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Compère V, Froemer B, Clavier T, Selim J, Burey J, Dureuil B, Gillibert A, Besnier E. Evaluation of the Duration of Preanesthesia Consultation: Prospective and Multicenter Study. Anesth Analg 2022; 134:496-504. [PMID: 35180166 DOI: 10.1213/ane.0000000000005889] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND The time allocated to the preanesthesia consultation (PAC) of a patient undergoing an elective surgical procedure is an important factor to optimize consultation sessions. The main objective of this study was to build a model predictive of the duration of the PAC. METHODS We prospectively studied 1007 patients undergoing a PAC from January 2016 to June 2018 in 4 different hospitals. A general linear model was fitted to predict the overall duration of the PAC. Secondary models predicted the time spent on clinical evaluation and the time assigned to delivering information. RESULTS After exclusion of 40 patients with major data inconsistencies, the mean (standard deviation [SD]) overall duration of the PAC was 11.2 (5.8) minutes, split into 6.8 (4.1) minutes of information and 4.4 (2.7) minutes of clinical evaluation. It was, respectively, 11.4 (5.9), 6.9 (4.2), and 4.4 (2.7) in the 924 patients ≥16 years of age and, respectively, 8.3 (2.3), 4.3 (1.8), and 4.1 (1.8) in 43 children. The American Society of Anesthesiologists (ASA) score, the number of comorbidities or treatment, surgery discipline, and context (ambulatory, conventional hospitalization, and intensive care unit) were significantly correlated to PAC time. In the 924 adult patients, the models had an R2 adjusted for overfitting at 0.47 for the total duration of PAC, 0.45 for the clinical examination time, and 0.24 for the information time. The estimated residual standard deviations were, respectively, 4.3, 3.1, and 2.7 minutes. CONCLUSIONS The predictive performances of the model explaining the overall duration of PAC were average (R2 = 0.47) and should be confirmed by further studies to use it for optimizing the organization of the consultation by individualizing the time dedicated to each consultation.
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Affiliation(s)
- Vincent Compère
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France.,Normandie University, UNIROUEN, Inserm U982, Mont-Saint-Aignan, France
| | - Benoit Froemer
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
| | - Thomas Clavier
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
| | - Jean Selim
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
| | - Julien Burey
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
| | - Bertrand Dureuil
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
| | - André Gillibert
- Biostatistics Department, Rouen University Hospital, Rouen, France
| | - Emmanuel Besnier
- From the Department of Anesthesia and Intensive Care, Rouen University Hospital, Rouen, France
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James JP, Thampi SM. Time spent by patients in a pre-anaesthetic clinic and the factors affecting it: An audit from a tertiary care teaching hospital. Indian J Anaesth 2018; 62:16-22. [PMID: 29416146 PMCID: PMC5787885 DOI: 10.4103/ija.ija_368_17] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background and Aims: Patient satisfaction from a pre-anaesthetic clinic (PAC) visit is greatly influenced by time spent there. We aimed to determine time spent in a PAC without an appointment system and the factors affecting the same. Methods: Four hundred and eight patients coming to PAC were tracked using a time-motion study model. Time spent in waiting and consultation was recorded. Independent variables potentially affecting time spent were documented. Patients were grouped based on independent variables, and the groups were compared for significant differences using appropriate statistical tests. Workload pending on physicians was calculated on an hourly basis by counting number of patients waiting and number of physicians in PAC. Results: Non-parametric statistical tests were used for analysis because the data were not normally distributed. The median and inter-quartile range for waiting time, consultation time and total time were 60 (30–90) minutes, 17 (12–26) minutes and 79 (53–111) minutes, respectively. There was considerable variation in all three. Waiting time was significantly lower in patients posted for same-day surgery or those arriving on a stretcher or wheelchair. Consultation time was correlated with American Society of Anesthesiologists physical status and grade of surgery. Most patients arrived in the morning rather than at equal intervals. Waiting time and workload were therefore maximum in the midmorning and dropped rapidly in the afternoon. Conclusion: Large variability in waiting time is linked to lack of an appointment system, and to patients being seen out of turn.
