National and institutional quality initiatives provide benchmarks for evaluating the effectiveness of medical care. However, the dramatic growth in the number and type of medical and organizational quality-improvement standards creates a challenge to identify and understand those that most accurately determine quality in cardiac surgery. It is important that surgeons have knowledge and insight into valid, useful indicators for comparison and improvement. We therefore reviewed the medical literature and have identified improvement initiatives focused on cardiac surgery. We discuss the benefits and drawbacks of existing methodologies, such as comprehensive regional and national databases that aid self-evaluation and feedback, volume-based standards as structural indicators, process measurements arising from evidence-based research, and risk-adjusted outcomes. In addition, we discuss the potential of newer methods, such as patient-reported outcomes and composite measurements that combine data from multiple sources.

The concept of healthcare outcome research and quality improvement (QI) was introduced by Codman,1  who in 1918 recommended “End Results Cards” to document and enable a systematic review of outcomes. Donabedian2  later advanced an approach for evaluating healthcare quality from 3 vantage points: structure, process, and outcome. Despite the intuitive desire everywhere to promote quality care, it was not until 1999 that focus on patient safety was reinvigorated, when the Institute of Medicine detailed the prevalence and the lack of awareness of preventable medical errors.3 

Since then, the number of contemporary quality measurements has expanded, so defining which ones truly identify high-quality care is challenging. In this review, we provide a basic framework for surgical QI and discuss examples of existing QI standards, focusing on cardiac surgery.

National Registries and Regional Consortia

Cardiac surgery has a rich history of QI, thanks to pioneers who systematically collected and analyzed performance data for monitoring quality of care, developed follow-up methods, and identified learning opportunities to prompt clinical improvement. The considerable progress during the last 30 years is indicated by the development of large multi-institutional databases.

Veterans Affairs Cardiac Surgery Advisory Group

The first broad monitoring of cardiac surgical quality began with the United States Veterans Administration, now the U.S. Department of Veterans Affairs (VA), in 1971. This prospective monitoring of outcomes in cardiac surgery initially used volume and unadjusted operative mortality data to measure quality. The first comprehensive report of identifiable hospital death rates was published in 1986 by the Health Care Financing Administration.4  These unadjusted death rates were widely criticized for inadequate risk adjustment. Thereafter, the VA developed a risk model for coronary artery bypass grafting (CABG) and for valvular and other surgical procedures, presenting its first report in 1990.5  Since 1987, the VA has continued to analyze mortality and morbidity data to provide feedback to each VA cardiac center.6  In 2009, the VA Surgical Quality Improvement Program was established as a risk-adjusted database intended to serve as a benchmark for quality assurance and improvement in all surgical specialties.

Society of Thoracic Surgeons Registry

The idea of a national database for comparing national outcomes was proposed in 1984. In 1988, an ad hoc committee was entrusted with developing a risk-adjusted national database benchmark for thoracic surgery. In 1990, the software for data storage and risk-stratification models was developed,7  and the Society of Thoracic Surgeons (STS) National Database enrolled 50 participants.8 

The STS Congenital Heart Surgery Database was begun in 1994, and the STS General Thoracic Surgery Database, in 2002. The STS National Database includes these functional task forces: Quality Measurement, Quality Initiatives, Public Reporting, Informatics, and Patient-Reported Outcomes. The database has provided a source for identifying variations in care processes and has stimulated important QI efforts. Cardiac surgical centers submit data to the STS and receive quarterly reports that show their performance in relation to peer institutions nationwide. This risk-adjusted feedback—a comparison with national and regional averages—is important for self-monitoring, for focusing quality initiatives on areas of concern, and as a benchmark for best practice. After 3 decades, the STS National Database is the foundation for measuring performance, QI, public reporting, and research in cardiothoracic surgery.

Statewide and Regional Collaboration

State and regional collaboration for continuous QI in cardiac surgery has a long history. Groups include the Virginia Cardiac Services Quality Initiative,9  the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative,10  the Northern New England Cardiovascular Disease Study Group,11  and the Surgical Care and Outcome Assessment Program in Washington state.12  These surgical QI consortia collect more data than do individual hospitals and have central data registries, thus enabling more meaningful comparison and broader improvement in care.

Once in place, a registry-based system can provide anonymous, risk-adjusted comparative reports that enable surgeons and hospitals to compare their processes of care with others and learn from institutional and surgeon-dependent disparities in care. Systematic sharing of knowledge improves quality by reducing variations in outcomes and processes of care at every participating hospital.

National databases are often criticized because the data reports are perceived to focus more on hospitals than on surgeons. Regional collaboration engenders a strong sense of ownership, including confidence in the quality and value of the data being collected and the content of the subsequent reports. Smaller regional groups can then lead research and quality projects, promoting a joint purpose that may be more difficult to achieve in one national consortium.

