Exploratory analysis of the potential for advanced diagnostic testing to reduce healthcare expenditures of patients hospitalized with meningitis or encephalitis
Brent D. Fulton aff001; David G. Proudman aff001; Hannah A. Sample aff002; Jeffrey M. Gelfand aff003; Charles Y. Chiu aff004; Joseph L. DeRisi aff002; Michael R. Wilson aff003
Působiště autorů: School of Public Health, University of California, Berkeley, Berkeley, California, United States of America aff001; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, United States of America aff002; Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, United States of America aff003; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, California, United States of America aff004; Department of Medicine, University of California, San Francisco, San Francisco, California, United States of America aff005; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, United States of America aff006; Chan Zuckerberg Biohub, San Francisco, California, United States of America aff007
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
To estimate healthcare expenditures that could be impacted by advanced diagnostic testing for patients hospitalized with meningitis or encephalitis
Patients hospitalized with meningitis (N = 23,933) or encephalitis (N = 7,858) in the U.S. were identified in the 2010–2014 Truven Health MarketScan Commercial Claims and Encounters Database using ICD-9-CM diagnostic codes. The database included an average of 40.8 million commercially insured enrollees under age 65 per year. Clinical, demographic and healthcare utilization criteria were used to identify patient subgroups early in their episode who were at risk to have high inpatient expenditures. Healthcare expenditures of patients within each subgroup were bifurcated: those expenditures that remained five days after the patient could be classified into the subgroup versus those that had occurred previously.
The hospitalization episode rate per 100,000 enrollee-years for meningitis was 13.0 (95% CI: 12.9–13.2) and for encephalitis was 4.3 (95% CI: 4.2–4.4), with mean inpatient expenditures of $36,891 (SD = $92,636) and $60,181 (SD = $130,276), respectively. If advanced diagnostic testing had been administered on the day that a patient could be classified into a subgroup, then a test with a five-day turnaround time could impact the following mean inpatient expenditures that remained by subgroup for patients with meningitis or encephalitis, respectively: had a neurosurgical procedure ($83,337 and $56,020), had an ICU stay ($34,221 and $46,051), had HIV-1 infection or a previous organ transplant ($37,702 and $62,222), were age <1 year ($35,371 and $52,812), or had a hospital length of stay >2 days ($18,325 and $30,244).
Inpatient expenditures for patients hospitalized with meningitis or encephalitis were substantial and varied widely. Patient subgroups who had high healthcare expenditures could be identified early in their stay, raising the potential for advanced diagnostic testing to lower these expenditures.
Diagnostic medicine – Encephalitis – Health economics – HIV-1 – Hospitals – Inpatients – Intensive care units – Meningitis
1. Holmquist L, Russo CA, Elixhauser A. Meningitis-Related Hospitalizations in the United States. HCUP Statistical Brief #57. Rockville, MD: Agency for Healthcare Research and Quality; 2008.
