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Planning for the Size of the Nursing Staff at an Outpatient Chemotherapy Unit

Rujnan Tuna
Ulku Baykal
Emine Turkmen
Aytolan Yildirim
CJON 2015, 19(6), E115-E120 DOI: 10.1188/15.CJON.E115-E120

Background: Use of a patient classification system particular to the unit, including size of nursing staff, is required for nurses to have adequate staffing and provide high-quality nursing care in oncology units.

Objectives: The study was conducted to create a planning system for nursing staff size for an outpatient chemotherapy unit at a university hospital.

Methods: The study was conducted with the nurses working in an outpatient chemotherapy unit of a university hospital and patients who received five weeks of treatment. Patients were classified by using the Magnuson Model. Data related to job analysis were collected by two independent observers who made measurements with a stopwatch, in line with safety and quality standards on the chemotherapy units.

Findings: A total of 1,795 patients who received care at the outpatient chemotherapy unit were classified using the model. Based on the job analysis, on average, 17.12 nurses per day were needed to care for the patients.

The scarcity of nurses in many countries has resulted in an increased workload for nurses and affects the quality and outcomes of patient care (Needleman et al., 2011). Regulating the workload of nurses is a vital component of the healthcare system that is improved by the implementation of an effective planning system for nursing staff size.

To plan the size of nursing staff required for patient care, the workload of nurses must be defined (Morris, MacNeela, Scott, Treacy, & Hyde, 2007). Patient classification systems are one method used for calculating nursing staff size and nurse workload. One classification system takes into account the duration of nursing care required by patients. The top priority of that patient classification system is aligning the patients’ requirements with the existing nurse resources (Giovannetti & Johnson, 1990; Hurst, 2002). Although many patient classification systems were developed for general purposes, newer ones were developed for specific patient groups and units (Shaha, 1995), including outpatient chemotherapy units.

Many cancer centers around the world use patient classification systems to direct nurse staffing with appropriate qualifications and quantity, establish nursing staff size planning, and satisfy care requirements of patients with cancer. At Warren Grant Magnuson Clinical Center in Bethesda, Maryland, Cusack, Jones-Wells, and Chisholm (2004) developed a nursing staff size planning system with patient classification for oncology units called the Magnuson Model. This easy-to-use system deals with care requirements of patients, as well as the illness level of each patient, and has been implemented in many oncology centers. Using this model, the patient classification system ranges from level I, lasting for 0–15 minutes as a minimum (venous catheter implementation, intramuscular and subcutaneous implementations), to level IV, lasting for four hours and more (complex chemotherapy cures) (Cusack et al., 2004; Hawley & Carter, 2009; Vivian, 2005; West & Sherer, 2009).

Cusack et al. (2004) developed another system that determines the average care period for each patient class. They also integrated the number of nurses required for the care needs of patients at every level in the care period based on an eight-hour full-time shift. A score of 1 corresponds to the daily workload of one nurse working on a full-time basis within the system. According to the system, with one nurse, 1.03 full-time care can be provided to a maximum of five patients, including 0.75 care requirement for two patients at level V and 0.28 care requirement for three patients at level III (Cusack et al., 2004; Jones, Cusack, & Chisholm, 2004; West & Sherer, 2009).

Despite an increase in cancer cases and number of patients across Turkey, failure to use patient classification systems specific to outpatient chemotherapy units and lack of nursing staff size planning specific to these units prevent nurses from planning and implementing high-quality nursing care (Republic of Turkey Ministry of Health Public Health Agency, 2013). In addition, oncology nurses face an increased workload (Clarke & Aiken, 2003; Tuna & Baykal, 2013). Therefore, it would be useful for planning and staffing to employ an easy-to-use patient classification system, such as the widely used Magnuson Model (Hawley & Carter, 2009; Vivian, 2005; West & Sherer, 2009).

