Walk-in clinics: implications for family practice.

To understand better the reasons for the growth in popularity of walk-in clinics in Canada we surveyed 321 patients with a regular physician in Toronto who attended a walk-in clinic in the same city over a 16-day period in February 1988. They were asked their reason for attending the clinic, their perception of the urgency of their problem, their choices as alternatives to walk-in clinics and their satisfaction and concerns with the type of care received at the clinic. The three most common reasons for attending the clinic were convenient location (in 33% of the cases), inability to see their regular physician soon enough (in 16%) and no appointment needed (in 13%). Most (80%) of the patients felt that they needed medical attention within 24 hours after the onset of their problem. Most (83%) of the respondents would have sought medical attention at another walk-in clinic, from their regular physician or at an emergency department had the clinic been closed. Only 36% and 18% of the patients respectively responded that their regular physician worked evenings or weekends. Most of the visits to the clinic were outside regular weekday business hours. The level of satisfaction with the service received at the clinic was high. The extended hours and no-appointment philosophy of walk-in clinics, coupled with family physicians' reluctance to work evenings and weekends, have made such clinics an attractive option for patients with primary care problems that they believe require prompt attention.     

医院分时就诊服务流程优化设计

针对患者预约服务及候诊排队拥挤的问题,讨论了基于手机短信的院外候诊服务流程和基于专家问诊时间的分时就诊流程。首先介绍了预约诊疗的几种模式,并讨论了预约就诊数据交换流程,然后阐述了基于手机短信的院外候诊服务流程和基于专家问诊时间的分时就诊流程,完全改变了传统取号后直接候诊的就医流程。主要从院外候诊、分时就诊以及服务质量评价几个方面对预约诊疗服务流程进行优化,对有效解决医院“三长一短”问题,缓解医院拥挤的现状,减少患者感染几率具有非常重要作用。     

Impact of adjustment measures on reducing outpatient waiting time in a community hospital: application of a computer simulation

Background As an important determinant of patient satisfaction, waiting time, has gained increasing attention in the field of health care services. The present study aimed to illustrate the distribution characteristics of waiting time in a community hospital and explore the impact of potential measures to reduce outpatient waiting time based on a computer simulation approach. Methods Dudng a one-month study period in 2006, a cross-sectional study was conducted in a community hospital located in Shanghai, China. Baseline data of outpatient waiting time were calculated according to the records of registration time and payment time. A simulation technique was adopted to investigate the impact of perspective reform methods on reducing waiting time. Results Data from a total of 10 092 patients and 26 816 medical consultations were collected in the study and 19 947 medical consultations were included. The average of the total visit time for outpatients in this hospital was 43.6 minutes in the morning, 19.1 minutes in the afternoon, and 34.3 minutes for the whole day studied period. The simulation results suggested that waiting time for outpatients could be greatly reduced through the introduction of appointment system and flexible demand-orientated doctor scheduling according to the numbers of patients waiting at different time of the workday. Conclusion Adoption of an appointment system and flexible management of doctor scheduling may be effective way to achieve decreased waiting time.     

A physiotherapy specialist clinic in paediatric orthopaedics: is it effective?

A physiotherapy specialist clinic was set up to reduce waiting times for non-urgent, new paediatric orthopaedic referrals. The outcome was reviewed at a minimum of 12 months for 1046 referrals assessed in the physiotherapy support clinic to analyse its effectiveness. Altogether 114 patients failed to attend the clinic. The remaining 932 patients form the basis of this study. Ninety three percent of these patients were managed without direct consultant intervention-72% with advice and reassurance, 17% by referral to the physiotherapy department, and 4% with surgical appliances. Only 7% needed consultant evaluation. Median waiting time for non-urgent conditions was reduced from 72 weeks in May 1996 to five weeks in May 1999. A majority of the parents were satisfied with the clinic. The clinic was found to be cost effective. The success of the clinic was attributable to good cooperation between the consultant and physiotherapist and a well defined protocol for assessment and management of patients.     

