Health Care Quality Metrics Research Articles

Assessment of the Accuracy and Reliability of Vascular Surgery Quality Metrics

Health care quality metrics are crucial to medical institutions, payers, and patients. Obtaining current and reliable quality data is challenging, as publicly reported databases lag by several years. Vizient Clinical Data Base (previously University Health Consortium) is utilized by over 5,000 academic and community medical centers to benchmark health care metrics with results based on predetermined Vizient service lines. We sought to assess the accuracy and reliability of vascular surgery service line metrics, as determined by Vizient. Vizient utilizes encounter data submitted by participating medical centers and generates a diverse array of health care metrics ranging from mortality to costs. All inpatient cases captured by Vizient under the vascular surgery service line were identified at the University of Massachusetts Medical Center (fiscal year 2016). Each case within the service line was reviewed and categorized as "vascular" or "nonvascular" based on care provided by UMass vascular surgery faculty: vascular=vascular surgery was integral part of care, nonvascular=vascular surgery had minimal or no involvement. Statistical analysis comparing length of stay (LOS), cost, readmission, mortality, and complication rates between vascular and nonvascular cohorts was performed. All inpatient cases discharged by a vascular surgeon National Provider Identifier number were also reviewed and categorized according to Vizient service lines. Vizient's vascular surgery service line identified 696 cases, of which 556 (80%) were vascular and 140 (20%) were nonvascular. When comparing these 2 cohorts, vascular cases had a significantly lower LOS (3.4 vs. 8.7days; P<0.0001), cost ($8,535 vs. $16,498; P<0.0001), and complication rate (6.5% vs. 18%; P<0.0001) than nonvascular. Mortality was also lower (1.6% vs. 5.7%; P<0.01), but after risk-adjustment, this difference was not significant. When discharging vascular surgeon National Provider Identifier was used to identify vascular surgery cases, only 69% of these cases were placed within the vascular surgery service line. Health care quality metrics play an important role for all stakeholders but obtaining accurate and reliable data to implement improvements is challenging. In this single institution experience, inpatient cases that were not under the direction or care of a vascular surgeon resulted in significantly negative impacts on LOS, cost, complication rate, and mortality to the vascular surgery service line, as defined by a national clinical database. Therefore, clinicians must understand the data abstracting and reporting process before implementing effective strategic plans.

Impact of Clinic-Based Blood Pressure Approaches on Blood Pressure Measurement.

Clinic-based blood pressure (BP) is a closely-tracked metric of health care quality, but is prone to inaccuracy and measurement imprecision. Recent guidelines have advocated for automated office blood pressure (AOBP) devices to improve clinic-based BP assessments. Patients from a single hypertension clinic underwent a 3-day evaluation that included a 24-hour ambulatory blood pressure monitoring (ABPM), 2 manual clinic-based BP measurements (over 2 visits), and an unattended AOBP measurement (single visit). All measurements were compared to the average wake-time systolic BP (SBP) and diastolic BP (DBP) from ABPM. Among 103 patients (mean age 57.3 ± 14.8 years, 51% women, 29% black) the average wake-time SBP was 131.3 ± 12.3 mm Hg and DBP was 78.3 ± 9.2 mm Hg. The average of 2 manual BPs was significantly higher than wake-time ABPM with mean differences of 5.5 mm Hg (P < 0.001) for SBP and 2.7 mm Hg (P = 0.002) for DBP. In contrast, the averages of the last 2 AOBP measurements did not significantly differ from ABPM with mean differences of 1.6 mm Hg (P = 0.21) for SBP and -0.5 mm Hg (P = 0.62) for DBP. The estimated prevalence of SBP ≥ 140 or DBP ≥ 90 mm Hg based on wake-time ABPM was 27.2% vs. 49.5% based on the average of 2 manual measurements (difference 22.3%; P < 0.001) and 31.1% based on the average of the last 2 AOBP measurements (difference 3.9%; P = 0.57). A single visit, unattended AOBP more precisely estimated BP and the prevalence of stage 2 and uncontrolled hypertension than even the average of 2 manual clinic visits, supporting guideline recommendations to use AOBP for clinic-based BP measurements.