It has been suggested that, because of an increased workload, nurses are unable to provide the necessary care to patients. In addition, they are more apt to experience emotional exhaustion and resentment toward their jobs (Barrett & Yates, 2002). A study conducted by Tuna and Baykal (2013) revealed that 74% of oncology nurses mentioned excessive workload and 83% of them cited an insufficient number of nurses in the oncology units, and that these factors increased work stress. In another study conducted by Lamkin, Rosiak, Buerhaus, Mallory, and Williams (2001), 50% of nurses stated that the number of nurses was insufficient and that they were responsible for more patients than they could care for. Studies have indicated that nursing shortages can have a negative effect on quality of care provided and can affect survival rates of patients, which increases healthcare costs (Vivian, 2005; West & Sherer, 2009). In line with such data, Turkey needs to employ a patient classification system specific to the needs of patients and nurses in outpatient chemotherapy units.

Methods

This study was conducted using the Magnuson Model patient classification system specific to outpatient chemotherapy units (Cusack et al., 2004). The model was tested to establish a nursing staff size planning system at an outpatient chemotherapy unit of the Cerrahpasa Faculty of Medicine at Istanbul University in Turkey. The study was expected to find answers to the following questions:

•   How large is the nursing staff size required according to workload as determined within the unit in line with patient classification?

•   Is there a difference between existing staff size on the unit and the recommended staffing based on planning from the patient classification system?

The sample for this study consisted of all nurses working in an outpatient chemotherapy unit of a university hospital and 1,795 patients treated during five weeks from the end of April 2013 to the end of May 2013. Nurses assigned to the outpatient chemotherapy unit ranged in age from 28–42 years (mean = 35.6, SD = 5.32). Their professional experience ranged from 3.5–20 years (mean = 14.1, SD = 6.88), with 1–15 years in oncology (mean = 8.25, SD = 5.85).

Setting

The study was conducted in an outpatient chemotherapy unit that operated from 8–16 hours per day using an appointment system. Appointments are grouped according to disease type, and five nurses who work full-time (eight hours) in the unit.

Instruments

Five tools were used for data collection for this study. A 17-item question form, developed by the researchers, aimed at identifying characteristics of nurses (e.g., age, professional experience, work experience in oncology) and the unit (e.g., working hours, days). A 22-item chemotherapy practices monitoring form was developed from safety and quality standards from the American Society of Clinical Oncology and Oncology Nursing Society with regard to chemotherapy practice. The form contains three parts: pretreatment control-preparation phase, implementation phase, and termination phase (Jacobson et al., 2012; Neuss et al., 2013). A five-item venous port catheter implementation monitoring form was used regarding venous port catheter implementation standards (Agency for Healthcare Research and Quality, 2015). A seven-item blood and blood products transfusion inspection form was used, which was made by taking into consideration blood transfusion standards (Murphy et al., 2001). Finally, a 24-item intramuscular and subcutaneous implementation monitoring form was used in accordance with nursing care protocols developed by Istanbul University nurse managers (Yıldırım et al., 2003).

Research Administration

After approval was received from Cerrahpasa Faculty of Medicine at Istanbul University and the ethics board, data were collected. Consent was obtained from the nurses working in the outpatient chemotherapy unit and patients receiving treatment.

Study data were collected at the outpatient chemotherapy unit for five weeks. In the unit, 1,795 patients received chemotherapy treatment, and the patients were classified using the patient classification system developed by Cusack et al. (2004) (see Figure 1). All procedures carried out by nurses working at the unit were entered simultaneously by two independent observers using inspection forms and measuring time required for the procedure using a stopwatch. Average care periods of each implementation at the level of every patient were calculated. The number of patients treated at the unit at each level for five weeks was multiplied by the average care period to calculate the workload for about a month for nurses on the unit. In this way, researchers assessed nursing staff size needed for an eight-hour shift dependent on the patient level.

Observers taking part in the study were also nurses with vast experience in oncology nursing and certified in chemotherapy administration. Correlation between independent observers was calculated, and level of correlation was found to be 98.2% (p = 0.001; intraclass correlation coefficient [ICC] = 0.982; 95% confidence interval [0.979, 0.985]).

Evaluation of Research Data

Study data were entered into an electronic database by the researcher and analyzed with the support of a statistics consultant using SPSS®, version 21.0, for statistical analyses. For the purpose of evaluation of the data, percentage, mean, standard deviation, and dual concordance were used. For evaluations between independent observers, ICC was used.