The pediatric walk-in clinic: competition for the private practitioner

In an affluent city with many pediatricians a 20% increase in patients seen in a hospital-based walk-in clinic in 1982 prompted a study to determine the characteristics of clinic users and their reasons for using the clinic. It was found that users of the clinic were middle-class, that they had a higher employment rate than the average for the region, and that in 54% of the families both parents worked outside the home. The children of 85% of the families were patients of pediatricians in private practice; most of the others were patients of a family physician in private practice. Most of the children seen at the clinic had had symptoms for more than 24 hours, but few parents had attempted to contact their own physicians. In the previous 12 months 95% of the children had been seen at the clinic, 43% in the month preceding the study. They came to the clinic for two main reasons: the broad range of services offered --laboratory, radiology and pharmacy as well as medical--and the convenient hours, with 71% coming outside of their physicians' office hours. Given the reality of social trends pediatricians will either have to share their patients with facilities that offer services outside of regular office hours or devise another system for the treatment of their patients.     

Patient care and professional staffing patterns in McKinney Act clinics providing primary care to the homeless.

OBJECTIVE--To describe the patient care and staffing patterns of the 157 clinics that receive federal funding to provide health care to the homeless. DATA SOURCES--Telephone interviews with clinic medical directors. RESULTS--Clinics treated a mean of 96 homeless patients per week, approximately 50% of the estimated homeless population. Three quarters treated homeless patients only, the others integrated homeless patients into an existing setting. One third of the clinics had no physician more than 5 hours per week, 10% had no physician staff at all, and 80% employed a nurse practitioner. The proportion of patients initially examined by a nurse practitioner and the proportion subsequently referred to a physician ranged between 10% and 100%. Clinic directors reported that in over 50% of clinics, physician recruitment was hampered by poor working conditions, inadequate salaries, physician biases against working with the homeless, and the lack of respect this work receives from the medical profession. CONCLUSIONS--Current financial constraints may be impeding the ability of clinics serving the homeless to ensure adequate access to high quality care. Additional research should evaluate the impact various staffing patterns have on access and quality of care and develop methods to improve physician recruitment.     

Fairness in the coronary angiography queue

BACKGROUND: Since waiting lists for coronary angiography are generally managed without explicit queuing criteria, patients may not receive priority on the basis of clinical acuity. The objective of this study was to examine clinical and nonclinical determinants of the length of time patients wait for coronary angiography. METHODS: In this single-centre prospective cohort study conducted in the autumn of 1997, 357 consecutive patients were followed from initial triage until a coronary angiography was performed or an adverse cardiac event occurred. The referring physicians' hospital affiliation (physicians at Sunnybrook & Women's College Health Sciences Centre, those who practice at another centre but perform angiography at Sunnybrook and those with no previous association with Sunnybrook) was used to compare processes of care. A clinical urgency rating scale was used to assign a recommended maximum waiting time (RMWT) to each patient retrospectively, but this was not used in the queuing process. RMWTs and actual waiting times for patients in the 3 referral groups were compared; the influence clinical and nonclinical variables had on the actual length of time patients waited for coronary angiography was assessed; and possible predictors of adverse events were examined. RESULTS: Of 357 patients referred to Sunnybrook, 22 (6.2%) experienced adverse events while in the queue. Among those who remained, 308 (91.9%) were in need of coronary angiography; 201 (60.0%) of those patients received one within the RMWT. The length of time to angiography was influenced by clinical characteristics similar to those specified on the urgency rating scale, leading to a moderate agreement between actual waiting times and RMWTs (kappa = 0.53). However, physician affiliation was a highly significant (p < 0.001) and independent predictor of waiting time. Whereas 45.6% of the variation in waiting time was explained by all clinical factors combined, 9.3% of the variation was explained by physician affiliation alone. INTERPRETATION: Informal queuing practices for coronary angiography do reflect clinical acuity, but they are also influenced by nonclinical factors, such as the nature of the physicians' association with the catheterization facility.     

