Validity and Reliability of Administrative Coded Data for the Identification of Hospital-Acquired Infections: An Updated Systematic Review with Meta-Analysis and Meta-Regression Analysis

Barriers and facilitators for using administrative data for surveillance purpose: A narrative overview

Although administrative data are not originally intended for surveillance purposes, they are frequently used for monitoring public health and patient safety. This article provides a narrative overview of the barriers and facilitators for the use of administrative data for surveillance, with a focus on healthcare-associated infection (HAI) in Canada. In this case, only articles on administrative data in general or related to HAI were included. Validation study and meta-analyses on administrative data accuracy were excluded. Medline, Embase and Google Scholar were searched as well as references list of all included articles, for a total of 90 articles included. Our analysis identifies 78 barriers at the individual, organizational and systemic levels and outlines 75 facilitators and solutions to improve administrative data utilization and quality. This narrative overview will help to understand barriers, facilitators and offer practical recommendations for optimizing the use of administrative data.

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.

Performance of ICD-10-AM codes for quality improvement monitoring of hospital-acquired pneumonia in a haematology-oncology casemix in Victoria, Australia

BACKGROUND

The Australian hospital-acquired complication (HAC) policy was introduced to facilitate negative funding adjustments in Australian hospitals using ICD-10-AM codes.

OBJECTIVE

The aim of this study was to determine the positive predictive value (PPV) of the ICD-10-AM codes in the HAC framework to detect hospital-acquired pneumonia in patients with cancer and to describe any change in PPV before and after implementation of an electronic medical record (EMR) at our centre.

METHOD

A retrospective case review of all coded pneumonia episodes at the Peter MacCallum Cancer Centre in Melbourne, Australia spanning two time periods (01 July 2015 to 30 June 2017 [pre-EMR period] and 01 September 2020 to 28 February 2021 [EMR period]) was performed to determine the proportion of events satisfying standardised surveillance definitions.

RESULTS

HAC-coded pneumonia occurred in 3.66% (n = 151) of 41,260 separations during the study period. Of the 151 coded pneumonia separations, 27 satisfied consensus surveillance criteria, corresponding to an overall PPV of 0.18 (95% CI: 0.12, 0.25). The PPV was approximately three times higher following EMR implementation (0.34 [95% CI: 0.19, 0.53] versus 0.13 [95% CI: 0.08, 0.21]; p = .013).

CONCLUSION

The current HAC definition is a poor-to-moderate classifier for hospital-acquired pneumonia in patients with cancer and, therefore, may not accurately reflect hospital-level quality improvement. Implementation of an EMR did enhance case detection, and future refinements to administratively coded data in support of robust monitoring frameworks should focus on EMR systems.

IMPLICATIONS

Although ICD-10-AM data are readily available in Australian healthcare settings, these data are not sufficient for monitoring and reporting of hospital-acquired pneumonia in haematology-oncology patients.

Best Practices for Identifying Hospitalized Lower Respiratory Tract Infections Using Administrative Data: A Systematic Literature Review of Validation Studies

INTRODUCTION

Estimating the burden of lower respiratory tract infections (LRTIs) increasingly relies on administrative databases using International Classification of Diseases (ICD) codes, but no standard methodology exists. We defined best practices for ICD-based algorithms that estimate LRTI incidence in adults.

METHODS

We conducted a systematic review of validation studies assessing the use of ICD code-based algorithms to identify hospitalized LRTIs in adults, published in Medline, EMBASE, and LILACS between January 1996 and January 2022, according to PRISMA guidelines. We assessed sensitivity, specificity, and other accuracy measures of different algorithms.

RESULTS

We included 26 publications that used a variety of ICD code-based algorithms and gold standard criteria, and 18 reported sensitivity and/or specificity. Sensitivity was below 80% in 72% (38/53) of algorithms and specificity exceeded 90% in 77% (37/48). Algorithms for all-cause LRTI (n = 18) that included only pneumonia codes in primary position (n = 3) had specificity greater than 90% but low sensitivity (55-72%). Sensitivity increased by 5-15%, with minimal loss in specificity, with the addition of primary codes for severe pneumonia (e.g. sepsis) while pneumonia codes were in secondary position, and by 13% with codes from LRTI-related infections (e.g. viral) or other respiratory diseases (e.g. empyema). Sensitivity increased by 8% when pneumonia codes were in any position, but specificity was not reported. In hospital-acquired pneumonia and pneumococcal-specific pneumonia, algorithms containing only nosocomial- or pathogen-specific ICD codes had poor sensitivity, which improved when broader pneumonia codes were added, in particular codes for unspecified organisms.

