3962 cases for which (1) there had been previously at least 30 cases of the same combination of scheduled procedure(s), surgeon, and type of anesthetic and (2) the actual OR time exceeded the 0.9 quantile of case duration before the case started. A Bayesian statistical method was used to calculate the mean (expected) minutes remaining in the case at the 0.9 quantile. The estimate was compared with the actual minutes from the time of the start of closure until the patient exited the OR. RESULTS: The mean ± standard error of the pairwise difference was 0.2 ± 0.4 minutes. The Bayesian estimate for the 0.9 quantile was exceeded by 10.2% ± 0.01% of cases (i.e., very close to the desired 10.0% rate). CONCLUSIONS: If a case is taking longer than the expected (scheduled) duration, closure has not yet started, and someone in the OR is asked how much time the case likely has remaining, the value recorded on a clipboard for viewing later should be the estimated time remaining (e.g., "1 hour") not an end time (e.g., "5:15 pm"). Electronic whiteboard displays should not show that the estimated time remaining in the case is less than the mean time from start of closure to OR exit. Similarly, if closure has started, the expected time remaining that is displayed should not be longer than the mean time from closure to OR exit. Finally, our results match previous reports that, before a case starts, statistical methods can reliably be used to assist in decisions involving the longest amount of time that cases may take (e.g., conflict checking for resources, filling holes in the OR schedule, and preventing holes in the schedule).

Analysis of variance of communication latencies in anesthesia: comparing means of multiple log-normal distributions.

Anesthesiologists rely on communication over periods of minutes. The analysis of latencies between when messages are sent and responses obtained is an essential component of practical and regulatory assessment of clinical and managerial decision-support systems. Latency data including times for anesthesia providers to respond to messages have moderate (> n = 20) sample sizes, large coefficients of variation (e.g., 0.60 to 2.50), and heterogeneous coefficients of variation among groups. Highly inaccurate results are obtained both by performing analysis of variance (ANOVA) in the time scale or by performing it in the log scale and then taking the exponential of the result. To overcome these difficulties, one can perform calculation of P values and confidence intervals for mean latencies based on log-normal distributions using generalized pivotal methods. In addition, fixed-effects 2-way ANOVAs can be extended to the comparison of means of log-normal distributions. Pivotal inference does not assume that the coefficients of variation of the studied log-normal distributions are the same, and can be used to assess the proportional effects of 2 factors and their interaction. Latency data can also include a human behavioral component (e.g., complete other activity first), resulting in a bimodal distribution in the log-domain (i.e., a mixture of distributions). An ANOVA can be performed on a homogeneous segment of the data, followed by a single group analysis applied to all or portions of the data using a robust method, insensitive to the probability distribution.

The effect of hospital size and surgical service on case cancellation in elective surgery: results from a prospective multicenter study.

BACKGROUND: Short-term case cancellation causes frustration for anesthesiologists, surgeons, and patients and leads to suboptimal use of operating room (OR) resources. In many facilities, >10% of all cases are cancelled on the day of surgery, thereby causing major problems for OR management and anesthesia departments. The effect of hospital type and service type on case cancellation rate is unclear. METHODS: In 25 hospitals of different types (university hospitals, large community hospitals, and mid- to small-size community hospitals) we studied all elective surgical cases of the following subspecialties over a period of 2 weeks: general surgery, trauma/orthopedics, urology, and gynecology. Case cancellation was defined as any patient who had been scheduled to be operated on the next day, but cancelled after the finalization of the OR plan on the day before surgery. A list of possible cancellation reasons was provided for standardized documentation. RESULTS: A total of 6009 anesthesia cases of 82 different anesthesia services were recorded during the study period. Services in university hospitals had cancellation rates 2.23 (95% confidence interval [CI] = 1.49 to 3.34) times higher than mid- to small-size community hospitals 12.4% (95% CI = 11.0% to 13.8%) versus 5.0% (95% CI = 4.0% to 6.2%). Of the surgical services, general surgical services had a significantly (1.78, 95% CI = 1.25 to 2.53) higher cancellation rate than did gynecology services-11.0% (95% CI = 9.7% to 12.5%) versus 6.6% (95% CI = 5.1% to 8.4%). CONCLUSIONS: When benchmarking cancellation rates among hospitals, comparisons should control for academic institutions having higher incidences of case cancellation than nonacademic hospitals and general surgery services having higher incidences than other services.

Evaluation of a mandatory quality assurance data capture in anesthesia: a secure electronic system to capture quality assurance information linked to an automated anesthesia record.

