scholarly journals Measurement of surgical wait times in a universal health care system

2008 ◽  
Vol 2 (6) ◽  
pp. 597 ◽  
Author(s):  
Jun Kawakami ◽  
Wilma M. Hopman ◽  
Rachael Smith-Tryon ◽  
D. Robert Siemens
Keyword(s):  
Health Care ◽  
Multivariate Analysis ◽  
Real Time ◽  
Access To Health Care ◽  
A Priori ◽  
Wait Time ◽  
Administrative Databases ◽  
Wait Times ◽  
Data Set ◽  
Care Indicator

Introduction: Reported increases in surgical wait times for cancer have intensified the focus on this quality of health care indicator and have created a very public, concerted effort by providers to decrease wait times for cancer surgeryin Ontario. Delays in access to health care are multifactorial and their measurement from existing administrative databases can lack pertinent detail. The purpose of our study was to use a real-time surgery-booking software program to examine surgical wait times at a single centre.Methods: The real-time wait list management system Axcess.Rx has been used exclusively by the department of urology at the Kingston General Hospital to book all nonemergency surgery for 4 years. We reviewed the length of time from the decision to perform surgery to the actual date of surgery for patients in our group urological practice. Variables thought to be potentially important in predicting wait time were also collected, including the surgeon’s assessment of urgency, the type of procedure (i.e., diagnostic, minor cancer, major cancer, minor benign, major benign), age and sex of the patient, inpatient versus outpatient status and year of surgery. Analysis was planned a priori to determine factors that affected wait time by using multivariate analysis to analyze variables that were significant in univariate analysis.Results: There were 960 operations for cancer and 1654 for benign conditions performed during the evaluation period. The overall mean wait time was 36 days for cancer and 47 days for benign conditions, respectively. The mean wait time for cancer surgery reached a nadir in 2004 at 29.9 days and subsequently increased every year, reaching 56 days in 2007. In comparison, benign surgery reached a nadir wait time of 33.7 days in 2004 and in 2007 reached 74 days at our institution. Multivariate analysis revealed that the year of surgery was still a significant predictor of wait time. Urgency score, type of procedure and inpatient versus outpatient status were also predictive of wait time.Conclusion: The application of a prospectively collected data set is an effective and important tool to measure and subsequently examine surgical wait times. This tool has been essential to the accurate assessment of the effect of resource allocation on wait times for priority and nonpriority surgical programs within a discipline. Such tools are necessary to more fully assess and follow wait times at an institution or across a region.

scholarly journals P012: Why did you leave? Contacting left without being seen patients to understand their emergency department experience

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S61-S61
Author(s):  
B. Brar ◽  
J. Stempien ◽  
D. Goodridge
Keyword(s):  
Health Care ◽  
Wait Time ◽  
Wait Times ◽  
Average Wait Time ◽  
Left Without Being Seen ◽  
Care Processes ◽  
Time Period ◽  
Initial Interaction ◽  
Improving Health Care