CONCLUSION

Our systematic review highlights that most ICD code-based algorithms are relatively specific, but miss a substantial number of hospitalized LRTI adult cases. Best practices to estimate LRTI incidence in this population include the use of all pneumonia ICD codes for any LRTI outcome and, to a lesser extent, those for other LRTI-related infections or respiratory diseases.

Prevalence of hospital-associated infections and its association with discharge destinations and hospital readmissions in Brussels, Belgium, from 2008 to 2020: A hospital-based, cross-sectional study

OBJECTIVES

To examine time trends of hospital-associated infections (HAIs) in people living in the Brussels-Capital Region, and to evaluate the consequences for hospitals and long-term care facilities (LTCFs).

DESIGN

Cross-sectional analyses of yearly hospital administrative data.

SETTING

All Belgian hospitals and discharge destinations, focusing on LTCFs.

PARTICIPANTS

All individuals from the Brussels-Capital Region hospitalized for >1 day throughout Belgium between 2008 and 2020 (N = 1,915,572).

METHODS

We calculated HAI prevalences and then, adjusting for confounders, the odds of being discharged to a LTCF or being readmitted within 30 days postdischarge after an HAI. HAIs included hospital-associated bloodstream infections, hospital-associated urinary tract infections, hospital-associated pneumonia, ventilator-associated pneumonia, and surgical-site infections.

RESULTS

Between 2008 and 2020, we identified 77,004 HAIs. Changes in time trends occurred. We observed a decrease of all HAIs from 2012 to 2014 from 5.17% to 2.19% (P < .001) and an increase from 2019 to 2020 from 3.38% to 4.06% (P < .001). Among patients with HAIs, 24.36% were discharged to LTCFs and 13.51% underwent early readmission. For stays ≥4 days, HAIs were associated with higher odds of LTCF discharge (adjusted odds ratio [aOR], 1.25; 95% confidence interval [CI], 1.22-1.28), but with lesser odds of early readmission (aOR, 0.88; 95% CI, 0.85-0.90).

CONCLUSIONS

Administrative data can be useful to detect HAIs trends, but they seem to underestimate the burden compared to surveillance systems. Risk factors of readmission should be identified during hospital stays to ensure continuity of care. Considering the results from 2020 coinciding with the COVID-19 pandemic, monitoring the impact of HAIs should continue.

Incidence of Hospital-Acquired Conditions During Pediatric Clinical Research Inpatient Hospitalizations: A Matched Cohort Study

OBJECTIVES

In this matched cohort study using data from pediatric hospitals, we compared the incidence of hospital-acquired conditions (HACs) during clinical research hospitalizations to nonresearch hospitalizations.

METHODS

Using Pediatric Health Information System data for inpatient discharges January 2017-June 2022, we matched research hospitalizations (identified by International Classification of Diseases, Tenth Revision, diagnosis code) to nonresearch hospitalizations within hospital on age (±3 y), sex, discharge year (±2), and All Patients Refined Diagnosis Related Groups classification, severity of illness (±1), and risk of mortality (±1). We calculated the incidence (per 1000 discharges) and incidence rate (per 10,000 patient days) of HAC identified by International Classification of Diseases, Tenth Revision, codes and compare research versus nonresearch using logistic and Poisson regression, accounting for matching using generalized estimating equations and adjusting for sociodemographic factors and hospital utilization.

