Paying for Prevention: A Critical Opportunity for Public Health

2013 ◽  
Vol 41 (S1) ◽  
pp. 69-72 ◽  
Author(s):  
Jean C. O’Connor ◽  
Bruce J. Gutelius ◽  
Karen E. Girard ◽  
Danna Drum Hastings ◽  
Luci Longoria ◽  
...  

Despite spending more on health care than every other industrialized country, the U.S. ranks 37th in health outcomes. These differences cannot be explained away with differences in age and income, or even with quality of care. And, the rate of growth in health care spending in the U.S. continues to increase. The share of the Gross Domestic Product (GDP) attributable to health care grew from 9% in 1980 to more than 17% in 2011. Health care costs are projected to account for more than one-fifth of our economy by 2021. Despite spending more and more, the U.S. does not have better health outcomes than other countries. Worse, our increasing spending is largely attributable to preventable conditions. More than 85 cents of every dollar spent on health in the U.S. are spent on the treatment and management of chronic diseases, such as those caused by preventable conditions related to obesity and tobacco use.

2018 ◽  
Vol 77 (2) ◽  
pp. 131-142 ◽  
Author(s):  
Marina Soley-Bori ◽  
Theodore Stefos ◽  
James F. Burgess ◽  
Justin K. Benzer

Quality of care worries and rising costs have resulted in a widespread interest in enhancing the efficiency of health care delivery. One area of increasing interest is in promoting teamwork as a way of coordinating efforts to reduce costs and improve quality, and identifying the characteristics of the work environment that support teamwork. Relational climate is a measure of the work environment that captures shared employee perceptions of teamwork, conflict resolution, and diversity acceptance. Previous research has found a positive association between relational climate and quality of care, yet its relationship with costs remains unexplored. We examined the influence of primary care relational climate on health care costs incurred by diabetic patients at the U.S. Department of Veterans Affairs between 2008 and 2012. We found that better relational climate is significantly related to lower costs. Clinics with the strongest relational climate saved $334 in outpatient costs per patient compared with facilities with the weakest score in 2010. The total outpatient cost saving if all clinics achieved the top 5% relational climate score was $20 million. Relational climate may contribute to lower costs by enhancing diabetic treatment work processes, especially in outpatient settings.


2001 ◽  
Vol 1 ◽  
pp. 544-546
Author(s):  
Stephen R. Spindler

According to government figures, total health care spending in the U.S. in 1999 was $1.316 trillion. The government projects an increase in health care costs to $2.176 trillion by 2008. If we project this growth rate to 2020, health care costs will reach $4.009 trillion. Today, people often spend more health care dollars during the last year of their lives than in all previous years combined. Medical treatment in the last few years of life is usually very expensive and often futile. With the baby-boom generation now moving through middle age, the prescription for the U.S. health care system will be disastrous unless we learn how to keep people healthier longer. This dramatic increase in health care costs leaves us with only one acceptable alternative to rationed health care or financial ruin — to discover interventions that make people functionally younger, healthier, and less susceptible to debilitating, age-related diseases.


2012 ◽  
Vol 15 (2) ◽  
pp. 101-112 ◽  
Author(s):  
Julie Priest ◽  
Ami Buikema ◽  
Nicole M. Engel-Nitz ◽  
Christopher L. Cook ◽  
C. Ron Cantrell

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3298-3298
Author(s):  
Adrianne W Casebeer ◽  
Sari Hopson ◽  
Dana A Drzayich Jankus ◽  
Zhuliang Tao ◽  
Stephen Stemkowski ◽  
...  

