Skip to main content

The AHRQ National Quality Measures Clearinghouse (NQMC, qualitymeasures.ahrq.gov) Web site will not be available after July 16, 2018 because federal funding
through AHRQ will no longer be available to support the NQMC as of that date. For additional information, read our full announcement.
  • Measure Summary
  • NQMC:010749
  • Aug 2015
  • NQF-Endorsed Measure

Failure to rescue: percentage of patients who died with a complication within 30 days from admission.

Failure to rescue 30-day mortality measure specifications. Philadelphia (PA): The Children's Hospital of Philadelphia Research Institute; 2015 Aug. 56 p. [33 references]

View the original measure documentation External Web Site Policy

This is the current release of the measure.

This measure updates a previous version: Failure to rescue 30-day mortality measure specifications. Philadelphia (PA): The Children's Hospital of Philadelphia Research Institute; 2015 May. 24 p.

Primary Measure Domain

Clinical Quality Measures: Outcome

Secondary Measure Domain

Does not apply to this measure

Description

This measure is used to assess the percentage of patients who died with a complication within 30 days from admission.

Rationale

Evidence to date suggests that complication measures are less sensitive to hospital characteristics, after adjusting for severity of illness, than mortality based measures. This is an underlying assumption of failure to rescue (FTR) theory—complications are undesirable outcome measures because they reflect underlying patient severity and diagnosis coding more than they reflect hospital care. Instead, a hospital's quality is put to the test when a patient develops a complication, and whether a patient is salvaged after a complication will be a function of the care delivered by the hospital and its knowledge base, depth, and facilities. Thus, "good" hospitals will rescue patients by identifying complications quickly and treating them aggressively, resulting in lower FTR. Although many "failures," just like deaths, are often not preventable, we have argued that FTR may be a better measure for comparing hospital quality because of better severity adjustment properties, and because of its focus on hospital actions. By studying a population of patients who, by definition, have already developed a complication, the specifics of severity of illness adjustment becomes less important in failure rate analyses, because all patients have experienced complications and thus are more uniformly ill.

Evidence for Rationale

Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med. 2009 Oct 1;361(14):1368-75. PubMed External Web Site Policy

Hartz AJ, Krakauer H, Kuhn EM, Young M, Jacobsen SJ, Gay G, Muenz L, Katzoff M, Bailey RC, Rimm AA. Hospital characteristics and mortality rates. N Engl J Med. 1989 Dec 21;321(25):1720-5. PubMed External Web Site Policy

Sheetz KH, Waits SA, Krell RW, Campbell DA, Englesbe MJ, Ghaferi AA. Improving mortality following emergent surgery in older patients requires focus on complication rescue. Ann Surg. 2013 Oct;258(4):614-7; discussion 617-8. PubMed External Web Site Policy

Silber JH, Rosenbaum PR. A spurious correlation between hospital mortality and complication rates: the importance of severity adjustment. Med Care. 1997 Oct;35(10 Suppl):OS77-92. PubMed External Web Site Policy

Primary Health Components

30-day mortality; general, orthopedic or vascular surgery; complications

Denominator Description

General surgery, orthopedic and vascular patients with complications plus patients who died without documented complications within 30 days of admission (see the related "Denominator Inclusions/Exclusions" field)

Numerator Description

Patients who died with a complication plus patients who died without documented complications. Death is defined as death within 30 days from admission. See the related "Numerator Inclusions/Exclusions" field.

Type of Evidence Supporting the Criterion of Quality for the Measure

  • One or more research studies published in a National Library of Medicine (NLM) indexed, peer-reviewed journal

Additional Information Supporting Need for the Measure

Unspecified

Extent of Measure Testing

Split half sample reliability was 0.30, similar to 30 day mortality (0.29).

  1. Marginal and partial coefficients in logit models using detailed patient characteristics and hospital characteristics shown to be associated with better outcomes in previous studies (Silber et al., 2007; Aiken et al., 2002). The marginal results use one hospital characteristic at a time along with all patient characteristics. "Partial" regression results, using all hospital and patient variables simultaneously have the disadvantage that correlation between hospital characteristics can cause difficulty in interpreting the effects of individual hospital variables. The following hospital characteristics have been shown to be associated with better outcomes: (1) teaching hospital status (member of the American Council of Teaching Hospitals); (2) high technology status (does the hospital perform open heart surgery or perform organ transplantation); (3) hospital size greater than 200/250 beds; (4) bed-to-nurse ratio (where nurses are the sum of registered nurse [RN] plus licensed practical nurse [LPN] full-time equivalent [FTE] positions); and (5) nursing skill mix (the ratio of RN/[RN+LPN]) (Silber et al., 2007; Silber et al., 1995; Silber et al., 1997; Silber et al., 2000; Silber et al., 2002; Aiken et al., 2002; Aiken et al., 2003).
  2. The relative contribution of patient-to-hospital characteristics that predicted each outcome of interest, as provided by the omega statistic (Silber et al., 2007; Silber, Rosenbaum, & Ross, 1995). The omega statistic computes a ratio of the squared sum of the log odds for model patent variables divided by a similar quantity calculated for the model hospital variables. All else being equal, outcome measures that have lower omega ratios may be more desirable quality indicators, since the lower the omega, the greater the hospital's impact on outcome relative to the patient's impact. This is especially important if modeling patient severity is difficult (as with claims data) so that the lower the omega suggests the higher relative influence of hospital characteristics as compared to patient characteristics.

