Detecting adverse events in surgery: comparing events detected by the Veterans Health Administration Surgical Quality Improvement Program and the Patient Safety Indicators

Efficacy of an intervention program to prevent patient safety indicators in aneurysmal subarachnoid haemorrhage

OBJECTIVE

Patient safety indicators (PSI) are a set of potentially preventable events related to patient safety and opportunities for improvement. Eight pertinent PSI have been identified in patients with aneurysmal subarachnoid haemorrhage (ASAH), such as decubitus ulcer, and central line-related bacteraemia. Our aim was to evaluate the efficacy of a health care quality protocol to prevent the appearance of PSI in ASAH patients.

METHODS

Adult patients treated for ASAH were included in a retrospective control group of 35 patients and a prospective experimental group of 35 patients when the prevention program was implemented. We evaluated the occurrence of PSI, and its relation to age, sex, Hunt and Hess scale grade, type of aneurysm treatment, length of hospital stay, and Glasgow Outcome Scale scores.

RESULTS

Both groups had similar characteristics except for a longer hospital stay in the control group. The overall PSI prevalence decreased significantly in the experimental group compared to the control group. The experimental group had a decreased risk for having at least one PSI: OR = 0.21 (0.08-0.57, CI 95%). The absolute risk reduction is 37.1% (58.9%-15.4%), the preventable fraction for the population is 28.3% (10.6%-40.0%), and the number needed to treat is 2.69.

CONCLUSIONS

The health care quality protocol is effective to prevent ISP in ASAH patients. Implementing this prevention program has no effect on the neurological state of the patient at the hospital discharge. Still, it is successful in decreasing the PSI prevalence and the days of hospital stay.

Preoperative Risk Factors for Discharge to Facility After Surgery in Geriatric Patients

BACKGROUND

The Geriatric Surgery Verification Program (GSV) was developed to address perioperative care for patients ≥75 years, with a goal of improving outcomes and functional abilities after surgery. We sought to evaluate preoperative factors that place patients at risk for inability to return home (ie, discharge to a facility).

METHODS

Retrospective review of patients ≥75 years old who underwent inpatient surgery from January 2018 to December 2022 at a referral Veterans Administration Medical Center enrolled in the GSV program. Preoperative factors included fall history, mobility aids, housing status, function, cognition, and nutritional status. Postoperative outcomes were discharge designations as home and home with services compared to a facility (skilled nursing facility and acute rehab). Exclusion criteria included preoperative facility residence, cardiac surgery, hospital transfer, postoperative complications, hospice discharge, or in-hospital mortality.

RESULTS

605 patients met inclusion criteria and 173 (29%) excluded as above. Of the remaining 432 patients, mean age was 79 ± 5 and the majority were male, 426 (99%). The majority of patients were discharged home, 388 (90%), compared to a facility, 44 (10%). Patients with a fall history (OR: 2.95, 95% CI: 1.56, 5.57), utilizing a mobility aid (OR: 6.0, 95% CI: 2.8, 12.83), were partial or totally dependent (OR: 4.83, 95% CI: 2.29, 10.17), or who lived alone (OR: 2.57, 95% CI: 1.08, 6.07) had higher rates of discharge to a facility.

DISCUSSION

Preoperative mobility compromise and functional dependence are associated with higher rates of discharge to a facility. These preoperative factors are possibly modifiable with multidisciplinary care teams to decrease risks of facility placement.

A scoping review of the methodological approaches used in retrospective chart reviews to validate adverse event rates in administrative data

Patient safety is a key quality issue for health systems. Healthcare acquired adverse events (AEs) compromise safety and quality; therefore, their reporting and monitoring is a patient safety priority. Although administrative datasets are potentially efficient tools for monitoring rates of AEs, concerns remain over the accuracy of their data. Chart review validation studies are required to explore the potential of administrative data to inform research and health policy. This review aims to present an overview of the methodological approaches and strategies used to validate rates of AEs in administrative data through chart review. This review was conducted in line with the Joanna Briggs Institute methodological framework for scoping reviews. Through database searches, 1054 sources were identified, imported into Covidence, and screened against the inclusion criteria. Articles that validated rates of AEs in administrative data through chart review were included. Data were extracted, exported to Microsoft Excel, arranged into a charting table, and presented in a tabular and descriptive format. Fifty-six studies were included. Most sources reported on surgical AEs; however, other medical specialties were also explored. Chart reviews were used in all studies; however, few agreed on terminology for the study design. Various methodological approaches and sampling strategies were used. Some studies used the Global Trigger Tool, a two-stage chart review method, whilst others used alternative single-, two-stage, or unclear approaches. The sources used samples of flagged charts (n = 24), flagged and random charts (n = 11), and random charts (n = 21). Most studies reported poor or moderate accuracy of AE rates. Some studies reported good accuracy of AE recording which highlights the potential of using administrative data for research purposes. This review highlights the potential for administrative data to provide information on AE rates and improve patient safety and healthcare quality. Nonetheless, further work is warranted to ensure that administrative data are accurate. The variation of methodological approaches taken, and sampling techniques used demonstrate a lack of consensus on best practice; therefore, further clarity and consensus are necessary to develop a more systematic approach to chart reviewing.