Introduction: As experienced in Emergency Departments (EDs) across Canada, Saskatoon EDs have a percentage of patients that leave before being assessed by a physician. This Left Without Being Seen (LWBS) group is well documented and we follow the numbers closely as a marker of quality, what happens after they leave is not well documented. In Saskatoon EDs, if a CTAS 3 patient that has not been assessed by a physician decides to leave the physician working in the ED is notified. The ED physician will: try to talk to the patient and convince them to stay, can assess the patient immediately if required, or discuss other appropriate care options for the patient. In spite of this plan patients with a CTAS score of 3 or higher (more acute) still leave Saskatoon EDs without ever being seen by a physician. Our desire was to follow up with the LWBS patients and try to understand why they left the ED. Methods: Daily records from one of the three EDs in Saskatoon documenting patients with a CTAS of 3 or more acute who left before being seen by a physician were reviewed over an eight-month period. A nurse used a standardized questionnaire to call patients within a few days of their ED visit to ask why they left. If the patients declined to take part in the quality initiative the interaction ended, but if they agreed a series of questions was asked. These included: how long they waited, reasons why they left, if they went somewhere else for care and suggestions for improvement. Descriptive statistics were obtained and analyzed to answer the above questions. Results: We identified 322 LWBS patients in an eight-month time period as CTAS 3 or more acute. We were able to contact 41.6% of patients. The average wait time was 2 hours and 18 minutes. The shortest wait time was 11 minutes, whereas the longest wait time was 8 hours and 39 minutes. It was found that 49.1% of patients went to another health care option (Medi-Clinic or another ED in Saskatoon) within 24hrs of leaving the ED. Long wait times were cited as the number one reason for leaving. Lack of better communication from triage staff regarding wait time expectations was cited as the top response for perceived roadblocks to care. Reducing wait times was cited as the number one improvement needed to increase the likelihood of staying. Conclusion: The Saskatoon ED LWBS patient population reports long wait times as the main reason for leaving. In order to improve the LWBS rates, improving communication and expectations regarding perceived wait times is necessary. The patient perception of the ED experience is largely intertwined with wait times, their initial interaction with triage staff, and how easily they navigate our very busy departments. Therefore, it is vital that we integrate the patient voice in future initiatives geared towards improving health care processes.

scholarly journals A comparative study of patient characteristics, opinions, and outcomes, for patients who leave the emergency department before medical assessment

CJEM ◽  
2016 ◽  
Vol 19 (5) ◽  
pp. 347-354 ◽  
Author(s):  
Jacqueline Fraser ◽  
Paul Atkinson ◽  
Audra Gedmintas ◽  
Michael Howlett ◽  
Rose McCloskey ◽  
...  
Keyword(s):  
Health Care ◽  
Emergency Department ◽  
Performance Indicator ◽  
Medical Condition ◽  
Demographic Data ◽  
Family Doctor ◽  
Wait Time ◽  
Wait Times ◽  
Control Group ◽  
Fisher Exact Test

AbstractObjectiveThe emergency department (ED) left-without-being-seen (LWBS) rate is a performance indicator, although there is limited knowledge about why people leave, or whether they seek alternate care. We studied characteristics of ED LWBS patients to determine factors associated with LWBS.MethodsWe collected demographic data on LWBS patients at two urban hospitals. Sequential LWBS patients were contacted and surveyed using a standardized telephone survey. A matched group of patients who did not leave were also surveyed. Data were analysed using the Fisher exact test, chi-square test, and student t-test.ResultsThe LWBS group (n=1508) and control group (n=1504) were matched for sex, triage category, recorded wait times, employment and education, and having a family physician. LWBS patients were younger, more likely to present in the evening or at night, and lived closer to the hospital. A long wait time was the most cited reason for leaving (79%); concern about medical condition was the most common reason for staying (96%). Top responses for improved likelihood of waiting were shorter wait times (LWBS, 66%; control, 31%) and more information on wait times (41%; 23%). A majority in both groups felt that their condition was a true emergency (63%; 72%). LWBS patients were more likely to seek further health care (63% v. 28%; p<0.001) and sooner (median time 1 day v. 2-4 days; p=0.002). Among patients who felt that their condition was not a true emergency, the top reason for ED attendance was the inability to see their family doctor (62% in both groups).ConclusionLWBS patients had similar opinions, experiences, and expectations as control patients. The main reason for LWBS was waiting longer than expected. LWBS patients were more likely to seek further health care, and did so sooner. Patients wait because of concern about their health problem. Shorter wait times and improved communication may reduce the LWBS rate.

scholarly journals Potentials, challenges, and limitations of the analysis of administrative data on vascular limb amputations in health care

