The Benefits for Nurses of Using Psychosocial Cancer Registry Data

Carol G. Kelley, PhD, RN

Amy R. Lipson, PhD

Barbara Daly, PhD,RN

Sara L. Douglas, PhD, RN

Registries, large databases of patient information collected in a systematic, standardized fashion, most often focus on biologic measures, such as pathology, radiology, and laboratory results, to track incidence and prevalence of disease as well as causative factors. They also provide data for large-scale observations and measurement of outcomes of prevention, treatment, and measures of quality of care. Currently, the National Program of Cancer Registries collects data on cancer cases occurring among 96% of the US population.

A nurse-initiated psychosocial cancer registry can provide insight about quality of life (QOL) in patients with cancer.¹ Evidence about QOL, as perceived by the patient, is a concern of all clinicians but is of particular importance to the bedside nurse. There has been a great deal of study of QOL of cancer patients; however, most of these reports focus on narrow or limited samples and typically one specific cancer type. Having access to a registry that enrolled patients with diverse cancer types and collected QOL data could be very useful to practicing nurses.²

Before deciding to use a registry, it is important to know the characteristics of the patients enrolled. Data for our registry were collected in an outpatient clinic at an NCI-designed Comprehensive Cancer Center and included all cancer diagnoses and stages. Among the inclusion criteria were >18 years of age, ability to comprehend the English language, having a new diagnosis of cancer, and receiving ongoing care at the cancer center. Exclusion criteria were cognitive impairment or immediate referral for a bone marrow/ stem cell transplant, because much of this type of treatment is conducted in the inpatient setting.

Demographic and clinical data were gathered at enrollment, and QOL was measured using several questionnaires administered at enrollment, 3 months, and 9 months.

Patient demographic data included education level, employment status, and income. Cancer demographics were gathered for tumor type and staging and for the patient’s history of cancer and ECOG performance status.

The project was approved by the hospital’s Institutional Review Board. Of the 410 participants in this registry, the majority were married (64%), Caucasian (76%), and female (57%); the mean age was 59.6 (range, 18-90 years).

Several instruments were used in this registry to capture data about various aspects of QOL, including mood state, functional status, and spiritual well-being (Table). Measuring several dimensions of QOL is important in designing a registry so that it can serve a variety of purposes. For example, when planning to initiate or improve supportive care services by increasing access to palliative care or changing social services staffing,it would be useful to know if services should be targeted to patients with particular demographic or clinical characteristics.

Table 1.Second-Generation Proteasome Inhibitors

Instrument

Domain

Number of Items

Range of Scores

Enrollment

Demographics

Eastern Cooperative Oncology Group (ECOG)⁵

Performance status

1

0-5

Charlson comorbidity index⁶

Predicts 1-year mortality

19

0-37

Functional Assessment of Cancer Therapy-General Scale (FACT-G)⁷

Quality of life

27

0-108

Functional Assessment of Chronic Illness Therapy- Spiritual Well-Being Scale (FACIT-Sp)⁸

Spirituality

12

0-48

Profile of Mood States short form (POMS-SF)⁹

Mood state

30

20-100

Our results showed the mean and median scores of the FACT-G, which was used to assess QOL, were 80.3 and 82, respectively. With the exception of age, no statistically significant associations were found between QOL and patient characteristics. Patients who were older reported a higher QOL which is similar to previous findings about QOL and age.^3,4

These results support the importance of addressing QOL in all patients with cancer, regardless of stage or demographic characteristics.

Nurses at the bedside should not assume, for example, that patients with a late-stage cancer or with lower income or education levels are at higher risk of impaired QOL.

Nurse managers planning clinical programs to contribute to the QOL of patients undergoing cancer therapy should not target predetermined types or subsets of patients. Instead, screening patients on admission and throughout treatment would be a more reliable method to identify persons who might benefit from more intense support.

• Daly BJ, Douglas SL, Foley H, et al.Psychosocial registry for persons with cancer and their family caregivers: a method for facilitating quality of life and symptom research. Psychooncology. 2007;16(4):1-7.
• Kelley CG, Lipson AR, Daly B, Douglas SL. Using a psychosocial registry as a data source for nurses. Clin J Oncol Nurs. 2013;17(4):444-446.
• Burfeind WR, Tong BC, O’Branksi E, et al. Quality of life outcomes are equivalent after lobectomy in the elderly. J Thoracic and Cardiovasc Surg. 2008;136(3):597-604.
• Smith SK, Zimmerman S, Williams CS, Zebrack BJ. Health status and quality of life among non-Hodgkin lymphoma survivors. Cancer. 2009;115(14):3312-3323.
• Chaudhry S, Jin L, Meltzer D. Use of a self-report-generated Charlson comorbidity index for predicting mortality. Med Care. 2005;43(6):607-615.
• Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5(6):649- 655.
• Brucker PS, Yost K, Cashy J, et al. General population and cancer patient norms for the functional assessment of cancer therapy-general (FACT-G). Eval Health Prof. 2005;28(3):192-211.
• Peterman AH, Fitchett G, Brady MJ, et al. Measuring spiritual wellbeing in people with cancer: the Functional Assessment of Chronic Illness Therapy-Spiritual Well Being Scale (FACIT-Sp). Ann Behav Med. 2002;24(1):49-58.
• McNair DM, Lorr M, Droppleman LF. EdITS Manual for the Profile of Mood States. San Diego, CA: Educational and Industrial Testing Service;1992.