Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Uterine Cervical Neoplasms

Uterine Neoplasms

Genital Neoplasms, Female

Urogenital Neoplasms

Uterine Cervical Diseases

Uterine Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Cost-effectiveness analysis of 3 strategies to increase the recruitment of population screening for cervical cancer. These interventions will be compared to the current opportunistic screening strategy

Different alternatives to improve the coverage of the populational screening programmes of cervical cancer

JM Manresa, Doctor

Amelia Acera, Doctor

JM Manresa, BS MSc

Pere Toran, MD

Amelia Acera, MD MSc

Ana Rodriguez, Midwife

Marta Trapero

Pilar Soteras

Norman Sanchez

JM Bonet

Pablo Hidalgo

Pere Toran

Gemma Prieto

The aim of this study was to compare the effectiveness and the costs of three types of population interventions to increase the number of female participants in the screening programmes for cancer of the cervix carried out by Primary Care in four Basic Health Care Areas.

Background A high percentage of cervical cancer cases have not undergone cytological tests within 10 years prior to diagnosis. Different population interventions could improve coverage in the public system, although costs will also increase. The aim of this study was to compare the effectiveness and the costs of three types of population interventions to increase the number of female participants in the screening programmes for cancer of the cervix carried out by Primary Care in four basic health care areas.

Methods A cost-effectiveness analysis will be performed from the perspective of public health system including women from 30 to 70 years of age (n=20,994) with incorrect screening criteria from four basic health care areas in the Valles Occidental, Barcelona, Spain. The patients will be randomly distributed into the control group and the three Intervention Groups (IG1: invitation letter to participate in the screening; IG2: invitation letter and informative leaflet; IG3: invitation letter, informative leaflet and a phone call reminder) and followed for three years. Clinical effectiveness will be measured by the number of Human Papillomavirus (HPV), epithelial lesions and cancer of cervix cases detected. The number of deaths avoided will be secondary measures of effectiveness. The temporal horizon of the analysis will be the life expectancy of the female population in the study. Costs and effectiveness will be discounted at 3 %. In addition, univariate and multivariate sensitivity analysis will be carried out.

Expected results IG3 is expected to be more cost-effective intervention than IG1 and IG2, with greater detection of HPV infections, epithelial lesions and cancer than other strategies, albeit at a greater cost.

METHODS

An economic evaluation of three populational screening strategies for cervical cancer will be performed. Particularly, a cost-effectiveness analysis will be conducted. These interventions will be compared to the current opportunistic screening strategy using data of the multicentre randomised trial (CRICERVA). The analysis will be conducted from the National Health Care System perspective.

Design: Pragmatic, blinded, multicentre, randomised, controlled clinical trial with four branches, and a three years follow-up. The randomisation unit was Basic Health Care Area (BHCA).

Setting: Primary Health Care Services (PCS) of Cerdanyola-Ripollet, province of Barcelona, comprising 4 municipalities and 5 BHCA. The population covered by this Primary Care Service (PCS) is 120,293 inhabitants over 14 years. As there are four study groups and 5 BHCAs, only 4 BHCAs with most homogeneous socioeconomic criteria will be considered.

Population: 20,994 women from 30 to 70 years of age with incorrect screening criteria (data obtained from Data Base of Primary Health Care Services) ascribed to the BHCA will be included in the study. Incorrect screening will be defined as \[9\]: 1.- No cytology in the last 3 years from women between 30 to 40 years, 2.- No cytology in the previous 5 years from women between 40 to 65 years, 3.- No previous cytology history for females older than 65 years or women who have not had their last cytology before the age of 60. The exclusion criteria will be: (a) hysterectomised women, with a current history of pre-malignant lesions \[Atypical Glandular Cells of Undetermined Significance (AGUS), Atypical Squamous Cells of Undetermined Significance (ASCUS), Low-grade Squamous Intraepithelial Lesions (LSIL), High-grade Squamous Intraepithelial Lesions (HSIL)\], carcinoma in situ and cervical-uterine cancer, Human Immunodeficiency Virus (HIV) positive or other causes of immunosuppression (since these women follow a specific protocol); (b) those residing outside the study setting for more than 6 months; and (c) those ascribed to the study BHCA but with a physician assigned in an UBA of another zone different from the one considered in the study.

