Steven M. Asch, MD, MPH

Nearly 57 million outpatient surgeries—invasive procedures performed on an outpatient basis in hospital outpatient departments (HOPDs) or ambulatory surgery centers (ASCs)&mdash;produced annually in the United States account for roughly 7% of healthcare expenditures. Although moving inpatient surgeries to outpatient settings has lowered the cost of care, substantial opportunities to improve the value of outpatient surgery remain. To exploit these remaining opportunities, we composed an evidence-based care delivery composite for national discussion and pilot testing.

We synthesized peer-reviewed publications describing efforts to improve the value of outpatient surgical care, interviewed patients and clinicians to understand their most deeply felt discontents, reviewed potentially relevant emerging science and technology, and observed surgeries at healthcare organizations nominated by researchers as exemplars of efficiency and effectiveness. Primed by this information, we iterated potential new designs utilizing criticism from practicing clinicians, health services researchers, and healthcare managers.

We found that 3 opportunities are most likely to improve value: 1) maximizing the appropriate use of surgeries via decision aids, clinical decision support, and a remote surgical coach for physicians considering a surgical referral; 2) safely shifting surgeries from HOPDs to high-volume, multi-specialty ASCs where costs are much lower; and 3) standardizing processes in ASCs from referral to recovery.

Extrapolation based on published studies of the effects of each component suggests that the proposed 3-part composite may lower annual national outpatient surgical spending by as much as one-fifth, while maintaining or improving outcomes and the care experience for patients and clinicians. Pilot testing and evaluation will allow refinement of this composite.

		Outpatient surgeries account for roughly 7% of annual US healthcare expenditures. There are substantial opportunities to lower national spending while improving quality and patients’ experience of outpatient surgical care.

		We found that 3 opportunities are most likely to improve value: 1) maximizing the appropriate use of surgeries via decision aids, clinical decision support, and a remote surgical coach for physicians considering a surgical referral; 2) safely shifting surgeries from hospital outpatient departments to high-volume, multi-specialty ambulatory surgery centers (ASCs) where costs are much lower; and 3) standardizing processes in ASCs from referral to recovery.

		Extrapolation based on published studies of the effects of each component suggests that the proposed 3-part composite may lower annual national outpatient surgical spending by as much as one-fifth while maintaining or improving outcomes and the care experience for patients and clinicians.

Outpatient surgeries—surgical and nonsurgical invasive procedures performed on an outpatient basis in hospital outpatient departments (HOPDs) or freestanding ambulatory surgery centers (ASCs)&mdash;are a fast-growing segment of healthcare,

 fueled by improved pain management, less invasive surgical techniques, patient convenience, and lower cost.

 However, its growth also carries risks, such as more pain and longer recovery times than patients expect,

 unplanned subsequent hospital admissions,

To help US clinicians and healthcare organizations respond constructively to rising incentives to improve value, we used a method adapted from biomedical technology innovation to design an innovative care delivery “composite” offering the greatest potential to improve value to US patients and their healthcare sponsors.

A year-long, 3-person team of postdoctoral clinicians and management scientists, supported by senior mentors from clinical practice, health services research, and healthcare management, was recruited via a national search to create the new care composite. The team conducted site visits to understand costs, quality, and patient experience at 3 institutions, all nominated by health services researchers to reflect today’s high-value “frontier” in the United States and globally. During these visits, the team compared care delivery methods for a single surgical procedure and created detailed process maps. They also observed care more broadly at several additional sites selected via “convenience” samples (eg, based on established relationships between the authors and the administrators of those facilities) to represent mainstream care. At all sites, the team sought to elicit the most deeply felt unmet needs of patients, family members, and clinicians; they intended the site selection to be as inclusive as they could design by a mix of “frontier” and “convenience” samples. In addition, the team did not rely on observations directly unless these observations were also supported by literature and/or approved by experts in the area. Yet, the team acknowledges that there is always the possibility that different site selection might have influenced the model construction.

The team conducted a literature review of efforts to improve the quality, patient experience, and total cost of outpatient surgical care. Via a series of seminars with individuals regarded as global or national leaders in their field, the team considered the applicability of relevant emerging science and technologies. Using these diverse exploration methods, the team discerned several correctable major shortfalls in value (

Over the next 6 months, the team iterated a proposed innovative care composite to correct these shortfalls, with the goal of identifying opportunities that are most likely to improve value. Diverse senior mentors continuously challenged or encouraged the team’s design

 and its national impact projections. This process expanded the team’s consideration of the “adjacent possible”

—innovations used for other medical conditions, such as medical and surgical homes, and by other industries, such as an automated check-in process for surgery that is similar to airline passenger check-ins and screenings. After 6 months of continuous refinement, the team converged on a composite new “care model,” along with an estimate of its likely impact on annual US health spending after accounting for implementation and operating costs (

The resulting 3-component composite is displayed in the 

 and is summarized by the words REFINE, RE-SET, and REPLICATE, or the “Triple-R” in short. The Table also displays evidence pertaining to the quantitative impact of each component. The next section summarizes rough estimates of the impact on the annual national outpatient surgical spending from combining all 3 components after 5 foundation-building years of implementation, learning, refinement, and competency-building. These estimates are speculative since the proposed combination of elements and their national scaling are unprecedented.

REFINE: Maximize Appropriate Use of Outpatient Surgeries

 of all elective surgeries may be inappropriate, which is defined as surgeries in which the expected health benefits offer no clear advantage over less risky alternatives.

 Perverse financial incentives may contribute to inappropriate use,

 as can poor alignment between a patient’s overall condition, goals of care, and desired outcomes.

 Referring providers—generally primary care providers&mdash;often lack adequate time and support to assure better alignment.

 In addition, effective communication to patients of likely benefits and risks occurs in only 20% of cases,

 often resulting in unrealistic patient expectations.

 Addressing the appropriateness of a surgical referral in primary care is one way to avert surgical overuse. We discerned several combinable solutions intended to be implemented by primary care providers prior to surgical referral.   

 These reduce surgical use for conditions associated with multiple clinically appropriate treatment options by as much as 20% and improve patient satisfaction,

 yet only 10% to 30% of eligible patients receive them.

 Roughly 500 ready-to-implement and validated decision aids are available for most high-volume outpatient surgeries, such as cataract, cholecystectomy, hernia, and spine surgeries.

