Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Symptoms and General Pathology

Uterine Cervical Neoplasms

Facies

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

Stepwise approach, with increasing complexity and cost, to improve adherence to organized cervical cancer screening, implemented through three steps:

step 1a - customized text message invitation; step 1b - customized automatic phone call invitation; step 2 - secretary phone call; step 3 - health professional phone call and face-to-face appointment.

Intervention stops whenever the participant adheres to organized screening or after undergoing the complete stepwise intervention.

Comparator will be the standard of care of invitation to cervical cancer screening: written letter

Personalized text messages, automatically sent by Smart Message v.3.1 software. These text messages intend to invite women to cervical cancer screening

Customized text message invitation ( Step 1a)

Personalized phone call, not operator dependent, automatically sent by Smart-Interactive Voice Response v.1.1 software These phone calls intend to invite women to cervical cancer screening

Customized automatic phone call invitation (Step 1b)

Manual phone call, performed by a trained secretary. These phone calls invite women to cervical cancer screening, but will only be used after automatic strategies (customized text messages and phone calls)

Secretary phone call (Step 2)

Women randomized to experimental arm, who do not undergo cervical cancer screening after automatic invitation or manual phone call, receive this intervention. First, women are contacted through a phone call, performed by a health professional, inviting them for a face-to-face appointment at her primary care unit.

During appointments, the health professional understands possible barriers felt by women for not undergoing cervical cancer screening. Health professionals will try to overcome these barriers, using pre-defined arguments and facts. Finally, women are invited to perform screening.

Health professional face-to-face appointment (Step 3)

A written letter will be used to invite eligible women to cervical cancer screening.

This intervention will be used only for women randomized to active comparator arm.

Written Letter

Firmino DB Machado, MD

This study aims to assess the effectiveness of a stepwise approach, with increasing complexity and cost, to improve adherence to organized cervical cancer screening: step 1a - customized text message invitation; step 1b - customized automatic phone call invitation; step 2 - secretary phone call; step 3 - health professionals face-to-face appointment.

A population-based randomized controlled trial will be implemented in Portuguese urban and rural areas. Women eligible for cervical cancer screening will be randomized (1:1) to intervention and control. In the intervention group, women will be invited for screening through text messages, automatic phone calls, manual phone calls and health professional appointments, to be applied sequentially to participants remaining non-adherent after each step. Control will be the standard of care (invitation by written letter).

As primary objectives, we intend to test the superiority of interventions based on step 1 (1a+1b) and multistage interventions based on steps 1 and 2 and steps 1 to 3, based on intention-to-treat analyses.

The secondary objectives will be the following:

1. To test the non-inferiority of interventions based on step 1a and step 1 (1a+1b), considering a non-inferiority limit of 5%;
2. To test the superiority of the specific components of the multistage intervention corresponding to step 2 and step 3;
3. To quantify the differences in adherence to cervical cancer screening, for interventions based on step 1 (1a+1b) and multistage interventions based on steps 1 and 2 and steps 1 to 3, between:

   1. Urban and rural areas;
   2. Younger and older population;
   3. Deprived and wealthy population;
   4. Never vs. ever users of screening;
   5. History of regular vs. irregular participation in screening programs.
4. To quantify the differences in adherence to cervical cancer screening when using a positive or a neutral content of text messages and automatic phone calls, in step 1;
5. To estimate the proportion of women who were performing cervical cancer screening in private health care services who started to be screened in an organized cervical cancer screening program, after a nurse face-to-face appointment at their primary care unit.

Intention-to-treat analysis will be used as primary strategy for all comparisons between interventions and control. Secondary per-protocol analysis will also be conducted. Binary logistic regression may be used to control for confounding, or in secondary analyses of the isolate effects of steps 1a, 2 and 3.

Stepwise Strategy to Improve CANcer Screening Adherence: Cervical Cancer

Stepwise Strategy to Improve Cervical Cancer Screening Adherence (SCAN-CC): Automatic Text Messages, Phone Calls and Face-to-face Interviews

Proportion/cumulative proportion of women who performed cervical cancer screening on scheduled date, among those who were invited to undergo it, after step 1 or sequences of steps from 1 to 3

Proportion of women who performed cervical cancer screening on scheduled date, among those who were invited to undergo it, after step 1a, after step 2 or after step 3

Proportion of received text messages, from those that were sent

Proportion of delivered automatic phone calls, from those that were sent

Proportion of women undergoing cervical cancer screening in a private health institution who changed to organized cervical cancer screening

Universidade do Porto

João Firmino Domingues Barbosa Machado

Principal Investigator

Skin and Connective Tissue Diseases

Breast Neoplasms

Breast Diseases

Skin Diseases

alert from SEBASTIAN decision support system

SEBASTIAN is an example of a clinical decision support technology that supports the latest, service-based architectural approach to CDSS implementation. Developed at Duke University, SEBASTIAN is a clinical decision support Web service whose interface is now the basis of the HL7 Decision Support Service draft standard SEBASTIAN places a standardized interface in front of clinical decision support knowledge modules and makes only limited demands on how relevant patient data are collected or on how decision support inferences are communicated to end-users

SEBASTIAN Clinical Decision Support System (CDSS)

Ana M Gomez, MD

Damian A Borbolla, MD

Clinical decision support has been shown to improve the performance of screening tests; however, few studies have documented direct clinical benefit resulting from the increased screening promoted by clinical decision support systems.

The purpose of this study was to determine if a standards-based, sophisticated decision support system could not only promote additional breast cancer screening, but also detect significantly more breast cancer

Breast cancer is the most common female cancer. In the United States, the second most common cause of cancer death in women, and the main cause of death in women ages 45 to 55 years old. The U.S. Preventive Services Task Force recommends screening mammography, with or without clinical breast examination, every one to two years among women aged 50 to 69 years old.

