Cancer Care Team's Management of Clinical Alerts Generated by Electronically Collected Patient Reported Outcomes: We Could Do Better.

Electronically administered patient-reported outcome measures (ePROMs) are effective digital health tools for informing clinicians about cancer patients' symptoms and facilitating timely patient-centred care. This paper describes the delivery of healthcare activities supported by the PROMPT-Care model, including ePROMs generated clinical alerts, cancer care team (CCT) response to alerts, and patients' perceptions of the CCT response and ePROMs system. This mixed-methods study includes cancer patients from four cancer therapy centres in New South Wales, Australia. Quantitative and qualitative data were collected regarding clinical alert activity, CCT response, and patient perceptions of the CCT responses and ePROMs system. Qualitative data were thematically analysed. Of the 328 participants whose care was informed by the digital health tool, 70.8% (n = 233) generated at least one alert during the trial period, with 877 alerts generated in total. Although 43.7% (n = 383) were actioned by the CCT, at least 80% of participants found follow-up CCT phone calls beneficial, with multiple benefits confirmed in interviews. The cancer care delivery arm of the PROMPT-Care trial involving clinical alerts to the CCT was positively perceived by most participants, resulting in a diverse range of benefits. However, further work is required, informed by implementation science, to improve the percentage of actioned clinical alerts.

Adapting an integrated care pathway for implementing electronic patient reported outcomes assessment in routine oncology care: Lessons learned from a case study.

RATIONALE, AIMS AND OBJECTIVE: Details of the development and implementation of integrated care pathways (ICPs) in the context of electronic collection of patient reported outcomes (ePROs) for cancer patients are largely lacking in the literature. This study describes what, why and how decisions were made to adapt and implement an ePROs ICP for patients with lung cancer. METHODS: A consensus process was utilized, with the implementation advisory group including multidisciplinary representation from three participating hospitals, to identify local champions and adapt and incorporate the ePRO ICP into the local contexts. Engagement meetings were documented via meeting transcripts, and detailed notes from October 2019 to November 2020 were content-analysed to identify decision-making themes based on the Consolidated Framework for Implementation Research; workflows and process maps were reviewed and modified to integrate ePROs. RESULTS: In total, 55 engagement activities were held (24 meetings, 20 workshops 11 educational sessions), with n = 96 staff from multiple disciplines participating in the ePROs implementation through advisory meetings, process mapping, change management and staff education. Decisions were made regarding eligible patient cohorts to include, the process for onboarding patients onto the ePRO system, and follow-up and referral pathways. Rationales for decisions included alignment with existing workflows, utilizing available staff, minimizing staff and patient burden and maximizing patient engagement. CONCLUSION: Existing resources, staff input and technical and logistical reasons often guided the ICP decisions, highlighting the need for in-depth engagement across all stakeholders for optimal implementation of ePRO ICPs. The ePRO implementation required substantial dialogue and systematic resolution to reach agreement on the final processes. Adapting the local ICP through rigorous engagement facilitated the successful implementation of ePROs as business-as-usual at all three cancer centres. Involving all relevant stakeholders is critical to the successful adaptation of ICPs before their introduction into routine care.

Variation in the use of radiotherapy fractionation for breast cancer: Survival outcome and cost implications.

BACKGROUND AND PURPOSE: Substantial variation in the adoption of hypofractionation for breast radiation therapy has been observed, despite the availability of consensus guidelines. This study aimed to investigate the variation in radiation therapy fractionation in breast cancer patients in New South Wales (NSW), Australia, and to estimate survival outcome and cost implications. MATERIALS AND METHODS: This is a population-based cohort of patients who received radiation therapy for breast cancer (2009-2013), as captured in the NSW Central Cancer Registry. A logistic regression model was used to identify factors associated with fractionation type. Survival outcome was estimated using multivariable Cox proportional hazards model. Cost per treatment and potential cost saving associated with evidence-based fractionation was estimated. RESULTS: A total of 10,482 patients were available for analysis, divided into 3 cohorts (breast alone: N = 7000; breast + nodes: N = 1119; all chestwall: N = 2363). In multivariable analysis, increasing age, laterality (right), year of treatment (2013), early stage, lower socioeconomic status, and regional area of residence were independent predictors of hypofractionation for breast alone radiation therapy. For the breast + nodes and chest wall cohorts, common factors that predicted the use of hypofractionation were increasing age. In multivariable survival analysis, there was no difference between the fractionation regimens at 5 years. Estimated radiation therapy cost of this cohort approximated $52.1 million, compared with $38.5 million had these patients been treated with evidence-based fractionation. This demonstrated a potential saving of $13.6 million. CONCLUSION: Hypofractionation appears underused for breast radiation therapy in NSW over time. This study highlights that evidence-based practice will translate to reduced health care treatment costs.