VASA ◽  
2020 ◽  
Vol 49 (2) ◽  
pp. 87-97 ◽  
Author(s):  
Endre Kolossváry ◽  
Tamás Ferenci ◽  
Tamás Kováts
Keyword(s):  
Health Care ◽  
Administrative Data ◽  
Access To Health Care ◽  
Claims Data ◽  
Data Extraction ◽  
Analytical Data ◽  
Extraction Methods ◽  
Administrative Databases ◽  
Methodological Problems ◽  
Administrative Data Analysis

Summary. Although more and more data on lower limb amputations are becoming available by leveraging the widening access to health care administrative databases, the applicability of these data for public health decisions is still limited. Problems can be traced back to methodological issues, how data are generated and to conceptual issues, namely, how data are interpreted in a multidimensional environment. The present review summarised all of the steps from converting the claims data of administrative databases into the analytical data and reviewed the wide array of sources of potential biases in the analysis of such data. The origins of uncertainty of administrative data analysis include uncontrolled confounding due to a lack of clinical data, the left- and right-censored nature of data collection, the non-standardized diagnosis/procedure-based data extraction methods (i.e., numerator/denominator problems) and additional methodological problems associated with temporal and spatial analyses. The existence of these methodological challenges in the administrative data-based analysis should not deter the analysts from using these data as a powerful tool in the armamentarium of clinical research. However, it must be done with caution and a thorough understanding and respect of the methodological limitations. In addition to this requirement, there is a profound need for pursuing further research on methodology and widening the search for other indicators (structural, process or outcome) that allow a deeper insight how the quality of vascular care may be assessed. Effective research using administrative data is based on strong collaboration in three domains, namely expertise in claims data handling and processing, the clinical field, and statistical analysis. The final interpretations of results and the countermeasures on the level of vascular care ought to be grounded on the integrity of research, open discussions and institutionalized mechanisms of science arbitration and honest brokering.

scholarly journals Optimizing Outpatient Phlebotomy Staffing: Tools to Assess Staffing Needs and Monitor Effectiveness

2014 ◽  
Vol 138 (7) ◽  
pp. 929-935 ◽  
Author(s):  
Aleksandar S. Mijailovic ◽  
Milenko J. Tanasijevic ◽  
Ellen M. Goonan ◽  
Rachel D. Le ◽  
Jonathan M. Baum ◽  
...  
Keyword(s):  
Health Care ◽  
Wait Time ◽  
Data Driven ◽  
Wait Times ◽  
Service Capacity ◽  
Staffing Levels ◽  
Number Of Patients ◽  
Patient Wait Time ◽  
Staffing Needs ◽  
Improve Patient

Context.—Short patient wait times are critical for patient satisfaction with outpatient phlebotomy services. Although increasing phlebotomy staffing is a direct way to improve wait times, it may not be feasible or appropriate in many settings, particularly in the context of current economic pressures in health care. Objective.—To effect sustainable reductions in patient wait times, we created a simple, data-driven tool to systematically optimize staffing across our 14 phlebotomy sites with varying patient populations, scope of service, capacity, and process workflows. Design.—We used staffing levels and patient venipuncture volumes to derive the estimated capacity, a parameter that helps predict the number of patients a location can accommodate per unit of time. We then used this parameter to determine whether a particular phlebotomy site was overstaffed, adequately staffed, or understaffed. Patient wait-time and satisfaction data were collected to assess the efficacy and accuracy of the staffing tool after implementing the staffing changes. Results.—In this article, we present the applications of our approach in 1 overstaffed and 2 understaffed phlebotomy sites. After staffing changes at previously understaffed sites, the percentage of patients waiting less than 10 minutes ranged from 88% to 100%. At our previously overstaffed site, we maintained our goal of 90% of patients waiting less than 10 minutes despite staffing reductions. All staffing changes were made using existing resources. Conclusions.—Used in conjunction with patient wait-time and satisfaction data, our outpatient phlebotomy staffing tool is an accurate and flexible way to assess capacity and to improve patient wait times.

scholarly journals Canadian Consensus on Medically Acceptable Wait Times for Digestive Health Care