Using national electronic health care registries for comparing the risk of psychiatric re-hospitalisation in six European countries: Opportunities and limitations

Psychiatric re-hospitalisation rates have been of longstanding interest as health care quality metric for planners and policy makers, but are criticized for not being comparable across hospitals and countries due to measurement unclarities. The objectives of the present study were to explore the interoperability of national electronic routine health care registries of six European countries (Austria, Finland, Italy, Norway, Romania, Slovenia) and, by using variables found to be comparable, to calculate and compare re-hospitalisation rates and the associated risk factors. A “Methods Toolkit” was developed for exploring the interoperability of registry data and protocol led pilot studies were carried out. Problems encountered in this process are described. Using restricted but comparable data sets, up to twofold differences in psychiatric re-hospitalisation rates were found between countries for both a 30- and 365-day follow-up period. Cumulative incidence curves revealed noteworthy additional differences. Health system characteristics are discussed as potential causes for the differences. Multi-level logistic regression analyses showed that younger age and a diagnosis of schizophrenia/mania/bipolar disorder consistently increased the probability of psychiatric re-hospitalisation across countries. It is concluded that the advantage of having large unselected study populations of national electronic health care registries needs to be balanced against the considerable efforts to examine the interoperability of databases in cross-country comparisons.

Readmission Adversely Affects Survival in Surgical Rectal Cancer Patients.

Readmission has received attention as a potential healthcare quality metric. No studies have investigated the relationship between readmission and survival in patients undergoing rectal cancer surgery. The aims of this study were to identify factors associated with 30-day readmission after rectal cancer surgery and to determine the impact of readmission on overall survival (OS). Patients who underwent surgical treatment for rectal/rectosigmoid adenocarcinoma stages I-IV were identified using the National Cancer Database (2004-2014). Multivariable logistic regression was used to identify factors for readmission. 2:1 nearest neighbor caliper matching without replacement was used to ensure similarity of patients being compared. Survival analyses were performed using Kaplan-Meier method along with log-rank test and Cox proportional hazards model. Of 110,167 patients, 7045 (6.39%) were readmitted. Factors associated with readmission included higher Charlson comorbidity score, non-private or no insurance, procedure type, hospitals in the Northeast, South, and Midwest regions, and prolonged length of stay. Within the matched cohort (13,756 non-readmitted and 6878 readmitted), readmitted patients had worse 5- and 10-year OS regardless of cancer stage (p < 0.001) and procedure type. Five- and 10-year OS were 58.98% and 41.01% for readmitted patients, 64.96% and 43.50% for non-readmitted patients. Readmitted patients had shorter OS by 13.14months and increased risk of mortality (HR 1.20, 95% CI 1.15-1.25, p < 0.001). Thirty-day readmission after rectal cancer surgery is associated with decreased OS. Efforts to reduce readmissions should be considered to advance cancer care and enhance the potential for improved patient survival.

Effect of Institutional Volume on Acoustic Neuroma Surgical Outcomes: State Inpatient Database 2009–2013

Evolving technologies and health care quality metrics have altered treatment algorithms for acoustic neuromas (ANs), increasing trends toward observation and radiosurgery, with proportionate declines in use of microsurgery. A correlation between increasing surgical volumes and superior outcomes has been investigated previously in numerous surgical diseases, including AN. To re-evaluate the volume-outcome relationship of AN resection in a changing health care system, with evolving treatment strategies. Patients who underwent AN resection between 2009 and 2013 were retrospectively identified in the State Inpatient Database subset of the Healthcare Cost and Utilization Project. Generalized linear mixed-effect models were used to assess odds of various outcome measures (length of stay [LOS], discharge disposition, and facial nerve or severe clinical complications). Institutions were grouped into low-volume centers (1-6 cases/year) and high-volume centers (HVC; ≥31 cases/year) for analysis. A total of 1873 patients underwent AN resection between 2009 and 2013 with a mean age of 50.1 ± 14.1 years (±standard deviation). For each additional case treated annually, patients were 2% (odds ratio [OR], 0.98; 95% confidence interval, 0.96-0.99) less likely to experience a severe complication (P= 0.004). Each additional case also trended toward a decreased rate of facial nerve complications and nonroutine discharge. Inpatient LOS was also shorter for patients at HVCs (median, 4 vs. 5 days; P < 0.001). Despite a relative decline in microsurgery compared with previous eras, care at HVCs is still associated with superior short-term outcomes, such as decreased LOS, facial nerve or other severe complications, and nonroutine discharges.