Estimating the cost of radiotherapy for 5-year local control and overall survival benefit.

BACKGROUND AND PURPOSE: Escalating health care costs have led to greater efforts directed at measuring the cost and benefits of medical treatments. The aim of this study was to estimate the costs of 5-year local control and overall survival benefits of radiotherapy for the cancer population in Australia. MATERIALS AND METHODS: The local control and overall survival benefits of radiotherapy at 5-years and optimal number of fractions per course have been estimated for 26 tumour sites for which radiotherapy is indicated. For this study, a hybrid approach that merges features from activity based costing (ABC) and relative value units costing (RVU) were used to provide cost estimates. ABC methodology was used to allocate costs to all radiotherapy activities associated with each patient's treatment course, while the RVUs represent the cost of each radiotherapy activity relative to the average cost of all activities and were used to achieve a weighted cost allocation. A patient's journey for the financial year was constructed by consolidating all the radiotherapy activities and their associated costs, and the average cost per activity (fraction) was determined. The cost of radiotherapy per 5-year overall survival and local control was then estimated. RESULTS: The estimated population 5-year local control and overall survival benefits of radiotherapy for all cancer were 23% and 6%, respectively. The optimal number of fractions per treatment course if guidelines were followed was 19.4 fractions. The average cost per fraction for all cancer was AU$276. The estimated cost of radiotherapy was AU$23,585 per 5-year local control and AU$86,480 per 5-year overall survival (equivalent to 5 life years) for all cancer. CONCLUSION: The cost of AU$86,480 per 5-year overall survival would translate to AU$17,296 1-year overall survival. Therefore, the cost of radiotherapy is inexpensive if delivered optimally. Policy implications from this study include knowledge about cost to deliver radiotherapy to allow one to quantify the expected benefit at a population level.

A Standard Set of Value-Based Patient-Centered Outcomes for Breast Cancer: The International Consortium for Health Outcomes Measurement (ICHOM) Initiative.

A major challenge in value-based health care is the lack of standardized health outcomes measurements, hindering optimal monitoring and comparison of the quality of health care across different settings globally. The International Consortium for Health Outcomes Measurement (ICHOM) assembled a multidisciplinary international working group, comprised of 26 health care providers and patient advocates, to develop a standard set of value-based patient-centered outcomes for breast cancer (BC). The working group convened via 8 teleconferences and completed a follow-up survey after each meeting. A modified 2-round Delphi method was used to achieve consensus on the outcomes and case-mix variables to be included. Patient focus group meetings (8 early or metastatic BC patients) and online anonymized surveys of 1225 multinational BC patients and survivors were also conducted to obtain patients' input. The standard set encompasses survival and cancer control, and disutility of care (eg, acute treatment complications) outcomes, to be collected through administrative data and/or clinical records. A combination of multiple patient-reported outcomes measurement (PROM) tools is recommended to capture long-term degree of health outcomes. Selected case-mix factors were recommended to be collected at baseline. The ICHOM will endeavor to achieve wide buy-in of this set and facilitate its implementation in routine clinical practice in various settings and institutions worldwide.

Assessment of dose variation for accelerated partial-breast irradiation using rigid and deformable image registrations.

