The acceptability of waiting times for elective general surgery and the appropriateness of prioritising patients

Time to elective surgery and its predictors after first cancellation at Debremarkos Comprehensive Specialized Hospital, Northwest Ethiopia

Canceling elective surgical procedures is quite common throughout Ethiopia. Despite this, there is limited evidence about the time to elective surgery after cancellation in the country. Thus, the current study aimed to determine the time to elective surgery and its predictors after the first cancellation. An institution-based retrospective follow-up study was conducted on 386 study participants at Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia, between September 1, 2017, and August 31, 2022. Utilizing a checklist, data were retrieved. To choose study participants, systematic random sampling was employed. Epi-Data version 3.1 and STATA version 14.1 were utilized. Kaplan-Meier curves and log-rank tests were employed. The Cox proportional hazard model was fitted. The mean age of the participants was 41.01 + 18.61 years. Females made up 51% of the patients. The majority were illiterate (72.3%) and resided in rural areas (70.5%). Surgery following the first cancellation had a cumulative incidence of 83.6% (95% CI: 79.6, 87.05) and an incidence rate of 32.3 per 1,000 person-days (95% CI: 29.3, 35.5). The median survival time to surgery was 25 (IQR: 17-40) days. Urban residence (AHR = 1.62; 95% CI: 1.26-1.96), being a member of health insurance schemes (AHR = 1.55; 95% CI: 1.24-1.96), stable other medical conditions (AHR = 1.43; 95% CI: 1.13-1.79), and timely completion of diagnostic tests (AHR = 1.62; 95% CI: 1.29-2.04) were significant predictors of time to surgery after first cancellation. Our study revealed that the time to surgery after the first cancellation was in the globally acceptable range and met the national target. Clinicians should focus on timely completion of diagnostic or laboratory tests, facilitating health insurance coverage, and comprehensive assessment and treatment of any coexisting medical conditions. It is urged to stratify each department's time for surgery, taking into consideration of important variables.

A Delphi study to explore clinician and lived experience perspectives on setting priorities in eating disorder services

Background

Due to scarce resources and high demand, priority setting in mental health services is necessary and inevitable. To date, no study has examined priority setting in eating disorder (ED) services specifically. Here, we evaluate the level of consensus and perceived relative importance of factors used to determine patient prioritisation in ED services, amongst clinicians and individuals with lived experience (LE) of an ED.

Methods

A three round Delphi study and a ranking task were used to determine the level of consensus and importance. Consensus was defined as > 80% agreement or disagreement. Items that reached consensus for agreement were ranked in order of importance from most to least important. Participants were 50 ED clinicians and 60 LE individuals. Participant retention across rounds 2, 3, and 4 were 92%, 85%, and 79%, respectively.

Results

Over three iterative rounds, a total of 87 statements about patient prioritisation were rated on a 5-point Likert-scale of agreement. Twenty-three items reached consensus in the clinician panel and 20 items reached consensus in the LE panel. The pattern of responding was broadly similar across the panels. The three most important items in both panels were medical risk, overall severity, and physical health deteriorating quickly. Clinicians tended to place greater emphasis on physical risk and early intervention whereas the LE panel focused more on mental health and quality of life.

Conclusions

Eating disorder services tend to prioritise patients based upon medical risk and severity, and then by the order in which patients are referred. Our findings align in some respects with what is observed in services, but diverge in others (e.g., prioritising on quality of life), providing important novel insights into clinician and LE opinions on waiting list prioritisation in EDs. More research is warranted to validate these findings using multi-criterion decision techniques and observational methods. We hope these findings provide a foundation for future research and encourage evidence-based conversations around priority setting in ED services.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08170-4.

Developing a prioritisation framework for patients in need of coronary artery angiography

BACKGROUND

Effective waiting list management and comprehensive prioritisation can provide timely delivery of appropriate services to ensure that the patient needs are met and increase equity in the provision of health services. We developed a prioritisation framework for patients in need of coronary artery angiography (CAA).

