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  • Measure Summary
  • NQMC:010941
  • Apr 2015

Cancer: 30-day unplanned readmission rate for cancer patients.

The Alliance of Dedicated Cancer Centers, Duke Cancer Institute, Norris Cotton Cancer Center at Dartmouth-Hitchcock, Sidney Kimmel Cancer Center at Johns Hopkins, Smilow Cancer Center at Yale-New Haven. 2014-2015 measure specifications and beta testing report: 30-day unplanned readmissions for cancer patients (version 1.0). Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Apr 5. 66 p. [13 references]
The Alliance of Dedicated Cancer Centers. 2015 measure update and specifications report: risk-adjusted 30-day unplanned readmissions for cancer patients (version 1.0). Addendum to the 2014-2015 measure specifications and beta testing report. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Jun 30. 22 p. [6 references]

This is the current release of the measure.

Primary Measure Domain

Related Health Care Delivery Measures: Use of Services

Secondary Measure Domain

Does not apply to this measure

Description

This measure is used to assess the risk-adjusted 30-day unplanned readmission rate for cancer patients.

This is a cancer-specific measure. It provides the rate at which all patients, regardless of payer type, have an unplanned re-hospitalization within 30 days of an index admission. The readmission is defined as a subsequent inpatient admission to the reporting facility, which occurs within 30 days of the discharge date of an eligible index admission.

Rationale

Unnecessary hospital readmissions negatively impact cancer patients, by compromising their quality of life, by placing them at risk for health-acquired infections, and by increasing the costs of their care. Furthermore, unplanned readmissions during treatment can delay treatment completion and, potentially, worsen patient prognosis. Preventing these readmissions improves the quality of care for cancer patients. While several studies have examined readmissions, readmissions in cancer patients have not been studied extensively. Existing studies have largely focused on post-operative readmissions in cancer patients, particularly in patients with colon or pancreatic cancer, and calculated readmission rates following major cancer surgery at between 16% and 25%. Moreover, patient factors, including age, comorbidities, and hospital length of stay have been identified as risk factors in these patients (Rochefort & Tomlinson, 2012). Moya et al. (2006) observed a 20% readmission rate in hematopoietic cell transplantation (HCT) recipients along with an extended length of stay during the readmission (25 ± 21 days). Infections (some associated with the graft), graft failure, coagulation disorders, and a second neoplasm were the most frequent causes of readmission. Bejanyan et al. (2012) examined readmissions in patients with myeloablative allogeneic HCT and observed a 39% readmission rate in these patients. Infections, fever, gastrointestinal complications, and graft-versus-host disease (GVHD) were the most frequent reasons for readmission. Less is known about other readmissions in cancer patients as well as the predictive factors in these readmissions.

This measure was developed in support of the following goals:

  • Initiate data-driven initiatives to improve the safety and patient-centeredness of cancer care
  • Optimize cancer care to balance obligatory hospital stays with potential nights at home during recovery
  • Foster improved patient care, better population health, and reductions in hospital costs, where possible, in line with the National Quality Strategy
  • Enhance the portfolio of meaningful outcome measures that may be adopted for the Prospective Payment System (PPS)-Exempt Cancer Hospital Quality Reporting (PCHQR)

Following alpha and beta testing of this measure, the Alliance of Dedicated Cancer Centers (ADCC) and Comprehensive Cancer Center Consortium for Quality Improvement (C4QI) member institutions plan to use this measure in support of these goals. Routine measurement of unplanned readmissions will allow for improvements in care coordination and will support quality improvement efforts to drive reductions in unplanned readmissions. The routine use of a more valid measure that is specific to cancer will help the centers to direct their efforts to address potentially preventable readmissions, thereby improving the quality of care at their centers.

Evidence for Rationale

Bejanyan N, Bolwell BJ, Lazaryan A, Rybicki L, Tench S, Duong H, Andresen S, Sobecks R, Dean R, Pohlman B, Kalaycio M, Copelan EA. Risk factors for 30-day hospital readmission following myeloablative allogeneic hematopoietic cell transplantation (allo-HCT). Biol Blood Marrow Transplant. 2012 Jun;18(6):874-80. PubMed External Web Site Policy

Moya R, Espigado I, Parody R, Carmona M, Márquez F, De Blas JM. Evaluation of readmissions in hematopoietic stem cell transplant recipients. Transplant Proc. 2006 Oct;38(8):2591-2. PubMed External Web Site Policy