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Affiliation(s)
- Justin P James
- Department of Anaesthesiology, Christian Medical College, Vellore, Tamil Nadu, India
| | - Suma Mary Thampi
- Department of Anaesthesiology, Christian Medical College, Vellore, Tamil Nadu, India
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Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS. Health Syst (Basingstoke) 2017. [DOI: 10.1057/hs.2012.18] [Citation(s) in RCA: 233] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Kieninger M, Eissnert C, Seitz M, Judemann K, Seyfried T, Graf B, Sinner B. [Analysis and options for optimization of preoperative assessment for anesthesia at a university hospital]. Anaesthesist 2017; 67:93-108. [PMID: 29230500 DOI: 10.1007/s00101-017-0392-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Revised: 11/09/2017] [Accepted: 11/15/2017] [Indexed: 12/17/2022]
Abstract
BACKGROUND Risk assessment prior to elective surgery is an important tool in the context of perioperative patient care; however, only a few studies have been carried out to address the processes and problems during preoperative assessment for anesthesia. AIM Over a period of several weeks all preoperative anesthesia evaluations prior to elective surgery were prospectively recorded in order to generate a data pool with a view to identifying options for process optimization. MATERIAL AND METHODS All preoperative evaluations over a period of 38 working days at the University Medical Center Regensburg were recorded and analyzed with respect to waiting time for the patient and the duration of the preoperative consultation on medication. Also documented were the patient age, ASA score, the faculty carrying out the operation, type and risk of surgery, planned time of surgery, professional experience of the anesthesiologist and the approval status for surgery. In addition, all problems which occurred during the preoperative anesthesia evaluation were documented using a questionnaire. RESULTS Overall 2233 preoperative assessments for anesthesia were recorded and analyzed. The number of patients attending the preoperative assessment clinic differed markedly in the course of a day and was lower at the end of the week. Approval for surgery with no reservations was given more frequently by anesthesiologists with more than 5 years professional experience and consultants compared to younger colleagues. The main reason for approval with reservations or no approval was the lack of patient records and test results, which should have been presented according to the in-house standard for preoperative assessment for anesthesia. The mean waiting time was 58.6 ± 30.3 min, the mean duration of the patient documentation review and physician-patient consultation together was 33.6 ± 16.3 min. Anesthesiologists with 2-5 years professional experience needed significantly less time for patient documentation reviews and physician-patient consultations than younger and more experienced colleagues. The duration of the preoperative assessment for anesthesia correlated with the ASA score and risks of surgery. CONCLUSION The analysis of processes and problems in the context of preoperative assessment for anesthesia revealed several options for optimization. Major efforts should be the implementation of an appointment system for the preoperative assessment clinic in order to generate a homogeneous distribution of patients during the course of a day. Furthermore, surgeons and case managers should be requested to refer patients to the preoperative assessment clinic only with complete records and test results according to the in-house standard.
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Affiliation(s)
- M Kieninger
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
| | - C Eissnert
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
| | - M Seitz
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
| | - K Judemann
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
| | - T Seyfried
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
| | - B Graf
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
| | - B Sinner
- Klinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland
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Munavalli JR, Rao SV, Srinivasan A, Manjunath U, van Merode GG. A Robust Predictive Resource Planning under Demand Uncertainty to Improve Waiting Times in Outpatient Clinics. JOURNAL OF HEALTH MANAGEMENT 2017; 19:563-583. [PMID: 30166799 PMCID: PMC6097127 DOI: 10.1177/0972063417727627] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Jyoti R Munavalli
- Research Associate, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Shyam Vasudeva Rao
- Cofounder, President and CTO, Forus Health, Bangalore, Technical Director, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | - Usha Manjunath
- Professor, Institute of Health Management Research, Bangalore, Karnataka, India
| | - G G van Merode
- Professor of Logistics and Operations Management in Health Care, Maastricht University Medical Centre, Maastricht, The Netherlands
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A multidisciplinary approach to improve preoperative understanding and reduce anxiety: a randomised study. Eur J Anaesthesiol 2014; 30:734-42. [PMID: 24141644 DOI: 10.1097/eja.0b013e3283652c0c] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Emotional factors may influence reception of information provided during informed consent leading to incomplete understanding and reduced satisfaction. OBJECTIVE This study was designed to test the hypothesis that a multidisciplinary approach could improve understanding of the information provided by the anaesthesiologist and in turn, reduce anxiety. DESIGN A randomised controlled clinical trial. SETTING Veneto Oncology Institute, Italian comprehensive cancer centre. Recruitment from December 2008 to June 2010. PATIENTS Two hundred and fifty-one women requiring anaesthesia for breast cancer surgery. INTERVENTIONS Women undergoing surgery for primary breast cancer were randomly assigned to either the structured anaesthesiology interview group (SAI) or the integrated multidisciplinary psycho-oncological approach (IPA). In the IPA arm, patients underwent an interview with the psycho-oncologist. Subsequently, and prior to preoperative anaesthesia evaluation, the psycho-oncologist informed the anaesthesiologist of the type of communicative strategy to adopt for each individual. In the SAI arm, patients received only the anaesthesiology interview. MAIN OUTCOME MEASURES Anxiety as assessed by State-Trait Anxiety Inventory (STAI) questionnaire. RESULTS Two hundred and fifty-one patients were randomised and 234 analysed: 124 in the IPA arm and 110 in the SAI arm. For both groups, mean anxiety scores, according to the STAI questionnaire, were statistically lower after the anaesthesiology visit than at baseline, with a reduction of 6.5 points for the IPA arm [95% confidence interval (CI) 4.6 to 8.4, P < 0.0001] and 4.7 points for the SAI arm (95% CI 2.6 to 6.7, P < 0.0001). There were no significant differences between the two groups in the mean anxiety score before and after the interview. For highly anxious patients, the STAI score decreased significantly more in the IPA group (10.2 points, 95% CI 7.4 to 13.0) than in the SAI group (6.8 points, 95% CI 3.8 to 9.8), P = 0.024.The information provided during the anaesthesiology visit was correctly understood by more than 80% of patients and was similar in both groups. CONCLUSION In breast cancer surgical patients with high levels of preoperative anxiety, a multidisciplinary approach with psycho-oncological intervention proved to be useful at the preoperative anaesthesiology interview.
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Dexter F, Ahn HS, Epstein RH. Choosing Which Practitioner Sees the Next Patient in the Preanesthesia Evaluation Clinic Based on the Relative Speeds of the Practitioner. Anesth Analg 2013; 116:919-23. [DOI: 10.1213/ane.0b013e31826cc0ba] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Mata J, Cabrera S, Valldeperas MI, Fernández S, Aguilar JL, Atanassoff PG. A national survey on current practice of preanaesthetic assessment in elective surgery patients in Spain. ACTA ACUST UNITED AC 2012; 59:299-305. [PMID: 22742870 DOI: 10.1016/j.redar.2012.04.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2011] [Accepted: 04/23/2012] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To analyse the preanaesthetic assessment prior to elective surgery in hospitals of the Spanish National Health Care System. METHODS A prospective cross-sectional descriptive observational survey was performed. Primary variables were patient characteristics, type of preanaesthetic evaluation and the evaluator, as well as type of support the evaluator received during patient assessment. Secondary variables included the number of operating rooms available for elective surgery, as well as preanaesthesia clinic facilities. Data were analysed by univariate and bivariate descriptive analysis. RESULTS A total of 214 hospitals of the Spanish Health Care System were invited to participate, and 203 centres responded, with all of them having a preanaesthesia assessment clinic. In 183 of them (90%), elective surgerypatients were interviewed prior to their surgical intervention, and in 202 hospitals (99.5%) a anaesthesiologist physician performed the interview. In 128 hospitals (63%), anaesthesiologists were helped during preoperative assessment by nurses alone (49%) or together with auxillary nurses (14%). In 68 of hospitals (33%) they were supported only by auxillary nurses and in 7 hospitals (3%) they obtained no help at all. In 14 centres (7%) anaesthesia nurses assessed patients directly (under supervision of an anaesthesiologist physician). Hospitals with a higher volume of patients performed more preanaesthesia interviews. Hospitals with more running operating rooms received more nurse support in the preanaesthesia assessment clinic. CONCLUSIONS Some kind of preanaesthesia assessment clinic exists in all Anaesthesia Departments of public Spanish hospitals, although there are differences in design and organisation.