Findings

For five weeks, treatments and interventions in the outpatient chemotherapy unit were evaluated according to days of the week. Chemotherapy was administered to patients with gastrointestinal cancer (25%) on Mondays, for patients with lung cancer (24%) on Tuesdays, and for patients with breast cancer (26%) on Thursdays. Chemotherapy not specified by type (26%) was administered on Wednesdays and Fridays. Overall, 82% of patients received chemotherapy, 11% had additional treatments other than chemotherapy, 2.3% had venous port catheter irrigation, 2.1% received blood transfusions, and 2.6% had a venous port catheter removal procedure.

When reviewing average time for nursing intervention, researchers found that laboratory findings took 43.65 seconds (SD = 9.77), dose calculations for medications took 67.1 seconds (SD = 10.11), taking preventive measures took 73.28 seconds (SD = 61.78), medication preparation took 200.47 seconds (SD = 129.16), cases of medication spill took 106.71 seconds (SD =18.76), informing the patient prior to treatment took 282.67 seconds (SD = 68.49), establishing vascular access took 150.13 seconds (SD = 116.73), management of side effects of treatment took 950 seconds (SD = 192.61), post-treatment patient education took 150.58 seconds (SD = 25.03), inserting venous port needles took 136.02 seconds (SD = 30.01), follow-up of vital findings took 457.19 seconds (SD = 78.01), and reactions to blood transfusions took 1,050 seconds (SD = 212.13).

When considering percentage distribution of the treatments and averages of time for the treatment periods by patient levels, treatments were found to take 5.64 minutes (SD = 7.25) for level I patients (receiving treatment for 0–15 minutes) (see Table 1). For level II patients (receiving treatment for 16–30 minutes), treatments took 29.65 minutes (SD = 1.63). Level III patients (receiving treatment for 31–60 minutes) received treatments for 56.49 minutes (SD = 6.64). For level IV patients (receiving treatment for 61–120 minutes), treatment was given for 86.18 minutes (SD = 13.94). Patients at level V (receiving treatment for 121–240 minutes) received treatment for 180.09 minutes (SD = 32.1). For level VI patients (receiving treatment for 241 minutes or more), patients received treatment for 304.45 minutes (SD = 43.32).

Using the patient classification system, researchers determined how many treatments a nurse can implement working full-time for eight hours (see Table 2). The nursing staff size requirement for five weeks was an average of 17.12 nurses working on a full-time basis (see Table 3). An obvious increase occurred in the number of patients seen on Mondays, Tuesdays, and Thursdays.

Discussion

The majority of patients who visited the unit for five weeks had lung, gastrointestinal, and breast cancers, and patient density had an obvious rise on those days. When looking into incidence of cancer types observed in the world, it has been reported that lung and breast cancers comprise the majority (Cancer Research UK, 2012). In Turkey, it has been reported that 66% of all cancers in men are lung cancers, 41% of all cancers in women are breast cancers; these patients form a great majority of patients with cancer (Republic of Turkey Ministry of Health Public Health Agency, 2013).

This study showed that clustering patients diagnosed with the same type of cancer and chemotherapy regimens requiring similar efforts on the same day aggravates patient acuity and nurse workload. In other studies, excessive workload has several negative effects, including increased work dissatisfaction, work stress, and exhaustion, as well as decreased turnover speed and job performance in nurses (Clarke & Aiken, 2003; Darvas & Hawkins, 2002; Duffield & O’Brien-Pallas, 2003; Tuna & Baykal, 2013). In addition, it has been reported that the negative aspects arising out of excessive workload negatively affect patient safety and communication between patient and nurse (Davis, Kristjanson, & Blight, 2003; Lang, Hodge, Olson, Romano & Kravitz, 2004).

When looking into nursing interventions in the unit, medication preparation, patient education about treatment, and development of side effects were found to be the most time-consuming activities for nurses. Most of the treatments administered in the unit are chemotherapy treatments, which is important because patient education about potential adverse effects is essential. In studies, nurses have important responsibilities regarding assessment of adverse effects of chemotherapy, patient education, and provision of psychological support, which all require time (Shell, 2002; Zuk & Qinn, 2002).

