An Analysis of Methodologies That Can Be Used to Validate if a Perioperative Surgical Home Improves the Patient-centeredness, Evidence-based Practice, Quality, Safety, and Value of Patient Care
Vetter, Thomas R. M.D., M.P.H.*; Ivankova, Nataliya V. Ph.D.†; Goeddel, Lee A. M.D., M.P.H.‡; McGwin, Gerald Jr. M.S., Ph.D.§; Pittet, Jean-Francois M.D.‖; for the UAB Perioperative Surgical Home Group
Approximately 80 million inpatient and outpatient surgeries are performed annually in the United States. Widely variable and fragmented perioperative care exposes these surgical patients to lapses in expected standard of care, increases the chance for operational mistakes and accidents, results in unnecessary and potentially detrimental care, needlessly drives up costs, and adversely affects the patient healthcare experience. The American Society of Anesthesiologists and other stakeholders have proposed a more comprehensive model of perioperative care, the Perioperative Surgical Home (PSH), to improve current care of surgical patients and to meet the future demands of increased volume, quality standards, and patient-centered care. To justify implementation of this new healthcare delivery model to surgical colleagues, administrators, and patients and maintain the integrity of evidenced-based practice, the nascent PSH model must be rigorously evaluated. This special article proposes comparative effectiveness research aims or objectives and an optimal study design for the novel PSH model.
AN estimated 30 million major inpatient surgeries1
and 50 million ambulatory outpatient surgeries3
are performed annually in the United States. Widely variable and fragmented perioperative care plans, undertaken by different practitioners, currently expose these surgical patients to lapses in expected standard of care, increase the chance for operational mistakes and accidents, result in unnecessary and potentially detrimental care, needlessly drive up costs, and adversely affect the patient healthcare experience.5–9
To address this fragmentation and depersonalization of surgical care, new approaches are needed that are more efficient and less costly yet emphasize the patient as the center of care.8–10
The medical community and public are increasingly embracing shared decision-making, a process by which healthcare choices are made jointly by the practitioner and patient.11–13
Akin to the Medical Home in outpatient primary care,10
the Surgical Home has been proposed by the American Society of Anesthesiologists (ASA)#
and others as an innovative, patient-centered, surgical continuity of care model that fully incorporates shared decision-making.8
Like all areas of health care, the specialty of anesthesiology is also facing strong economic pressures which require a broader competitive strategy.8
Hospital-physician collaborations continue to evolve to include greater economic integration, including major financial gain and risk sharing.20
Furthermore, value-based purchasing of health care,22–24
pay for performance,25
and a changing payment paradigm that includes bundled payments or accountable care arrangements27
are all powerful motivators to improve the effectiveness and efficiency of patient care via
a surgical home type model.8
There will very likely be multiple
future variations of the surgical home concept that may work effectively, depending on institutional infrastructure and yet to be identified external forces. However, at its essence, the Perioperative Surgical Home (PSH) model integrates the three well recognized, but heretofore frequently fragmented, preoperative, intraoperative, and postoperative phases of patient care (fig. 1
The PSH seeks to more intentionally engage the patient, family, clinicians, and other stakeholders, thereby enhancing the ability of patients to actively participate in shared decision-making concerning their surgical care. Fundamentally, the anesthesiologist-intensivist serves as the surgical patient’s “perioperativist”—the primary physician who provides seamless continuity of current best practices of care—while actively involving the patient, family, and other healthcare providers.8
In the PSH model, an anesthesiologist-intensivist works with a nurse practitioner to provide, coordinate, and integrate pre-, intra-, and postoperative care. This anesthesiology-based team is readily available throughout the perioperative continuum to address the patient’s questions or concerns about their care. This team also oversees the patient’s transitional plans on hospital discharge—initiated, however, preoperatively. Specifically, tenets of the Institute for Healthcare Improvement’s “How-to Guide: Improving Transitions from the Hospital to Home Health Care to Reduce Avoidable Rehospitalizations” are translated into the perioperative setting (fig. 2
A key element of this perioperative Transitional Care Model is a nurse clinician (or medical social worker) serving as the patient’s “perioperative transitions coach.”29
The implementation of such a PSH model will likely also be an evolutionary process that varies across local practice environments. Because a given PSH evolves from the existing local model of care, different institutions may well adopt different elements at different rates, with variable emphasis on specific surgical populations (e.g., total joint replacement) or specific portions of the perioperative continuum of care (e.g., preoperative medical optimization and patient education and counseling). Although this article examines more complex surgical procedures requiring postoperative admission, the proposed outcomes and methodology are applicable to outpatient surgeries, endoscopic procedures, and routine obstetrical care—high-volume areas in which anesthesiologists can also provide needed greater integration and coordination of care.
The Institute of Medicine (IOM) has defined comparative effectiveness research (CER) as the “generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care.”31
In 2009, the IOM established a national CER agenda.33
“Health Care Delivery Systems” was the highest ranked IOM CER priority.31
The proposed PSH model falls squarely in this highest ranked IOM CER category.
In obligatorily assessing whether a new PSH model is superior to current conventional surgical care, four specific, pertinent CER aims or objectives include whether the PSH results in (1) enhanced patient-centered care of the surgical patient; (2) greater clinician adherence to evidence-based patient management guidelines; (3) improved quality and safety of perioperative care; and (4) reduced overall cost and thus enhanced value. The other fundamental question is what is the optimal study design for the PSH model? Most importantly, such an ability to define, obtain, and analyze outcomes in a rigorous way will be essential to test the variety of surgical home models that will likely be trialed in the next few years as surgical paradigms evolve—especially in response to economic influences.
Patient-centered Care of the Surgical Patient
In assessing whether the PSH model results in greater patient-centered care of the surgical patient, initial primary patient-reported outcomes would include conventional perioperative (1) pain intensity; (2) health-related quality of life; (3) quality of recovery; and (4) patient satisfaction.
The assessment of pain intensity is essential for clinical trials and effective pain management. Acute pain can be measured, both at rest (important for comfort) and during movement (important for function and risk of postoperative complications), using a valid and reliable unidimensional self-reported pain intensity scale.34
Health-related quality of life has become a well-accepted primary outcome measure in clinical studies, including in surgical patients.35–40
Quality of recovery, when assessed in a patient-centered manner, provides an additional important information in postsurgical patients.41
If measured with a robustly developed and subsequently validated instrument, patient satisfaction is a standard indicator of the quality of delivered health care and can contribute to a comprehensive evaluation of the classic triad of structure, process, and outcome, including with existing and new perioperative services.43–46
Patient satisfaction is most validly measured sequentially and in close proximity to the delivered health care (i.e.
, the patient’s surgical experience).46
This would ideally involve measurements before or at the time of hospital admission, during the postoperative phase on the day of hospital discharge, and at 28 days postdischarge. Interviewing the same patients three times during their surgical care continuum will provide them with the opportunity to express their expectations of perioperative outcomes, discuss benefits and risks of available treatment options, identify patients’ unmet needs, and explore the relevance of the measured outcomes.47
Undergoing a major surgical procedure is often one the most stressful events in an individual’s life. An independent, well-informed, and proactive person can become a dependent, passive, and bewildered patient in the very foreign and often ironically hostile healthcare environment. Thus a very appropriate question posed by many surgical patients is “What can I do to improve the outcomes that are most important to me?” This questions speaks directly to the fundamental tenet of patient–stakeholder engagement—specifically, how to define it and how to measure it.
According to the Agency for Healthcare Research and Quality, stakeholders are “persons or groups who have a vested interest in the clinical decision and the evidence that supports that decision.48
In the PSH model, stakeholders may include surgical patients, their families, and other lay caregivers, as well as anesthesiologists, surgeons, nurses, hospital administrators, and other professional healthcare providers. All these stakeholder groups, regardless of varied professional and personal interest in specific outcomes of patient’s perioperative surgical care, will likely have a vested interest in patient-centered health care and its associated outcomes. With the creation of the Patient-Centered Outcomes Research Institute by the Patient Protection and Affordable Care Act of 2010, CER has effectively been renamed “patient-centered outcomes research”—underscoring the goals and importance of person-centered medicine.49
It seems important that stakeholder engagement in the evaluation of the PSH model implementation follows the key principles of community-based participatory research.50
These principles emphasize stakeholder participation, equal power, and joint planning.51
Participation underscores the involvement of community members (e.g.