Within an electronic health record, clinical decision support can help clinicians apply guidelines, thus increasing the appropriateness of surgeries that clinicians recommend.

 For example, when 120 procedures at risk for overuse, identified by the Choosing Wisely

 campaign, were translated into clinical decision support tools by Cedars-Sinai Medical Center, utilization decreased by as much as 18%.

 Clinical decision support tools may reduce complications

 and increase patient satisfaction. Automated clinical decision support tools can facilitate awareness of Appropriate Use Criteria

 and are more effective when endorsed via consensus among an organization’s clinicians.

Patient decision aids and clinical decision support are insufficient to delineate an appropriate decision in approximately 8% of cases.

 In such instances, referring providers could be supported by a remotely located surgeon who does not benefit financially from the referral to serve as a “case coach” to verify the adequacy and appropriateness of the proposed program of care. For example, an e-consult service adopted by a number of integrated systems, such as the Veterans Health Administration, have decreased subsequent referrals for specialist care by 20% to 40%.

We estimate potential net national reduction in annual US health spending from successful implementation of REFINE at $7.4 billion, or 3.5% of total annual spending on outpatient surgeries.

RE-SET: Safely Shift More Surgeries to Ambulatory Surgery Centers

Despite similar outcomes, the same surgeries performed on low-risk patients in HOPDs cost much more to produce than in ASCs.

 Today, over half of US outpatient surgeries take place in HOPDs.

 This ratio can be safely changed by shifting a large number of surgeries from HOPDs to ASCs, as already occurs in other medically advanced nations.

 Based on the payment differential between sites,

 the Washington Ambulatory Surgery Center Association estimated that CMS could save $25 billion over a 10-year period with such a shift.

 We predict there may be additional savings due to differences in procedure and recovery duration.

 Expanding ASC operating room hours to 18 hours a day, 7 days a week would substantially boost throughput in multi-specialty ASCs. Human factors research suggests that such a shift could be safely implemented. Expansion of hours has been tested in other labor- and process-driven industries, such as aviation,

 and in healthcare settings in wealthy and poor countries. Narayana Health in India produces coronary artery bypass graft surgery with low mortality rates for less than $2000,

 in part, by spreading fixed costs over a larger patient base by expanded hours of operation.

 Similar cost reductions can be achieved in the United States.

 Because cognitive function and performance diminishes between the hours of midnight and 6 AM,

18 hours per day may be the maximum expansion of operating room hours without jeopardizing clinical outcomes. Research on volume-outcome relationships suggests that outcomes may also improve (Table).

We estimate net national reduction in annual US health spending from RE-SET to be $26.2 billion, or 12.5% of annual current US spending on outpatient surgeries.

REPLICATE: Standardize and Integrate Care Across an Episode 

Inefficient processes, slow adoption of evidence-based practice, and fragmentation of care is thought to account for as much as 30% of US healthcare spending.

 Standardizing today’s ASC processes on those that demonstrate the highest level of value and integrating them across the entire surgical episode can further boost the value of US surgical care.

 Because ASCs avoid urgent circumstances and high-risk patients, they are especially well-suited for care-process standardization. Standardized care can incorporate 3 elements and extend from the point of referral to recovery.

 These are structured, multidisciplinary plans of care that integrate clinical guidelines and protocols adjusted to fit local environments and workflow capabilities. These algorithms improve outcomes and yield an average cost savings of 18%.

 Checklists may ensure the use of clinical algorithms. A number of off-the-shelf options currently exist for preoperative checklists, such as those generated by organizations like Strong for Surgery,

 which focuses on patients’ preoperative behavior.

 Additional clinical algorithms should be designed to optimize care transitions for postdischarge care.

 Clinical algorithms yield to standardized workflows that, in turn, allow lower-cost clinical team members to perform work that is currently performed by more costly health professionals. Standard workflows extend outside the procedure to encompass tasks such as discharge planning

 and turnovers to reduce operating room down time.

 Standardizing nonlabor inputs, such as surgical supplies, based on comparative effectiveness and price, reduces the cost of surgery and allows for volume-based price discounts from suppliers. It also simplifies purchasing and reduces the time and effort needed to tailor supplies to surgical team preferences. Such standardization may lead to cost savings of roughly 20%

 and improve quality of care by reducing variation in equipment and supplies that support staff members must master, thus reducing errors attributed to unfamiliarity. 

Continuous monitoring and adjustment of clinical algorithms and workflows.

 Additional reduction in variation can further boost the yield from algorithms and standard workflows by continuously analyzing deviations and making further refinements. As clinician confidence builds in algorithms, information technology tools, such as patient dashboards, automated check-in,

 can ease care pathway implementation and improve the clinician and patient experience of care.

We estimate that net annual US savings associated with the REPLICATE element could approach $6.3 billion, or 3% of annual spending on outpatient surgeries after a 5-year implementation and refinement period.

Major opportunities remain to improve the value of US outpatient surgical care (

). To capitalize on these opportunities, we gathered evidence from diverse sources. The validity of our forecast for lowering the cost of better surgical care hinges on the quality and transferability of the evidence that we sourced. Pilot-testing of the Triple-R will reveal synergies and friction points among component parts.

Some elements of the composite, such as the expanded hours of operation, extend beyond directly relevant evidence and rely instead on successes in plausibly similar circumstances. When operationalizing such elements, it is important to consider context-dependent implementation hurdles; for example, expanding hours in the ASC context may present implementation challenges in incorporating provider and staff preferences for certain work hours. Furthermore, some of the reported efficiency in ASCs

 may be due to incentives to finish cases quickly because staffing is not performed in shifts. Thus, adding shifts may paradoxically lengthen case and turnaround times. Incentives, such as bonus payments for off-hour shifts may mitigate this issue. Expanded hours may also pose challenges to incorporating patient preferences. In previous studies of other procedures, patients have opted for inconvenient hours if the wait time for therapy was shorter.

 However, understanding patient preferences and trade-offs in elective surgery would be valuable; additionally, discounted pricing for unfavorable times may be considered.

