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Wang C, Onega T, Wang F. Multiscale analysis of cancer service areas in the United States. Spat Spatiotemporal Epidemiol 2022; 43:100545. [PMID: 36460451 DOI: 10.1016/j.sste.2022.100545] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 10/20/2022] [Accepted: 10/26/2022] [Indexed: 11/30/2022]
Abstract
The purpose of delineating Cancer Service Areas (CSAs) is to define a reliable unit of analysis, more meaningful than geopolitical units such as states and counties, for examining geographic variations of the cancer care markets using geographic information systems (GIS). This study aims to provide a multiscale analysis of the U.S. cancer care markets based on the 2014-2015 Medicare claims of cancer-directed surgery, chemotherapy, and radiation. The CSAs are delineated by a scale-flexible network community detection algorithm automated in GIS so that the patient flows are maximized within CSAs and minimized between them. The multiscale CSAs include those comparable in size to those 4 census regions, 9 divisions, 50 states, and also 39 global optimal CSAs that generates the highest modularity value. The CSAs are more effective in capturing the U.S. cancer care markets because of its higher localization index, lower cross-border utilizations, and shorter travel time. The first two comparisons reveal that only a few regions or divisions are representative of the underlying cancer care markets. The last two comparisons find that among the 39 CSAs, 54% CSAs comprise multiple states anchored by cities near inner state borders, 28% are single-state CSAs, and 18% are sub-state CSAs. Their (in)consistencies across state borders or within each state shed new light on where the intervention of cancer care delivery or the adjustment of cancer care costs are needed to meet the challenges in the U.S. cancer care system. The findings could guide stakeholders to target public health policies for more effective coordination of cancer care in improving outcomes and reducing unnecessary costs.
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Affiliation(s)
- Changzhen Wang
- Department of Geography, University of Alabama, Tuscaloosa, AL 35401, United States
| | - Tracy Onega
- Department of Population Health Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, United States
| | - Fahui Wang
- The Graduate School and Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, United States.
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Takvorian SU, Yasaitis L, Liu M, Lee DJ, Werner RM, Bekelman JE. Differences in Cancer Care Expenditures and Utilization for Surgery by Hospital Type Among Patients With Private Insurance. JAMA Netw Open 2021; 4:e2119764. [PMID: 34342648 PMCID: PMC8335573 DOI: 10.1001/jamanetworkopen.2021.19764] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
IMPORTANCE With rising expenditures on cancer care outpacing other sectors of the US health system, national attention has focused on insurer spending, particularly for patients with private insurance, for whom price transparency has historically been lacking. The type of hospital at which cancer care is delivered may be an important factor associated with insurer spending for patients with private insurance. OBJECTIVE To examine differences in spending and utilization for patients with private insurance undergoing common cancer surgery at National Cancer Institute (NCI) centers vs community hospitals. DESIGN, SETTING, AND PARTICIPANTS This retrospective cross-sectional study included adult patients with an incident diagnosis of breast, colon, or lung cancer who underwent cancer-directed surgery from 2011 to 2014. Mean risk-adjusted spending and utilization outcomes were examined for each hospital type using multilevel generalized linear mixed-effects models, adjusting for patient, hospital, and region characteristics. Data were collected from the Health Care Cost Institute's national multipayer commercial claims data set, which encompasses claims paid by 3 of the 5 largest commercial health insurers in the United States (ie, Aetna, Humana, and UnitedHealthcare). Data analyses were conducted from February 2018 to February 2019. EXPOSURES Hospital type at which cancer surgery was performed: NCI, non-NCI academic, or community. MAIN OUTCOMES AND MEASURES Spending outcomes were surgery-specific insurer prices paid and 90-day postdischarge payments. Utilization outcomes were length of stay (LOS), emergency department (ED) use, and hospital readmission within 90 days of discharge. RESULTS The study included 66 878 patients (51 569 [77.1%] women; 31 585 [47.2%] aged ≥65 years) with incident breast (35 788 [53.5%]), colon (21 378 [32.0%]), or lung (9712 [14.5%]) cancer undergoing cancer surgery at 2995 hospitals (5522 [8.3%] at NCI centers; 10 917 [16.3%] at non-NCI academic hospitals; 50 439 [75.4%] at community hospitals). Treatment at NCI centers was associated with higher surgery-specific insurer prices paid compared with community hospitals ($18 526 [95% CI, $16 650-$20 403] vs $14 772 [95% CI, $14 339-$15 204]; difference, $3755 [95% CI, $1661-$5849]; P < .001) and 90-day postdischarge payments ($47 035 [95% CI, $43 289-$50 781] vs $41 291 [95% CI, $40 350-$42 231]; difference, $5744 [95% CI, $1659-9829]; P = .006). There were no significant differences in LOS, ED use, or hospital readmission within 90 days of discharge. CONCLUSIONS AND RELEVANCE In this cross-sectional study, surgery at NCI centers vs community hospitals was associated with higher insurer spending for a surgical episode without differences in care utilization among patients with private insurance undergoing cancer surgery. A better understanding of the factors associated with prices and spending at NCI cancer centers is needed.