, surgical patients, their family members, and other lay patient caregivers) in a specific project with shared ownership, from setting project objectives to disseminating project outcomes. Performing research in collaboration with those affected by the issue (e.g.
, the perioperative patient experience) for the purpose of taking action or making change increases the likelihood that research findings will be accepted and used.52
Surgical patients and other invested stakeholders would ideally be involved in all phases of a PSH model—from the early stages of conceptualization and inception, to design and refinement of assessment instruments, data collection and analysis, and evaluation of project outcomes and related health benefits. Such active participation and collaboration will promote capacity building among all partners and will create an empowering environment for all stakeholders to equally contribute to the decision-making and control over all stages of the healthcare delivery process and the assessment of risks and benefits of the PSH model.53
A set of strategies have been recommended to ensure stakeholders’ consistent engagement with the project and active dissemination and implementation of the results (table 1
Assessment of stakeholders’ views can best be achieved using a mixed-method (integrated qualitative and quantitative) approach, as set forth in the “Best Practices for Mixed Methods Research in Health Sciences” commissioned by National Institutes of Health Office of Behavioral and Social Sciences Research.56
Collecting and meaningfully integrating data from qualitative narratives and quantitative measures allow exploring the views of all engaged stakeholders from multiple perspectives and in various phases in the project implementation and evaluation. For example, patients’ and caregivers’ experiences with provided health care can be explored by individual interviews at several stages in the perioperative care process to understand patients’ needs and expectations for preoperative, intraoperative, and postoperative patient care, to assess the relevance of the above a priori
chosen conventional patient-centered outcomes, and to enhance patients’ engagement in shared decision making about their health care. Similarly, interviews of focus groups with professional healthcare providers can help solicit their input into the effectiveness of the PSH model and to enhance the establishment of outcomes that are patient-centered and that are tailored to patients’ personal characteristics, conditions, preferences, and needs.
Mixed-method approach would be particularly useful in developing new assessment tools to measure patient satisfaction with perioperative care that are tailored to their personal (individual) characteristics, conditions, preferences, and needs.10
Applying mixed methods to assessing patient satisfaction with perioperative health care entails an initial qualitative exploration of stakeholders’ views through patient interviews and/or focus groups and using the emerging themes to inform the subsequent development, testing, and validation of the quantitative questionnaire by administering it to a large sample. The procedural steps have been defined for developing a satisfaction instrument grounded in the views of surgical patients using a mixed-method approach (fig. 3
Finally, integrated qualitative and quantitative results from different stages in the PSH model implementation can be used for a summative evaluation of the model and an assessment of its effectiveness by patients, various healthcare providers, and other stakeholders.57
Clinician Adherence to Evidence-based Patient Management Guidelines
In assessing whether the PSH model results in greater clinician adherence to evidence-based patient management guidelines
and thus provision of current best practices, examples include those set forth by: (1) the American College of Chest Physicians for the perioperative management of antithrombotic therapy and the prevention of thrombosis in patients who require an elective surgery or procedure;58
(2) the Heart Rhythm Society/ASA on the perioperative management of patients with implantable defibrillators, pacemakers, and arrhythmia monitors;59
(3) the ASA for the perioperative management of acute pain;60
(4) the ASA for the perioperative management of patients with obstructive sleep apnea;61
(5) the Society of Ambulatory Anesthesia for the for the management of postoperative nausea and vomiting;62
(6) the American College of Cardiology/American Heart Association for perioperative cardiovascular evaluation and care for noncardiac surgery, including perioperative β-blockade;63
(7) the European Society of Cardiology for the preoperative cardiac risk assessment and perioperative cardiac management in noncardiac surgery;65
and (8) the Society for Advancement of Blood Management,**
the Network for Advancement of Transfusion Alternatives,66
and the American Association of Blood Banks68
for perioperative anemia and blood management.
A patient-centered approach to surgical patient blood management has been advocated by the ASA.69
Associated concerted efforts may thus be better termed, patient-centered blood management
to reflect the increasing emphasis on patient-centeredness in other areas of medicine and the consumer-perspective of health care.10
Additional patient-centered outcomes in the PSH model would thus, for example, be those associated with state-of-the-art patient-centered blood management and include (1) the immediate preoperative complete cell blood count; (2) the postoperative complete cell blood count at the time of hospital discharge; (3) the total number of units of packed erythrocyte units administered intraoperatively, postoperatively during the initial surgical hospitalization, and during the first 30 days after hospital discharge; and (3) clinician adherence to recently published guidelines on blood transfusion criteria (i.e.
Quality and Safety of Perioperative Care
In assessing whether the PSH model results in improved overall quality and safety of perioperative care, additional primary outcomes would include (1) perioperative mortality; (2) perioperative complications; (3) failure-to-rescue (FTR) rate; (4) a subset of current national performance metrics; (5) admission rate to an intensive care unit; (6) readmission rate to an intensive care unit from a regular inpatient unit; (7) length of stay in an intensive care unit and in the hospital; (8) readmission rate to the hospital after discharge home; and (9) not-present-on-admission diagnostic codes (International Classification of Diseases) that are indicative of potential complications. Several of these quality and safety outcomes also have current and future reimbursement and thus fiscal ramifications.
Reported surgical death rates vary widely across hospitals in the United States, from 3.5% in very-low-mortality hospitals to 6.9% in very-high-mortality hospitals.72
, Centers for Medicare and Medicaid Services), regulators (e.g.
, The Joint Commission), and providers are currently focusing on ways of reducing postoperative complications, which may be one approach to reducing this observed variability in surgical mortality. However, based on Medicare administrative beneficiary data from 2005 to 2006, complication rates in patients undergoing major inpatient surgical procedures were similar at the worst and best hospitals (36.4 vs.
32.7%), but the worst hospitals had mortality rates 2.5-fold higher than the best hospitals.73
The above reported administrative data72
may have suffered from misclassification bias away from the null due to larger and well-endowed hospitals more accurately reporting adverse outcomes, as well as existing financial incentives to collect and to report multiple comorbidities.
One plausible explanation for this disparate mortality is FTR. FTR was first defined in 1992 by Silber et al.74
as hospital deaths after adverse events such as postsurgical complications.75
In 2001, IOM identified FTR as one of the key areas for improvement in patient safety.75
Contributors to FTR have been broadly categorized as the lack of a timely
response (prompt recognition of the complication) and an appropriate
response (correct management and treatment).72
In the above Medicare surgical cohort, overall FTR rates were higher (16.7 vs.
6.8%) at the worst compared with the best hospitals—but differed by as much as 4.0 versus
50.8% for major abdominal surgery.73
The highly coordinated and integrated care provided by the PSH model should allow for a timelier and more appropriate response to patient physiologic derangement, thus reducing the FTR rate, major complications, and associated surgical morbidity and mortality.72
Numerous healthcare quality and safety metrics have been put forth by various healthcare agencies, including (1) the Appropriate Care Measures and Hospital-Acquired Conditions from the Centers for Medicare and Medicaid Services;77
(2) the interventions and outcomes from the Surgical Care Improvement Project;78
(3) major surgical complications from the American College of Surgeons National Surgical Quality Improvement Program;80
(4) the National Patient Safety Goals from The Joint Commission;81
and (5) the Patient Safety Indicators from the Agency for Healthcare Research.82
The majority of the Centers for Medicare and Medicaid Services Appropriate Care Measures are not applicable to our proposed perioperative patient care model. The effect of Surgical Care Improvement Project adherence in lowering surgical site infection rates at the patient or hospital level has recently been challenged.83–85
The National Patient Safety Goals from The Joint Commission lack adequate surgical specificity.
