Article

Factors predicting Medicare national coverage: an empirical analysis.

Health Economics Research Group, Brunel University, Uxbridge, UK.
Medical care (Impact Factor: 2.94). 12/2011; 50(3):249-56. DOI: 10.1097/MLR.0b013e318241eb40
Source: PubMed

ABSTRACT Interventions considered to be particularly controversial or expected to significantly impact the Medicare program in the United States are considered in National Coverage Determinations. Medicare coverage for such interventions is limited to those deemed "reasonable and necessary" for the diagnosis or treatment of an illness or injury. What constitutes reasonable and necessary has not, however, been clearly defined.
To determine factors associated with positive National Coverage Determinations.
A dataset of coverage decisions from 1999 to 2007 (n=195) was created with the following variables: direction of coverage decision; quality of supporting evidence; availability of alternative interventions; cost-effectiveness of intervention; type of intervention; coverage requestor; and year of decision. Univariate and multivariate logistic regression analysis was used to determine factors associated with positive coverage.
The following variables were independently associated with positive Medicare coverage: good or fair quality supporting evidence (adjusted odds ratio, OR=6.04, P<0.01); presence of an alternative intervention (OR=0.130, P<0.01); no associated estimate of cost-effectiveness (OR=0.190, P<0.05). In addition, in comparison with coverage decisions made in the years 1999 to 2001, those made in the years 2002 to 2003, 2004 to 2005, and 2006 to 2007, were associated with positive coverage [ORs of 0.311 (P<0.05), 0.310 (P<0.1), and 0.109 (P<0.01), respectively].
Findings suggest that good or fair quality supporting evidence is a strong predictor of positive coverage. Availability of alternative interventions, more recent decisions, and lack of an associated estimate of cost-effectiveness are associated with a decreased likelihood of positive coverage. The findings highlight Medicare's move to evidence-based coverage decisions, and suggest that coverage decisions are influenced by the availability of cost-effectiveness evidence.

Download full-text

Full-text

Available from: James D Chambers, Jan 14, 2014
0 Followers
 · 
158 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Health technology assessment organizations evaluate medical therapies and technologies to help inform coverage and reimbursement decisions for payers around the globe. Even as they establish strict review processes, these organizations--and the reimbursement authorities that use their assessments--have sometimes handled cancer interventions with special care. We found that some countries have created separate health technology assessment pathways for cancer treatment, while others have eased access to cancer treatments through end-of-life or disease-severity exceptions within health technology assessment policies. In the United States, although no separate evaluation pathways exist for cancer, cancer drugs receive special status by virtue of unique Medicare rules covering off-label indications. Worldwide, we demonstrate that health technology assessment organizations are struggling with cancer's "exceptionalism."
    Health Affairs 04/2012; 31(4):700-8. DOI:10.1377/hlthaff.2011.1309 · 4.64 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: To systematically review and summarize the Center for Medicare and Medicaid Services (CMS) national coverage determination (NCDs) pertaining diagnostic imaging technologies from 1999 through 2010. All NCDs pertaining to diagnostic imaging were identified from the Tufts Medical Center NCD database. The variables under study included the quality of the clinical evidence and the final coverage determination. The types of restrictions were categorized. We also categorized the final decisions as "positive coverage" or "no positive/no change in coverage" and assessed the correlation between positive coverage and other variables using Fisher exact test. Twenty-two of 152 (15%) NCDs pertained to diagnostic imaging technologies. The supporting evidence was judge to be good, fair, and poor in 5, 6, and 11 cases, respectively. Eleven technologies (50%) were covered with conditions, four (18%) deferred the coverage decision to local level, and two (9%) were completely not covered. In five instances there was no change to the prior coverage status. Of the 11 decisions resulting in positive coverage, 8 (73%) restricted use to specific population subgroups, 5 (46%) applied restrictions related to treatment, 4 were covered with evidence development, and 2 were restricted to care in specific settings. A significantly higher rate of positive coverage decisions was achieved if the available evidence was good (100% 5/5) or fair (83% 5/6) compared to technologies with poor evidence (10% 1/10) (P < .01). CMS has demonstrated a propensity to limit the use of advanced diagnostic imaging to scenarios in which appropriateness is supported by adequate evidence of clinical utility and improved outcomes with the quality of evidence being a significant factor on final decisions. Understanding the need for high-quality evidence and the types of limitations placed on coverage allows for appropriate planning for the incorporation of diagnostic imaging technologies into clinical practice.
    Academic radiology 06/2012; 19(9):1060-5. DOI:10.1016/j.acra.2012.05.005 · 2.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was to analyze influences of process- and technology-related characteristics on the outcomes of coverage decisions. Using survey data on 77 decisions from 13 countries, we examined whether outcomes differ by 14 variables that describe components of decision-making processes and the technology. We analyzed the likelihood of committees covering a technology, i.e. positive (including partial coverage) vs. negative coverage decisions. We performed non-parametric univariate tests and binomial logistic regression with a stepwise variable selection procedure. We identified a negative association between a positive decision and whether the technology is a prescribed medicine (p=0.0097). Other significant influences on a positive decision outcome included one disease area (p=0.0311) and whether a technology was judged to be (cost-)effective (p<0.0001). The first estimation of the logistic regression yielded a quasi-complete separation for technologies that were clearly judged (cost-)effective. In uncertain decisions, a higher number of stakeholders involved in voting (odds ratio=2.52; p=0.03) increased the likelihood of a positive outcome. The results suggest that decisions followed the lines of evidence-based decision-making. Despite claims for transparent and participative decision-making, the phase of evidence generation seemed most critical as decision-makers usually adopted the assessment recommendations. We identified little impact of process configurations.
    Health Policy 05/2013; 112(3). DOI:10.1016/j.healthpol.2013.04.011 · 1.73 Impact Factor
Show more