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'Predictive no-show overbooking' intervention. Patients who volunteer to enroll in "fast-track" line, which gives them an opportunity to overbook their appointment for endoscopy earlier in a predictive no-show slots.

During intervention period, every Veteran scheduled for an endoscopy will be offered "fast-track" offer, which gives them a chance to get their endoscopy procedure done earlier than usual scheduling by overbooking their appointment in a predictive no-show slot.

Predictive no-show overbooking

Paul G. Shekelle, MD PhD MPH

In this research study, investigators use colonoscopy as a case example to evaluate a predictive overbooking model derived using patient-level predictors of absenteeism. The no-show overbooking intervention employs a logistic regression model that uses patient data to predict the odds of no-showing with 80% accuracy. These projected no-show appointments will be overbooked by clerks for patients who agree to join a "fast track" short-call line. By rapidly processing endoscopy patients and moving them out of traditional slots, investigators predict more scheduling slots would become available for patients awaiting colonoscopy.

Patient "no-shows" are especially common in VA gastrointestinal (GI) endoscopy units, where both open-access endoscopy scheduling and patient dislike of procedures contribute to high absenteeism. In this proposal, investigators use endoscopy as a case example to evaluate a predictive overbooking model derived using patient-level predictors of absenteeism. The no-show overbooking intervention employs a logistic regression model that uses patient data to predict the odds of no-showing with 80% accuracy. These projected no-show appointments will be overbooked by clerks for patients who agree to join a "fast track" short-call line. However, patients scheduled for upper endoscopies in the "fast track" assume a small risk of service denial on the day of their overbooking in case of inaccurate predictions. If this occurs, the patient is guaranteed service in the next available position and is assured of having a shorter wait time. Patients scheduled for colonoscopies will never be turned down but may experience delays in the waiting room the day of their "fast track" appointment. By rapidly processing endoscopy patients and moving them out of traditional slots, investigators predict more scheduling slots would become available for patients awaiting colonoscopy. Investigators propose to conduct a prospective, 24-month, interrupted time series (ITS) trial in the WLAVA (West Los Angeles Veterans Administration) GI clinic endoscopy unit. During intervention periods, investigators will activate the no-show predictive overbooking strategy described above. Investigators will compare outcomes between scheduling strategies, including differences in percent utilization of capacity (primary outcome), number of Veterans served, mean patient lag time between scheduling and procedure, number of unexpected service denials ("bumps") from no-show predictive overbooking, and direct costs of care. Investigators will analyze differences using both traditional univariate and multivariate approaches, and using autoregressive integrated moving average (ARIMA) analyses to adjust for auto-correlations in ITS data.

Reducing VA No-Shows: Evaluation of Predictive Overbooking Applied to Colonoscopy

Investigators' primary objective will be to evaluate the impact of no-show predictive overbooking on percentage of the GI endoscopy clinic that are filled on a given day. Days where at least one Fast-tracked patient attended an appointment were compared to days where only Control patients attended appointments. Percentage of GI Clinic Capacity is calculated as the number of appointments completed divided by number of appointment spots available on a given day. This percentage was compared between Fast-tracked days and Control days, using data from 1672 patients.

The investigators will calculate the mean daily lag time for all colonoscopy and upper endoscopies performed per day

The investigators will compare the number of patients bumped per day between scheduling approaches

The investigators will compare daily advanced adenomatous polyp detection and daily cecal intubation rates between groups.

Length of Workday in hours (comparing days with Fast-Tracked Appointments to Control days without)

For cost comparisons, the investigators will aggregate total provider overtime costs for colonoscopies performed. Cost is reported per day.

VA Office of Research and Development

This study involved scheduling patients for appointments, so the odds of an adverse event are extremely low.

Patients who volunteer to enroll in "fast-track" line, which gives them an opportunity to overbook their appointment for endoscopy earlier in a predictive no-show slots.

Predictive no-show overbooking: During intervention period, every Veteran scheduled for an upper endoscopy will be offered "fast-track" offer, which gives them a chance to get their endoscopy procedure done earlier than usual scheduling by overbooking their appointment in a predictive no-show slot.

Fast-tracked

Control

Total

Age, Categorical

Age, Continuous

Sex: Female, Male

Ethnicity (NIH/OMB)

Race (NIH/OMB)

United States

Region of Enrollment

This study was impeded by our ability to schedule Veterans into Fast-Tracked appointments. Although the method is very promising, integration of predictive scheduling is vital for this program to benefit Veterans on a large scale.

