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| Name | Class |
|---|---|
| Azienda USL Reggio Emilia - IRCCS | OTHER_GOV |
| Azienda Ospedaliera Universitaria Policlinico | OTHER |
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This is a multicenter, observational study involving a retrospective collection of data. A total of potential 16 key performance indicators (KPIs) had been developed from a panel of experts (clinicians, IT experts, etc..) to investigate the appropriateness of care in NSCLC patients, with a special focus on the use of immunotherapy. The eligible population and data will be gathered retrospectively using an algorithm. Administrative databases will be used as unique resource: to identify target population and to collect patient's data with which measure KPIs.
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:
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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Patient pathway | Other | Investigation on the appropriateness and quality of NSCLC care among participating sites |
| Measure | Description | Time Frame |
|---|---|---|
| Key Performance indicators | 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. | six months |
| Measure | Description | Time Frame |
|---|---|---|
| Algorithm evaluatation | 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. | two month |
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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:
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The study population consisted of all adult patients (aged ≥ 18 years) residing in Emilia-Romagna region, identified in the Hospital discharge card, who has been discharged in any one of the participating sites (hospitals of Modena, Reggio-Emilia and Forlì-Cesena provinces) with a newly diagnosis of Non small cell lung cancer between January and December 2017.
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| Name | Affiliation | Role |
|---|---|---|
| Mattia Altini, Master | IRST | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| IRST | Meldola | Forlì-Cesena | 47014 | Italy | ||
| IRCCS Arcispedale S.Maria Nuova |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34561258 | Derived | Balzi W, Roncadori A, Danesi V, Massa I, Manunta S, Gentili N, Delmonte A, Crino L, Altini M. How to discriminate non-small cell lung cancer (NSCLC) cases from an Italian administrative database? A retrospective, secondary data use study for evaluating a novel algorithm performance. BMJ Open. 2021 Sep 24;11(9):e048188. doi: 10.1136/bmjopen-2020-048188. |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Sep 19, 2019 | Dec 4, 2020 | Prot_000.pdf |
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| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| D008175 | Lung Neoplasms |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
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| Reggio Emilia |
| RE |
| 42123 |
| Italy |
| Policlinico of Modena | Modena | 41125 | Italy |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |