To evaluate the cost-benefit of appointment-based medication synchronization (ABMS) offered in community pharmacies for patients taking chronic medications to prevent negative outcomes associated with hyperlipidemia, hypertension, and diabetes.

Decision-tree analysis based on published literature and publicly available data.

 Program benefits were based on linking published findings of improvements in medication adherence due to the implementation of an ABMS program to a claims-based study of disease-related medical costs associated with different levels of adherence. The direct cost of the program—increased medication utilization as a result of improved adherence&mdash;was calculated from publicly available prescription pricing data. Benefit-cost ratios were assessed from a payer perspective over a 1-year time frame.

 Additional medication expenditures due to improved adherence associated with ABMS enrollment were offset by lower disease-specific medical costs. Medical savings per additional dollar spent on medications ranged from approximately $1 to $37 depending on the medication and medication class considered. ABMS was most cost-beneficial for metformin and statins. Sensitivity analyses showed that cost-benefit was significantly impacted by medication costs and any service fees associated with ABMS.

 ABMS programs have been shown to increase medication adherence in patients taking chronic medications. These programs were shown to have a significant cost-benefit for healthcare payers by reducing medical utilization and costs. Payers should consider supporting the provision of these programs in community pharmacies.

	Appointment-based medication synchronization (ABMS) programs in community pharmacies have been shown to increase medication adherence in patients taking chronic medications.  

		Medication expenditures due to improved adherence associated with ABMS enrollment were offset by lower disease-specific medical costs. 

		Economic analyses suggest that ABMS programs offer a significant cost-benefit to payers. 

		Payers should consider supporting the provision of ABMS programs in community pharmacies.

Medication nonadherence is a major barrier to the provision of effective pharmacotherapy in patients with chronic conditions, and it is also associated with negative health outcomes and increased risks of hospitalization and mortality in patients with a variety of disease states, including cardiovascular conditions and diabetes.

 It is estimated that 33% to 69% of medicine-related hospitalizations are caused by poor adherence.

 Additionally, medication nonadherence accounts for projected annual US healthcare expenditures of $100 to $300 billion

; improving adherence, on the other hand, has been projected to result in annual per-person savings ranging from $1000 to over $7000 depending on the disease state.

 These savings reflect the association between poor adherence and increased nursing home admissions, physician visits, and hospitalizations and are robust even after controlling for healthy adherer behaviors.

Although studies vary in their estimated rates of nonadherence for long-term medications, most studies report adherence at approximately 50%.

 Rates of adherence tend to decline over time and are lower in patients who are prescribed multiple chronic medications.

 Adherence appears to be similarly low among patients with hypertension, type 2 diabetes, or hyperlipidemia.

Causes of medication nonadherence are multifactorial and often involve interconnecting patient, treatment plan, and healthcare system factors.

 Efforts to improve adherence often fail to achieve long-term desired results because they are too narrow in scope. Interventions, such as drug reminder packaging, mobile text messaging, and written and oral education, have inconsistent impact on both measures of adherence and clinical outcomes.

 Even when the scope of interventions is more ambitious, as with comprehensive medication therapy management, programs are not sustainable because they are often labor-intensive and costly.

Pharmacists are well-positioned to impact patient adherence, particularly in community pharmacy settings.

 Regular pharmacist—patient communication and monitoring has consistently been linked to improved adherence.

 Still, current community pharmacy efforts at counseling, monitoring, and education show variable rates of success.

Appointment-based medication synchronization (ABMS)—a system that offers individualized solutions to patients’ medication-related barriers&mdash;has been suggested as an effective and sustainable way of improving medication adherence in community pharmacies.

 In ABMS, pharmacists work with patients to synchronize their chronic medications to be filled on a single day each month. Prior to this date every month, pharmacists review patients’ medications, address patient concerns, and discuss any changes to the medication regimen. This system is designed to simplify the complexity of patients’ medication regimens and provide opportunities for consistent pharmacist—patient communications, which can help to clarify, modify, and enhance patient therapy. Communications with physicians are also enhanced through a formal process of physician contact regarding patient enrollment in the program and periodic calls to address medication therapy issues.

ABMS has demonstrated significant impact on patient adherence and persistence for chronic medications.

 A study in rural pharmacies in the midwestern United States showed that patients enrolled in an ABMS program who newly started a chronic medication had 3.4 to 6.1 times greater odds of adherence over a 1-year period than matched comparisons.

 Another study, of Ohio pharmacies with patients who had been taking chronic medicines for 6 months or more, indicated 2.3 to 3.6 times greater odds of adherence over a 1-year period with ABMS.

