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  • Measure Summary
  • NQMC:011296
  • Mar 2017
  • NQF-Endorsed Measure

Heart failure (HF): hospital 30-day, all-cause, unplanned risk-standardized readmission rate (RSRR) following HF hospitalization.

Yale New Haven Health Services Corporation (YNHHSC), Center for Outcomes Research and Evaluation (CORE). 2017 condition-specific measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2017 Mar. 112 p.

View the original measure documentation External Web Site Policy

This is the current release of the measure.

This measure updates a previous version: Specifications manual for national hospital inpatient quality measures, version 5.0b. Centers for Medicare & Medicaid Services (CMS), The Joint Commission; Effective 2015 Oct 1. various p.

Primary Measure Domain

Related Health Care Delivery Measures: Use of Services

Secondary Measure Domain

Does not apply to this measure

Description

This measure estimates a hospital-level 30-day risk-standardized readmission rate (RSRR) for patients discharged from the hospital with a principal diagnosis of heart failure (HF). The outcome is defined as unplanned readmission for any cause within 30 days of the discharge date for the index admission. A specified set of planned readmissions do not count as readmissions.

The Centers for Medicare & Medicaid Services (CMS) annually reports the measure for individuals who are 65 years and older and are Medicare Fee-for-Service (FFS) beneficiaries hospitalized in non-federal short-term acute care hospitals (including Indian Health Services hospitals) and critical access hospitals.

Rationale

Readmission of patients who were recently discharged after hospitalization with heart failure (HF) represents an important, expensive, and often preventable adverse outcome. The risk of readmission can certainly be modified by the quality and type of care provided to these patients. Improving readmission rates is the joint responsibility of hospitals and clinicians. Measuring readmission will create incentives to invest in interventions to improve hospital care, better assess the readiness of patients for discharge and facilitate transitions to outpatient status.

Evidence for Rationale

Yale University/Yale-New Haven Hospital Center for Outcomes Research & Evaluation (YNHH-CORE). Hospital 30-day heart failure readmission measure: methodology. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2008 Apr 23. 51 p. [27 references]

Primary Health Components

Heart failure (HF); 30-day readmission rate

Denominator Description

The measure cohort consists of admissions for Medicare Fee-for-Service (FFS) beneficiaries aged 65 years and older and discharged from non-federal acute care hospitals and critical access hospitals, having a principal discharge diagnosis of heart failure (HF).

The risk-standardized readmission rate (RSRR) is calculated as the ratio of the number of "predicted" readmissions to the number of "expected" readmissions at a given hospital, multiplied by the national observed readmission rate. For each hospital, the denominator is the number of readmissions expected based on the nation's performance with that hospital's case-mix.

See the related "Denominator Inclusions/Exclusions" field.

Note: This outcome measure does not have a traditional numerator and denominator like a core process measure; thus, this field is used to define the measure cohort.

See the 2017 Condition-specific Measures Updates and Specifications Report: Hospital-level 30-day Risk-standardized Readmission Measures External Web Site Policy for more details.

Numerator Description

The measure assesses unplanned readmissions to an acute care hospital, from any cause, within 30 days from the date of discharge from an index heart failure (HF) admission.

The risk-standardized readmission rate (RSRR) is calculated as the ratio of the number of "predicted" readmissions to the number of "expected" readmissions at a given hospital, multiplied by the national observed readmission rate. For each hospital, the numerator of the ratio is the number of readmissions within 30 days predicted based on the hospital's performance with its observed case-mix.

See the related "Numerator Inclusions/Exclusions" field.

Note: This outcome measure does not have a traditional numerator and denominator like a core process measure; thus, this field is used to define the measure cohort.

See the 2017 Condition-specific Measures Updates and Specifications Report: Hospital-level 30-day Risk-standardized Readmission Measures External Web Site Policy for more details.

