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Effect of Health Literacy Education on Chemotherapy-Induced Nausea and Vomiting
Purpose: To improve patient understanding of recommended antiemetics and self-reported nausea following chemotherapy with a simple pill-identifying calendar handout.
Background: Chemotherapy-induced nausea and vomiting (CINV) is among the most severe adverse effects and important concerns in cancer patients. While there are multiple antiemetics available, dosing and timing can be confusing for patients, especially those with poor health literacy. Inadequate health literacy has been associated with poor self-management behaviors, and greater risk for non-compliance with treatment.
Methods: We assessed CINV in 25 patients treated in the Medical Oncology clinic at the University of Arkansas for Medical Sciences by using the existing validated Multinational Association of Supportive Care in Cancer (MASCC) Antiemesis Tool (MAT). We performed a Plan-Do-Study-Act (PDSA) cycle by implementing dosing calendar handouts with images and names of antiemetics scheduled per National Comprehensive Cancer Network (NCCN) guidelines.
Data Analysis: McNemar’s test was used for paired nominal data. Wilcoxon signed-rank test was utilized to evaluate differences in cohort means before and after intervention.
Results: At baseline, we utilized the MAT to document patient-reported incidence and severity of acute and delayed nausea and vomiting on a 10-point scale during one cycle of chemotherapy. Subsequently, we provided handouts for future cycles of chemotherapy. MAT was completed again following this intervention. Nausea was improved in 63% of patients. Vomiting was improved in 82% of patients. Severity of acute and delayed nausea improved from 4.40 (SD 4.25) to 2.54 (SD 2.28; P=0.008) and from 5.84 (SD 3.13) to 3.13 (SD 3.15, P=0.0016), respectively. Mean duration of nausea and vomiting was decreased from 3.72 days (SD 2.79) to 2.0 days (SD 2.55, P=0.0002). In addition, a single question was utilized to assess patient’s confidence in understanding their antiemetic regimen on a 10-point scale, which improved in 16 of 25 patients from a mean score of 7.84 (SD 1.97) to 9.50 (SD 1.18, P=0.0001).
Implications: Our calendar handout with pill images is an effective method to improve understanding of cancer treatment and decrease CINV in patients. As a result, a future PDSA cycle is planned to incorporate these handouts into our institution’s electronic medical record system.
Purpose: To improve patient understanding of recommended antiemetics and self-reported nausea following chemotherapy with a simple pill-identifying calendar handout.
Background: Chemotherapy-induced nausea and vomiting (CINV) is among the most severe adverse effects and important concerns in cancer patients. While there are multiple antiemetics available, dosing and timing can be confusing for patients, especially those with poor health literacy. Inadequate health literacy has been associated with poor self-management behaviors, and greater risk for non-compliance with treatment.
Methods: We assessed CINV in 25 patients treated in the Medical Oncology clinic at the University of Arkansas for Medical Sciences by using the existing validated Multinational Association of Supportive Care in Cancer (MASCC) Antiemesis Tool (MAT). We performed a Plan-Do-Study-Act (PDSA) cycle by implementing dosing calendar handouts with images and names of antiemetics scheduled per National Comprehensive Cancer Network (NCCN) guidelines.
Data Analysis: McNemar’s test was used for paired nominal data. Wilcoxon signed-rank test was utilized to evaluate differences in cohort means before and after intervention.
Results: At baseline, we utilized the MAT to document patient-reported incidence and severity of acute and delayed nausea and vomiting on a 10-point scale during one cycle of chemotherapy. Subsequently, we provided handouts for future cycles of chemotherapy. MAT was completed again following this intervention. Nausea was improved in 63% of patients. Vomiting was improved in 82% of patients. Severity of acute and delayed nausea improved from 4.40 (SD 4.25) to 2.54 (SD 2.28; P=0.008) and from 5.84 (SD 3.13) to 3.13 (SD 3.15, P=0.0016), respectively. Mean duration of nausea and vomiting was decreased from 3.72 days (SD 2.79) to 2.0 days (SD 2.55, P=0.0002). In addition, a single question was utilized to assess patient’s confidence in understanding their antiemetic regimen on a 10-point scale, which improved in 16 of 25 patients from a mean score of 7.84 (SD 1.97) to 9.50 (SD 1.18, P=0.0001).