 These studies indicate that ABMS can be effective in improving medication adherence and, thereby, possibly improve health outcomes; however, there have been no analyses of the economic consequences of these programs.

The objective of this study was to model the economic impact of ABMS in community pharmacies for patients taking medications to prevent negative outcomes associated with diabetes, hypertension, and hyperlipidemia. The analysis was conducted from the perspective of a healthcare payer who wants to quantify the value to chronic disease populations of individuals enrolling in ABMS programs offered by community pharmacies.

The patients studied in the ABMS program consisted of adults who had been taking chronic medicines for 6 months or more and received at least 2 refills for at least 1 of 6 types of chronic disease medication categories. The medication classes studied were angiotensin-converting enzyme (ACE) inhibitors/angiotensin receptor blockers (ARBs), beta-blockers (BBs), dihydropyridine calcium channel blockers (DCCBs), thiazide diuretics, metformin, and statins. Patients who opted into the ABMS program were matched with control patients who received standard pharmacy dispensing services. Matching was done according to patient history of prior adherence behavior, medication class, age, gender, and geographic region.

) was constructed to model the cost-benefit of ABMS programs when compared with standard community pharmacy dispensing practices. The results of separate cost-benefit analyses for each medication class were presented with benefit-cost ratios calculated as follows:

Total Disease-Specific Direct Medical Costs Saved Due to Improved Medication Adherence Associated With ABMS (Diabetes, Hypertension, Hyperlipidemia) /

Total Medication Costs Added Due to Improved Medication Adherence Associated With ABMS

The model estimated, in US dollars, the benefit of the program on reduced disease-specific health expenditures over a 1-year period, relative to additional medication costs. Program benefits came from projecting how improvements in medication adherence due to the program would reduce medical costs for the treatment of the disease state associated with each medication class. This was done by matching adherence levels to chronic medications reported in an ABMS study,

 with research linking the same adherence with disease-related medical costs (

 Program costs were estimated based on the average cost per prescription refill and the number of additional fills due to improved adherence.

Adherence data for the base-case model came from the Ohio ABMS study of individuals on the chronic medications for at least 6 months.

 The proportion of days covered (PDC)—a ratio of the number of days covered by prescription fills divided by the total number of days in a study period&mdash;was used to measure adherence. PDC scores range from 0 to 1, with larger proportions indicating greater adherence. The PDC scores for patients from the study

 were stratified into 5 categories (PDC scores of 1%-20%, 21%-40%, 41%-60%, 61%-80%, and 81%-100%) to match utilization data in the study linking medication adherence with disease-related medical costs.

To model the relationship between medication adherence and disease-specific medical costs, indications needed to be assigned to the medication classes. The indication for ACE inhibitors/ARBs, BBs, DCCBs, and thiazide diuretics was assumed to be hypertension.

 Metformin and statins were assumed to be treating diabetes and hyperlipidemia, respectively. This allowed each of the 5 levels of adherence (1%-20%, 21%-40%, 41%-60%, 61%-80%, 81%-100%) to be matched with data from research linking these medication adherence levels with disease-related healthcare costs.

Additional costs associated with ABMS in the base case came from the increased medication costs that resulted from a higher number of annual medication refills. In the calculation of medication cost per fill, the price of the medication from each class with the highest total prescriptions in 2012 was assumed to be representative of the entire class.

 These representative drugs were lisinopril (ACE inhibitors/ARBs), simvastatin (statins), metoprolol (BBs), amlodipine (DCCBs), hydrochlorothiazide (thiazide diuretics), and metformin (diabetic medications). Cost per fill was calculated at an assumed cost of average wholesale price (AWP) minus 70% to reflect generic drug pricing.

Sensitivity analyses were conducted on key variables in the model. These variables included the relative effectiveness of ABMS compared with usual care on medication adherence, cost of chronic medications, medical costs, patient cost sharing, and addition of a service fee for the program.

Adherence data for comparing ABMS with controls are presented in 

. Significantly more patients in the ABMS program had PDC scores of 81% to 100%, whereas patients in the comparison group had more patients in categories with lower PDC scores.

 shows disease-related medical costs for levels of medication adherence adjusted to 2015 costs, according to the medical inflation index.

 With the exception of drug costs, which increased with greater adherence, direct medical costs were much lower, on average, for patients with higher PDC scores.