1245-P: The Association of Glucose Variability during the Last Day of Hospitalization and 30-Day Readmission in Adults with Diabetes

Objective: Thirty-day hospital readmission (30-day RA) rates are a metric of healthcare quality. Limited data is available, whether increased glucose variability (GV) during the last day of hospital stay is associated with an increased risk of 30-day RA. Design: Nationwide cohort of 1,042,859 admissions of patients with diabetes in the non-critical care setting in 129 Veteran Affairs hospitals, between 2001-2014. Coefficient of Variation (CV) was measured using point of care- glucometer values and was used as measurement of GV, divided into ten equal categories (tentiles). Covariates, including demographics, socio-economic and hospital related factors and up to 30 comorbidities were collected. Poisson regression was used to determine if CV during the last stay day of the hospitalization was associated with 30-day RA. Results: After adjusting for age, gender and race (Model 1), there was a gradual increase in 30-day RA ratio among admissions with higher CV. Following adjusting for all the covariates collected (Model 2), only admissions with the highest CV demonstrated an increased 30-day RA. The rate ratios and 95% CIs were 1.049 (1.026, 1.073, p&amp;lt;0.0001), 1.038 (1.015,1.061, p=0.0011), 1.065 (1.042,1.089, p&amp;lt;0.0001), for the 8th, 9th and the 10th tentiles respectively, compared to those with CV in the 1st tentile. In Model 3, after adjusting for covariates used in Model 2 and for hypoglycemia, results remained statistically significant for those admissions with the highest CV [rate ratios and 95% CIs are 1.044 (1.021,1.068, p=0.0001), 1.028 (1.006,1.052, p=0.014), 1.042 (1.018,1.067, p=0.0005) for the 8th, 9th and the 10th tentiles]. Conclusions: Higher glucose variability during the last day of hospitalization was associated with increased 30-day RA rates after adjustment for multiple covariates and hypoglycemia. Disclosure E. Spanakis: None. L.G. Singh: None. T. Siddiqui: None. J.D. Sorkin: None. G. Notas: None. M.F. Magee: Consultant; Self; Mytonomy. Research Support; Self; Lilly Diabetes, Mytonomy, Sanofi. Speaker's Bureau; Self; PRIMED. J.C. Fink: None. M. Zhan: None. G.E. Umpierrez: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc. Research Support; Self; AstraZeneca, Merck &amp; Co., Inc., Novo Nordisk Inc., Sanofi US. Funding U.S. Department of Veterans Affairs (1I01CX001825-01)

Maintaining automated measurement of Choosing Wisely adherence across the ICD 9 to 10 transition.

It remains unclear how to incorporate terminology changes, such as the International Classification of Disease (ICD) transition from ICD-9 to ICD-10, into established automated healthcare quality metrics. To evaluate whether general equivalence mapping (GEM) can apply ICD-9 based metrics to ICD-10 patient data. To develop and validate novel ICD-10 reference codesets. Retrospective analysis for eleven Choosing Wisely (CW) metrics was performed using three scripted algorithms on an institutional clinical data warehouse. ICD-10 data were compared against published ICD-9 based metric definitions using two equivalence mapping algorithms. A third algorithm implemented novel reference ICD-10 codes matching the original ICD-9 codes' intent for comparison with patient ICD-10 data. All adult patients seen at Vanderbilt University Medical Center, April - September 2016. The prevalence of eleven CW services during the six-month period. The three algorithms found similar prevalence of avoidable CW services, with an unweighted-mean of 8.4% (range: 0.16-65%), or approximately 20,000 CW services out of 240,000 potential cases in 515,406 unique patients. The algorithms' median sensitivity was 0.80 (interquartile range: 0.75-0.95), median specificity was 0.88 (IQR: 0.77-0.94), and median Rand accuracy was 0.84 (IQR: 0.79-0.89). The attributed waste of these eleven services for the period ranged from $871,049 to $951,829 between methods. Accuracy assessment demonstrated that the GEM-based methods suffered recall losses for metrics requiring multistep mapping due to incompleteness, while novel ICD-10 metric definitions avoided these challenges. Comprehensive mapping enables use of legacy metrics across ICD generations, but requires computational complexity that can be avoided with novel ICD-10 based metric definitions. Variation in the dollars attributed to waste due to ICD mapping introduces ambiguity that may affect quality-based reimbursement.