Sample size: The sample size has been calculated based on the detection of a difference in effectiveness compared with the Non Intervention Group (NIG). It has been calculated by multiplying the size of a simple randomised design by the design effect or factor of inflation. For the simple randomised design, on accepting an alpha risk of 0.05 and a beta risk of 0.20 in a bilateral contrast, 59 subjects will be required in the first group and 59 in the second group to detect a difference greater than or equal to 28.4 % in the screening coverage of the 41.6 % in the Non Intervention Group (NIG). The lost to follow up rate has been estimated at 20 %. The calculation of the sample has been performed with the Granmo 5.2 computer programme for Windows. According to a review of the literature \[23-25\], considering an intraclass correlation coefficient of 0.05 and a mean number of 3,500 women from 30 to 70 years of age with incorrect screening by BHCA, the design effect will be 176 and thus, 20,768 women with incorrect screening will be required.

ETHICAL ASPECTS The investigators are committed to respect the prevailing norms of Good Clinical Practice as well as the requisites of the Declaration of Helsinki and the clauses of general and particular ethical conditions related to the right to privacy, anonymity and confidentiality. Neither the first name nor surname or any other type of data indicating the identification of the women will be registered. Therefore, identification will be made by numeric codes. Since this type of study is developed in the usual clinical setting, authorisation and support must be and has already been granted by the representatives and authorities of the collectives involved and thus, individualised informed consent is not necessary. Nonetheless, the research team decided that women attending the consultation for the cytology should sign the consent form. The protocol has been evaluated by the Clinical Investigation Ethics Committee of the IDIAP Jordi Gol.

LIMITATIONS Randomisation by groups will avoid the potential introduction of selection bias which may be produced among the interventions performed at the same site. Since the characteristics of the study do not allow the application of the double-blind masking technique, the masked response evaluation will be used to ensure that the measurement and interpretation of the dependent variables is carried out the same way in all groups. The possible loss of information, which may be produced in women doing screening outside public health care if they are not contacted by the research team, will be minimised with a phone call reminder. This will be made when the women do not attend the appointment. The language difficulties in women from other countries will be solved with cultural mediators at each site. Within the setting of the study, the administrative personnel have been updating the postal addresses of the users attending the BHCA since 2007 and, therefore the postal registry is quite precise, thereby reducing the potential loss of letters.

List of abbreviations

AETM Agency for Evaluation of Technology and Medical Investigation BHCA Basic Health Care Area AGUS Atypical glandular cells of undetermined significance ASCUS Atypical squamous cells of undetermined significance PCC Primary Care Centre ECCI Ethical Committee of Clinical Investigation eCCN Electronic Data Collection Notebook PCT Primary Care Team c-CH Computerised Clinical History IT Investigative Team IG Intervention Group NIG Non intervention Group HC2 Hybrid Capture 2 HSIL High grade Squamous Intraepithelial Lesion CIO Catalan Institute of Oncology CIH Catalan Institute of Health IIPC Institute of Investigation in Primary Care LSIL Low grade Squamous Intraepithelial Lesion SRHC Sexual and Reproductive Health Care PCS Primary Care Service ISU Investigation Support Unit HSV Herpes Simple Virus HIV Human Immunodeficiency Virus HPV Human Papilloma Virus UBA Unitat Bàsica Assistencial (General Practicioner and Nurse Team)

Financial support

This protocol has received financial support from the Fondo de Investigación Sanitaria del Instituto Carlos III de Madrid (exp PI10/01275).

Economic Evaluation of Three Populational Screening Strategies for Cervical Cancer

Economic Evaluation of Three Populational Screening Strategies for Cervical Cancer in the County of Valles Occidental: CRICERVA Clinical Trial.