Benefit-cost ratios for 6 medication classes were reported (

). In base-case analyses of the cost-benefit, ABMS enrollment was associated with slight increases in medication expenditures due to improved adherence, but lower disease-specific medical costs. Medical savings per additional dollar spent on medications ranged from $1.25 to almost $37 depending on the medication class. ABMS yielded the greatest benefit relative to costs for metformin and statins and lower benefits relative to costs for thiazide diuretics and ACE inhibitors/ARBs.

One-way sensitivity analyses varied the medication costs from as low as Veterans’ Health Administration (VA) costs, obtained from the National Acquisition Center website, to as high as the AWP. Additional medication costs included in the sensitivity analyses included AWP minus 50% (AWP — 50%) and AWP minus 30% (AWP – 30%) (Table 4).

 In additional 1-way sensitivity analyses, disease-specific medical costs and the PDC distribution of ABMS patients were each increased and decreased by 20%. (

The impact of adding a service fee to ABMS programs was also examined in sensitivity analyses. ABMS is currently offered free of charge by most pharmacies, so the effect of annual per-patient fees of $100, $150, and $200 for program enrollment was explored in sensitivity analyses. In addition, co-payments of $5 and $10 per fill were included in sensitivity analyses to reflect average cost-sharing arrangements with patients.

 Discounting was not performed because both costs and outcomes occurred within a 1-year period.

In sensitivity analyses, the benefit-cost ratio of ABMS was most sensitive to drug prices (Table 5). As drug prices were lowered to VA pricing, estimated savings per additional dollar spent on medications ranged from $40 to $301. Favorable cost-benefit findings were robust for metformin, statins, and BBs. Cost-benefit was no longer favorable for thiazides at a drug price of AWP — 50%, ACE inhibitors/ARBs at AWP – 30%, and DCCBs at AWP. With the introduction of patient cost sharing through a $10 co-pay, benefit-cost ratios increased from 3.8 to 1 up to 59 to 1, depending on the drug class and assuming that co-pays did not reduce medication adherence. Cost-benefit was robust to changes in medical costs and ABMS effectiveness; however, with the introduction of payer reimbursements for ABMS, benefit-cost ratios remained favorable only for metformin and statins.

This study quantifies the cost-benefit of an ABMS model to improve adherence among patients prescribed chronic medications. Previously studied interventions to improve nonadherence often lack reliable effectiveness or contribute to higher overall costs to a payer or provider. ABMS has a demonstrated impact on improving adherence and persistence to chronic medications,

 which can increase annual medication costs to a payer on account of increased annual medication refills. This study calculated the overall disease-related healthcare savings attributed to improved adherence due to ABMS and analyzed the cost-benefit of ABMS compared with standard pharmacy dispensing from a payer perspective.

Few studies have used cost-benefit analyses to model the costs and outcomes of community pharmacy-based adherence interventions, and even fewer have taken a payer perspective.

 This study found that, due to improved adherence with ABMS, the disease-related medical savings per additional dollar spent on medications ranged from $1.25 to nearly $37 for 6 classes of chronic medications. These results suggest that payer partnerships with pharmacies offering ABMS are cost-beneficial and provide a positive return on investment.

ABMS works within the existing framework of medication dispensing in a community pharmacy setting to emphasize proactive medication management and consistent patient—provider communication. Because it can be incorporated into a pharmacy workflow, the nondrug cost of ABMS programs is minimal to the pharmacy and is provided free of charge to patients and payers. The combined low cost and high effectiveness of ABMS promotes more favorable cost-benefit ratios than expensive, but effective, educational and management interventions

 and low-cost, but less effective, electronic and reminder interventions.

The addition of pharmacist compensation to ABMS programs was not justified in this economic model. Annual per-patient fees were not made up by medical savings of negative health consequences, although the results might change for populations who are at greater risk of chronic illnesses or if the analysis looked at a time period longer than 1 year. Furthermore, this analysis was limited to separate analyses for each medication class, when patients with diabetes and hypertension take, on average, 4.1 and 1.7 disease-related prescriptions, respectively.

The widespread implementation of ABMS faces a number of barriers. Pharmacy benefit managers (PBMs) may not be incentivized to support ABMS under some business models. Additionally, ABMS would not benefit PBMs whose performance is measured solely on medication cost, as medication costs increase with improved adherence. Here, the disease-specific medical savings would show up on the income statements of other payers. PBM disincentives might also exist for ABMS programs offered by pharmacies that are out-of-network. ABMS programs might hinder PBM efforts to shift dispensing to mail order services or influence terms of contract for rebates. 

