Description of Baseline Characteristics of Patients Provided Cancer Care within a Novel Commercial Health Plan Cancer Care Quality Program in the First Year

42 Background: As value-based payment models for cancer care expand, the need for measures which reliably assess the quality of care provided increases. This is especially true for models like the Oncology Care Model (OCM) that rely on quality rankings to determine potential shared savings. Under models like these, unreliable measures may result in arbitrary application of value-based payments. The goal of this project is to evaluate the extent to which measures used within the OCM are reliable indicators of provider performance. Methods: Data for this project came from North Carolina Medicare claims from 2015-2017. Episodes were attributed to physician practices at the tax identification number (TIN) level, lasted 6 months, and were divided into two performance years beginning 1/1/2016 and 7/1/2016. TINs with fewer than 20 attributed patients were excluded. Three claims-based OCM measures were used in this evaluation: 1) proportion of episodes with all-cause hospital admissions; 2) proportion of episodes with all-cause emergency department (ED) visits or observation stays; and 3) proportion of patients that died who were admitted to hospice for 3 days or more. Risk adjustment followed the method described by measure specifications from the OCM. Reliability was calculated as the ratio of between practice variation (e.g. signal) to the sum of between practice variation and within practice variation (e.g. noise). Variance estimates were derived from hierarchical logistic regression models used for risk adjustment. Results: For the hospitalization and ED visit measures, episode counts for years 1 and 2 were 30,746 and 28,430 and TIN counts were 86 and 84, respectively. Hospice use measures had fewer episodes (2,677 and 2,428) and TINs (36 and 33). Across all measures, median reliability scores failed to achieve the recommended 0.7 threshold and only hospice had a median reliability score above 0.5 (Table). Conclusions: These findings suggest claims-based measures included in the OCM may produce imprecise estimates of provider performance and are vulnerable to random variation. Consideration should be given to developing alternative measures which may be more reliable estimates of provider performance and to increasing minimum denominator requirements for existing measures.[Table: see text]

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A disease-based evaluation of lung cancer care quality in a community healthcare system.

Journal of Clinical Oncology ◽

10.1200/jco.2020.39.28_suppl.251 ◽

2021 ◽

Vol 39 (28_suppl) ◽

pp. 251-251

Author(s):

Meghan Brooke Taylor ◽

Meredith Ray ◽

Nicholas Faris ◽

Matthew Smeltzer ◽

Carrie Fehnel ◽

...

Keyword(s):

Lung Cancer ◽

Quality Improvement ◽

Surgical Treatment ◽

Healthcare System ◽

Cancer Care ◽

Care Quality ◽

Nodal Points ◽

Diagnostic Biopsy ◽

Pre Treatment ◽

Non Surgical Treatment

251 Background: Lung cancer care is complex, but, for quality improvement, can be simplified into five ‘nodal points’: lesion detection, diagnostic biopsy, radiologic staging, invasive staging, and treatment. We previously demonstrated great heterogeneity in passage through these nodal points in patients who received surgical resection for lung cancer in our healthcare system. However, examining only surgical patients may underestimate the enormity of the opportunity for quality improvement. With the aim of identifying quality gaps in pre-treatment evaluation for lung cancer, we evaluated the flow of care through these nodal points within a community-based healthcare system. Methods: We classified lung cancer care procedures received by all suspected lung cancer patients treated within the Multidisciplinary Thoracic Oncology Program at Baptist Cancer Center, Memphis TN between 2014 and 2019, into five nodal points. We compared the frequency of, and time intervals between, nodal points among patients receiving surgical, nonsurgical (chemotherapy/radiation), or no definitive treatment, using Chi-square or Kruskal Wallis tests, where appropriate. Results: Of 1304 eligible patients: 11% had no pre-treatment diagnostic procedure, 20% no PET/CT, and 39% no invasive staging. 39% of patients underwent surgical resection, 51% received non-surgical treatment, and 10% received no treatment. Patients who had surgery were less likely than those who had non-surgical treatment to get a diagnostic test, radiologic staging, and invasive staging (Table). Patients who had non-surgical treatment were more likely to pass through all five nodal points (50% v 68%, p<0.0001). The median (IQR) duration from initial lesion identification to treatment (n=1126) was 77 days (45-190); 27 days (10-90) from lesion identification to diagnostic biopsy (n=1115); and 38 days (26-63) from diagnostic biopsy to treatment (n=1041). Patients who had surgery received less timely care than those who had non-surgical or no treatment: median 122 v 66 v 68 days from lesion identification to treatment; 40 v 21 v 29 days from lesion identification to diagnostic biopsy; 46 v 38 v 31 days from diagnostic biopsy to treatment (p<0.0001 all comparisons). Conclusions: Quality improvement initiatives within our healthcare system, such as the establishment of a coordinated multidisciplinary program, enhanced care quality over previous benchmarks. Despite improvements, lung cancer patients who had surgery received less frequent and less timely pre-treatment evaluation than those without surgery. Implementing a standardized cancer care pathway from diagnosis to surgery could help to reduce variations in optimal care delivery.[Table: see text]

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Next-of-kin involvement in improving hospital cancer care quality and safety – a qualitative cross-case study as basis for theory development

BMC Health Services Research ◽

10.1186/s12913-018-3141-7 ◽

2018 ◽

Vol 18 (1) ◽

Cited By ~ 8

Author(s):

Inger Johanne Bergerød ◽

Bjørnar Gilje ◽

Geir S. Braut ◽

Siri Wiig

Keyword(s):

Cancer Care ◽

Theory Development ◽

Care Quality ◽

Quality And Safety ◽

Next Of Kin

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Value-Based HIV Care: A Method to Improve Quality of HIV Care.

10.21203/rs.3.rs-117180/v1 ◽

2020 ◽

Author(s):

Guido van den berk ◽

Daoud Ait Moha ◽

Janneke Stalenhoef ◽

Marie-Jose Kleene ◽

Narda van der Meche ◽

...

Keyword(s):

Quality Of Life ◽

Care Delivery ◽

Population Level ◽

Care Quality ◽

Hiv Care ◽

First Year ◽

Outcome Indicators ◽

Number Of Patients ◽

Care Path

Abstract Background : To support our goal of providing optimal HIV care to our patients, we started applying the value-based health care principle to the HIV care that we offer in our HIV center, measuring relevant health outcomes and costs to allow continuous implementation of improvements (Value-Based HIV Care; VBHiC). Methods : In line with the principles of Michael Porter, our approach consisted of the following steps: 1) Organizing into integrated practice units / describing the HIV care path; 2) Defining an HIV outcome indicator set; 3) Building an enabling information technology platform; 4) Integrating care delivery across separate facilities; 5) Moving to bundled payments for care cycles and 6) Expanding excellent services and interventions for improvement across geographic boundaries. Results : The following set of 9 outcome indicators was developed: undetectable HIV load within the first year of care; quality of life within the first year of care; mortality within the first year of care; retention in care; therapy effectiveness; therapy tolerance; cardiovascular risk; quality of life for every subsequent year and overall annual mortality. These indicators, which were evaluated retrospectively, are shown in figures 1-5. Collection of the underlying data started in January 2016. The HIV care path was also integrated into the electronic file system. Creation of the ability to monitor outcome indicators at patient level, population level and process level allowed us to implement a quality cycle (plan-do-study-act). Conclusion : Our Value-Based HIV Care approach facilitated structured evaluation of parameters that are of value to the patient. It also boosted the quality of the HIV care that we provide and allowed us to increase the number of patients to whom we can offer high quality HIV care.

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