METHODS

We used a multi-methods approach to elicit effective factors that affect CAA patient prioritisation. Qualitative data wase collected using semi-structured interviews with 15 experts. The final set of factors was selected using experts' consensus through modifed Delphi technique. The framework was finalised during expert panel meetings.

RESULTS

212 effective factors were identified based on the literature review, interviews, and expert panel discussion of them, 37 factors were selected for modifed Delphi study. Following two rounds of Delphi discussions, seven final factors were selected and weighed by ten experts using pair-wise comparisons. The following weights were given: the severity of pain and symptoms (0.22), stress testing (0.18), background diseases (0.15), number of myocardial infarctions (0.15), waiting time (0.10), reduction of economic and social performance (0.12), and special conditions (0.08).

CONCLUSION

Clinical effective factors were important for CAA prioritisation framework. Using this framework can potentially lead to improved accountability and justice in the health system.

Patients’ Prioritization on Surgical Waiting Lists: A Decision Support System

Currently, in Chile, more than a quarter-million of patients are waiting for an elective surgical intervention. This is a worldwide reality, and it occurs as the demand for healthcare is vastly superior to the clinical resources in public systems. Moreover, this phenomenon has worsened due to the COVID-19 sanitary crisis. In order to reduce the impact of this situation, patients in the waiting lists are ranked according to a priority. However, the existing prioritization strategies are not necessarily systematized, and they usually respond only to clinical criteria, excluding other dimensions such as the personal and social context of patients. In this paper, we present a decision-support system designed for the prioritization of surgical waiting lists based on biopsychosocial criteria. The proposed system features three methodological contributions; first, an ad-hoc medical record form that captures the biopsychosocial condition of the patients; second, a dynamic scoring scheme that recognizes that patients’ conditions evolve differently while waiting for the required elective surgery; and third, a methodology for prioritizing and selecting patients based on the corresponding dynamic scores and additional clinical criteria. The designed decision-support system was implemented in the otorhinolaryngology unit in the Hospital of Talca, Chile, in 2018. When compared to the previous prioritization methodology, the results obtained from the use of the system during 2018 and 2019 show that this new methodology outperforms the previous prioritization method quantitatively and qualitatively. As a matter of fact, the designed system allowed a decrease, from 2017 to 2019, in the average number of days in the waiting list from 462 to 282 days.

Improving access to services for psychotic patients: does implementing a waiting time target make a difference

OBJECTIVE

In April 2015, the English National Health Service started implementing the first waiting time targets in mental health care. This study aims to investigate the effect of the 14-day waiting time target for early intervention in psychosis (EIP) services after the first six months of its implementation.

STUDY DESIGN

We analyse a cohort of first-episode psychosis patients from the English administrative Mental Health and Learning Disabilities Dataset 2011 to 2015. We compare patients being treated by EIP services (treatment) with those receiving care from standard community mental health services (control). We combine non-parametric matching with a difference-in-difference approach to account for observed and unobserved group differences. We analyse the probability of waiting below target and look at different percentiles of the waiting time distribution.

RESULTS

EIP patients had an 11.6-18.4 percentage point higher chance of waiting below target post-policy compared to standard care patients. However, post-policy trends at different percentiles of the waiting time distribution were not different between groups.

CONCLUSIONS

Mental health providers seem to respond to waiting time targets in a similar way as physical health providers. The increased proportion waiting below target did not, however, result in an overall improvement across the waiting time distribution.

Long Waiting Times for Elective Hospital Care - Breaking the Vicious Circle by Abandoning Prioritisation

Background: Policies assigning low-priority patients treatment delays for care, in order to make room for patients of higher priority arriving later, are common in secondary healthcare services today. Alternatively, each new patient could be granted the first available appointment. We aimed to investigate whether prioritisation can be part of the reason why waiting times for care are often long, and to describe how departments can improve their waiting situation by changing away from prioritisation.