This research included several limitations. The adherence data was collected from the implementation of ABMS in a small pharmacy chain offering services within a limited geography in Ohio. The impact of ABMS on adherence may not be duplicated for other populations in other settings, although ABMS programs offered by other pharmacies in different geographic locations have shown similar effectiveness.

This study used data that reported associations between ABMS programs and adherence. The participants in the ABMS program opted into the program, which may have made them more likely or motivated to adhere to their medications. Matching ABMS patients to control patients based on prior adherence behavior and demographics aimed to minimize this potential bias. The analysis also did not control for other potential influences on medication adherence, including socioeconomic and insurance status, regimen complexity, and patient health status. Although increasing and decreasing the effectiveness of ABMS by 20% in sensitivity analyses did not substantially change the benefit-cost ratios, the impact of unmeasured confounders and self-selection bias on the association between ABMS programs and adherence is not known.

Finally, this study used data that reported associations between medication adherence and disease-related costs based on the findings of an observational study, and the design of that study has important limitations.

 In their study of the association between medication adherence and healthcare costs, Sokol et al adjusted for demographic and health status variables, but the impact of prior adherence behavior and the healthy adherer effect on their findings is not known. These potential confounders may have biased the results of their observational study toward overestimating the association between improved adherence and lower healthcare costs. However, compared to a study by Roebuck et al,

 which employed more rigorous linear fixed-effects modeling to account for the endogeneity of adherence, the Sokol et al study reports smaller decreases in healthcare costs associated with improved adherence. Beyond providing a more conservative estimate of the association between adherence and medical costs compared with that reported by Roebuck et al, the use of data from the study by Sokol et al in this model provided the opportunity to consider in the cost-benefit model the prescription and medical costs associated with 5, rather than 2, adherence categories.

Additionally, disease-related costs by adherence level were reported over a 1-year time frame. The conditions studied—diabetes, hypertension, and hyperlipidemia&mdash;are chronic in nature and are linked to long-term sequelae, including myocardial infarction, stroke, and kidney disease. The limited 1-year time frame utilized in this study may have underestimated the impact of ABMS on long-term adverse health events associated with nonadherence in chronic conditions.

This research reports the cost-benefit of a synchronization and appointment-based program for 6 classes of chronic medications. The adherence data for patients with ABMS-based care and usual dispensing practices were linked to previously published, claims-based data reporting the disease-specific medical costs associated with 5 levels of adherence. The direct effect of synchronization, as it relates to patient outcomes and costs, has not been reported. Future research is needed to explore the impact of ABMS on adherence, costs, and outcomes in the same population.

The cost-benefit of maintaining an ABMS program from a pharmacy perspective should also be explored. Synchronization may improve control of medication inventory and efficient personnel scheduling. Improved adherence may also result in increased refill revenue. The impact of ABMS on front-end sales is unknown. ABMS may improve patient loyalty, but it may also reduce up-front sales due to fewer monthly pharmacy visits.

Additional research could focus on expanding ABMS programs to include other chronic disease states, including chronic obstructive pulmonary disease

 for which other adherence interventions have shown cost-beneficial results. Previously documented interventions have had limited impact on adherence to medications for depression,

 which has been associated with significant increases in medical service utilization

; however, improved adherence may not reduce utilization.

 The cost-benefit of ABMS for depression is not known.

A recent clinical and economic analysis of the use of liraglutide in the treatment of type 2 diabetes concluded that adherent and persistent patients recorded higher total healthcare costs driven by higher pharmacy costs.

 This current study focused on the impact of ABMS on adherence to predominately generic oral medication classes. In these cases, an increase in medication usage confers minimal additional cost; expanding the use of injectable and biologic medications for chronic conditions may impact the benefit-cost ratios by substantially increasing the costs associated with improved adherence. Future research may focus on the cost-benefit of ABMS with more expensive drug classes.

To our knowledge, this is the first study to evaluate the cost-benefit of ABMS in community pharmacies. The results indicated that ABMS offers payers a positive return on investment. Although further research is needed to evaluate the long-term costs and outcomes of ABMS, payer partnerships with pharmacies offering ABMS may improve patient outcomes in a cost-beneficial manner.

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This study conducted a cost-benefit analysis of appointment-based medication synchronization for improving adherence in patients on chronic medications for hypertension, hyperlipidemia, and diabetes.

Cost-Benefit of Appointment-Based Medication Synchronization in Community Pharmacies

 Unwarranted geographic variation in spending has received intense scrutiny in the United States. However, few studies have compared variation in spending and surgical outcomes between the United States healthcare system and those of other nations. In this study, we compare the geographic variation in postsurgical outcomes and cost between the United States and Japan.