The assessment of patients' waiting and nursing consultation times at urban clinics in the National Capital District, Papua New Guinea

This study was conducted in the National Capital District during the months of August, September and October 2000. The study sites were the 3 urban clinics situated in the suburbs of Six Mile, Hohola and Konedobu. The aim of the study was to determine the patients' waiting times and nursing consultation times in the urban clinics. A total of 1075 patients were surveyed, including 264 children under 5 years of age. 58% of patients were males. 24% of patients were able to see a nurse within 30 minutes and 70% within 2 hours. 47% had to wait 1-3 hours to see a consulting nurse and a further 9.5% had to wait 3-5 hours. 67% of nursing consultations were 5 minutes or less, which is too short to interview, examine and prescribe treatment for the patients and to use the Paediatric 10 Steps. The short consultations of 5 minutes or less did not involve children under 5 years of age. There were only one to two nurses seeing the patients when 79% of patients were seen. This explains why the patients' waiting time was long. After consultations many patients (71%) were able to get their treatment within 30 minutes but 28% had to wait from 30 minutes to 2 hours for their treatment. The small number of nurses giving treatment leads to long waiting times. From the time of entry to exit out of the clinic, only 11% of patients spent 30 minutes or less in the clinic while 51% spent between 1 and 3 hours. The patients' waiting times and the short nursing consultation times are directly related to the insufficient number of nursing officers working in the clinics.     

Consequences of queuing for care at a public hospital emergency department

OBJECTIVE: To determine whether the length of a queue at a public hospital emergency department was associated with increased likelihood of patients' leaving without being seen by a physician and whether leaving adversely affected patients' health or affected their subsequent use of health care services. DESIGN: Observational cohort. Patients were surveyed during 1 week in July 1990 and received a follow-up survey 7 to 14 days later. The responses of patients who left without being seen by a physician were compared with those who were seen by a physician. SETTING: Emergency department at San Francisco (Calif) General Hospital. PATIENTS: All English-, Spanish-, and Cantonese-speaking adults waiting for emergency care were eligible. Of 882 eligible individuals, 700 agreed to participate; 85% of enrolled subjects saw a physician and 15% left without being seen. Demographic characteristics of patients who were and who were not seen were not significantly different. MAIN OUTCOME MEASURES: Emergency department waiting time and changes in patients' self-reported health. RESULTS: Patients were more likely to leave as waiting times increased. At follow-up, patients who left without being seen were twice as likely as those who were seen to report that their pain or the seriousness of their problem was worse. Only 4% of patients who left required subsequent hospitalization, but 27% returned to an emergency department. CONCLUSION: Many patients can appropriately decide whether their problem is truly urgent and make alternative plans in the face of long waits, but the health of some patients may be jeopardized by long queues for emergency care.     

Personnel and Patient Scheduling in the High Demanded Hospital Services: A Case Study in the Physiotherapy Service

High demand but limited staffs within some services of a hospital require a proper scheduling of staff and patients. In this study, a hierarchical mathematical model is proposed to generate weekly staff scheduling. Due to computational difficulty of this scheduling problem, the entire model is broken down into manageable three hierarchical stages: (1) selection of patients, (2) assignment of patients to the staff, (3) scheduling of patients throughout a day. The developed models were tested on the data collected in College of Medicine Research Hospital at Cukurova University using GAMS and MPL optimization packages. From the results of the case study, the presented hierarchical model provided a schedule that ensures to maximize the number of selected patients, to balance the workload of physiotherapist, and to minimize waiting time of patients in their treatment day.     

Analysis of Factors Causing Long Patient Waiting Time and Clinic Overtime in Outpatient Clinics

This paper is focused on the factors causing long patient waiting time/clinic overtime in outpatient clinics and how to mitigate them using discrete event simulation. A two-week period of data collection is conducted in an outpatient clinic of a Singapore government hospital. Detailed time study from patient arrival to patient departure is conducted, and the possible factors causing long patient waiting time/clinic overtime are discussed. A discrete simulation model is constructed to illustrate how to improve the clinic performance by mitigating the detected factors. Simulation and implementation results show that significant improvement is achieved if the factors are well addressed.     