Therefore, for the purposes of comparing the quality, safety, effectiveness, and efficiency of perioperative care delivered in the PSH model versus
current typical surgical care, a combination of conventional perioperative complications, Agency for Healthcare Research and Quality Patient Safety Indicators, Centers for Medicare and Medicaid Services Hospital-Acquired Conditions, and elements from Surgical Care Improvement Project and National Surgical Quality Improvement Program (table 2
) appear to be the most appropriate quality and safety variables in assessing the effect of the PSH model.
Many of the above-mentioned perioperative outcomes data and performance metrics are currently being collected by individual hospitals in their efforts to meet various national benchmarking, pay-for-performance, and value-based purchasing payment criteria.77
However, national quality and safety registries are other valid sources for anesthesia care–related data and might prove less costly and redundant than specific institutional research efforts. Registry data may be an important CER pathway going forward—especially for a timely, pragmatic assessment of the efficacy of the PSH. The Anesthesia Quality Institute and its National Anesthesia Clinical Outcomes Registry,††
which are developed and maintained with a major support from the ASA, is a prime example of such a well-established, consensus-based national quality and safety registry. The Michigan Surgical Quality Collaborative is another such national registry.‡‡
Of note, there is a common tension between locally developed (“homegrown”) quality and safety measures versus
the use of national metrics and attendant benchmarking. Such locally developed metrics may more accurately reflect the surgical population being studied and the practically available information technology infrastructure. Multicenter collaboratives and national quality and safety registries (e.g.
, Anesthesia Quality Institute) can facilitate creation and adoption of common definitions.86
To aggregate complications and to stratify them by severity, the revised Clavien-Dindo Classification of Surgical Complications (table 3
which grades surgical complications (I, II, IIIa, IIIb, IVa, IVb, and V) based on the therapy used to treat the complication, could plausibly also be applied in assessing the effect of the PSH model. This classification system can account for very serious adverse events (e.g.
, anaphylaxis, malignant hyperthermia, and intraoperative cardiac arrest) that might not result in a permanent adverse outcome but nonetheless should be captured. The Clavien-Dindo Classification System has been successfully applied in gastrointestinal surgery,89
Reduced Cost and Enhanced Value
In assessing whether the PSH model results in reduced overall cost and thus enhanced value, potential outcomes include (1) total direct medical costs of the surgical procedure, anesthesia services, and related hospitalization(s); (2) the rate of surgical case delays and surgical case cancellations on the day of surgery; (3) the duration of specific surgical procedures; (4) the duration of postanesthesia care unit stay; and (5) other pertinent operational and fiscal measures (e.g., unplanned postoutpatient procedure admission, allogeneic blood transfusion rates for cardiac surgery).
Aggregate healthcare expenditures are projected to increase in the United States from $5,572 per capita (15.9% of gross domestic product) in 2005 to $8,832 per capita (2005 dollars) in 2025 (25.2% of U.S. gross domestic product).96
Specifically, aggregate surgical expenditures in the United States are expected to grow from $572 billion in 2005 (4.6% of U.S. gross domestic product) to $912 billion (2005 dollars) in the year 2025 (7.3% of U.S. gross domestic product).96
Thus not surprisingly, prospective healthcare initiatives will focus not only on quality and safety but also on delivering cost-effective care or enhanced value.97
Value in health care, including with anesthesia and surgical services, is broadly defined as the patient health outcomes achieved per dollar spent.10
Efforts to provide enhanced patient care in the PSH model, while controlling unnecessary or wasteful healthcare expenditures, will presumably deliver “high-value, cost-conscious health care.”99
Whether an intervention like the PSH provides such high value is predicated on assessing whether its associated improved health benefits justify its (added) costs.100
There are three key concepts in understanding how to assess the value of new versus
existing health care interventions.100
First, assessing the benefits, harms, and costs of an intervention is essential to understand whether it provides a good value. Second, assessing the cost of an intervention should include not only the cost of the intervention itself but also any downstream costs that occur because the intervention was performed. Third, the incremental cost-effectiveness ratio estimates the additional cost required to obtain additional health benefits and provides a key measure of the value of a healthcare intervention.99–101
Full healthcare economic evaluation techniques conventionally include cost-minimization analysis, cost–benefit analysis, cost–effectiveness analysis, and cost–utility analysis.101–106
A cost–utility analysis is a cost–effectiveness analysis that measures outcomes using quality-adjusted life years or another similar measure. Such full economic evaluations require that two or more therapeutic interventions be compared in relation to both their costs and effects.103
The six fundamental steps in undertaking a full economic evaluation include: (1) identify the perspective of the study; (2) identify the alternatives that will be compared; (3) identify the relevant costs and effects; (4) determine how to collect the cost and effect data; (5) determine how to perform calculation for cost and effects data; and (6) determine the manner in which to depict the results, draw comparisons, and make conclusions.101
With proper planning, a full healthcare economic evaluation can be validly performed and reported alongside a clinical trial.100
However, given the logistical challenges of such a conjoint study,114
researchers often combine previously published cost and clinical outcomes data to create a decision-analysis model.100
The validity of such studies depends on how well the model reflects the key clinical issues and on the reliability of the parameters used to estimate costs, outcomes, and health status utilities.101
Sensitivity analyses are therefore critical for understanding how reported conclusions might change depending on the variability or uncertainty in key parameters.101
Methodologic Considerations for the Evaluation of the PSH Model
In assessing whether the new PSH model is superior to current conventional surgical care, a fundamental question is what is the optimal study design? Related issues include the use of composite outcomes as well as the need for a clinical proof-of-concept (PoC) study data before advocating wider implementation of this model.
Optimal Study Design
Randomized Controlled Trial.
The randomized controlled trial (RCT) has been viewed as the de facto
“definitive standard” of clinical trial design for evaluating the efficacy
and safety (risk vs.
benefit) of a treatment or intervention.116–118
The primary feature underlying the RCTs prominence is the ability to randomize study participants thereby dramatically reducing the opportunity for confounding, by both known and unknown factors, and thereby increasing internal validity relative to observational study designs.116
However, it is important to note that well-designed and executed observational studies have been shown to yield equally valid results with the added benefit of addressing the effectiveness
of a population-based or systems-based intervention like the PSH model, in a more “real-life” and thus externally valid setting.120
Nonetheless, the RCT design is a reasonable choice for assessing many important questions related to the PSH model. There are a number of other RCT designs, which may, on a situational basis, be more appropriate to apply in conducting human research (e.g.
, the comparative effectiveness of the PSH model).122
Thus although the main Consolidated Standards of Reporting Trials Statement is focused on the typical two-group parallel RCT design,123
there are several different types of randomized trials, some of which have different fundamental designs, as well as types of interventions and data, for which specific Consolidated Standards of Reporting Trials Extensions exist.123–125
With respect to evaluating the PSH model, a cluster randomized trial (CRT) is the most suitable RCT design. Individual clinicians, group practices, clinics, hospitals, health plans, or even geographic regions (counties or states) can be defined as the clusters. In a CRT, all individuals within a given cluster are assigned to the same study arm.126
The methodology of CRTs has been widely discussed.127–129
The applicability of the CRT to the PSH model is largely attributable to the fact that it would be impractical for a given institution to modify its process of care on a patient-by-patient basis.
In addition, when evaluating a new therapy, or care model like the PSH, unlike a standard RCT, a CRT typically focuses on effectiveness
by evaluating outcomes under conditions of actual use. A CRT is often done when individual randomization is not feasible. A CRT can also offer considerable cost and time efficiencies when implemented by a health system or health insurance plan that has extensively existing information about its members’ characteristics, treatments, and outcomes, along with a robust existing research infrastructure.126
A CRT design could thus be applied in a comparative study of the PSH model if a sufficiently large number of separate clusters (i.e.