 This retrospective cohort study uses Medicare Part A data from the United States (2010-2011) and similar inpatient data from Japan (2012). Patients 65 years or older undergoing 1 of 5 surgeries (coronary artery bypass graft, abdominal aortic aneurysm repair, colectomy, pancreatectomy, or gastrectomy) were selected in the United States and Japan.

 Reliability- and case-mix—adjusted coefficient of variation (COV) values were calculated using hierarchical modeling and empirical Bayes techniques for the following 5 outcomes: postoperative mortality, the development of a complication, death after complication (failure to rescue), length of stay, and the cost of the hospitalization. Sensitivity analyses were also performed by calculating patient demographic-and case-mix–adjusted COV values for each outcome using weighted age- and sex-standardized values.

 The variability of the postsurgical outcomes was uniformly lower in the United States compared with Japan. Cost variation was consistently higher in the United States for all surgeries.

 Although the US healthcare system may be more inefficient regarding costs, the presence of higher geographic variation in postoperative care in Japan, relative to the United States, suggests that the observed geographic variation in the United States—both for health expenditures and outcomes&mdash;is not a unique manifestation of its structural shortcomings.

This investigation compares the amount of observed geographic variation in the United States and Japan for the surgical outcomes and costs of 5 common, higher-risk surgeries. Key findings include:

		The United States has less variation in surgical outcomes compared with Japan, but it has higher geographic cost variation.

		The surgical outcome variation in the United States is not unique; it exists even in a country that consistently ranks highly on public health quality measures. This variation is likely the result of unique structural inefficiencies in each healthcare system.

		There is an opportunity to reduce wasteful spending by standardizing the cost of care in the United States.

Countries around the world are attempting to contain increasing healthcare costs without sacrificing quality of care. Relative to other developed countries, the United States fares poorly on measures of both healthcare expenditure and health outcomes. Although the United States spent $7929 per person (16.4% of gross domestic product [GDP]) in 2010—the most of any Organisation for Economic Co-operation and Development (OECD) country&mdash;health outcomes, such as life expectancy, are among the worst in the developed world.

Much research has focused on small-area geographic variation in healthcare spending as evidence of inefficient healthcare in the United States.

 A recent report released by the Institute of Medicine (IOM) has affirmed that higher healthcare expenditures within a region are not related to better outcomes.

 In principle, the lack of relationship between spending and outcomes suggests that any unwarranted variation is potentially wasteful, and, if eliminated, might decrease costs while maintaining quality. Variations in healthcare expenditure have been identified as a potential area for up to a 30% reduction in waste (approximately $650 billion) in the US healthcare system.

Apart from issues of economic inefficiency, geographic variations in treatments and outcomes have important clinical and health policy implications. Outcome differences across regions are evidence for the presence of inequalities in care across regions, which represent a distinct and important problem in itself. Regional differences in quality of care may indicate opportunities to improve care for patients in places with worse outcomes. Identifying centers that have better outcomes than others and promoting the practice styles of those centers may be a practical way to improve patient outcomes.

Researchers have proposed several reasons for the observed geographic variation in the United States. Studies cite fragmentation of care,

 racial and socioeconomic barriers to care, and the diversity of financing and coverage options as reasons that the United States has unwarranted variation.

 Other studies have also investigated physician peer effects and the ways that social influences can affect medical decisions.

One premise underlying the interpretation of these findings is that the American healthcare system is unique in its inefficient stewardship of healthcare dollars. This naturally leads to a question: If the United States is so singularly ineffective at controlling costs and ensuring quality relative to other countries, then does it also experience singularly high geographic variation in costs and outcomes relative to other countries?

In this study, we compared the variability in postoperative outcomes and cost of hospitalization for 5 major surgeries in the United States and Japan. There are several key similarities and differences between the 2 countries. Japan is a modern OECD country that has access to technologies and treatments similar to those used in the United States; however, in 2010, Japan spent only $3204 per person (9.5% of GDP) on healthcare while attaining the highest average life expectancy at birth of any OECD country. Its system also provides universal access to care, and it is consistently well-graded from a public health standpoint.

 In other words, it does not have many of the shortcomings of the US healthcare system that potentially lead to unwarranted variation.

Although the prevalence of various surgical procedures has been studied, to our knowledge, there have been only few and limited comparisons of the variability in surgical outcomes among countries.

