Skip to main content
Log in

The development and acceptability of symptom management quality improvement reports based on patient-reported data: an overview of methods used in PROSSES

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

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.

Methods

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.

Results

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).

Conclusions

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. 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/.

  2. 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.

    Article  PubMed  Google Scholar 

  3. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cella, D., & Fallowfield, L. J. (2008). Recognition and management of treatment-related side effects for breast cancer patients receiving adjuvant endocrine therapy. Breast Cancer Research and Treatment, 107(2), 167–180. doi:10.1007/s10549-007-9548-1.

    Article  CAS  PubMed  Google Scholar 

  5. Banna, G. L., Collovà, E., Gebbia, V., Lipari, H., Giuffrida, P., Cavallaro, S., & Ferraù, F. (2010). Anticancer oral therapy: emerging related issues. Cancer Treatment Reviews, 36(8), 595–605. doi:10.1016/j.ctrv.2010.04.005.

    Article  PubMed  Google Scholar 

  6. Barbera, L., Seow, H., Howell, D., Sutradhar, R., Earle, C., Liu, Y., & Dudgeon, D. (2010). Symptom burden and performance status in a population-based cohort of ambulatory cancer patients. Cancer, 116(24), 5767–5776. doi:10.1002/cncr.25681.

    Article  PubMed  Google Scholar 

  7. 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.

    Article  CAS  PubMed  Google Scholar 

  8. 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.

  9. Chen, J., Ou, L., & Hollis, S. (2013). A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Services Research, 13(1), 211.

    Article  PubMed  PubMed Central  Google Scholar 

  10. PROMIS. (n.d.). January 21, 2016, http://www.nihpromis.org/about/overview.

  11. 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/.

  12. O’Malley, A. J., Zaslavsky, A. M., Elliott, M. N., Zaborski, L., & Cleary, P. D. (2005). Case-mix adjustment of the CAHPS hospital survey. Health Services Research, 40(6 Pt 2), 2162–2181. doi:10.1111/j.1475-6773.2005.00470.x.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Johnson, M. L., Rodriguez, H. P., & Solorio, M. R. (2010). Case-mix adjustment and the comparison of community health center performance on patient experience measures. Health Services Research, 45(3), 670–690. doi:10.1111/j.1475-6773.2010.01101.x.

    Article  PubMed  PubMed Central  Google Scholar 

  14. D’Agostino, R. B. (1998). Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Statistics in Medicine, 17(19), 2265–2281.

    Article  PubMed  Google Scholar 

  15. Austin, P. C., & Mamdani, M. M. (2006). A comparison of propensity score methods: A case-study estimating the effectiveness of post-AMI statin use. Statistics in Medicine, 25(12), 2084–2106. doi:10.1002/sim.2328.

    Article  PubMed  Google Scholar 

  16. Leung, K. M., Elashoff, R. M., Rees, K. S., Hasan, M. M., & Legorreta, A. P. (1998). Hospital- and patient-related characteristics determining maternity length of stay: a hierarchical linear model approach. American Journal of Public Health, 88(3), 377–381.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. 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.

    Google Scholar 

  19. NCI Community cancer centers program—About NCCCP overview. (n.d.). October 2, 2015, http://ncccp.cancer.gov/about/index.htm.

  20. 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.

    Article  Google Scholar 

  21. 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.

    Article  PubMed  Google Scholar 

  22. Standard definitions—AAPOR. (n.d.). January 21, 2016, http://www.aapor.org/AAPORKentico/Communications/AAPOR-Journals/Standard-Definitions.aspx.

  23. Rea, L. M., & Parker, R. A. (1992). Designing and conducting survey research: A comprehensive guide. San Francisco: Jossey-Bass Publishers.

    Google Scholar 

  24. 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.

    Article  CAS  PubMed  Google Scholar 

  25. Menard, S. (2000). Coefficients of determination for multiple logistic regression analysis. The American Statistician, 54, 17–24.

    Google Scholar 

  26. 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.

  27. Agresti, A. (1996). An introduction to categorical data analysis. New Jersey: John Wiley & Sons Inc.

    Google Scholar 

  28. Bains, N. (2009). Standardization of rates. http://www.apheo.ca/resources/indicators/Standardization%20report_NamBains_FINALMarch16.pdf.

  29. SAS Institute Inc. (n.d.). Cary, NC, USA.

  30. 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.

  31. 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.

  32. 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.

  33. 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.

  34. Bennett, M. I., Bagnall, A.-M., & José Closs, S. (2009). How effective are patient-based educational interventions in the management of cancer pain? Systematic review and meta-analysis. Pain, 143(3), 192–199. doi:10.1016/j.pain.2009.01.016.

    PubMed  Google Scholar 

  35. 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.

  36. 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.

  37. 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.

  38. 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.

  39. Landon, B. E., Normand, S.-L. T., Blumenthal, D., & Daley, J. (2003). Physician clinical performance assessment: Prospects and barriers. JAMA, 290(9), 1183–1189. doi:10.1001/jama.290.9.1183.

    Article  CAS  PubMed  Google Scholar 

  40. Eliasson, B., & Gudbjörnsdottir, S. (2014). Diabetes care—improvement through measurement. Diabetes Research and Clinical Practice, 106(Supplement 2), S291–S294. doi:10.1016/S0168-8227(14)70732-6.

    Article  PubMed  Google Scholar 

  41. Kiefe, C. I., Allison, J. J., Williams, O., Person, S. D., Weaver, M. T., & Weissman, N. W. (2001). Improving quality improvement using achievable benchmarks for physician feedback: A randomized controlled trial. JAMA, 285(22), 2871–2879. doi:10.1001/jama.285.22.2871.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors are grateful for the contributions of the patients and clinicians who participated in this study. We appreciate contributions from the PROSSES Study Group: M Sitki Copur, MD, FACP; Kendra E. Johnson, MPH, CTR; Kevin Yiee, MD, MPH; Patricia Swanson, BSN; Kristi Olesen, BSBA; Mildred Nunez Jones, CTR, BA; Michaela Sherbeck, RN, BSN, OCN, CCR. We thank Rose Menton and Lance Grove for their data collection from St. Joseph- Towson; Andrew Salner, Susan Wright and Donna Handley from Hartford Hospital; James Bearden and Lucy Gansauer from Spartanburg Regional Hospital; Craig Schulz and Nichole Nikolic from Columbia St. Mary; David Hanson, Renea Duffin, and Linda Lee from Our Lady of the Lake Regional Medical Center; John Schallenkamp, Jo Duszkiewicz and Sarah Porter-Osen from Billings Clinic; Jay Harness and Pam Hockett from St. Joseph’s Hospital- Orange; and Debbie Salas-Lopez, Suresh Nair and Keith Weinhold from Lehigh Valley Hospital. Deborah Hill, from Leidos Biomedical Research, Inc. and Connie Hobbs, from RTI International, provided important study-related communication and administration tasks. We also acknowledge Kevin Stein, Elizabeth Ward, Otis Brawley and the American Cancer Society Mission Outcomes Committee for strategic advice.

Funding

This project has been funded by the American Cancer Society Intramural Research Department and with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views of policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tenbroeck Smith.

Ethics declarations

Conflict of interest

The authors declare they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 38 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Troeschel, A., Smith, T., Castro, K. et al. The development and acceptability of symptom management quality improvement reports based on patient-reported data: an overview of methods used in PROSSES. Qual Life Res 25, 2833–2843 (2016). https://doi.org/10.1007/s11136-016-1305-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-016-1305-7

Keywords

Navigation