The main effectiveness measures of this evaluation would be the total number of cytologies performed, HPV infections detected, lesions of different grades detected, episodes of cancer detected and the number of deaths avoided

Include costs of diagnosis, interventions and treatment for all women

* Diagnosis: cost of cytology, HPV determination test and control visit by the midwife or gynaecologist
* Interventions: cost of a full-time administrator, personalized screening invitation letters, informative leaflets and phone calls
* Treatment: will depend on the state of health of the women but may include the costs of the visits to the gynaecologist, cytology tests, HPV determination, control visits with the physician, costs of radical hysterectomy, radiotherapy, chemotherapy, etc

Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina

Amelia Acera Perez

Skin and Connective Tissue Diseases

Breast Neoplasms

Premature Birth

Obstetric Labor, Premature

Obstetric Labor Complications

Breast Diseases

Skin Diseases

Information services tailored to the needs of individual patients. The information prescription (IRx)or service is defined for this study as a combination of: 1)An evidence-based web site for use by patients and their families; 2) A reference interview and assistance in locating relevant general information in response to patient information needs; 3) Documentation of the questions and the information service provided in response to these in the patient's Electronic Patient Record for review by providers as needed; and, 4) Triage of patient's/parents clinical questions to providers.

Information Services (IRx)

Nancy K Oliver, MLS

Kathleen B Oliver, MLS, MPH

Research shows that patient satisfaction with medical care correlates strongly with how satisfied they are with the ease of getting information from their providers regarding their medical condition. Although the Internet is a wonderful source of information for patients, research has shown that, unmediated, it comprises a potential quagmire of information poorly matched to users needs. Providers typically do not have enough time to fulfill all of their patients' information needs. One strategy to meeting the patient's information needs is to introduce librarians trained and experienced in consumer health information services into the relationship between the patient and the provider. One recently described tactic is for providers to provide information the way they of provide treatment-through an information prescription (IRx) filled by a librarian. The librarian fills the prescription by offering information services tailored to the needs of individual patients. At Johns Hopkins, we have piloted such a tactic, and in this project, extend and evaluate it. The research hypothesis is that provision of an IRx will improve patient satisfaction, provider knowledge and attitudes regarding patient information needs, and the efficiencies of care.

The goal of this research is to evaluate IRx, to provide enough data so care organizations can decide whether to implement this in their own environment.

To that end, our specific aims are:

1. To evaluate the impact of IRx on patients. We are performing a randomized clinical trial, comparing IRx with standard provision of information. The primary outcome is patient satisfaction.
2. To evaluate the impact of IRx on providers. As part of the trial, provider perceptions and behavior will be assessed.
3. To evaluate the impact of IRx on the health-care system. As part of the trial, costs entailed and resources utilized will be assessed.
4. To evaluate how IRx generalizes across service environments. The trial will be performed in two environments: adult breast cancer and neonatal intensive care.

At the heart of this proposal are the randomized clinical trials. In each, patients in both intervention and control groups will receive standard clinical care in their clinic visits. Patients randomized to the intervention group will receive information services from a specially trained librarian; patients in the control groups will receive routine, current information provision. For Aim 1, immediately after their clinic visits and four weeks later, all participants will report their satisfaction on a survey that include measures of patient-provider communication. For Aim 2, participating providers are surveyed for their perceptions of information needs being met and about patient-provider interaction. For Aim 3, costs of care and costs of providing the IRx environment will be tabulated.

Evaluating Patient Information Prescriptions

Evaluating Patient Information Prescriptions in Different Service Environments

National Institutes of Health (NIH)

National Library of Medicine (NLM)

Johns Hopkins University

Digestive System Diseases

Colonic Neoplasms

Colorectal Neoplasms

Intestinal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Colonic Diseases

Intestinal Diseases

'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

Heart and Blood Diseases

Thrombosis

Thromboembolism

Venous Thromboembolism

Venous Thrombosis

Embolism

Embolism and Thrombosis

Vascular Diseases

Fibrinolytic Agents

Anticoagulants

All Drugs and Chemicals

Bone Density Conservation Agents

Anti-Infective Agents

Amino Acids

Heparin

Enoxaparin

Calcium heparin

Heparin, Low-Molecular-Weight

Tinzaparin

Dalteparin

PENTA

Fondaparinux

Enoxaparin sodium

Calcium

Calcium, Dietary

Factor Xa Inhibitors

Antithrombins

Antithrombin III

Protease Inhibitors

Serine Proteinase Inhibitors

HIV Protease Inhibitors

Enzyme Inhibitors

Serine

Healthcare claims records from patients aged 18 years or older with at least one primary inpatient discharge diagnosis of cancer and a cancer-related surgery during the hospitalization

An injectable anticoagulant medication for the prevention of VTE related to cancer surgery. Patients received dalteparin during one day prior to or two days after cancer-related surgery during the hospitalization.

