How to Analyze Palliative Care Outcome Data for Patients in Sub-Saharan Africa: An International, Multicenter, Factor Analytic Examination of the APCA African POS

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dc.contributor.authorHarding, Richard
dc.contributor.authorSelman, Lucy
dc.contributor.authorSimms, Victoria M.
dc.contributor.authorAgupio, Godfrey
dc.contributor.authorNatalya, Dinat
dc.contributor.authorIkin, Barbara
dc.contributor.authorMmoledi, Keletso
dc.contributor.authorSebuyira, Lydia Mpanga
dc.contributor.authorMwangi-Powell, Faith
dc.contributor.authorNamisango, Eve
dc.contributor.authorSiegert, Richard J.
dc.date.accessioned2022-07-01T13:39:13Z
dc.date.available2022-07-01T13:39:13Z
dc.date.issued2013
dc.description.abstractThe incidence of life-limiting progressive disease in sub-Saharan Africa presents a significant clinical and public health challenge. The ability to easily measure patient outcomes is essential to improving care.The present study aims to determine the specific factors (if any) that underpin the African Palliative Care Association African Palliative Outcome Scale to assist the analysis of data in routine clinical care and audit.Using self-reported data collected from patients with HIV infection in eastern and southern Africa, an exploratory factor analysis was undertaken with 1337 patients; subsequently, a confirmatory analysis was done on two samples from separate data sets (n = 445).Using exploratory factor analysis initially, both two- and three-factor solutions were examined and found to meet the criteria for simple structure and be readily interpretable. Then using confirmatory factor analysis on two separate samples, the three-factor solution demonstrated better fit, with Goodness-of-Fit Index values greater than 0.95 and Normative Fit Index values close to 0.90. The resulting three factors were 1) physical and psychological well-being, 2) interpersonal well-being, and 3) existential well-being.This analysis presents an important new opportunity in the analysis of outcome data for patients with progressive disease. It has advantages over both the total scoring of multidimensional scaling (which masks differences between domains) and of item scoring (which requires repeated analyses). The three factors map well onto the underlying concept and clinical goals of palliative care, and will enable audit of facility care.en_US
dc.identifier.citationHarding, R., Selman, L., Simms, V. M., Penfold, S., Agupio, G., Dinat, N., ... & Siegert, R. J. (2013). How to analyze palliative care outcome data for patients in Sub-Saharan Africa: an international, multicenter, factor analytic examination of the APCA African POS. Journal of pain and symptom management, 45(4), 746-752.https://doi.org/10.1016/j.jpainsymman.2012.04.007en_US
dc.identifier.issn0885-3924
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4145
dc.language.isoenen_US
dc.publisherJournal of pain and symptom managementen_US
dc.subjectPalliative, progressive, HIV, cancer, factor analysis, Africa, outcome measureen_US
dc.titleHow to Analyze Palliative Care Outcome Data for Patients in Sub-Saharan Africa: An International, Multicenter, Factor Analytic Examination of the APCA African POSen_US
dc.typeArticleen_US
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