定制医疗器械增材制造的负载均衡进化调度方法

目的/意义 提出并利用负载均衡进化调度方法,缩短定制医疗器械增材制造生产活动中的等待时间、均衡各机器负载。方法/过程 通过分析时间维度下的影响因素,建立双目标多约束优化问题的数学模型,引入负载均衡算子,采用负载均衡进化调度算法求解模型。结果/结论 含有负载均衡算子的负载均衡进化调度方法在任务等待时间和负载均衡性能方面优于其他算法,特别是在大规模任务下效果显著。该方法能够有效缩短任务等待时间并实现机器负载均衡。     

A randomized controlled trial of academic group practice. Improving the operation of the medicine clinic

We conducted a controlled trial of the adoption of a group-practice model within an academic department of medicine. Ongoing randomization yielded similar groups of patients and residents. To determine the effect of the intervention on medicine-clinic operation, we monitored the hospital outpatient activity of 28 residents and 2299 patients during an 11-month study period. The group-practice clinics generated 20% more patient encounters per month than did the traditional, control clinics (328 vs 273 encounters), primarily because twice as many voluntary, overflow clinic sessions were scheduled (20.2 vs 9.7 sessions). Yet, because group-practice registration was decentralized, patients spent 15% less time in completing scheduled visits (93.2 vs 109.9 minutes). Regular utilizers of the group practices made 7% more scheduled clinic visits on average (3.27 vs 3.05 visits), but 39% fewer walk-in visits (0.14 vs 0.23 visits). Hospital-wide, continuity of care was not affected. We conclude that adoption of a group-practice model at our institution improved clinic productivity, enhanced patient flow, and decreased unscheduled clinic visits.     

Surgery dot.com: the quality of information disseminated by Web-based waiting time information services

OBJECTIVES: To assess Web-based waiting time information services to identify how they aimed to meet the information needs of patients and general practitioners, and to evaluate how well waiting time information was presented. DESIGN: A cross-sectional survey of six government websites in English-speaking countries with publicly funded hospitals. Sites were evaluated on the clarity of instructions about how their information should be used, and the accuracy of the statistics they contained was assessed indirectly using methodological criteria. RESULTS: The services were judged to encourage GPs and patients to use the statistics to avoid surgical units with long waiting times, but overall advice was poor. Services did not state whether the statistics predicted expected waiting times, and just one stated that the statistics were only intended as a guide. Statistics were based on different types of data, and derived at different levels of aggregation, raising questions of accuracy. Most sites explained waiting list terms, but provided inadequate advice on the uncertainty associated with making statistical inferences. CONCLUSIONS: GPs and patients should use Web-based waiting time information services cautiously because of a lack of guidance on how to appropriately interpret the presented information.     

Waiting list statistics. III. Comparison of two measures of waiting times

The length of time that patients spend on waiting lists is a topic of current concern. Calculating the proportion of patients who have been on a waiting list for a long time by taking a census of patients on the list at a single point in time will tend to yield a higher estimate than that obtained by calculating waiting times of patients admitted to hospital during a period of time. To illustrate this point the waiting times of patients in the Oxford region as measured by SBH 203 returns ("census" data) were compared with those as measured by the Hospital Activity Analysis ("event" data). As expected, the SBH 203 census returns showed a higher proportion of patients who had waited over a year compared with the "event" measure of all admissions. This difference, which is analagous to the difference between prevalence and incidence in epidemiology, should be considered when using data from these sources to calculate waiting times.     

A Proposed Scheduling Model To Improve Use of Computed Tomography Facilities

A nonpreemptive queuing system based upon operations management theory is used to evaluate expected steady state wait periods for traditional and distributed CT scheduling models. Both models are constructed using two classes of patient service—emergent and nonemergent. The former model uses only one point of service per scanner while the latter employs multiple points of service in order to accomplish all of the functions necessary to complete a CT scan. Sample data are drawn from a tertiary care hospital-based system using a traditional service model. Comparison of a traditional and distributed service system, each with emergent and nonemergent service classes, shows that breaking as many activities as possible out of the scanner should provide substantial improvements in cost efficiency and service for patients having CT scans. Nonemergent patients may experience as much as an 89% reduction in steady-state wait times while emergent patients may experience as much as a 59% reduction in wait times. The cost efficiencies recognized either through increased scanner utilization or reduced scanner needs, even with only modest improvements, should more than offset any additional personnel needed to implement a distributed model. Proper implementation of a distributed scheduling model for CT scanning can provide substantial cost efficiencies and improvements in service for both nonemergent and emergent CT scans.     