Rochefort MM, Tomlinson JS. Unexpected readmissions after major cancer surgery: an evaluation of readmissions as a quality-of-care indicator. Surg Oncol Clin N Am. 2012 Jul;21(3):397-405. PubMed External Web Site Policy

The Alliance of Dedicated Cancer Centers, Duke Cancer Institute, Norris Cotton Cancer Center at Dartmouth-Hitchcock, Sidney Kimmel Cancer Center at Johns Hopkins, Smilow Cancer Center at Yale-New Haven. 2014-2015 measure specifications and beta testing report: 30-day unplanned readmissions for cancer patients (version 1.0). Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Apr 5. 66 p. [13 references]

Primary Health Components

Cancer; 30-day unplanned readmission

Denominator Description

Index admissions of the following patients:

  • Patients with a malignant cancer diagnosis
  • Medicare and non-Medicare patients (all payers)
  • Adults (ages 18 years and older)
  • Inpatient discharges from prospective payment system (PPS)-exempt cancer hospitals (PCHs)
  • Without an in-hospital death
  • Who were not transferred to another acute care facility

See the related "Denominator Inclusions/Exclusions" field.

Numerator Description

Unplanned readmissions for patients within 30 days of the index admission (see the related "Numerator Inclusions/Exclusions" field)

Type of Evidence Supporting the Criterion of Quality for the Measure

  • A formal consensus procedure, involving experts in relevant clinical, methodological, public health and organizational sciences
  • One or more research studies published in a National Library of Medicine (NLM) indexed, peer-reviewed journal

Additional Information Supporting Need for the Measure

Cancer is the second leading cause of death in the United States, with nearly 600,000 cancer-related deaths expected in 2015. It is estimated that more than 1.7 million Americans will be diagnosed with cancer in 2015, and nearly 14.5 million Americans with a history of cancer were alive in 2014. Cancer disproportionately affects older Americans, with 78% of all cancers diagnosed in people 55 years of age and older (American Cancer Society [ACS], 2015). Oncology care contributes greatly to Medicare spending and accounted for an estimated $125 billion in healthcare spending in 2010. This figure is projected to rise to between $173 billion and $207 billion by 2020 (Mariotto et al., 2011). Given the current and projected increases in cancer prevalence and costs of care, it is essential that healthcare providers look for opportunities to lower the costs of cancer care.

Reducing readmissions after hospital discharge has been proposed as an effective means of lowering healthcare costs and improving the outcomes of care. Research suggests that between 9% and 48% of all hospital readmissions are preventable, owing to inadequate treatment during the patient's original (index) admission or after discharge (Benbassat & Taragin, 2000). Jencks et al. (2009) estimated that unplanned readmissions cost the Medicare program $17.4 billion in 2004. Accordingly, all-cause and disease-specific unplanned readmissions rates have been adopted by the Centers for Medicare & Medicaid Services (CMS) as key indicators of inpatient quality care. Additionally, Medicare began reducing payments to hospitals with excess readmissions in October 2012, as mandated in the Patient Protection and Affordable Care Act of 2010.

Benbassat et al. (2000) concluded that global readmission rates are not useful indicators of healthcare quality and, instead, recommended measuring readmissions at the condition level. Readmission rates have been developed for pneumonia, acute myocardial infarction, and heart failure. However, cancer has lagged behind these conditions in the development of validated readmission rates.

Evidence for Additional Information Supporting Need for the Measure

American Cancer Society (ACS). Cancer facts & figures 2015. Atlanta (GA): American Cancer Society (ACS); 2015. 56 p. [54 references]

Benbassat J, Taragin M. Hospital readmissions as a measure of quality of health care: advantages and limitations. Arch Intern Med. 2000 Apr 24;160(8):1074-81. PubMed External Web Site Policy

Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009 Apr 2;360(14):1418-28. PubMed External Web Site Policy

Mariotto AB, Yabroff KR, Shao Y, Feuer EJ, Brown ML. Projections of the cost of cancer care in the United States: 2010-2020. J Natl Cancer Inst. 2011 Jan 19;103(2):117-28. PubMed External Web Site Policy

The Alliance of Dedicated Cancer Centers, Duke Cancer Institute, Norris Cotton Cancer Center at Dartmouth-Hitchcock, Sidney Kimmel Cancer Center at Johns Hopkins, Smilow Cancer Center at Yale-New Haven. 2014-2015 measure specifications and beta testing report: 30-day unplanned readmissions for cancer patients (version 1.0). Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Apr 5. 66 p. [13 references]

Extent of Measure Testing

Validity

Currently, there are only a few peer-reviewed publications that are specific to readmissions in cancer patients. Thus, the measure's face validity was confirmed through written and oral communications between the measure developers and clinicians across Comprehensive Cancer Center Consortium for Quality Improvement (C4QI) during alpha testing.

