Abstract
Women who develop ovarian cancer usually present with advanced disease at diagnosis and these women are at high risk for prolonged physical problems and sustained psychological distress over their illness trajectory. The specific aims of the study are to:
- Test the effects of a standardized nursing intervention protocol (SNIP) on quality of life (QOL) outcomes (anxiety, depressive symptoms, overall QOL, and uncertainty) for adult women newly diagnosed with ovarian cancer at 1, 3, and 6 months post-hospitalization as compared to adult women newly diagnosed with ovarian cancer who receive usual attention control care plus.
- Test the effects of SNIP on costs of care, including health services resource use.
- Explore the differential effects of SNIP on patterns of symptom distress, number of symptoms, dimensions of QOL, number of complications, resource utilization including rehospitalizations, and survival.
The design is a single blind, randomized clinical trial study to test the effects of a SNIP in 225 patients with ovarian cancer at 1, 3, and 6 months post-hospitalization. The intervention is provided by an oncology advanced practice nurse working in consultation with a psychiatric consultation-liaison nurse over a 5 month period including post-surgical care and the initiation of chemotherapy. The effects of the intervention will be evaluated using self-report questionnaires administered at pre-treatment, 1, 3, and 6 months post-hospitalization. The intervention will be demonstrated to be cost effective when compared to costs incurred by patients who do not receive it. Cost data will be obtained from the Resource Information Management System at Yale-New Haven Hospital to measure directly required resources. Additional mediating or outcome variables include: patterns of symptom distress, dimensions of QOL, number of complications, resource utilization including rehospitalizations, and survival. Data analysis will include: mean difference analyses, individual difference analyses, and outcome analyses. The primary analysis will be a multivariate analysis of covariance with repeated measures.
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