Metrics for Evaluating Quality of Care

Donabedian13  described 7 attributes of health care: efficacy, effectiveness, efficiency, equity, optimality, acceptability, and legitimacy. These principles highlight the importance of patient and social preferences when assuring health care. Donabedian's definition of quality of care encompasses structure, process, and outcome.

Structural Measurements

Healthcare structure refers to fixed attributes of the system in which patients receive care. Structural measurements apply to the infrastructure of a healthcare environment, including material resources (such as electronic health records), human resources (such as staff expertise), and organizational format (such as hospitals or clinics).

Case volume is the structural factor evaluated most often. It became an established part of healthcare discussion after a seminal publication that showed an association between higher case volume and lower rates of perioperative mortality.14  The association between hospitals' CABG volume and outcome has been investigated.14,15  Hospital volume was proposed as an indicator of CABG quality by the Center for Medicare & Medicaid Services (CMS). These data are easy to collect and interpret and accompany a belief that “practice makes perfect.”

National Medicare claims data from 1994 through 1999 and the New York Cardiac State registry showed that high-volume hospitals had lower mortality rates than did low-volume hospitals.14  Furthermore, in a review of the STS database of more than 26,000 patients who underwent CABG, procedural volume was modestly associated with outcomes.15 

However, the association of CABG outcomes with volume is weak. An analysis of the National Inpatient Sample revealed that 85% of low-volume and 89% of medium-volume hospital-years showed risk-standardized mortality rates that were statistically lower than or comparable to those expected, and only 6% of high-volume hospital-years had outcomes statistically better than expected.16  Patients experience increased travel and discontinuity in postoperative care.17  Hence, CABG volume might be a surrogate for other process or structural measurements, and adherence to evidence-based metrics is more important than volume alone.17  However, the volume-outcome relationship has been found to be important in other cardiac operations, such as transcatheter valve replacement.18  Evidence shows that this relationship is stronger for procedures that are newer, but that it weakens as technology matures.18  Moreover, individual operator volume might be more important than institutional volume.19 

Process Measurements

Processes, referring to services provided to the patient, are evidence-based best practices. Adhering to them leads to improved care.

Process factors for CABG endorsed by the National Quality Forum (NQF) include perioperative β-blockade; internal mammary artery use; and β-blockade therapy, lipid-lowering therapy, and antiplatelet medications given patients before their discharge from the hospital.20  These data, all collected by STS, are included in a CABG bundle of care, and STS uses them to calculate a CABG Composite Score. Results of extensive studies support the benefit of applying these factors to CABG and to the prevention or progression of coronary atherosclerosis.21,22  These factors are included in the American College of Cardiology/American Heart Association Guidelines for Secondary Prevention for patients with coronary and other atherosclerotic vascular disease.23 

Outcome Measurements

Outcome measurements have been defined as the “measure of the end result of what happens to patients as a consequence of their encounter(s) with the healthcare system,”24  and healthcare institutions therefore seek to develop and apply them.

Risk-Adjusted Mortality

All STS databases define operative mortality as all deaths occurring during the hospitalization in which the operation was performed, even after 30 days, and all deaths occurring after discharge from the hospital through the 30th postoperative day.25  The risk-adjusted observed-to-predicted mortality ratio is frequently used for comparison in STS databases.26 

The STS Predicted Risk of Mortality score has been validated for predicting short-term morbidity and death after typical cardiac operations. However, the STS mortality risk and other risk algorithms, for example the European System for Cardiac Operative Risk Evaluation (EuroSCORE), do not evaluate relevant anatomic factors such as porcelain aorta, a patent internal mammary artery crossing the sternotomy, frailty, or the patient's age. Concomitant with the increase in minimally invasive and transcatheter cardiac interventions, expanding risk scores to include frailty and disability enables incremental prognosis, especially in elderly populations. This is highly relevant in patients considered for transcatheter intervention.27  In addition, all-cause mortality measurements do not provide information about preventable deaths, which are the focus from a QI perspective.28 

Risk-Adjusted Morbidity

In 2007, the STS Quality Measurement Task Force bundled NQF morbidity factors into a separate outcome domain.20  By combining multiple quality indicators for a single operation (for example, risk-adjusted mortality and risk-adjusted morbidity), this approach strengthens the quality signal and improves reliability. Five postoperative complications from the NQF cardiac surgery measurement that are considered as a bundle include stroke, renal insufficiency (defined as a new requirement for dialysis or an increase in serum creatinine level to more than 2 mg/dL), deep sternal wound infection, repeat exploration for any cause, and prolonged intubation or ventilation (>24 hr).29  Complications are associated with reduced survival30,31  and lead to poor quality of life.32  Retrospective analysis of the general risk factors associated with these complications helps to identify patients at risk for prolonged length of stay and readmissions.33  These factors have been the focus in continuous QI projects, which in turn have led to improvement in other quality metrics.34,35 

For meaningful comparison, the risk adjustment incorporates case-mix adjustment for procedural and patient-level factors. However, the calculation depends on accuracy and inclusion of crucial data, which need constant updating.

