Virtual Library

Start Your Search

Semujju David

Author of

  • +

    P1.15 - Treatment in the Real World - Support, Survivorship, Systems Research (Not CME Accredited Session) (ID 947)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
    • +

      P1.15-06 - Integrative Quality Improvement for Management of Lung Cancer in Uganda (ID 14161)

      16:45 - 18:00  |  Presenting Author(s): Semujju David

      • Abstract


      Uganda is currently engaged in quality improvement initiatives for cancer patients. One of them is the creation of an integrative quality system, consisting of guideline development, quality indicators definition and feedback to hospitals. This approach has already been successfully implemented for five types of cancers: rectum (in collaboration with development partners), breast, testis, oesophagus and stomach. Building on previous experience, the study presents the development of a set of quality indicators (QIs) for the management of lung cancer.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      We followed the standardized MOH methodology to identify, select, test and measure the indicators. Because patients may be in contact with different hospitals (for instance, be diagnosed in one hospital but receive treatment – surgery or radiotherapy – in another), we developed a specific algorithm to attribute each patient to the centre where he/she was diagnosed or received treatment (surgical centre or centre of radiotherapy). The method to test the feasibility of identifying comorbidities of patients based on their pharmaceutical billing data during the year before the cancer diagnosis is also described.

      4c3880bb027f159e801041b1021e88e8 Result

      The results of this project made clear that we need more complete and accurate reporting of data to allow more precise and correct evaluation of the quality of care for lung cancer patients in Uganda. Quick and fluent data collection would make it possible to provide comprehensive feedback to care providers on a regular and timely basis. To make this happen, investments in data registration and analysis will be necessary.

      8eea62084ca7e541d918e823422bd82e Conclusion

      When benchmarking results between hospitals, cautious interpretation is warranted. The use of funnel plots avoids spurious ranking of hospitals and outlier dots can reliably designate either good or bad performers. Statistical modeling can often only partially account for differences in case-mix and other biases. Judging quality of care delivered by a hospital is further hindered by the often small number of patients treated per hospital. Hence, from a sheer statistical point of view, small volumes of activity make it impossible to offer an acceptable level of assurance about the quality delivered to the patient.