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Affiliation(s)
- J Mata
- Servicio de Anestesiología y Reanimación, Hospital Son Llàtzer, Palma de Mallorca, Baleares, Spain
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Dexter F, Witkowski TA, Epstein RH. Forecasting Preanesthesia Clinic Appointment Duration from the Electronic Medical Record Medication List. Anesth Analg 2012; 114:670-3. [DOI: 10.1213/ane.0b013e31823fba9e] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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de la Matta Martín M, Forastero Rodríguez A, López Romero JL. [Evaluation of a new computerized recording system for preoperative assessment data]. REVISTA ESPANOLA DE ANESTESIOLOGIA Y REANIMACION 2011; 58:485-492. [PMID: 22141216 DOI: 10.1016/s0034-9356(11)70123-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
BACKGROUND AND OBJECTIVES Little information is available on the use of computerized systems in preanesthetic assessment. Our aim was to evaluate staff acceptance of a computerized system for the structured recording of preoperative assessment data in our hospital. The time taken to complete the assessment was compared to the time usually taken to record the information on paper. MATERIAL AND METHODS Observational, descriptive cross-sectional survey of user satisfaction 3 months after the system had been launched. We later carried out a prospective observational study of 796 preanesthetic assessment visits, comparing the mean time the users took to record information on paper to the time required to enter the data into the computer, analyzing differences between anesthesiologists and according to American Society of Anesthesiologists (ASA) classification and patient age. RESULTS A total of 401 paper records and 395 electronic files were included. The users believed that the computerized system improved quality and accessibility of recorded data and clinical decision-making. The time required to enter data into the computer was believed to be the main drawback; the users took a mean (SD) 15.21 (5.41) minutes to enter the electronic data and 13.37 (5.08) minutes to record the information on paper (P < .001). There were also significant differences in the time taken to record data according to ASA classification and between anesthesiologists (P < .001). CONCLUSIONS In spite of drawbacks such as extra time taken to record electronic data, the users perceived benefits, such as improved quality and accessibility of records. For this reason, the computerized system was well accepted.
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Affiliation(s)
- M de la Matta Martín
- Servicio de Anestesiología y Reanimación, Hospitales Universitarios Virgen del Rocío, Sevilla.
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Abstract
Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.