Case Sampling for Evaluating Hospital Postoperative Morbidity in US Surgical Quality Improvement Programs

Importance

US surgical quality improvement (QI) programs use data from a systematic sample of surgical cases, rather than universal review of all cases, to assess and compare risk-adjusted hospital postoperative complication rates. Given decreasing postoperative complication rates over time and the types of cases eligible for abstraction, it is unclear whether case sampling is robust for identifying hospitals with higher than expected complications.

Objective

To compare the assessment of hospital 30-day complication rates derived from sampling strategy used by some US surgical QI programs relative to universal review of all cases.

Design, Setting, and Participants

This US hospital-level analysis took place from January 1, 2016, through September 30, 2020. Data analysis was performed from July 1, 2022, through December 21, 2022. Quarterly, risk-adjusted, 30-day complication observed to expected (O-E) ratios were calculated for each hospital using the sample (n = 502 730) and universal review (n = 1 725 364). Outlier hospitals (ie, those with higher than expected mortality) were identified using an O-E ratio significantly greater than 1.0. Patients 18 years and older who underwent a noncardiac operation at US Department of Veterans Affairs (VA) hospitals with a record in the VA Surgical Quality Improvement Program (systematic sample) and the VA Corporate Data Warehouse surgical domain (100% of surgical cases) were included.

Main Outcome Measure

Thirty-day complications.

Results

Most patients in both the representative sample and the universal sample were men (90.2% vs 91.2%) and White (74.7% vs 74.5%). Overall, 30-day complication rates were 7.6% and 5.3% for the sample and universal review cohorts, respectively (P < .001). Over 2145 hospital quarters of data, hospitals were identified as an outlier in 15.0% of quarters using the sample and 18.2% with universal review. Average hospital quarterly complication rates were 4.7%, 7.2%, and 7.4% for outliers identified using the sample only, universal review only, and concurrent identification in both data sources, respectively. For nonsampled cases, average hospital quarterly complication rates were 7.0% at outliers and 4.4% at nonoutliers. Among outlier hospital quarters in the sample, 54.2% were concurrently identified with universal review. For those identified with universal review, 44.6% were concurrently identified using the sample.

Conclusion

In this observational study, case sampling identified less than half of hospitals with excess risk-adjusted postoperative complication rates. Future work is needed to ascertain how to best use currently collected data and whether alternative data collection strategies may be needed to better inform local QI efforts.

Case Sampling vs Universal Review for Evaluating Hospital Postoperative Mortality in US Surgical Quality Improvement Programs

Importance

Representative surgical case sampling, rather than universal review, is used by US Department of Veterans Affairs (VA) and private-sector national surgical quality improvement (QI) programs to assess program performance and to inform local QI and performance improvement efforts. However, it is unclear whether case sampling is robust for identifying hospitals with safety or quality concerns.

Objective

To evaluate whether the sampling strategy used by several national surgical QI programs provides hospitals with data that are representative of their overall quality and safety, as measured by 30-day mortality.

Design, Setting, and Participants

This comparative effectiveness study was a national, hospital-level analysis of data from adult patients (aged ≥18 years) who underwent noncardiac surgery at a VA hospital between January 1, 2016, and September 30, 2020. Data were obtained from the VA Surgical Quality Improvement Program (representative sample) and the VA Corporate Data Warehouse surgical domain (100% of surgical cases). Data analysis was performed from July 1 to December 21, 2022.

Main Outcomes and Measures

The primary outcome was postoperative 30-day mortality. Quarterly, risk-adjusted, 30-day mortality observed-to-expected (O-E) ratios were calculated separately for each hospital using the sample and universal review cohorts. Outlier hospitals (ie, those with higher-than-expected mortality) were identified using an O-E ratio significantly greater than 1.0.

Results

In this study of data from 113 US Department of Veterans Affairs hospitals, the sample cohort comprised 502 953 surgical cases and the universal review cohort comprised 1 703 140. The majority of patients in both the representative sample and the universal sample were men (90.2% vs 91.1%) and were White (74.7% vs 74.5%). Overall, 30-day mortality was 0.8% and 0.6% for the sample and universal review cohorts, respectively (P < .001). Over 2145 quarters of data, hospitals were identified as an outlier in 11.7% of quarters with sampling and in 13.2% with universal review. Average hospital quarterly 30-day mortality rates were 0.4%, 0.8%, and 0.9% for outlier hospitals identified using the sample only, universal review only, and concurrent identification in both data sources, respectively. For nonsampled cases, average hospital quarterly 30-day mortality rates were 1.0% at outlier hospitals and 0.5% at nonoutliers. Among outlier hospital quarters in the sample, 47.4% were concurrently identified with universal review. For those identified with universal review, 42.1% were concurrently identified using the sample.

Conclusions and Relevance

In this national, hospital-level study, sampling strategies employed by national surgical QI programs identified less than half of hospitals with higher-than-expected perioperative mortality. These findings suggest that sampling may not adequately represent overall surgical program performance or provide stakeholders with the data necessary to inform QI efforts.

Association Between Postoperative Complications and Long-term Survival After Non-cardiac Surgery Among Veterans

OBJECTIVE

To evaluate the relationship between postoperative complications and long-term survival.