Readmissions

The rate of early unplanned hospital readmissions after cardiac surgery varies widely, from 8% to 24%. Interest is high in the readmission rate as a quality-care indicator, because some readmissions are avoidable.36,37 

Results of a prospective multicenter study showed an 18.7% overall rate of readmission after CABG; the chief causes were infection, arrhythmia, and volume overload. Almost 80% of these readmissions occurred within 30 days of discharge from the hospital.38  Focusing resources on high-risk patients during this crucial time period and exploring predictive models for readmission risk have potential value.39  However, these models usually do not consider socioeconomic factors40  such as household environment, family support, and cultural norms, all of which affect readmission risk after CABG.41  Of note, not all early unplanned readmissions result from poor care; only about 25% are classified as potentially avoidable.42 

Failure to Rescue

Failure to rescue (FTR) is defined as the rate of death after adverse occurrences, such as postoperative complications.43  Because FTR indicates how a system deals with potentially modifiable complications in a timely and appropriate manner, this measure may reliably reflect quality. In addition, FTR is independently associated with hospital characteristics and is less sensitive to errors in severity adjustment and patient-specific factors that affect other outcome measures, such as morbidity and death.44  In an analysis of a large Medicare population of patients who underwent 6 major cardiac operations that included valve replacement and CABG, complication rates were similar between the best- and worst-performing hospitals, but the hospitals with a higher mortality rate had significantly higher FTR rates, overall and when individual surgical operations were compared.44  A statewide review of 33 hospitals in Michigan showed that low-mortality-rate hospitals had not only low complication rates, but also superior ability to rescue patients from complications when they occurred.45  An analysis of the STS database, intended to calculate FTR rates for 4 complications after CABG (stroke, reoperation, prolonged intubation, and renal failure), revealed similar results, with mortality rates varying directly with FTR rates.46 

The STS model to predict a patient's risk of FTR after CABG considers age, preoperative predicted risk of death, and complications.46  These FTR rates, derived from the STS National Database, can serve as a benchmark for comparing programs.

Quality of Life and Patient-Reported Outcomes

Surgical outcomes are increasingly quantified in terms of the effect that surgery has on patients' daily functional status. Patient-reported outcome measurements (PROM) involve using generic or disease-specific structured questionnaires that convert the patient's own perception of physical and mental health into an objective numerical score. These directly reported scores may provide insight into the patient's response to treatment and thus be a more patient-centered way of comparing the effectiveness of treatments. The NQF and CMS have both endorsed the use of PROM as a performance measurement for QI,47  and the U.S. Food and Drug Administration has recommended that PROM be incorporated into trials of new devices and drug therapies. Indeed, PROM capture is becoming obligatory because payers demand to understand the value of the healthcare that they purchase. This trend has subsequently mandated PROM reporting as a criterion for payment by CMS in transcatheter aortic valve replacement (AVR). The PROM Task Force was established by the STS in April 2016 to incorporate PROM data into the STS National Database. The result is the Patient-Reported Outcomes Measurement Information System (PROMIS).48 

Using PROM in routine patient care, however, presents challenges, including managing resources, expertise, time, and clinical workflow concerns, accurately interpreting data from standardized questionnaires, matching domains to clinical situations, not adjusting for risk, and linking measurements to clinical outcomes.49 

Public Reporting and Surgeon Scorecards

New York was among the first states to begin public reporting of outcomes in cardiac surgery, in 1990.50  In 2010, the STS began voluntary public reporting of outcomes of isolated CABG by using a composite score.29  Subsequently, the initiatives have expanded to include isolated AVR,51  combined AVR and CABG, 52  isolated mitral valve replacement and repair (MVR),53  and combined MVR and CABG.54  Amid these investigations, the STS developed an individual composite measurement, surgeon “report cards,” based on a 3-year period of major surgical procedures, such as CABG and valve replacement.55 

Public reporting initially sounds beneficial. Investigators compared in-hospital and 30-day risk-adjusted mortality rates for CABG from 1994 through 1999 between states and regions of the U.S. that had public reporting or formal QI programs and those that did not, and found benefit when programs existed.56  In-hospital mortality rates for CABG were significantly lower in New York state with its mandated public reporting and in STS programs that voluntarily participated than in programs with other protocols.57  A systematic review and meta-analysis showed a relative risk reduction of 0.85 (95% CI, 0.79–0.92) in the rate of adverse events when public reporting was performed.58 

On the other hand, despite the availability of report cards for surgeons, few cardiologists used them as a basis for referral, and fewer shared these reports with their patients during decision-making.59  Denial of care to high-risk patients is a serious consequence of public reporting.60  When cardiac surgeons in New York state were surveyed, 62% of respondents said that they had declined to perform CABG in at least one high-risk patient after public records of their performance became available.61  In addition, these data can be used to compare the performance of 2 hospitals without considering the case mix.62  Poor interrater reliability between hospital rating systems has been found, as well as poor correlation between private media organizations' findings and the STS adult cardiac surgery database.63  The impact on surgical training is not fully understood.64  Surgeon-specific mortality data inaccurately apply to patients undergoing multidisciplinary care.65 

In summary, public reporting—although imperfect—is a new reality that can help patients make informed decisions regarding their care. However, the data must be meaningful, risk-adjusted, easily understood, and properly interpreted.

