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No reimbursement for hospital medical errors

Health Factors: Quality of Care
Decision Makers: Government - State, Healthcare Organizations
Evidence Rating: Insufficient Evidence
Population Reach: 10-19% of WI's population
Impact on Disparities: No impact on disparities likely

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Description

Recently, the Centers for Medicare and Medicaid Services (CMS) ceased paying hospitals for some of the care made necessary by “preventable complications,” conditions that result from medical errors or improper care and that can reasonably be expected to be averted.

Expected Beneficial Outcomes

Reduced hospital errors
Increased performance measurement

Evidence of Effectiveness

Rosenthal 2007 indicates that the Centers for Medicare and Medicaid Services' (CMS') decision to cease paying hospitals for some care necessitated by “preventable complications” will result in hospitals receiving reduced payment for the care of individual patients with preventable complications but is unlikely to change the total Medicare payments to hospitals substantially. The article indicates that this policy may lead to more wide-spread adoption of quality measurement and reporting or to improved targeting of prophylaxis for community-acquired infections as hospitals will have to ascertain and code infections and other conditions as “present on admission” to avoid revenue reductions.

Implementation Examples

United States

The Federal Centers for Medicare and Medicaid Services (CMS) will not pay for some “never events.” Aetna and Blue Cross Blue Shield halted reimbursement for hospital care resulting from serious medical errors. There is some further enactment in this regard in Pennsylvania, Minnesota, Washington, and Massachusetts.

Wisconsin

In June 2008, the Wisconsin Medical Society (WMS) and the Wisconsin Hospital Association (WHA) jointly endorsed a set of nine adverse events for hospital non-billing, encouraging purchasers and payers to support this effort. As well, several Wisconsin health plans are adding CMS' list of adverse events for non-billing to their hospital contracts. WMS has activated a physician advisory group to study impact on physician care and reimbursement.

Citations - Evidence

Rosenthal 2007 - Rosenthal MB. Nonpayment for performance? Medicare’s new reimbursement rule. New England Journal of Medicine. 2007;357(16):1573-5. Accessed on January 16, 2013
Webpage: http://www.nejm.org/doi/full/10.1056/NEJMp078184

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Decision Makers

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Evidence Rating

Level of effectiveness based on a scan of academic literature and key recommendations of leading organizations.

  • Scientifically Supported Numerous studies or systematic review(s) with positive results
  • Some Evidence Research suggests positive impacts; further study may be warranted
  • Expert Opinion Recommended by credible groups*; research evidence limited
  • Insufficient Evidence Evidence limited or unavailable; further study warranted
  • Mixed Evidence Evidence mixed; further study warranted
  • Evidence of Ineffectiveness Research consistently shows program is detrimental or has no effect

Although many policies and programs are recommended by credible groups, we apply the rating ‘expert opinion’ only when policies are recommended but limited scientific evidence of effectiveness is available.

* The American Heritage Dictionary defines credible as 'capable of being believed; plausible.' and 'worthy of confidence; reliable.' To be considered an 'expert recommendation,' policies and programs must be recommended by one or more organizations that are recognized for their impartial expertise in the area of interest and have limited evidence available.

Potential Population Reach

Portion of Wisconsin's population likely to be reached by a policy or program if implemented statewide, based on its characteristics (e.g., target population(s), geographic limitations, and potential implementers).

<1%   20-49%
1-9%   50-99%
10-19%   100%

Potential Population Reach

Portion of Wisconsin's population likely to be reached by a policy or program if implemented statewide, based on its characteristics (e.g., target population(s), geographic limitations, and potential implementers).

<1%   20-49%
1-9%   50-99%
10-19%   100%

Potential Impact on Health Disparities

Likely impact of a given policy or program on racial/ethnic, socioeconomic, geographic or other disparities in Wisconsin based on its characteristics (e.g., target audience, mode of delivery, etc.) and best available evidence related to disparities.

  • Likely to decrease disparities
  • No impact on disparities likely
  • Likely to increase disparities