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

Many care processes that can influence readmission risk. In general, randomized controlled trials have shown that improvement in the following areas can directly reduce readmission rates: quality of care during the initial admission; improvement in communication with patients, their caregivers, and their clinicians; patient education; predischarge assessment; and coordination of care after discharge. Evidence that hospitals have been able to reduce readmission rates through these quality-of-care initiatives illustrates the degree to which hospital practices can affect readmission rates. Successful randomized trials have reduced 30-day readmission rates by 20% to 40% (Jack et al., 2009; Coleman et al., 2004; Courtney et al., 2009; Garasen, Windspoll, & Johnsen, 2007; Koehler et al., 2009; Mistiaen, Francke, & Poot, 2007; Naylor et al., 1994; Naylor et al., 1999; van Walraven et al., 2002; Weiss, Yakusheva, & Bobay, 2010; Krumholz et al., 2002). Since 2008, 14 Medicare Quality Improvement Organizations have been funded to focus on care transitions, applying lessons learned from clinical trials. Several have been notably successful in reducing readmissions. The strongest evidence supporting the efficacy of improved discharge processes and enhanced care at transitions is a randomized controlled trial by the Project RED (Re-Engineered Discharge) intervention, in which a nurse was assigned to each patient as a discharge advocate, responsible for patient education, follow-up, medication reconciliation, and preparing individualized discharge instructions sent to the patient's primary care provider (Jack et al., 2009). There was also a follow-up phone call from a pharmacist within 4 days of discharge. This intervention demonstrated a 30% reduction in 30-day readmissions (Jack et al., 2009). Hospital processes that reflect the quality of inpatient and outpatient care such as discharge planning, medication reconciliation, and coordination of outpatient care have been shown to reduce readmission rates (Nelson, Maruish, & Axler, 2000). Although readmission rates are also influenced by hospital system characteristics, such as the bed capacity of the local health care system, these hospital characteristics should not influence quality of care (Fisher et al., 1994). Therefore, this measure does not risk adjust for such hospital characteristics.

The Medicare Payment Advisory Commission (MedPAC) (2007) has called for hospital-specific public reporting of readmission rates, identifying heart failure (HF) as a priority condition. MedPAC finds that readmissions are common, costly, and often preventable. Based on 2005 Medicare data, MedPAC estimates that about 12.5% of Medicare HF admissions were followed by a readmission within 15 days, accounting for more than 90,000 admissions at a cost of $590 million. Between July 2005 and June 2008, the median 30-day readmission rate for HF was 24.4%, with a range of 15.9% to 34.4% (Krumholz et al., 2009).

HF incidence approaches 10 per 1000 of the population after 65 years of age (National Heart, Lung, and Blood Institute, 2007); prevalence of HF in the U.S. is estimated at nearly 6 million (Mozaffarian et al., 2015; Lloyd-Jones et al., 2010). HF is the most common principal discharge diagnosis among older adults and the third highest for hospital reimbursements in 2005 (Jessup & Brozena, 2003; Centers for Medicare & Medicaid Services [CMS], 2006), and the leading cause of readmission among Medicare beneficiaries, with nearly half of HF patients expected to return to the hospital within 6 months of discharge (Jencks, Williams, & Coleman, 2009; Krumholz et al., 1997). All-cause 30-day readmission rates per 1,000 patients discharged with HF increased by 11% between 1992 and 2001 (Merrill, 2003). HF readmission is a costly event and represents an undesirable outcome of care from the patient's perspective, and highly disparate HF readmission rates among hospitals suggest there is room for improvement (MedPAC, 2007; Bernheim et al., 2010). Moreover, there is substantial inter-hospital variation in the risk of readmission that is not clearly explained by differences in case mix.

The HF risk-standardized readmission rate (RSRR) measure is thus intended to inform quality-of-care improvement efforts, as individual process-based performance measures cannot encompass all the complex and critical aspects of care within a hospital that contribute to patient outcomes. Many stakeholders, including patient organizations, are interested in outcomes measures that allow patients and providers to assess relative outcomes performance for hospitals.

Evidence for Additional Information Supporting Need for the Measure

Bernheim SM, Grady JN, Lin Z, Wang Y, Wang Y, Savage SV, Bhat KR, Ross JS, Desai MM, Merrill AR, Han LF, Rapp MT, Drye EE, Normand SL, Krumholz HM. National patterns of risk-standardized mortality and readmission for acute myocardial infarction and heart failure. Update on publicly reported outcomes measures based on the 2010 release. Circ Cardiovasc Qual Outcomes. 2010 Sep;3(5):459-67. PubMed External Web Site Policy

Centers for Medicare & Medicaid Services (CMS). Medicare ranking for all short-stay hospitals by disc: fiscal year 2005 versus 2004. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2006 Sep. 1 p.

