The aim of this study was to produce a patient-centred information strategy based on the results of a local survey of cancer patients about the information they receive and their information needs. An anonymous patient survey was distributed at the Dorset Cancer Centre, Poole Hospital, the regional cancer centre for Dorset, in the South-west of England. All patients attending the Cancer Centre during 1 week in September 1999 were asked to complete a questionnaire on patient experience of the Cancer Centre, information sources, receipt and quality of Centre information, and perception of information requirements. Two hundred and eighty-two were returned. Most respondents had accessed information from a number of sources. Written Cancer Centre information had been given to most patients, and was generally perceived to be useful, understandable and timely. However, most patients had received information 'all at once', from a single professional group, and a notable proportion did not recall discussing it with staff. Furthermore, most patients indicated that information should also be provided to families and professionals. Seven items of information were selected as valuable by the majority of patients, with many others listed. There was a great deal of satisfaction with the current content of the patient information provided. However, the distribution system was shown to be in need of improvement. A new information strategy has been developed in the light of these findings.
PURPOSE: As expenditures for cancer care continue to grow substantially, value-based payment models are being tested to control costs. The Oncology Care Model (OCM) is the largest value-based payment program in oncology. The primary objective of this analysis was to determine the impact of high-cost novel agents on total cost of care for multiple myeloma (MM) episodes of care in the OCM. METHODS: This was a retrospective analysis using Medicare claims data for 258 MM OCM episodes initiated between July 1, 2016, and July 1, 2017. Patients were organized into 3 cohorts: those who received pomalidomide (cohort A), those who received lenalidomide (cohort B), and those who did not receive either drug but had received another chemotherapy agent (cohort C). We compared the actual episode expenditures and the Centers for Medicare and Medicaid target price to create an observed versus expected (O/E) ratio. RESULTS: The average O/E for cohort A (n = 73) was 1.73, compared with 1.31 for cohort B (n = 84) and 1.01 for cohort C (n = 101). The difference the in O/E ratio among the groups was statistically significant ( P < .001). The average episode target price for cohorts A, B, and C was $66,149, $63,483, and $63,937, respectively. Despite the high cost of pomalidomide and lenalidomide, there was no significant difference in the average episode target prices of the cohorts. CONCLUSION: The O/E ratio and target prices of the cohorts demonstrate a lack of adequate adjustment to the OCM target price for episodes in which pomalidomide and lenalidomide were used to treat patients with MM.
Background: In July of 2016, CMMI started a five year bundled payment program called OCM. Beneficiaries are attributed to practices providing their cancer care for a 6 month episode triggered by the administration or distribution of specified cancer drugs. The model provides risk adjustments to the target price based on risk factors such as age, chemotherapy and the receipt of certain treatments (radiation or bone marrow transplant). Target prices are adjusted by geographic region, novel therapy use, and a trend factor. Multiple Myeloma was identified in our practice as a cancer type with high variance on expenditures after the first Performance Period within the model (July 2016-December 2016). Chemotherapy represented 52% of total episode expenditures with oral chemotherapy and hormone therapy representing 24%. The average cost of lenalidomide for one year is $115,000. The model adjusts for novel therapies, including new drugs approved by the FDA after December 31, 2014 with status lasting two years. However, literature demonstrates that this does not fully adjust for the high costs of novel therapies (Muldoon et at., Health Affairs, 2018). Unlike solid tumors, Multiple Myeloma staging may not improve risk adjustment and target price. Methods: We analyzed the total cost of care of beneficiaries who triggered an OCM episode for Performance Period 1 (PP1). Beneficiaries were identified by diagnosis of Multiple Myeloma, and then segregated into cohorts of those who received lenalidomide and/or pomalidomide and those who did not. Observed vs. Expected (O/E) target price for each episode was determined for both cohorts comparing the actual episode expenditures and the target price per episode calculated by the Oncology Care Model. A two sample t-test was conducted followed by a linear regression to determine relation between drug days prescribed and O/E. Results: There were 125 attributed beneficiaries with a Multiple Myeloma diagnosis who triggered an episode during PP1. The average O/E of the cohort which received the chemotherapy, Cohort A, was 1.624 compared to 0.986 for those that did not, Cohort B. The difference in average O/E in the two cohorts was 39% higher in Cohort A, p<0.001. There were no significant differences in the amount of inpatient claims, ED visits, or Bone Marrow Transplants between the two cohorts (Table 1). Figure 1 demonstrates the positive linear relationship (p<0.01, r=.40) between number of days supplied and O/E. Discussion: This is the first report on the impact of lenalidomide and pomalidomide on the total cost of care in an OCM practice. The results demonstrate the lack of adequate adjustment to the CMS target price for episodes in which one or both of these drugs were prescribed. Lenalidomide and pomalidomide are first and second line drugs used both for induction and maintenance. Both drugs are frequently used for prolonged periods of time in patients and trigger more than one episode in OCM. Therefore, the use of these agents greatly affects the total cost of care against a target price that is not adequately adjusted. Academic Medical Centers that care for larger populations of multiple myeloma patients may be disproportionately affected and this will impede their success under the OCM methodology. Additional analysis similar to this will inform CMMI as to further refinements to the OCM adjusters. Disclosures No relevant conflicts of interest to declare.
205 Background: Spiritual care is identified as a core component of quality oncologic care. Unmet spiritual needs can lead to worse quality of life, lower satisfaction with care, and greater psychological distress. Despite increasing evidence that cancer outpatients also have unmet spiritual needs, professional spiritual care is often limited in the ambulatory setting. Many cancer centers provide access to professional chaplains only while patients are hospitalized. Where chaplain services are available to outpatients, access is often limited. At Mount Sinai, we embedded a full-time professional chaplain in our ambulatory cancer center. This presentation will describe our methods, results, and conclusions from a year of data on outpatient spiritual care referrals. Methods: We identified three sources of referrals to spiritual care: direct referrals from patients’ primary oncology teams, direct referrals from Supportive Oncology/Palliative Care, and automatic referrals through a question about meaning and purpose on our distress screen. We also included the opportunity for patients to self-refer to spiritual care through our distress screen. We collected data on the number of patients identified through these referral sources, time to initial contact, and the validity of the referral as assessed by our chaplain. Results: These three sources resulted in 454 referrals to spiritual care. We screened 1,410 patients through our distress screen and 16% (226) triggered a referral to spiritual care. Distress screen referrals comprised nearly 50% of all spiritual care referrals. In addition, 32% (144) of our referrals came from the patients’ clinical teams and 10% (46) from the Supportive Oncology team. Our chaplain assessed that 31% (141) had a spiritual need that required regular follow-up and 12% (56) required monitoring. Conclusions: Using multiple referral methods we were able to identify a significant number of ambulatory cancer patients with an identified spiritual need. Future projects will look at specific metrics for patient experience, improving chaplain ability to connect with patients, validating our screening question for spiritual distress, and determining an appropriate patient load for an outpatient chaplain.
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