RESULTS

We matched 7000 research hospitalizations to 26,447 nonresearch from 28 hospitals. Median age was 6.0 years (interquartile range, 10.6 y). Median length of stay was 4.0 days (interquartile range, 11.0 days) with longer stays among research hospitalizations ( P < 0.001). Incidence of HAC among research hospitalizations was 13.1 versus 7.2 per 1000 for nonresearch ( P < 0.001) and incidence rate 6.7 versus 4.5 per 10,000 patient days. Adjusting for sociodemographic and clinical factors, research stays had 1.65 times the odds of any HAC (95% confidence interval, 1.27-2.16; P < 0.001) and 1.38 times the incidence rate (95% confidence interval, 1.09-1.75; P = 0.009).

CONCLUSIONS

Our findings indicate that pediatric research hospitalizations are more likely to experience HACs compared with nonresearch hospitalizations. These findings have important safety implications for pediatric inpatient clinical research that warrant further study.

Renal disease and diabetes increase the risk of failed outpatient management of cellulitic hand infections: a retrospective cohort study

BACKGROUND

Hand infections are heterogeneous, and some may undergo successful outpatient management. There are no strict guidelines for determining which patients will likely require inpatient admission for successful treatment, and many patients succeed with outpatient therapy. We sought to determine risk factors for failed outpatient management of cellulitic hand infections.

METHODS

We performed a retrospective review of patients who presented to the Emergency Department (ED) for hand cellulitic infections over five years, from 2014 to 2019. Vital signs, lab markers, Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Measure (ECM), and antibiotic use were investigated. Discharge from the ED without subsequent admission was considered an outpatient success, while admission within 30 days of the prior visit was considered a failure. Continuous variables were compared with Welch's t test, and categorical data with Fisher's exact tests. Multivariable logistic regression was performed on comorbidities. Multiple testing adjustment was performed on p-values to generate q-values.

RESULTS

Outpatient management was attempted for 1,193 patients. 31 (2.6%) infections failed treatment, and 1,162 (97.4%) infections succeeded. Attempted outpatient treatment was 97.4% successful. Multivariable analysis demonstrated higher odds of failure with renal failure according to both CCI (OR 10.2, p < 0.001, q = 0.002) and ECM (OR 12.63, p = 0.003, q = 0.01) and with diabetes with complications according to the CCI (OR 18.29, p = 0.021, q = 0.032).

CONCLUSIONS

Outpatient treatment failure was higher in patients with renal failure and complicated diabetes. These patients require a high index of suspicion for outpatient failure. These comorbidities should influence consideration for inpatient therapy though most patients can undergo successful treatment as outpatients.

LEVEL OF EVIDENCE

Level III.

Validation of the first computerized indicator for orthopaedic surgical site infections in France: ISO-ORTHO

BACKGROUND

The French national authority for health (HAS) develops in-hospital indicators for improving quality of care, safety and patient outcome. Since 2017, it has developed a measurement of surgical site infections (SSI) after total hip or knee arthroplasty (TH/KA) by using a computerized indicator, called ISO-ORTHO, based on a hospital discharge database (HDD) algorithm. The aim of the study was to assess the performance of this new indicator .

METHODS

The ISO-ORTHO performance was estimated via its positive predictive value (PPV) among adult patients having undergone a TH/KA between January 1st and September 30th 2018, based on the orthopaedic procedure codes. Patients at very high risk of SSI and/or with SSI not related to the in-hospital care were excluded. SSI were detected from the date of admission up to 90 days after the TH/KA using the ISO-ORTHO algorithm, based on 15 combinations of ICD-10 and procedure codes. Its PPV was estimated by a chart review in volunteer healthcare organisations (HCO).

RESULTS

Over the study period, 777 HCO including 143,227 TH/KA stays were selected, providing 1,279 SSI according to the ISO-ORTHO indicator. The 90-day SSI rate was 0.89 per 100 TH/KA stays (0.98% for THA and 0.80% for TKA). Among the 448 HCO with at least 1 SSI, 250 HCO participated in reviewing 725 SSI charts; 665 were confirmed, giving a PPV of 90.3% [88.2-92.5%], 89.9% [87.1-92.8%] in THA and 90.9% [87.7-94.2%] in TKA.

CONCLUSIONS

The PPV of ISO-ORTHO over 90% confirms its validity for any use according to the HAS method. ISO-ORTHO and detailed information were provided in 2020 to HCO and used for quality assessment and in-hospital risk management.