We estimate that the potential for annual nationwide savings is roughly $40 billion net of implementation costs, or 19% of current annual spending on outpatient surgeries and more than 1% of total annual US healthcare spending. To achieve such savings, the Triple-R uses disruptive elements that would require structural and cultural shifts in the healthcare system. One such element is shifting procedures to ASCs despite current economic incentives to keep them in HOPDs. Our composite is designed with value-based payment, tiered networks, and reference pricing in mind, where such a tradeoff is indeed financially encouraged. However, even in other types of systems, market competition may ultimately work in favor of ASCs due to the low price, better convenience, and better quality. In addition, shifting higher turnover cases to ASCs will open up capacity at HOPDs, and allow them to streamline inputs and specialize their labor and care. Even with the shift, HOPDs will continue to produce a significant percentage of outpatient procedures (eg, complex procedures or procedures on medically complex patients).

The Triple-R focuses broadly on all outpatient procedures, but not all procedures will generate the same value. Future pilot studies will most likely focus on a smaller group of specialties. Although this choice will be site-dependent, there may be specialties and procedures that are likely to generate relatively more value from the application of our composite, due to, for example, a high volume of outpatient surgeries that can safely be moved to ASCs within the specialty. Our preliminary analysis suggests that certain procedures within the specialty areas of orthopedics, ophthalmology, plastic surgery, gastrointestinal, and gynecology may be good candidates for future pilot testing.

Results from pilot testing and scaling the proposed composite will hinge on each organization’s culture and management capabilities. Therefore, local operational and cultural factors must be a part of any implementation. The composite is designed to target levers with the highest opportunity to lower per capita healthcare spending safely. For example, even though there are opportunities to increase the value of care in HOPDs, ambulatory surgery represents a larger cost-reduction opportunity, and therefore has been chosen as the focus of the composite. Having said that, elements of REPLICATE can be used at HOPDs to increase efficiency and improve outcomes, while elements of REFINE apply to all outpatient procedures independent of surgical location.

Extrapolation based on published studies of the effects of each component suggests that the proposed 3-part composite may lower annual national outpatient surgical spending by as much as one-fifth, while maintaining or improving outcomes and the care experience for patients and clinicians. We have begun partnerships with healthcare organizations to assess the impact of the REFINE-RESET-REPLICATE composite. As clinicians and their organizations face increasing use of value-based payment, tiered networks, and reference pricing,

 its successful implementation and refinement may help secure their financial viability.

The authors wish to thank Dani Zionts, MSPH, for reviewing the article, and Rajbinder Mann for administrative support. They also thank Craig Albanese, MD, MBA; Jeffrey Belkora, PhD; John Chardos, MD; Alana Conner, PhD; David Hopkins, PhD; Mohit Kaushal, MD; Dhruv Kazi, MD; William Kennedy, MD; Thomas Krummel, MD; Richard Levy, PhD; Harold Luft, PhD; Richard Popp, MD; Stanley Rosenschein, PhD; Kristan Staudenmayer, MD; Ming Tai-Seale, PhD, MPH; Samuel Wald, MD, MBA; Thomas Weiser, MD; Paul Wise, MD, MPH; and Donna Zulman, MD, for their guidance. 

 Clinical Excellence Research Center (KB, FE, MK, AM, EM, CN, TP) and Division of General Medical Disciplines (SMA, FE, AM, EM, CN), Stanford University, Stanford, CA; Department of Neurosurgery, Stanford University Medical Center (MK), Stanford, CA; Department of Pediatrics, Lucile Packard Children’s Hospital (TP), Stanford, CA.

 The study was supported by the Sue and Dick Levy Fund, an advised fund of the Silicon Valley Community Foundation.

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.  

 Concept and design (SMA, KB, FE, MK, AM, CN, TP); acquisition of data (KB, FE, MK, AM, CN, TP); analysis and interpretation of data (SMA, KB, FE, MK, EM, AM, CN, TP); drafting of the manuscript (SMA, KB, FE, MK, AM, EM); critical revision of the manuscript for important intellectual content (SMA, KB, FE, AM, EM, TP); statistical analysis (CN); provision of patients or study materials (MK); obtaining funding (AM); administrative, technical, or logistic support (FE, EM, TP); and supervision (SMA, MK, AM, EM, TP).

 Feryal Erhun, PhD, Judge Business School, University of Cambridge, Trumpington S, Cambridge CB2 1AG, UK. E-mail: f.erhun@jbs.cam.ac.uk.

1. Cullen KA, Hall MJ, Golosinskiy A. Ambulatory surgery in the United States, 2006. 

2. Manchikanti L, Parr AT, Singh V, Fellows B. Ambulatory surgery centers and interventional techniques: a look at long-term survival. 

Articles

Outpatient surgeries in the United States account for roughly 7% of annual healthcare expenditures. To exploit substantial opportunities to improve the value of outpatient surgical care, the authors composed an evidence-based care delivery composite for national discussion and pilot testing.

Opportunities to Improve the Value of Outpatient Surgical Care

 To analyze inappropriate use of magnetic resonance imaging (MRI) for patients with low back pain in a healthcare system with no financial incentives for overuse.

 We used administrative data to assess the appropriateness of lumbar spine (LS) MRI in the Veterans Health Administration.

All veterans who received LS MRI in the outpatient setting in fiscal year 2012 were included. We based our assessments of appropriateness on CMS criteria, which have been endorsed by the National Quality Forum. Generalized estimating equations were used to evaluate characteristics of inappropriate scans.

Of the 110,661 LS MRIs performed, 31% were classified as inappropriate. Most scans that were considered appropriate were characterized as such because they were preceded by conservative therapy (53%). "Red flag" conditions were responsible for a much smaller percentage of scans being considered appropriate; 13% of scans were preceded by conservative therapy and were performed in patients with a red flag condition, while only 4% of scans were considered appropriate because of red flag conditions only. Scans ordered in the emergency department and in urgent care, primary care, and internal medicine clinics were most likely to be classified as inappropriate. Resident physicians were significantly less likely than other provider types to order inappropriate LS MRIs (odds ratio, 0.80; 

 <.0001). Approximately 24% of providers ordered 74% of inappropriate scans.

We found that 31% of LS MRIs were inappropriate in a healthcare system largely absent of financial and other incentives for ordering. The problem of inappropriate ordering of LS MRI is concentrated in a small number of providers; any provider-facing interventions to reduce inappropriate order should therefore be targeted, rather than aimed at all providers who order LS MRI.