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Affiliation(s)
- Samuel U. Takvorian
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Laura Yasaitis
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Manqing Liu
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Daniel J. Lee
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Rachel M. Werner
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Justin E. Bekelman
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Departments of Radiation Oncology and Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
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End-of-Life Spending and Healthcare Utilization Among Older Adults with Chronic Obstructive Pulmonary Disease. Am J Med 2020; 133:817-824.e1. [PMID: 31883772 PMCID: PMC7319886 DOI: 10.1016/j.amjmed.2019.11.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 11/19/2019] [Accepted: 11/19/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND End-of-life spending and healthcare utilization among older adults with COPD have not been previously described. METHODS We examined data on Medicare beneficiaries aged 65 years or older with chronic obstructive pulmonary disease (COPD) who died during the period of 2013-2014. End-of-life measures were retrospectively reviewed for 2 years prior to death. Hospital referral regions (HRRs) were categorized into quintiles of age-sex-race-adjusted overall spending during the last 2 years of life. Geographic quintile variation in spending and healthcare utilization was examined across the continuum. RESULTS We investigated data on 146,240 decedents with COPD from 306 HRRs. Age-sex-race-adjusted overall spending per decedent during the last 2 years of life varied significantly nationwide ($61,271±$11,639 per decedent; range: $48,288±$3,665 to $79,453±$9,242). Inpatient care accounted for 40.2% of spending ($24,626±$6,192 per decedent). Overall, 82%±4% of decedents were admitted to the hospital for 13.7±3.1 days, and 55%±11% were admitted to an intensive care unit for 5.4±2.5 days. Compared with HRRs in the lowest spending quintile, HRRs in the highest spending quintile had a 1.5-fold longer hospital length of stay. Skilled nursing facilities accounted for 11.6% of spending ($7101±$2403 per decedent), and these facilities were utilized by 38%±7% of decedents for 18.7±4.9 days. Hospice accounted for 10.3% of spending ($6,307±$2,201 per decedent) and was utilized by 47%±9% of decedents for 39.7±14.8 days. Significant geographic variation in hospice utilization existed nationwide. CONCLUSIONS End-of-life spending and healthcare utilization among older adults with COPD varied substantially nationwide. Decedents with COPD frequently utilized acute care near the end of life. Hospice utilization was higher than expected, with significant geographic disparities.
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Vail D, Pershing S, Reeves MG, Afshar AR. The Relative Impact of Patient, Physician, and Geographic Factors on Variation in Primary Rhegmatogenous Retinal Detachment Management. Ophthalmology 2020; 127:97-106. [DOI: 10.1016/j.ophtha.2019.04.019] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 04/06/2019] [Accepted: 04/09/2019] [Indexed: 11/27/2022] Open
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Cutler D, Skinner JS, Stern AD, Wennberg D. Physician Beliefs and Patient Preferences: A New Look at Regional Variation in Health Care Spendingf. AMERICAN ECONOMIC JOURNAL. ECONOMIC POLICY 2019; 11:192-221. [PMID: 32843911 PMCID: PMC7444804 DOI: 10.1257/pol.20150421] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
There is considerable controversy about the causes of regional variations in health care expenditures. Using vignettes from patient and physician surveys linked to fee-for-service Medicare expenditures, this study asks whether patient demand-side factors or physician supply-side factors explain these variations. The results indicate that patient demand is relatively unimportant in explaining variations. Physician organizational factors matter, but the most important factor is physician beliefs about treatment. In Medicare, we estimate that 35 percent of spending for end-of-life care and 12 percent of spending for heart attack patients (and for all enrollees) is associated with physician beliefs unsupported by clinical evidence. (JEL D83, H75, I11, I18).