Abstract Background: Hospital acquisitions of community clinics in the United States have led to a shift in oncology infusion therapy from physician office (PO) to hospital outpatient (HO) settings. Studies in commercially insured populations suggest that inherent differences between sites of care (SOC) can impact cancer treatment delivery and overall health care costs. This study utilizes a predominantly Medicare population to examine differences in treatment patterns, cost, and quality of care among patients with NHL/CLL receiving infusion chemotherapy and/or rituximab in a HO versus PO setting. Methods: Patients ≥ 18 years initiating infusion therapy in 2008-2012 with at least 2 claims with a diagnosis of NHL or CLL occurring 30 or more days apart were identified from Humana medical claims data. The index date was the date of the first NCCN recommended infusion therapy. SOC attribution (HO vs PO) was based on where patients received ≥ 90% of their infusions. Differences by SOC in duration of first line treatment, number of infusions, and quality of care indicators, such as the use of infusions or hospitalizations within 30 days of death, were evaluated using Χ2 and Wilcoxon Rank Sum tests. Median and interquartile range for duration of treatment and number of infusions by SOC were reported. Health care costs were determined by the sum of plan and patient costs for medical and pharmacy claims in the 6-months following the index date. Oncology costs, including supportive care, were computed from claims with cancer specific ICD-9 diagnostic codes. To control for the impact of case mix differences by SOC on costs, generalized linear models adjusting for age, sex, comorbidity, total health care cost in the pre-index period and geographic region were conducted. Results: A total of 1,859 patients with a diagnosis for NHL or CLL were identified and 68% (1,262) received infusion therapy in the PO setting. Medicare beneficiaries represented 85% (1,587) of the study sample. Mean comorbidity index was higher among HO [3.7 ± 2.4 (SD)] compared to PO patients [3.3 ± 2.2 (SD)], p=0.0001. The proportion of patients receiving certain treatment regimens differed by SOC. Rituximab monotherapy was received by 24.5% (146) of HO and 14.1% (178) of PO patients, p<0.0001. Rituximab with chemotherapy was received by 63.3% (378) of HO and 72.7% (917) of PO patients, p<0.0001. Treatment regimens consisting of chemotherapy only did not differ by SOC, 12.1% (72) of HO and 13% (164) of PO patients, p<0.57. Treatment duration did not differ by SOC among those receiving any Rituximab therapy (p>0.05). Among those receiving chemotherapy only, treatment duration was shorter in the HO setting with 78.5 days (22.5-111) versus the PO setting with 112 days (59-162.5) p=0.0002. In the HO setting, there were fewer infusions for patients receiving chemotherapy and Rituximab, HO 6 (5-10), PO 7 (5-12), p=0.012 and chemotherapy only HO 6 (3-10), PO 7.5 (5-12), p=0.006. In multivariate analyses, total healthcare costs were 22% higher among patients in the HO ($60,536) compared to the PO ($49,800) setting, p< 0.0001. Total oncology-related health care costs were also 24% higher in HO compared to PO, $58,033 versus $46,652 respectively, p<0.0001. There were no statistically significant differences in the quality of care indicators by SOC, including the use of infusions or hospitalizations within 30 days of death among Medicare patients. Among 427 Medicare patients who died, use of infusions within 30 days of death was 25.7% (36) for HO and 23.7% (68) for PO,p=0.6479. Hospitalizations within 30 days of death occurred among 67.1% (94) of HO and 66.9% (192) of PO patients, p=0.9599. Conclusion: This study, among the first to utilize a mostly Medicare NHL/CLL population, found differences by SOC in treatment patterns and cost, but not in the area of quality, defined as infusion and hospitalization within 30 days of death. Patients receiving care in the HO setting had a shorter duration of therapy and fewer infusions, but had higher total healthcare costs than those in the PO setting. As care shifts from the PO to HO setting, future studies should assess the impact of SOC on the delivery of care and health care costs associated with current therapeutic options for NHL/CLL. Disclosures Casebeer: Comprehensive Health Insights: Employment, Equity Ownership, Research Funding. Hopson:Genentech/Roche: Consultancy, Research Funding; Comprehensive Health Insights, A Humana Company: Employment. Stemkowski:Comprehensive Health Insights: Employment, Equity Ownership, Research Funding. Howe:Comprehensive Health Insights: Employment, Research Funding. Patton:Amgen, BMS, J & J, Astellas, Lilly: Honoraria, Speakers Bureau. Small:Genentech: Employment. Masaquel:Genentech: Employment, Research Funding.


2020 ◽  
Vol 11 ◽  
pp. 215013271989976
Author(s):  
Roanna Burgess ◽  
James Hall ◽  
Annette Bishop ◽  
Martyn Lewis ◽  
Jonathan Hill

Background: Identifying variation in musculoskeletal service costs requires the use of specific standardized metrics. There has been a large focus on costing, efficiency, and standardized metrics within the acute musculoskeletal setting, but far less attention in primary care and community settings. Objectives: To ( a) assess the quality of costing methods used within musculoskeletal economic analyses based primarily in primary and community settings and ( b) identify which cost variables are the key drivers of musculoskeletal health care costs within these settings. Methods: Medline, AMED, EMBASE, CINAHL, HMIC, BNI, and HBE electronic databases were searched for eligible studies. Two reviewers independently extracted data and assessed quality of costing methods using an established checklist. Results: Twenty-two studies met the review inclusion criteria. The majority of studies demonstrated moderate- to high-quality costing methods. Costing issues included studies failing to fully justify the economic perspective, and not distinguishing between short- and long-run costs. Highest unit costs were hospital admissions, outpatient visits, and imaging. Highest mean utilization were the following: general practitioner (GP) visits, outpatient visits, and physiotherapy visits. Highest mean costs per patient were GP visits, outpatient visits, and physiotherapy visits. Conclusion: This review identified a number of key resource use variables that are driving musculoskeletal health care costs in the community/primary care setting. High utilization of these resources (rather than high unit cost) appears to be the predominant factor increasing mean health care costs. There is, however, need for greater detail with capturing these key cost drivers, to further improve the accuracy of costing information.


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