According to the Magnuson Model, the average time to care is 7.5 minutes for level I patients, 22 minutes for level II patients, 45 minutes for level III patients, 90 minutes for level IV patients, 180 minutes for level V patients, and 360 minutes for level VI (Cusack et al., 2004; Jones et al., 2004). In this study, the average periods of time spent with level IV (86.18 minutes) and level V patients (180.09 minutes). In both studies, average durations spent for levels V and VI patients were close.

Patient classifications have five levels; however, even if these patient classifications consist of five levels, implementation of standard chemotherapy protocols and time spent with patients would be similar even if patient levels were grouped differently by the classification system (Delisle, 2009; Hawley & Carter, 2009). Using manpower planning with information from the patient classification system, it was determined that an average of 17.12 nurses are needed per shift on a full-time basis to care for the patients. Because only five nurses work on the unit at the study site, a remarkable difference clearly exists between what is required based on the classification system and the actual situation.

Insufficient numbers of nurses and excessive workload make it possible that negative effects, such as medication errors, might take place in the unit. Excessive workload at the chemotherapy units, work stress, nursing shortage, and low performance have been reported to give rise to mistakes in medication administration (Bailey, Engel, Luescher, & Taylor, 2008; Rinke, Shore, Morlock, Hicks, & Miller, 2007). Rinke et al. (2007) have the reported rate of erroneous medicine administration as high as 48%. Medication administration mistakes directly influence the safety and health of patients and include errors in dosage calculation and infusion speed, as well as mistakes during medicine preparation and administration of wrong medications to wrong patients (Rinke et al., 2007). In a study conducted with nurses at an oncology unit, Tang, Sheu, Yu, Wei, and Chen (2007) reported that the most important reasons for medicine administration mistakes were interpersonal conflicts (86%), excessive workload (38%), and new staff members (38%).

When findings of all studies are evaluated, the scarcity of nurses on chemotherapy units is apparent, and those units tend to require more intense labor and attention. Poor staffing and increased workload seem to be important elements affecting the physical and psychological well-being of employees and threaten the safety of patients. Therefore, more studies should be conducted to take into account the importance of nursing staff size planning. In terms of limitations, only one nurse was observed at a time because it was not possible to observe all nurses concurrently on the day of observation.

Conclusion

At the end of the study, the Magnuson Model for patient classification and nursing staff size planning was implemented on the unit. In addition, distribution of patient visits in the unit for treatment is now made depending on the classification levels of the patients, not the type of disease. The authors would suggest that outpatient chemotherapy units should use patient classification systems, make a balanced day-to-day patient distribution and staff size based on levels of patients, and find solutions for the nursing shortage to prevent administration mistakes, preserve employee health, and maintain patient safety.

References

Agency for Healthcare Research and Quality. (2015). Toolkit for reducing CAUTI in hospitals. Retrieved from http://www.ahrq.gov/professionals/quality-patient-safety/hais/tools/caut...

Bailey, C.G., Engel, B.S., Luescher, J.N., & Taylor, M.L. (2008). Medication errors in relation to education and medication errors in relation to years of nursing experience. Retrieved from http://www.lagrange.edu/resources/pdf/citations/nursing/medication%20err...

Barrett, L., & Yates, P. (2002). Oncology/hematology nurses: A study of job satisfaction, burnout, and intention to leave the specialty. Australian Health Review, 25, 109–121.

Cancer Research UK. (2012). Worldwide cancer incidence statistics. Retrieved from http://www.cancerresearchuk.org/cancer-info/cancerstats/world/incidence

Clarke, S.P., & Aiken, L.H. (2003). Failure to rescue. American Journal of Nursing, 103, 42–47.

Cusack, G., Jones-Wells, A., & Chisholm, L. (2004). Patient intensity in an ambulatory oncology research center: A step forward for the field of ambulatory care. Nursing Economics, 22, 58–63.

Darvas, J.A., & Hawkins, L.G. (2002). What makes a good intensive care unit: A nursing perspective. Australian Critical Care, 15, 77–82.