Jennifer Talley Soares

We counted days containing at least one Fast-tracked participant as a "Fast-tracked" day for the sake of analysis at the clinic level. Our null hypothesis is that these days will not differ in terms of percentage of clinic capacity filled. We are powered to detect a 0.5 Standard Deviation (SD) difference in clinic capacity (Type I error rate = 5%; Power = 81%), with a equal ratio of Experimental and Control days.

These 1672 patients are a subset of all patients who were enrolled in this study. We dropped data on a first wave of participants (69 Fast-tracked and 3294 Controls) because of problems incorporating recruitment strategy into clinic. However, data from these individuals was used to build predictive model.

Percentage of GI Clinic Capacity Filled

We calculated this measure on the patient level. Our null hypothesis is that the lag time between scheduling and appointment, measured in days, will not differ between groups. We are powered to detect a 0.3 SD difference in lag time (Type I error rate = 5%; Power = 84%), accounting for the large sampling ratio (approximately 14:1).

Scheduling-to-procedure Lag Time

We did not explicitly power this study to detect differences in the number of service bumps, but we can compare them using Fisher's Exact Test

Daily Service Denials ("Bumps")

We calculated this measure on the patient level, but were hampered by a large sampling ratio (more than 50:1). Our null hypothesis is that the number of polyps detected will not differ between groups. We are powered to detect a 0.25 SD difference in polyp count per patient (Type I error rate = 5%; Power = 80%).

We only collected data on polyp detection for the first half of our Fast-tracked participants and all Controls seen over the same time period (4897 in total).

Advanced Adenoma Detection/Cecal Intubation Rates

We counted days containing at least one Fast-tracked participant as a "Fast-tracked" day for the sake of analysis at the clinic level. Our null hypothesis is that these days will not differ in terms of length of workday. We are powered to detect approximately 0.5 SD difference in workday length in hours (Type I error rate = 5%; Power = 81%), with a equal ratio of Experimental and Control days.

Length of Workday

We counted days containing at least one Fast-tracked participant as a "Fast-tracked" day for the sake of analysis at the clinic level. Our null hypothesis is that these days will not differ in terms of cost per day. We are powered to detect a 0.5 SD difference in clinic capacity (Type I error rate = 5%; Power = 81%), with a equal ratio of Experimental and Control days.

Cost Comparisons

Overall Study

Symptoms and General Pathology

Behaviors and Mental Disorders

Fatigue

Quality of Life

A single-faceted patient-directed (PD) strategy that will embed the change at patient level.

A multi-faceted (MF) strategy that will embed the change at the patient, professional and organizational levels.

The patient-directed strategy will be designed to embed the success of implementation of PCRPs by influencing the patients.

The patient-directed (PD) strategy

The multi-faceted strategy will be designed to embed the success by not only influencing the patients, but also professionals and organizational aspects.

The multi-faceted (MF) strategy

C. IJsbrandy, MD

R.P.M.G. Hermens, PhD

C. IJsbrandy, drs.

The aim of this study is to develop and identify the most effective strategy to implement PCRPs into daily care. We want to assess the added value of a multi-faceted strategy compared with a single-faceted patient-directed strategy.

The aim of this study is to develop and identify the most effective strategy to implement PCRPs into daily care. We want to assess the added value of a multi-faceted strategy compared with a single-faceted patient-directed strategy.

We will conduct a clustered controlled before and after study (CBA) in the Netherlands that compares two strategies to implement PCRPs. The patient-directed (PD) strategy (five hospitals) will focus on change at the patient level. The multi-faceted (MF) strategy (five hospitals) will focus on change at the patient, professional and organizational levels. Eligibility criteria are as follows: (A) patients: adults; preferably (history of) cancer in the gastro-intestinal, reproductive and/or urological system; successful primary treatment; and without recurrence/metastases. (B) Healthcare professionals: involved in cancer care.

A stepwise approach will be followed:

Step 1: Analysis of the current implementation of PCRPs and the examination of barriers and facilitators for implementation, via a qualitative study with patients (four focus groups n = 10-12) and their healthcare workers (four focus groups n = 10-12 and individual interviews n = 30-40) and collecting data on adherence to quality indicators (n = 500 patients, 50 per hospital).

Step 2: Selection and development of interventions to create a PD and MF strategy during expert's roundtable discussions, using the knowledge gained in step 1 and a literature search of the effect of strategies for implementing PCRPs.

