Design of Appointment Systems for Preanesthesia Evaluation Clinics to Minimize Patient Waiting Times: A Review of Computer Simulation and Patient Survey Studies

Patient satisfaction in anesthesiology: a narrative review

PURPOSE OF REVIEW

Healthcare is increasingly expanding its view in outcome discussions to integrate patient-reported outcomes such as patient satisfaction. Involving patients in the evaluation of services and the development of quality improvement strategies is paramount, especially in the service-oriented discipline of anaesthesiology.

RECENT FINDINGS

Currently, while the development of validated patient satisfaction questionnaires is well established, the use of rigorously tested scores in research and clinical practice is not standardized. Furthermore, most questionnaires are validated for specific settings, which limits our ability to draw relevant conclusions from them, especially considering the rapidly expanding scope of anaesthesia as a discipline and the addition of same-day surgery.

SUMMARY

For this manuscript, we review recent literature regarding patient satisfaction in the inpatient and ambulatory anaesthesia setting. We discuss ongoing controversies and briefly digress to consider management and leadership science regarding 'customer satisfaction'.

Queueing Theory and COVID-19 Prevention: Model Proposal to Maximize Safety and Performance of Vaccination Sites

Introduction

COVID-19 (Coronavirus Disease 19) has rapidly spread all around the world. Vaccination represents one of the most promising counter-pandemic measures. There is still little specific evidence in literature on how to safely and effectively program access and flow through specific healthcare settings to avoid overcrowding in order to prevent SARS-CoV-2 transmission. Literature regarding appointment scheduling in healthcare is vast. Unpunctuality however, especially when targeting healthcare workers during working hours, is always possible. Therefore, when determining how many subjects to book, using a linear method assuming perfect adhesion to scheduled time could lead to organizational problems.

Methods

This study proposes a "Queuing theory" based approach. A COVID-19 vaccination site targeting healthcare workers based in a teaching hospital in Rome was studied to determine real-life arrival rate variability. Three simulations using Queueing theory were performed.

Results

Queueing theory application reduced subjects queueing over maximum safety requirements by 112 in a real-life based vaccination setting, by 483 in a double-sized setting and by 750 in a mass vaccination model compared with a linear approach. In the 3 settings, respectively, the percentage of station's time utilization was 98.6, 99.4 and 99.8%, while the average waiting time was 27.2, 33.84, and 33.84 min.

Conclusions

Queueing theory has already been applied in healthcare. This study, in line with recent literature developments, proposes the adoption of a Queueing theory base approach to vaccination sites modeling, during the COVID-19 pandemic, as this tool enables to quantify ahead of time the outcome of organizational choices on both safety and performance of vaccination sites.

Evaluation of the Duration of Preanesthesia Consultation: Prospective and Multicenter Study

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.

Time spent by patients in a pre-anaesthetic clinic and the factors affecting it: An audit from a tertiary care teaching hospital

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.

[Analysis and options for optimization of preoperative assessment for anesthesia at a university hospital]

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.

Modified open-access scheduling for new patient evaluations at an academic chronic pain clinic increased patient access to care, but did not materially reduce their mean cancellation rate: A retrospective, observational study

STUDY OBJECTIVE

To determine if open-access scheduling would reduce the cancellation rate for new patient evaluations in a chronic pain clinic by at least 50%.

DESIGN

Retrospective, observational study using electronic health records.

SETTING

Chronic pain clinic of an academic anesthesia department.

PATIENTS

All patients scheduled for evaluation or follow-up appointments in the chronic pain clinic between April 1, 2014, and December 31, 2015.

INTERVENTIONS

Open-access scheduling was instituted in April 2015 with appointments offered on a date of the patient's choosing ≥1 business day after calling, with no limit on the daily number of new patients.

MEASUREMENTS

Mean cancellation rates for new patients were compared between the 12-month baseline period prior to and for 7months after the change, following an intervening 2-month washout period. The method of batch means (by month) and the 2-sided Student t-test were used; P<0.01 required for significance.

