Using the Kitagawa Decomposition to Measure Overall-and Individual Facility Contributions to-Within-facility and Between-facility Differences: Analyzing Racial and Ethnic Wait Time Disparities in the Veterans Health Administration.

BACKGROUND: Identifying whether differences in health care disparities are due to within-facility or between-facility differences is key to disparity reductions. The Kitagawa decomposition divides the difference between 2 means into within-facility differences and between-facility differences that are measured on the same scale as the original disparity. It also enables the identification of facilities that contribute most to within-facility differences (based on facility-level disparities and the proportion of patient population served) and between-facility differences. OBJECTIVES: Illustrate the value of a 2-stage Kitagawa decomposition to partition a disparity into within-facility and between-facility differences and to measure the contribution of individual facilities to each type of difference. SUBJECTS: Veterans receiving a new outpatient consult for cardiology or orthopedic services during fiscal years 2019-2021. MEASURES: Wait time for a new-patient consult. METHODS: In stage 1, we predicted wait time for each Veteran from a multivariable model; in stage 2, we aggregated individual predictions to determine mean adjusted wait times for Hispanic, Black, and White Veterans and then decomposed differences in wait times between White Veterans and each of the other groups. RESULTS: Noticeably longer wait times were experienced by Hispanic Veterans for cardiology (2.32 d, 6.8% longer) and Black Veterans for orthopedics (3.49 d, 10.3% longer) in both cases due entirely to within-facility differences. The results for Hispanic Veterans using orthopedics illustrate how positive within-facility differences (0.57 d) can be offset by negative between-facility differences (-0.34 d), resulting in a smaller overall disparity (0.23 d). Selecting 10 facilities for interventions in orthopedics based on the largest contributions to within-in facility differences instead of the largest disparities resulted in a higher percentage of Veterans impacted (31% and 12% of Black and White Veterans, respectively, versus 9% and 10% of Black and White Veterans, respectively) and explained 21% of the overall within-facility difference versus 11%. CONCLUSIONS: The Kitagawa approach allows the identification of disparities that might otherwise be undetected. It also allows the targeting of interventions at those facilities where improvements will have the largest impact on the overall disparity.

Comparing Postoperative Readmission Rates Between Veterans Receiving Total Knee Arthroplasty in the Veterans Health Administration Versus Community Care.

BACKGROUND: There are growing concerns that Veterans' increased use of Veterans Health Administration (VA)-purchased care in the community may lead to lower quality of care. OBJECTIVE: We compared rates of hospital readmissions following elective total knee arthroplasties (TKAs) that were either performed in VA or purchased by VA through community care (CC) at both the national and facility levels. METHODS: Three-year cohort study using VA and CC administrative data from the VA's Corporate Data Warehouse (October 1, 2016-September 30, 2019). We obtained Medicare data to capture readmissions that were paid by Medicare. We used the Centers for Medicare and Medicaid Services (CMS) methods to identify unplanned, 30-day, all-cause readmissions. A secondary outcome, TKA-related readmissions, identified readmissions resulting from complications of the index surgery. We ran mixed-effects logistic regression models to compare the risk-adjusted odds of all-cause and TKA-related readmissions between TKAs performed in VA versus CC, adjusting for patients' sociodemographic and clinical characteristics. PRINCIPAL FINDINGS: Nationally, the odds of experiencing an all-cause or TKA-related readmission were significantly lower for TKAs performed in VA versus CC (eg, the odds of experiencing an all-cause readmission in VA were 35% of those in CC. At the facility level, most VA facilities performed similarly to their corresponding CC providers, although there were 3 VA facilities that performed worse than their corresponding CC providers. CONCLUSIONS: Given VA's history in providing high-quality surgical care to Veterans, it is important to closely monitor and track whether the shift to CC for surgical care will impact quality in both settings over time.

Interpretability, credibility, and usability of hospital-specific template matching versus regression-based hospital performance assessments; a multiple methods study.