 Surgical outcomes as a quality metric are ideal to examine, given their well-established definitions and close association between the surgical process and the postoperative outcome. If the observed variability in Japan is low, the implication would be that the United States is truly unique. If, however, the variability in Japan is high, that would suggest that variability could be an inherent feature of healthcare systems. Our main aim is to study whether the United States is truly uniquely inefficient or whether geographic variation is part of the natural fabric of modern healthcare delivery.

Our analysis uses 2 data sources: a large Japanese administrative database and the Medicare 5% sample standard analytical file. The Japanese administrative database contains anonymous patient and encounter-level information collected over the 9-month period between April 1, 2012, and December 31, 2012. The data were originally collected from hospital forms that were submitted to the Japanese government as part of an ongoing effort to reform the healthcare reimbursement system in Japan.

 Hospitals that participate in this program are designated as Diagnosis Procedure Combination (DPC) hospitals, and together, they account for more than half of all the acute care beds in Japan. The DPC hospitals represent approximately 20% of all hospitals in Japan; they include all major academic medical centers and most of the nation’s larger hospitals. Our sample encompasses 100% of the patients from roughly half of these DPC hospitals. Please see eAppendix Figure A (

) for a comparison of our sample with the full set of DPC hospitals. The data contain information on patient status at admission and discharge; cost of admission; and details on surgeries, procedures, and drugs administered during the patient’s stay at the hospital. Medical clerks and licensed information managers generally oversee the collection and reporting of DPC data at individual hospitals to optimize the accuracy of the data. Studies correlating data from electronic health records and DPC data have shown very high compliance.

 In total, our data encompass information for approximately 5 million patients in more than 600 hospitals located across every region of Japan.

Data on patients in the United States were obtained from the Medicare 5% sample from 2010 to 2011. This is a random sampling of 5% of Medicare beneficiaries across all hospitals in the United States and has been used extensively to analyze different outcome measures.

 In our study, we analyze all inpatient claims by hospitals for this 5% sample. The information about each hospitalization includes dates of hospital admission and discharge, discharge status, disease(s) diagnosed, and cost of hospitalization.

Patients undergoing any of 5 relatively common, higher-risk surgeries (abdominal aortic aneurysm repair, coronary artery bypass grafting, colectomy, gastrectomy, or pancreatectomy) were included in the analysis. We follow the definitions outlined in the US Agency for Healthcare Research Quality’s Inpatient Quality Indicator guidelines when available.

 These surgeries have been previously used in related investigations studying the variability of surgical quality and outcomes.

 Japanese patients were selected using a Japan-specific surgery classification scheme (K-codes). K-codes were individually selected and verified to correspond to their 

International Classification of Diseases, Ninth Revision, Clinical Modification

) counterparts for this study; they have similarly been used in other studies to create comparable cohorts.

 Comorbidities were defined using Elixhauser classification definitions for both the US and Japanese cohorts. Prior validation studies have shown that both 

 coding algorithms produce similar estimates of comorbidity prevalence in administrative data.

 Patients were restricted to those 65 years or older.

We investigated 5 outcomes: in-hospital mortality, postsurgical complications, failure to rescue, length of stay, and cost of hospitalization. Postsurgical complications are defined using 

 codes in the US Medicare dataset, and corresponding 

 codes for the Japanese dataset. Complications included pulmonary failure, pneumonia, myocardial infarction, deep vein thrombosis/pulmonary embolism, acute renal failure, postoperative hemorrhage, surgical site infection, and gastrointestinal bleeding. The specific 

 codes for these complications have been previously validated as having reasonable agreement when comparing administrative data with the medical record.

 Failure to rescue is defined as death after any of the previously listed complications. Variations in cost in the United States were calculated using the Medicare Part A reimbursement to hospitals.

We subtracted disproportionate share payments, indirect medical education payments, and payments classified under total prospective payment system capital from United States cost totals, because these represent intended systemic cost variation and would inflate our variation estimates for the United States. Regions of comparison were defined for each country so that they were similar; variability was compared among states in the United States and among prefectures in Japan, graphically depicted in eAppendix Figure B.

In this study, we calculated outcome-specific coefficients of variation (COVs), defined as the sample standard deviation divided by the mean. The COV is a unitless measure that allows for a comparison of variation between a random variable with different means from 2 samples. For example, when used to measure the consistency of an elite athlete’s performance across multiple races, the COV will usually be between 1% and 2%.

Potential confounders, such as patient characteristics (age and gender for both countries’ cohorts, and additionally race for the US cohort), comorbidities, and urgent versus scheduled admissions, were included in all regression models. We additionally used hierarchical modeling techniques to adjust our COV estimates for reliability.