MAIN RESULTS

The new patient mean cancellation rate decreased from a baseline of 35.7% by 4.2% (95% confidence interval [CI] 1.4% to 6.9%; P=0.005); however, this failed to reach the 50% reduction target of 17.8%. Appointment lag time decreased by 4.7days (95% CI 2.3 to 7.0days, P<0.001) from 14.1days to 9.4days in the new patient group. More new patients were seen within 1week compared to baseline (50.6% versus 19.1%; P<0.0001). The mean number of new patient visits per month increased from 158.5 to 225.0 (P=0.0004). The cancellation rate and appointment lag times did not decrease for established patient visits, as expected because open-access scheduling was not implemented for this group.

CONCLUSIONS

Access to care for new chronic pain patients improved with modified open-access scheduling. However, their mean cancellation rate only decreased from 35.7% to 31.5%, making this a marginally effective strategy to reduce cancellations.

Patient satisfaction with anaesthesia services and associated factors at the University of Gondar Hospital, 2013: a cross-sectional study

BACKGROUND

Patient satisfaction is the degree of fulfilling patients' anticipation which is an important component and quality indicator in anaesthesia service. It can be affected by anaesthetist patient interaction, perioperative anaesthetic management and postoperative follow up. No previous study conducted in our setup. The aim was to assess patient satisfaction with anaesthesia services and associated factors.

METHODS

Institutional based cross sectional study was conducted from April 15-30, 2013 at the University of Gondar referral and teaching hospital. All patients who were operated upon both under general and regional anaesthesia during the study period were included. Standardized questionnaire used for postoperative patient interview. Data was entered and analyzed using Statistical Package for Social Sciences (SPSS) window version 20. Chi Square test used to assess the association between each factor and the overall satisfaction of patients. The proportion of patients who said they were satisfied with anaesthesia services was presented in percentage.

RESULTS

A total of 200 patients were operated upon under anaesthesia during the study period. Of these, a total of 156 patients were included in this study with a response rate of 78%. The overall proportion of patients who said they were satisfied with anaesthesia services was 90.4%. Factors that affected patient satisfaction negatively (dissatisfaction level and p value) were general anaesthesia (12.6%, P = 0.046), intraoperative awareness (50%, P = <0.001), pain during operation (61.1%, P = <0.001), and pain immediately after operation (25%, P = <0.001) respectively.

CONCLUSION AND RECOMMENDATION

Patient satisfaction with anaesthesia services was low in our setup compared with many previous studies. Factors that affected patient satisfaction negatively may be preventable or better treated. Awareness creation about the current problem and training need to be given for anaesthetists.

Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations: a case study in a primary care clinic

Background

Consumer e-Health is a potential solution to the problems of accessibility, quality and costs of delivering public healthcare services to patients. Although consumer e-Health has proliferated in recent years, it remains unclear if patients are willing and able to accept and use this new and rapidly developing technology. Therefore, the aim of this research is to study the factors influencing patients’ acceptance and usage of consumer e-health innovations.

Methods

A simple but typical consumer e-health innovation – an e-appointment scheduling service – was developed and implemented in a primary health care clinic in a regional town in Australia. A longitudinal case study was undertaken for 29 months after system implementation. The major factors influencing patients’ acceptance and use of the e-appointment service were examined through the theoretical lens of Rogers’ innovation diffusion theory. Data were collected from the computer log records of 25,616 patients who visited the medical centre in the entire study period, and from in-depth interviews with 125 patients.

Results

The study results show that the overall adoption rate of the e-appointment service increased slowly from 1.5% at 3 months after implementation, to 4% at 29 months, which means only the ‘innovators’ had used this new service. The majority of patients did not adopt this innovation. The factors contributing to the low the adoption rate were: (1) insufficient communication about the e-appointment service to the patients, (2) lack of value of the e-appointment service for the majority of patients who could easily make phone call-based appointment, and limitation of the functionality of the e-appointment service, (3) incompatibility of the new service with the patients’ preference for oral communication with receptionists, and (4) the limitation of the characteristics of the patients, including their low level of Internet literacy, lack of access to a computer or the Internet at home, and a lack of experience with online health services. All of which are closely associated with the low socio-economic status of the study population.

Conclusion

The findings point to a need for health care providers to consider and address the identified factors before implementing more complicated consumer e-health innovations.