BACKGROUND: Hospital-specific template matching (HS-TM) is a newer method of hospital performance assessment. OBJECTIVE: To assess the interpretability, credibility, and usability of HS-TM-based vs. regression-based performance assessments. RESEARCH DESIGN: We surveyed hospital leaders (January-May 2021) and completed follow-up semi-structured interviews. Surveys included four hypothetical performance assessment vignettes, with method (HS-TM, regression) and hospital mortality randomized. SUBJECTS: Nationwide Veterans Affairs Chiefs of Staff, Medicine, and Hospital Medicine. MEASURES: Correct interpretation; self-rated confidence in interpretation; and self-rated trust in assessment (via survey). Concerns about credibility and main uses (via thematic analysis of interview transcripts). RESULTS: In total, 84 participants completed 295 survey vignettes. Respondents correctly interpreted 81.8% HS-TM vs. 56.5% regression assessments, p < 0.001. Respondents "trusted the results" for 70.9% HS-TM vs. 58.2% regression assessments, p = 0.03. Nine concerns about credibility were identified: inadequate capture of case-mix and/or illness severity; inability to account for specialized programs (e.g., transplant center); comparison to geographically disparate hospitals; equating mortality with quality; lack of criterion standards; low power; comparison to dissimilar hospitals; generation of rankings; and lack of transparency. Five concerns were equally relevant to both methods, one more pertinent to HS-TM, and three more pertinent to regression. Assessments were mainly used to trigger further quality evaluation (a "check oil light") and motivate behavior change. CONCLUSIONS: HS-TM-based performance assessments were more interpretable and more credible to VA hospital leaders than regression-based assessments. However, leaders had a similar set of concerns related to credibility for both methods and felt both were best used as a screen for further evaluation.

Did Access to Care Improve Since Passage of the Veterans Choice Act?: Differences Between Rural and Urban Veterans.

BACKGROUND: The 2014 Veterans Choice Program aimed to improve care access for Veterans through expanded availability of community care (CC). Increased access to CC could particularly benefit rural Veterans, who often face obstacles in obtaining medical care at the Veterans Health Administration (VHA). However, whether Veterans Choice Program improved timely access to care for this vulnerable population is understudied. OBJECTIVES: To examine wait times among rural and urban Veterans for 5 outpatient specialty care services representing the top requests for CC services among rural Veterans. RESEARCH DESIGN: Retrospective study using VHA and CC outpatient consult data from VHA's Corporate Data Warehouse in Fiscal Year (FY) 2015 (October 1, 2014 to September 30, 2015) and FY2018 (October 1, 2017 to September 30, 2018). SUBJECTS: All Veterans who received a new patient consult for physical therapy, cardiology, optometry, orthopedics, and/or dental services in VHA and/or CC. MEASURES: Wait time, care setting (VHA/CC), rural/urban status, sociodemographics, and comorbidities. RESULTS: Our sample included 1,112,876 Veterans. Between FY2015 and FY2018, mean wait times decreased for all services for both rural and urban Veterans; declines were greatest in VHA (eg, mean optometry wait times for rural Veterans in VHA vs. CC declined 8.3 vs. 6.4 d, respectively, P<0.0001). By FY2018, for both rural and urban Veterans, CC mean wait times for most services were longer than VHA wait times. CONCLUSIONS: Timely care access for all Veterans improved between FY15 and FY18, particularly in VHA. As expansion of CC continues under the MISSION Act, more research is needed to evaluate quality of care across VHA and CC and what role, if any, wait times play.

Rural Veterans' Experiences With Outpatient Care in the Veterans Health Administration Versus Community Care.

BACKGROUND: The 2014 Veterans Access, Choice and Accountability Act was intended to improve Veterans' access to timely health care by expanding their options to receive community care (CC) paid for by the Veterans Health Administration (VA). Although CC could particularly benefit rural Veterans, we know little about rural Veterans' experiences with CC. OBJECTIVE: The objective of this study was to compare rural Veterans' experiences with CC and VA outpatient health care services to those of urban Veterans and examine changes over time. RESEARCH DESIGN: Retrospective, cross-sectional study using data from the Survey of Healthcare Experiences of Patients (SHEP) and VA Corporate Data Warehouse. Subjects: All Veterans who responded to the SHEP survey in Fiscal Year (FY) 16 or FY19. MEASURES: Outcomes were 4 measures of care experience (Access, Communication, Coordination, and Provider Rating). Independent variables included care setting (CC/VA), rural/urban status, and demographic and clinical characteristics. RESULTS: Compared with urban Veterans, rural Veterans rated CC the same (for specialty care) or better (for primary care). Rural Veterans reported worse experiences in CC versus VA, except for specialty care Access. Rural Veterans' care experiences improved between FY16 and FY19 in both CC and VA, with greater improvements in CC. CONCLUSIONS: Rural Veterans' reported comparable or better experiences in CC compared with urban Veterans, but rural Veterans' CC experiences still lagged behind their experiences in VA for primary care. As growing numbers of Veterans use CC, VA should ensure that rural and urban Veterans' experiences with CC are at least comparable to their experiences with VA care.