, individual healthcare delivery sites) could be identified and enrolled.
However, compared with individually randomized trials, CRTs are more complex to design, require more participants to obtain equivalent statistical power, and require more complex analysis (e.g.
, adjustment for the intracluster correlation coefficient of the cluster randomization).130–132
A CRT is also typically not blinded. Thus not surprisingly, the use of this trial design has been fraught with challenges, undermining the validity of some published findings.131
As noted above, observational study designs can yield valid results often in a more timely and cost-efficient manner and have greater ability to measure effects under “real world” clinical settings.134
Specifically, an observational prospective cohort study can assess in representative populations the comparative effectiveness
of interventions (e.g.
, the PSH) to reduce risk from coexisting diseases, prevent adverse events, and improve patient-centered outcomes—once again in settings typically encountered in clinical practice.135
An observational prospective cohort study design could also readily assess shared clinician-patient decision-making, a salient feature of the PSH model.135
Cohort study methodology has been widely discussed.116
Specifically, guidelines have been promulgated STrengthening the Reporting of OBservational studies in Epidemiology Initiative for analytic observational studies.145
A cohort study design has several advantages in comparative effectiveness studies, including one comparing status quo surgical patient care with a new PSH model. By applying the active perioperative interventions at the clinic and hospital level, a cohort study would more readily investigate these therapeutic interventions under conditions of actual use. Furthermore, a prospective cohort study design is preferable in a setting where individual randomization is not feasible. For the purposes of studying the PSH, prospective outcomes data would be collected on a group of surgical patients, who receive their care after the implementation of the PSH model, and compared with those receiving conventional perioperative care. Given the relatively short timeframe (e.g., 30–90 days) of a perioperative study, differential attrition would not be expected to be a major concern (though it should be noted that such differential attrition is also a concern in an RCT). However, it will be necessary to explore and address confounding by first adjusting conducting stratified analyses according to (1) the indications for the surgical procedure (2) the presence of known risk factors for postoperative complications, specifically, the level of risk associated with the surgical procedure, and the presence of coronary artery disease, congestive heart failure, hypertension, cerebrovascular disease, diabetes mellitus, chronic renal insufficiency, chronic liver disease, and chronic obstructive pulmonary disease and, in the absence of differential effects, adjust for any characteristics that appear to act as confounders.
A recent trend in clinical trials and some observational studies is the increasing use of composite outcomes,147
which may be applied to assessing the comparative effectiveness of a new PSH model. A composite outcome is comprised several separate yet related component outcomes (e.g.
, death, myocardial infarction, atrial fibrillation, congestive heart failure).147
These components should be a parsimonious set of individual outcomes, which when taken together, well represent the disease of interest (e.g.
, perioperative morbidity and mortality) and are very plausibly related to the intervention (e.g.
, the PSH model).149
A study subject is considered to have experienced the binary (dichotomous) composite outcome if one or more of the component outcomes occur.147
Advantages to using composite outcomes include a reduction in required sample size to achieve adequate power and simplifying data presentation.147
The former is particularly relevant if an individual major outcome is rare yet the statistical power of a realistically sized trial is inadequate to demonstrate a statistically significant treatment difference.149
If many or all of the purported benefits of the PSH are considered clinically important and thus could influence the wider adoption of this nascent patient care model, it would be difficult to identify any single one as the primary clinical outcome.147
In contrast, a composite outcome would allow investigators of the PSH to report a broader but equally valid array of benefits (or harms).
However, the use of composite outcomes in trials can be problematic.150
Components are often unreasonably combined, inconsistently defined, and inadequately reported, resulting in an exaggerated observation of how well interventions work.152
Three major caveats with a composite outcome are that its individual components are similarly important to patients; occur with similar frequency; and are affected to a similar degree by the intervention.148
This assumed homogeneity of effect across its component outcomes can be substantiated by the concomitant reporting of data for each of the component elements as secondary outcomes.147
A parallel can be drawn between the development of a new PSH model and the development of a new drug. PoC typically refers to early studies in clinical drug development, conventionally designated as phase I and phase IIa.153
Unlike a confirmatory
RCT that is required for regulatory drug approval, a PoC trial is exploratory
in nature, and designers of such trials have the liberty to choose the type I error rate and the power.154
However, the selection of clinical endpoints and their effect size, as well as choice of type I and type II error rates, are often at the center of heated debates in the design of PoC trials.155
A PoC trial also supports a so-called “Go-No Go” decision for further drug development.155
Clinical PoC (CPoC) has been defined as: “The construction of working prototypes of the necessary functionality and infrastructure in sufficient quality to investigate evidence for improving health in daily use for a suitable period of time; a limited but relevant set of people [patients] serving as [study] subjects.”§§
An initial, limited scale CPoC study could be appropriately undertaken at one’s institutional level to determine the operational and fiscal viability of further development and deployment (Go-No Go decision) of a novel yet nascent PSH model for the management of surgical patients. The particular clinical endpoints that may make up a CPoC trial for the PSH are a point of active discussion and may include the collection of clinical outcomes proposed in this article, in addition to those recommended by patients, focus groups, institutional committees, payers, and other stakeholders. Permutation P
value trend analysis has been used in CPoC trials to evaluate trends collectively across multiple endpoints. This decreases the likelihood of type II error in trend interpretation as a trend in one endpoint is more likely due to chance than trends in multiple endpoints.156
Finally, the CPoC process emphasizes the identification of previously unforseen challenges and pitfalls unique to each particular environment to save time and resources and improve efficiency when a more robust trial is implemented.§§
The PSH model seeks to deliver a highly patient-centered, anesthesia-led yet interdisciplinary, and team-based system of coordinated care, which guides the patient throughout the entire surgical continuum, from the decision for the need for a surgery to discharge from a medical facility and beyond. By implementing evidence-informed best practices, standardization of processes where applicable, shared decision-making, and management accountability by a single coordinating service, patients are likely to get the most appropriate care possible.8
Eliminating overuse, underuse, and misuse of perioperative care may also lead to better outcomes at a lower cost—the definition of added value.8
However, such value assessments should be ongoing and result not only in the initial implementation of the surgical home concept but also its continued successful evolution. Traditional financial, patient, and surgical metrics will likely have to be redefined to accurately assess new definitions of value.
Nevertheless, the onus is clearly on the advocates and early adopters of this nascent alternate care model to demonstrate its ability to achieve its various espoused goals and objectives. Toward that end, it is prudent to capture the experience of these early adopters in the context of an observational cohort study for the purposes of not only establishing preliminary evidence for the effectiveness of the PSH model but also for providing pilot data necessary for the design of a CRT. This approach will allow a sufficient number of geographically distinct PSHs that would be required for such a trial to become well-established—likely in 3–5 yr.
# American Society of Anesthesiologists. The perioperative or surgical home. Available at: http://www.asahq.org
. Accessed May 10, 2012. Cited Here...
** Society for Advancement of Blood Management (SABM). What is patient blood management? Available at: http://www.sabm.org/
. Accessed October 12, 2012. Cited Here...
†† Anesthesia Quality Institute. About us. Available at: http://www.aqihq.org/
. Accessed July 12, 2013. Cited Here...
‡‡ Michigan Surgical Quality Collaborative. Program overview. Available at: http://www.msqc.org/about_program_overview.php
. Accessed July 12, 2013. Cited Here...
§§ Bardram, Jakob. Clinical Proof-of-Concept—An evaluation method for pervasive healthcare systems. UbiComp '08 Workshop on Ubiquitous Systems Evaluation (USE '08). Available at: http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-393/
. Accessed May 21, 2013. Cited Here...