Coleman EA, Smith JD, Frank JC, Min SJ, Parry C, Kramer AM. Preparing patients and caregivers to participate in care delivered across settings: the Care Transitions Intervention. J Am Geriatr Soc. 2004 Nov;52(11):1817-25. PubMed External Web Site Policy

Courtney M, Edwards H, Chang A, Parker A, Finlayson K, Hamilton K. Fewer emergency readmissions and better quality of life for older adults at risk of hospital readmission: a randomized controlled trial to determine the effectiveness of a 24-week exercise and telephone follow-up program. J Am Geriatr Soc. 2009 Mar;57(3):395-402. PubMed External Web Site Policy

Fisher ES, Wennberg JE, Stukel TA, Sharp SM. Hospital readmission rates for cohorts of Medicare beneficiaries in Boston and New Haven. N Engl J Med. 1994 Oct 13;331(15):989-95. PubMed External Web Site Policy

Garasen H, Windspoll R, Johnsen R. Intermediate care at a community hospital as an alternative to prolonged general hospital care for elderly patients: a randomised controlled trial. BMC Public Health. 2007 May 2;7:68. PubMed External Web Site Policy

Jack BW, Chetty VK, Anthony D, Greenwald JL, Sanchez GM, Johnson AE, Forsythe SR, O'Donnell JK, Paasche-Orlow MK, Manasseh C, Martin S, Culpepper L. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009 Feb 3;150(3):178-87. 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

Jessup M, Brozena S. Heart failure. N Engl J Med. 2003 May 15;348(20):2007-18. PubMed External Web Site Policy

Koehler BE, Richter KM, Youngblood L, Cohen BA, Prengler ID, Cheng D, Masica AL. Reduction of 30-day postdischarge hospital readmission or emergency department (ED) visit rates in high-risk elderly medical patients through delivery of a targeted care bundle. J Hosp Med. 2009 Apr;4(4):211-8. PubMed External Web Site Policy

Krumholz HM, Amatruda J, Smith GL, Mattera JA, Roumanis SA, Radford MJ, Crombie P, Vaccarino V. Randomized trial of an education and support intervention to prevent readmission of patients with heart failure. J Am Coll Cardiol. 2002 Jan 2;39(1):83-9. PubMed External Web Site Policy

Krumholz HM, Merrill AR, Schone EM, Schreiner GC, Chen J, Bradley EH, Wang Y, Wang Y, Lin Z, Straube BM, Rapp MT, Normand SL, Drye EE. Patterns of hospital performance in acute myocardial infarction and heart failure 30-day mortality and readmission. Circ Cardiovasc Qual Outcomes. 2009 Sep;2(5):407-13. PubMed External Web Site Policy

Krumholz HM, Parent EM, Tu N, Vaccarino V, Wang Y, Radford MJ, Hennen J. Readmission after hospitalization for congestive heart failure among Medicare beneficiaries. Arch Intern Med. 1997 Jan 13;157(1):99-104. PubMed External Web Site Policy

Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, Ferguson TB, Ford E, Furie K, Gillespie C, Go A, Greenlund K, Haase N, Hailpern S, Ho PM, Howard V, Kissela B, Kittner S, Lackland D, Lisabeth L, Marelli A, McDermott MM, Meigs J, Mozaffarian D, Mussolino M, Nichol G, Roger VL, Rosamond W, Sacco R, Sorlie P, Roger VL, Thom T, Wasserthiel-Smoller S, Wong ND, Wylie-Rosett J, American Heart Association Statistics Committee and Stroke Statistics, Writing Group Members. Heart disease and stroke statistics--2010 update: a report from the American Heart Association. Circulation. 2010 Feb 23;121(7):e46-e215. PubMed External Web Site Policy

Medicare Payment Advisory Commission (MedPAC). Report to the Congress: promoting greater efficiency in Medicare. Washington (DC): Medicare Payment Advisory Commission (MedPAC); 2007 Jun. 277 p.