Criterion-related validity demonstrates if the new measure specifications actually measure true 30-day unplanned readmissions for cancer patients. This was demonstrated after alpha testing, using calendar year (CY) 2012 data for participating facilities to demonstrate the appropriateness of the denominator population and numerator inclusion and exclusion criteria. Please see the original measure documentation for more details.

Admission status variables for the 30-Day Unplanned Readmissions for Cancer Patients measure are defined using the Type of Admission/Visit on the Centers for Medicare and Medicaid Services (CMS) UB-04 Uniform Bill (CMS, 2006). The following definitions were applied:

  • Emergency (code 1): The patient required immediate medical intervention as a result of severe, life threatening or potentially disabling conditions. Generally, the patient was admitted through the emergency room.
  • Urgent (code 2): The patient required immediate attention for the care and treatment of a physical or mental disorder. Generally, the patient was admitted to the first available, suitable accommodation.
  • Elective (code 3): The patient's condition permitted adequate time to schedule the availability of a suitable accommodation.

For the purpose of the measure, these categories were grouped into "planned" and "unplanned" admission visits:

  • Planned readmissions are those within 30 days of discharge from an acute care hospital that are a scheduled part of the patient's plan of care. Planned readmissions are not counted as outcomes in this measure.
  • Unplanned readmissions are defined as an acute clinical event experienced by a patient that requires urgent re-hospitalization. Unplanned readmissions are counted as outcomes in this measure. For the purpose of the 30-Day Unplanned Readmissions for Cancer Patients measure, unplanned readmissions include those with an "emergency" or "urgent" type of admission/visit.

90.9% of unplanned readmissions that were reviewed during beta testing were included in the new 30-Day Unplanned Readmission for Cancer Patients measure. Moreover, 86.2% of planned readmissions were not included, indicating that the new measure is accurately capturing 30-day unplanned readmissions in cancer patients (see Table 4.4 in the original measure documentation for more details).

Reliability

Statistical analyses confirmed that the measure is well-defined and precisely specified so that it can be implemented consistently within and across organizations and allow for accurate comparisons to be made. Refer to Sections 4.2, 4.3, and 4.4 in the original measure documentation for more details.

The results for all ten participating centers as well as individual facilities indicates that, while the measure is reliable, some variability from the average across all participating sites is present when examining scores at the individual facility level. This could be due to:

  • Inconsistent application of the definitions of "planned" or "unplanned" among facilities
  • Inconsistent assignment of admission types (emergency, urgent, and/or elective)
  • Anomalies in other numerator inclusion/exclusion criteria
  • Application of numerator exclusion criteria

It is important to note that this measure has been submitted for consideration for the Prospective Payment System (PPS)-Exempt Cancer Hospital Quality Reporting (PCHQR) Program, which would exclude mandatory reporting by non-PCHs. The measure testing results (presented in the original measure documentation) suggest that it is an appropriate measure for PCHs and non-PCH member institutions of C4QI. Through additional use and further testing, the measure denominator may be expanded to a broader patient population.

Evidence for Extent of Measure Testing

Centers for Medicare & Medicaid Services (CMS). CMS manual system: pub 100-04 Medicare claims processing, transmittal 1104. Uniform billing (UB-04) implementation. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2006 Nov 3. 109 p.

The Alliance of Dedicated Cancer Centers, Duke Cancer Institute, Norris Cotton Cancer Center at Dartmouth-Hitchcock, Sidney Kimmel Cancer Center at Johns Hopkins, Smilow Cancer Center at Yale-New Haven. 2014-2015 measure specifications and beta testing report: 30-day unplanned readmissions for cancer patients (version 1.0). Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Apr 5. 66 p. [13 references]

State of Use

Current routine use

Current Use

Monitoring and planning

Measurement Setting

Hospital Inpatient

Professionals Involved in Delivery of Health Services

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 greater than or equal to 18 years