Davis, S., Kristjanson, L.J., & Blight, J. (2003). Communicating with families of patients in an acute hospital with advanced cancer: Problems and strategies identified by nurses. Cancer Nursing, 26, 337–345.

DeLisle, J. (2009). Designing an acuity tool for an ambulatory oncology setting. Clinical Journal of Oncology Nursing, 13, 45–50.

Duffield, C., & O’Brien-Pallas, L. (2003). The causes and consequences of nursing shortages: A helicopter view of the research. Australian Health Review, 26, 186–193.

Giovannetti, P., & Johnson, J.M. (1990). A new generation patient classification system. Journal of Nursing Administration, 20, 33–40.

Hawley, E., & Carter, N.G. (2009). An acuity rating system for infusion center nurse staffing. Oncology Issues, November/December, 34–37.

Hurst, K. (2002). Selecting and applying methods for estimating the size and mix of nursing teams: A systematic review of the literature commissioned by the Department of Health. Retrieved from http://www.who.int/hrh/documents/hurst_mainreport.pdf

Jacobson, J.O., Polovich, M., Gilmore, T.R., Schulmeister, L., Esper, P., LeFebvre, K.B., . . . Neuss, M.N. (2012). Revisions to the 2009 American Society of Clinical Oncology/Oncology Nursing Society chemotherapy administration safety standards: Expanding the scope to include inpatient settings. Journal of Oncology Practice, 8, 2–6.

Jones, A., Cusack, G., & Chisholm, L. (2004). Patient intensity in an ambulatory oncology research center: A step forward for the field of ambulatory care—Part II. Nursing Economics, 22, 120–123.

Lamkin, L., Rosiak, J., Buerhaus, P., Mallory, G., & Williams, M. (2001). Oncology Nursing Society workforce survey. Part 1: Perceptions of the nursing workforce environment and adequacy of nurse staffing in outpatient and inpatient oncology settings. Oncology Nursing Forum, 28, 1545–1552.

Lang, T.A., Hodge, M., Olson, V., Romano, P.S., & Kravitz, R.L. (2004). Nurse-patient ratios: A systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes. Journal of Nursing Administration, 34, 326–337.

Morris, R., MacNeela, P., Scott, A., Treacy, P., & Hyde, A. (2007). Reconsidering the conceptualization of nursing workload: Literature review. Journal of Advanced Nursing, 57, 463–471.

Murphy, M.F., Wallington, T.B., Kelsey, P., Boulton, F., Bruce, M., Cohen, H., . . . Williamson, L.M. (2001). Guidelines for the clinical use of red cell transfusions. British Journal of Haematology, 113, 24–31.

Needleman, J., Buerhaus, P., Pankratz, V.S., Leibson, C.L., Stevens, S.R., & Harris, M. (2011). Nurse staffing and inpatient hospital mortality. New England Journal of Medicine, 364, 1037–1045.

Neuss, M.N., Polovich, M., McNiff, K., Esper, P., Gilmore T.R., LeFebvre, K.B., . . . Jacobson, J.O. (2013). 2013 Updated American Society of Clinical Oncology/Oncology Nursing Society chemotherapy administration safety standards including standards for the safe administration and management of oral chemotherapy. Journal of Oncology Practice, 9, 5–13.

Republic of Turkey Ministry of Health Public Health Agency. (2013). Turkey cancer statistics. Retrieved from http://kanser.gov.tr/daire-faaliyetleri/kanser-istatistikleri.html

Rinke, M.L., Shore, A.D., Morlock, L., Hicks, R.W., & Miller, M.R. (2007). Characteristics of pediatric chemotherapy medication errors in a national error reporting database. Cancer, 110, 186-195.

Shaha, S.H. (1995). Acuity systems and control charting. Quality Management in Health Care, 3(3), 22–30.

Shell, J.A. (2002). Evidence-based practice for symptom management in adults with cancer: Sexual dysfunction. Oncology Nursing Forum, 29, 53–66.

Tang, F.I., Sheu, S.J., Yu, S., Wei, I.L., & Chen, C.H. (2007). Nurses relate the contributing factors involved in medication errors. Journal of Clinical Nursing, 16, 447–457.