Thirty-Day Readmissions in Hematopoietic Stem Cell Transplantation Recipients: Insight from Nationwide Readmission Database

Introduction Hematopoietic Stem Cell Transplant HSCT is an established therapeutic modality for hematological and non hematological diseases. There is a paucity of information regarding the rate, causes and predictors of readmission in HSCT patients. Hospital readmission burden is an important health care quality metric. We aimed to estimate the 30- day readmission burden post HSCT. Methods We used the Nationwide Readmission Database NRD from 2012-2014. HSCT recipients were identified using ICD-9 codes. December was excluded from the index admission as NRD doesn't follow patients over the years, therefore, 30 days readmissions will not be available for these index admission if included. We stratified the patients according to age below and above 18 years and by the type of HSCT to either Bone Marrow or Cord Blood Transplant. We demonstrated the rate and most common causes of readmission through using ICD-9 codes. Multivariate analysis was performed to identify the independent predictors of the 30 day readmissions in HSCT. Results A total of 20,691 HSCT recipients were identified through NRD 2012-2014. Patients above and below 18 years were 92.5% and 7.5% respectively. Bone Marrow Transplant accounted for 97.4% while Cord Blood Transplant was 2.6%. Median age of the adult group was 57 years and of the pediatric group was 8 years, median length of stay was 21 days in adult cohort versus 35 days in pediatric cohort. 58.8% of the whole cohort were male. All cause 30-day readmission rate in HSCT recipients was 21.8% with a median number of 8 days till readmission. In pediatrics cohort, all cause 30-day readmission rate was 39.6% compared to 20.3% in adult cohort. Furthermore, when we stratified according to source of transplant, Cord Blood readmission rate was 42.4 % versus 21.2% in Bone Marrow Transplant. The most common causes of 30-day readmissions were infection, fluid-electrolyte disorder, acute kidney injury and relapse. Among the infection group, the top three causes were bacteremia, clostridium difficile (c.diff), and cytomegalovirus (CMV) infections respectively. On multivariate analysis, Cord Blood Transplant and below 18 years were among the significant predictors of 30-day readmission (HR=2.3, 95% CI (1.9-2.8); p=0.001, and HR=2.4, 95% CI (2.2-2.7); p=0.001, respectively). The estimated total cost of 30-day readmissions in HSCT patients was $6.66 billion, and the mortality rate was 4.4%. Trends of 30-day readmission over 2012-2014 years were rising; 30.2%, 32.2%, and 37.2%, respectively. Conclusions The highest burden of 30-day readmission rates and costs in HSCT recipients in the US were demonstrated among the pediatric and Cord Blood groups. The most common cause of readmission was infection with bacteremia, c. diff and CMV were the highest observed etiologies. Further researches are needed to identify strategies to cut down the rate and cost of readmissions

SPEAR: STUDY OF PATIENTS WITH PARA-PNEUMONIC PLEURAL EFFUSION WHO ARE RE-ADMITTED WITHIN 30 DAYS

SESSION TITLE: Disorders of the Pleura SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/10/2018 01:00 pm - 02:00 pm PURPOSE: Parapneumonic pleural effusions (PPE) pose a significant risk of morbidity and mortality in patients admitted with pneumonia. There are limited data on readmissions in such patients. Readmission rate is an important healthcare quality metric. We sought to determine the rate of 30-day readmissions following an index admission for PPE and the major causes and in-hospital mortality in such cases. METHODS: This is a retrospective cohort study using the 2014 National Readmission Database (NRD). Adults admitted with a primary diagnosis of pneumonia complicated by pleural effusion were included. Patients with primary diagnosis of lung cancer and heart failure, those who died during index admission and inter-hospital transfers were excluded. ICD 9 codes were used to identify all diagnoses. RESULTS: A total of 10,167 index admissions were identified with primary diagnosis of PPE between January to November of 2014. After excluding 364 patients (3.6%) who died during the index admission, 9803 patients were included in the readmission analysis. Of these, 1,313 (13.4%) were re-admitted within 30 days. The average age of these patients was 68.4 years and half were women. The most common causes of readmission were pneumonia (15.5%) and pleural effusion including empyema (13%). Other causes included sepsis (9.7%), heart failure (7.1%) and respiratory failure (3.9%). The in-hospital mortality was 9%, which is higher compared to the index admission (3.6%). CONCLUSIONS: There is a major risk of 30-day readmissions in patients admitted with PPE. Major causes of readmissions were respiratory including pneumonia and pleural effusion. CLINICAL IMPLICATIONS: There is a need to identify predictors of early re-admission in patients with PPE. DISCLOSURES: No relevant relationships by Karishma Bhatia, source=Web Response No relevant relationships by Sathish Pondaiah, source=Web Response No relevant relationships by Naveen Premnath, source=Web Response No relevant relationships by Adil Shujaat, source=Web Response No relevant relationships by Karan Sud, source=Web Response

Semi-Automated Visualization and ANalysis of Trends: A "SAVANT" for Facilitating Antimicrobial Stewardship Using Antistaphylococcal Resistance and Consumption as a Prototype.