1. Centers for Disease Control and Prevention. National Hospital Discharge Survey: 2009. 2009 Atlanta Centers for Disease Control and Prevention
2. Kehlet H, Wilmore DW. Evidence-based surgical care and the evolution of fast-track surgery. Ann Surg. 2008;248:189–98
3. Cullen KA, Hall MJ, Golosinskiy A. Ambulatory surgery in the United States, 2006. Natl Health Stat Report. 2009:1–25
4. Hall MJ, DeFrances CJ, Williams SN, Golosinskiy A, Schwartzman A. National Hospital Discharge Survey: 2007 summary. Natl Health Stat Report. 2010:1–20, 24
5. Phipps D, Meakin GH, Beatty PC, Nsoedo C, Parker D. Human factors in anaesthetic practice: Insights from a task analysis. Br J Anaesth. 2008;100:333–43
6. Schimpff SC. Improving operating room and perioperative safety: Background and specific recommendations. Surg Innov. 2007;14:127–35
7. Grocott MP, Pearse RM. Perioperative medicine: The future of anaesthesia? Br J Anaesth. 2012;108:723–6
8. Vetter TR, Goeddel LA, Boudreaux AM, Hunt TR, Jones KA, Pittet JF. The Perioperative Surgical Home: How can it make the case so everyone wins? BMC Anesthesiol. 2013;13:6
9. Fry DE, Pine M, Jones BL, Meimban RJ. The impact of ineffective and inefficient care on the excess costs of elective surgical procedures. J Am Coll Surg. 2011;212:779–86
10. Vetter TR, Ivankova NV, Pittet JF. Patient satisfaction with anesthesia: Beauty is in the eye of the consumer. ANESTHESIOLOGY. 2013;119:245–7
11. Kon AA. The shared decision-making continuum. JAMA. 2010;304:903–4
12. Legare F, Ratte S, Stacey D, Kryworuchko J, Gravel K, Graham ID, Turcotte S. Interventions for improving the adoption of shared decision making by healthcare professionals. Cochrane Database of Systematic Reviews (Online). 2010:CD006732
13. Légaré F, Turcotte S, Stacey D, Ratté S, Kryworuchko J, Graham ID. Patients’ perceptions of sharing in decisions: A systematic review of interventions to enhance shared decision making in routine clinical practice. Patient. 2012;5:1–19
14. Carrier E, Gourevitch MN, Shah NR. Medical homes: Challenges in translating theory into practice. Med Care. 2009;47:714–22
15. Rittenhouse DR, Shortell SM. The patient-centered medical home: Will it stand the test of health reform? JAMA. 2009;301:2038–40
16. Stange KC, Nutting PA, Miller WL, Jaén CR, Crabtree BF, Flocke SA, Gill JM. Defining and measuring the patient-centered medical home. J Gen Intern Med. 2010;25:601–12
17. Warner MA. The Surgical HomeTM
. ASA Newsl. 2012;76:30–2
18. Gross WL, Gold B. Anesthesiology and competitive strategy. Anesthesiol Clin. 2009;27:167–74
19. Scurlock C, Dexter F, Reich DL, Galati M. Needs assessment for business strategies of anesthesiology groups’ practices. Anesth Analg. 2011;113:170–4
20. Burns LR, Muller RW. Hospital-physician collaboration: Landscape of economic integration and impact on clinical integration. Milbank Q. 2008;86:375–434
21. Trybou J, Gemmel P, Annemans L. The ties that bind: An integrative framework of physician-hospital alignment. BMC Health Serv Res. 2011;11:36
22. Porter M, Teisberg E, Olmsted E Redefining Health Care: Creating Value-Based Competition on Results. 2006 Cambridge Harvard Business School Press
23. Porter ME. A strategy for health care reform—Toward a value-based system. N Engl J Med. 2009;361:109–12
24. Porter ME. What is value in health care? N Engl J Med. 2010;363:2477–81
25. Rosenthal MB, Dudley RA. Pay-for-performance: Will the latest payment trend improve care? JAMA. 2007;297:740–4
26. Epstein AM. Pay for performance at the tipping point. N Engl J Med. 2007;356:515–7
27. Mayes R. Moving (realistically) from volume-based to value-based health care payment in the USA: Starting with medicare payment policy. J Health Serv Res Policy. 2011;16:249–51
28. Sevin C, Evdokimoff M, Sobolewski S, Taylor J, Rutherford P, EA C How-to Guide: Improving Transitions from the Hospital to Home Health Care to Reduce Avoidable Rehospitalizations. 2012 Cambridge Institute for Healthcare Improvement
29. Coleman EA, Parry C, Chalmers S, Min SJ. The care transitions intervention: Results of a randomized controlled trial. Arch Intern Med. 2006;166:1822–8
30. Bradway C, Trotta R, Bixby MB, McPartland E, Wollman MC, Kapustka H, McCauley K, Naylor MD. A qualitative analysis of an advanced practice nurse-directed transitional care model intervention. Gerontologist. 2012;52:394–407
31. Iglehart JK. Prioritizing comparative-effectiveness research—IOM recommendations. N Engl J Med. 2009;361:325–8
32. Sox HC. Defining comparative effectiveness research: The importance of getting it right. Med Care. 2010;48(6 suppl):S7–8
33. Institute of Medicine. Committee on Comparative Effectiveness Research Prioritization: Initial National Priorities for Comparative Effectiveness Research. 2009 Washington, D.C. National Academies Press
34. Breivik H, Borchgrevink PC, Allen SM, Rosseland LA, Romundstad L, Hals EK, Kvarstein G, Stubhaug A. Assessment of pain. Br J Anaesth. 2008;101:17–24
35. Fayers PM, Hays RD Assessing Quality of Life in Clinical Trials: Methods and Practice. 2005 Oxford Oxford University Press
36. Fayers PM, Machin D Quality of Life: The Assessment, Analysis and Interpretation of Patient-reported Outcomes. 2007 Chichester; Hoboken John Wiley & Sons
37. DeVine J, Norvell DC, Ecker E, Fourney DR, Vaccaro A, Wang J, Andersson G. Evaluating the correlation and responsiveness of patient-reported pain with function and quality-of-life outcomes after spine surgery. Spine (Phila Pa 1976). 2011;36(21 suppl):S69–74
38. Urbach DR. Measuring quality of life after surgery. Surg Innov. 2005;12:161–5
39. Jokinen JJ, Hippeläinen MJ, Turpeinen AK, Pitkänen O, Hartikainen JE. Health-related quality of life after coronary artery bypass grafting: A review of randomized controlled trials. J Card Surg. 2010;25:309–17
40. Quintana JM, Escobar A, Aguirre U, Lafuente I, Arenaza JC. Predictors of health-related quality-of-life change after total hip arthroplasty. Clin Orthop Relat Res. 2009;467:2886–94
41. Kluivers KB, Riphagen I, Vierhout ME, Brölmann HA, de Vet HC. Systematic review on recovery specific quality-of-life instruments. Surgery. 2008;143:206–15
42. Jakobsson J. Assessing recovery after ambulatory anaesthesia, measures of resumption of activities of daily living. Curr Opin Anaesthesiol. 2011;24:601–4
43. Myles PS, Williams DL, Hendrata M, Anderson H, Weeks AM. Patient satisfaction after anaesthesia and surgery: Results of a prospective survey of 10,811 patients. Br J Anaesth. 2000;84:6–10
44. Heidegger T, Saal D, Nuebling M. Patient satisfaction with anaesthesia care: What is patient satisfaction, how should it be measured, and what is the evidence for assuring high patient satisfaction? Best Pract Res Clin Anaesthesiol. 2006;20:331–46
45. Baumann C, Rat AC, Osnowycz G, Mainard D, Cuny C, Guillemin F. Satisfaction with care after total hip or knee replacement predicts self-perceived health status after surgery. BMC Musculoskelet Disord. 2009;10:150
46. Barnett SF, Alagar RK, Grocott MP, Giannaris S, Dick JR, Moonesinghe SR. Patient-satisfaction measures in anesthesia: Qualitative systematic review. ANESTHESIOLOGY. 2013;119:452–78