Methods: We used patient flow data from 2015 at the Department of Otorhinolaryngology, Haukeland University Hospital, Norway. In Dynaplan Smia, Dynaplan AS, dynamic simulations were used to compare how waiting time, size and shape of the waiting list, and capacity utilisation developed with and without prioritisation. Simulations were started from the actual waiting list at the beginning of 2015, and from an empty waiting list (simulating a new department with no initial patient backlog).

Results: From an empty waiting list and with capacity equal to demand, waiting times were built 7 times longer when prioritising than when not. Prioritisation also led to poor resource utilisation and short-lived effects of extra capacity. Departments where prioritisation is causing long waits can improve their situation by temporarily bringing capacity above demand and introducing "first come, first served" instead of prioritisation.

Conclusion: A poor appointment allocation policy can build long waiting times, even when capacity is sufficient to meet demand. By bringing waiting times down and going away from prioritisation, the waiting list size and average waiting times at the studied department could be maintained almost 90% below the current level – without requiring permanent change in the capacity/demand ratio.

Complications While Waiting for IBD Surgery-Short Report

BACKGROUND AND AIMS

While striving to meet the quality standards for oncological care, hospitals frequently prioritize oncological procedures, resulting in longer waiting times to surgery for benign diseases like inflammatory bowel disease [IBD]. The aim of this Short Report is to highlight the potential consequences of a longer interval to surgery for IBD patients.

METHODS

The mean waiting times to elective surgery for IBD patients with active and inactive disease [e.g. pouch surgery after subtotal colectomy] at the Amsterdam UMC, location AMC, between 2013 and 2015 were compared with those for colorectal cancer surgery. Correlations between IBD waiting times and disease complications [e.g. >5% weight loss, abscess formation] and additional health-care consumption [e.g. telephone/outpatient clinic appointment, hospital admission] during these waiting times were assessed.

RESULTS

The mean waiting was 10 weeks [SD 8] for patients with active disease [n = 173] and 15 weeks [SD 16] for those with inactive disease [n = 97], remarkably higher than that for colorectal cancer patients [5 weeks]. While awaiting surgery, 1 out of 8 patients had to undergo surgery in an acute or semi-acute setting. Additionally, 19% of patients with active disease had disease complications, and 44% needed additional health care. The rates were comparable for patients with inactive disease.

CONCLUSIONS

The current waiting time to surgery is not medically justified and creates a burden for health-care resources. This issue should be brought to the attention of policy makers, as it requires a structural solution. It is time to also set a maximally acceptable waiting time to surgery for IBD patients.

Specific timely appointments for triage to reduce wait times in a medical outpatient clinic: protocol of a pre-post study with process evaluation

Background

Managing demand for services is a problem in many areas of healthcare, including specialist medical outpatient clinics. Some of these clinics have long waiting lists with variation in access for referred people. A model of triage and appointment allocation has been developed and tested that has reduced waiting times by about a third in community outpatient services. This study aims to determine whether the model can be applied in the setting of a specialist medical outpatient clinic to reduce wait time from referral to first appointment.

Methods

A pre-post study will collect data before and after implementing the Specific Timely Appointments for Triage (STAT) model of access and triage. The study will incorporate a pre-implementation period of 12 months, an implementation period of up to 6 months and a post STAT-implementation period of 6 months. The setting will be the epilepsy clinic at a metropolitan health service in Melbourne. Included will be all people referred to the clinic, or currently waiting, during the allocated periods of data collection (total sample estimated n = 975). Data routinely collected by the health service and qualitative data from staff will be analysed to determine the effects of introducing the STAT model. The primary outcome will be wait time, measured by number of patients on the wait list at monthly time points and the mean number of days waited from referral to first appointment. Secondary outcomes will include patient outcomes, such as admission to hospital while waiting, and service outcomes, including rate of discharge. Analysis of the primary outcome will include interrupted time series analysis and simple comparisons of the pre and post-implementation periods. Process evaluation will include investigation of the fidelity of the intervention, adaptations required and qualitative analysis of the experiences of clinic staff.