Risk of and duration of protection from SARS-CoV-2 reinfection assessed with real-world data

This retrospective observational study aimed to gain a better understanding of the protective duration of prior SARS-CoV-2 infection against reinfection. The objectives were two-fold: to assess the durability of immunity to SARS-CoV-2 reinfection among initially unvaccinated individuals with previous SARS-CoV-2 infection, and to evaluate the crude SARS-CoV-2 reinfection rate and associated risk factors. During the pandemic era time period from February 29, 2020, through April 30, 2021, 144,678,382 individuals with SARS-CoV-2 molecular diagnostic or antibody test results were studied. Rates of reinfection among index-positive individuals were compared to rates of infection among index-negative individuals. Factors associated with reinfection were evaluated using multivariable logistic regression. For both objectives, the outcome was a subsequent positive molecular diagnostic test result. Consistent with prior findings, the risk of reinfection among index-positive individuals was 87% lower than the risk of infection among index-negative individuals. The duration of protection against reinfection was stable over the median 5 months and up to 1-year follow-up interval. Factors associated with an increased reinfection risk included older age, comorbid immunologic conditions, and living in congregate care settings; healthcare workers had a decreased reinfection risk. This large US population-based study suggests that infection induced immunity is durable for variants circulating pre-Delta predominance.

Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care-Associated Infection

BACKGROUND

With the widespread adoption of electronic healthcare records (EHRs) by US hospitals, there is an opportunity to leverage this data for the development of predictive algorithms to improve clinical care. A key barrier in model development and implementation includes the external validation of model discrimination, which is rare and often results in worse performance. One reason why machine learning models are not externally generalizable is data heterogeneity. A potential solution to address the substantial data heterogeneity between health care systems is to use standard vocabularies to map EHR data elements. The advantage of these vocabularies is a hierarchical relationship between elements, which allows the aggregation of specific clinical features to more general grouped concepts.

OBJECTIVE

This study aimed to evaluate grouping EHR data using standard vocabularies to improve the transferability of machine learning models for the detection of postoperative health care-associated infections across institutions with different EHR systems.

METHODS

Patients who underwent surgery from the University of Utah Health and Intermountain Healthcare from July 2014 to August 2017 with complete follow-up data were included. The primary outcome was a health care-associated infection within 30 days of the procedure. EHR data from 0-30 days after the operation were mapped to standard vocabularies and grouped using the hierarchical relationships of the vocabularies. Model performance was measured using the area under the receiver operating characteristic curve (AUC) and F₁-score in internal and external validations. To evaluate model transferability, a difference-in-difference metric was defined as the difference in performance drop between internal and external validations for the baseline and grouped models.

RESULTS

A total of 5775 patients from the University of Utah and 15,434 patients from Intermountain Healthcare were included. The prevalence of selected outcomes was from 4.9% (761/15,434) to 5% (291/5775) for surgical site infections, from 0.8% (44/5775) to 1.1% (171/15,434) for pneumonia, from 2.6% (400/15,434) to 3% (175/5775) for sepsis, and from 0.8% (125/15,434) to 0.9% (50/5775) for urinary tract infections. In all outcomes, the grouping of data using standard vocabularies resulted in a reduced drop in AUC and F₁-score in external validation compared to baseline features (all P<.001, except urinary tract infection AUC: P=.002). The difference-in-difference metrics ranged from 0.005 to 0.248 for AUC and from 0.075 to 0.216 for F₁-score.

CONCLUSIONS

We demonstrated that grouping machine learning model features based on standard vocabularies improved model transferability between data sets across 2 institutions. Improving model transferability using standard vocabularies has the potential to improve the generalization of clinical prediction models across the health care system.

Estimated costs of preoperative evaluation of postmenopausal hysterectomy for prolapse at a safety-net hospital: an observational descriptive study

BACKGROUND

In practice, preoperative evaluation prior to hysterectomy varies. Unnecessary preoperative evaluation may add cost and risk with little benefit to the patient.

OBJECTIVE

This study aimed to describe practice patterns and the associated costs related to preoperative evaluations before hysterectomy for prolapse at a safety-net hospital.