Value-Based Care

Consequent to the institution of STS quality metrics and tracking of outcome data, the mortality rate for cardiac surgery has been steadily declining; however, costs have increased proportionately,66  prompting a transition from volume-based to value-based models. Such a change is thought to encourage patient-centered care, which would enable high-quality care at lower cost. Value is defined as health outcomes achieved relative to the costs of care.67  However, the financial charges differ substantially from the actual costs of care delivery, and few institutions have adequate tools to measure value.68  The University of Utah Health Science Center uses a Value-Driven Outcome (VDO) management and reporting tool to help analyze actual system costs and outcomes.69  By using VDO and identifying institution-and patient-specific metrics of “perfect care” and appropriate clinical pathways, the University substantially lowered the cost of CABG and improved its outcomes.70 

Establishing a Culture of Safety and Quality

Supportive leadership,71  emphasis on safety and QI as organizational priorities,72,73  and systemwide QI leadership development are important in making substantive changes.71  Open communication, including sharing results with stakeholders in specifying purpose and strategy74  and being open to concerns and criticisms throughout the process of change,75  is important. Other positive factors are having multidisciplinary teams, using proven methodologies for QI, following evidence-based practice, standardizing care processes, and sharing continuous feedback from collected data.76,77 

Conclusion

The contributions of the cardiothoracic surgeons who established the VA and STS registries in cardiac surgery cannot be overstated, within the medical specialty itself and healthcare nationally. The data generated, questions answered, and programs developed from the STS database use have had substantial impact on the way cardiac surgery is practiced. Although the traditional standards based on morbidity and mortality remain useful, newer concepts such as FTR and PROM are important additions to quality and safety measurement. Finally, a transition from focusing strictly on outcomes to the broader value of care may enable more nuanced QI evaluation in modern health care.

Author contributions: Dr. Sharma conceived, designed, and drafted the manuscript; Drs. Selzman, Glotzbach, and Ryan helped to revise it.

Funding/support: This study was funded by the Division of Cardiothoracic Surgery, University of Utah.