dalteparin

An injectable anticoagulant medication for the prevention of VTE related to cancer surgery. Patients received enoxaparin during one day prior to or two days after cancer-related surgery during the hospitalization.

enoxaparin

An injectable anticoagulant medication for the prevention of VTE related to cancer surgery. Patients received fondaparinux during one day prior to or two days after cancer-related surgery during the hospitalization.

fondaparinux

An injectable anticoagulant medication for the prevention of VTE related to cancer surgery. Patients unfractionated heparin received during one day prior to or two days after cancer-related surgery during the hospitalization.

unfractionated heparin

GSK Clinical Trials

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is a common post-operative complication. The effectiveness of fondaparinux compared with other injectable anticoagulants in VTE following major orthopedic and abdominal surgery has been evaluated in database studies; however, the effectiveness of injectable anticoagulant medications following cancer-related surgeries in the practice setting has not been as well documented.

The objective of this study is to analyze patient records from a national hospital database and compare the outcomes and costs between four types of injectable anticoagulant medications that were prescribed for the prevention of VTE following cancer-related surgery. This analysis will assess and quantify the outcomes, resource utilization, and cost of care for patients receiving fondaparinux, enoxaparin, dalteparin or unfractionated heparin. The outcomes of interest include the occurence of VTE, rates of major bleeds, medical resource utilization, and total costs (medical plus pharmacy).

The source of data for this study is the Premier Perspective Database™. This hospital claims database links de-identified inpatient medical, pharmacy, and billing data from more than 500 hospitals.

This study is a retrospective cohort study that uses propensity score matching to adjust for the differences between the numbers of patients treated with each medication.

Comparative Analysis of Injectable Anticoagulants for Thromboprophylaxis Post Cancer-related Surgery

VTE events were identified by International Classification of Disease-9 (ICD-9) codes for deep vein thrombosis (451.xx. 453.xx) and pulmonary embolism (415.xx) during the index hospitalization. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes

Major bleeding events were identified according to ICD-9 codes for major bleed (568.81, 430.xx, 431.xx, 432.xx, or 998.11) or other bleeding accompanied by more than 2 units of blood transfused (246.3, 286.5, 287.3, 287.4, 287.5, 287.8, 287.9, 459.0, 530.82, 569.3, 578.x, 596.7, 599.7, 719.1, 784.7, 784.8, 786.3, 958.2, or 997.02) as recorded in the billing file during the index hospitalization plus 1 month post discharge. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes.

Readmission rates were defined as a subsequent hospitalization for major bleeding or VTE that occurred within the follow-up period (discharge month plus 1 month).

Length of hospital stay was obtained from the discharge record and was defined as the number of days from patient admission to the hospital for cancer-related surgery until discharge from the hospital.

The mean total costs (medical plus pharmacy costs) from patient records in each antithrombotic cohort from the index hospitalization. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes.

VTE events were identified according to ICD-9 codes for DVT and PE during the index hospitalization plus 1 month post discharge. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes.

Major bleeding events were identified according to ICD-9 codes for hemoperitoneum bleed, intracranial hemorrhage/hemorrhagic stroke, hemorrhage complicating a procedure, or other bleeding accompanied by more than 2 units of blood transfused as recorded in the billing file during the index hospitalization plus 1 month post discharge. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes.

The mean total costs (medical plus pharmacy costs) from patient records in each antithrombotic cohort from both the index hospitalization and the 1-month follow-up period. Results will be calculated, reported as unadjusted, and adjusted to control for the effect of covariates on outcomes

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Economic Evaluation of Three Populational Screening Strategies for Cervical Cancer	NCT01373723	Uterine Cervica...	Different alter...	30 Years - 70 Years	Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina
Evaluating Patient Information Prescriptions	NCT00355381	Breast Neoplasm... Premature Birth	Information Ser...	-	Johns Hopkins University
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
Comparative Analysis of Injectable Anticoagulants for Thromboprophylaxis Post Cancer-related Surgery	NCT01444612	Thrombosis, Ven...	dalteparin enoxaparin fondaparinux unfractionated ...	18 Years -	GlaxoSmithKline
Evaluating Patient Information Prescriptions	NCT00355381	Breast Neoplasm... Premature Birth	Information Ser...	-	Johns Hopkins University
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

Spots Global Cancer Trial Database for costs and cost analysis