Governments and health care regulators now require hospitals and nursing homes to establish programs to monitor and report antimicrobial consumption and resistance. However, additional resources were not provided. We sought to develop an approach for monitoring antimicrobial resistance and consumption that health care systems can implement with minimal added costs or modifications to existing diagnostic and informatics infrastructure. Using (1) the electronic laboratory information system of a nationwide managed care network, (2) the 3 most widely used commercial microbiology diagnostic platforms, and (3) Staphylococcus aureus, one of the most common causes of infections worldwide, as a prototype, we validated the approach dubbed "SAVANT" for Semi-Automated Visualization and ANalysis of Trends. SAVANT leverages 3 analytical methods (time series analysis, the autoregressive integrated moving average, and generalized linear regression) on either commercial or open source software to report trends in antistaphylococcal use and resistance. All laboratory results from January 2010 through December 2015 from an annual average of 9.2 million health care beneficiaries were queried. Inpatient and outpatient prescription rates were calculated for 8 key antistaphylococcal compounds. Trends and relationships of antistaphylococcal consumption and resistance among 81 840 unique S. aureus isolates from >6.5 million cultures were revealed. Using existing or freely available resources, SAVANT was successfully implemented across a complex and geographically dispersed 280-hospital network, bridging a critical gap between medical informatics, large-scale data analytics, and mandatory reporting of health care quality metrics.

IN-HOSPITAL OUTCOMES AND ETIOLOGIES FOR 30-DAY READMISSIONS IN PATIENTS WITH ACUTE PERICARDITIS

There is limited data available on the burden and major etiologies of rehospitalization after admission for acute pericarditis. Readmissions are now an important healthcare quality metric. We aim to analyze the in-hospital outcomes and etiologies of 30 day readmissions after an index admission for

Never events and hospital-acquired conditions after kidney transplant.

Never events (NE) and hospital-acquired conditions (HAC) after surgery have been designated as quality metrics in health-care by the Centres for Medicare and Medicaid Services (CMS). The Nationwide Inpatient Sample (NIS) database 2002-2012 was used to identify patientswho underwent kidney transplant. Multivariate analysis using logistic regression was used to identify outcomes and risk factors of HAC and NE after transplantation; however, we were limited by using a retrospective database missing some important variables specified for the kidney transplant, such as some operative factors, donor factors, and cold and warm ischemia times. Among 35 058 patients who underwent kidney transplant, there were 11 NEs, all of which were due to retained foreign bodies. Among HAC after surgery, falling was the most common (44.9%), followed by poor glycemic control (21.7%), vascular catheter-associated infection (21%), and catheter-associated urinary tract infection (8%). HAC and NE after surgery lead to a significant increase in mortality (adjusted odds ratio [AOR] 2.49; p=0.04), hospitalization length (13 vs. 7 days; p<0.01), and total hospital charges ($231 801 vs. $146 717; p<0.01). A significantly higher risk of HAC or NE was seen for patients who had more loss of function before surgey (AOR 3.25; p<0.01) and patients expected to have higher postoperative mortality before operation (AOR 1.62; p=0.03). Despite the limitations of the study, we found HAC and NE significantly increase mortality, hospitalization length, and total hospital charges of kidney transplant patients. Quality improvement initiatives should target HAC and NE in order to successfully reduce or prevent these events.

Risk factors for thirty‐day readmission following flap reconstruction of oncologic defects of the head and neck