Evidence for Extent of Measure Testing

Aiken LH, Clarke SP, Cheung RB, Sloane DM, Silber JH. Educational levels of hospital nurses and surgical patient mortality. JAMA. 2003 Sep 24;290(12):1617-23. PubMed External Web Site Policy

Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002 Oct 23-30;288(16):1987-93. PubMed External Web Site Policy

Silber J, Rosenbaum P, Ross R. Comparing the contributions of groups of predictors: which outcomes vary with hospital rather than patient characteristics?. J Am Stat Assoc. 1995;90:7-18.

Silber JH, Kennedy SK, Even-Shoshan O, Chen W, Koziol LF, Showan AM, Longnecker DE. Anesthesiologist direction and patient outcomes. Anesthesiology. 2000 Jul;93(1):152-63. PubMed External Web Site Policy

Silber JH, Kennedy SK, Even-Shoshan O, Chen W, Mosher RE, Showan AM, Longnecker DE. Anesthesiologist board certification and patient outcomes. Anesthesiology. 2002 May;96(5):1044-52. PubMed External Web Site Policy

Silber JH, Romano PS, Rosen AK, Wang Y, Even-Shoshan O, Volpp KG. Failure-to-rescue: comparing definitions to measure quality of care. Med Care. 2007 Oct;45(10):918-25. PubMed External Web Site Policy

Silber JH, Rosenbaum PR, Schwartz JS, Ross RN, Williams SV. Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA. 1995 Jul 26;274(4):317-23. PubMed External Web Site Policy

Silber JH, Rosenbaum PR, Williams SV, Ross RN, Schwartz JS. The relationship between choice of outcome measure and hospital rank in general surgical procedures: implications for quality assessment. Int J Qual Health Care. 1997 Jun;9(3):193-200. PubMed External Web Site Policy

State of Use

Current routine use

Current Use

External oversight/Medicare

External oversight/Veterans Health Administration

Internal quality improvement

Public reporting

Quality of care research

Measurement Setting

Hospital Inpatient

Professionals Involved in Delivery of Health Services

Advanced Practice Nurses

Nurses

Physician Assistants

Physicians

Least Aggregated Level of Services Delivery Addressed

Single Health Care Delivery or Public Health Organizations

Statement of Acceptable Minimum Sample Size

Does not apply to this measure

Target Population Age

Age 18 to 90 years

Target Population Gender

Either male or female

National Quality Strategy Aim

Better Care

National Quality Strategy Priority

Making Care Safer
Prevention and Treatment of Leading Causes of Mortality

IOM Care Need

Getting Better

IOM Domain

Effectiveness

Safety

Case Finding Period

Typically, at least one year of data has been searched to identify cases.

Denominator Sampling Frame

Patients associated with provider

Denominator (Index) Event or Characteristic

Clinical Condition

Institutionalization

Patient/Individual (Consumer) Characteristic

Therapeutic Intervention

Denominator Time Window

Time window follows index event

Denominator Inclusions/Exclusions

Inclusions
General surgery, orthopedic and vascular patients with complications plus patients who died without documented complications within 30 days of admission

Include adult patients admitted for one of the procedures in the general surgery, orthopedic or vascular diagnosis-related groups (DRGs). Refer to Appendix A in the original measure documentation for additional information.

Exclusions
Patients over age 90, under age 18

Exclusions/Exceptions

Unspecified

Numerator Inclusions/Exclusions

Inclusions
Patients who died with a complication plus patients who died without documented complications. Death is defined as death within 30 days from admission.

Failure to rescue (FTR) is defined as the probability of death following a complication. All patients in an FTR analysis have developed a complication or died without a documented complication (by definition). Refer to the original measure documentation for additional information.

Note:

  • Complicated patient has at least one of the complications defined in Appendix B of the original measure documentation. Complications are defined using the secondary International Classification of Diseases, Ninth Revision (ICD-9) diagnosis and procedure codes and the diagnosis-related group (DRG) code of the current admission. International Classification of Diseases, Tenth Revision (ICD-10) codes are provided in Appendix D of the original measure documentation.
  • Comorbidities are defined in Appendix C of the original measure documentation using secondary ICD-9 diagnosis codes of the current admission and primary or secondary ICD-9 diagnosis codes of previous admission within 90 days of the admission date of the current admission. ICD-10 codes are provided in Appendix E of the original measure documentation.
  • When Current Procedural Terminology (CPT) codes are available, the definition of complications and comorbidities are augmented to include them.