2. Khetsuriani N, Holman RC, Anderson LJ. Burden of Encephalitis-Associated Hospitalizations in the United States, 1988–1997. Clin Infect Dis. 2002;35(2):175–82. doi: 10.1086/341301 12087524
3. George BP, Schneider EB, Venkatesan A. Encephalitis Hospitalization Rates and Inpatient Mortality in the United States, 2000–2010. PLOS ONE. 2014;9(9):e104169. doi: 10.1371/journal.pone.0104169 25192177
4. Vora NM, Holman RC, Mehal JM, Steiner CA, Blanton J, Sejvar J. Burden of Encephalitis-Associated Hospitalizations in the United States, 1998–2010. Neurology. 2014;82(5):443–51. doi: 10.1212/WNL.0000000000000086 24384647
5. Hasbun R, Rosenthal N, Balada-Llasat JM, Chung J, Duff S, Bozzette S, et al. Epidemiology of Meningitis and Encephalitis in the United States, 2011–2014. Clin Infect Dis. 2017;65(3):359–63. doi: 10.1093/cid/cix319 28419350
6. Britton PN, Eastwood K, Paterson B, Durrheim DN, Dale RC, Cheng AC, et al. Consensus guidelines for the investigation and management of encephalitis in adults and children in Australia and New Zealand. Internal Medicine Journal. 2015;45(5):563–76. doi: 10.1111/imj.12749 25955462
7. Messacar K, Breazeale G, Robinson CC, Dominguez SR. Potential Clinical Impact of the Film Array Meningitis Encephalitis Panel in Children with Suspected Central Nervous System Infections. Diagn Microbiol Infect Dis. 2016;86(1):118–20. doi: 10.1016/j.diagmicrobio.2016.05.020 27342782
8. Beernink TM, Wever PC, Hermans MH, Bartholomeus MG. Capnocytophaga Canimorsus Meningitis Diagnosed By 16S rRNA PCR. Pract Neurol. 2016;16(2):136–8. doi: 10.1136/practneurol-2015-001166 26608220
9. Simner PJ, Miller S, Carroll KC. Understanding the promises and hurdles of metagenomic next-generation sequencing as a diagnostic tool for infectious diseases. Clin Infect Dis. 2018;66(5):778–88. doi: 10.1093/cid/cix881 29040428
10. Schlaberg R, Chiu CY, Miller S, Procop GW, Weinstock G, Professional Practice Committee and Committee on Laboratory Practices of the American Society for Microbiology, et al. Validation of metagenomic next-generation sequencing tests for universal pathogen detection. Arch Pathol Lab Med. 2017;141(6):776–86. doi: 10.5858/arpa.2016-0539-RA 28169558
11. Wilson MR, Naccache SN, Samayoa E, Biagtan M, Bashir H, Yu G, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med. 2014;370(25):2408–17. doi: 10.1056/NEJMoa1401268 24896819
12. Wilson MR, O’Donovan BD, Gelfand JM, Sample HA, Chow FC, Betjemann JP, et al. Chronic meningitis investigated via metagenomic next-generation sequencing. JAMA Neurology. 2018:E1–E9.
13. Murkey JA, Chew KW, Carlson M, Shannon CL, Sirohi D, Sample HA, et al. Hepatitis E Virus–associated meningoencephalitis in a lung transplant recipient diagnosed by clinical metagenomic sequencing. Open Forum Infectious Diseases. 2017:1–4.
14. Mongkolrattanothai K, Naccache SN, Bender JM, Samayoa E, Pham E, Yu G, et al. Neurobrucellosis: unexpected answer from metagenomic next-generation sequencing. Journal of the Pediatric Infectious Diseases Society. 2017;6(4):393–8. doi: 10.1093/jpids/piw066 28062553
15. Wilson M, Tyler KL. Emerging diagnostic and therapeutic tools for central nervous system infections. JAMA Neurology. 2016;73(12):1389–90. doi: 10.1001/jamaneurol.2016.3617 27695862
16. Naccache SN, Peggs KS, Mattes FM, Phadke R, Garson JA, Grant P, et al. Diagnosis of neuroinvasive astrovirus infection in an immunocompromised adult with encephalitis by unbiased next-generation sequencing. Clin Infect Dis. 2015;60(6):919–23. doi: 10.1093/cid/ciu912 25572898
17. Hong DK, Blauwkamp TA, Kertesz M, Bercovici S, Truong C, Banaei N. Liquid biopsy for infectious diseases: Sequencing of cell-free plasma to detect pathogen DNA in patients with invasive fungal disease. Diagn Microbiol Infect Dis. 2018;92(3):210–13. doi: 10.1016/j.diagmicrobio.2018.06.009 30017314
18. Bai G, Anderson GF. Extreme markup: the fifty US hospitals with the highest charge-to-cost ratios. Health Aff (Millwood). 2015;34(6):922–8.
19. Bai G. California’s Hospital Fair Pricing Act reduced the prices actually paid by uninsured patients. Health Aff (Millwood). 2015;34(1):64–70.