2006 ◽  
Vol 20 (6) ◽  
pp. 411-423 ◽  
Author(s):  
William G Paterson ◽  
William T Depew ◽  
Pierre Paré ◽  
Denis Petrunia ◽  
Connie Switzer ◽  
...  
Keyword(s):  
Health Care ◽  
Digestive Disease ◽  
Access To Health Care ◽  
Colonic Polyps ◽  
Signs And Symptoms ◽  
Wait Times ◽  
Future Health ◽  
Specialist Consultation ◽  
Screening And Surveillance ◽  
Disease Specialist

BACKGROUND: Delays in access to health care in Canada have been reported, but standardized systems to manage and monitor wait lists and wait times, and benchmarks for appropriate wait times, are lacking. The objective of the present consensus was to develop evidence- and expertise-based recommendations for medically appropriate maximal wait times for consultation and procedures by a digestive disease specialist.METHODS: A steering committee drafted statements defining maximal wait times for specialist consultation and procedures based on the most common reasons for referral of adult patients to a digestive disease specialist. Statements were circulated in advance to a multidisciplinary group of 25 participants for comments and voting. At the consensus meeting, relevant data and the results of voting were presented and discussed; these formed the basis of the final wording and voting of statements.RESULTS: Twenty-four statements were produced regarding maximal medically appropriate wait times for specialist consultation and procedures based on presenting signs and symptoms of referred patients. Statements covered the areas of gastrointestinal bleeding; cancer confirmation and screening and surveillance of colon cancer and colonic polyps; liver, biliary and pancreatic disorders; dysphagia and dyspepsia; abdominal pain and bowel dysfunction; and suspected inflammatory bowel disease. Maximal wait times could be stratified into four possible acuity categories of 24 h, two weeks, two months and six months.FUTURE DIRECTIONS: Comparison of these benchmarks with actual wait times will identify limitations in access to digestive heath care in Canada. These recommendations should be considered targets for future health care improvements and are not clinical practice guidelines.

scholarly journals Wait times for psychiatric care in Ontario

2017 ◽  
Vol 86 (2) ◽  
pp. 48-50
Author(s):  
Rachel Loebach ◽  
Sasha Ayoubzadeh
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Health Care ◽  
Psychiatric Inpatient ◽  
Wait Time ◽  
Mandatory Reporting ◽  
Psychiatric Services ◽  
Wait Times ◽  
Time Data ◽  
Developed Nations

Mental illness is a prevalent and costly health care issue. Lengthy wait times for psychiatric services in Ontario are a barrier to adequate mental health care for adults, children and youth. The objective of this paper is to highlight the current state of psychiatric wait times in Ontario by looking at provincial policies and comparing data to physical health services, as well as between provinces and other developed nations. The Ontario government has successfully implemented mandatory reporting of wait-time data for many medical and surgical services. However, such policies have yet to be implemented for psychiatric services. As a result, availability of current data for comparison is limited. Nova Scotia is currently the only province to government mandate reporting of wait times for mental health. Furthermore, The Organisation for Economic Co-operation and Development ranks Canada below average on measures related to accessibility of psychiatric inpatient services compared to other developed nations. While Ontario has implemented new initiatives to address the issue of timely mental health care, there is still insufficient evidence to determine if they are effective. Continued advocacy for mandatory wait-time reporting at the provincial level and further analysis of current initiatives worldwide are essential steps toward reducing wait times.

scholarly journals General Anesthetic Versus Light Sedation: Effect on Pediatric Endoscopy Wait Times

2013 ◽  
Vol 27 (9) ◽  
pp. 519-522
Author(s):  
Christine Edwards ◽  
Vikram Kapoor ◽  
Christopher Samuel ◽  
Robert Issenman ◽  
Herbert Brill
Keyword(s):  
Health Care ◽  
Emergency Room ◽  
General Anesthesia ◽  
Clinical Outcomes ◽  
Hospital Admissions ◽  
Wait Time ◽  
Wait Times ◽  
Pediatric Gastroenterology ◽  
Emergency Room Visits ◽  
Light Sedation