An Evaluation of Patients’ Opinions of Primary Care Physicians: the Use of EUROPEP in Gaza Strip-Palestine

The objective of this paper is to identify the level of patients' satisfaction with primary care physicians. Data were gathered from an exit interview using a standardized questionnaire (EUROPEP) and background variables. A total of 956 patients in fifteen primary health care clinics in Gaza Strip participated. Outcome measures is positive patient satisfaction (good and excellent ratings in the EUROPEP Index). As a results, the mean percentage of positive satisfaction with medical services was poor (41.8%). The poorest performance was recorded for: getting through to the clinic on the phone, being able to speak to physician on the telephone, time spent in waiting rooms and helping the patient deal with emotional problems. The comparison between clinical behaviour dimension and organization of care showed that clinical behaviour was evaluated higher. In conclusion, Palestinian patients expressed overall dissatisfaction with services provided by primary care physicians. These findings present a real challenge for Palestinian authority policy makers and administrators in terms of designing appropriate quality improvement strategies.     

Effect of Anesthesia Staffing Ratio on First-Case Surgical Start Time

On time start of the first case of the day is an important operating room (OR) efficiency metric, in which delays can have effects throughout the day. Although previous studies have identified various causes of first case start delays, none have attempted to evaluate the effect anesthesia staffing ratios have on first case start times. We performed a single-center retrospective analysis at an academic teaching hospital. Data was collected and analyzed over a period of 4 years and on more than 8,700 cases. We examined whether staffing ratios of attending only (solo staffing ratio), attending working with 1 resident/certified registered nurse anesthetist (CRNA) (1 to 1), or attending covering 2 residents/CRNAs (1 to 2) had a significant effect on first patient in room time (FPIR) and first case on time start (FCOTS). In addition, we examined whether staffing ratios had an effect on start times in various surgical subspecialties. We performed a univariate logistic regression analysis to determine if age, anesthesia base units, American Society of Anesthesiologists Physical Status (ASA PS) classification score, and staffing ratio was associated with FPIR and FCOTS being on time. Then, we performed a multivariate logistic regression analysis to determine if staffing ratio was associated with these outcomes, utilizing age, anesthesia base units, and ASA PS class as covariates. A decreased odds for FPIR being on time were seen in general and orthopedic surgeries when staffed 1 to 1, and cardiac surgery when staffed 1 to 2, when compared to solo staffing. FCOTS showed statistically significant differences when looking at all services with solo staffing having the highest odds for FCOTS being on time. This effect was seen also when analyzing only oncologic and orthopedic surgeries. Hospitals should consider using different staffing ratios in different surgical specialties to minimize delays and maximize OR efficiency.     

A System-Wide Approach to Physician Efficiency and Utilization Rates for Non-Operating Room Anesthesia Sites

There has been little in the development or application of operating room (OR) management metrics to non-operating room anesthesia (NORA) sites. This is in contrast to the well-developed management framework for the OR management. We hypothesized that by adopting the concept of physician efficiency, we could determine the applicability of this clinical productivity benchmark for physicians providing services for NORA cases at a tertiary care center. We conducted a retrospective data analysis of NORA sites at an academic, rural hospital, including both adult and pediatric patients. Using the time stamps from WiseOR® (Palo Alto, CA), we calculated site utilization and physician efficiency for each day. We defined scheduling efficiency (SE) as the number of staffed anesthesiologists divided by the number of staffed sites and stratified the data into three categories (SE < 1, SE = 1, and SE >1). The mean physician efficiency was 0.293 (95% CI, [0.281, 0.305]), and the mean site utilization was 0.328 (95% CI, [0.314, 0.343]). When days were stratified by scheduling efficiency (SE < 1, =1, or >1), we found differences between physician efficiency and site utilization. On days where scheduling efficiency was less than 1, that is, there are more sites than physicians, mean physician efficiency (95% CI, [0.326, 0.402]) was higher than mean site utilization (95% CI, [0.250, 0.296]). We demonstrate that scheduling efficiency vis-à-vis physician efficiency as an OR management metric diverge when anesthesiologists travel between NORA sites. When the opportunity to scale operational efficiencies is limited, increasing scheduling efficiency by incorporating different NORA sites into a “block” allocation on any given day may be the only suitable tactical alternative.