SUMMARY AND BACKGROUND

Postoperative complications remain a significant driver of healthcare costs and are associated with increased perioperative mortality, yet the extent to which they are associated with long-term survival is unclear.

METHODS

National cohort study of Veterans who underwent non-cardiac surgery using data from the Veterans Affairs Surgical Quality Improvement Program (2011-2016). Patients were classified as having undergone outpatient, low-risk inpatient, or high-risk inpatient surgery. Patients were categorized based on number and type of complications. The association between the number of complications (or the specific type of complication) and risk of death was evaluated using multivariable Cox regression with robust standard errors using a 90-day survival landmark.

RESULTS

Among 699,002 patients, complication rates were 3.0%, 6.1%, and 18.3% for outpatient, low-risk inpatient, and high-risk inpatient surgery, respectively. There was a dose-response relationship between an increasing number of complications and overall risk of death in all operative settings [outpatient surgery: no complications (ref); one-hazard ratio (HR) 1.30 (1.23 - 1.38); multiple-HR 1.61 (1.46 - 1.78); low-risk inpatient surgery: one-HR 1.34 (1.26 - 1.41); multiple-HR 1.69 (1.55 - 1.85); high-risk inpatient surgery: one-HR 1.14 (1.10 - 1.18); multiple-HR 1.42 (1.36 - 1.48)]. All complication types were associated with risk of death in at least 1 operative setting, and pulmonary complications, sepsis, and clostridium difficile colitis were associated with higher risk of death across all settings. Conclusions: Postoperative complications have an adverse impact on patients' long-term survival beyond the immediate postoperative period. Although most research and quality improvement initiatives primarily focus on the perioperative impact of complications, these data suggest they also have important longer-term implications that merit further investigation.

A Pragmatic Method for Measuring Inpatient Complications and Complication-Specific Mortality

OBJECTIVES

The primary objective of this study was to develop hospital-level metrics of major complications associated with mortality that allows for the identification of opportunities for improvement. The secondary objective is to improve upon current metrics for failure to rescue (i.e., death from serious but treatable complications.).

METHODS

Agency for Healthcare Research and Quality metrics served as the basis for identifying specific complications related to major organ system morbidity associated with death. Complication-specific occurrence rates, observed mortality, and risk-adjusted mortality indices were calculated for the study institution and 182 peer organizations using component International Classification of Disease, Tenth Revision codes. Data were included for adults over a 4-year period, with exclusion of hospice patients and complications present on admission. Temporal visualizations of each metric were used to compare past and recent performance at the study hospital and in comparison to peers.

RESULTS

The complication-specific method showed statistically significant differences in the study hospital occurrence rates and associated mortality rates compared with peer institutions. The monthly control-chart presentation of these metrics provides assessment of hospital-level interventions to prevent complications and/or reduce failure to rescue deaths.

CONCLUSIONS

The method described supplements existing metrics of serious complications that occur during the course of acute hospitalization allowing for enhanced visualization of opportunities to improve care delivery systems. This method leverages existing measure components to minimize reporting burden. Monthly time-series data allow interventions to prevent and/or rescue patients to be rapidly assessed for impact.

Quality Reporting Windows May Not Capture the Effects of Surgical Site Infections After Orthopaedic Surgery

BACKGROUND

Postoperative surgical site infections (SSIs) and the associated complications impact morbidity and mortality and result in substantial burden to the health-care system. These complications are typically reported during the 90-day surveillance period, with implications for reimbursement and quality measurement; however, the long-term effects of SSI are not routinely assessed. We evaluated the long-term effects of SSI on health-care utilization and cost following orthopaedic surgery in an observational cohort study.

METHODS

Patients in the Veterans Affairs health-care system who underwent an orthopaedic surgical procedure were included. The exposure of interest was an SSI within 90 days after the index procedure. The primary outcome was health-care utilization in the 2 years after discharge. Data for inpatient admission, inpatient days, outpatient visits, emergency room visits, total costs, and subsequent surgeries were also obtained. After adjusting for factors affecting SSI, we examined differences in each health-care utilization outcome by postoperative SSI occurrence and across time with use of differences-in-differences analysis. Cost differences were modeled with use of a gamma distribution with a log link.

RESULTS

A total of 96,983 patients were included, of whom 4,056 (4.2%) had an SSI within 90 days of surgery. After adjusting for factors known to impact SSI and preoperative health-care utilization, SSI was associated with a greater risk of outpatient visits (relative risk [RR], 1.29; 95% confidence interval [CI], 1.26 to 1.32), emergency room visits (RR, 1.18; 95% CI, 1.15 to 1.21), and inpatient admission (RR, 1.35; 95% CI, 1.32 to 1.38) at 2 years postoperatively. The average cost among patients with an SSI was $148,824 ± $268,358 compared with $42,125 ± $124,914 among those without an SSI (p < 0.001). In the adjusted analysis, costs for patients with an SSI were 64% greater at 2 years compared with those without an SSI (RR, 1.64; 95% CI, 1.57 to 1.70). Overall, of all subsequent surgeries conducted within the 2-year postoperative period, 37% occurred within the first 90 days.