47. Dicicco-Bloom B, Crabtree BF. The qualitative research interview. Med Educ. 2006;40:314–21
48. Agency for Healthcare Research and Quality (AHRQ): The Effective Health Care Program Stakeholder Guide. 2011 Rockville, MD Agency for Healthcare Research and Quality (AHRQ)
49. Wu AW, Snyder C, Clancy CM, Steinwachs DM. Adding the patient perspective to comparative effectiveness research. Health Aff (Millwood). 2010;29:1863–71
50. Israel BA, Schulz AJ, Parker EA, Becker ABCommunity-Campus Partnerships for Health. . Community-based participatory research: Policy recommendations for promoting a partnership approach in health research. Educ Health (Abingdon). 2001;14:182–97
51. Eisinger A, Senturia K. Doing community-driven research: A description of Seattle Partners for Healthy Communities. J Urban Health. 2001;78:519–34
52. Royal Society of Canada: Guidelines and Categories for Classifying Participatory Research Projects in Health. 1995 Ottawa, Ontario, Canada Royal Society of Canada
53. Schulz A, Israel B, Selig S, Bayer I, Griffin CMacNair R. Development and implementation of principles for community-based research in public health. Research Strategies for Community Practice. 1998 New York Haworth Press:83–110 . Edited by
54. Horowitz CR, Robinson M, Seifer S. Community-based participatory research from the margin to the mainstream: Are researchers prepared? Circulation. 2009;119:2633–42
55. Patton MQ Qualitative Evaluation and Research Methods. 2002 Thousands Oaks SAGE
56. Creswell J, Klassen A, Plano Clark V, Smith K Best Practices for Mixed Methods Research in the Health Sciences. 2011 Bethesda National Institutes of Health:1–37
57. Holden DJ, Zimmerman MA A Practical Guide to Program Evaluation Planning: Theory and Case Examples. 2009 Thousand Oaks SAGE Productions
58. Douketis JD, Spyropoulos AC, Spencer FA, Mayr M, Jaffer AK, Eckman MH, Dunn AS, Kunz RAmerican College of Chest Physicians. . Perioperative management of antithrombotic therapy: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141(2 suppl):e326S–50S
59. Crossley GH, Poole JE, Rozner MA, Asirvatham SJ, Cheng A, Chung MK, Ferguson TB Jr, Gallagher JD, Gold MR, Hoyt RH, Irefin S, Kusumoto FM, Moorman LP, Thompson A. The Heart Rhythm Society (HRS)/American Society of Anesthesiologists (ASA) Expert Consensus Statement on the perioperative management of patients with implantable defibrillators, pacemakers and arrhythmia monitors: Facilities and patient management this document was developed as a joint project with the American Society of Anesthesiologists (ASA), and in collaboration with the American Heart Association (AHA), and the Society of Thoracic Surgeons (STS). Heart Rhythm. 2011;8:1114–54
60. . American Society of Anesthesiologists Task Force on Acute Pain Management: Practice guidelines for acute pain management in the perioperative setting: An updated report by the American Society of Anesthesiologists Task Force on Acute Pain Management. ANESTHESIOLOGY. 2012;116:248–73
61. Gross JB, Bachenberg KL, Benumof JL, Caplan RA, Connis RT, Coté CJ, Nickinovich DG, Prachand V, Ward DS, Weaver EM, Ydens L, Yu SAmerican Society of Anesthesiologists Task Force on Perioperative Management. . Practice guidelines for the perioperative management of patients with obstructive sleep apnea: A report by the American Society of Anesthesiologists Task Force on Perioperative Management of patients with obstructive sleep apnea. ANESTHESIOLOGY. 2006;104:1081–93; quiz 1117–8
62. Gan TJ, Meyer TA, Apfel CC, Chung F, Davis PJ, Habib AS, Hooper VD, Kovac AL, Kranke P, Myles P, Philip BK, Samsa G, Sessler DI, Temo J, Tramèr MR, Vander Kolk C, Watcha MSociety for Ambulatory Anesthesia. . Society for Ambulatory Anesthesia guidelines for the management of postoperative nausea and vomiting. Anesth Analg. 2007;105:1615–28
63. Fleisher LA, Beckman JA, Brown KA, Calkins H, Chaikof E, Fleischmann KE, Freeman WK, Froehlich JB, Kasper EK, Kersten JR, Riegel B, Robb JF, Smith SC Jr, Jacobs AK, Adams CD, Anderson JL, Antman EM, Buller CE, Creager MA, Ettinger SM, Faxon DP, Fuster V, Halperin JL, Hiratzka LF, Hunt SA, Lytle BW, Nishimura R, Ornato JP, Page RL, Tarkington LG, Yancy CW. ACC/AHA 2007 guidelines on perioperative cardiovascular evaluation and care for noncardiac surgery: Executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 2002 Guidelines on Perioperative Cardiovascular Evaluation for Noncardiac Surgery). Anesth Analg. 2008;106:685–712
64. Fleisher LA, Beckman JA, Brown KA, Calkins H, Chaikof EL, Fleischmann KE, Freeman WK, Froehlich JB, Kasper EK, Kersten JR, Riegel B, Robb JF. 2009 ACCF/AHA focused update on perioperative beta blockade incorporated into the ACC/AHA 2007 guidelines on perioperative cardiovascular evaluation and care for noncardiac surgery. J Am Coll Cardiol. 2009;54:e13–e118
65. Poldermans D, Bax JJ, Boersma E, De Hert S, Eeckhout E, Fowkes G, Gorenek B, Hennerici MG, Iung B, Kelm M, Kjeldsen KP, Kristensen SD, Lopez-Sendon J, Pelosi P, Philippe F, Pierard L, Ponikowski P, Schmid JP, Sellevold OF, Sicari R, Van den Berghe G, Vermassen F. Guidelines for pre-operative cardiac risk assessment and perioperative cardiac management in non-cardiac surgery. Eur Heart J. 2009;30:2769–812
66. Bisbe E, Muñoz M. Management of preoperative anemia: The NATA consensus statements. ISBT Science Series. 2012;7:283–7
67. Goodnough LT, Maniatis A, Earnshaw P, Benoni G, Beris P, Bisbe E, Fergusson DA, Gombotz H, Habler O, Monk TG, Ozier Y, Slappendel R, Szpalski M. Detection, evaluation, and management of preoperative anaemia in the elective orthopaedic surgical patient: NATA guidelines. Br J Anaesth. 2011;106:13–22
68. Carson JL, Grossman BJ, Kleinman S, Tinmouth AT, Marques MB, Fung MK, Holcomb JB, Illoh O, Kaplan LJ, Katz LM, Rao SV, Roback JD, Shander A, Tobian AA, Weinstein R, Swinton McLaughlin LG, Djulbegovic B. Red blood cell transfusion: A clinical practice guideline from the AABB. Ann Intern Med. 2012;157:49–58
69. Shander A. Developments in blood management: A patient-centered approach. ASA Newsl. 2012;76:10
70. Singer SJ, Burgers J, Friedberg M, Rosenthal MB, Leape L, Schneider E. Defining and measuring integrated patient care: Promoting the next frontier in health care delivery. Med Care Res Rev. 2011;68:112–27
71. Epstein RM, Fiscella K, Lesser CS, Stange KC. Why the nation needs a policy push on patient-centered health care. Health Aff (Millwood). 2010;29:1489–95
72. Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med. 2009;361:1368–75
73. Ghaferi AA, Birkmeyer JD, Dimick JB. Complications, failure to rescue, and mortality with major inpatient surgery in medicare patients. Ann Surg. 2009;250:1029–34
74. 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;30:615–29
75. Taenzer AH, Pyke JB, McGrath SP. A review of current and emerging approaches to address failure-to-rescue. ANESTHESIOLOGY. 2011;115:421–31
76. Institute of Medicine. Committee on Quality of Health Care in America: Crossing the Quality Chasm: A New Health System for the 21st Century. 2001 Washington, D.C National Academy Press