Comparing Driving Miles for Department of Veterans Affairs-delivered Versus Department of Veterans Affairs-purchased Cataract Surgery.

BACKGROUND: The Veterans Choice Act of 2014 increased the number of Veterans eligible for Department of Veterans Affairs (VA)-purchased care delivered in non-VA community care (CC) facilities. Driving >40 miles from home to a VA facility is a key eligibility criterion for CC. It remains unclear whether this policy change improved geographical access by reducing drive distance for Veterans. OBJECTIVES: Describe the driving distance for Veterans receiving cataract surgery in VA and CC facilities, and if they visited the closest-to-home facility or if they drove to farther facilities. SUBJECTS: Veterans who had cataract surgery in federal fiscal year 2015. MEASURES: We calculated driving miles to the Closest VA and CC facilities that performed cataract surgeries, and to the location where Veterans received care. RESULTS: A total of 61,746 Veterans received 83,875 cataract surgeries. More than 50% of CC surgeries occurred farther than the Closest CC facility providing cataract surgery (median Closest CC facility 8.7 miles vs. Actual CC facility, 19.7 miles). Most (57%) Veterans receiving cataract surgery at a VA facility used the Closest VA facility (median Closest VA facility 28.1 miles vs. Actual VA facility at 31.2 miles). In all, 26.1% of CC procedures occurred in facilities farther away than the Closest VA facility. CONCLUSIONS: Although many Veterans drove farther than needed to get cataract surgery in CC, this was not true for obtaining care in the VA. Our findings suggest that there may be additional reasons, besides driving distance, that affect whether Veterans choose CC and, if they do, where they seek CC.

Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

BACKGROUND: Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings. OBJECTIVE: The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality. RESEARCH DESIGN: Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality. SUBJECTS: A total of 556,266 hospitalizations at 122 VA hospitals in 2017. MEASURES: A number of comparison hospitals identified per hospital; 30-day mortality. RESULTS: Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals. CONCLUSIONS: Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.

County-level Predictors of Growth in Community-based Primary Care Use Among Veterans.

BACKGROUND: The 2014 Choice Act expanded the Veterans Health Administration's (VA) capacity to purchase services for VA enrollees from community providers, yet little is known regarding the growth of Veterans' primary care use in community settings. OBJECTIVES: The aim was to measure county-level growth in VA community-based primary care (CBPC) penetration following the Choice Act and to assess whether CBPC penetration increased in rural counties with limited access to VA facilities. DATA AND SAMPLE: A total of 3132 counties from VA administrative data from 2015 to 2018, Area Health Resources Files, and County Health Rankings. ANALYSIS: We defined the county-level CBPC penetration rate as the proportion of VA-purchased primary care out of all VA-purchased primary care (ie, within and outside VA). We estimated county-level multivariate linear regression models to assess whether rurality and supply of primary care providers and health care facilities were significantly associated with CBPC growth. RESULTS: Nationally, CBPC penetration rates increased from 2.7% in 2015 to 7.3% in 2018. The rurality of the county was associated with a 2-3 percentage point (pp) increase in CBPC penetration growth (P<0.001). The presence of a VA facility was associated with a 1.7 pp decrease in CBPC penetration growth (P<0.001), while lower primary care provider supply was associated with a 0.6 pp increase in CBPC growth (P<0.001). CONCLUSION: CBPC as a proportion of all VA-purchased primary care was small but increased nearly 3-fold between 2015 and 2018. Greater increases in CBPC penetration were concentrated in rural counties and counties without a VA facility, suggesting that community care may enhance primary care access in rural areas with less VA presence.