CONCLUSIONS

The reported effects of a postoperative SSI on health-care utilization and cost are sustained at 2 years post-surgery-a long-term impact that is not recognized in quality-measurement models. Efforts, including preoperative care pathways and optimization, and policies, including reimbursement models and risk-adjustment, should be made to reduce SSI and to account for these long-term effects.

LEVEL OF EVIDENCE

Economic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Incidence and Risk Factors for Complications and Mortality After Vertebroplasty or Kyphoplasty in the Osteoporotic Vertebral Compression Fracture-Analysis of 1,932 Cases From the American College of Surgeons National Surgical Quality Improvement

STUDY DESIGN

Retrospective cohort.

OBJECTIVE

The purpose was to investigate the incidence of and risk factors for complications associated with vertebroplasty (VP) or kyphoplasty (KP) for osteoporotic vertebral compression fracture (OVCF) using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.

METHODS

A cohort of patients undergoing VP/KP was constructed from the 2011-2013 ACS-NSQIP dataset using Current Procedural Terminology (CPT) codes. The incidences of minor complications (i.e. urinary tract infection, pneumonia, renal insufficiency, superficial infection, wound dehiscence), major complications (i.e. reoperation, deep vein thrombosis, pulmonary embolism, sepsis, dialysis, cardiac arrest, deep infection, stroke), and mortality within 30 days post-surgery were investigated, and their risk factors were assessed using logistic regression modeling.

RESULTS

Of 1932 patients undergoing VP/KP, 166 (8.6%) experienced a complication, including minor complications in 53 (2.7%), major complications in 95 (4.9%), and death in 40 (2.1%). Multivariate logistic regression analysis indicated that the adjusted odds ratios (95% confidence interval [CI]) of mortality was significantly associated with ASA 4: 16.604 (1.956-140.959) and increased creatinine (≥ 1.3 mg/dL): 3.494 (1.128-10.823). History of chronic obstructive pulmonary disease was associated with minor complications. Increased WBC count and hypoalbuminemia (<3.0 g/dL) were also associated with major complications.

CONCLUSIONS

The major complication and mortality rates associated with VP/KP were 4.9% and 2.1% respectively, higher than previous reports. Increased creatinine and ASA 4 were independently associated with mortality after VP/KP. Therefore, cautious monitoring and counseling is needed for elderly, patients with preexisting kidney disease or ASA 4 undergoing VP/KP.

Association Between Hospital Perioperative Quality and Long-term Survival After Noncardiac Surgery

IMPORTANCE

There is known variation in perioperative mortality rates across hospitals. However, the extent to which this variation is associated with hospital-level differences in longer-term survival has not been characterized.

OBJECTIVE

To evaluate the association between hospital perioperative quality and long-term survival after noncardiac surgery.

DESIGN, SETTING, AND PARTICIPANTS

This national cohort study included 654 093 US veterans who underwent noncardiac surgery at 98 hospitals using data from the Veterans Affairs Surgical Quality Improvement Program from January 1, 2011, to December 31, 2016. Data were analyzed between January 1 and November 1, 2021.

EXPOSURES

Hospitals were stratified separately into quintiles of reliability-adjusted failure to rescue (FTR) and mortality rates. Patients were further categorized as having a complicated or uncomplicated postoperative course.

MAIN OUTCOMES AND MEASURES

The association between hospital FTR or mortality performance quintile (with quintile 1 representing low FTR or mortality and quintile 5 representing very high FTR or mortality) and overall risk of death was evaluated separately using multivariable shared frailty modeling among patients with a complicated and uncomplicated postoperative course.

RESULTS

For the overall cohort of 654 093 patients, the mean (SD) age was 61.1 (13.2) years; 597 515 (91.4%) were men and 56 578 (8.7%) were women; 111 077 (17.0%) were Black, 5953 (0.9%) were Native American, 467 969 (71.5%) were White, 42 219 (6.5%) were missing a racial category, and 26 875 (4.1%) were of another race; and 37 538 (5.7%) were Hispanic. Hospital-level 5-year survival for patients with a complicated course ranged from 42.7% (95% CI, 38.1%-46.9%) to 82.4% (95% CI, 59.0%-93.2%) and from 76.2% (95% CI, 74.4%-78.0%) to 95.2% (95% CI, 92.5%-97.7%) for patients with an uncomplicated course. Overall, 47 (48.0%) and 83 (84.7%) of 98 hospitals were either in the same or within 1 performance quintile for FTR and mortality, respectively. Among patients who had a postoperative complication, there was a dose-dependent association between care at hospitals with higher FTR rates and risk of death (compared with quintile 1: quintile 2 hazard ratio [HR], 1.05 [95% CI, 0.99-1.12]; quintile 3 HR, 1.17 [95% CI, 1.10-1.26]; quintile 4 HR, 1.30 [95% CI, 1.22-1.38]; and quintile 5 HR, 1.34 [95% CI, 1.22-1.43]). Similarly, increasing hospital FTR rates were associated with increasing risk of death among patients without complications (compared with quintile 1: quintile 2 HR, 1.07 [95% CI, 1.01-1.14]; quintile 3 HR, 1.10 [95% CI, 1.04-1.16]; quintile 4 HR, 1.15 [95% CI, 1.09-1.21]; and quintile 5 HR, 1.10 [95% CI, 1.05-1.19]). These findings were similar across hospital mortality quintiles for patients with complicated and uncomplicated courses.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that the structures, processes, and systems of care that underlie the association between FTR and worse short-term outcomes may also have an influence on long-term survival through a pathway other than rescue from complications. A better understanding of these differences could lead to strategies that address variation in both perioperative and longer-term outcomes.