Tuna, R., & Baykal, U. (2013). The job stress of the oncology nurses and influential factors. Florence Nightingale Journal of Nursing, 21, 92–100.

Vivian, A.G. (2005). Nurse resource allocation in ambulatory cancer centers. Oncology Issues, September/October, 36–42.

West, S., & Sherer, M. (2009). ISO: The “right” nurse staffing model. Oncology Issues, November/December, 26–30.

Yıldırım, A., Sayık, F., Kutlu, L., Aygün, P., Yeliltepe, G., User, R.., . . . Kosar, N. (2003). Nursing care protocols handbook. Retrieved from http://istanbultip.istanbul.edu.tr/wp-content/uploads/attachments/021_he...

Zuk, S.M., & Qinn, L.K. (2002). Cancer education: Using the evidence. Seminars in Oncology Nursing, 18, 60–65.

About the Author(s)

Rujnan Tuna, RN, PhD, is a research assistant in the Department of Nursing and Faculty of Health Sciences at the Istanbul Medeniyet University; Ulku Baykal, RN, PhD, is an associate professor in the Department of Nursing Management and the Florence Nightingale Faculty of Nursing at Istanbul University; Emine Turkmen, RN, PhD, is an assistant professor in the School of Nursing at Koc University; and Aytolan Yildirim, RN, PhD, is a professor in the Department of Nursing Management and the Florence Nightingale Faculty of Nursing at Istanbul University, all in Istanbul, Turkey. The authors take full responsibility for the content of the article. The authors did not receive honoraria for this work. The content of the article has been reviewed by independent peer reviewers to ensure that it is balanced, objective, and free from commercial bias. No financial relationships relevant to the content of this article have been disclosed by the authors, planners, independent peer reviewers, or editorial staff. Tuna can be reached at rujnantuna@yahoo.com, with copy to editor at CJONEditor@ons.org. (Submitted January 2015. Revision submitted March 2015. Accepted for publication March 18, 2015.)

 

References 

Agency for Healthcare Research and Quality. (2015). Toolkit for reducing CAUTI in hospitals. Retrieved from http://www.ahrq.gov/professionals/quality-patient-safety/hais/tools/caut...

Bailey, C.G., Engel, B.S., Luescher, J.N., & Taylor, M.L. (2008). Medication errors in relation to education and medication errors in relation to years of nursing experience. Retrieved from http://www.lagrange.edu/resources/pdf/citations/nursing/medication%20err...

Barrett, L., & Yates, P. (2002). Oncology/hematology nurses: A study of job satisfaction, burnout, and intention to leave the specialty. Australian Health Review, 25, 109–121.

Cancer Research UK. (2012). Worldwide cancer incidence statistics. Retrieved from http://www.cancerresearchuk.org/cancer-info/cancerstats/world/incidence

Clarke, S.P., & Aiken, L.H. (2003). Failure to rescue. American Journal of Nursing, 103, 42–47.

Cusack, G., Jones-Wells, A., & Chisholm, L. (2004). Patient intensity in an ambulatory oncology research center: A step forward for the field of ambulatory care. Nursing Economics, 22, 58–63.

Darvas, J.A., & Hawkins, L.G. (2002). What makes a good intensive care unit: A nursing perspective. Australian Critical Care, 15, 77–82.

Davis, S., Kristjanson, L.J., & Blight, J. (2003). Communicating with families of patients in an acute hospital with advanced cancer: Problems and strategies identified by nurses. Cancer Nursing, 26, 337–345.

DeLisle, J. (2009). Designing an acuity tool for an ambulatory oncology setting. Clinical Journal of Oncology Nursing, 13, 45–50.

Duffield, C., & O’Brien-Pallas, L. (2003). The causes and consequences of nursing shortages: A helicopter view of the research. Australian Health Review, 26, 186–193.

Giovannetti, P., & Johnson, J.M. (1990). A new generation patient classification system. Journal of Nursing Administration, 20, 33–40.

Hawley, E., & Carter, N.G. (2009). An acuity rating system for infusion center nurse staffing. Oncology Issues, November/December, 34–37.