 Using random effects logistic regression models, we generated empirical Bayes predictions of the outcomes that were used to calculate our final COV values. This technique minimizes the impact of statistical outliers such as those from small-volume hospitals whose estimates can be considered less reliable than those of larger-volume hospitals. By variably shrinking the contribution of small-volume hospital estimates toward the average mortality rate across all hospitals, we are able to better estimate systematic, nonrandom variation as opposed to variation due to chance.

We additionally performed a sensitivity analysis by calculating age- and sex-standardized COV values for both countries to the 2000 US population, weighting all estimates by the number of procedures performed in each state and prefecture. These demographic- and case-mix—adjusted COVs were evaluated by performing multivariate regressions for each outcome of interest. We then calculated the adjusted COV (adjusted for age, gender, race, comorbidities, and urgency of admission) based on these regression estimates.

We assessed the geographic variation of in-hospital mortality, complication rate, failure to rescue rate, length of stay, and the cost of hospitalization for 5 major surgical procedures in the United States and Japan.

The Japanese surgical cohort had higher rates of colectomy and gastrectomy, together composing 74% of the analyzed surgeries versus 31% for the United States. The US surgical cohort was composed of a higher number of coronary artery bypass graft (CABG) procedures, representing 52% of the surgical cohort (

). Pancreatectomies were the least frequent surgery performed in both groups. Table 1 shows the raw descriptive statistics of each cohort, but they should not be used for comparison against each country as they do not take into account differing patient demographics and comorbidities between each country.

In comparing the United States and Japan’s reliability-adjusted COV values (

), the observed geographic variations among regions in Japan were higher than those of the United States for all 20 surgical outcome measures (4 outcomes for 5 surgeries). Our sensitivity analyses (

) reiterated these results, as the variation was higher in all 20 outcomes except for 1: there was lower variation in length of stay for colectomy in Japan. Of note, is that colectomy was the most frequently performed surgery in our analysis (41% of the total cohort) in Japan, but not in the United States (26% of the total cohort).

The variation in the cost of hospitalization was uniformly lower for Japan across all 5 surgeries for reliability-adjusted COVs. This was true in our sensitivity analysis as well. The level of cost variation between surgeries was similar across surgeries in Japan (adjusted COV values of 7.3 to 7.6), indicating that the specific type of surgery did not have much influence on the cost variability between regions. This is mostly true for the United States as well, as the adjusted COV values ranged from 21.7 to 22.8 with the exception of CABG with a COV of 25.3.

The level of variation for a given postsurgical outcome was similar across different surgeries in each country. For example, the approximate reliability-adjusted COVs for mortality across the 5 surgeries ranged from 15 to 17 in the United States, while ranging from 29 to 33 in Japan. The failure-to-rescue COV ranges from 16 to 19 in the United States and between 47 and 50 in Japan. One notable deviation from this pattern was length of stay in the United States. Four of 5 surgeries in the United States had a length-of-stay COV between 42 and 55, with the exception of CABG, which had a much lower COV at 29.

Our sensitivity analysis endorses the conclusions from our reliability-adjusted models, and it also demonstrates the importance of using the reliability-adjusted estimates. Though our conclusions remain the same, the estimates of variability are much higher and dispersed in our sensitivity analysis, especially for less frequently performed procedures such as pancreatectomy where small differences in outcomes could have large statistical manifestations (Table 3 and Figure 2).

In summary, the United States has lower variability for all postsurgical outcomes, but it has higher cost variability relative to Japan. The United States and Japan have low variability between surgeries for a given postsurgical outcome, suggesting that the differences in overall variation between the countries are not dependent on the specific surgery performed.

Much of the discussion around geographic variation in US healthcare expenditure and quality has focused singularly on the United States, with little work comparing the geographic variation in healthcare outcomes among other countries and the United States, especially for resource-intensive surgical procedures. Although previous studies have investigated whether the US healthcare system as a whole is uniquely inefficient compared with other countries,

 much of the literature around geographic variation does not address this topic, instead citing the inefficiency of the US healthcare system as a cause for geographic variation. This context is important when evaluating the causes and consequences of variation.

Healthcare efficiency has previously been framed as a combination of productive and allocative efficiency. Productive efficiency refers to the impact of healthcare given a series of inputs such as physicians and hospitals, and allocative efficiency measures the benefits from the marginal cost of healthcare versus the cost of other goods. In this analysis, we characterize both the variation in healthcare outcomes (outputs) and the variation in procedure costs (inputs) across each country, therefore addressing both aspects of efficiency described above. Higher outcome variations reflect lower productive efficiency—that is, given the same level of healthcare inputs, there are differences in achieving desirable outcomes. In the same manner, higher cost variations reflect lower allocative efficiency&mdash;that is, in order to achieve the desirable outcome, the amount and therefore the value of each healthcare dollar spent varies greatly.