BACKGROUND: Wait times are an important measure of health care system effectiveness. There are no studies describing wait times in pediatric gastroenterology for either outpatient visits or endoscopy. Pediatric endoscopy is performed under light sedation or general anesthesia. The latter is hypothesized to be associated with a longer wait time due to practical limits on access to anesthesia in the Canadian health care system.OBJECTIVE: To identify wait time differences according to sedation type and measure adverse clinical outcomes that may arise from increased wait time to endoscopy in pediatric patients.METHODS: The present study was a retrospective review of medical charts of all patients <18 years of age who had been assessed in the pediatric gastroenterology clinic and were scheduled for an elective outpatient endoscopic procedure at McMaster Children’s Hospital (Hamilton, Ontario) between January 2006 and December 2007. The primary outcome measure was time between clinic visit and date of endoscopy. Secondary outcome measures included other defined waiting periods and complications while waiting, such as emergency room visits and hospital admissions.RESULTS: The median wait time to procedure was 64 days for general anesthesia patients and 22 days for patients who underwent light sedation (P<0.0001). There was no significant difference between the two groups with regard to the number of emergency room visits or hospital admissions, both pre- and postendoscopy.CONCLUSIONS: Due to the lack of pediatric anesthetic resources, patients who were administered general anesthesia experienced a longer wait time for endoscopy compared with patients who underwent light sedation. This did not result in adverse clinical outcomes in this population.

scholarly journals Wait Times from Presentation to Treatment for Colorectal Cancer: A Population-Based Study

2010 ◽  
Vol 24 (1) ◽  
pp. 33-39 ◽  
Author(s):  
H Singh ◽  
C De Coster ◽  
E Shu ◽  
K Fradette ◽  
S Latosinksy ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cox Regression ◽  
Diagnostic Delay ◽  
Wait Time ◽  
Occult Blood ◽  
Population Based ◽  
Administrative Databases ◽  
Wait Times ◽  
Fecal Occult Blood ◽  
Cox Regression Analysis

BACKGROUND: The wait time from cancer diagnosis to treatment has been a recent focus of cancer care in Canada.OBJECTIVE: To examine the trends in wait times from patient presentation to treatment (overall health system wait time [OWT]) for colorectal cancer (CRC).METHODS: Patients with colorectal adenocarcinomas, diagnosed between 2001 and 2005, and their first definitive treatments were identified from the population-based Manitoba Cancer Registry (Winnipeg, Manitoba). By linkage to Manitoba Health and Healthy Living’s administrative databases, a patient’s first gastrointestinal investigation (abdominal radiological imaging, lower gastrointestinal endoscopy or fecal occult blood test) before CRC diagnosis was identified. The index contact with the health care system was estimated from the date of the visit with the physician who ordered the first gastroenterological investigation. The OWT was defined as the time from the index contact to the first treatment, while diagnostic delay was defined as the time from the index contact to the diagnosis of CRC. Multivariate Cox regression analysis was performed to determine independent predictors of OWT.RESULTS: The OWT was estimated for 2552 cases of CRC over the five years that were examined. The median OWT increased from 61 days in 2001 to 95 days in 2005 (P<0.001). Most of the increase was in diagnostic wait times (median of 44 days in 2001 versus 64 days in 2005 [P<0.001]). Year of diagnosis, older age, urban residence and diagnosis at a teaching facility were independent predictors of OWT.CONCLUSIONS: The OWT from presentation to treatment of CRC in Manitoba steadily increased between 2001 and 2005, mostly due to diagnostic delays.

scholarly journals Variable effects of obesity on access to total hip and knee arthroplasty