Discussion

Prompt access to service and optimum patient flow is important for patients and service providers. Testing the STAT model in a specialist medical outpatient clinic will add to the evidence informing service providers and policy makers about how the active management of supply and demand in health care can influence wait times. The results from this study may be applicable to other specialist medical outpatient clinics, potentially improving access to care for many people.

A model of access combining triage with initial management reduced waiting time for community outpatient services: a stepped wedge cluster randomised controlled trial

BACKGROUND

Long waiting times are associated with public community outpatient health services. This trial aimed to determine if a new model of care based on evidence-based strategies that improved patient flow in two small pilot trials could be used to reduce waiting time across a variety of services. The key principle of the Specific Timely Appointments for Triage (STAT) model is that patients are booked directly into protected assessment appointments and triage is combined with initial management as an alternative to a waiting list and triage system.

METHODS

A stepped wedge cluster randomised controlled trial was conducted between October 2015 and March 2017, involving 3116 patients at eight sites across a major Australian metropolitan health network.

RESULTS

The intervention reduced waiting time to first appointment by 33.8% (IRR = 0.663, 95% CI 0.516 to 0.852, P = 0.001). Median waiting time decreased from a median of 42 days (IQR 19 to 86) in the control period to a median of 24 days (IQR 13 to 48) in the intervention period. A substantial reduction in variability was also noted. The model did not impact on most secondary outcomes, including time to second appointment, likelihood of discharge by 12 weeks and number of appointments provided, but was associated with a small increase in the rate of missed appointments.

CONCLUSIONS

Broad-scale implementation of a model of access and triage that combined triage with initial management and actively managed the relationship between supply and demand achieved substantial reductions in waiting time without adversely impacting on other aspects of care. The reductions in waiting time are likely to have been driven, primarily, by substantial reductions for those patients previously considered low priority.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12615001016527 registration date: 29/09/2015.

An innovative approach to improve ear, nose and throat surgical access for remote living Cape York Indigenous children

INTRODUCTION

On a background of high rates of severe otitis media (OM) with associated hearing loss, children from the Torres Strait and Cape York region requiring ear, nose and throat (ENT) surgery, faced waiting times exceeding three years. After numerous clinical safety incidents were raised, indicating a failure of the current system to deliver appropriate care, the governing Hospital and Health service opted to deliver surgical care through an alternate process. ENT surgeries were performed on 16 consented children from two remote locations via the private health care system, funded by a health provider partnership.

METHODS

We examined the collaboration processes alongside clinical findings from this ENT surgery. Collated patient data, included patient demographics, clinical and audiometry presentation features were reviewed and compared pre and post-operatively. Cost savings associated with the use of TeleHealth post-operatively were briefly examined.

RESULTS

Surgeries were successfully completed in all 16 children. The reported mean waitlist time for ENT surgery was 1.2 years. Pre-surgery pure-tone average hearing thresholds were reported at left: 30.9 dB, right: 38.2 dB. The majority of presentations were for bilateral OM with Effusion (69%). Post-surgical follow up indicated successful clinical outcomes in 80% of patients and successful hearing outcomes in 88% of patients. Mean difference pure-tone average hearing thresholds, left: 8.4 dB and right: 11.2 dB. Furthermore, the majority of patients reported improved hearing and breathing. The use of TeleHealth for post-operative review enabled a minimum cost saving of AUD$21,664 for these 16 children. Overall, a high level of staffing resources was required to successfully coordinate this intense surgical activity.

CONCLUSION

This innovative approach to a health system crisis enabled successful ENT surgical and hearing outcomes in 16 children, whose waitlisted time grossly exceeded state health recommendations. Using private health facilities funded by a health partnership, while unlikely to be a suitable model of care for routine service delivery; may be applied as an adjunct service model when blockages and delays lead to sub-standard service provision. This approach may be applicable to other health care facilities when facing extended elective surgery wait times in ENT or other specialty areas.