	Using CMS criteria, we found that 31% of lumbar spine magnetic resonance imaging (LS MRI) performed in fiscal year 2012 was inappropriate. This high level of inappropriate ordering is particularly striking in a system largely free of financial and other incentives for ordering, suggesting that nonpecuniary factors play a role in these inappropriate ordering choices. We found a high concentration of inappropriate ordering among few providers. Results indicate that efforts to reduce inappropriate use of LS MRI should involve cultural change, as well as patient and provider education, rather than financial incentives alone, and that provider-facing efforts should be targeted instead of universal.

Most Americans will experience low back pain (LBP) at some point in their adult lives.

 Many patients with LBP receive imaging to explore the cause of their pain

; advances in imaging technology have revealed unprecedented anatomical detail for LBP patients. The underlying difficulty is that, for many patients, anatomical and functional abnormalities do not correlate well, and thus imaging can fail to guide treatment of the primary complaint.

 In one study of individuals who underwent magnetic resonance imaging (MRI), approximately 90% were detected to have a degenerated or bulging disc, 36% had a herniated disc, and 21% had spinal stenosis—but all patients were asymptomatic.

 For most patients, LBP resolves on its own

; even sophisticated imaging of the lumbar spine (LS) for nonchronic pain does not improve outcomes.

Overuse of LS MRI is suspected to be a large problem; multiple societies have prioritized it as a quality-of-care measure or a measure of prudent stewardship of resources. The American College of Physicians and the American Association of Neurological Surgeons recommend against the use of LS MRI for nonspecific or nonpersistent LBP in their Choosing Wisely campaign.

 The National Quality Forum (NQF), a nonprofit entity that sets national priorities for quality measurement, has endorsed a CMS measure regarding inappropriate use of imaging in LBP.

The reasons for overuse of imaging are not well understood. Fee-for-service financial incentives have been suggested as a potential reason for overuse of lumbar spine imaging,

 In this study, we explored inappropriate use of LS MRI in a US healthcare system—one largely free of financial incentives for overuse, and in which physicians are largely insulated from malpractice concerns&mdash;to understand whether inappropriate ordering occurs in the absence of these financial or legal influences. The federal government accepts liability for any instances of medical negligence or wrongdoing on the part of the Department of Veterans Affairs (VA) providers; concerns over malpractice or incentives to practice defensive medicine are therefore much lower for VA providers compared with providers in the larger US healthcare environment. It is also not well understood whether inappropriate ordering is equally distributed across providers, or concentrated among relatively few high-ordering providers; this information carries important implications for quality improvement activities. Here, we use NQF-endorsed CMS criteria to evaluate inappropriate ordering of LS MRI across the entire VA, including the patient-, provider-, and system-level factors associated with the practice.

To study the appropriateness of this imaging modality, we identified the population of veterans who received an outpatient LS MRI in VA in fiscal year (FY) 2012. If patients received more than 1 LS MRI, we retained information regarding the first MRI. Additionally, we searched VA inpatient and outpatient data from FY 2010 to FY 2012 to evaluate the care and condition of these veterans prior to receipt of LS MRI. CMS criteria pertain to LS MRIs with a diagnosis of LBP on the MRI claim; because VA MRIs do not have associated diagnosis codes, we evaluated all LS MRIs. We considered the clinic visit with the ordering provider that immediately preceded the scan to be the ordering visit.

We evaluated the appropriateness of LS MRI according to the NQF-endorsed CMS measure #0514 (“MRI Lumbar Spine for Low Back Pain”),

). This measure classifies an LS MRI as appropriate if it was: 1) preceded by conservative therapy, or 2) conducted in a patient who has a “red flag” condition. CMS considers physical therapy or chiropractic care in the 60 days prior to the scan, or an evaluation and management visit occurring between 28 to 60 days prior to the scan, to be conservative therapy. Physical therapy, chiropractic care, and evaluation and management visits were identified by Current Procedural Terminology codes specified by the NQF-endorsed CMS measure.

 We classified an evaluation and management (E&M) visit as conservative therapy only if the scan was not ordered during that visit.

We made minor modifications to the CMS criteria regarding red flag conditions. The CMS measure excludes LS MRIs occurring in patients with red flag conditions from the denominator; here, we included them but considered them to be appropriate in order to present a complete view of all LS MRIs in VA. CMS red flag conditions include trauma in the 45 days preceding the scan; LS surgery in the 90 days preceding the scan; or intravenous drug abuse, neurologic impairment, cancer, HIV diagnosis, or diagnosis of unspecified immune deficiency in the 365 days preceding the scan. The measure includes all cancer; we excluded primary skin and primary prostate cancer as these types of neoplasms would not cause lumbar compression and rarely have an impact on spine pain. Additionally, there are concerns regarding a high false-positive rate for prostate cancer due to overuse of prostate-specific antigen (PSA) screening. To the CMS red flag conditions, we added intraspinal abscess or compression fracture in the 30 days prior to the scan, and osteomyelitis in the previous 365 days. All red flag conditions were identified through

 International Classification of Diseases, Ninth Revision, Clinical Modification 

) codes in inpatient and outpatient data sets.

From these data, we identified which LS MRI scans were considered inappropriate. LS MRIs were considered inappropriate in patients who did not have a red flag condition in the time frame of interest and those who did not receive appropriate conservative therapy.

We also investigated patient-, provider- and facility-level characteristics associated with inappropriate scans, as well as any regional differences in proportion of inappropriate scans. Patient-level characteristics included age, gender, and race. Provider-level variables included ordering provider type (attending physician, resident, physician’s assistant, and advanced practice nurse/nurse practitioner) and the clinic in which the scan was ordered (internal medicine/primary care, physical medicine and rehabilitation; neurology, neurosurgery, orthopedics, pain medicine, “other” medicine services, miscellaneous other medicine services, chiropractic care, and emergency department [ED] and urgent care). Other medicine services refer to various primary and specialty care clinics separate from the other categories of care (eg, geriatrics, oncology, hospice, dementia clinic).  Miscellaneous other services refer to all ancillary and support services (eg, cast clinic, social work, telephone triage).  The facility-level variable included complexity, defined in 5 levels (1a, 1b, 1c, 2, and 3; from most to least complex).