Opioid Use Disorder is Associated With Complications and Increased Length of Stay After Major Abdominal Surgery

OBJECTIVE

The objective of this study was to determine the impact of opioid use disorder (OUD) on perioperative outcomes after major upper abdominal surgeries.

SUMMARY OF BACKGROUND DATA

OUD, defined as dependence/abuse, is a national health epidemic. Its impact on outcomes after major abdominal surgery has not been well characterized.

METHODS

Patients who underwent elective esophagectomy, total/partial gastrectomy, major hepatectomy, and pancreatectomy were identified using the National Inpatient Sample (2003-2015). Propensity score matching by baseline characteristics was performed for patients with and without OUD. Outcomes measured were in-hospital complications, mortality, length of stay (LOS), and discharge disposition.

RESULTS

Of 376,467 patients, 1096 (0.3%) had OUD. Patients with OUD were younger (mean 53 vs 61 years, P < 0.001) and more often male (55.1% vs 53.2%, P < 0.001), black (15.0% vs 7.6%, P < 0.001), Medicaid beneficiaries (22.0% vs 6.4%, P < 0.001), and in the lowest income quartile (32.6% vs 21.3%, P < 0.001). They also had a higher rate of alcohol (17.2% vs 2.8%, P < 0.001) and nonopioid drug (2.2% vs 0.2%, P = 0.023) dependence/abuse. After matching (N = 1077 OUD, N = 2164 no OUD), OUD was associated with a higher complication rate (52.9% vs 37.3%, P < 0.001), including increased pain [odds ratio (OR) 3.5, P < 0.001], delirium (OR 3.0, P = 0.004), and pulmonary complications (OR 2.0, P = 0.006). Additionally, OUD was associated with increased LOS (mean 12.4 vs 10.6 days, P = 0.015) and nonroutine discharge (OR 1.6, P < 0.001). In-hospital mortality did not differ (OR 2.4, P = 0.10).

CONCLUSION

Patients with OUD more frequently experienced complications and increased LOS. Close postoperative monitoring may mitigate adverse outcomes.

Relationship Between Perioperative Outcomes Used for Profiling Hospital Noncardiac Surgical Quality

BACKGROUND

Risk-adjusted morbidity and mortality are commonly used by national surgical quality improvement (QI) programs to measure hospital-level surgical quality. However, the degree of hospital-level correlation between mortality, morbidity, and other perioperative outcomes (like reoperation) collected by contemporary surgical QI programs has not been well-characterized.

MATERIALS AND METHODS

Veterans Affairs (VA) Surgical Quality Improvement Program (VASQIP) data (2015-2016) were used to evaluate hospital-level correlation in performance between risk-adjusted 30-d mortality, morbidity, major morbidity, reoperation, and 2 composite outcomes (1- mortality, major morbidity, or reoperation; 2- mortality or major morbidity) after noncardiac surgery. Correlation between outcomes rates was evaluated using Pearson's correlation coefficient. Correlation between hospital risk-adjusted performance rankings was evaluated using Spearman's correlation.

RESULTS

Based on a median of 232 [IQR 95-331] quarterly surgical cases abstracted by VASQIP, statistical power for identifying 30-d mortality outlier hospitals was estimated between 3.3% for an observed-to-expected ratio of 1.1 and 45.7% for 3.0. Among 230,247 Veterans who underwent a noncardiac operation at 137 VA hospitals, there were moderate hospital-level correlations between various risk-adjusted outcome rates (highest r = 0.40, mortality and composite 1; lowest r = 0.32, mortality and morbidity). When hospitals were ranked based on performance, there was low-to-moderate correlation between rankings on the various outcomes (highest ρ = 0.47, mortality and composite 1; lowest ρ = 0.37, mortality and major morbidity).

CONCLUSIONS

Modest hospital-level correlations between perioperative outcomes suggests it may be difficult to identify high (or low) performing hospitals using a single measure. Additionally, while composites of currently measured outcomes may be an efficient way to improve analytic sample size (relative to evaluations based on any individual outcome), further work is needed to understand whether they provide a more robust and accurate picture of hospital quality or whether evaluating performance across a portfolio of individual measures is most effective for driving QI.

A Novel Interdisciplinary Iterative Approach for Optimizing the Electronic Health Record to Improve Perioperative Efficiency

OBJECTIVE

We present a holistic perioperative optimization approach led by a CI team with the goal to optimize the workflow within our EHR, improve operative room metrics and user satisfaction.

SUMMARY OF BACKGROUND DATA

The EHR has become integral to perioperative care. Many approaches are utilized to improve performance including systems-based approaches, process redesign, lean methodology, checklists, root cause analysis, and parallel processing. Although most reports describe strategies improving day or surgery productivity, few include perioperative interventions to improve efficiencies.