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Villamizar J, Coelli F, Pereira W, Almeida R. Discrete-event computer simulation methods in the optimisation of a physiotherapy clinic. Physiotherapy 2011; 97:71-7. [DOI: 10.1016/j.physio.2010.02.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2009] [Accepted: 02/27/2010] [Indexed: 11/26/2022]
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Improving clinical access and continuity through physician panel redesign. J Gen Intern Med 2010; 25:1109-15. [PMID: 20549379 PMCID: PMC2955464 DOI: 10.1007/s11606-010-1417-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2009] [Revised: 04/20/2010] [Accepted: 05/05/2010] [Indexed: 10/19/2022]
Abstract
BACKGROUND Population growth, an aging population and the increasing prevalence of chronic disease are projected to increase demand for primary care services in the United States. OBJECTIVE Using systems engineering methods, to re-design physician patient panels targeting optimal access and continuity of care. DESIGN We use computer simulation methods to design physician panels and model a practice's appointment system and capacity to provide clinical service. Baseline data were derived from a primary care group practice of 39 physicians with over 20,000 patients at the Mayo Clinic in Rochester, MN, for the years 2004-2006. Panel design specifically took into account panel size and case mix (based on age and gender). MEASURES The primary outcome measures were patient waiting time and patient/clinician continuity. Continuity is defined as the inverse of the proportion of times patients are redirected to see a provider other than their primary care physician (PCP). RESULTS The optimized panel design decreases waiting time by 44% and increases continuity by 40% over baseline. The new panel design provides shorter waiting time and higher continuity over a wide range of practice panel sizes. CONCLUSIONS Redesigning primary care physician panels can improve access to and continuity of care for patients.
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Swart M, Houghton K. Pre-operative preparation: Essential elements for delivering enhanced recovery pathways. ACTA ACUST UNITED AC 2010. [DOI: 10.1016/j.cacc.2010.02.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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The effects of implementing a new schedule at the preoperative assessment clinic. Eur J Anaesthesiol 2010; 27:209-13. [DOI: 10.1097/eja.0b013e328330f347] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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How work context affects operating room processes: using data mining and computer simulation to analyze facility and process design. Qual Manag Health Care 2010; 18:305-14. [PMID: 19851238 DOI: 10.1097/qmh.0b013e3181bee2c6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
The complexity of the operating room (OR) requires that both structural (eg, department layout) and behavioral (eg, staff interactions) patterns of work be considered when developing quality improvement strategies. In our study, we investigated how these contextual factors influence outpatient OR processes and the quality of care delivered. The study setting was a German university-affiliated hospital performing approximately 6000 outpatient surgeries annually. During the 3-year-study period, the hospital significantly changed its outpatient OR facility layout from a decentralized (ie, ORs in adjacent areas of the building) to a centralized (ie, ORs in immediate vicinity of each other) design. To study the impact of the facility change on OR processes, we used a mixed methods approach, including process analysis, process modeling, and social network analysis of staff interactions. The change in facility layout was seen to influence OR processes in ways that could substantially affect patient outcomes. For example, we found a potential for more errors during handovers in the new centralized design due to greater interdependency between tasks and staff. Utilization of the mixed methods approach in our analysis, as compared with that of a single assessment method, enabled a deeper understanding of the OR work context and its influence on outpatient OR processes.
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Hunziker S, Baumgart A, Denz C, Schüpfer G. [Economic benefits of overlapping induction: investigation using a computer simulation model]. Anaesthesist 2009; 58:623-32. [PMID: 19562399 DOI: 10.1007/s00101-009-1551-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The aim of this study was to investigate the potential economic benefit of overlapping anaesthesia induction given that all patient diagnosis-related groups (AP DRG) are used as the model for hospital reimbursement. A computer simulation model was used for this purpose. Due to the resource-intensive production process, the operating room (OR) environment is the most expensive part of the supply chain for surgical disciplines. The economical benefit of a parallel production process (additional personnel, adaptation of the process) as compared to a conventional serial layout was assessed. A computer-based simulation method was used with commercially available simulation software. Assumptions for revenues were made by reimbursement based on AP DRG. Based on a system analysis a model for the computer simulation was designed on a step-by-step abstraction process. In the model two operating rooms were used for parallel processing and two operating rooms for a serial production process. Six different types of surgical procedures based on historical case durations were investigated. The contribution margin was calculated based on the increased revenues minus the cost for the additional anaesthesia personnel. Over a period of 5 weeks 41 additional surgical cases were operated under the assumption of duration of surgery of 89+/-4 min (mean+/-SD). The additional contribution margin was CHF 104,588. In the case of longer surgical procedures with 103+/-25 min duration (mean+/-SD), an increase of 36 cases was possible in the same time period and the contribution margin was increased by CHF 384,836. When surgical cases with a mean procedural time of 243+/-55 min were simulated, 15 additional cases were possible. Therefore, the additional contribution margin was CHF 321,278. Although costs increased in this simulation when a serial production process was changed to a parallel system layout due to more personnel, an increase of the contribution margin was possible, especially with procedures of shorter duration (<120 min). For longer surgical times, the additional costs for the workforce result in a reduced contribution margin depending on the models chosen to handle overtime of the technical OR personnel. Important advantages of this approach for simulation are the use of the historical production data and the reflection of the specificities of the local situation. Computer simulation is an ideal tool to support operation room management, particularly regarding the planning of resource allocation and the coordination of workflow.
