Incremental direct healthcare expenditures of valvular heart disease in the USA
Publication: Journal of Comparative Effectiveness Research
Abstract
Aim: To quantify the healthcare expenditures for valvular heart disease (VHD) in the USA. Patients & methods: Direct annual incremental healthcare expenditures were estimated using multiple logistic and linear regression models. Results were stratified by age cohorts (18–64 years, ≥65 and ≥75 years) and disease status: symptomatic aortic valve disease (AVD), asymptomatic AVD, symptomatic mitral valve disease (MVD) and asymptomatic MVD. Results: A total of 1463 VHD patients were identified. The overall aggregated incremental direct expenditures were $56.62 billion ($26.48 billion for patients ≥75 years). Individuals ≥75 years with symptomatic AVD had the largest incremental effect on annual, per-patient healthcare expenditure of $30,949. The annualized incremental costs of VHD were greatest for individuals ≥75 years with AVD. Conclusion: Identification of VHD at an earlier stage may reduce the economic burden.
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References
Papers of special note have been highlighted as: • of interest; •• of considerable interest
1.
Lee JL, Naguwa SM, Cheema GS, Gershwin ME. Acute rheumatic fever and its consequences: a persistent threat to developing nations in the 21st century. Autoimmun. Rev. 9(2), 117–123 (2009).
2.
Benjamin EJ, Virani SS, Callaway CW et al. Heart disease and stroke statistics – 2018 update: a report from the American Heart Association. Circulation 137(12), e67–e492 (2018).
3.
Marijon E, Celermajer DS, Tafflet M et al. Rheumatic heart disease screening by echocardiography: the inadequacy of World Health Organization criteria for optimizing the diagnosis of subclinical disease. Circulation 120(8), 663–668 (2009).
4.
Helms AS, Bach DS. Heart valve disease. Prim Care 40(1), 91–108 (2013).
5.
Ray S. Changing epidemiology and natural history of valvular heart disease. Clin. Med. 10(2), 168–171 (2010).
6.
Iung B, Baron G, Butchart EG et al. A prospective survey of patients with valvular heart disease in Europe: The Euro Heart Survey on Valvular Heart Disease. Eur. Heart J. 24(13), 1231–1243 (2003).
7.
Bonow RO, Carabello BA, Chatterjee K et al. 2008 focused update incorporated into the ACC/AHA 2006 guidelines for the management of patients with valvular heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to revise the 1998 guidelines for the management of patients with valvular heart disease). Endorsed by the Society of Cardiovascular Anesthesiologists, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J. Am. Coll. Cardiol. 52(13), e1–142 (2008).
8.
Nishimura RA, Otto CM, Bonow RO et al. 2017 AHA/ACC focused update of the 2014 AHA/ACC Guideline for the Management of Patients With Valvular Heart Disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 135(25), e1159–e1195 (2017).
•• The American College of Cardiology/American Heart Association guidelines for valvular heart disease are the definitive source for screening and treatment protocols.
9.
Vahanian A, Alfieri O, Andreotti F et al. Guidelines on the management of valvular heart disease (version 2012): the Joint Task Force on the Management of Valvular Heart Disease of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS). Eur. J. Cardiothorac. Surg. 42(4), S1–S44 (2012).
• The European guidelines for valvular heart disease are consistent with the American College of Cardiology/American Heart Association recommendations for screening and treatment.
10.
Nkomo VT, Gardin JM, Skelton TN, Gottdiener JS, Scott CG, Enriquez-Sarano M. Burden of valvular heart diseases: a population-based study. Lancet 368(9540), 1005–1011 (2006).
•• This study is the largest community based study documenting the prevalence by age group of valvular heart disease in the USA.
11.
Osnabrugge RL, Mylotte D, Head SJ et al. Aortic stenosis in the elderly: disease prevalence and number of candidates for transcatheter aortic valve replacement: a meta-analysis and modeling study. J. Am. Coll. Cardiol. 62(11), 1002–1012 (2013).
12.
United States Census Bureau: population (2018) www.census.gov/topics/population/data.html
13.
Cohen JW, Monheit AC, Beauregard KM et al. The Medical Expenditure Panel Survey: a national health information resource. Inquiry 33(4), 373–389 (1996).
14.
Cohen SB, DiGaetano R, Goksel H. Estimation procedures in the 1996 Medical Expenditure Panel Survey Household Component. Agency for Health Care Policy and Research, MD, USA, MEPS Methodology Report No. 5. AHCPR Pub. No. 99-0027 (1999).
15.