METHODS

An interdisciplinary CI team consisting of clinicians, informatics specialists, and analysts spent 6 weeks assessing users and optimizing all perioperative areas (scheduling, day of surgery, postop discharge/admission). Elbow-to-elbow retraining and simultaneous content development was performed utilizing an Agile workflow process optimization with the Scrum framework. This iterative approach averaged 1 week from build to change implementation. Pre/post optimization surveys were sent.

RESULTS

Two hundred forty-two perioperative enhancements were completed. While most impacted documentation, all areas were enhanced including billing, reporting, registration, device integration, scheduling, central supply, and so on. FCOTS improved from <70% to >85% and total delay was halved. These parameters were consistently sustained for over 1 year after the 6-week optimization. While only 5% of pre-optimization users agreed to proficiency in the EHR system, this improved to 70% post-optimization. Furthermore, EHR confidence and acceptance improved from 40% to 90%.

CONCLUSIONS

To improve workflow efficiency, all who contribute to the perioperative process must be assessed. This IT driven initiative resulted in improved FCOTS, perioperative workflows, and user satisfaction.

Novel Method to Flag Cardiac Implantable Device Infections by Integrating Text Mining With Structured Data in the Veterans Health Administration's Electronic Medical Record

IMPORTANCE

Health care-associated infections (HAIs) are preventable, harmful, and costly; however, few resources are dedicated to infection surveillance of nonsurgical procedures, particularly cardiovascular implantable electronic device (CIED) procedures.

OBJECTIVE

To develop a method that includes text mining of electronic clinical notes to reliably and efficiently measure HAIs for CIED procedures.

DESIGN, SETTING, AND PARTICIPANTS

In this multicenter, national cohort study using electronic medical record data for patients undergoing CIED procedures in Veterans Health Administration (VA) facilities for fiscal years (FYs) 2016 and 2017, an algorithm to flag cases with a true CIED-related infection based on structured (eg, microbiology orders, vital signs) and free text diagnostic and therapeutic data (eg, procedure notes, discharge summaries, microbiology results) was developed and validated. Procedure data were divided into development and validation data sets. Criterion validity (ie, positive predictive validity [PPV], sensitivity, and specificity) was assessed via criterion-standard manual medical record review.

EXPOSURES

CIED procedure.

MAIN OUTCOMES AND MEASURES

The concordance between medical record review and the study algorithm with respect to the presence or absence of a CIED infection. CIED infection in the algorithm included 90-day mortality, congestive heart failure and nonmetastatic tumor comorbidities, CIED or surgical site infection International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes, antibiotic treatment of Staphylococci, a microbiology test of a cardiac specimen, and text documentation of infection in specific clinical notes (eg, cardiology, infectious diseases, inpatient discharge summaries).

RESULTS

The algorithm sample consisted of 19 212 CIED procedures; 15 077 patients (78.5%) were White individuals, 1487 (15.5%) were African American; 18 766 (97.7%) were men. The mean (SD) age in our sample was 71.8 (10.6) years. The infection detection threshold of predicted probability was set to greater than 0.10 and the algorithm flagged 276 of 9606 (2.9%) cases in the development data set (9606 procedures); PPV in this group was 41.4% (95% CI, 31.6%-51.8%). In the validation set (9606 procedures), at predicted probability 0.10 or more the algorithm PPV was 43.5% (95% CI, 37.1%-50.2%), and overall sensitivity and specificity were 94.4% (95% CI, 88.2%-97.9%) and 48.8% (95% CI, 42.6%-55.1%), respectively.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that the method of combining structured and text data in VA electronic medical records can be used to expand infection surveillance beyond traditional boundaries to include outpatient and procedural areas.

Sensitivity of Administrative Coding in Identifying Inpatient Acute Strokes Complicating Procedures or Other Diseases in UK Hospitals

Background

Administrative hospital diagnostic coding data are increasingly used in “big data” research and to assess complication rates after surgery or acute medical conditions. Acute stroke is a common complication of several procedures/conditions, such as carotid interventions, but data are lacking on the sensitivity of administrative coding in identifying acute stroke during inpatient stay.

Methods and Results

Using all acute strokes ascertained in a population‐based cohort (2002–2017) as the reference, we determined the sensitivity of hospital administrative diagnostic codes (International Classification of Diseases, Tenth Revision; ICD‐10) for identifying acute strokes that occurred during hospital admission for other reasons, stratified by coding strategies, study periods, and stroke severity (National Institutes of Health Stroke Score</≥5). Of 3011 acute strokes, 198 (6.6%) occurred during hospital admissions for procedures/other diseases, including 122 (61.6%) major strokes. Using stroke‐specific codes (ICD‐10=I60–I61 and I63–I64) in the primary diagnostic position, 66 of the 198 cases were correctly identified (sensitivity for any stroke, 33.3%; 95% CI, 27.1–40.2; minor stroke, 30.3%; 95% CI, 21.0–41.5; major stroke, 35.2%; 95% CI, 27.2–44.2), with no improvement of sensitivity over time (P_trend=0.54). Sensitivity was lower during admissions for surgery/procedures than for other acute medical admissions (n/% 17/23.3% versus 49/39.2%; P=0.02). Sensitivity improved to 60.6% (53.6–67.2) for all and 61.6% (50.0–72.1) for surgery/procedures if other diagnostic positions were used, and to 65.2% (58.2–71.5) and 68.5% (56.9–78.1) respectively if combined with use of all possible nonspecific stroke‐related codes (ie, adding ICD‐10=I62 and I65–I68).