Merrill A. MQMS highlights: a report from the Medicare Quality Monitoring System. Heart failure, 1992-2001. Washington (DC): Mathematica Policy Research, Inc.; 2003. 2 p. [4 references]

Mistiaen P, Francke AL, Poot E. Interventions aimed at reducing problems in adult patients discharged from hospital to home: a systematic meta-review. BMC Health Serv Res. 2007;7:47. [111 references] PubMed External Web Site Policy

Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, de Ferranti S, Despres JP, Fullerton HJ, Howard VJ, Huffman MD, Judd SE, Kissela BM, Lackland DT, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Matchar DB, McGuire DK, Mohler ER, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Willey JZ, Woo D, Yeh RW, Turner MB, American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2015 update: a report from the American Heart Association. Circulation. 2015 Jan 27;131(4):e29-322. PubMed External Web Site Policy

National Heart, Lung, and Blood Institute. Tabulation of NHANES, 1971-1975, 1976-1980, 1988-1994, 1999-2002, 2003-2006, and extrapolation to the U.S. population, 2007 [unpublished].

Naylor M, Brooten D, Jones R, Lavizzo-Mourey R, Mezey M, Pauly M. Comprehensive discharge planning for the hospitalized elderly. A randomized clinical trial. Ann Intern Med. 1994 Jun 15;120(12):999-1006. PubMed External Web Site Policy

Naylor MD, Brooten D, Campbell R, Jacobsen BS, Mezey MD, Pauly MV, Schwartz JS. Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial. JAMA. 1999 Feb 17;281(7):613-20. PubMed External Web Site Policy

Nelson EA, Maruish ME, Axler JL. Effects of discharge planning and compliance with outpatient appointments on readmission rates. Psychiatr Serv. 2000 Jul;51(7):885-9. PubMed External Web Site Policy

van Walraven C, Seth R, Austin PC, Laupacis A. Effect of discharge summary availability during post-discharge visits on hospital readmission. J Gen Intern Med. 2002 Mar;17(3):186-92. PubMed External Web Site Policy

Weiss M, Yakusheva O, Bobay K. Nurse and patient perceptions of discharge readiness in relation to postdischarge utilization. Med Care. 2010 May;48(5):482-6. PubMed External Web Site Policy

Extent of Measure Testing

Assessment of Updated Models

The heart failure (HF) readmission measure estimates hospital-specific 30-day all-cause risk-standardized readmission rates (RSRRs) using a hierarchical logistic regression model. Refer to Section 2 in the original measure documentation for a summary of the measure methodology and model risk-adjustment variables. Refer to prior methodology and technical reports for further details.

The Centers for Medicare & Medicaid Services (CMS) evaluated and validated the performance of the models using July 2013 to June 2016 data for the 2017 reporting period. They also evaluated the stability of the risk-adjustment model over the three-year measurement period by examining the model variable frequencies, model coefficients, and the performance of the risk-adjustment model in each year.

CMS assessed logistic regression model performance in terms of discriminant ability for each year of data and for the three-year combined period. They computed two summary statistics to assess model performance: the predictive ability and the area under the receiver operating characteristic (ROC) curve (c-statistic). CMS also computed between-hospital variance for each year of data and for the three-year combined period. If there were no systematic differences between hospitals, the between-hospital variance would be zero.

The results of these analyses are presented in Section 4.4 of the original measure documentation.

HF Readmission 2017 Model Result

Frequency of HF Model Variables

CMS examined the change in the frequencies of clinical and demographic variables. Frequencies of model variables were stable over the measurement period. The largest changes in the frequencies (those greater than 2% absolute change) include:

  • Increases in Asthma (10.1% to 13.3%), Cardio-respiratory failure and shock (29.9% to 33.7%), Other psychiatric disorders (21.1% to 23.6%), and Renal failure (62.8% to 65.0%)
  • A decrease in Other urinary tract disorders (30.9% to 28.5%)

HF Model Parameters and Performance

Table 4.4.2 in the original measure documentation shows hierarchical logistic regression model variable coefficients by individual year and for the combined three-year dataset. Table 4.4.3 in the original measure documentation shows the risk-adjusted odds ratios (ORs) and 95% confidence intervals for the HF readmission model by individual year and for the combined three-year dataset. Overall, the variable effect sizes were relatively constant across years. In addition, model performance was stable over the three-year time period; the c-statistic remained constant at 0.61.

Refer to the original measure documentation for additional information.