References

1.
Codman
EA.
The classic: a study in hospital efficiency: as demonstrated by the case report of first five years of private hospital [classical article]
.
Clin Orthop Relat Res
2013
;
471
(
6
):
1778
83
.
2.
Donabedian
A.
Evaluating the quality of medical care
.
Milbank Q
2005
;
83
(
4
):
691
729
.
3.
Institute of Medicine (US) Committee on Quality of Health Care in America.
To err is human: building a safer health system
.
Kohn
LT,
Corrigan
JM,
Donaldson
MS,
editors.
Washington (DC)
:
National Academies Press (US)
;
2000
.
4.
Blumberg
MS.
Comments on HCFA hospital death rate statistical outliers
.
Health Care Financing Administration. Health Serv Res
1987
;
21
(
6
):
715
39
.
5.
Grover
FL,
Hammermeister
KE,
Burchfiel
C.
Initial report of the Veterans Administration Preoperative Risk Assessment Study for Cardiac Surgery
.
Ann Thorac Surg
1990
;
50
(
1
):
12
28
.
6.
Grover
FL,
Johnson
RR,
Shroyer
AL,
Marshall
G,
Hammermeister
KE.
The Veterans Affairs Continuous Improvement in Cardiac Surgery study
.
Ann Thorac Surg
1994
;
58
(
6
):
1845
51
.
7.
Clark
RE.
The Society of Thoracic Surgeons National Database status report
.
Ann Thorac Surg
1994
;
57
(
1
):
20
6
.
8.
Anderson
RP.
First publications from the Society of Thoracic Surgeons National Database
.
Ann Thorac Surg
1994
;
57
(
1
):
6
7
.
9.
Speir
AM,
Rich
JB,
Crosby
I,
Fonner
E
Jr.
Regional collaboration as a model for fostering accountability and transforming health care
.
Semin Thorac Cardiovasc Surg
2009
;
21
(
1
):
12
9
.
10.
Prager
RL,
Armenti
FR,
Bassett
JS,
Bell
GF,
Drake
D,
Hanson
EC,
et al.
Cardiac surgeons and the quality movement: the Michigan experience
.
Semin Thorac Cardiovasc Surg
2009
;
21
(
1
):
20
7
.
11.
O'Connor
GT,
Plume
SK,
Olmstead
EM,
Morton
JR,
Maloney
CT,
Nugent
WC,
et al.
A regional intervention to improve the hospital mortality associated with coronary artery bypass graft surgery. The Northern New England Cardiovascular Disease Study Group
.
JAMA
1996
;
275
(
11
):
841
6
.
12.
Flum
DR,
Fisher
N,
Thompson
J,
Marcus-Smith
M,
Florence
M,
Pelligrini
CA.
Washington state's approach to variability in surgical processes/outcomes: Surgical Clinical Outcomes Assessment Program (SCOAP)
.
Surgery
2005
;
138
(
5
):
821
8
.
13.
Eldar
R.
Book review: Avedis Donabedian. An introduction to quality assurance in health care
.
Croat Med J
2003
;
44
(
5
):
655
.
14.
Birkmeyer
JD,
Siewers
AE,
Finlayson
EV,
Stukel
TA,
Lucas
FL,
Batista
I,
et al.
Hospital volume and surgical mortality in the United States
.
N Engl J Med
2002
;
346
(
15
):
1128
37
.
15.
Peterson
ED,
Coombs
LP,
DeLong
ER,
Haan
CK,
Ferguson
TB.
Procedural volume as a marker of quality for CABG surgery
.
JAMA
2004
;
291
(
2
):
195
201
.
16.
Rathore
SS,
Epstein
AJ,
Volpp
KGM,
Krumholz
HM.
Hospital coronary artery bypass graft surgery volume and patient mortality, 1998–2000
.
Ann Surg
2004
;
239
(
1
):
110
7
.
17.
Schwartz
DM,
Fong
ZV,
Warshaw
AL,
Zinner
MJ,
Chang
DC.
The hidden consequences of the volume pledge: “no patient left behind”?
Ann Surg
2017
;
265
(
2
):
273
4
.
18.
Vemulapalli
S,
Carroll
JD,
Mack
MJ,
Li
Z,
Dai
D,
Kosinski
AS,
et al.
Procedural volume and outcomes for transcatheter aortic-valve replacement
.
N Engl J Med
2019
;
380
(
26
):
2541
50
.
19.
Birkmeyer
JD,
Stukel
TA,
Siewers
AE,
Goodney
PP,
Wennberg
DE,
Lucas
FL.
Surgeon volume and operative mortality in the United States
.
N Engl J Med
2003
;
349
(
22
):
2117
27
.
20.
Shahian
DM,
Edwards
FH,
Ferraris
VA,
Haan
CK,
Rich
JB,
Normand
SL,
et al.
Quality measurement in adult cardiac surgery: part 1--conceptual framework and measure selection
.
Ann Thorac Surg
2007
;
83
(
4 Suppl
):
S3
12
.
21.
Denton
TA,
Fonarow
GC,
LaBresh
KA,
Trento
A.
Secondary prevention after coronary bypass: the American Heart Association “Get with the Guidelines” program
.
Ann Thorac Surg
2003
;
75
(
3
):
758
60
.
22.
Ferguson
TB
Jr,
Peterson
ED,
Coombs
LP,
Eiken
MC,
Carey
ML,
Grover
FL,
et al.