Step 3: Test and compare both strategies with a clustered CBA (effectiveness, process evaluation and costs), by data extraction from existing registration systems, questionnaires and interviews. For the effectiveness and cost-effectiveness, n = 500 patients, 50 per hospital. For the process evaluation, n=50 patients, 5 per hospital, and n = 40 healthcare professionals, 4 per hospital.

Implementation of Physical Cancer Rehabilitation Programmes in a European Healthcare System.

An Evaluation of a Patient-directed Strategy Compared With a Multi-faceted Strategy to Implement Physical Cancer Rehabilitation Programmes; a Controlled Before and After Study.

The experiences and exposure of patients and professionals with the PD- and MF strategy will be evaluated by interviews.

incremental costs and incremental cost-effectiveness ratios (ICERs)

A pre- and post measurement of 'the percentage of screened patients with the screening tool recommended by the Dutch guideline 'Cancer Rehabilitation'' will be done. The differences between the pre- and post measurement will be measured.

A pre- and post measurement of 'The percentage of referrals to PCRPs where needed, according to the Dutch guideline 'Cancer Rehabilitation'' will be done. The differences between the pre- and post measurement will be measured.

A pre- and post measurement of 'QoL' will be done. The differences between the pre- and post measurement will be measured.

A pre- and post measurement of 'patientempowerment' will be done. The differences between the pre- and post measurement will be measured.

A pre- and post measurement of ' the Remaining quality indicators of the Dutch guideline 'Cancer Rehabilitation'' will be done. The differences between the pre- and post measurement will be measured.

Radboud University Medical Center

Diseases and Abnormalities at or Before Birth

Nutritional and Metabolic Diseases

Rare Diseases

Colorectal Neoplasms, Hereditary Nonpolyposis

Rectal Diseases

Syndrome

Neoplastic Syndromes, Hereditary

Genetic Diseases, Inborn

DNA Repair-Deficiency Disorders

Metabolic Diseases

Familial Colorectal Cancer

* Patients and clinicians have access to a website with information on familial colorectal cancer risk; a risk assessment tool and decision aids
* Clinicians receive the guidelines and a risk communication tool, as well as education

Implementation aids

Nicoline Hoogerbrugge, MD, PhD

Rosella PMG Hermens, PhD

The aim of this study is to improve clinicians' calculation, interpretation and communication of familial colorectal cancer risk, as well as patients' risk perception and uptake of referral for genetic counselling or for surveillance by colonoscopy for their relatives at risk.

Regular colonoscopy is effective in reducing morbidity and mortality due to colorectal cancer (CRC) in patients at increased familial CRC risk. Currently, the majority of these at-risk individuals are not properly referred for increased surveillance by colonoscopy or genetic counselling. In 2008, a national multidisciplinary evidence-based guideline on familial and hereditary CRC was launched in the Netherlands. Clinicians have new tasks in familial CRC risk calculation, interpretation and communication. A clustered randomized controlled trial including an effect, process and cost evaluation will be conducted in eighteen Dutch hospitals to determine the most cost effective way to implement these new guidelines.

Surgeons and gastroenterologists in both the intervention group and the control group will receive background information on familial colorectal cancer risk and the guidelines. Patients and clinicians in the intervention group will receive an additional intervention strategy.

The effect evaluation is done by assessing the number of CRC patients for whom correct risk calculation, interpretation and communication is performed, as well as patients' uptake of the recommended follow up policy. The actual exposure to the different elements of the implementation procedure and the experiences of users will be assessed in the process evaluation. The costs of the implementation procedure will be determined by means of a cost evaluation.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Reducing VA No-Shows: Evaluation of Predictive Overbooking Applied to Colonoscopy	NCT01639443	Colon Cancer	Predictive no-s...	18 Years -	VA Office of Research and Development
Implementation of Physical Cancer Rehabilitation Programmes in a European Healthcare System.	NCT02205853	Cancer Fatigue	The patient-dir... The multi-facet...	18 Years -	Radboud University Medical Center
Implementation of Guidelines on Hereditary or Familial Colorectal Cancer	NCT00929097	Colorectal Neop...	Implementation ... Control	18 Years - 70 Years	Radboud University Medical Center
Reducing VA No-Shows: Evaluation of Predictive Overbooking Applied to Colonoscopy	NCT01639443	Colon Cancer	Predictive no-s...	18 Years -	VA Office of Research and Development

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