Recent research has shown that health care delivered in industrialized nations often falls short of optimal, evidence based care. US adults receive only about half of recommended care. To address these deficiencies in care, health-care organizations are increasingly turning to clinical decision support systems. A clinical decision-support system is any computer program designed to help health-care professionals to make clinical decisions. In a sense, any computer system that deals with clinical data or knowledge is intended to provide decision support.

Examples include manual or computer based systems that attach care reminders to the charts of patients needing specific preventive care services and computerized physician order entry systems that provide patient-specific recommendations as part of the order entry process. Such systems have been shown to improve prescribing practices, reduce serious medication errors, enhance the delivery of preventive care services, and improve adherence to recommended care standards.

The aim of this study is to show the efficacy of a decision-support system as a strategy for improving the performance of the mammography care process and the detection of significantly more breast cancer.

Effectiveness of a Decision Support System in Improving the Diagnosis and Screening Rate of Breast Cancer

New Breast Neoplasms Diagnosis (Incident cases from biopsy reports). Breast Neoplasms are stored in the institutional Clinical Data Repository. The diagnosis are automatically codified using a terminology server that use SNOMED-CT as reference terminology

Number of patient with breast cancer screening due that received the order to perform the study (mammography). This information will be record through the clinical data repository every time that a provider order a screening test to each of the patients involve in the study

Duke University

Hospital Italiano de Buenos Aires

All Drugs and Chemicals

Aromatase Inhibitors

Weekly SMS reminder to take aromatase inhibitors as prescribed by doctor

Weekly SMS reminder to take aromatase inhibitors as prescribed by doctor for 1 year

SMS reminder

Bee Choo Tai, PhD

The purpose of this study is to determine whether weekly SMS reminders are effective in improving medication adherence of adjuvant aromatase inhibitors in women with breast cancer.

This study is a prospective randomised controlled parallel trial of SMS reminder versus standard care to investigate whether SMS reminder improves adherence to oral aromatase inhibitor (AI) therapy amongst women with breast cancer at 1-year follow-up.

All subjects will be randomised to receive either SMS reminder or standard care in a 1:1 ratio. Balanced permuted block randomisation will be implemented with random varying of block sizes of 4 or 6.

The sample size is estimated based on the primary endpoint of medication adherence (as measured via SMAQ) at 1-year. Assuming that the proportion of medication adherence in the intervention and control groups are 80% and 60% respectively, then based on a 5% significance level and a power of 90%, a minimum sample of 240 subjects (i.e. 120 per group) will be required. Further assuming an attrition rate of 10%, the anticipated trial size is 280 overall.

The assessment of medication adherence at 1-year (as measured via SMAQ) between the SMS reminder and control groups will be made using chi-square test. Adjustment for baseline covariate and potential confounders will be made using the logistic regression where appropriate.

Other measures of adherence such as the 1-year MPR, PDC and pill count will be compared between treatment arms via the t- test, with adjustment for confounders made via the analysis of covariance (ANCOVA).

Natural log transformation will be implemented on the estrone and androstenedione measures to normalise the data. The assessment of secondary outcomes involving the log transformed estrone and androstenedione levels will be made using the analysis of covariance (ANCOVA) to adjust for the respective baseline levels and other potential confounders. Comparison of estradiol levels (defined as \<18.4 versus ≥18.4) between the two arms will be made using chi-square test. The logistic regression analysis will be implemented to adjust for baseline covariate and other potential confounders where appropriate.

The assessment of knowledge, attitude, behavior, as well as barrier and facilitating factors between the intervention and control groups will be made using chi-square test, with treatment effect quantified based on odds ratio estimate and its 95% CI. Further adjustment for baseline scores and other potential confounders will be made using the logistic regression where appropriate.

Additionally, the investigators will compare the 4 different measures of adherence in a separate paper, to determine which of these provide a more meaningful or reliable information in the local context based on sensitivity analysis.

All analyses will be performed according to intention-to-treat using STATA, assuming a two-sided test at the 5% level of significance.

SMS Reminders to Improve Medication Adherence of Aromatase Inhibitors

Improving Medication Adherence With Adjuvant Aromatase Inhibitor in Women With Breast Cancer: A Randomised Controlled Trial to Evaluate the Effect of Short Message Service (SMS) Reminder

The Beliefs about Medicines Questionnaire (BMQ)

Adherence Starts with Knowledge (ASK)-12 survey

Simplified medication adherence questionnaire (SMAQ)

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Stepwise Strategy to Improve CANcer Screening Adherence: Cervical Cancer	NCT03122275	Mass Screening Early Detection... Uterine Cervica... Text Message Reminder System...	Customized text... Customized auto... Secretary phone... Health professi... Written Letter	25 Years - 49 Years	Universidade do Porto
Stepwise Strategy to Improve CANcer Screening Adherence: Cervical Cancer	NCT03122275	Mass Screening Early Detection... Uterine Cervica... Text Message Reminder System...	Customized text... Customized auto... Secretary phone... Health professi... Written Letter	25 Years - 49 Years	Universidade do Porto
Effectiveness of a Decision Support System in Improving the Diagnosis and Screening Rate of Breast Cancer	NCT01336257	Breast Cancer	SEBASTIAN Clini...	50 Years - 69 Years	Hospital Italiano de Buenos Aires
SMS Reminders to Improve Medication Adherence of Aromatase Inhibitors	NCT02524548	Breast Cancer Medication Adhe...	SMS reminder	21 Years - 80 Years	National University of Singapore

Spots Global Cancer Trial Database for reminder systems