BACKGROUND: Efforts to assure high-quality, safe, clinical care depend upon capturing information about near-miss and adverse outcome events. Inconsistent or unreliable information capture, especially for infrequent events, compromises attempts to analyze events in quantitative terms, understand their implications, and assess corrective efforts. To enhance reporting, we developed a secure, electronic, mandatory system for reporting quality assurance data linked to our electronic anesthesia record. METHODS: We used the capabilities of our anesthesia information management system (AIMS) in conjunction with internally developed, secure, intranet-based, Web application software. The application is implemented with a backend allowing robust data storage, retrieval, data analysis, and reporting capabilities. We customized a feature within the AIMS software to create a hard stop in the documentation workflow before the end of anesthesia care time stamp for every case. The software forces the anesthesia provider to access the separate quality assurance data collection program, which provides a checklist for targeted clinical events and a free text option. After completing the event collection program, the software automatically returns the clinician to the AIMS to finalize the anesthesia record. RESULTS: The number of events captured by the departmental quality assurance office increased by 92% (95% confidence interval [CI] 60.4%-130%) after system implementation. The major contributor to this increase was the new electronic system. This increase has been sustained over the initial 12 full months after implementation. Under our reporting criteria, the overall rate of clinical events reported by any method was 471 events out of 55,382 cases or 0.85% (95% CI 0.78% to 0.93%). The new system collected 67% of these events (95% confidence interval 63%-71%). CONCLUSION: We demonstrate the implementation in an academic anesthesia department of a secure clinical event reporting system linked to an AIMS. The system enforces entry of quality assurance information (either no clinical event or notification of a clinical event). System implementation resulted in capturing nearly twice the number of events at a relatively steady case load.

Surgeons' and anesthesiologists' perceptions of turnover times.

BACKGROUND: Perception of turnovers may be influenced less by actual turnover times per se than by a mental model of factors influencing turnover times. METHODS: A survey was performed at a U.S. academic hospital in 2010. Each of the 78 subjects estimated characteristics of his/her turnover times in 2009. Responses were compared with the actual times. RESULTS: Numbers of comments were not proportional to actual total waiting times experienced. Surgeons with 2 or more comments (n = 10) averaged the same numbers of turnovers as did surgeons who made 1 or no comments (n = 13) (P = 0.62). Four of the 10 surgeons with 2 or more comments averaged <2 turnovers per month ("very few turnovers"). Perceptions of turnover times were influenced by opinion about team activity during shift change. Most (>79%) subjects thought that the time of the day with the subject's largest number of prolonged (>45 minutes) turnovers was at least 2 hours later than actual (P < 0.0001). Although most prolonged turnovers occurred around noon, 8 surgeons mentioned shift change qualitatively, and most (68%, P = 0.002) subjects estimated a time overlapping with shift change. Surgeons overall overestimated their observed percentage of prolonged turnovers (P = 0.020), and anesthesiologists' estimates were overall unbiased. Surgeons' bias cannot be explained by knowing times of a longer interval such as "skin to skin," because the other surgeons, with very few turnovers, had responses that were essentially identical (P ≥ 0.87). When we corrected for each subject's actual mean turnover time, surgeons' estimates for their averages were longer than were anesthesiologists' estimates (P = 0.002). Responses were again essentially indistinguishable from those of subjects with very few turnovers (P ≥ 0.23). CONCLUSIONS: Managers should not rely on surgeons or anesthesiologists for their expert judgment on turnover times. Managers should also not interpret comments about turnover times as literally referring to the time, but instead as factors perceived as contributing to the time (e.g., attitude about the facility and the activity of its personnel).

The design and implementation of an automated system for logging clinical experiences using an anesthesia information management system.

BACKGROUND: Residents in anesthesia training programs throughout the world are required to document their clinical cases to help ensure that they receive adequate training. Current systems involve self-reporting, are subject to delayed updates and misreported data, and do not provide a practicable method of validation. Anesthesia information management systems (AIMS) are being used increasingly in training programs and are a logical source for verifiable documentation. We hypothesized that case logs generated automatically from an AIMS would be sufficiently accurate to replace the current manual process. We based our analysis on the data reporting requirements of the American College of Graduate Medical Education (ACGME). METHODS: We conducted a systematic review of ACGME requirements and our AIMS record, and made modifications after identifying data element and attribution issues. We studied 2 methods (parsing of free text procedure descriptions and CPT4 procedure code mapping) to automatically determine ACGME case categories and generated AIMS-based case logs and compared these to assignments made by manual inspection of the anesthesia records. We also assessed under- and overreporting of cases entered manually by our residents into the ACGME website. RESULTS: The parsing and mapping methods assigned cases to a majority of the ACGME categories with accuracies of 95% and 97%, respectively, as compared with determinations made by 2 residents and 1 attending who manually reviewed all procedure descriptions. Comparison of AIMS-based case logs with reports from the ACGME Resident Case Log System website showed that >50% of residents either underreported or overreported their total case counts by at least 5%. CONCLUSION: The AIMS database is a source of contemporaneous documentation of resident experience that can be queried to generate valid, verifiable case logs. The extent of AIMS adoption by academic anesthesia departments should encourage accreditation organizations to support uploading of AIMS-based case log files to improve accuracy and to decrease the clerical burden on anesthesia residents.