Lee DW, Meyer JW, Clouse J. Implications of controlling for comorbid conditions in cost-of-illness estimates: a case study of osteoarthritis from a managed care system perspective. Value Health 4(4), 329–334 (2001).
16.
Cragg JG. Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica 39(5), 829–844 (1971).
17.
Mullahy J. Much ado about two: reconsidering retransformation and the two-part model in health econometrics. J. Health Econ. 17(3), 247–281 (1998).
18.
Pedrote A, Arana-Rueda E, Arce-León A et al. Impact of contact force monitoring in acute pulmonary vein isolation using an anatomic approach. A Randomized Study. Pacing Clin. Electrophysiol. 39(4), 361–369 (2016).
19.
Rizzo JA, Chen J, Gunnarsson CL, Naim A, Lofland JH. Adjusting for comorbidities in cost of illness studies. J. Med. Econ. 18(1), 12–28 (2015).
• This methodological study illustrates the importance of sensitivity analysis to highlight the inherent uncertainty contained in burden of illness studies.
20.
Moore M, Chen J, Mallow PJ, Rizzo JA. The direct health-care burden of valvular heart disease: evidence from US national survey data. Clinicoecon. Outcomes Res. 8, 613–627 (2016).
21.
Reynolds MR, Lei Y, Wang K et al. Cost–effectiveness of transcatheter aortic valve replacement with a self-expanding prosthesis versus surgical aortic valve replacement. J. Am. Coll. Cardiol. 67(1), 29–38 (2016).
22.
Freed BH, Sugeng L, Furlong K et al. Reasons for nonadherence to guidelines for aortic valve replacement in patients with severe aortic stenosis and potential solutions. Am. J. Cardiol. 105(9), 1339–1342 (2010).
23.
Cameron HL, Bernard LM, Garmo VS, Hernandez JB, Asgar AW. A Canadian cost–effectiveness analysis of transcatheter mitral valve repair with the MitraClip system in high surgical risk patients with significant mitral regurgitation. J. Med. Econ. 17(8), 599–615 (2014).
24.
Brennan JM, Edwards FH, Zhao Y et al. Long-term survival after aortic valve replacement among high-risk elderly patients in the United States: insights from the Society of Thoracic Surgeons Adult Cardiac Surgery Database, 1991 to 2007. Circulation 126(13), 1621–1629 (2012).
25.
d'Arcy JL, Coffey S, Loudon MA et al. Large-scale community echocardiographic screening reveals a major burden of undiagnosed valvular heart disease in older people: the OxVALVE Population Cohort Study. Eur. Heart J. 37(47), 3515–3522 (2016).
26.
Arden C, Chambers JB, Sandoe J et al. Can we improve the detection of heart valve disease? Heart 100(4), 271–273 (2014).
27.
Fleming C, Whitlock EP, Beil TL, Lederle FA. Screening for abdominal aortic aneurysm: a best-evidence systematic review for the U.S. Preventive Services Task Force. Ann. Intern. Med. 142(3), 203–211 (2005).
28.
Lee ES, Pickett E, Hedayati N, Dawson DL, Pevec WC. Implementation of an aortic screening program in clinical practice: implications for the Screen For Abdominal Aortic Aneurysms Very Efficiently (SAAAVE) Act. J. Vasc. Surg. 49(5), 1107–1111 (2009).
29.
Lefevre ML, Force USPST. Screening for abdominal aortic aneurysm: U.S. Preventive Services Task Force recommendation statement. Ann. Intern. Med. 161(4), 281–290 (2014).
30.
Mussa FF. Screening for abdominal aortic aneurysm. J. Vasc. Surg. 62(3), 774–778 (2015).
31.
Buntin MB, Zaslavsky AM. Too much ado about two-part models and transformation? Comparing methods of modeling Medicare expenditures. J. Health Econ. 23(3), 525–542 (2004).
32.
Machlin S, Cohen J, Elixhauser A, Beauregard K, Steiner C. Sensitivity of household reported medical conditions in the medical expenditure panel survey. Med. Care 47(6), 618–625 (2009).
33.
Adams DH, Rosenhek R, Falk V. Degenerative mitral valve regurgitation: best practice revolution. Eur. Heart J. 31(16), 1958–1966 (2010).
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Pages: 879 - 887
PubMed: 31433207
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© 2019 Peter J Mallow.
History
Received: 8 January 2019
Accepted: 17 May 2019
Published online: 21 August 2019
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Incremental direct healthcare expenditures of valvular heart disease in the USA. (2019) Journal of Comparative Effectiveness Research. DOI: 10.2217/cer-2019-0007
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