Target Population Gender

Either male or female

IOM Care Need

Not within an IOM Care Need

IOM Domain

Not within an IOM Domain

Case Finding Period

The reporting period

Denominator Sampling Frame

Patients associated with provider

Denominator (Index) Event or Characteristic

Clinical Condition

Institutionalization

Patient/Individual (Consumer) Characteristic

Denominator Time Window

Does not apply to this measure

Denominator Inclusions/Exclusions

Inclusions
Index admissions of the following patients:

  • Patients with a malignant cancer diagnosis (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] range: 140.00 to 209.99; refer to Appendix C in the original measure documentation)
  • Medicare and non-Medicare patients (all payers)
  • Adults (ages 18 years and older)
  • Inpatient discharges from prospective payment system (PPS)-exempt cancer hospitals (PCHs)
  • Without an in-hospital death
  • Who were not transferred to another acute care facility

Exclusions
The following index admissions are excluded from the measure denominator:

  • Admissions with missing (incomplete/inaccurate) data
  • Patients who expired within the term of the index admission
  • Patients with an admission to an inpatient hospice bed
  • Patients who were discharged against medical advice (AMA), because providers did not have the opportunity to deliver full care and prepare the patient for discharge

Exclusions/Exceptions

Medical factors addressed

Patient factors addressed

Numerator Inclusions/Exclusions

Inclusions
Unplanned readmissions* for patients within 30 days of the index admission

Unplanned readmissions are defined as readmissions at the reporting facility classified as "emergency" or "urgent" type on the UB-04 Uniform Bill. Any unplanned readmissions that do not fall within the numerator exclusions below are counted in the measure numerator.

Note: All patients from the denominator population who experience an unplanned hospital readmission within 30 days of an index admission with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) principal diagnosis codes different from the two bundles of codes listed above are included in the numerator calculation for the measure.

*Unplanned readmissions: An unplanned readmission is defined as a hospital readmission that occurs within 30 days of discharge from a prospective payment system (PPS)-exempt cancer hospital (PCH) and is not scheduled as part of the patient's plan of care. Typically, it is associated with an acute medical event experienced by a patient that requires urgent re-hospitalization. For the purpose of this measure, this includes any readmission (within 30 days of the index admission) with a type of admission/visit of "emergency" or "urgent" on the UB-04 Uniform Bill. For example, some cancer patients develop post-operative infections after discharge that require management in the inpatient setting. Unplanned readmissions may be potentially avoidable and are, therefore, included in the measure numerator.

Unplanned readmissions are identified using the type of admission/visit (form locator 14) submitted on the UB-04 Uniform Bill, where the type of admission/visit is "emergency" or "urgent" (coded value = 1 or 2):

  • Emergency (code 1): The patient required immediate medical intervention as a result of severe, life threatening or potentially disabling conditions. Generally, the patient was admitted through the emergency room.
  • Urgent (code 2): The patient required immediate attention for the care and treatment of a physical or mental disorder. Generally, the patient was admitted to the first available, suitable accommodation.

Exclusions
The following unplanned readmissions are excluded from the measure numerator:

  • Patients who had progression of disease, which was defined as patients with a principal diagnosis of metastatic disease, identified by the ICD-9-CM and ICD-10-CM codes as listed in Appendix C in the original measure documentation
  • Patients with a principal diagnosis of chemotherapy or radiation encounter, identified by ICD-9-CM and ICD-10-CM codes as listed in Appendix C in the original measure documentation

Note: There are other codes available to indicate admission priority. Codes that specify admissions for newborns (code 4), to trauma centers (code 5), those reserved for national assignment (codes 6 to 8), and/or "information not available" (code 9) do not pertain to the population studied and were, therefore, excluded from measure specifications.

Numerator Search Strategy

Institutionalization

Data Source

Administrative clinical data

Type of Health State

Proxy for Outcome

Instruments Used and/or Associated with the Measure

Unspecified

Measure Specifies Disaggregation

Does not apply to this measure

Scoring

Rate/Proportion

Interpretation of Score

Does not apply to this measure (i.e., there is no pre-defined preference for the measure score)

Allowance for Patient or Population Factors

Risk adjustment method widely or commercially available

Description of Allowance for Patient or Population Factors

Risk Adjustment Model

The most common type of risk adjustment used in healthcare outcomes measures is based on the observed rate of the outcome compared to the expected rate. The expected rate is based on patient and, sometimes, hospital demographics. If the observed rate is much higher than the expected rate, then the performance of the hospital would be considered poor. Conversely, if the observed rate is much lower than the expected rate, then the performance of the hospital would be better than expected. A risk-adjusted rate may also be formulated for comparing hospital performance as presented in Figure 2 in the original measure documentation.