Can you feel IT coming? Though adoption of anesthesiology information systems is still low, their use is rising, and will continue as ARRA approaches.

Anesthesia information management systems have high satisfaction ratings, but there are holes in functionality, and interfaces are difficult. The market for these systems is still immature. Opportunities can be realized in billing and charge capture. Anesthesiologist face a complex OR environment and don't want to be burdened. Use of an AIMS can protect the anesthesiologist from liability. AIMS can be used to improve patterns of care.

Numbers of simultaneous turnovers calculated from anesthesia or operating room information management system data.

BACKGROUND: More personnel are needed to turn over operating rooms (ORs) promptly when there are more simultaneous turnovers. Anesthesia and/or OR information management system data can be analyzed statistically to quantify simultaneous turnovers to evaluate whether to add an additional turnover team. METHODS: Data collected for each case at a six OR facility were room, date of surgery, time of patient entry into the OR, and time of patient exit from the OR. The number of simultaneous turnovers was calculated for each 1 min of 122 4-wk periods. Our end point was the reduction in the daily minutes of simultaneous turnovers exceeding the number of teams caused by the addition of a team. RESULTS: Increasing from two turnover teams to three teams reduced the mean daily minutes of simultaneous turnovers exceeding the numbers of teams by 19 min. The ratio of 19 min to 8 h valued the time of extra personnel as 4.0% of the time of OR staff, surgeons, and anesthesia providers. Validity was suggested by other methods of analyses also suggesting staffing for three simultaneous turnovers. Discrete-event simulation showed that the reduction in daily minutes of turnover times from the addition of a team would likely match or exceed the reduction in the daily minutes of simultaneous turnovers exceeding the numbers of teams. Confidence intervals for daily minutes of turnover times achieved by increasing from two to three teams were calculated using successive 4-wk periods. The distribution was sufficiently close to normal that accurate confidence intervals could be calculated using Student's t distribution (Lilliefors' test P = 0.58). Analysis generally should use 13 4-wk periods as increasing the number of periods from 6 to 13 significantly reduced the coefficient of variation of the averages but not increasing the number of periods from 6 to 9 or from 9 to 13. CONCLUSION: The number of simultaneous turnovers can be calculated for each 1 min over 1 yr. The reduction in the daily minutes of simultaneous turnovers exceeding the number of teams achieved by the addition of a turnover team can be averaged over the year's 13 4-wk periods to provide insight as to the value (or not) of adding an additional team.

The use of distributed displays of operating room video when real-time occupancy status was available.

INTRODUCTION: On the day of surgery, real-time information of both room occupancy and activities within the operating room (OR) is needed for management of staff, equipment, and unexpected events. METHODS: A status display system showed color OR video with controllable image quality and showed times that patients entered and exited each OR (obtained automatically). The system was installed and its use was studied in a 6-OR trauma suite and at four locations in a 19-OR tertiary suite. Trauma staff were surveyed for their perceptions of the system. RESULTS: Evidence of staff acceptance of distributed OR video included its operational use for >3 yr in the two suites, with no administrative complaints. Individuals of all job categories used the video. Anesthesiologists were the most frequent users for more than half of the days (95% confidence interval [CI] >50%) in the tertiary ORs. The OR charge nurses accessed the video mostly early in the day when the OR occupancy was high. In comparison (P < 0.001), anesthesiologists accessed it mostly at the end of the workday when occupancy was declining and few cases were starting. Of all 30-min periods during which the video was accessed in the trauma suite, many accesses (95% CI >42%) occurred in periods with no cases starting or ending (i.e., the video was used during the middle of cases). The three stated reasons for using video that had median surveyed responses of "very useful" were "to see if cases are finished," "to see if a room is ready," and "to see when cases are about to finish." CONCLUSIONS: Our nurses and physicians both accepted and used distributed OR video as it provided useful information, regardless of whether real-time display of milestones was available (e.g., through anesthesia information system data).

