- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04676321
Key Performance Indicators for the Assessment of NSCLC Patients Pathway (KIND)
Key Performance Indicators for the Assessment of Diagnostic and Therapeutic Pathway of NSCLC Patients: a Multicenter Study (KIND NSCLC)
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
This is a multi-center, observational study involving retrospective collection of NSCLC patients information. All consecutive patients who had a newly diagnosis of NSCLC in 2017 from healthcare administrative database between January 2017 and December 2017, identified through the proposed algorithm, will be considered. All data needed for KPI calculation, even if they fall outside January-December 2017 period, will be collected. The end of data collection will be defined as patient death or 30 June 2018, whichever came first.
A set of potential KPIs had been developed from a panel of experts (clinicians, IT experts etc..) to investigate the appropriateness of activities within NSCLC care pathway, with a special focus on the use of immunotherapy. The following KPIs will be measured to investigate the appropriateness of NSCLC patient care pathways, with a special focus on the use of immunotherapy:
- Percentage of patients who performed biopsy within 7 days from the date of examination prescription;
- Percentage of metastatic NSCLC patients at diagnosis;
- Percentage of major surgical resections within the year of analysis;
- Percentage of surgical patients on the total number of patients with exploratory thoracotomy in inpatient setting;
- Percentage of patients undergoing neoadjuvant therapy ( CT or CT+RT within 6 months prior to the first major resection date;
- 30-day mortality rate from major surgery;
- Percentage of patients discussed in the multidisciplinary team (MDT) meeting at least once in the year of incidence;
- Percentage of patients who performed imaging exams such as MRI, TC and PET within 7 days from MDT meeting;
- Average and range of length of stay;
- Average time between biopsy and the first administration of systematic anti-cancer drug;
- Percentage of patients treated with immunotherapies;
- Percentage of patients who underwent immunotherapy for more than 6 months after first dose;
- Percentage of patients who underwent anti-cancer drug treatment in the last 30 days of life;
- Percentage of patients who underwent the first administration of systematic anticancer drug within 30 days from discussed in MDT meeting;
- Percentage of patients who underwent RT in the last 30 days of life ( excluded palliative treatments single fraction);
- Percentage of patients who underwent at least one Integrated Home Care (IHC);
- Percentage of patients who underwent at least one hospice care;
The eligible population and data will be gathered retrospectively through an algorithm from administrative databases (Hospital discharge cards, pharmaceutical databases as FED and AFT - direct and territorial distribution, the regional register of mortality REM, the regional register of outpatient specialist medical procedure ASA, the integrated home care IHC, and SDHS-hospice). Administrative data will be used as unique resource to identify patients cohort and to measure KPIs along care pathway. An evaluation of the NSCLC patients selection algorithm will be performed on a sub-population using the electronic health record EHR as gold standard.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
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Modena, Italy, 41125
- Policlinico of Modena
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Forlì-Cesena
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Meldola, Forlì-Cesena, Italy, 47014
- IRST
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RE
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Reggio Emilia, RE, Italy, 42123
- IRCCS Arcispedale S.Maria Nuova
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- patients identified from hospital administrative databases of Emilia-Romagna region using a case selection algorithm for identifying Non small cell lung cancer
Exclusion Criteria:
- patients not residing in Emilia Romagna region (due to the difficulty in obtaining the medical data).
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Key Performance indicators
Time Frame: six months
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To measure a set of potential indicators (KPIs) derived from administrative database in order to investigate the appropriateness and quality of NSCLC care among participating sites.
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six months
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Algorithm evaluatation
Time Frame: two month
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The secondary outcome is to develop and evaluate an algorithm to identify the eligible population of the study from administrative databases against to a clinical database.
Algorithm will be used to identify study eligible patients and measure KPIs from hospital administrative databases.
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two month
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Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Mattia Altini, Master, IRST
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- IRST 162.13
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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