Characteristics of inappropriate scans were evaluated using generalized estimating equations to account for clustering of patients within facilities. Our generalized estimating equations employed a logit link, a binomial distribution family, and an independent correlation structure. We ran sensitivity analyses in which we evaluated facility-level physical therapy penetration—defined as physical therapy visits per 1000 pro-rated patients&mdash;and in which, we evaluated alternative definitions of conservative therapy. Specifically, we required the conservative therapy visits to have an accompanying diagnosis of low back pain. Post estimation commands were used to compare outcomes among different levels of each categorical level; for example, to compare residents with each other provider type, physician’s assistants to each other provider type, etc. All analyses were conducted in SAS version 9.2 (SAS Institute, Inc, Cary, North Carolina). 

In FY 2012, 110,661 LS MRIs were ordered in the outpatient setting by 16,273 unique providers. Most patients received 1 LS MRI; only 3.7% of patients received more than 1. Each provider ordered a median of 3 LS MRIs and a mean of 6.8 LS MRIs. Of the 110,661 total scans, 33,998 (30.7%) were classified as inappropriate; these patients had no red flag conditions coded and did not receive conservative therapy in a VA facility prior to their scan (

). The majority of scans classified as appropriate were done so because the patient was deemed to have received prior conservative therapy (65.3%). Another 16.6% of LS MRIs were classified as appropriate because the patient had a red flag condition. (Note that the numbers add up to more than 100% because patients could have had both a red flag condition and have received conservative therapy.)

describes the demographics of the population, which on average, was male, white, and middle-aged. The greatest proportion of scans (42%) was ordered for patients seen at the most-complex (level 1a) facilities. However, the greatest proportion of inappropriate scans (36%) was ordered for patients seen at the least-complex facilities (level 3) (Table 2). The number of scans ordered varied greatly by clinic setting, with the greatest percentage of scans ordered by the primary care/internal medicine clinic (62%), and the fewest percentage ordered by neurosurgery and orthopedics (6% combined). The greatest percentage of total scans (69%) was ordered by medical doctors or doctors of osteopathy, and the lowest was ordered by physicians’ assistants (8%). We did not find meaningful regional variation in proportion to scans considered inappropriate.

Results from generalized estimating equations revealed that patients aged under 35 years were more likely to have an inappropriate scan than those of all other ages (

). Black patients were less likely to have an inappropriate scan compared with white patients (odds ratio [OR], 0.80; 

 <.0001). Scans ordered at the lowest-complexity facility (level 3) were more likely to be inappropriate compared with those ordered at the highest-complexity facilities (OR, 1.27; 

 = .0096). These multivariate results also show the ED or urgent care clinic to be the settings most strongly associated with an inappropriate scan (OR, 1.42; 

 <.0001, with reference category of primary care/internal medicine clinic). In fact, ED/urgent care providers were more likely than providers practicing in any other clinic to order inappropriate scans (Table 3). Primary care/internal medicine clinics were also associated with a high likelihood of ordering inappropriate scans; all other clinic settings were less likely to order inappropriate scans than the primary care/internal medicine clinic (Table 3). Neurology, neurosurgery, and orthopedic clinics all practiced similarly; after adjusting for covariates, each was equally likely to order an inappropriate scan compared with the others (Table 3). Medical doctors (MDs), doctors of osteopathy (DOs), nurses, and physician’s assistants were also equally likely to order an inappropriate scan; however, residents were less likely to order an inappropriate LS MRI scan compared with MD/DOs (OR, 0.80; 

Results also show that 10.9% of providers ordered 50.1% of inappropriate scans, and 23.6% of providers ordered 74% of inappropriate scans (

). There appeared to be a weak, volume-percent inappropriate relationship; that is, there was little evidence of a relationship between the volume of scans ordered by a provider and the percentage of those scans deemed inappropriate.

We ran sensitivity analyses in which we modified the categorization of E&M codes. CMS considers any E&M visit between 28 and 60 days prior to the MRI to be conservative therapy, as long as the MRI was not ordered during that visit. Using this definition in our base-case, 63% of scans were conducted in patients who had a qualifying E&M visit. In sensitivity analyses, we restricted the E&M visit to have a diagnosis of LBP. Using this more restrictive definition, we found only 34% of LS MRI scans had a qualifying E&M visit, and thus, 53% of LS MRIs were considered inappropriate.

We also ran other sensitivity analyses. We tested a model with a covariate of facility-level physical therapy penetration. This variable was not a significant predictor of inappropriate LS MRI. Additionally, we ran a model on the subset of scans ordered by providers who ordered 5 or more scans per year, to avoid drawing conclusions based on a large number of providers each ordering few scans. Results did not change with respect to direction or significance. Third, we tested the inclusion of all prostate cancer in the red flag conditions, thus considering all LS MRI imaging in patients with a prostate cancer diagnosis in the previous 365 days to be appropriate. This resulted in slightly fewer (28.9%) LS MRIs being considered inappropriate.

We estimated the cost of providing each LS MRI in VA using the Decision Support System, the activity-based cost allocation system used by VA. We estimated that VA spent $44.4 million on LS MRIs in FY 2012, including $13.6 million on inappropriate scans.

The extent of overuse of LS MRI has been the subject of much debate. Here, we find that, despite a strong body of evidence regarding the poor utility of LS MRI in nonchronic LBP, and the identification of LS MRI as a low-value service by multiple specialty societies,

 31% of LS MRIs conducted in VA in FY 2012 were inappropriate.

Estimates of inappropriateness of LBP imaging vary in the literature. The 2000 to 2006 claims-based analysis of Pham and colleagues found that 29% of Medicare beneficiaries received x-ray, computed tomography (CT), or MRI inappropriately.

 A 2004 to 2006 claims-based analysis of privately insured patients found 9% of patients with LBP had an MRI within 14 days of initial diagnosis, and approximately 60% of patients had MRI, CT, or x-ray on the same day as the first diagnosis of LBP.

 These variations in the ordering of imaging could be due to increasing supply of MRI scanners from 2000 to 2012,

 different ratios of acute and chronic LBP patients in study samples, and varying definitions of inappropriate.

We found inappropriate use of MRI in VA, even though its providers have little to no financial incentive to order more scans and have less malpractice liability than physicians in private practice—2 factors often cited as reasons for overuse of imaging.

 This suggests that nonpecuniary factors play an important role in ordering behavior in VA. Thus, it also suggests that changes in financial incentives alone will not be sufficient to reduce inappropriate ordering of LS MRI, and that provider and patient education may be necessary. Further research to explore the reasons for inappropriate ordering in this healthcare system, including the relative importance of lack of awareness of guidelines and concerns about patient satisfaction or reassurance

 will be informative for quality improvement. Reducing inappropriate ordering of LS MRI also may be a question of educating patients, as well as providers. One randomized controlled trial found that patients receiving MRI were more satisfied than those receiving x-ray, independent of functional outcome.