20. U.S. Census Bureau. [Available from: https://www.census.gov/].
21. Kaiser Family Foundation. 2017 Employer Health Benefits Survey—Section 5: Market Shares of Health Plans Menlo Park, CA: Kaiser Family Foundation; 2017 [updated September 19, 2017. Available from: https://www.kff.org/report-section/ehbs-2017-section-5-market-shares-of-health-plans/].
22. Truven Health Analytics. The Truven Health MarketScan Databases for Health Services Researchers. Ann Arbor, MI 2017.
23. Takhar SS, Ting SA, Camargo CA, Pallin DJ. US Emergency Department Visits for Meningitis, 1993–2008. Acad Emerg Med. 2012;19(6):632–9. doi: 10.1111/j.1553-2712.2012.01377.x 22687178
24. Nigrovic LE, Fine AM, Monuteaux MC, Shah SS, Neuman MI. Trends in the Management of Viral Meningitis at United States Children’s Hospitals. Pediatrics. 2013;131(4):670–6. doi: 10.1542/peds.2012-3077 23530164
25. Jouan Y, Grammatico-Guillon L, Espitalier F, Cazals X, François P, Guillon A. Long-term outcome of severe herpes simplex encephalitis: a population-based observational study. Critical Care. 2015;19(1):345.
26. Thakur KT, Motta M, Asemota AO, Kirsch HL, Benavides DR, Schneider EB, et al. Predictors of outcome in acute encephalitis. Neurology. 2013;81(9):793–800. doi: 10.1212/WNL.0b013e3182a2cc6d 23892708
27. Kennedy C, Duffy S, Smith R, Robinson R. Clinical predictors of outcome in encephalitis. Arch Dis Child. 1987;62(11):1156–62. doi: 10.1136/adc.62.11.1156 3688920
28. Wilson MR, Sample HA, Zorn KC, al. E. Clinical metagenomic sequencing for diagnosis of meningitis and encephalitis. N Engl J Med. 2019;380(24):2327–40. doi: 10.1056/NEJMoa1803396 31189036
29. Maeda JL, Nelson L. An Analysis of Private-Sector Prices for Hospital Admissions. Washington, DC: Congressional Budget Office; 2017. Contract No.: Working Paper 2017–02.
30. Frémond M-L, Perot P, Muth E, Cros G, Dumarest M, Mahlaoui N, et al. Next-generation sequencing for diagnosis and tailored therapy: a case report of astrovirus-associated progressive encephalitis. Journal of the Pediatric Infectious Diseases Society. 2015;4(3):e53–e7. doi: 10.1093/jpids/piv040 26407445
31. Chiu CY, Coffey LL, Murkey J, Symmes K, Sample HA, Wilson MR, et al. Diagnosis of fatal human case of St. Louis encephalitis virus infection by metagenomic sequencing, California, 2016. Emerg Infect Dis. 2017;23(10):1694–98.
32. Wilson MR, Shanbhag NM, Reid MJ, Singhal NS, Gelfand JM, Sample HA, et al. Diagnosing Balamuthia mandrillaris encephalitis with metagenomic deep sequencing. Ann Neurol. 2015;78(5):722–30. doi: 10.1002/ana.24499 26290222
33. Greninger AL, Messacar K, Dunnebacke T, Naccache SN, Federman S, Bouquet J, et al. Clinical metagenomic identification of Balamuthia mandrillaris encephalitis and assembly of the draft genome: the continuing case for reference genome sequencing. Genome Med. 2015;7(113):1–14.
34. Greninger AL. The challenge of diagnostic metagenomics. Expert Rev Mol Diagn. 2018:1–11.
Článek vyšel v časopise
2020 Číslo 1
- Aktuální legislativní změny týkající se zdravotnických prostředků – přehledné shrnutí v kostce
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Českým pacientům je nově k dispozici extrakt léčebného konopí. Jaké benefity přináší?
- Není statin jako statin aneb praktický přehled rozdílů jednotlivých molekul
- Od března je hrazena malá molekula slibující velké výsledky hned ve dvou indikacích