Swipe om te navigeren naar een ander artikel
The online version of this article (doi:10.1007/s11136-016-1305-7) contains supplementary material, which is available to authorized users.
Patient experiences with symptom care need to be assessed and documented to ensure successful management of cancer-related symptoms. This paper details one method for creating symptom management quality improvement (SMQI) reports, including case-mix adjustment of patient-reported measures. Qualitative data regarding the acceptability of these reports at participating cancer centers (CCs) are also provided.
Data were collected from 2226 patients treated at 16 CCs via mailed/Web questionnaires. Twelve items assessing patient perceptions of symptom management—pain, fatigue, emotional distress—served as key quality indicators. Medico-demographic variables suitable for case-mix adjustment were selected using an index score combining predictive power and heterogeneity across CCs. SMQI reports were designed with staff feedback and produced for each CC, providing crude and adjusted CC-specific rates, along with study-wide rates for comparison purposes.
Cancer type and participant educational level were selected for case-mix adjustment based upon high index scores. The Kendall rank correlation coefficient showed that case-mix adjustments changed the ranking of CCs on the key quality indicators (% Δ rank range: 5–22 %). The key quality indicators varied across CCs (all p < 0.02). SMQI reports were well received by CC staff, who described plans to share them with key personnel (e.g., cancer committee, navigator).
This paper provides one method for creating hospital-level SMQI reports, including case-mix adjustment. Variation between CCs on key quality indicators, even after adjustment, suggested room for improvement. SMQI reports based on patient-reported data can inform and motivate efforts to improve care through professional/patient education and applying standards of care.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Supplementary material 1 (DOCX 38 kb)11136_2016_1305_MOESM1_ESM.docx
Jemal, A., Vineis, P., and Bray, F. (2014). The Cancer Atlas. The Cancer Atlas. July 17, 2015, http://canceratlas.cancer.org/the-burden/the-burden-of-cancer/.
Patrick, D. L., Ferketich, S. L., Frame, P. S., Harris, J. J., Hendricks, C. B., Levin, B., & Vernon, S. W. (2003). National institutes of health state-of-the-science conference statement: symptom management in cancer: Pain, depression, and fatigue, July 15–17, 2002. Journal of the National Cancer Institute, 95(15), 1110–1117. CrossRefPubMed
Kroenke, K., Zhong, X., Theobald, D., Wu, J., Tu, W., & Carpenter, J. S. (2010). Somatic symptoms in patients with cancer experiencing pain or depression: Prevalence, disability, and health care use. Archives of Internal Medicine, 170(18), 1686–1694. doi: 10.1001/archinternmed.2010.337. CrossRefPubMedPubMedCentral
Oberguggenberger, A., Hubalek, M., Sztankay, M., Meraner, V., Beer, B., Oberacher, H., & Holzner, B. (2011). Is the toxicity of adjuvant aromatase inhibitor therapy underestimated? Complementary information from patient-reported outcomes (PROs). Breast Cancer Research and Treatment, 128(2), 553–561. doi: 10.1007/s10549-011-1378-5. CrossRefPubMed
Assessing the quality of cancer care: An approach to measurement in Georgia. (2005). Washington, D.C.: National Academies Press. http://www.nap.edu/catalog/11244.
PROMIS. (n.d.). January 21, 2016, http://www.nihpromis.org/about/overview.
Patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE). (n.d.). January 21, 2016, http://healthcaredelivery.cancer.gov/pro-ctcae/.
Pouw, M. E., Peelen, L. M., Lingsma, H. F., Pieter, D., Steyerberg, E., Kalkman, C. J., & Moons, K. G. (2013). Hospital standardized mortality ratio: Consequences of adjusting hospital mortality with indirect standardization. PLoS ONE, 8(4), e59160. doi: 10.1371/journal.pone.0059160. CrossRefPubMedPubMedCentral
Smith, T. G., Castro, K. M., Troeschel, A. N., Arora, N. K., Lipscomb, J., Jones, S. M., & Clauser, S. B. (2015). The rationale for patient-reported outcomes surveillance in cancer and a reproducible method for achieving it. Cancer,. doi: 10.1002/cncr.29767.