STUDY DESIGN

This was a retrospective cohort study of postmenopausal women who underwent a hysterectomy for prolapse. Nonfacility-associated cost data were obtained from the Centers for Medicare Services. The biopsy cost was estimated to be $172.55 and $125.23 for ultrasounds.

RESULTS

A total of 505 postmenopausal cases were identified. Of those, 155 (31%) underwent a preoperative biopsy, 305 (60%) had an ultrasound, and 124 (25%) had both. Of those, 72.9% had an indication for a biopsy. A total of 64 biopsies and 216 ultrasounds lacked clear indication. Of those, 56 biopsies were performed for bleeding in cases with an endometrial thickness of <4 mm. The total cost of nonvalue-added testing was $42,576.

CONCLUSION

Adherence to a strict preoperative algorithm would have saved $38,092 over the study period, although 0.50% of these biopsies would potentially have detected endometrial cancer preoperatively. These results underscore the value of clinical algorithms at teaching institutions.

Duration of Protection Against SARS-CoV-2 Reinfection and Associated Risk of Reinfection Assessed with Real-World Data

IMPORTANCE

Better understanding of the protective duration of prior SARS-CoV-2 infection against reinfection is needed.

OBJECTIVE

Primary: To assess the durability of immunity to SARS-CoV-2 reinfection among initially unvaccinated individuals with previous SARS-CoV-2 infection. Secondary: Evaluate the crude SARS-CoV-2 reinfection rate and associated characteristics.

DESIGN AND SETTING

Retrospective observational study of HealthVerity data among 144,678,382 individuals, during the pandemic era through April 2021.

PARTICIPANTS

Individuals studied had SARS-CoV-2 molecular diagnostic or antibody index test results from February 29 through December 9, 2020, with ≥365 days of pre-index continuous closed medical enrollment, claims, or electronic health record activity.

MAIN OUTCOMES AND MEASURES

Rates of reinfection among index-positive individuals were compared to rates of infection among index-negative individuals. Factors associated with reinfection were evaluated using multivariable logistic regression. For both objectives, the outcome was a subsequent positive molecular diagnostic test result.

RESULTS

Among 22,786,982 individuals with index SARS-CoV-2 laboratory test data (2,023,341 index positive), the crude rate of reinfection during follow-up was significantly lower (9.89/1,000-person years) than that of primary infection (78.39/1,000 person years). Consistent with prior findings, the risk of reinfection among index-positive individuals was 87% lower than the risk of infection among index-negative individuals (hazard ratio, 0.13; 95% CI, 0.13, 0.13). The cumulative incidence of reinfection among index-positive individuals and infection among index-negative individuals was 0.85% (95% CI: 0.82%, 0.88%) and 6.2% (95% CI: 6.1%, 6.3%), respectively, over follow-up of 375 days. The duration of protection against reinfection was stable over the median 5 months and up to 1-year follow-up interval. Factors associated with an increased reinfection risk included older age, comorbid immunologic conditions, and living in congregate care settings; healthcare workers had a decreased reinfection risk.

CONCLUSIONS AND RELEVANCE

This large US population-based study demonstrates that SARS-CoV-2 reinfection is uncommon among individuals with laboratory evidence of a previous infection. Protection from SARS-CoV-2 reinfection is stable up to one year. Reinfection risk was primarily associated with age 85+ years, comorbid immunologic conditions and living in congregate care settings; healthcare workers demonstrated a decreased reinfection risk. These findings suggest that infection induced immunity is durable for variants circulating prior to Delta.

KEY POINTS

Question: How long does prior SARS-CoV-2 infection provide protection against SARS-CoV-2 reinfection?Finding: Among >22 million individuals tested February 2020 through April 2021, the relative risk of reinfection among those with prior infection was 87% lower than the risk of infection among individuals without prior infection. This protection was durable for up to a year. Factors associated with increased likelihood of reinfection included older age (85+ years), comorbid immunologic conditions, and living in congregate care settings; healthcare workers had lower risk.Meaning: Prior SARS-CoV-2 infection provides a durable, high relative degree of protection against reinfection.