77. Centers for Medicare & Medicaid Services (CMS). . HHS: Medicare program; hospital inpatient value-based purchasing program. Final rule. Fed Regist. 2011;76:26490–547
78. Bratzler DW. The Surgical Infection Prevention and Surgical Care Improvement Projects: Promises and pitfalls. Am Surg. 2006;72:1010–6 discussion 1021–30, 1133–48
79. Bratzler DW, Hunt DR. The surgical infection prevention and surgical care improvement projects: National initiatives to improve outcomes for patients having surgery. Clin Infect Dis. 2006;43:322–30
80. Velanovich V, Rubinfeld I, Patton JH Jr, Ritz J, Jordan J, Dulchavsky S. Implementation of the National Surgical Quality Improvement Program: Critical steps to success for surgeons and hospitals. Am J Med Qual. 2009;24:474–9
81. The Joint Commission: National Patient Safety Goals. 2012 Oakbrook Terrace The Joint Commission
82. Agency for Healthcare Research: Patient Safety Indicators Overview. 2012 Rockville Agency for Healthcare Research
83. Schwulst SJ, Mazuski JE. Surgical prophylaxis and other complication avoidance care bundles. Surg Clin North Am. 2012;92:285–305, ix
84. Hawn MT, Vick CC, Richman J, Holman W, Deierhoi RJ, Graham LA, Henderson WG, Itani KM. Surgical site infection prevention: Time to move beyond the surgical care improvement program. Ann Surg. 2011;254:494–9 discussion 499–501
85. Stulberg JJ, Delaney CP, Neuhauser DV, Aron DC, Fu P, Koroukian SM. Adherence to surgical care improvement project measures and the association with postoperative infections. JAMA. 2010;303:2479–85
86. Anesthesia Quality Institute. Outcomes of Anesthesia: Core Measures. 2013 Park Ridge, IL, Anesthesia Quality Institute
87. Clavien PA, Barkun J, de Oliveira ML, Vauthey JN, Dindo D, Schulick RD, de Santibañes E, Pekolj J, Slankamenac K, Bassi C, Graf R, Vonlanthen R, Padbury R, Cameron JL, Makuuchi M. The Clavien-Dindo classification of surgical complications: Five-year experience. Ann Surg. 2009;250:187–96
88. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240:205–13
89. DeOliveira ML, Winter JM, Schafer M, Cunningham SC, Cameron JL, Yeo CJ, Clavien PA. Assessment of complications after pancreatic surgery: A novel grading system applied to 633 patients undergoing pancreaticoduodenectomy. Ann Surg. 2006;244:931–7 discussion 937–9
90. Reddy SK, Pawlik TM, Zorzi D, Gleisner AL, Ribero D, Assumpcao L, Barbas AS, Abdalla EK, Choti MA, Vauthey JN, Ludwig KA, Mantyh CR, Morse MA, Clary BM. Simultaneous resections of colorectal cancer and synchronous liver metastases: A multi-institutional analysis. Ann Surg Oncol. 2007;14:3481–91
91. Park JY, Kim TJ, Kang HJ, Lee YY, Choi CH, Lee JW, Bae DS, Kim BG. Laparoendoscopic single site (LESS) surgery in benign gynecology: Perioperative and late complications of 515 cases. Eur J Obstet Gynecol Reprod Biol. 2013;167:215–8
92. Siedhoff MT, Carey ET, Findley AD, Riggins LE, Garrett JM, Steege JF. Effect of extreme obesity on outcomes in laparoscopic hysterectomy. J Minim Invasive Gynecol. 2012;19:701–7
93. Sink EL, Leunig M, Zaltz I, Gilbert JC, Clohisy JAcademic Network for Conservational Hip Outcomes Research Group. . Reliability of a complication classification system for orthopaedic surgery. Clin Orthop Relat Res. 2012;470:2220–6
94. Permpongkosol S, Link RE, Su LM, Romero FR, Bagga HS, Pavlovich CP, Jarrett TW, Kavoussi LR. Complications of 2,775 urological laparoscopic procedures: 1993 to 2005. J Urol. 2007;177:580–5
95. Sundaram CP, Martin GL, Guise A, Bernie J, Bargman V, Milgrom M, Shalhav A, Govani M, Goggins W. Complications after a 5-year experience with laparoscopic donor nephrectomy: The Indiana University experience. Surg Endosc. 2007;21:724–8
96. Muñoz E, Muñoz W III, Wise L. National and surgical health care expenditures, 2005–2025. Ann Surg. 2010;251:195–200
97. Newman MF, Mathew JP, Aronson S. The evolution of anesthesiology and perioperative medicine. ANESTHESIOLOGY. 2013;118:1005–7
98. Neuman MD. Patient satisfaction and value in anesthesia care. ANESTHESIOLOGY. 2011;114:1019–20
99. Owens DK, Qaseem A, Chou R, Shekelle PClinical Guidelines Committee of the American College of Physicians. . High-value, cost-conscious health care: Concepts for clinicians to evaluate the benefits, harms, and costs of medical interventions. Ann Intern Med. 2011;154:174–80
100. Robinson RL, Vetter TRMoore RJ. Healthcare economic evaluation of chronic pain: Measuring the economic, social and personal impact of chronic pain. Biobehavioral Approaches to Pain. 2009 New York Springer:219–58 . Edited by
101. Vetter TR, Chou RBenzon HT, Rathmell JP, Turk DC. Clinical trial methodology for pain outcome studies. Raj’s Practical Management of Pain. 20135th edition New York Elsevier:1057–65 . Edited by
102. Vetter TR. The application of economic evaluation methods in the chronic pain medicine literature. Anesth Analg. 2007;105:114–8
103. Drummond M, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL Methods for Economic Evaluation of Health Care Programmes. 20053rd edition New York Oxford University Press
104. Jefferson T, Demicheli V, Mugford M Elementary Economic Evaluation in Health Care. 20002nd edition London BMJ Publishing Group
105. Korthals-de Bos I, van Tulder M, van Dieten H, Bouter L. Economic evaluations and randomized trials in spinal disorders: Principles and methods. Spine. 2004;29:442–8
106. Tan MCY, Regier DA, Esdaile JM, Lynd LD, Anis AH, Marra CA. Health economic evaluation: A primer for the practicing rheumatologist. Arthritis Care Res. 2006;55:648–56
107. Asche CV, Seal B, Jackson KC, Oderda GM. Economic evaluations in pain management. J Pain Palliat Care Pharmacother. 2006;20:15–23
108. van der Roer N, Boos N, van Tulder MW. Economic evaluations: A new avenue of outcome assessment in spinal disorders. Eur Spine J. 2006;15(suppl 1):S109–17
109. Drummond M. Introducing economic and quality of life measurements into clinical studies. Ann Med. 2001;33:344–9
110. Ramsey S, Willke R, Briggs A, Brown R, Buxton M, Chawla A, Cook J, Glick H, Liljas B, Petitti D, Reed S. Good research practices for cost-effectiveness analysis alongside clinical trials: The ISPOR RCT-CEA Task Force report. Value Health. 2005;8:521–33
111. Petrou S, Gray A. Economic evaluation alongside randomised controlled trials: Design, conduct, analysis, and reporting. BMJ. 2011;342:d1548
112. Ramsey SD, McIntosh M, Sullivan SD. Design issues for conducting cost-effectiveness analyses alongside clinical trials. Annu Rev Public Health. 2001;22:129–41
113. Glick HA, Doshi J, Sonnad S, Polsky D Economic Evaluation in Clinical Trials. 2007 New York Oxford University Press
114. Ramsey SD, McIntosh M, Sullivan SD. Design issues for conducting cost-effectiveness analyses alongside clinical trials. Annu Rev Public Health. 2001;22:129–41
115. Weinstein MC, O’Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, Luce BRISPOR Task Force on Good Research Practices–Modeling Studies. . Principles of good practice for decision analytic modeling in health-care evaluation: Report of the ISPOR Task Force on Good Research Practices–Modeling Studies. Value Health. 2003;6:9–17