 This tactic may be increasingly important as organizations move to include patient satisfaction metrics in their measures of quality of care.

This is, to the best or our knowledge, the first analysis of NQF-endorsed CMS criteria to evaluate inappropriate ordering of LS MRI. Our analysis indicated that providers in primary care and internal medicine clinics, EDs, and urgent care clinics were most likely to order inappropriate LS MRIs. MDs, DOs, nurses, and physician’s assistants were equally likely to order inappropriately. Of note, we found that residents were significantly less likely than all other provider types to order inappropriately. Although resident behavior has been relatively understudied in the literature, Pitts and colleagues found that ED visits with residents were more likely to have resulted in advanced imaging orders compared with ED visits without residents.

 Our dissimilar results may be due to questions of appropriateness; Pitts and colleagues did not evaluate the appropriateness of the imaging. We also found a weak relationship between the volume of scans ordered by a provider and the percentage of those scans considered inappropriate; high-ordering providers were not necessarily inappropriately ordering providers. Rather, we found that inappropriate LS MRIs were concentrated among relatively few providers. Approximately a quarter of providers (24%) ordered roughly three-fourths of all inappropriate scans (74%). Most providers (58%) ordered 3 or fewer scans per year, accounting for 60% of all LS MRIs ordered in this year. This suggests that the majority of providers do not need to be involved in interventions to reduce inappropriate use.

Our results indicate that interventions to reduce inappropriate ordering will be most appropriately directed at providers who order 18 or more scans per year, at providers and managers at the lowest-complexity facilities, and at providers in primary care/internal medicine clinics. Interventions aimed at providers who order 18 or more scans per year represent an opportunity to have a substantive impact on reducing the absolute number of inappropriate MRIs ordered. Although ED and urgent care services have the greatest percentage of inappropriate scans (41% in univariate analysis), intervening in these clinics will have modest effects, as they account for only 4% of all scans. Primary care/internal medicine clinics accounted for 62% of all scans. Scans ordered in these settings were significantly more likely to be inappropriate, making them likely targets for intervention.

It is possible that scans are being ordered in these primary care/internal medicine clinics to meet the scheduling requirements of specialists; specialty clinics may require an LS MRI before seeing a patient. We found that orthopedics and neurosurgery, together, ordered only 6% of all LS MRIs in VA, suggesting this may be a factor. Further research is needed to determine if scans attributed to primary care/internal medicine providers were ordered to secure referral to specialty clinics; this research should inform any interventions to reduce inappropriate ordering.

Our sensitivity analyses showed that changes in the definition of evaluation and management—which are a major component of what constitutes conservative therapy&mdash;have a large influence on estimates of appropriateness. Using a more restrictive definition of evaluation and management reduced the number of scans with conservative therapy and almost halved the percentage of scans regarded as appropriate. We used the most generous definition of evaluation and management in our base-case analyses. Our choice of a generous definition was two-fold: We wished to be consistent with the definition developed by CMS, and we prioritized identifying sensitivity (true appropriateness) over specificity (true inappropriateness). Maximizing sensitivity represents a cautious approach that avoids erroneously categorizing scans as inappropriate.

Use of imaging that provides no benefit to patients, and may in fact cause harm through catalyzing medical interventions for common and asymptomatic abnormalities, represents waste within the healthcare system. With healthcare expenditures of $2.6 trillion in 2010 and a consistently positive rate of growth in healthcare costs,

 waste is something the US healthcare system and US economy can ill afford. Our analysis indicates an excess annual cost of $13.7 million for LS MRI in VA. Outside of VA, it has been estimated that if all US adults were treated in accordance with imaging guidelines for LBP, the healthcare system would save at least $300 million annually (in 2009 dollars),

 with even greater cost savings achieved if accounting for costs associated with treating asymptomatic disease.

This study was a retrospective analysis of administrative VA data and is subject to certain limitations. We used administrative data to assess the appropriateness of LS MRI. Administrative data do not contain the complete details of the content of care; there may be data captured through history and physical (eg, regarding duration of treatment) that was not assigned an 

code. For example, it is possible that patients received some conservative therapy in a non-VA setting prior to their VA MRI, or that physicians had some rationale for ordering the MRI that was not captured in the coding of care such as progressively worsening symptoms; in this case, our analysis would overestimate the proportion of scans that were inappropriate. However, we employed CMS-generated and NQF-endorsed administrative data-based algorithms that were generous in their categorization of appropriate scans in order to mitigate the likelihood of this. Additionally, MRIs conducted at VA do not contain diagnosis codes; our analysis thus evaluated all LS MRIs. It is possible that we included LS MRIs that were conducted for reasons other than low back pain. This may overestimate the proportion of LS MRIs considered inappropriate. However, the appropriateness of LS MRIs is a function of both the reason for the LS MRI (eg, low back pain), as well as the reasons for which the LS MRI may be warranted (ie, prior failed conservative therapy or a patient with a red flag condition). As we used the least restrictive definition of conservative therapy (that which did not require the conservative therapy visit to have a diagnosis of low back pain) to evaluate care prior to the scan within VA, it is more likely that our analysis actually underestimates the proportion of scans that were inappropriate.

VA is a unique healthcare setting; our results may differ from those of studies of other US providers. While our analysis has limited generalizability outside of VA, analyzing this population provides important insight, by illuminating that even in a healthcare system largely absent of financial and other incentives for overuse, inappropriate ordering of LS MRI is still a substantial problem. Furthermore, our results may be of particular interest to accountable care organizations, whose financial incentives and organizational structure more closely resemble those of VA.

Despite recommendations from specialty societies that LS imaging should be performed only in patients who have severe or progressive neurological deficits or signs and symptoms of serious underlying conditions, we found that 31% of LS MRIs performed in a US healthcare system largely absent financial incentives for overuse—were inappropriate. This work reveals 2 important insights that will be informative for quality improvement purposes. First, our work suggests that nonpecuniary factors have a role to play in inappropriate ordering of imaging for low back pain; efforts to reduce inappropriate ordering cannot rely on financial incentives alone. Second, we found a high concentration of inappropriate ordering among few providers, indicating that provider-focused efforts to reduce inappropriate orders should be targeted rather than universal. Further work should be conducted to assess the proportion of inappropriate LS MRI in environments where defensive medicine or fee-for-service incentives may be at play. 