Association between antiulcer agents and Clostridioides difficile infection in patients receiving antibiotics: A retrospective cohort study using the diagnosis procedure combination database in Japan

OBJECTIVES

To evaluate baseline risk for hospital onset Clostridioides difficile infection (HO-CDI) and the association with the use of antiulcer agents among patients undergoing antibiotic therapy in Japan.

METHODS

We conducted a retrospective cohort study using Japanese Diagnosis Procedure Combination database. Between July 2018 and January 2019, patients aged ≥18 years were included if they started antibiotics within two days of hospital admission. We defined exposure as proton pump inhibitors or histamine 2 receptor antagonists starting from day 2 to day 4 and the primary outcome as HO-CDI within 30 days. We performed multivariable analyses with complete cases using the propensity score (inverse probability treatment weighting [IPTW]) and several sensitivity analyses.

RESULTS

In total, 87,137 patients were included. The median age was 78 years; 52.0% were men, and 23.6% received antiulcer agents. Within 30 days of admission, HO-CDI were observed in 0.41% and 0.26% of the antiulcer agent and control groups, respectively. IPTW revealed a positive association between antiulcer agents and HO-CDI (adjusted odds ratio, 1.33; 95% confidence interval [CI]: 1.13, 1.56). In the IPTW method, the risk difference was smaller (0.09%, 95% CI: 0.04%, 0.15%).

CONCLUSION

The use of antiulcer agents in patients with antibiotics was associated with HO-CDI in Japan. However, the baseline risk and the difference in HO-CDI event rates were small; thus, as per several clinical practice guidelines, it is important to monitor antiulcer agent use and discontinue unnecessary use. The baseline risk should be considered when clinically evaluating the association between antiulcer agents and HO-CDI.

Effect of Early Tracheostomy on Mortality of Mechanically Ventilated Patients with Guillain-Barré Syndrome: A Nationwide Observational Study

Background

Patients with Guillain–Barré syndrome (GBS) who require mechanical ventilation (MV) are regarded as candidates for early tracheostomy because of the high risk of prolonged MV; however, the association between early tracheostomy and favorable outcomes in patients with GBS remains unclear. In this study, we evaluated the association between early tracheostomy and outcomes in mechanically ventilated patients with GBS.

Methods

This retrospective observational study included adult patients with GBS identified in the Japanese Diagnosis Procedure Combination national inpatient database from July 1, 2010, to March 31, 2018, who initiated MV within the first week of admission and who received MV for more than 1 week. Early tracheostomy was defined as tracheostomy performed within 7 days of MV. The primary outcome was in-hospital mortality, and the secondary outcomes were 28-day mortality, nosocomial pneumonia, length of hospital stay, length of intensive care unit (ICU) stay, duration of MV, duration of sedation, duration of analgesia, duration of delirium, and total hospitalization costs. Propensity scores for early tracheostomy were calculated using a logistic regression model on the following variables: age; sex; body mass index; Japan Coma Scale status at admission; Charlson comorbidity index score; comorbidity of chronic pulmonary disease; complication of pneumonia at admission; complication of hyponatremia at admission; neurological presentation at admission; ambulance use; referral from other hospitals; treatment year; days from hospital admission to MV initiation; ICU admission until the day of MV initiation; and treatments until the day of MV initiation. Stabilized inverse probability of treatment weighting analyses was performed to compare the outcomes between patients with and without early tracheostomy.

Results

Among 919 eligible patients, 654 patients (71%) underwent tracheostomy, with 136 patients (15%) receiving early tracheostomy. Overall, the median time from initiation of MV to tracheostomy was 12 days (interquartile range 8–15 days). After stabilized inverse probability of treatment weighting, early tracheostomy was not associated with lower in-hospital mortality (risk difference 0.4%; 95% confidence interval − 5.6 to 6.7%) compared with patients without early tracheostomy. There were no significant differences in 28-day mortality (risk difference − 1.3%; 95% confidence interval − 3.5 to 0.9%) and incidence of nosocomial pneumonia (risk difference − 2.6%; 95% confidence interval − 9.1 to 4.2%) between the two groups. None of the other secondary outcomes differed significantly between the groups.

Conclusions

Early tracheostomy was not significantly associated with decreased mortality or morbidity in patients with GBS requiring MV for more than 1 week.