Use of continuous quality improvement to increase use of process measures in patients undergoing coronary artery bypass graft surgery: a randomized controlled trial
.
JAMA
2003
;
290
(
1
):
49
56
.
23.
Smith
SC
Jr,
Allen
J,
Blair
SN,
Bonow
RO,
Brass
LM,
Fonarow
GC,
et al.
AHA/ACC guidelines for secondary prevention for patients with coronary and other atherosclerotic vascular disease: 2006 update: endorsed by the National Heart, Lung, and Blood Institute
.
Circulation
2006
;
113
(
19
):
2363
72
.
24.
Krousel-Wood
MA
.
Outcomes assessment and performance improvement: measurements and methodologies that matter in mental healthcare
.
In:
Rodenhauser
P,
editor.
Mental health care administration: a guide for practitioners
.
Ann Arbor (MI)
:
University of Michigan Press
;
2000
. p.
233
.
25.
Jacobs
JP,
Mavroudis
C,
Jacobs
ML,
Maruszewski
B,
Tchervenko
CI,
Lacour-Gayet
FG,
et al.
What is operative mortality? Defining death in a surgical registry database: a report of the STS Congenital Database Taskforce and the Joint EACTS-STS Congenital Database Committee
.
Ann Thorac Surg
2006
;
81
(
5
):
1937
41
.
26.
Orr
RK,
Maini
BS,
Sottile
FD,
Dumas
EM,
O'Mara
P.
A comparison of four severity-adjusted models to predict mortality after coronary artery bypass graft surgery
.
Arch Surg
1995
;
130
(
3
):
301
6
.
27.
Afialo
J,
Mottillo
S,
Eisenberg
MJ,
Alexander
KP,
Noiseux
N,
Perrault
LP,
et al.
Addition of frailty and disability to cardiac surgery risk scores identifies elderly patients at high risk of mortality or major morbidity
.
Circ Cardiovasc Qual Outcomes
2012
;
5
(
2
):
222
8
.
28.
Guru
V,
Tu
JV,
Etchells
E,
Anderson
GM,
Naylor
CD,
Novick
RJ,
et al.
Relationship between preventability of death after coronary artery bypass graft surgery and all-cause risk-adjusted mortality rates
.
Circulation
2008
;
117
(
23
):
2969
76
.
29.
O'Brien
SM,
Shahian
DM,
DeLong
ER,
Normand
SL,
Edwards
FH,
Ferraris
VA,
et al.
Quality measurement in adult cardiac surgery: part 2--statistical considerations in composite measure scoring and provider rating
.
Ann Thorac Surg
2007
;
83
(
4 Suppl
):
S13
26
.
30.
Khuri
SF,
Henderson
WG,
DePalma
RG,
Mosca
C,
Healey
NA,
Kumbhani
DJ.
Determinants of long-term survival after major surgery and the adverse effect of postoperative complications
.
Ann Surg
2005
;
242
(
3
):
326
43
.
31.
Rahmanian
PB,
Kroner
A,
Langebartels
G,
Ozel
O,
Wippermann
J,
Wahlers
T.
Impact of major non-cardiac complications on outcome following cardiac surgery procedures: logistic regression analysis in a very recent patient cohort
.
Interact Cardiovasc Thorac Surg
2013
;
17
(
2
):
319
27
.
32.
Pappalardo
F,
Franco
A,
Landoni
G,
Cardano
P,
Zangrillo
A,
Alfieri
O.
Long-term outcome and quality of life of patients requiring prolonged mechanical ventilation after cardiac surgery
.
Eur J Cardiothorac Surg
2004
;
25
(
4
):
548
52
.
33.
Maniar
HS,
Bell
JM,
Moon
MR,
Meyers
BF,
Marsala
J,
Lawton
JS,
Damiano
RJ
Jr.
Prospective evaluation of patients readmitted after cardiac surgery: analysis of outcomes and identification of risk factors
.
J Thorac Cardiovasc Surg
2014
;
147
(
3
):
1013
8
.
34.
Griffith
D,
Hampton
D,
Switzer
M,
Daniels
J.
Facilitating the recovery of open heart surgery patients through quality improvement efforts and CareMAP implementation
.
Am J Crit Care
1996
;
5
(
5
):
346
52
.
35.
Stamou
SC,
Camp
SL,
Reames
MK,
Skipper
E,
Stiegel
RM,
Nussbaum
M,
et al.
Continuous quality improvement program and major morbidity after cardiac surgery
.
Am J Cardiol
2008
;
102
(
6
):
772
7
.
36.
D'Agostino
RS,
Jacobson
J,
Clarkson
M,
Svensson
LG,
Williamson
C,
Shahian
DM.
Readmission after cardiac operations: prevalence, patterns, and predisposing patterns
.
J Thorac Cardiovasc Surg
1999
;
118
(
5
):
823
32
.
37.
Ferraris
VA,
Ferraris
SP,
Harmon
RC,
Evans
BD.
Risk factors for early hospital readmission after cardiac operations
.
J Thorac Cardiovasc Surg
2001
;
122
(
2
):
278
86
.
38.
Iribarne
A,
Chang
H,
Alexander
JH,
Gillinov
AM,
Moquete
E,
Puskas
JD,
et al.