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Affiliation(s)
- David Cutler
- Cutler: Department of Economics, Harvard University, 230 Littauer Center, 1805 Cambridge Street, Cambridge, MA 02138, and National Bureau of Economic Research; Skinner: Department of Economics, Dartmouth College, Hinman Box 6106, Hanover, NH 03755, Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, and National Bureau of Economic Research; Stern: Technology and Operations Management Unit, Harvard Business School, Morgan Hall 433, Boston, MA 02136, and Ariadne Labs at Brigham and Women’s Hospital and the Harvard T. H. Chan School of Public Health; Wennberg: Quartet Health, 114 West 41st Street, New York, NY 10036
| | - Jonathan S. Skinner
- Cutler: Department of Economics, Harvard University, 230 Littauer Center, 1805 Cambridge Street, Cambridge, MA 02138, and National Bureau of Economic Research; Skinner: Department of Economics, Dartmouth College, Hinman Box 6106, Hanover, NH 03755, Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, and National Bureau of Economic Research; Stern: Technology and Operations Management Unit, Harvard Business School, Morgan Hall 433, Boston, MA 02136, and Ariadne Labs at Brigham and Women’s Hospital and the Harvard T. H. Chan School of Public Health; Wennberg: Quartet Health, 114 West 41st Street, New York, NY 10036
| | - Ariel Dora Stern
- Cutler: Department of Economics, Harvard University, 230 Littauer Center, 1805 Cambridge Street, Cambridge, MA 02138, and National Bureau of Economic Research; Skinner: Department of Economics, Dartmouth College, Hinman Box 6106, Hanover, NH 03755, Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, and National Bureau of Economic Research; Stern: Technology and Operations Management Unit, Harvard Business School, Morgan Hall 433, Boston, MA 02136, and Ariadne Labs at Brigham and Women’s Hospital and the Harvard T. H. Chan School of Public Health; Wennberg: Quartet Health, 114 West 41st Street, New York, NY 10036
| | - David Wennberg
- Cutler: Department of Economics, Harvard University, 230 Littauer Center, 1805 Cambridge Street, Cambridge, MA 02138, and National Bureau of Economic Research; Skinner: Department of Economics, Dartmouth College, Hinman Box 6106, Hanover, NH 03755, Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, and National Bureau of Economic Research; Stern: Technology and Operations Management Unit, Harvard Business School, Morgan Hall 433, Boston, MA 02136, and Ariadne Labs at Brigham and Women’s Hospital and the Harvard T. H. Chan School of Public Health; Wennberg: Quartet Health, 114 West 41st Street, New York, NY 10036
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El Majzoub I, Qdaisat A, Chaftari PS, Yeung SCJ, Sawaya RD, Jizzini M, Carreras MTC, Abunafeesa H, Elsayem AF. Association of emergency department admission and early inpatient palliative care consultation with hospital mortality in a comprehensive cancer center. Support Care Cancer 2018; 27:2649-2655. [DOI: 10.1007/s00520-018-4554-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 11/13/2018] [Indexed: 01/10/2023]
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Lan L, Cai Y, Zhang T, Wu R, Xue M, Meng Q. Influencing factors of inpatient expenditure pattern for cancer in China, 2015. Chin J Cancer Res 2017; 29:11-17. [PMID: 28373749 PMCID: PMC5348471 DOI: 10.21147/j.issn.1000-9604.2017.01.02] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Objective We analyzed the proportion of cancer-caused hospitalization expenses in total hospitalization expenses from national authoritative data and explored influencing factors of the proportion so as to provide effective data information for more rational utilization of health resources. Methods Two-level lineal regression model was used to explore influencing factors of ratios of the cancer inpatient expenditure over the total inpatient expenditure of hospitals in China in 2015. A total of 40.76 million inpatient medical records were used to generate the outcome variables, while the explanatory variables were from hospital information database and China Health and Family Planning Statistical Yearbook and literatures. Results Inpatient expenditure pattern for cancer (IEPC) varied largely across provinces, ranging from 3.03% to 19.61%. The major sources of variability were from the differences of hospital level and number of beds. There was homogeneity within a province, while heterogeneity between the provinces. Rising one level of the hospital led to the increase of 0.475 natural logarithm units of IEPC averagely. The number of beds increasing 1,000 each made the natural logarithm of IEPC increase one unit averagely. Conclusions Our study showed that a considerable proportion of IEPC variation could be explained by the differences of hospital level and number of beds. It implied that it is possible to estimate disease-specific ratio of inpatient expense taking into account key influencing factors in China. Furthermore, this study is an input to economic and financial analyses and provides evidence for future study on the national economic burden of cancer.
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Affiliation(s)
- Lan Lan
- West China School of Public Health, Sichuan University, Chengdu 610041, China
| | - Yue Cai
- Center for Health Statistics and Information, National Health and Family Planning Commission, Beijing 100032, China
| | - Tao Zhang
- West China School of Public Health, Sichuan University, Chengdu 610041, China
| | - Ruixian Wu
- Center for Health Statistics and Information, National Health and Family Planning Commission, Beijing 100032, China
| | - Ming Xue
- Center for Health Statistics and Information, National Health and Family Planning Commission, Beijing 100032, China
| | - Qun Meng
- West China School of Public Health, Sichuan University, Chengdu 610041, China; Center for Health Statistics and Information, National Health and Family Planning Commission, Beijing 100032, China
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