Implications: Our calendar handout with pill images is an effective method to improve understanding of cancer treatment and decrease CINV in patients. As a result, a future PDSA cycle is planned to incorporate these handouts into our institution’s electronic medical record system.
Purpose: To improve patient understanding of recommended antiemetics and self-reported nausea following chemotherapy with a simple pill-identifying calendar handout.
Background: Chemotherapy-induced nausea and vomiting (CINV) is among the most severe adverse effects and important concerns in cancer patients. While there are multiple antiemetics available, dosing and timing can be confusing for patients, especially those with poor health literacy. Inadequate health literacy has been associated with poor self-management behaviors, and greater risk for non-compliance with treatment.
Methods: We assessed CINV in 25 patients treated in the Medical Oncology clinic at the University of Arkansas for Medical Sciences by using the existing validated Multinational Association of Supportive Care in Cancer (MASCC) Antiemesis Tool (MAT). We performed a Plan-Do-Study-Act (PDSA) cycle by implementing dosing calendar handouts with images and names of antiemetics scheduled per National Comprehensive Cancer Network (NCCN) guidelines.
Data Analysis: McNemar’s test was used for paired nominal data. Wilcoxon signed-rank test was utilized to evaluate differences in cohort means before and after intervention.
Results: At baseline, we utilized the MAT to document patient-reported incidence and severity of acute and delayed nausea and vomiting on a 10-point scale during one cycle of chemotherapy. Subsequently, we provided handouts for future cycles of chemotherapy. MAT was completed again following this intervention. Nausea was improved in 63% of patients. Vomiting was improved in 82% of patients. Severity of acute and delayed nausea improved from 4.40 (SD 4.25) to 2.54 (SD 2.28; P=0.008) and from 5.84 (SD 3.13) to 3.13 (SD 3.15, P=0.0016), respectively. Mean duration of nausea and vomiting was decreased from 3.72 days (SD 2.79) to 2.0 days (SD 2.55, P=0.0002). In addition, a single question was utilized to assess patient’s confidence in understanding their antiemetic regimen on a 10-point scale, which improved in 16 of 25 patients from a mean score of 7.84 (SD 1.97) to 9.50 (SD 1.18, P=0.0001).
Implications: Our calendar handout with pill images is an effective method to improve understanding of cancer treatment and decrease CINV in patients. As a result, a future PDSA cycle is planned to incorporate these handouts into our institution’s electronic medical record system.
Distress Screening at the Central Arkansas Veterans Healthcare System Hematology/Oncology Clinics: A Quality Improvement Project
Purpose: Distress screening (DS) of cancer patients is likely to improve access to supportive care services and adherence to cancer treatment.
Background: We assessed DS at the CAVHS and the University of Arkansas for Medical Sciences by completing Quality Oncology and Practice Initiatives (QOPI) survey. At baseline, we identified assessment of distress screening in only 15% of patients compared to the national average of 50%.
Methods: Based on QOPI data, we performed 3 Plan-Do-Study-Act (PDSA) cycles. We implemented a DS template on computer patient record system (CPRS) at the CAVHS hematology-oncology clinic, validated the template after initial use, and modified it in each PDSA cycle.
Results: At baseline DS was identified in 18 out of 121 charts (15%) per QOPI survey results in 2013 Spring Round. During our first PDSA cycle, we decided to add DS templates to all electronic medical notes in CPRS. We validated the template in 20 patient charts. Thereafter, in the second PDSA cycle, we modified the template and included distress thermometer (DT). After this intervention, we noted distress screening in 27 of 100 charts from 14 providers. Out of these 27 patients, 4 had a distress score of 4 or greater; these patients were all referred to subspecialty services. We did a third PDSA cycle and DS improved to 46% (51 out of 111 charts) on QOPI 2015 Spring Round. Subsequently, we added daily reminders at staff meetings, weekly e-mail reminders, and visual DT in each clinic room to perform DS and improved DS to 55 screenings out of 100 charts audited (27% to 55%). In these patients, only 1 had score of 4 and 7 had scores of 3. Intervention was offered in 15 out of 55 (27.2%) patients including counseling and referral to subspecialty services.