Alternative methodologies include indirect or direct standardization and hierarchical modeling. Applying indirect or direct standardization to models that include multiple risk factors is cumbersome. Standardization techniques are typically applied in creating age-adjusted rates in epidemiological studies. Hierarchical modeling is applied when there are multiple levels of risk adjustors. For instance, hierarchical modeling may be used to adjust for variables at the hospital level (e.g., teaching hospital, specialization, etc.) and patient level (e.g., race, payer, diagnosis, etc.). Although some hospital-level variables may be of interest in risk-adjusting readmission rates, the proposed cancer measure will only be applied to eleven hospitals at this point. Therefore, it would not be possible to estimate hospital level adjusters with an acceptable level of precision.

Statistical modeling is typically used to estimate the expected rate for a hospital. In this case, logistic regression was used to estimate the probability of an unplanned readmission that meets the proposed definition outlined in this report based on the risk factors included in the model. The probability of readmission was then summed over the index admissions for each hospital to calculate the expected readmission rate. Prior to fitting the logistic regression model, the dataset was randomly divided into a fit (i.e., model set) and validation set. This strategy allowed the fitting of the model to be tested for robustness or generalization by comparing the c-statistic resulting from using the fit model on the validation dataset. A similar value for the c-statistic (or Area Under the Curve) was indicative of a stable model that may be used for risk adjustment.

The logistic model was fit using SAS/STAT software, Version 9.4 using the 'stepwise' option and maximum likelihood estimation (MLE). Prior to inclusion in the model, the potential association between the various risk adjustors was assessed by calculating the tetrachoric correlation. Variables were reviewed to identify any variables with correlations of more than 0.5 or less than -0.5, which would require exclusion from the model to avoid multicollinearity (highly-correlated risk factors). No variables were excluded due to multicollinearity. The logistic model diagnostics, such as the c-statistic, receiver operating characteristic (ROC), Hosmer and Lemeshow Goodness of Fit Test, the likelihood ratio test and Akaike Information Criterion (AIC), were all collected and analyzed prior to selecting the risk adjustment model.

Continuous variables, such as the number of comorbidities, length of stay and patient age, were all analyzed to determine cut points where the rate of readmission increased or decreased. The model was constructed using only binary indicator variables to allow for an intuitive interpretation and application in practice. The table below lists the risk adjustors that were included in the modeling. Note that three of the variables were removed due to non-statistical issues. The relationship between the presence and absence of metastatic disease was inconsistent among the providers. Two of the reporting hospitals reported lower readmission rates for patients with metastatic disease and four reported higher rates. Due to this inconsistency, this variable was not included in the model at this time. Further investigation is required to determine if this is a reporting issue or if this this is due to the mix of cancer services offered at the various hospitals. The treatment of the patient in the emergency room and bone marrow transplant (BMT) status were both removed from the model because only two providers reported these services. As more providers are added to the dataset, these two variables may be good candidates to include in future models.

Potential Risk Adjustors

Variable Description
Surgical/Non-surgical Admission Based on surgical/non-surgical designation of the Medicare Severity-Diagnosis Related Group (MS-DRG)
Intensive Care Unit (ICU) Utilization Based on use of the ICU revenue codes on claim
Length of Stay Number of days between admission and discharge date
Admission through Emergency Department Admission source
Patient Age Converted to categories based on the Agency for Healthcare Research and Quality (AHRQ) logic for Patient Safety Indicators (PSIs) (refer to Appendix F in the original measure documentation)
Patient Gender As recorded on claim
Low Socioeconomic Status Primary payer of: Medicaid, charity or self-pay uninsured
Comorbidities More than one comorbidity based on Elixhauser index (excludes tumor and mets comorbidity)
Patient Race As recorded on claim; recoded to white/non-white
Metastatic Disease International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) Codes: 196 to 198.99
Solid Tumor (Not Metastatic) ICD-9-CM Codes: 140 to 199 (excluding metastatic)
Bone Marrow Transplant V42.81, V42.82, 996.88, or 996.85
Patient Discharged to Home Based on discharge status on claim
Patient Discharged to Hospice Based on discharge status on claim

Standard of Comparison

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

Internal time comparison

Original Title

30-day unplanned readmissions for cancer patients.