Disparities in Utilization of Ambulatory Cholecystectomy: Results From Three States.

BACKGROUND: Inpatient cholecystectomy is associated with higher cost and morbidity relative to ambulatory cholecystectomy, yet the latter may be underutilized by minority and underinsured patients. The purpose of this study was to examine the effects of race, income, and insurance status on receipt of and outcomes following ambulatory cholecystectomy. MATERIALS AND METHODS: Retrospective observational cohort study of patients 18-89 undergoing cholecystectomy for benign indications in Florida, Iowa, and New York, 2011-2014 using administrative databases. The primary outcome of interest was odds of having ambulatory cholecystectomy; secondary outcomes included intraoperative and postoperative complications, and 30-day unplanned admissions following ambulatory cholecystectomy. RESULTS: Among 321,335 cholecystectomies, 190,734 (59.4%) were ambulatory and 130,601 (40.6%) were inpatient. Adjusting for age, sex, insurance, income, residential location, and comorbidities, the odds of undergoing ambulatory versus inpatient cholecystectomy were significantly lower in black (aOR = 0.71, 95% CI [0.69, 0.73], P< 0.001) and Hispanic (aOR = 0.71, 95% CI [0.69, 0.72], P< 0.001) patients compared to white patients, and significantly lower in Medicare (aOR = 0.77, 95% CI [0.75, 0.80] P < 0.001), Medicaid (aOR = 0.56, 95% CI [0.54, 0.57], P< 0.001) and uninsured/self-pay (aOR = 0.28, 95% CI [0.27, 0.28], P< 0.001) patients relative to privately insured patients. Patients with Medicaid and those classified as self-pay/uninsured had higher odds of postoperative complications and unplanned admission as did patients with Medicare compared to privately insured individuals. CONCLUSIONS: Racial and ethnic minorities and the underinsured have a higher likelihood of receiving inpatient as compared to ambulatory cholecystectomy. The higher incidence of postoperative complications in these patients may be associated with unequal access to ambulatory surgery.

How hospitals select their patient safety priorities: An exploratory study of four Veterans Health Administration hospitals.

BACKGROUND: Hospitals face ongoing pressure to reduce patient safety events. However, given resource constraints, hospitals must prioritize their safety improvements. There is limited literature on how hospitals select their safety priorities. PURPOSE: The aim of this research was to describe and compare the approaches used by Veterans Health Administration (VA) hospitals to select their safety priorities. METHODOLOGY: Semistructured telephone interviews with key informants (n = 16) were used to collect data on safety priorities in four VA hospitals from May to December 2016. We conducted a directed content analysis of the interview notes using an organizational learning perspective. We coded for descriptive data on the approaches (e.g., set of cues, circumstances, and activities) used to select safety priorities, a priori organizational learning capabilities (learning processes, learning environment, and learning-oriented leadership), and emergent domains. For cross-site comparisons, we examined the coded data for patterns. RESULTS: All hospitals used multiple approaches to select their safety priorities; these approaches used varied across hospitals. Although no single approach was reported as particularly influential, all hospitals used approaches that addressed system level or national requirements (i.e., externally required activities). Additional approaches used by hospitals (e.g., responding to staff concerns of patient safety issues, conducting a multidisciplinary team investigation) were less connected to externally required activities and demonstrated organizational learning capabilities in learning processes (e.g., performance monitoring), learning environment (e.g., staff's psychological safety), and learning-oriented leadership (e.g., establishing a nonpunitive culture). PRACTICE IMPLICATIONS: Leaders should examine the approaches used to select safety priorities and the role of organizational learning in these selection approaches. Exclusively relying on approaches focused on externally required activities may fail to identify safety priorities that are locally relevant but not established as significant at the system or national levels. Organizational learning may promote hospitals' use of varied approaches to guide their selection of safety priorities and thereby benefit hospital safety improvement efforts.

Patient Possession of Excess Medication Supply in the VA: A Retrospective Database Study.