2021 ◽  
Vol 64 (1) ◽  
pp. E84-E90
Author(s):  
Glen Richardson ◽  
Chris Dusik ◽  
Lynn Lethbridge ◽  
Michael Dunbar
Keyword(s):  
Nova Scotia ◽  
Total Joint Arthroplasty ◽  
Wait Time ◽  
Preoperative Assessment ◽  
Study Data ◽  
Joint Arthroplasty ◽  
Wait Times ◽  
Weight Class ◽  
Data Set ◽  
Total Hip

Background: Obesity is an important comorbidity affecting outcomes after total joint arthroplasty. Consequently, surgeons may delay care of obese patients to first address obesity through different care pathways. The effect of obesity on patient wait times for total joint arthroplasty has not been explored. The purpose of this study was to evaluate the effect of obesity on access to total hip (THA) and knee (TKA) arthroplasty. Methods: The study data set was constructed from the Nova Scotia Health Authority’s Horizon Patient Folder system and the Patient Access Registry Nova Scotia. Wait time was measured as days between the decision to treat and date of surgery. Body mass index (BMI) was calculated from a preoperative assessment, and patients were grouped into BMI categories. Multivariate log-linear regression was used to test for statistical differences, controlling for confounding factors. Results: We observed longer wait times for TKA with increasing BMI weight class. Patients with BMIs greater than 50 had 34% longer waits than reference weight patients. However, THA recipients showed no statistical difference in wait times across weight categories. Furthermore, there was variability among surgeons in the wait times experienced by patients. Conclusion: The finding of longer wait times for TKAs, but not THAs, among patients who were obese was unexpected. This shows the variable wait times for THA and TKA that patients who are obese can experience with different surgeons. It is important to understand the variability in wait times so that efforts to standardize the patient experience can be accomplished.

Building a novel near real-time multisource database to assess and improve infusion wait time at a comprehensive cancer center.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 4-4
Author(s):  
Jing Jing Wang Yakowec ◽  
Mark Pettengill ◽  
Sadiqa Mahmood ◽  
Belen Fraile ◽  
Hakim Lakhani
Keyword(s):  
Real Time ◽  
Processing Time ◽  
Treatment Plan ◽  
Wait Time ◽  
Medication Administration ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Wait Times ◽  
Automatic Data ◽  
The Impact

4 Background: Evidence has shown that long infusion wait time is one of the main contributors to oncology patient dissatisfaction. To identify bottlenecks and inefficient processing, a comprehensive understanding of the infusion workflow at Dana-Farber Cancer Institute was explored. The goal of the project is to leverage existing data sources to quantify time to process completion and to serve as the database for multiple wait time improvement projects. Methods: Infusion workflow from patient check-in or appointment time to first infusion medication administration (wait time) was mapped. Data from Epic and Real-Time Locating System (RTLS) were pulled into a single integrated source in Tableau and SAS for analysis. Using a custom SQL query, the following tables including crucial timestamps were pulled and pooled: encounters, pharmacy processing and dispense, treatment plan and protocol, RTLS events related to infusion chair occupancy, and medication administration records. Further programming was written to flag categories such as investigational versus non-investigational drugs, linked versus un-linked to exam appointments, and inclusion and exclusion criteria regarding date range, infusion floor, and encounter type. Results: The final clean infusion database includes data from September 1, 2017 through the day before current day via automatic data pull. Processing and wait times were analyzed at multiple levels by drug, encounter, department, staff, and protocol. To date, four known wait time improvement projects that aim to shorten processing time, such as early signing of orders by providers, have leveraged this near real-time dataset to monitor and evaluate the impact of the projects. The automation of data to pre-built visualizations in Tableau comparing baseline processing time to post-pilot impact and overall wait time trends has been extremely well received by all improvement stakeholders at the institute. Conclusions: A novel database merging Epic and RTLS data was successfully built to explore and improve infusion patient wait time. This technique can be applied at other institutions interested in reducing wait times and improving patient satisfaction.

Sign in / Sign up

Export Citation Format

Share Document