Conclusions

Low sensitivity of administrative coding in identifying acute strokes that occurred during admission does not support its use alone for audit of complication rates of procedures or hospitalization for other reasons.

Surgeon-Reported Complications vs AHRQ Patient Safety Indicators: A Comparison of Two Approaches to Identifying Adverse Events

BACKGROUND

Traditionally, clinicians present complications at surgical morbidity and mortality (M&M) conferences, and the AHRQ Patient Safety Indicators (PSIs) use inpatient administrative data to identify certain adverse outcomes. Although both methods are used to identify adverse events and inform quality improvement efforts, these 2 methods might not overlap.

STUDY DESIGN

This is a retrospective observational study of all hospitalizations at a single academic department of surgery (including subspecialties) in 2016 involving a PSI-defined event (PSIs 03, 05 to 15) identified by surgery faculty and residents for review by departmental M&M conference or administrative data (according to AHRQ, version 6.0). Pediatric cases were excluded. We analyzed the degree to which these 2 processes captured PSI-defined events and reasons for exclusion by each process.

RESULTS

Among 6,563 surgical hospitalizations, 647 hospitalizations (9.9%) had at least 1 complication identified by the M&M process or the PSIs (or both). Of these hospitalizations, 116 had at least 1 PSI-defined event (for a total of 149 PSI-defined events) captured by either M&M or the PSIs. Most complications (n = 82 [88.2%]) identified by M&M alone were excluded by PSI criteria (as intended), but 11 true PSI events (ie false negatives) were identified by M&M only. In contrast, pressure ulcers and central venous catheter-related bloodstream infections were detected exclusively by the PSIs and not reported via M&M. There was limited overlap, with 18 events (12.1%) captured by both processes.

CONCLUSIONS

Surgical M&M and the PSIs are complementary approaches to identifying complications. Both case-finding processes should be used to inform quality improvement efforts.

Frequency and Impact of Adverse Events in Inpatients: A Nationwide Analysis of Episodes between 2000 and 2015

Despite being a potential cause of morbidity and economic costs, adverse events remain insufficiently studied. Therefore, we aimed to assess the frequency and impact of adverse events among inpatients. We analysed an administrative database containing a registration of all hospitalisations occurring in Portuguese public hospitals between 2000 and 2015. We identified all episodes with a registration of adverse events, and classified them into three categories, namely (1) misadventures of surgical and medical care, (2) complications of surgical or medical procedures, and (3) adverse drug events (including adverse drug reactions, poisoning events, and late effects). These episodes were compared over their length of stay, in-hospital mortality, and hospital costs with an equal number of hospitalisations matched for patients' and episodes' characteristics. Between 2000 and 2015, 5.8% (n = 861,372) of all Portuguese hospitalisations had a registration of at least one adverse event. Hospitalisations with registration of adverse events had a median length of stay of 8 days, median hospitalisation costs of 3060.7 Euro, and an in-hospital mortality of 6.7%. Hospitalisations with registration of misadventures of care, complications of procedures and adverse drug reactions had significantly higher lengths of stay and hospitalisation costs than their matched controls. In-hospital mortality was significantly higher for episodes of misadventures of care and complications of procedures, but lower for adverse drug events hospitalisations. Therefore, adverse events are common among inpatients, and have an important clinical and economic impact. Administrative databases may be useful in their epidemiological assessment.

Geriatric Patient Safety Indicators Based on Linked Administrative Health Data to Assess Anticoagulant-Related Thromboembolic and Hemorrhagic Adverse Events in Older Inpatients: A Study Proposal

Background

Frail older people with multiple interacting conditions, polypharmacy, and complex care needs are particularly exposed to health care-related adverse events. Among these, anticoagulant-related thromboembolic and hemorrhagic events are particularly frequent and serious in older inpatients. The growing use of anticoagulants in this population and their substantial risk of toxicity and inefficacy have therefore become an important patient safety and public health concern worldwide. Anticoagulant-related adverse events and the quality of anticoagulation management should thus be routinely assessed to improve patient safety in vulnerable older inpatients.

Objective

This project aims to develop and validate a set of outcome and process indicators based on linked administrative health data (ie, insurance claims data linked to hospital discharge data) assessing older inpatient safety related to anticoagulation in both Switzerland and France, and enabling comparisons across time and among hospitals, health territories, and countries. Geriatric patient safety indicators (GPSIs) will assess anticoagulant-related adverse events. Geriatric quality indicators (GQIs) will evaluate the management of anticoagulants for the prevention and treatment of arterial or venous thromboembolism in older inpatients.