Estimating the incidence of prolonged turnover times and delays by time of day.

BACKGROUND: Prolonged turnover times cause frustration and can thereby reduce professional satisfaction and the workload surgeons bring to a hospital. METHODS: The authors analyzed 1 yr of operating room information system data from two academic, tertiary hospitals and Monte-Carlo simulations of a 15-operating room hospital surgical suite. RESULTS: Confidence interval widths for the mean turnover times at the hospitals were negligible when compared with the variation in sample mean turnover times among 31 hospitals. The authors developed a statistical method to estimate the proportion of all turnovers that were prolonged (> 15 min beyond mean) and that occurred during specified hours of the day. Confidence intervals for the proportions corrected for the effect of multiple comparisons. Statistical assumptions were satisfied at the two studied hospitals. The confidence intervals achieved family-wise type I error rates accurate to within 0.5% when applied to between five and nineteen 4-week periods of data. The diurnal pattern in the proportions of all turnovers that were prolonged provided different, more managerially relevant information than the time course throughout the day in the percentage of turnovers at each hour that were prolonged. CONCLUSIONS: Benchmarking sample mean turnover times among hospitals, without the use of confidence intervals, can be valid and useful. The authors successfully developed and validated a statistical method to estimate the percentage of turnover times at a surgical suite that are prolonged and occur at specified times of the day. Managers can target their quality improvement efforts on times of the day with the largest percentages of prolonged turnovers.

Improving operating room performance in a center of excellence.

The financial success of centers of excellence typically depends on effective utilization of the OR. Therefore, it's important to align the strategy, structure, information and reporting systems, culture, and behavior of both entities. Moving from management based on anecdote to a data-driven process can enhance the quality of decision-making.

[Possibilities in improving patients's turn-over coordination in the OR of an University Hospital]. / Möglichkeiten zur Ablaufoptimierung im OP - Prozessanalyse der Wechselzeiten in einem OP der Maximalversorgung.

An efficient Operating Room (OR) management might increase the cost-effectiveness of an OR. For this purpose, we have evaluated the coordination and the times of the solitary processes that are involved in the patient turnover. The mean time between skin suture of the preceding patient and incision of the following patient (SI-time) was, depending on the type of operation, between 44 and 78 minutes. Mean empty-room time (ERT) was 7 minutes. SI-times depended on various factors, including the times necessary to discharge the preceding patient from the OR and the times necessary for induction of anesthesia or for preparation of the OR. Altogether, our data provide evidence for the fact, that optimisation of the patients turnover can decrease SI-times between 10-15 minutes. Although this period appears too short to reliably allow an additional scheduled operation during regular working hours, an improved coordination may result in reduced overtimes of the OR-staff and thus should increase staff satisfaction.

The use of an interactive computerized daily schedule in a busy interventional radiology practice increases efficiency.

PURPOSE: The effect on efficiency of patient care in a busy academic interventional radiology practice was studied by the analysis of procedure times both before and after the implementation of a computerized interactive daily schedule. Procedure start and end times were retrospectively collected from the department's quality assurance database for two identical 6-month periods, representing the time before and after the deployment of the software. The delay in the start of the first case, the time between cases, and the time required to complete each day's work were compared for the two periods. RESULTS: The average time of delay between cases was reduced after the implementation of the software (p < 0.025). More total cases were performed during the period of time after the implementation of the software, resulting in a greater work relative value unit production. Although the average number of cases performed per day was greater after the software was in use (p < 0.03), the average amount of time required to complete the day's work was not significantly changed (p = 0.08). There was no apparent effect on the average delay of the start of the day's first case (p = 0.34). CONCLUSION: The use of a computerized interactive daily schedule has a positive effect on departmental efficiency by allowing more cases to be performed without lengthening the workday.

[The registration of complications of medical treatment]. / Het registreren van complicaties van geneeskundige behandeling.

The National Surgical Adverse Event Registration (LHCR) software has been fully implemented in 25 (18.7%) departments of surgery in the Netherlands. This is a relatively low percentage considering that 92.5% of all hospitals are already using a local registration system for complications. Software difficulties in creating a link between the LHCR and local systems is suggested to be the main impeding factor. There are still a number of questions, notably concerning the validity of the system for registration of all complications versus a selected group of (severe) complications, the issue of the implications of the registration system in terms of quality control and subsequent regulation or centralization of procedures, and the importance for other specialists, in particular those performing invasive procedures, to introduce a complication registration system to establish a quality control system in those areas as well.