BACKGROUND: Medication overlap leading to medication excess is a form of therapeutic duplication, itself a type of potentially inappropriate prescribing. OBJECTIVE: To determine the prevalence of potential medication excess in the Veterans Health Administration (VHA) and identify associated medication-level, patient-level, and system-level factors. RESEARCH DESIGN: A retrospective database study. SUBJECTS: All veterans who received ≥1 prescription dispensed by a VHA pharmacy in fiscal year 2014. MEASURES: The primary outcome of "medication excess" was defined for each patient as the number of excess days' worth of medications for all overlap episodes (concurrently dispensed medications with the same name for >10 d). Predictors included medication-level, patient-level, and system-level factors. Multivariable negative binomial regression analyses estimated the rate ratio of each predictor with medication excess. RESULTS: Among 4,687,453 veterans, 64% had ≥1 medication overlap episodes. Patients were prescribed a median of 7 [interquartile range (IQR), 3-12] unique medications, had a median of 2 (IQR, 0-5) overlap episodes, and a median of 27 (IQR, 0-96) days of medication excess. In adjusted regression models, factors associated with greater risk of medication excess included having more comorbidities, multiple prescribers, a combination of filling locations (consolidated mail-order pharmacy vs. local pharmacy), and multiple prescription durations (≥90 d vs. less). CONCLUSIONS: Medication excess was high among VHA users, with nearly two-thirds of patients experiencing at least 1 duplicative medication. As systems such as mail-order pharmacies and 90-day supply are increasingly implemented to reduce costs and improve medication adherence, it is important to recognize the potential for systems-level inefficiencies and potentially inappropriate prescribing.

Tailoring an educational program on the AHRQ Patient Safety Indicators to meet stakeholder needs: lessons learned in the VA.

BACKGROUND: Given that patient safety measures are increasingly used for public reporting and pay-for performance, it is important for stakeholders to understand how to use these measures for improvement. The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) are one particularly visible set of measures that are now used primarily for public reporting and pay-for-performance among both private sector and Veterans Health Administration (VA) hospitals. This trend generates a strong need for stakeholders to understand how to interpret and use the PSIs for quality improvement (QI). The goal of this study was to develop an educational program and tailor it to stakeholders' needs. In this paper, we share what we learned from this program development process. METHODS: Our study population included key VA stakeholders involved in reviewing performance reports and prioritizing and initiating quality/safety initiatives. A pre-program formative evaluation through telephone interviews and web-based surveys assessed stakeholders' educational needs/interests. Findings from the formative evaluation led to development and implementation of a cyberseminar-based program, which we tailored to stakeholders' needs/interests. A post-program survey evaluated program participants' perceptions about the PSI educational program. RESULTS: Interview data confirmed that the concepts we had developed for the interviews could be used for the survey. Survey results informed us on what program delivery mode and content topics were of high interest. Six cyberseminars were developed-three of which focused on two content areas that were noted of greatest interest: learning how to use PSIs for monitoring trends and understanding how to interpret PSIs. We also used snapshots of VA PSI reports so that participants could directly apply learnings. Although initial interest in the program was high, actual attendance was low. However, post-program survey results indicated that perceptions about the program were positive. CONCLUSIONS: Conducting a formative evaluation was a highly important process in program development. The useful information that we collected through the interviews and surveys allowed us to tailor the program to stakeholders' needs and interests. Our experiences, particularly with the formative evaluation process, yielded valuable lessons that can guide others when developing and implementing similar educational programs.

Evaluating the Implementation of Project Re-Engineered Discharge (RED) in Five Veterans Health Administration (VHA) Hospitals.

BACKGROUND: Improving the process of hospital discharge is a critical priority. Interventions to improve care transitions have been shown to reduce the rate of early unplanned readmissions, and consequently, there is growing interest in improving transitions of care between hospital and home through appropriate interventions. Project Re-Engineered Discharge (RED) has shown promise in strengthening the discharge process. Although studies have analyzed the implementation of RED among private-sector hospitals, little is known about how hospitals in the Veterans Health Administration (VHA) have implemented RED. The RED implementation process was evaluated in five VHA hospitals, and contextual factors that may impede or facilitate the undertaking of RED were identified. METHODS: A qualitative evaluation of VHA hospitals' implementation of RED was conducted through semistructured telephone interviews with personnel involved in RED implementation. Qualitative data from these interviews were coded and used to compare implementation activities across the five sites. In addition guided by the Practical, Robust Implementation and Sustainability Model (PRISM), cross-site analyses of the contextual factors were conducted using a consensus process. RESULTS: Progress and adherence to the RED toolkit implementation steps and intervention components varied across study sites. A majority of contextual factors identified were positive influences on sites' implementation. CONCLUSION: Although the study sites were able to tailor and implement RED because of its adaptability, redesigning discharge processes is a significant undertaking, requiring additional support/resources to incorporate into an organization's existing practices. Lessons learned from the study should be useful to both VHA and private-sector hospitals interested in implementing RED and undertaking a care transition intervention.