Conclusion: Distress screening is important for identifying patients who need intervention. QOPI is an excellent method of evaluating compliance to distress screening and PDSA cycles are effective in improving compliance. We improved DS by more than 200% using QOPI, PDSA and other quality improvement methods.
Purpose: Distress screening (DS) of cancer patients is likely to improve access to supportive care services and adherence to cancer treatment.
Background: We assessed DS at the CAVHS and the University of Arkansas for Medical Sciences by completing Quality Oncology and Practice Initiatives (QOPI) survey. At baseline, we identified assessment of distress screening in only 15% of patients compared to the national average of 50%.
Methods: Based on QOPI data, we performed 3 Plan-Do-Study-Act (PDSA) cycles. We implemented a DS template on computer patient record system (CPRS) at the CAVHS hematology-oncology clinic, validated the template after initial use, and modified it in each PDSA cycle.
Results: At baseline DS was identified in 18 out of 121 charts (15%) per QOPI survey results in 2013 Spring Round. During our first PDSA cycle, we decided to add DS templates to all electronic medical notes in CPRS. We validated the template in 20 patient charts. Thereafter, in the second PDSA cycle, we modified the template and included distress thermometer (DT). After this intervention, we noted distress screening in 27 of 100 charts from 14 providers. Out of these 27 patients, 4 had a distress score of 4 or greater; these patients were all referred to subspecialty services. We did a third PDSA cycle and DS improved to 46% (51 out of 111 charts) on QOPI 2015 Spring Round. Subsequently, we added daily reminders at staff meetings, weekly e-mail reminders, and visual DT in each clinic room to perform DS and improved DS to 55 screenings out of 100 charts audited (27% to 55%). In these patients, only 1 had score of 4 and 7 had scores of 3. Intervention was offered in 15 out of 55 (27.2%) patients including counseling and referral to subspecialty services.
Conclusion: Distress screening is important for identifying patients who need intervention. QOPI is an excellent method of evaluating compliance to distress screening and PDSA cycles are effective in improving compliance. We improved DS by more than 200% using QOPI, PDSA and other quality improvement methods.
Purpose: Distress screening (DS) of cancer patients is likely to improve access to supportive care services and adherence to cancer treatment.
Background: We assessed DS at the CAVHS and the University of Arkansas for Medical Sciences by completing Quality Oncology and Practice Initiatives (QOPI) survey. At baseline, we identified assessment of distress screening in only 15% of patients compared to the national average of 50%.
Methods: Based on QOPI data, we performed 3 Plan-Do-Study-Act (PDSA) cycles. We implemented a DS template on computer patient record system (CPRS) at the CAVHS hematology-oncology clinic, validated the template after initial use, and modified it in each PDSA cycle.
Results: At baseline DS was identified in 18 out of 121 charts (15%) per QOPI survey results in 2013 Spring Round. During our first PDSA cycle, we decided to add DS templates to all electronic medical notes in CPRS. We validated the template in 20 patient charts. Thereafter, in the second PDSA cycle, we modified the template and included distress thermometer (DT). After this intervention, we noted distress screening in 27 of 100 charts from 14 providers. Out of these 27 patients, 4 had a distress score of 4 or greater; these patients were all referred to subspecialty services. We did a third PDSA cycle and DS improved to 46% (51 out of 111 charts) on QOPI 2015 Spring Round. Subsequently, we added daily reminders at staff meetings, weekly e-mail reminders, and visual DT in each clinic room to perform DS and improved DS to 55 screenings out of 100 charts audited (27% to 55%). In these patients, only 1 had score of 4 and 7 had scores of 3. Intervention was offered in 15 out of 55 (27.2%) patients including counseling and referral to subspecialty services.
Conclusion: Distress screening is important for identifying patients who need intervention. QOPI is an excellent method of evaluating compliance to distress screening and PDSA cycles are effective in improving compliance. We improved DS by more than 200% using QOPI, PDSA and other quality improvement methods.