Hurst, K. (2002). Selecting and applying methods for estimating the size and mix of nursing teams: A systematic review of the literature commissioned by the Department of Health. Retrieved from http://www.who.int/hrh/documents/hurst_mainreport.pdf

Jacobson, J.O., Polovich, M., Gilmore, T.R., Schulmeister, L., Esper, P., LeFebvre, K.B., . . . Neuss, M.N. (2012). Revisions to the 2009 American Society of Clinical Oncology/Oncology Nursing Society chemotherapy administration safety standards: Expanding the scope to include inpatient settings. Journal of Oncology Practice, 8, 2–6.

Jones, A., Cusack, G., & Chisholm, L. (2004). Patient intensity in an ambulatory oncology research center: A step forward for the field of ambulatory care—Part II. Nursing Economics, 22, 120–123.

Lamkin, L., Rosiak, J., Buerhaus, P., Mallory, G., & Williams, M. (2001). Oncology Nursing Society workforce survey. Part 1: Perceptions of the nursing workforce environment and adequacy of nurse staffing in outpatient and inpatient oncology settings. Oncology Nursing Forum, 28, 1545–1552.

Lang, T.A., Hodge, M., Olson, V., Romano, P.S., & Kravitz, R.L. (2004). Nurse-patient ratios: A systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes. Journal of Nursing Administration, 34, 326–337.

Morris, R., MacNeela, P., Scott, A., Treacy, P., & Hyde, A. (2007). Reconsidering the conceptualization of nursing workload: Literature review. Journal of Advanced Nursing, 57, 463–471.

Murphy, M.F., Wallington, T.B., Kelsey, P., Boulton, F., Bruce, M., Cohen, H., . . . Williamson, L.M. (2001). Guidelines for the clinical use of red cell transfusions. British Journal of Haematology, 113, 24–31.

Needleman, J., Buerhaus, P., Pankratz, V.S., Leibson, C.L., Stevens, S.R., & Harris, M. (2011). Nurse staffing and inpatient hospital mortality. New England Journal of Medicine, 364, 1037–1045.

Neuss, M.N., Polovich, M., McNiff, K., Esper, P., Gilmore T.R., LeFebvre, K.B., . . . Jacobson, J.O. (2013). 2013 Updated American Society of Clinical Oncology/Oncology Nursing Society chemotherapy administration safety standards including standards for the safe administration and management of oral chemotherapy. Journal of Oncology Practice, 9, 5–13.

Republic of Turkey Ministry of Health Public Health Agency. (2013). Turkey cancer statistics. Retrieved from http://kanser.gov.tr/daire-faaliyetleri/kanser-istatistikleri.html

Rinke, M.L., Shore, A.D., Morlock, L., Hicks, R.W., & Miller, M.R. (2007). Characteristics of pediatric chemotherapy medication errors in a national error reporting database. Cancer, 110, 186-195.

Shaha, S.H. (1995). Acuity systems and control charting. Quality Management in Health Care, 3(3), 22–30.

Shell, J.A. (2002). Evidence-based practice for symptom management in adults with cancer: Sexual dysfunction. Oncology Nursing Forum, 29, 53–66.

Tang, F.I., Sheu, S.J., Yu, S., Wei, I.L., & Chen, C.H. (2007). Nurses relate the contributing factors involved in medication errors. Journal of Clinical Nursing, 16, 447–457.

Tuna, R., & Baykal, U. (2013). The job stress of the oncology nurses and influential factors. Florence Nightingale Journal of Nursing, 21, 92–100.

Vivian, A.G. (2005). Nurse resource allocation in ambulatory cancer centers. Oncology Issues, September/October, 36–42.

West, S., & Sherer, M. (2009). ISO: The “right” nurse staffing model. Oncology Issues, November/December, 26–30.

Yıldırım, A., Sayık, F., Kutlu, L., Aygün, P., Yeliltepe, G., User, R.., . . . Kosar, N. (2003). Nursing care protocols handbook. Retrieved from http://istanbultip.istanbul.edu.tr/wp-content/uploads/attachments/021_he...

Zuk, S.M., & Qinn, L.K. (2002). Cancer education: Using the evidence. Seminars in Oncology Nursing, 18, 60–65.