Can Composite Measures Provide a Different Perspective on Provider Performance Than Individual Measures?

BACKGROUND: Composite measures, which aggregate performance on individual measures into a summary score, are increasingly being used to evaluate facility performance. There is little understanding of the unique perspective that composite measures provide. OBJECTIVE: To examine whether high/low (ie, high or low) performers on a composite measures are also high/low performers on most of the individual measures that comprise the composite. METHODS: We used data from 2 previous studies, one involving 5 measures from 632 hospitals and one involving 28 measures from 112 Veterans Health Administration (VA) nursing homes; and new data on hospital readmissions for 3 conditions from 131 VA hospitals. To compare high/low performers on a composite to high/low performers on the component measures, we used 2-dimensional tables to categorize facilities into high/low performance on the composite and on the individual component measures. RESULTS: In the first study, over a third of the 162 hospitals in the top quintile based on the composite were in the top quintile on at most 1 of the 5 individual measures. In the second study, over 40% of the 27 high-performing nursing homes on the composite were high performers on 8 or fewer of the 28 individual measures. In the third study, 20% of the 61 low performers on the composite were low performers on only 1 of the 3 individual measures. CONCLUSIONS: Composite measures can identify as high/low performers facilities that perform "pretty well" (or "pretty poorly") across many individual measures but may not be high/low performers on most of them.

Trends in the Purchase of Surgical Care in the Community by the Veterans Health Administration.

BACKGROUND: The 2014 implementation of the Veterans Choice Program increased opportunities for Veterans to receive care in the community. Although surgical care is a Veterans Health Administration (VHA) priority, little is known about the types of surgeries provided in the VHA versus those referred to community care (CC), and whether Veterans are increasing their use of surgical care through CC with these additional opportunities. OBJECTIVES: To examine national trends across VHA facilities in the frequencies and types of surgeries provided in the VHA and through CC, and explore the association between facilities' purchase of care with rurality and surgical complexity designation. RESEARCH DESIGN: Retrospective study using Veterans Administration (VA) outpatient and CC data from the VA's Corporate Data Warehouse (October 1, 2013-September 30, 2016). MEASURES: Veterans' demographics, outpatient surgeries, facility rurality, and surgical complexity. RESULTS: Our sample included 525,283 outpatient surgeries; 79% occurred in the VHA over the study timeframe. The proportion of CC surgeries increased from 16% in October 2013 to 29% in December 2014, and then subsequently declined, leveling off at 21% in June 2016 (trend, P<0.05). These trends varied by surgery type. Increases in CC surgeries were evident for 4 surgery types: cardiovascular, digestive, eye and ocular, and male genital surgeries (all trends, P<0.05). Rural and low-complexity facilities were more likely to purchase surgical CC than their urban and high-complexity counterparts (P<0.0001). CONCLUSIONS: Although the VHA remains the primary provider of surgical care for Veterans, Veterans Choice Program implementation increased Veterans' use of CC relative to the VHA for certain types of surgeries, potentially bringing challenges to the VHA in delivering and coordinating surgical care across settings.

A study to reduce readmissions after surgery in the Veterans Health Administration: design and methodology.