 VA Health Economics Resource Center (RG, PS, JL, PGB) and VA Center for Innovation to Implementation (RG, TA, SMA), VA Palo Alto Health Care System, Menlo Park, CA; Division of General Medical Disciplines (SMA) and Department of Health Research and Policy (PGB), Stanford University School of Medicine, Stanford, CA.

 This work was supported by VA QUERI Grant: RRP 12-442 Decision Support to Decrease Overuse of Imaging: Usability and Measurement; the funding source played no role in study design or interpretation of results. Dr Gidwani had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (RG, PS, SMA, PGB); acquisition of data (RG, JL, PGB); analysis and interpretation of data (RG, PS, TA, JL, SMA, PGB); drafting of the manuscript (RG, PGB); critical revision of the manuscript for important intellectual content (RG, PS, TA, SMA, PGB); statistical analysis (RG, JL, PGB); obtaining funding (SMA, PGB); administrative, technical, or logistic support (TA); and supervision (RG, SMA, PGB).

 Risha Gidwani, DrPH, VA Health Economics Resource Center, VA Center for Innovation to Implementation, 795 Willow Rd, 152 MPD, Menlo Park, CA 94025. E-mail: Risha.Gidwani@va.gov.

1. Deyo RA, Mirza SK, Martin BI. Back pain prevalence and visit rates: estimates from U.S. national surveys, 2002. 

2. Di Iorio D, Henley E, Doughty A. A survey of primary care physician practice patterns and adherence to acute low back problem guidelines. 

This article analyzes use of lumbar spine magnetic resonance imaging in a national sample of patients with low back pain.

Inappropriate Ordering of Lumbar Spine Magnetic Resonance Imaging: Are Providers Choosing Wisely?

Geographical barriers to subspecialty care may prevent optimal care of patients living in rural areas. We assess the impact of human immunodeficiency virus (HIV) and hepatitis C telemedicine consultation on patient-oriented outcomes in a rural Veterans Affairs population.

 This was a pre- and post-intervention study comparing telemedicine with in-person subspecialty clinic visits for HIV and hepatitis C. Eligible patients resided in 2 rural catchment areas. The primary binary outcome was clinic completion. We estimated a logistic regression model with patient-level fi xed effects. This approach controls for the clustering of visits by patient, uses each patient’s in-person clinic experience as an internal control group, and eliminates confounding by person-level factors. We also surveyed patients to assess satisfaction and patient-perceived reductions in health visit—related time.

 There were 43 patients who accounted for 94 telemedicine visits and 128 in-person visits. Clinic completion rates were higher for telemedicine (76%) than for in-person visits (61%). In regression analyses, telemedicine was strongly predictive of clinic completion (OR 2.2; 95% confi dence interval [CI]: 1.0-4.7). The adjusted effect of telemedicine on clinic completion rate was 13% (95% CI: 12-13). Of the 30 patients (70%) who completed the survey, more than 95% rated telemedicine at the highest level of satisfaction and preferred telemedicine to in-person clinic visits. Patients reported a signifi cant reduction in health visit—related time (median 340 minutes, interquartile range 250-440), mostly due to decreased travel time.

 HIV and hepatitis C telemedicine clinics are associated with improved access, high patient satisfaction, and reduction in health visit—related time.

We evaluated human immunodefi ciency virus (HIV) and hepatitis C telemedicine services at 2 rural clinics.

 HIV and hepatitis C are high-risk, prevalent, and chronic illnesses where subspecialty care can often improve quality of life and survival. Distance may be an important barrier to access.

 Visit completion rate, a proxy for access, was 13% greater for telemedicine compared with in-person clinics.

 >95% of respondents rated telemedicine at the highest level of satisfaction and preferred telemedicine to in-person visits.

 Telemedicine reduced health visit time by 340 minutes.

 This intervention was implemented within an existing telemedicine infrastructure without need for additional staff or equipment.

Electronic interactive healthcare consultations, also known as telemedicine, may reduce geographic barriers to timely subspecialty care. Human immunodefi ciency virus (HIV) and hepatitis C are ideal test conditions for telemedicine, because they are high-risk, prevalent, and chronic illnesses where subspecialty care can often improve quality of life and survival. The demand for such services will likely increase as more patients become eligible for treatment with new antiviral regimens.

 Unfortunately, limited access to subspecialty care is a major barrier to optimal care of patients infected with HIV and/or hepatitis C,

 particularly for those who live in rural settings.

The Veterans Affairs (VA) Healthcare System has taken a leadership role by investing heavily in telemedicine

 to better serve the 20% of veterans who reside in rural areas.

 Expanding telemedicine access to HIV/hepatitis C subspecialty care has been identified as a top priority by the VA national leadership and the VA HIV/Hepatitis Quality Enhancement Research Initiative.

 Although there have been reports of telemedicine care for HIV and hepatitis C in non-VA settings,

 we are unaware of published reports describing HIV/hepatitis C telemedicine efforts within the VA system. To address this clinical need, the VA Greater Los Angeles Health System (VAGLAHS) implemented HIV and hepatitis C telemedicine services at 2 rural clinics.

The goal of this study was to assess the impact of telemedicine services for the VAGLAHS HIV and hepatitis C clinics on patient-oriented outcomes. We used clinic completion rates as a proxy measure for access. Our primary hypothesis was that telemedicine would safely improve clinic completion rates. We also hypothesized that telemedicine would be associated with high patient satisfaction and reduced health visit—related time.

This is a pre-post intervention study of HIV/hepatitis C clinic visits clustered by patients. We used the pre-intervention, in-person clinic completion rate of each patient as an internal control group to assess the impact of the telemedicine clinics. The VAGLAHS HIV clinic initiated telemedicine consultations in February 2009 and the VAGLAHS hepatitis C clinic began telemedicine consultations in February 2010. Pre- and post-intervention data for this study were collected from June 2008 to June 2011. This study was approved by the VAGLAHS Institutional Review Board.