Evidence for Extent of Measure Testing

Yale New Haven Health Services Corporation (YNHHSC), Center for Outcomes Research and Evaluation (CORE). 2017 condition-specific measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2017 Mar. 112 p.

State of Use

Current routine use

Current Use

Collaborative inter-organizational quality improvement

External oversight/Medicare

Monitoring and planning

Pay-for-performance

Pay-for-reporting

Public reporting

Measurement Setting

Hospital Inpatient

Professionals Involved in Delivery of Health Services

Does not apply to this measure (e.g., measure is not provider specific)

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 65 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

Discharges July 1, 2013 through June 30, 2016

Denominator Sampling Frame

Patients associated with provider

Denominator (Index) Event or Characteristic

Clinical Condition

Institutionalization

Patient/Individual (Consumer) Characteristic

Denominator Time Window

Time window precedes index event

Denominator Inclusions/Exclusions

Inclusions
An index admission is the hospitalization to which the readmission outcome is attributed and includes admissions for patients:

  • Having a principal discharge diagnosis of heart failure*
  • Enrolled in Medicare Fee-for-Service (FFS) Part A and Part B for the 12 months prior to the date of admission, and enrolled in Part A during the index admission
  • Aged 65 or over
  • Discharged alive from a non-federal short-term acute care hospital
  • Not transferred to another acute care facility

*International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes used to define the HF cohort for discharges on or after October 1, 2015:

  • I11.0 Hypertensive heart disease with heart failure
  • I13.0 Hypertensive heart and chronic kidney disease with heart failure and stage 1 through stage 4 chronic kidney disease, or unspecified chronic kidney disease
  • I13.2 Hypertensive heart and chronic kidney disease with heart failure and with stage 5 chronic kidney disease, or end stage renal disease
  • I50.1 Left ventricular failure
  • I50.20 Unspecified systolic (congestive) heart failure
  • I50.21 Acute systolic (congestive) heart failure
  • I50.22 Chronic systolic (congestive) heart failure
  • I50.23 Acute on chronic systolic (congestive) heart failure
  • I50.30 Unspecified diastolic (congestive) heart failure
  • I50.31 Acute diastolic (congestive) heart failure
  • I50.32 Chronic diastolic (congestive) heart failure
  • I50.33 Acute on chronic diastolic (congestive) heart failure
  • I50.40 Unspecified combined systolic (congestive) and diastolic (congestive) heart failure
  • I50.41 Acute combined systolic (congestive) and diastolic (congestive) heart failure
  • I50.42 Chronic combined systolic (congestive) and diastolic (congestive) heart failure
  • I50.43 Acute on chronic combined systolic (congestive) and diastolic (congestive) heart failure
  • I50.9 Heart failure, unspecified

Note: International Classification of Diseases, Ninth Revision (ICD-9) code lists for discharges prior to October 1, 2015 can be found in the 2016 Condition-specific Measures Updates and Specifications Report: Hospital-Level 30-Day Risk-Standardized Readmission Measures External Web Site Policy.

Exclusions

  • Without at least 30 days of post-discharge enrollment in Medicare FFS
  • Discharged against medical advice
  • HF admissions within 30 days of discharge from a prior HF index admission
  • With a procedure code for left ventricular assist device (LVAD) implantation or heart transplantation either during the index admission or in the 12 months prior to the index admission

Exclusions/Exceptions

Does not apply to this measure

Numerator Inclusions/Exclusions

Inclusions
The measure assesses unplanned readmissions, from any cause, with 30 days from the date of discharge from an index heart failure (HF) admission.

If a patient has more than one unplanned admission within 30 days of discharge from the index admission, only the first is considered a readmission. The measures assess a dichotomous yes or no outcome of whether each admitted patient has any unplanned readmission within 30 days. If the first readmission after discharge is planned, any subsequent unplanned readmission is not considered in the outcome for that index admission because the unplanned readmission could be related to care provided during the intervening planned readmission rather than during the index admission.

The risk-standardized readmission rate (RSRR) is calculated as the ratio of the number of "predicted" readmissions to the number of "expected" readmissions at a given hospital, multiplied by the national observed readmission rate. For each hospital, the numerator of the ratio is the number of readmissions within 30 days predicted based on the hospital's performance with its observed case-mix.

Note: This outcome measure does not have a traditional numerator and denominator like a core process measure; thus, this field is used to define the outcome.