BACKGROUND: Hospital readmissions are associated with higher resource utilization and worse patient outcomes. Causes of unplanned readmission to the hospital are multiple with some being better targets for intervention than others. To understand risk factors for surgical readmission and their incremental contribution to current Veterans Health Administration (VA) surgical quality assessment, the study, Improving Surgical Quality: Readmission (ISQ-R), is being conducted to develop a readmission risk prediction tool, explore predisposing and enabling factors, and identify and rank reasons for readmission in terms of salience and mutability. METHODS: Harnessing the rich VA enterprise data, predictive readmission models are being developed in data from patients who underwent surgical procedures within the VA 2007-2012. Prospective assessment of psychosocial determinants of readmission including patient self-efficacy, cognitive, affective and caregiver status are being obtained from a cohort having colorectal, thoracic or vascular procedures at four VA hospitals in 2015-2017. Using these two data sources, ISQ-R will develop readmission categories and validate the readmission risk prediction model. A modified Delphi process will convene surgeons, non-surgeon clinicians and quality improvement nurses to rank proposed readmission categories vis-à-vis potential preventability. DISCUSSION: ISQ-R will identify promising avenues for interventions to facilitate improvements in surgical quality, informing specifications for surgical workflow managers seeking to improve care and reduce cost. ISQ-R will work with Veterans Affairs Surgical Quality Improvement Program (VASQIP) to recommend potential new elements VASQIP might collect to monitor surgical complications and readmissions which might be preventable and ultimately improve surgical care.

Postoperative 30-day Readmission: Time to Focus on What Happens Outside the Hospital.

OBJECTIVE: The aim of this study is to understand the relative contribution of preoperative patient factors, operative characteristics, and postoperative hospital course on 30-day postoperative readmissions. BACKGROUND: Determining the risk of readmission after surgery is difficult. Understanding the most important contributing factors is important to improving prediction of and reducing postoperative readmission risk. METHODS: National Veterans Affairs Surgical Quality Improvement Program data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital signs, prior healthcare utilization, and postoperative complications data. Variables were categorized as preoperative, operative, postoperative/predischarge, and postdischarge. Logistic models predicting 30-day readmission were compared using adjusted R and c-statistics with cross-validation to estimate predictive discrimination. RESULTS: Our study sample included 237,441 surgeries: 43% orthopedic, 39% general, and 18% vascular. Overall 30-day unplanned readmission rate was 11.1%, differing by surgical specialty (vascular 15.4%, general 12.9%, and orthopedic 7.6%, P < 0.001). Most common readmission reasons were wound complications (30.7%), gastrointestinal (16.1%), bleeding (4.9%), and fluid/electrolyte (7.5%) complications. Models using information available at the time of discharge explained 10.4% of the variability in readmissions. Of these, preoperative patient-level factors contributed the most to predictive models (R 7.0% [c-statistic 0.67]); prediction was improved by inclusion of intraoperative (R 9.0%, c-statistic 0.69) and postoperative variables (R 10.4%, c-statistic 0.71). Including postdischarge complications improved predictive ability, explaining 19.6% of the variation (R 19.6%, c-statistic 0.76). CONCLUSIONS: Postoperative readmissions are difficult to predict at the time of discharge, and of information available at that time, preoperative factors are the most important.

Does Use of a Hospital-wide Readmission Measure Versus Condition-specific Readmission Measures Make a Difference for Hospital Profiling and Payment Penalties?

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) use public reporting and payment penalties as incentives for hospitals to reduce readmission rates. In contrast to the current condition-specific readmission measures, CMS recently developed an all-condition, 30-day all-cause hospital-wide readmission measure (HWR) to provide a more comprehensive view of hospital performance. OBJECTIVES: We examined whether assessment of hospital performance and payment penalties depends on the readmission measure used. RESEARCH DESIGN: We used inpatient data to examine readmissions for patients discharged from VA acute-care hospitals from Fiscal Years 2007-2010. We calculated risk-standardized 30-day readmission rates for 3 condition-specific measures (heart failure, acute myocardial infarction, and pneumonia) and the HWR measure, and examined agreement between the HWR measure and each of the condition-specific measures on hospital performance. We also assessed the effect of using different readmission measures on hospitals' payment penalties. RESULTS: We found poor agreement between the condition-specific measures and the HWR measure on those hospitals identified as low or high performers (eg, among those hospitals classified as poor performers by the heart failure readmission measure, only 28.6% were similarly classified by the HWR measure). We also found differences in whether a hospital would experience payment penalties. The HWR measure penalized only 60% of those hospitals that would have received penalties based on at least 1 of the condition-specific measures. CONCLUSIONS: The condition-specific measures and the HWR measure provide a different picture of hospital performance. Future research is needed to determine which measure aligns best with CMS's overall goals to reduce hospital readmissions and improve quality.