TY - JOUR
T1 - High hospital-related burden of treatment for multiple myeloma patients
T2 - outcomes of a feasibility study using reimbursement data from electronic health records
AU - Bennink, Christine
AU - van der Klift, Marjolein
AU - Sonneveld, Pieter
AU - Hazelzet, Jan A.
AU - Blommestein, Hedwig M.
N1 - Publisher Copyright:
© 2022 Fellowship of Postgraduate Medicine
PY - 2022/12
Y1 - 2022/12
N2 - Objective: Multiple Myeloma (MM) is an incurable plasma cell malignancy with intensive and prolonged treatment, presumably causing a considerable burden of treatment on patients. The concept of treatment burden is defined as the work of being a patient and its impact on well-being. However, there is no consistent definition and method to measure treatment burden in patients with MM. Therefore, the aim of this study was to determine the burden of treatment in MM patients and to compare it to Chronic Lymphoid Leukaemia (CLL). Methods: We conducted a retrospective analysis using reimbursement data from electronic health records (EHR) to calculate treatment burden. Treatment burden was defined as the number of hospital visits on unique days. After data clearance, data were analysed using descriptive statistics comparing treatment burden between different types of visits, age groups, years since diagnosis, and between MM and CLL patients. Results: Reimbursement data of 176 MM and 173 CLL patients were included in the analysis, which showed i) highest treatment burden in the first year immediately after diagnosis, ii) small differences between age groups (total visits year 0: 68.2 ≤ 65/63.8>65 years in MM and 21.7 ≤ 65/25.6>65 years in CLL), iii) higher treatment rates with more treatment burden in MM patients compared to CLL. Conclusion: EHR reimbursement data provided useful information to measure treatment burden and showed higher burden in MM patients compared to CLL patients. With improving survival, measuring burden of treatment in clinical practice in patients with MM contributes to decreasing treatment burden and more patient-centred care. Conclusion: EHR reimbursement data provided useful information to measure treatment burden and showed higher burden in MM patients compared to CLL patients. With improving survival, measuring burden of treatment in clinical practice in patients with MM contributes to decreasing treatment burden and more patient-centred care. Public interest summary: As in other malignant diseases, new treatment options dramatically improved survival in patients with multiple myeloma (MM). As a consequence, MM patients undergo intensive and intermittent periods of treatment, which causes a considerable burden of treatment. In this study we used data retrieved from Electronic Health Records (EHR) from 176 patients with MM and 173 patients with chronic lymphoid leukaemia (CLL) (both haematological diseases), to measure and analyse patients’ burden of undergoing treatment. The results showed that EHR-data provided useful information to determine treatment burden in patients and that treatment burden is considerably higher in patients with MM compared to CLL patients. Further development of this method makes it possible to frequently monitor and evaluate treatment burden. Eventually, this may help health care professionals to provide more patient-centred care and improve quality of life by reducing treatment burden.
AB - Objective: Multiple Myeloma (MM) is an incurable plasma cell malignancy with intensive and prolonged treatment, presumably causing a considerable burden of treatment on patients. The concept of treatment burden is defined as the work of being a patient and its impact on well-being. However, there is no consistent definition and method to measure treatment burden in patients with MM. Therefore, the aim of this study was to determine the burden of treatment in MM patients and to compare it to Chronic Lymphoid Leukaemia (CLL). Methods: We conducted a retrospective analysis using reimbursement data from electronic health records (EHR) to calculate treatment burden. Treatment burden was defined as the number of hospital visits on unique days. After data clearance, data were analysed using descriptive statistics comparing treatment burden between different types of visits, age groups, years since diagnosis, and between MM and CLL patients. Results: Reimbursement data of 176 MM and 173 CLL patients were included in the analysis, which showed i) highest treatment burden in the first year immediately after diagnosis, ii) small differences between age groups (total visits year 0: 68.2 ≤ 65/63.8>65 years in MM and 21.7 ≤ 65/25.6>65 years in CLL), iii) higher treatment rates with more treatment burden in MM patients compared to CLL. Conclusion: EHR reimbursement data provided useful information to measure treatment burden and showed higher burden in MM patients compared to CLL patients. With improving survival, measuring burden of treatment in clinical practice in patients with MM contributes to decreasing treatment burden and more patient-centred care. Conclusion: EHR reimbursement data provided useful information to measure treatment burden and showed higher burden in MM patients compared to CLL patients. With improving survival, measuring burden of treatment in clinical practice in patients with MM contributes to decreasing treatment burden and more patient-centred care. Public interest summary: As in other malignant diseases, new treatment options dramatically improved survival in patients with multiple myeloma (MM). As a consequence, MM patients undergo intensive and intermittent periods of treatment, which causes a considerable burden of treatment. In this study we used data retrieved from Electronic Health Records (EHR) from 176 patients with MM and 173 patients with chronic lymphoid leukaemia (CLL) (both haematological diseases), to measure and analyse patients’ burden of undergoing treatment. The results showed that EHR-data provided useful information to determine treatment burden in patients and that treatment burden is considerably higher in patients with MM compared to CLL patients. Further development of this method makes it possible to frequently monitor and evaluate treatment burden. Eventually, this may help health care professionals to provide more patient-centred care and improve quality of life by reducing treatment burden.
UR - http://www.scopus.com/inward/record.url?scp=85143173971&partnerID=8YFLogxK
U2 - 10.1016/j.hlpt.2022.100695
DO - 10.1016/j.hlpt.2022.100695
M3 - Article
AN - SCOPUS:85143173971
SN - 2211-8837
VL - 11
JO - Health Policy and Technology
JF - Health Policy and Technology
IS - 4
M1 - 100695
ER -