PURPOSE: The aim of this study was to estimate the delivered dose to the target and organs at risk (OAR) for external beam accelerated partial-breast irradiation (APBI) accounting for day-to-day setup uncertainties, using rigid and deformable image registration. METHODS AND MATERIALS: One planning computed tomography (CT) scan and 5 cone beam CT scans for each of 25 patients previously treated with tangential breast radiation therapy were used. All cone beam CT scans were registered to the planning CT scan using 3 techniques: (1) rigid registration based on bony anatomy only, (2) rigid registration based on soft-tissue only, and (3) deformable image registration. For each patient, 4 dose distributions were calculated for APBI. The first dose distribution was the original plan. The other 3 were "dose-of-the-day" for each of the registration approaches. The effects of image registrations on estimating delivered dose to targets and OAR were determined. RESULTS: The average reductions in V95 (percentage of the PTV that received 95% of the prescribed dose) were 6%, 7%, and 5% for bone, soft-tissue, and deformable registrations, respectively. The average increase in mean dose to the heart were 9%, 9%, and 18% for bone, soft-tissue, and deformable registrations, respectively, whereas the average increase in maximum dose to the contralateral breast were 19%, 20%, and 28%, respectively. CONCLUSIONS: The results of this study have shown that there are differences between the planned and estimated delivered dose for APBI because of day-to-day setup uncertainties that may need to be accounted for. Estimated dosimetric impact of setup variation and breast deformation assessed using deformable registration was greater for OARs and smaller for target volumes compared to rigid registration.

Comparison of setup accuracy of three different image assessment methods for tangential breast radiotherapy.

INTRODUCTION: To compare the differences in setup errors measured with electronic portal image (EPI) and cone-beam computed tomography (CBCT) in patients undergoing tangential breast radiotherapy (RT). Relationship between setup errors, body mass index (BMI) and breast size was assessed. METHODS: Twenty-five patients undergoing postoperative RT to the breast were consented for this study. Weekly CBCT scans were acquired and retrospectively registered to the planning CT in three dimensions, first using bony anatomy for bony registration (CBCT-B) and again using breast tissue outline for soft tissue registration (CBCT-S). Digitally reconstructed radiographs (DRR) generated from CBCT to simulate EPI were compared to the planning DRR using bony anatomy in the V (parallel to the cranio-caudal axis) and U (perpendicular to V) planes. The systematic (Σ) and random (σ) errors were calculated and correlated with BMI and breast size. RESULTS: The systematic and random errors for EPI (ΣV = 3.7 mm, ΣU = 2.8 mm and σV = 2.9 mm, σU = 2.5) and CBCT-B (ΣV = 3.5 mm, ΣU = 3.4 mm and σV = 2.8 mm, σU = 2.8) were of similar magnitude in the V and U planes. Similarly, the differences in setup errors for CBCT-B and CBCT-S in three dimensions were less than 1 mm. Only CBCT-S setup error correlated with BMI and breast size. CONCLUSIONS: CBCT and EPI show insignificant variation in their ability to detect setup error. These findings suggest no significant differences that would make one modality considered superior over the other and EPI should remain the standard of care for most patients. However, there is a correlation with breast size, BMI and setup error as detected by CBCT-S, justifying the use of CBCT-S for larger patients.

Assessment of MRI image quality for various setup positions used in breast radiotherapy planning.

This study investigates breast magnetic resonance imaging (MRI) image quality for 3 different breast radiotherapy positions (prone, supine flat and supine inclined) and associated choice of breast coils. Supine breast MRI has comparable image quality to prone breast MRI for the purposes of radiotherapy delineation for T2-weighted sequences.

Estimating the demand for radiotherapy from the evidence: a review of changes from 2003 to 2012.

BACKGROUND AND PURPOSE: In 2003 we estimated that 52.3% of new cases of cancer in Australia had an indication for external beam radiotherapy at least once at some time during the course of their illness. This update reviews the contemporary evidence to define the optimal proportion of new cancers that would benefit from radiotherapy as part of their treatment and estimates the changes to the optimal radiotherapy utilisation rate from 2003 to 2012. MATERIALS AND METHODS: National and international guidelines were reviewed for external beam radiotherapy indications in the management of cancers. Epidemiological data on the proportion of new cases of cancer with each indication for radiotherapy were identified. Indications and epidemiological data were merged to develop an optimal radiotherapy utilisation tree. Univariate and Monte Carlo simulations were used in sensitivity analysis. RESULTS: The overall optimal radiotherapy utilisation rate (external beam radiotherapy) for all registered cancers in Australia changed from 52.3% in 2003 to 48.3% in 2012. Overall 8.9% of all cancer patients in Australia have at least one indication for concurrent chemo-radiotherapy during the course of their illness. CONCLUSIONS: The reduction in the radiotherapy utilisation rate was due to changes in epidemiological data, changes to radiotherapy indications and refinements of the model structure.