Unplanned 30-day readmission rate following hospital discharge is an important metric of healthcare quality. This study sought to characterize the rate, risk factors, and common causes of readmission in head and neck cancer patients following free or pedicled flap reconstruction. Retrospective cohort study. Charts were reviewed of all patients who underwent free or pedicled flap reconstruction following resection of head and neck cancer at the Massachusetts Eye and Ear Infirmary 2009 to 2014. Readmission risk factors were evaluated by univariate and multivariate analysis. Of 682 patients with free (76%) or pedicled flap reconstruction, 135 patients (19.8%) were readmitted. Factors not associated with readmission included age, gender, American Society of Anesthesiologists status, operative time, prior radiation therapy, primary cancer site, and free (vs. pedicled) flap type. Significant readmission risk factors included surgical site infections (SSI) (45.2% vs. 9.9%), use of hardware (18.5% vs. 11.3%), and clean-contaminated or contaminated surgery (15.2% vs. clean 8.2%). Surgical site infections (P < 0.001) and use of hardware (P = 0.03) remained predictive of readmission on multiple regression analysis. Primary reasons for readmission included wound complications (61.5%) and supportive care (15.6%). The median time to readmission was 8 days, and 41% of readmissions occurred within 1 week. Seventy percent of readmissions occurred within 2 weeks, including 77% of readmissions for SSIs and 86% for supportive care. Readmissions occurred in nearly one-fifth of patients following flap surgery. SSIs and use of hardware were risk factors, whereas wound complications were the most common cause of readmission. 4. Laryngoscope, 128:343-349, 2018.

Endoscopic Spine Surgery: Distance Patients Will Travel for Minimally Invasive Spine Surgery

Background: Transforaminal lumbar endoscopic discectomy is a minimally invasive spine surgery procedure performed principally for the treatment of lumbar herniated discs. Endoscopic spine surgeons around the world have noted how far patients will travel to undergo this minimally invasive spine surgery, but the actual distance patients travel has never been investigated. Objective: We present here our analysis of how far patients will travel for endoscopic spine surgery by studying the referral patterns of patients to 3 centers in 3 different countries. Study Design: Retrospective chart review of de-identified patient data was performed to analyze the distance patients travel for spine surgery. Methods: Patient demographic data was analyzed for patients undergoing transforaminal lumbar endoscopic discectomy procedures over the same 8 month period in 2015 at centers in the United States (U.S.), Netherlands, and Germany. Results: Travel distances for patients were determined for 327 patients. The average distance traveled for the U.S. center was 91 miles, the Dutch center was 287 miles, and the German center was 103 miles. For the U.S. center 16% of patients traveled out of state for surgery and for the European centers combined, 4% of patients traveled out of the country for surgery. Limitations: The period of data analyzed was less than one year and the data collected was analyzed retrospectively. Conclusions: Quality metrics in health care tend to be focused on how health care is delivered. Another health care metric that focuses more on what patients desire is presented here: how far patients will travel for innovative spine care. Key words: Endoscopic spine surgery, transforaminal, minimally invasive, travel, lumbar disc herniation

Should quality of the liver transplant candidate evaluation be measured?

Should quality of the liver transplant candidate evaluation be measured?

Observations from the Field: Reporting Quality Metrics in Health Care

Measurement is a critical tool for monitoring progress and driving improvement in health care. However, without meaningful coordination and management—particularly when public reporting is required—the effectiveness of measurement activities is […]

Decision Analysis for Metric Selection on a Clinical Quality Scorecard.

Clinical quality scorecards are used by health care institutions to monitor clinical performance and drive quality improvement. Because of the rapid proliferation of quality metrics in health care, BJC HealthCare found it increasingly difficult to select the most impactful scorecard metrics while still monitoring metrics for regulatory purposes. A 7-step measure selection process was implemented incorporating Kepner-Tregoe Decision Analysis, which is a systematic process that considers key criteria that must be satisfied in order to make the best decision. The decision analysis process evaluates what metrics will most appropriately fulfill these criteria, as well as identifies potential risks associated with a particular metric in order to identify threats to its implementation. Using this process, a list of 750 potential metrics was narrowed to 25 that were selected for scorecard inclusion. This decision analysis process created a more transparent, reproducible approach for selecting quality metrics for clinical quality scorecards.

Predictors of 30-day readmission after mastectomy: A multi-institutional analysis of 21,271 patients.

Recent healthcare legislation has made unplanned hospital readmission an important metric of health care quality, and current efforts center on reducing this complication in order to avoid fiduciary penalties. There is currently a paucity of data delineating risk factors for readmission following mastectomy. To this end, we sought to develop a predictive model of unplanned readmissions following mastectomy. The 2011 and 2012 National Surgical Quality Improvement Program (NSQIP) datasets were retrospectively queried to identify patients who underwent mastectomy. Multivariate logistic regression modeling was used to identify risk factors for readmission. Of 21,271 patients meeting inclusion criteria, 1,190 (5.59%) were readmitted. The most commonly cited reasons for readmission included surgical site complications (32.85%), infection not localized to the surgical site (2.72%), and venous thromboembolism (4.39%). Independent predictors of readmission included BMI, active smoking status, and skin-sparing mastectomy. Significantly, concurrent breast reconstruction and bilateral mastectomy were not independent predictors of readmission. This is the first study of readmission rates after mastectomy. Awareness of specific risk factors for readmission, particularly those that are modifiable, may serve to identify and manage high risk patients, aid in the development of pre- and postoperative clinical care guidelines, and ultimately improve patient care.