[Evaluation of a new computerized recording system for preoperative assessment data]

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.

Applications of simulation within the healthcare context

A large number of studies have applied simulation to a multitude of issues relating to healthcare. These studies have been published in a number of unrelated publishing outlets, which may hamper the widespread reference and use of such resources. In this paper, we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high-quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies' results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied to healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques in solving diverse healthcare problems.

Improving clinical access and continuity through physician panel redesign

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.

Effect of two-level provider capacities on the performance of open access clinics

The successful implementation of open access scheduling requires the match of daily healthcare provider capacity and patient demand at the high level of total capacity and the low levels of individual capacities for different types of appointments. In this paper, we introduce 12 scheduling rules for determining the two-level provider capacities and compare them in terms of four performance metrics: the probabilities of granting requests for fixed and open appointments, and the expectation and the variance of the number of patients consulted. Our analytical results show that adjusting low level provider capacities can reduce the difference between the two probabilities. When the ratios of low level capacities to the high level provider capacity are fixed, the two probabilities increase with the increase in the high level capacity. Meanwhile, our numerical results demonstrate that the expectation and the variance of the number of patients consulted increase with the increase in the high level capacity. The results provide insights in determining optimal two-level provider capacities to match daily patient demand. Potential approaches to optimality are also proposed based on the results.

Patient perception of the utility of the Preanesthetic Clinics in a Caribbean developing country

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.

Preoperative screening, evaluation, and optimization of the patient's medical status before outpatient surgery

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.

The impact on revenue of increasing patient volume at surgical suites with relatively high operating room utilization

We previously studied hospitals in the United States of America that are losing money despite limiting the hours that operating room (OR) staff are available to care for patients undergoing elective surgery. These hospitals routinely keep utilization relatively high to maximize revenue. We tested, using discrete-event computer simulation, whether increasing patient volume while being reimbursed less for each additional patient can reliably achieve an increase in revenue when initial adjusted OR utilization is 90%. We found that increasing the volume of referred patients by the amount expected to fill the surgical suite (100%/90%) would increase utilization by <1% for a hospital surgical suite (with longer duration cases) and 4% for an ambulatory surgery suite (with short cases). The increase in patient volume would result in longer patient waiting times for surgery and more patients leaving the surgical queue. With a 15% reduction in payment for the new patients, the increase in volume may not increase revenue and can even decrease the contribution margin for the hospital surgical suite. The implication is that for hospitals with a relatively high OR utilization, signing discounted contracts to increase patient volume by the amount expected to "fill" the OR can have the net effect of decreasing the contribution margin (i.e., profitability).

IMPLICATIONS

Hospitals may try to attract new surgical volume by offering discounted rates. For hospitals with a relatively high operating room utilization (e.g., 90%), computer simulations predict that increasing patient volume by the amount expected to "fill" the operating room can have the net effect of decreasing contribution margin (i.e., profitability).

Scheduling a delay between different surgeons' cases in the same operating room on the same day using upper prediction bounds for case durations

At some surgical suites, elective cases are only scheduled if they can be completed during regularly scheduled hours. At such a surgical suite, a surgeon may be scheduled to perform one or more cases in an operating room (OR), to be followed by another surgeon who will perform one or more cases. Scheduling a delay between the two surgeons' cases will improve the likelihood that the second surgeon's case(s) will start on time. We show that the mathematics of calculating a scheduled delay between the different surgeons' cases in the same OR on the same day is that of calculating an upper prediction bound for the duration of the second surgeon's case(s). We test an analytical expression for the upper prediction bound for the last one case of the day in an OR, and a Monte Carlo simulation method for the last two cases. We show that these 90% upper prediction bounds are at least as long as the actual durations for 90% +/- 0.2% of single cases and 92% +/- 0.6% of pairs of cases. We conclude that our methodology can be used to calculate an appropriate, and reasonably accurate, scheduled delay between two surgeons' cases in the same OR on the same day.

IMPLICATIONS

We show how to use a statistical analysis of historical case duration data to calculate an appropriate and accurate scheduled delay between two surgeons' cases in the same operating room on the same day.