Surgical waiting times and patient choice: how much delay do patients really want?

BACKGROUND

The 18-week target to treatment government initiative was implemented in 2004. In order for this to work, patients need to accept operative dates provided, otherwise the pathway will fail.

AIM

The aim of this prospective study was to identify the earliest time patients would accept surgical intervention following assessment at an outpatient clinic and to identify the reasons why some patients would choose to delay surgery.

METHODS

This prospective study was carried out at an elective orthopaedic centre over a 5-month period. All new adult referrals to the department were asked to complete a seven-point questionnaire on waiting time preference and possible reasons for delaying surgery. No paediatric or spinal orthopaedics was carried out at the centre.

RESULTS

A total of 73 % of the 797 questionnaires were completed. Up to 16 % of patients could not accept day-case/inpatient operation within 6 weeks. Work commitment was the most common reason for choosing to delay surgery, with nearly 50 % of employed patients citing it as a reason. No significant difference was identified between inpatient and day-case procedures.

CONCLUSION

There is a risk that operative slots will be unfilled within the 18-week pathway. 18 % of patients will potentially refuse an operative date offered within 6 weeks of their outpatient visit. Work, holidays and care arrangements are important in uptake. A proactive strategy to improve the uptake of offered surgery is required to prevent operating slots being underutilised.

Short-term gain for long-term pain? Which patients should be treated and should we ration?

Objectives:

Treatments of common conditions which do not affect mortality often become sidelined in the drive to improve efficiency and reduce costs. The rationing of patients is a divisive but crucial component to universal health care. How should this be accomplished?

Methods and Results:

In this article we examine the outcomes of various rationing methods in varicose veins.

Conclusions:

No method is perfect and treatment of symptoms and complications should remain the target for all physicians.

Achieving waiting list reform: a pilot program integrating waiting time, category and patient factors

Equity in resource allocation is central to the tenet of social justice in health care. The management of surgical waiting lists is of critical importance to clinicians, patients and regulators. In most hospital environments, the basic process has remained unchanged for decades. Patients are assigned to one of three urgency-related categories. Clinicians consequently administer three competing patient pools. The basis by which patients are selected for treatment may be difficult to define. The specific clinical circumstances of each patient are often unreported and may be unknown to those administering the list. Waiting list bias is also recognised. This may reflect clinician advocacy, pressure to meet category timeframe restrictions or perceived training requirements. In this environment, it is difficult to demonstrate propriety in care. We report the implementation of a pilot program to redesign waiting list management within a South Australian public hospital unit. This allows assemblage of patients into a single list. Overall priority is determined by balancing clinical acuity and waiting time. The determination of acuity takes into account both the primary category and the specific characteristics of each patient that are relevant to their intended procedure. Uniquely, the process is applicable to lists containing patients with dissimilar conditions. This paper reviews the limitations of current approaches in meeting reasonable community expectations. The principles and social justification underpinning this reform are introduced. Finally, the benefits offered by the program are discussed and interim results are reported.

Waiting for surgery from the patient perspective

The aim of this study was to perform a systematic review of the impact of waiting for elective surgery from the patient perspective, with a focus on maximum tolerance, quality of life, and the nature of the waiting experience. Searches were conducted using Medline, PubMed, CINAHL, EMBASE, and HealthSTAR. Twenty-seven original research articles were identified which included each of these three themes. The current literature suggested that first, patients tend to state longer wait times as unacceptable when they experienced severe symptoms or functional impairment. Second, the relationship between length of wait and health-related quality of life depended on the nature and severity of proposed surgical intervention at the time of booking. Third, the waiting experience was consistently described as stressful and anxiety provoking. While many patients expressed anger and frustration at communication within the system, the experience of waiting was not uniformly negative. Some patients experienced waiting as an opportunity to live full lives despite pain and disability. The relatively unexamined relationship between waiting, illness and patient experience of time represents an area for future research.