In this study, we demonstrate that although cost varies more in the United States compared with Japan, all postsurgical outcome measures show less variability in the United States. This suggests that geographic variation in outcomes is not a manifestation of US-specific inefficiencies, but is more likely an inherent part of healthcare delivery and a shared characteristic among healthcare systems.

Our conclusions are in line with the results of previous studies comparing the United States, United Kingdom, and Germany that show that among a group of medical conditions, no single country consistently spent less money and achieved better health outcomes across different indications.

 Our finding suggests that every country struggles in its own way to achieve productive efficiency in healthcare. In other words, building a healthcare system where the least expenditures result in the best outcomes is a universal problem.

The fact that the United States had higher observed cost variation than Japan is also consistent with previous analyses. In 2008, a report by the Congressional Budget Office concluded that the geographic variation in healthcare spending was higher in the United States than in Canada and the United Kingdom, citing the fact that the financing of healthcare is more centralized in those countries.

 In Japan, the government centrally controls healthcare costs by budgeting and setting standard reimbursement rates for procedures. Although our results show that there is more cost variation in the United States compared with Japan, this is unlikely to represent US-specific unwarranted variation in healthcare resource use. A recent report by the IOM found that if geographic variation were eliminated for postacute care services, variation in Medicare spending would fall by 73%.

 Much of the geographic variation in expenditure in the United States is actually attributable to postacute care and not to excess use of care during hospitalizations.

The most likely reason for Japan’s increased outcomes variability compared with that of the United States is the fact that Japan has many more hospitals per capita than the United States. In 2010, Japan had 68 hospitals per million individuals compared with 19 hospitals per million in the United States—a more than 3-fold difference.

 This translates into surgeons performing high-risk procedures, such as those in this study, relatively infrequently. Similarly, hospital staff may have less experience caring for these postoperative patients and are likely to be less prepared for both preventing and resolving postoperative complications. There is an extensive literature, both in the United States and in Japan, on the benefits of centralized surgical centers, where increased surgical and postoperative care experience, as well as differences in staffing, can translate to better outcomes for patients.

Other reasons that explain the high variability in Japan include the less-centralized regulation of hospitals and medical care, and the lower level of regulation over physicians’ training and development.

 In 1 study, adherence to clinical practice guidelines for cholangitis were measured in hospitals across Japan. Results showed markedly varied compliance that correlated directly with in-hospital mortality rates.

 Patients in Japan have universal access to any facility, and in general they do not require referrals to visit a specialist. Furthermore, physicians and nurses are currently licensed for life; they do not have requirements for license renewal or continuing medical education.

 Both of these factors could contribute to higher variability in quality of care that patients could receive, especially for higher-risk, lower-volume procedures.

Previous studies demonstrate that clinical decision making is affected by the supply of specialists, local training frameworks, and regulatory factors, all of which are more fragmented in Japan than in the United States. In addition, geographic variation in rates of surgery reflect physician beliefs about the level of appropriateness of the surgery and the extent to which patients have a say in their treatment.

 The decentralized nature of Japan’s healthcare system, with its many hospitals and unstructured referral system, presumably exacerbates variation by creating more physician “micro-communities” that lead to variable care.

Potential drivers for more homogeneous outcome performance in the United States may arise from the fact that the United States has greater standardization of the surgical training curriculum relative to Japan, as there is no standardized national surgical curriculum in Japan or even the equivalent of the Accreditation Council for Graduate Medical Education.

 The fact that the United States has a multiplicity of accrediting organizations that all work toward achieving a higher quality of care also undoubtedly plays a role.

 The existence of managed care in the United States is unique, and the role that national payers have in emphasizing quality of care also encourages more uniform quality of care across the country. Public disclosure of surgical outcomes in the United States may also influence quality, as public reporting has been extensively studied as an effective quality improvement strategy by encouraging changes in the behavior of providers.

 However, with respect to surgical outcomes the evidence is mixed.

 The higher variation in United States costs could be due to regional adjustments and variation in diagnoses billed for the same procedure.

POLICY

Compared with Japan, the United States has substantially less geographic variation in surgical outcomes, but it has higher variation in cost.

Geographic Variation in Surgical Outcomes and Cost Between the United States and Japan

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.

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.

September 2016

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