Methods

GPSIs will measure cumulative incidences of thromboembolic and bleeding adverse events based on hospital discharge data linked to insurance claims data. Using linked administrative health data will improve GPSI risk adjustment on patients’ conditions that are present at admission and will capture in-hospital and postdischarge adverse events. GQIs will estimate the proportion of index hospital stays resulting in recommended anticoagulation at discharge and up to various time frames based on the same electronic health data. The GPSI and GQI development and validation process will comprise 6 stages: (1) selection and specification of candidate indicators, (2) definition of administrative data-based algorithms, (3) empirical measurement of indicators using linked administrative health data, (4) validation of indicators, (5) analyses of geographic and temporal variations for reliable and valid indicators, and (6) data visualization.

Results

Study populations will consist of 166,670 Swiss and 5,902,037 French residents aged 65 years and older admitted to an acute care hospital at least once during the 2012-2014 period and insured for at least 1 year before admission and 1 year after discharge. We will extract Swiss data from the Helsana Group data warehouse and French data from the national health insurance information system (SNIIR-AM). The study has been approved by Swiss and French ethics committees and regulatory organizations for data protection.

Conclusions

Validated GPSIs and GQIs should help support and drive quality and safety improvement in older inpatients, inform health care stakeholders, and enable international comparisons. We discuss several limitations relating to the representativeness of study populations, accuracy of administrative health data, methods used for GPSI criterion validity assessment, and potential confounding bias in comparisons based on GQIs, and we address these limitations to strengthen study feasibility and validity.

Quality and Safety in Health Care, Part XVI: The VA Surgical Quality Improvement Program

As the result of a congressional mandate, the Veterans Health Administration (VA) undertook an initiative called the National VA Surgical Risk study. The purpose of this study was to collect information on its surgical patients to determine outcome data, adjusted for patient risk factors. In 1994, the VA started its National Surgical Quality Improvement Program (VASQIP). These efforts were one of the earliest well-done nationwide systems to study and improve outcomes in surgery adjusted for patient risk. Between 1991 and 2006, the VA hospitals observed a decrease of mortality of 47% and a decrease of morbidity of 43% of their patients in the first 30 days after an operation.

Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review

OBJECTIVE

Measuring the incidence of healthcare-associated infections (HAI) is of increasing importance in current healthcare delivery systems. Administrative data algorithms, including (combinations of) diagnosis codes, are commonly used to determine the occurrence of HAI, either to support within-hospital surveillance programmes or as free-standing quality indicators. We conducted a systematic review evaluating the diagnostic accuracy of administrative data for the detection of HAI.

METHODS

Systematic search of Medline, Embase, CINAHL and Cochrane for relevant studies (1995-2013). Methodological quality assessment was performed using QUADAS-2 criteria; diagnostic accuracy estimates were stratified by HAI type and key study characteristics.

RESULTS

57 studies were included, the majority aiming to detect surgical site or bloodstream infections. Study designs were very diverse regarding the specification of their administrative data algorithm (code selections, follow-up) and definitions of HAI presence. One-third of studies had important methodological limitations including differential or incomplete HAI ascertainment or lack of blinding of assessors. Observed sensitivity and positive predictive values of administrative data algorithms for HAI detection were very heterogeneous and generally modest at best, both for within-hospital algorithms and for formal quality indicators; accuracy was particularly poor for the identification of device-associated HAI such as central line associated bloodstream infections. The large heterogeneity in study designs across the included studies precluded formal calculation of summary diagnostic accuracy estimates in most instances.

CONCLUSIONS

Administrative data had limited and highly variable accuracy for the detection of HAI, and their judicious use for internal surveillance efforts and external quality assessment is recommended. If hospitals and policymakers choose to rely on administrative data for HAI surveillance, continued improvements to existing algorithms and their robust validation are imperative.

Measuring surgical quality: a national clinical registry versus administrative claims data

BACKGROUND

This study compared postoperative complications of patients who underwent pancreaticoduodenectomy (PD) recorded in the National Surgical Quality Improvement Program (NSQIP) to patients who underwent PD recorded in the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS).

METHODS

Data included 8,822 PD cases recorded in NSQIP and 9,827 PD cases recorded in NIS performed between 2005 and 2010. Eighteen postoperative adverse outcomes were identified in NSQIP and then matched to corresponding International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes in NIS. Using logistic regression, the relationship between database and postoperative complications was determined while accounting for patient factors.

RESULTS

Patients undergoing PD in the NIS were more likely to have several adverse outcomes, including urinary tract infection (odds ratio (OR) = 1.42, p < 0.001), pneumonia (OR = 1.51, p < 0.001), renal insufficiency (OR = 2.39, p < 0.001), renal failure (OR = 1.67, p = 0.005), graft/prosthetic failure (OR = 9.35, p < 0.001), and longer length of stay (1.1 days, p < 0.001). They were less likely to have cardiac arrest (OR = 0.45, p = 0.002), postoperative sepsis (OR = 0.38, p < 0.001), deep vein thrombosis (OR = 0.18, p < 0.001), and cerebrovascular accident (OR = 0.04, p = 0.003).

CONCLUSIONS

There is considerable discordance between NSQIP and NIS in the assessment of postoperative complications following PD, which underscores the value of recognizing the capabilities and limitations of each data source.