'There are too many of us to fix.' Patients' views of acceptable waiting times for hip and knee replacement

OBJECTIVES

To assess patients' views of maximum acceptable waiting times (MAWT) for hip and knee replacement, associated factors and the accuracy of self-reported waiting times.

METHODS

We mailed 1000 questionnaires each to two random samples of patients either waiting for or who had received an arthroplasty within the preceding 3-12 months. We used linear regression to assess the determinants of patient MAWT, and content analysis to assess reasons for MAWT and ideal waiting time.

RESULTS

Of the 1330 responses, 1127 had MAWT data. The sample was 57% women; mean age was 70 +/- 11 years. Median self-reported and actual waiting time was eight months (Spearman correlation = 0.70). Median MAWT was four months and ideal waiting time was two months. The most frequent reasons for MAWT were pain, quality of life and needing time to prepare for surgery. A longer MAWT was associated with younger age, group (waiting), a longer self-reported waiting time, better EQ-5D index, an acceptable waiting time, a perception of fairness and a view that others worse off on the list should go ahead.

CONCLUSIONS

Patients' views of acceptable waiting times are important for a fair process of establishing waiting time benchmarks for joint replacement.

Interventions for uncomplicated varicose veins

Objective

To review the evidence regarding interventions (compression, sclerotherapy, surgery and endoluminal) for uncomplicated venous disease.

Method

A literature search of MEDLINE and EMBASE was performed. In addition, bibliographies of published data and the Cochrane Peripheral Vascular Review Group Specialist Register were examined. Publications describing an intervention for uncomplicated venous disease or trials comparing one intervention against another were considered.

Results

Uncomplicated but symptomatic varicose veins are associated with a significant reduction in quality of life (QoL). Evaluation must include a detailed history and examination supported by non-invasive imaging. Although HHD is useful, its utility is limited in the popliteal fossa. It can not provide morphological/anatomical detail when considering an endoluminal treatment option. Regardless of intervention, all treatments considered are associated with a significant improvement in QoL at acceptable cost.

Conclusion

Uncomplicated symptomatic varicose veins lead to a reduced QoL, which can be significantly improved by all interventions considered.

A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time

Background

Prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery.

Methods

In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API).

Results

The SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT.

Conclusion

The SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.

Eqüidade no tempo de espera para determinadas cirurgias eletivas segundo o tipo de hospital em Sorocaba, SP

INTRODUÇÃO: A eqüidade na atenção à saúde tem sido alvo de grande preocupação, incluindo países em desenvolvimento e desenvolvidos. A eqüidade horizontal, entendida como tratamento igual de indivíduos que se encontram na mesma situação de saúde, tem sido investigada nos diferentes níveis de atenção à saúde. OBJETIVOS: O presente estudo busca verificar se existem disparidades no tempo de espera para cirurgias eletivas (safenectomia, colecistectomia, hemorroidectomia e histerectomia) segundo o tipo de hospital, público ou privado. METODOLOGIA: Realizou-se, em Sorocaba, um estudo transversal com 40 pacientes atendidos por hospital privado e 40 atendidos por hospital público, no período de outubro e novembro de 2005. Além do tempo de espera e tipo de hospital, foram pesquisados sexo, idade, escolaridade, renda, situação conjugal, procedência, tipo de cirurgia realizada e presença de determinadas comorbidades. RESULTADOS: Observou-se um tempo de espera maior nas categorias: hospital público (5,5 meses; p<0,001), baixa escolaridade (3,5 meses; p<0,001), menor renda (Spearman=-0,4426; p<0,001), procedência de outros municípios (2 meses; p=0,009), e cirurgia de safenectomia (5 a 7 meses; p=0,04). Após o ajuste para as variáveis comorbidade, renda, escolaridade ou procedência, o tempo de espera no hospital público se manteve significantemente maior (diferença mínima de 4,93 meses quando ajustada por renda; IC95% 3,4-6,4; p<0,001). CONCLUSÃO: Verifica-se relevante iniqüidade na atenção à saúde relacionada ao tipo de prestador de serviços de saúde.