Exclusions
Unspecified

Numerator Search Strategy

Institutionalization

Data Source

Administrative clinical data

Paper medical record

State/Province public health data

Type of Health State

Death

Instruments Used and/or Associated with the Measure

Unspecified

Measure Specifies Disaggregation

Does not apply to this measure

Scoring

Rate/Proportion

Interpretation of Score

Desired value is a lower score

Allowance for Patient or Population Factors

Analysis by high-risk subgroup (stratification by vulnerable populations)

Analysis by subgroup (stratification by individual factors, geographic factors, etc.)

Case-mix adjustment

Paired data at patient level

Risk adjustment devised specifically for this measure/condition

Risk adjustment method widely or commercially available

Description of Allowance for Patient or Population Factors

Risk Adjustment: Model was developed using logistic regression analysis.

Associated Data Elements: Age in years, sex, race, comorbidities, diagnosis-related groups (DRGs) (combined with and without complications) and procedure codes within DRGs, emergency admission status, and transfer-in status.

Failure to rescue (FTR) is adjusted using a logistic regression model where y is a failure and the total N is composed of patients who develop a complication and patients who died without a documented complication.

Standard of Comparison

External comparison at a point in, or interval of, time

External comparison of time trends

Internal time comparison

Original Title

Failure to rescue 30-day mortality.

Measure Collection Name

Failure to Rescue Measures

Submitter

The Children's Hospital of Philadelphia - Hospital/Medical Center

Developer

The Children's Hospital of Philadelphia - Hospital/Medical Center

Funding Source(s)

The Children's Hospital of Philadelphia

Composition of the Group that Developed the Measure

  • Jeffrey H. Silber, MD, PhD
  • The Children's Hospital of Philadelphia
  • The University of Pennsylvania

Financial Disclosures/Other Potential Conflicts of Interest

None

Endorser

National Quality Forum

NQF Number

0353

Date of Endorsement

2015 Dec 10

Adaptation

This measure was not adapted from another source.

Date of Most Current Version in NQMC

2015 Aug

Measure Maintenance

Annual

Date of Next Anticipated Revision

2017 Aug 30

Measure Status

This is the current release of the measure.

This measure updates a previous version: Failure to rescue 30-day mortality measure specifications. Philadelphia (PA): The Children's Hospital of Philadelphia Research Institute; 2015 May. 24 p.

Source(s)

Failure to rescue 30-day mortality measure specifications. Philadelphia (PA): The Children's Hospital of Philadelphia Research Institute; 2015 Aug. 56 p. [33 references]

Measure Availability

Source available from The Children's Hospital of Philadelphia (CHOP) Research Institute Web site External Web Site Policy.

For more information, contact Jeffery H. Silber at The Children's Hospital of Philadelphia (CHOP), 3535 Market Street, Suite 1029, Philadelphia, PA 19104; Phone: 215-590-5635; Fax: 215-590-2378; E-mail: silber@email.chop.edu; Web site: www.research.chop.edu/programs/cor External Web Site Policy.

NQMC Status

This NQMC summary was completed by ECRI Institute on April 1, 2014. The information was verified by the measure developer on April 9, 2014.

This NQMC summary was updated by ECRI Institute on July 2, 2015. The information was verified by the measure developer on July 22, 2015.

This NQMC summary was updated again by ECRI Institute on May 18, 2016. The information was verified by the measure developer on May 24, 2016.

Copyright Statement

No copyright restrictions apply.

NQMC Disclaimer

The National Quality Measures Clearinghouse™ (NQMC) does not develop, produce, approve, or endorse the measures represented on this site.

All measures summarized by NQMC and hosted on our site are produced under the auspices of medical specialty societies, relevant professional associations, public and private organizations, other government agencies, health care organizations or plans, individuals, and similar entities.

Measures represented on the NQMC Web site are submitted by measure developers, and are screened solely to determine that they meet the NQMC Inclusion Criteria.

NQMC, AHRQ, and its contractor ECRI Institute make no warranties concerning the content or its reliability and/or validity of the quality measures and related materials represented on this site. Moreover, the views and opinions of developers or authors of measures represented on this site do not necessarily state or reflect those of NQMC, AHRQ, or its contractor, ECRI Institute, and inclusion or hosting of measures in NQMC may not be used for advertising or commercial endorsement purposes.

Readers with questions regarding measure content are directed to contact the measure developer.

About NQMC Measure Summaries

NQMC provides structured summaries containing information about measures and their development.

Measure Summary FAQs


Measure Summaries

New This Week

View more and sign up for our Newsletter

Get Adobe Reader