NCI Community cancer centers program—About NCCCP overview. (n.d.). October 2, 2015, http://ncccp.cancer.gov/about/index.htm.
Halpern, M. T., Spain, P., Holden, D. J., Stewart, A., McNamara, E. J., Gay, G., & Clauser, S. (2013). Improving quality of cancer care at community hospitals: impact of the National Cancer Institute Community Cancer Centers Program pilot. Journal of Oncology Practice/American Society of Clinical Oncology, 9(6), e298–e304. doi: 10.1200/JOP.2013.000937. CrossRef
Siegel, R. D., Castro, K. M., Eisenstein, J., Stallings, H., Hegedus, P. D., Bryant, D. M., & Clauser, S. B. (2015). Quality improvement in the national cancer institute community cancer centers program: the quality oncology practice initiative experience. J Oncol Pract, 11(2), e247–e254. doi: 10.1200/jop.2014.000703. CrossRefPubMed
Standard definitions—AAPOR. (n.d.). January 21, 2016, http://www.aapor.org/AAPORKentico/Communications/AAPOR-Journals/Standard-Definitions.aspx.
Rea, L. M., & Parker, R. A. (1992). Designing and conducting survey research: A comprehensive guide. San Francisco: Jossey-Bass Publishers.
Mittlbock, M., & Schemper, M. (1996). Explained variation for logistic regression. Statistics in Medicine, 15(19), 1987–1997. doi: 10.1002/(sici)1097-0258(19961015)15:19<1987:aid-sim318>3.0.co;2-9. CrossRefPubMed
Menard, S. (2000). Coefficients of determination for multiple logistic regression analysis. The American Statistician, 54, 17–24.
Suchower, L. J., and Copenhaver, M. D. (n.d.). Using logistic regression to test for interaction in the presence of zero cells. http://www.lexjansen.com/nesug/nesug97/stat/suchower.pdf.
Agresti, A. (1996). An introduction to categorical data analysis. New Jersey: John Wiley & Sons Inc.
Bains, N. (2009). Standardization of rates. http://www.apheo.ca/resources/indicators/Standardization%20report_NamBains_FINALMarch16.pdf.
SAS Institute Inc. (n.d.). Cary, NC, USA.
R Development Core Team. (2008). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org.
New York City Department of Health and Mental Hygiene. (n.d.). BES data reliability flowchart. http://www.nyc.gov/html/doh/downloads/pdf/episrv/bes_data_reliability.pdf.
Klein, R. J., Proctor, S. E., Boudreault, M. A., and Turczyn, K. M. (2002). Healthy people 2010 criteria for data suppression. National Center for Health Statistics, Centers for Disease Control and Prevention. http://www.cdc.gov/nchs/data/statnt/statnt24.pdf.
Quality Oncology Practice Initiative (QOPI ®) and the QOPI Certification Program (QCP™) | ASCO Institute For Quality. (n.d.). January 21, 2016, http://www.instituteforquality.org/qopi-qcp.
Levit, L., Balogh, E., Nass, S., and Ganz, P. A. (2013). Delivering high-quality cancer care: Charting a new course for a system in crisis. Institute of Medicine. http://www.nap.edu/catalog/18359/delivering-high-quality-cancer-care-charting-a-new-course-for.
NCCN. (2015). NCCN clinical practice guidelines in oncology: Adult cancer pain Version 2.2015. National Comprehensive Cancer Network. http://www.nccn.org/professionals/physician_gls/pdf/pain.pdf.
NCCN. (2015). NCCN clinical practice guidelines in oncology: Cancer-related fatigue Version 2.2015. National Comprehensive Cancer Network. http://www.nccn.org/professionals/physician_gls/pdf/fatigue.pdf.
NCCN. (2015). NCCN clinical practice guidelines in oncology: Distress management Version 1.2015. National Comprehensive Cancer Network. http://www.nccn.org/professionals/physician_gls/PDF/distress.pdf.
- The development and acceptability of symptom management quality improvement reports based on patient-reported data: an overview of methods used in PROSSES
Ryan M. McCabe
Eliot L. Friedman
Patricia D. Hegedus
- Springer International Publishing