Readmissions after cardiac surgery: experience of the National Institutes of Health/Canadian Institutes of Health research cardiothoracic surgical trials network
.
Ann Thorac Surg
2014
;
98
(
4
):
1274
80
.
39.
Currie
KB,
Lancey
R.
A predictive model for readmission within 30 days after coronary artery bypass grafting
.
J Am Coll Surg
2011
;
213
(
3 Suppl
):
S107
.
40.
Shahian
DM,
He
X,
O'Brien
SM,
Grover
FL,
Jacobs
JP,
Edwards
EH,
et al.
Development of a clinical registry-based 30-day readmission measure for coronary artery bypass grafting
.
Circulation
2014
;
130
(
5
):
399
409
.
41.
Tsai
TC,
Joynt
KE,
Orav
EJ,
Gawande
AA,
Jha
AK.
Variation in surgical readmission rates and quality of hospital care
.
N Engl J Med
2013
;
369
(
12
):
1134
42
.
42.
van Walraven
C,
Bennett
C,
Jennings
A,
Austin
PC,
Forster
AJ.
Proportion of hospital readmissions deemed avoidable: a systematic review
.
CMAJ
2011
;
183
(
7
):
E391
E402
.
43.
Silber
JH,
Williams
SV,
Krakauer
H,
Schwartz
JS.
Hospital and patient characteristics associated with death after surgery. A study of adverse occurrence and failure to rescue
.
Med Care
1992
;
30
(
7
):
615
29
.
44.
Ghaferi
AA,
Birkmeyer
JD,
Dimick
JB.
Complications, failure to rescue, and mortality with major inpatient surgery in Medicare patients
.
Ann Surg
2009
;
250
(
6
):
1029
34
.
45.
Reddy
HG,
Shih
T,
Englesbe
MJ,
Shannon
FL,
Theurer
PF,
Herbert
MA,
et al.
Analyzing “failure to rescue”: is this an opportunity for outcome improvement in cardiac surgery?
Ann Thorac Surg
2013
;
95
(
6
):
1976
81
.
46.
Edwards
FH,
Ferraris
VA,
Kurlansky
PA,
Lodell
KW,
He
X,
O'Brien
SM,
et al.
Failure to rescue rates after coronary artery bypass grafting: an analysis from the Society of Thoracic Surgeons Adult Cardiac Surgery Database
.
Ann Thorac Surg
2016
;
102
(
2
):
458
64
.
47.
Centers for Medicare and Medicaid Services.
Physician quality reporting system. HeathIT.gov website
.
48.
Health Measures PROMIS: dynamic tools to measure health outcomes from the patient perspective
.
Available from: http://www.nihpromis.org/.
49.
Gensheimer
SG,
Wu
AW,
Snyder
CF,
PRO-HER Users' Guide Steering Group;
PRO-HER Users' Guide Working Group.
Oh, the places we'll go: patient-reported outcomes and electronic health record
.
Patient
2018
;
11
(
6
):
591
8
.
50.
Altman
LK.
Heart-surgery rates decline in New York
.
New York Times
.
December
5
,
1990
:
B10
.
Available from: https://nyti.ms/29wDYkc.
51.
Shahian
DM,
He
X,
Jacobs
JP,
Rankin
JS,
Welke
KF,
Filardo
G,
et al.
The Society of Thoracic Surgeons isolated aortic valve replacement (AVR) composite score: a report of the STS Quality Measurement Task Force
.
Ann Thorac Surg
2012
;
94
(
6
):
2166
71
.
52.
Shahian
DM,
He
X,
Jacobs
JP,
Rankin
JS,
Welke
KF,
Edwards
FH,
et al.
The STS AVR+CABG composite score: a report of the STS Quality Measurement Task Force
.
Ann Thorac Surg
2014
;
97
(
5
):
1604
9
.
53.
Badhwar
V,
Rankin
JS,
He
X,
Jacobs
JP,
Gammie
JS,
Furnary
AP,
et al.
The Society of Thoracic Surgeons Mitral Repair/Replacement Composite Score: a report of the Society of Thoracic Surgeons Quality Measurement Task Force
.
Ann Thorac Surg
2016
;
101
(
6
):
2265
71
.
54.
Rankin
JS,
Badhwar
V,
He
X,
Jacobs
JP,
Gammie
JS,
Furnary
AP,
et al.
The Society of Thoracic Surgeons Mitral Valve Repair/Replacement Plus Coronary Artery Bypass Grafting Composite Score: a report of the Society of Thoracic Surgeons Quality Measurement Task Force
.
Ann Thorac Surg
2017
;
103
(
5
):
1475
81
.
55.
Shahian
DM,
He
X,
Jacobs
JP,
Kurlansky
PA,
Badhwar
V,
Cleveland
JC
Jr,
et al.
The Society of Thoracic Surgeons Composite Measure of Individual Surgeon Performance for Adult Cardiac Surgery: a report of the Society of Thoracic Surgeons Quality Measurement Task Force
.
Ann Thorac Surg
2015
;
100
(
4
):
1315
25
.
56.
Hannan
EL,
Sarrazin
MS,
Doran
DR,
Rosenthal
GE.
Provider profiling and quality improvement efforts in coronary artery bypass graft surgery: the effect on short-term mortality among Medicare beneficiaries
.
Med Care
2003
;
41