VAGLAHS has an existing telemedicine infrastructure that includes “hub” sites located in urban Los Angeles. The “spoke” sites in this study included the Santa Maria and Bakersfield clinics, which are respectively 160 and 110 miles driving distance from the urban clinics. Telemedicine consultations are performed utilizing video teleconferencing end units over a high-speed Internet connection (Polycom; Pleasanton, California). At the hub sites, mobile end units with 32" monitors can be moved between clinics. A clinical manager at each of the hub and spoke sites is responsible for providing support to the telemedicine program. The HIV/ hepatitis C telemedicine clinics utilized this existing infrastructure, and no additional funds, staff, or equipment were required for implementation. However, the “clinical champions”

and nursing staff for these clinics did provide in-kind time to develop policies and processes to implement telemedicine services.

Telemedicine consultations were performed by healthcare providers during the existing infectious disease and hepatitis C clinic times at the urban hub sites. For both the HIV and hepatitis C clinics, there was a single half-day clinic per week. Patients scheduled for a telemedicine consultation presented to a spoke site. An onsite nurse measured vital signs, and patients were placed in a private examination room set up with teleconferencing equipment. The healthcare providers at the hub sites could remotely conduct consultations; perform interviews and patient education; view chart notes, radiology tests, and electrocardiograms; enter orders for pharmacy,

laboratory, and radiology; and perform documentation using the VA computerized patient record system. During the study period, there was a single provider in each of the HIV and hepatitis C clinics who performed all telemedicine consultations (CJG, JPS).

The study population is a convenience sample of patients residing in the Santa Maria and Bakersfi eld catchment areas who were referred by their HIV or hepatitis C provider to the telemedicine clinic. Providers selected patients who were deemed to have stable disease. There were no other eligibility criteria such as viral load or active antiviral therapy.

The primary binary outcome was clinic completion, defi ned as the completion of a scheduled appointment. Reasons for non-completion of a scheduled appointment included no-shows and patient cancellations. Cancellations by the clinic were excluded from this analysis.

Determination of clinic completion was performed by review of electronic medical records and administrative data. All telemedicine clinic encounters were reviewed. To create patient-specifi c internal control groups, we also reviewed all condition-specifi c in-person visits that occurred during the study period. For example, if a patient was scheduled for an HIV telemedicine clinic visit, we collected data on all prior scheduled HIV in-person clinic visits for that patient.

Secondary outcomes included patient satisfaction and health visit—related time. At the end of each telemedicine consult, a research assistant administered a 10-minute survey from the hub site. Overall satisfaction and ratings of physician interaction, privacy, physical environment, and convenience were measured on a 5-level Likert scale (very dissatisfied, somewhat dissatisfied, neither satisfi ed nor dissatisfied, somewhat satisfied, very satisfied). Preference for in-person versus telemedicine consultation was measured on a binary scale. Patients were also asked to estimate travel and on-site time required for in-person and telemedicine visits. For estimates of on-site time, patients were asked to consider time for checking in, waiting, and completing the consultation. Total health visit–related time is defi ned as the sum of travel and on-site time related to a clinic visit.

We collected demographic data on age at time of the first telemedicine visit, gender, and race/ethnicity from review of electronic medical records and administrative data. Race/ethnicity data were self-reported to VAGLAHS. Finally, we assessed whether there were any hospitalizations at a VA facility or deaths that occurred within 30 days of a subspecialty clinic.

All electronic and administrative records were reviewed by a research assistant (HNS). To assess inter-rater reliability, a physician-investigator (BCS) blinded to the research assistant’s abstractions independently re-reviewed notes from 50 randomly selected visits. There was 100% concordance on all data elements, including visit completion, demographic data, and occurrence of 30-day hospitalization or death.

We performed unadjusted and adjusted analyses of the primary outcome of clinic completion rates. Contingency table methods were used to estimate unadjusted clinic completion rates for scheduled in-person and telemedicine visits. To assess the adjusted effect of telemedicine on clinic completion, we estimated a logistic regression model with personfi xed effects. The binary outcome is clinic completion, and the predictor is clinic setting (in-person vs telemedicine). This approach controls for the clustering of visits by patient, uses each patient’s in-person clinic experience as an internal control group, and eliminates confounding by person-level factors. Odds ratio and 95% confi dence intervals were calculated directly from the regression results. We performed sensitivity analyses with person-level random effects, and with no person-level effects; there were no qualitative differences in the results.

Although odds ratios are commonly reported effect measures, they may be difficult to interpret clinically. We used a bootstrapping approach to estimate the adjusted impact of telemedicine on clinic completion rates. We generated 1000 re-samples of the patient population of equivalent size to the original patient population. For each sample, we fit the logistic regression model with patient-level fixed effects, and the absolute rate difference was estimated by hypothetically setting all visits to either in-person or to telemedicine. We used estimates across all 1000 re-samples to generate a mean point estimate and 95% confi dence intervals of the absolute rate difference between in-person and telemedicine visits.

To explore the possibility of condition-specific effects of telemedicine on visit completion, we re-fit the regression model with an interaction term between telemedicine and condition (HIV vs hepatitis C).

We describe all secondary outcomes in descriptive tables. All time-interval outcomes were highly right-skewed. Using patient estimates of health visit—related time, we calculated the median and interquartile range of the differences between in-person and telemedicine clinic visits. We used the Wilcoxon rank-sum test for non-parametric data to assess time-based measures.

Data entry was performed using Microsoft Access (Redmond, Washington). Data management and analyses were performed using SAS 9.1 (Cary, North Carolina).

There were 43 patients who accounted for 94 telemedicine visits and 128 in-person visits to HIV or hepatitis C subspecialty clinics. This cohort was predominantly male, as expected for a VA population, and the majority of patients were evaluated for hepatitis C (

The in-person clinic completion rate of the study cohort was 61%, which is similar to the historic in-person clinic completion rate of 61% for HIV and hepatitis C visits by all patients from the study catchment areas from 2008 to 2010 (

= 0.9). The adjusted odds ratio of clinic completion associated with telemedicine was 2.3 (95% CI: 1.0-4.7; 

 = 0.04). In bootstrapped analysis, telemedicine was associated with an increased clinic completion rate of 13% (95% CI: 12-13) (

In an integrated health system, human immunodeficiency virus and hepatitis C telemedicine clinics are associated with improved access, high patient satisfaction, and reduction in health visitâ€œrelated time.

Steven M. Asch, MD, MPH

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