Design and methodology of SNAP-1: a Sprint National Anaesthesia Project to measure patient reported outcome after anaesthesia.

BackgroundPatient satisfaction is an important metric of health-care quality. Accidental awareness under general anaesthesia (AAGA) is a serious complication of anaesthesia care which may go unrecognised in the immediate perioperative period but leads to long-term psychological harm for affected patients. The SNAP-1 study aimed to measure patient satisfaction with anaesthesia care and the incidence of AAGA, reported on direct questioning within 24 h of surgery, in a large multicentre cohort. A secondary aim of SNAP-1 was to test the effectiveness of a new network of Quality Audit and Research Coordinators in NHS anaesthetic departments, to achieve widespread study participation and high patient recruitment rates. This manuscript describes the study methodology.MethodsSNAP-1 was a prospective observational cohort study. The study protocol was approved by the National Research Ethics Service. All UK NHS hospitals with anaesthetic departments were invited to participate. Adult patients undergoing any type of non-obstetric surgery were recruited in participating hospitals on 13th and 14th May 2014. Demographic data were collected by anaesthetists providing perioperative care. Patients were then approached within 24 h of surgery to complete two questionnaires—the Bauer patient satisfaction questionnaire (to measure patient reported outcome) and the modified Brice questionnaire (to detect possible accidental awareness). Completion of postoperative questionnaires was taken as evidence of implied consent. Results were recorded on a standard patient case report form, and local investigators entered anonymised data into an electronic database for later analysis by the core research team.ResultsPreliminary analyses indicate that over 15,000 patients were recruited across the UK, making SNAP-1 the largest NIHR portfolio-adopted study in anaesthesia to date. Both descriptive and analytic epidemiological analyses will be used to answer specific questions about the patient perception of anaesthesia care overall and in surgical sub-specialties and to determine the incidence of AAGA.ConclusionsThe SNAP-1 study recruited a large number of UK hospitals and thousands of perioperative patients using newly established networks in the UK anaesthetic profession. The results will provide benchmarking information to aid interpretation of patient satisfaction data and also determine the incidence of AAGA reported on a single postoperative visit.Electronic supplementary materialThe online version of this article (doi:10.1186/s13741-015-0011-2) contains supplementary material, which is available to authorized users.

Assessment of healthcare quality metrics: Length-of-stay, 30-day readmission, and 30-day mortality for radical nephrectomy with inferior vena cava thrombectomy.

Length-of-stay (LOS), 30-day readmission, and 30-day mortality are metrics used to assess quality of care and provider reimbursement. Therefore, we investigated patient- and hospital-level characteristics associated with the three healthcare quality metrics for radical nephrectomy with inferior vena cava (IVC) thrombectomy. Using the National Cancer Data Base, we established a cohort of patients who received radical nephrectomy following the diagnosis of renal cell carcinoma (RCC) stage cT3b between 1998 and 2011. We then assessed the associations between patient- or hospital-level characteristics and LOS using multivariable negative binomial regression. We used multivariable logistic regression to determine the associations between the characteristics and 30-day readmission or 30-day mortality. During the study period, 5768 patients were diagnosed with RCC stage cT3b and underwent radical nephrectomy. LOS ≤2 days and ≥9 days were associated with a higher likelihood of 30-day readmission (respective odds ratio [OR] 1.61 and 1.58) and 30-day mortality (respective OR 11.62 and 11.87). Older patients (60-79 years vs. <50 years) were less likely to experience 30-day readmission (OR 0.46-0.52). Older patients (≥80 years vs. <50 years, OR 3.67) and patients with a high index of comorbidity (Charlson comorbidity score ≥ 2 vs. 0, OR 1.95) were more likely to suffer 30-day mortality. LOS is an important predictor of short-term readmission and mortality following radical nephrectomy with IVC thrombectomy. Older age and a high index of comorbidity also predict short-term mortality after the surgery.