(
10
):
1164
72
.
57.
Shahian
DM,
Grover
FL,
Prager
RL,
Edwards
FH,
Filardo
G,
O'Brien
SM,
et al.
The Society of Thoracic Surgeons voluntary public reporting initiative: the first 4 years
.
Ann Surg
2015
;
262
(
3
):
526
35
.
58.
Campanella
P,
Vukovic
V,
Parente
P,
Sulejmani
A,
Ricciardi
W,
Specchia
ML.
The impact of public reporting on clinical outcomes: a systematic review and meta-analysis
.
BMC Health Serv Res
2016
;
16
:
296
.
59.
Thourani
VH,
Sarin
EL.
Influence of cardiac surgeon report cards on patient referral by cardiologists in New York state after 20 years of public reporting
.
Circ Cardiovasc Qual Outcomes
2013
;
6
(
6
):
617
8
.
60.
Radford
MJ.
Does public reporting improve care?
J Am Coll Cardiol
2016
;
67
(
8
):
973
5
.
61.
Burack
JH,
Impellizzeri
P,
Homel
P,
Cunningham
JN
Jr.
Public reporting of surgical mortality: a survey of New York State cardiothoracic surgeons
.
Ann Thorac Surg
1999
;
68
(
4
):
1195
202
.
62.
Shahian
DM,
Normand
SL.
Comparison of “risk-adjusted” hospital outcomes
.
Circulation
2008
;
117
(
15
):
1955
63
.
63.
Raghuram
AC,
Dasari
TK,
Chou
B,
Balla
S,
Navarro
SM,
Shah
RM,
et al.
Confusion instead of clarity: publicly reported cardiac surgery ratings for coronary artery bypass grafting and aortic valve replacement
.
J Am Coll Surg
2019
;
228
(
2
):
180
7
.
64.
Khan
OA,
Iyengar
S,
Pontefract
DE,
Rogers
V,
Ohri
SK,
Livesey
SA.
Impact of surgeon-specific data reporting on surgical training
.
Ann R Coll Surg Engl
2007
;
89
(
8
):
796
8
.
65.
Walker
K,
Neuberger
J,
Groene
O,
Cromwell
DA,
van der Meulen
J.
Public reporting of surgeon outcomes: low numbers of procedures lead to false complacency [published erratum appears in Lancet 2013;382(9905):1628]
.
Lancet
2013
;
382
(
9905
):
1674
7
.
66.
Osnabrugge
RL,
Speir
AM,
Head
SJ,
Jones
PG,
Ailawadi
G,
Fonner
CE,
et al.
Prediction of costs and length of stay in coronary artery bypass grafting
.
Ann Thorac Surg
2014
;
98
(
4
):
1286
93
.
67.
Bradley
SM,
Strauss
CE,
Ho
PM.
Value in cardiovascular care
.
Heart
2017
;
103
(
16
):
1238
43
.
68.
Kilic
A,
Shah
AS,
Conte
JV,
Mandal
K,
Baumgartner
WA,
Cameron
DE,
Whitman
GJ.
Understanding variability in hospital-specific costs of coronary artery bypass grafting represents an opportunity for standardizing care and improving resource use
.
J Thorac Cardiovasc Surg
2014
;
147
(
1
):
109
15
.
69.
Kawamoto
K,
Martin
CJ,
Williams
K,
Tu
MC,
Park
CG,
Hunter
C,
et al.
Value Driven Outcomes (VDO): a pragmatic, modular, and extensible software framework for understanding and improving health care costs and outcomes
.
J Am Med Inform Assoc
2015
;
22
(
1
):
223
35
.
70.
Glotzbach
JP,
Sharma
V,
Tonna
JE,
Pettit
JC,
McKellar
SH,
Eckhauser
AW,
et al.
Value-driven cardiac surgery: achieving “perfect care” after coronary artery bypass grafting
.
J Thorac Cardiovasc Surg
2018
;
156
(
4
):
1436
48.e2
.
71.
Willeumier
D.
Advocate health care: a systemwide approach to quality and safety
.
Jt Comm J Qual Saf
2004
;
30
(
10
):
559
66
.
72.
Leape
LL,
Rogers
G,
Hanna
D,
Griswold
P,
Federico
F,
Fenn
CA,
et al.
Developing and implementing new safe practices: voluntary adoption through statewide collaboratives
.
Qual Saf Health Care
2006
;
15
(
4
):
289
95
.
73.
Smith
DS,
Haig
K.
Reduction of adverse drug events and medication errors in a community hospital setting
.
Nurs Clin North Am
2005
;
40
(
1
):
25
32
.
74.
Jimmerson
C,
Weber
D,
Sobek
DK
2nd.
Reducing waste and errors: piloting lean principles at Intermountain Healthcare
.
Jt Comm J Qual Patient Saf
2005
;
31
(
5
):
249
57
.
75.
Weir
VL.
Best-practice protocols: preventing adverse drug events
.
Nurs Manage
2005
;
36
(
9
):
24
30
.
76.
Berwick
DM.
Continuous improvement as an ideal in health care
.
N Engl J Med
1989
;
320
(
1
):
53
6
.
77.
Hughes
RG.
Tools and strategies for quality improvement and patient safety
.
In:
Patient safety and quality: an evidence-based handbook for nurses
.
Rockville (MD)
:
Agency for Healthcare Research and Quality (US)
;
2008
:
chap 44.