Do variations in hospital mortality patterns after weekend admission reflect reduced quality of care or different patient cohorts? A population-based study.

BACKGROUND: Proposed causes for increased mortality following weekend admission (the 'weekend effect') include poorer quality of care and sicker patients. The aim of this study was to analyse the 7 days post-admission time patterns of excess mortality following weekend admission to identify whether distinct patterns exist for patients depending upon the relative contribution of poorer quality of care (care effect) or a case selection bias for patients presenting on weekends (patient effect). METHODS: Emergency department admissions to all 501 hospitals in New South Wales, Australia, between 2000 and 2007 were linked to the Death Registry and analysed. There were a total of 3 381 962 admissions for 539 122 patients and 64 789 deaths at 1 week after admission. We computed excess mortality risk curves for weekend over weekday admissions, adjusting for age, sex, comorbidity (Charlson index) and diagnostic group. RESULTS: Weekends accounted for 27% of all admissions (917 257/3 381 962) and 28% of deaths (18 282/64 789). Sixteen of 430 diagnosis groups had a significantly increased risk of death following weekend admission. They accounted for 40% of all deaths, and demonstrated different temporal excess mortality risk patterns: early care effect (cardiac arrest); care effect washout (eg, pulmonary embolism); patient effect (eg, cancer admissions) and mixed (eg, stroke). CONCLUSIONS: The excess mortality patterns of the weekend effect vary widely for different diagnostic groups. Recognising these different patterns should help identify at-risk diagnoses where quality of care can be improved in order to minimise the excess mortality associated with weekend admission.

Estimation of an optimal chemotherapy utilisation rate for lung cancer: an evidence-based benchmark for cancer care.

BACKGROUND: Optimal chemotherapy utilisation rates can serve as benchmarks to assess the quality of cancer service delivery. This study aims to determine the optimal proportion of patients with lung cancer that should receive chemotherapy at least once during the course of their illness, based on the best available evidence. METHODS: An optimal chemotherapy utilisation tree was constructed using indications for chemotherapy identified from evidence-based treatment guidelines. Data on the proportion of patient and tumour-related attributes for which chemotherapy was indicated were obtained and merged with the treatment indications to calculate an optimal chemotherapy utilisation rate. This optimal rate was compared with reported actual rates of chemotherapy utilisation. RESULTS: Chemotherapy is recommended at least once in 73% of all patients with lung cancer (93% of small cell lung cancer (SCLC) patients and 69% of non-small cell lung cancer (NSCLC) patients). Comparison of these benchmark rates with international reported actual chemotherapy utilisation rates reveals under-utilisation of chemotherapy in all newly diagnosed lung cancer patients, regardless of histological type and stage, with the exception of stage I NSCLC. CONCLUSION: The optimal chemotherapy utilisation rate can serve as a feasible, evidence-based measure of the quality of cancer care. Chemotherapy may be under-utilised in the initial management of lung cancer.

Socio-economic status and patterns of care in lung cancer.

OBJECTIVE: This retrospective study aims to explore the associations between socio-economic factors and lung cancer management and outcomes in the Australian setting. METHODS: The study population consisted of patients who were living in the Northern Sydney Area Health Service (NSAHS) or South Western Sydney Area Health Service (SWSAHS) at the time of their lung cancer diagnosis in 1996. Data on patient demographics, tumour characteristics, management details, recurrence and survival were collected and compared between the two areas. Socio-economic status indicators of the two Area Health Services were obtained from the Australian Bureau of Statistics. RESULTS: There were 270 and 256 new cases of lung cancer identified in NSAHS and SWSAHS respectively. Patients in NSAHS were slightly older and there were more women. Based on the 1996 Census data, the population of NSAHS is more affluent, better educated and more likely to be employed compared with SWSAHS. The stage distributions and performance status of the two areas were similar. The utilisation rates of different treatment modalities in the two areas were similar except for chemotherapy. The five-year overall survival rate was 10.5% in NSAHS and 7.2% in SWSAHS (p=0.08). Comparison based on the SEIFA Index of Relative Socio-economic Disadvantage did not reveal significant differences. CONCLUSION: Patients with lung cancer had similar patterns of care and survival despite differences in socio-economic profiles between the two Area Health Services. IMPLICATION: There seems to be equity of access to lung cancer services between the two Area Health Services.