See the 2017 Condition-specific Measures Updates and Specifications Report: Hospital-level 30-day Risk-standardized Readmission Measures External Web Site Policy for more details.

Exclusions
Admissions identified as planned by the planned readmissions algorithm are not counted as readmissions. The planned readmission algorithm is a set of criteria for classifying readmissions and planned among the general Medicare population using Medicare administrative claims data. The algorithm identified admissions that are typically planned and may occur within 30 days of discharge from the hospital.

The planned readmission algorithm has three fundamental principles:

  1. A few specific, limited types of care are always considered planned (transplant surgery, maintenance chemotherapy/immunotherapy, rehabilitation);
  2. Otherwise, a planned readmission is defined as a non-acute readmission for a scheduled procedure; and
  3. Admissions for acute illness or for complications of care are never planned

The planned readmission algorithm uses a flow chart and four tables of specific procedure categories and discharge diagnosis categories to classify readmissions as planned. The flow chart and tables are available in the 2017 Condition-specific Measures Updates and Specifications Report: Hospital-level 30-day Risk-standardized Readmission Measures External Web Site Policy.

Numerator Search Strategy

Institutionalization

Data Source

Administrative clinical data

Type of Health State

Proxy for Outcome

Instruments Used and/or Associated with the Measure

Planned Readmission Algorithm Version 4.0 (ICD-10) Flowchart

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

Case-mix adjustment

Risk adjustment devised specifically for this measure/condition

Description of Allowance for Patient or Population Factors

Risk-Adjustment Variables

In order to account for differences in case mix among hospitals, the measure adjusts for variables (for example, age, comorbid diseases, and indicators of patient frailty) that are clinically relevant and have relationships with the outcome. For each patient, risk-adjustment variables are obtained from inpatient, outpatient, and physician Medicare administrative claims data extending 12 months prior to, and including, the index admission.

The measure adjusts for case mix differences among hospitals based on the clinical status of the patient at the time of the index admission. Accordingly, only comorbidities that convey information about the patient at that time or in the 12 months prior, and not complications that arise during the course of the hospitalization, are included in the risk adjustment.

The measure does not adjust for socioeconomic status (SES) because the association between SES and health outcomes can be due, in part, to differences in the quality of health care that groups of patients with varying SES receive. The intent is for the measures to adjust for patient demographic and clinical characteristics while illuminating important quality differences. As part of the National Quality Forum (NQF) endorsement process for this measure, the Centers for Medicare & Medicaid Services (CMS) completed analyses for the two-year Sociodemographic Trial Period. Although univariate analyses found that the patient-level observed (unadjusted) readmission rates are higher for dual-eligible patients (for patients living in lower Agency for Healthcare Research and Quality [AHRQ] SES Index census block groups) and African-American patients compared with all other patients, analyses in the context of a multivariable model demonstrated that the effect size of these variables was small, and that the c-statistics for the models are similar with and without the addition of these variables.

Refer to Appendix D of the original measure documentation for the list of comorbidity risk-adjustment variables and the list of complications that are excluded from risk adjustment if they occur only during the index admission.

Standard of Comparison

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

External comparison of time trends

Internal time comparison

Original Title

Hospital-level 30-day RSRR following HF.

Measure Collection Name

National Hospital Inpatient Quality Measures

Measure Set Name

Readmission Measures

Submitter

Centers for Medicare & Medicaid Services - Federal Government Agency [U.S.]

Developer

Centers for Medicare & Medicaid Services - Federal Government Agency [U.S.]

Yale-New Haven Health Services Corporation/Center for Outcomes Research and Evaluation under contract to Centers for Medicare & Medicaid Services - Academic Affiliated Research Institute

Funding Source(s)

Centers for Medicare & Medicaid Services (CMS)

Composition of the Group that Developed the Measure

This measure was developed by a team of experts:

  • Harlan M. Krumholz, MD, SM, Yale School of Medicine
  • Sharon-Lise T. Normand, PhD, Harvard Medical School, Department of Health Care Policy
  • Patricia S. Keenan, PhD, MHS, Centers for Medicare & Medicaid Services (CMS)
  • Zhenqiu Lin, PhD, Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation (YNHHSC/CORE)
  • Elizabeth E. Drye, MD, SM, Yale School of Medicine
  • Kanchana R. Bhat, MPH, YNHHSC/CORE
  • Geoffrey C. Schreiner, BS, YNHHSC/CORE
  • Yongfei Wang, MSc, Yale School of Medicine
  • Joseph Ross, MD, MHS, Mount Sinai School of Medicine
  • Jeremiah Schuur, MD, Brigham & Women's Hospital
  • Brett Stauffer, MD, Baylor Health Care System
  • Susannah Bernheim, MD, MHS, YNHHSC/CORE
  • Andrew Epstein, PhD, MPP, Yale University
  • Jeph Herrin, PhD, Yale School of Medicine
  • Jessica Federer, BS, Bayer HealthCare
  • Jennifer A. Mattera, MPH, Yale University/Yale-New Haven Hospital
  • Yun Wang, PhD, YNHHSC/CORE
  • Gregory Mulvey, BA, University of Connecticut School of Medicine
  • Frederick Masoudi, MD, MSPH, FACC, Denver Health Medical Center
  • Martha Radford, MD, NYU Medical Center
  • John Rumsfeld, MD, PhD, FACC, Denver VA Medical Center
  • John Spertus, MD, MPH, FACC, Mid America Heart Institute and University of Missouri
  • Frank Harrell, PhD, Vanderbilt University Medical Center

Financial Disclosures/Other Potential Conflicts of Interest

None

Endorser

National Quality Forum

NQF Number

0330

Date of Endorsement

2016 Dec 9

Core Quality Measures

Cardiology

Measure Initiative(s)

Hospital Compare

Hospital Inpatient Quality Reporting Program

Adaptation

This measure was not adapted from another source.

Date of Most Current Version in NQMC

2017 Mar

Measure Maintenance

Annual

Date of Next Anticipated Revision

2018 Apr

Measure Status

This is the current release of the measure.

This measure updates a previous version: Specifications manual for national hospital inpatient quality measures, version 5.0b. Centers for Medicare & Medicaid Services (CMS), The Joint Commission; Effective 2015 Oct 1. various p.

Source(s)

Yale New Haven Health Services Corporation (YNHHSC), Center for Outcomes Research and Evaluation (CORE). 2017 condition-specific measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2017 Mar. 112 p.

Measure Availability

Source available from the QualityNet Web site External Web Site Policy.

Check the QualityNet Web site regularly for the most recent version of the specifications manual and for the applicable dates of discharge.

Companion Documents

The following are available:

  • Hospital compare: a quality tool provided by Medicare. [internet]. Washington (DC): U.S. Department of Health and Human Services; [accessed 2017 Oct 30]. Available from the Medicare Web site External Web Site Policy.
  • Yale New Haven Health Services Corporation (YNHHSC), Center for Outcomes Research and Evaluation (CORE). 2017 Medicare hospital quality chartbook. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2017. Available from the Centers for Medicare & Medicaid Services (CMS) Web site External Web Site Policy.
  • Yale New Haven Health Services Corporation (YNHHSC), Center for Outcomes Research and Evaluation (CORE). 2017 condition-specific readmission measures updates and specifications report: supplemental ICD-10 code lists for use with claims for discharges on or after October 1, 2015. Baltimore (MD): Centers for Medicare & Medicaid Services (CMS); 2017. Available from the QualityNet Web site External Web Site Policy.

NQMC Status

This NQMC summary was completed by ECRI Institute on June 23, 2009. The information was verified by the measure developer on December 29, 2009.

This NQMC summary was updated by ECRI Institute on November 8, 2010. The information was verified by the measure developer on December 17, 2010.

This NQMC summary was retrofitted into the new template on May 18, 2011.

This NQMC summary was updated by ECRI Institute on August 23, 2012. The information was verified by the measure developer on October 19, 2012.

This NQMC summary was updated by ECRI Institute on December 4, 2013. The information was verified by the measure developer on January 10, 2014.

This NQMC summary was updated by ECRI Institute on December 5, 2014. The information was verified by the measure developer on January 21, 2015.

This NQMC summary was updated by ECRI Institute on July 21, 2015. The information was verified by the measure developer on September 23, 2015.

This NQMC summary was updated again by ECRI Institute on November 14, 2017. The information was verified by the measure developer on December 12, 2017.

Copyright Statement

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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.