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Affiliation(s)
- S Hunziker
- Medizinischer Stab, Luzerner Kantonsspital, 6000, Luzern, Schweiz.
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Hariharan S, Chen D, Jurai N, Partap A, Ramnath R, Singh D. Patient perception of the utility of the Preanesthetic Clinics in a Caribbean developing country. Rev Bras Anestesiol 2009; 59:194-205. [PMID: 19488531 DOI: 10.1590/s0034-70942009000200007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2008] [Accepted: 12/03/2008] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Perception of the patients regarding the utility of the Preanesthetic Clinics and flow time in clinics has not been widely studied in the developing world. The present study aims to study this aspect. METHODS A self-administered 15-item questionnaire survey was conducted among patients attending the Preanesthetic Clinics at a tertiary care teaching hospital in Trinidad. The questionnaire was also distributed to the patients attending the General Surgical Clinic for comparison. Another questionnaire was distributed among the staff of the Preanesthetic Clinic. Patient demographics including age, gender, and educational status and American Society of Anesthesiologists physical status were noted. Other data recorded were patient flow time and details of attending staff. RESULTS Of the 220 patients who attended the Preanesthetic Clinics, 92.7% participated in the study. The reliability of the questionnaire was supported by Cronbach's alpha coefficient (0.67). The median time for referral from the surgical clinic to Preanesthetic Clinic was 50 days, median waiting time in the clinic was 2.7 hours, and the median waiting time for surgery after acceptance in the clinic was 13 days. The patients' opinions regarding the benefits of the clinic, length of the waiting time was independent of their age and educational status. Patients felt that attending the Preanesthetic Clinic was beneficial and not costly to them, although the waiting times were found to be longer. CONCLUSIONS Patients perceive that attending the Preanesthetic Clinic has been useful before the surgical procedure and the care they received in the clinic was satisfactory.
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Preoperative screening, evaluation, and optimization of the patient's medical status before outpatient surgery. Curr Opin Anaesthesiol 2009; 21:711-8. [PMID: 18997522 DOI: 10.1097/aco.0b013e3283126cf3] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
PURPOSE OF THE REVIEW Preoperative evaluation and optimization of a patient's medical condition are important components of anesthesia practice. With ever increasing numbers of patients with serious comorbidities having complex procedures as outpatients, the task of gathering information and properly preparing for their care is challenging. Improvements in assessment and management can potentially reduce adverse events, improve patient and caregiver satisfaction, and reduce costs. RECENT FINDINGS A growing body of literature and evidence-based practices and guidelines can assist clinicians who work in the expanding field of preoperative medicine. Care providers from various specialties in medicine are developing innovative methods, tools, and knowledge to advance science and processes. Data-driven practices are beginning to close the information gap that has plagued this field of medical practice. SUMMARY Preparation of patients before surgery is a necessary and vital component of perioperative medicine. Practices are developing to guide effective interventions that benefit patients and healthcare systems. Outpatients present special challenges to preoperative assessment.
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Hardman JG, Moppett IK, Mahajan RP. Validity, credibility, and applicability: the rise and rise of the surrogate. Br J Anaesth 2008; 101:595-6. [PMID: 18854383 DOI: 10.1093/bja/aen292] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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