Submitter

Seattle Cancer Care Alliance - Clinical Specialty Collaboration

Developer

Alliance of Dedicated Cancer Centers - Clinical Specialty Collaboration

Consortium of Comprehensive Cancer Centers for Quality Improvement - Clinical Specialty Collaboration

Funding Source(s)

Unspecified

Composition of the Group that Developed the Measure

Alliance of Dedicated Cancer Centers (ADCC) Readmissions Project Team

City of Hope Comprehensive Cancer Center

  • Laura Crocitto, MD, MHA
  • Denise Morse, MBA
  • Merle Smith, RN, BSBA, MSN

Dana-Farber Cancer Institute

  • Steve Flaherty, MPH
  • Apar Gupta, MD

Duke Cancer Institute

  • Audrey Holland, MPH
  • Steve Power, MBA, CSQE, CQA

Health Policy Analytics, LLC

  • Susan White, PhD, RHIA, CHDA

Arthur G. James Cancer Hospital and Richard J. Solove Research Institute

  • Joseph M. Flynn, MD
  • Kristen Johnson, MHA
  • Linda Lane, RHIA, CPHQ
  • Tonja Plew, BSN, RN
  • Julie Rader, BSN, RN
  • Carl Schmidt, MD
  • Angie Wolf-Erdlitz, BS, MGS, RN

The University of Texas MD Anderson Cancer Center

  • Doug Browning, MBA
  • Mercy Cherian, RN, MSN, OCN, RN‐BC
  • Sobha George, MSN, CEN, RN
  • Tiffany Jones, DrPh
  • Bettina Patterson, MSN, RN, OCN
  • Shalonda Smith, RN, BSN
  • Tracy Spinks, BBA
  • Colleen Tallant, MS
  • Ron Walters, MD, MBA, MS, MHA
  • Lavinia Zanaj, MHA, RN

Memorial Sloan Kettering Cancer Center

  • Sara Berger, MBA
  • Steve Martin, MD
  • Dhruvkumar Patel, MS
  • Kathleen Trainor

Norris Cotton Cancer Center at Dartmouth-Hitchcock

  • Jennifer Snide, MS

Seattle Cancer Care Alliance

  • Keith Eaton, MD, PhD
  • Lois Helbert, RN
  • Paul Hendrie, MD, PhD (Chair)
  • Barb Jagels, RN, MHA, CPHQ
  • Tracy Kusnir-Wong, MBA
  • Paul Reitz

Johns Hopkins Sidney Kimmel Comprehensive Cancer Center

  • Joyce M. Kane, MSN, RN, CPHQ, RHIT, CTR

University of Miami Sylvester Comprehensive Cancer Center

  • Gloria (Gigi) Campos, MSIE
  • Laurian Walters, BS

USC Norris Comprehensive Cancer Center

  • Afsaneh Barzi, MD, PhD

Yale Cancer Center

  • Stephanie Buia Amport, MBA, CPHQ
  • Lisa Truini-Pittman, RN, MPH

Financial Disclosures/Other Potential Conflicts of Interest

Unspecified

Adaptation

This measure was not adapted from another source.

Date of Most Current Version in NQMC

2015 Apr

Measure Maintenance

Annual

Date of Next Anticipated Revision

2017 Jul

Measure Status

This is the current release of the measure.

Source(s)

The Alliance of Dedicated Cancer Centers, Duke Cancer Institute, Norris Cotton Cancer Center at Dartmouth-Hitchcock, Sidney Kimmel Cancer Center at Johns Hopkins, Smilow Cancer Center at Yale-New Haven. 2014-2015 measure specifications and beta testing report: 30-day unplanned readmissions for cancer patients (version 1.0). Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Apr 5. 66 p. [13 references]

The Alliance of Dedicated Cancer Centers. 2015 measure update and specifications report: risk-adjusted 30-day unplanned readmissions for cancer patients (version 1.0). Addendum to the 2014-2015 measure specifications and beta testing report. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2015 Jun 30. 22 p. [6 references]

Measure Availability

Source not available electronically.

For more information, contact the Seattle Cancer Care Alliance at 825 Eastlake Ave. E, PO Box 19023, Seattle, WA 98109; Phone: 206-288-7222; Fax: 206-288-1025; E-mail: contactus@seattlecca.org; Web site: www.seattlecca.org External Web Site Policy.

NQMC Status

This NQMC summary was completed by ECRI Institute on October 27, 2016. The information was verified by the measure developer on November 28, 2016.

Copyright Statement

This NQMC summary is based on the original measure, which is subject to the measure developer's copyright restrictions.

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