116. Grimes DA, Schulz KF. An overview of clinical research: The lay of the land. Lancet. 2002;359:57–61
117. Sox HC, Helfand M, Grimshaw J, Dickersin K, Tovey D, Knottnerus JA, Tugwell PPLoS Medicine Editors. . Comparative effectiveness research: Challenges for medical journals. J Clin Epidemiol. 2010;63:862–4
118. Grossman J, Mackenzie FJ. The randomized controlled trial: Gold standard, or merely standard? Perspect Biol Med. 2005;48:516–34
119. Schulz KF, Grimes DA. Blinding in randomised trials: Hiding who got what. Lancet. 2002;359:696–700
120. Sanson-Fisher RW, Bonevski B, Green LW, D’Este C. Limitations of the randomized controlled trial in evaluating population-based health interventions. Am J Prev Med. 2007;33:155–61
121. Mercer SL, DeVinney BJ, Fine LJ, Green LW, Dougherty D. Study designs for effectiveness and translation research: Identifying trade-offs. Am J Prev Med. 2007;33:139–54
122. Arnett DK, Claas SADavid R, Gordon HW. Introduction to epidemiology. Clinical and Translational Science. 2009 San Diego Academic Press:527–41 . Edited by
123. Schulz KF, Altman DG, Moher DCONSORT Group. . CONSORT 2010 statement: Updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010;152:726–32
124. Zwarenstein M, Treweek S, Gagnier JJ, Altman DG, Tunis S, Haynes B, Oxman AD, Moher DCONSORT Group; Pragmatic Trials in Healthcare (Practihc) Group. . Improving the reporting of pragmatic trials: An extension of the CONSORT statement. BMJ. 2008;337:a2390
125. Piaggio G, Elbourne DR, Pocock SJ, Evans SJ, Altman DGCONSORT Group. . Reporting of noninferiority and equivalence randomized trials: Extension of the CONSORT 2010 statement. JAMA. 2012;308:2594–604
126. Mazor KM, Sabin JE, Boudreau D, Goodman MJ, Gurwitz JH, Herrinton LJ, Raebel MA, Roblin D, Smith DH, Meterko V, Platt R. Cluster randomized trials: Opportunities and barriers identified by leaders of eight health plans. Med Care. 2007;45(10 suppl 2):S29–37
127. Donner A, Klar N Design and Analysis of Cluster Randomization Trials in Health Research. 2000 London Arnold
128. Hayes RJ, Moulton LH Cluster Randomised Trials. 2009 Boca Raton Taylor & Francis
129. Murray DM, Varnell SP, Blitstein JL. Design and analysis of group-randomized trials: A review of recent methodological developments. Am J Public Health. 2004;94:423–32
130. Kerry SM, Bland JM. The intracluster correlation coefficient in cluster randomisation. BMJ. 1998;316:1455
131. Campbell MK, Elbourne DR, Altman DGCONSORT Group. . CONSORT statement: Extension to cluster randomised trials. BMJ. 2004;328:702–8
132. Killip S, Mahfoud Z, Pearce K. What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. Ann Fam Med. 2004;2:204–8
133. Varnell SP, Murray DM, Janega JB, Blitstein JL. Design and analysis of group-randomized trials: A review of recent practices. Am J Public Health. 2004;94:393–9
134. Godwin M, Ruhland L, Casson I, MacDonald S, Delva D, Birtwhistle R, Lam M, Seguin R. Pragmatic controlled clinical trials in primary care: The struggle between external and internal validity. BMC Med Res Methodol. 2003;3:28
135. Gartlehner G, Hansen RA, Nissman D, Lohr KN, Carey TS. A simple and valid tool distinguished efficacy from effectiveness studies. J Clin Epidemiol. 2006;59:1040–8
136. Silverman SL. From randomized controlled trials to observational studies. Am J Med. 2009;122:114–20
137. Mann CJ. Observational research methods. Research design II: Cohort, cross sectional, and case-control studies. Emerg Med J. 2003;20:54–60
138. Hartung DM, Touchette D. Overview of clinical research design. Am J Health Syst Pharm. 2009;66:398–408
139. DiPietro NA. Methods in epidemiology: Observational study designs. Pharmacotherapy. 2010;30:973–84
140. Rothman KJ, Greenland S, Lash TL Modern Epidemiology. 2008 Philadelphia Wolters Kluwer Health/Lippincott Williams & Wilkins
141. Gordis L Epidemiology. 2009 Philadelphia Elsevier/Saunders
142. Rochon PA, Gurwitz JH, Sykora K, Mamdani M, Streiner DL, Garfinkel S, Normand SL, Anderson GM. Reader’s guide to critical appraisal of cohort studies: 1. Role and design. BMJ. 2005;330:895–7
143. Mamdani M, Sykora K, Li P, Normand SL, Streiner DL, Austin PC, Rochon PA, Anderson GM. Reader’s guide to critical appraisal of cohort studies: 2. Assessing potential for confounding. BMJ. 2005;330:960–2
144. Normand SL, Sykora K, Li P, Mamdani M, Rochon PA, Anderson GM. Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding. BMJ. 2005;330:1021–3
145. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JPSTROBE Initiative. . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Ann Intern Med. 2007;147:573–7
146. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger MSTROBE Initiative. . Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. Epidemiology. 2007;18:805–35
147. Sessler DI, Devereaux PJ. Emerging trends in clinical trial design. Anesth Analg. 2013;116:258–61
148. Ferreira-González I, Permanyer-Miralda G, Busse JW, Bryant DM, Montori VM, Alonso-Coello P, Walter SD, Guyatt GH. Methodologic discussions for using and interpreting composite endpoints are limited, but still identify major concerns. J Clin Epidemiol. 2007;60:651–7 discussion 658–62
149. Mascha EJ, Sessler DI. Statistical grand rounds: Design and analysis of studies with binary-event composite endpoints: Guidelines for anesthesia research. Anesth Analg. 2011;112:1461–71
150. Tomlinson G, Detsky AS. Composite end points in randomized trials: There is no free lunch. JAMA. 2010;303:267–8
151. Ferreira-González I, Busse JW, Heels-Ansdell D, Montori VM, Akl EA, Bryant DM, Alonso-Coello P, Alonso J, Worster A, Upadhye S, Jaeschke R, Schünemann HJ, Permanyer-Miralda G, Pacheco-Huergo V, Domingo-Salvany A, Wu P, Mills EJ, Guyatt GH. Problems with use of composite end points in cardiovascular trials: Systematic review of randomised controlled trials. BMJ. 2007;334:786
152. Cordoba G, Schwartz L, Woloshin S, Bae H, Gøtzsche PC. Definition, reporting, and interpretation of composite outcomes in clinical trials: Systematic review. BMJ. 2010;341:c3920
153. Gelenberg AJ, Thase ME, Meyer RE, Goodwin FK, Katz MM, Kraemer HC, Potter WZ, Shelton RC, Fava M, Khan A, Trivedi MH, Ninan PT, Mann JJ, Bergeson S, Endicott J, Kocsis JH, Leon AC, Manji HK, Rosenbaum JF. The history and current state of antidepressant clinical trial design: A call to action for proof-of-concept studies. J Clin Psychiatry. 2008;69:1513–28
154. Chen C, Beckman RA. Optimal cost-effective designs of Phase II proof of concept trials and associated go-no go decisions. J Biopharm Stat. 2009;19:424–36
155. Chen C, Sun L, Li CL. Evaluation of early efficacy endpoints for proof-of-concept trials. J Biopharm Stat. 2013;23:413–24
156. Davison BA, Cotter G, Sun H, Chen L, Teerlink JR, Metra M, Felker GM, Voors AA, Ponikowski P, Filippatos G, Greenberg B, Teichman SL, Unemori E, Koch GG. Permutation criteria to evaluate multiple clinical endpoints in a proof-of-concept study: Lessons from Pre-RELAX-AHF. Clin Res Cardiol. 2011;100:745–53
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