Evaluation of the accuracy of diagnostic coding for influenza compared to laboratory results: the availability of test results before hospital discharge facilitates improved coding accuracy

Background

Assessing the accuracy of diagnostic coding is essential to ensure the validity and reliability of administrative coded data. The aim of the study was to evaluate the accuracy of assigned International Classification of Diseases version 10-Australian Modification (ICD-10-AM) codes for influenza by comparing with patients’ results of their polymerase chain reaction (PCR)-based laboratory tests.

Method

A retrospective study was conducted across seven public hospitals in New South Wales, Australia. A total of 16,439 patients who were admitted and tested by either cartridge-based rapid PCR or batched multiplex PCR between January 2016 and December 2017 met the inclusion criteria. We calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of ICD-10-AM coding using laboratory results as a gold standard. Separate analyses were conducted to determine whether the availability of test results at the time of hospital discharge influenced diagnostic coding accuracy.

Results

Laboratory results revealed 2759 positive influenza cases, while ICD-10-AM coding identified 2527 patients. Overall, 13.7% (n = 378) of test positive patients were not assigned an ICD-10-AM code for influenza. A further 5.8% (n = 146) patients with negative test results were incorrectly assigned an ICD-10-AM code for influenza. The sensitivity, specificity, PPV and NPV of ICD-10-AM coding were 93.1%; 98.9%; 94.5% and 98.6% respectively when test results were received before discharge and 32.7%; 99.2%; 87.8% and 89.8% respectively when test results were not available at discharge. The sensitivity of ICD-10-AM coding varied significantly across hospitals. The use of rapid PCR or hospitalisation during the influenza season were associated with greater coding accuracy.

Conclusion

Although ICD-10-AM coding for influenza demonstrated high accuracy when laboratory results were received before discharge, its sensitivity was substantially lower for patients whose test results were not available at discharge. The timely availability of laboratory test results during the episode of care could contribute to improved coding accuracy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01531-9.

Spatial Patterns in Hospital-Acquired Infections in Portugal (2014-2017)

BACKGROUND

Hospital-Acquired Infections (HAIs) represent the most frequent adverse event associated with healthcare delivery and result in prolonged hospital stays and deaths worldwide.

AIM

To analyze the spatial patterns of HAI incidence from 2014 to 2017 in Portugal.

METHODS

Data from the Portuguese Discharge Hospital Register were used. We selected episodes of patients with no infection on admission and with any of the following HAI diagnoses: catheter-related bloodstream infections, intestinal infections by Clostridium difficile, nosocomial pneumonia, surgical site infections, and urinary tract infections. We calculated age-standardized hospitalization rates (ASHR) by place of patient residence. We used empirical Bayes estimators to smooth the ASHR. The Moran Index and Local Index of Spatial Autocorrelation (LISA) were calculated to identify spatial clusters.

RESULTS

A total of 318,218 HAIs were registered, with men accounting for 49.8% cases. The median length of stay (LOS) was 9.0 days, and 15.7% of patients died during the hospitalization. The peak of HAIs (n = 81,690) occurred in 2015, representing 9.4% of the total hospital admissions. Substantial spatial inequalities were observed, with the center region presenting three times the ASHR of the north. A slight decrease in ASHR was observed after 2015. Pneumonia was the most frequent HAI in all age groups.

CONCLUSION

The incidence of HAI is not randomly distributed in the space; clusters of high risk in the central region were seen over the entire study period. These findings may be useful to support healthcare policymakers and to promote a revision of infection control policies, providing insights for improved implementation.

Gender differences in incidence and in-hospital outcomes of community-acquired, ventilator-associated and nonventilator hospital-acquired pneumonia in Spain

AIMS

We aim to compare the incidence and in-hospital outcomes of community-acquired pneumonia (CAP), ventilator-associated pneumonia (VAP) and nonventilator hospital-acquired pneumonia (NV-HAP) according to gender.

METHODS

This was a retrospective observational epidemiological study using the Spanish National Hospital Discharge Database for the years 2016 and 2017.

RESULTS

Of 277 785 hospital admissions, CAP was identified in 257 455 (41.04% females), VAP was identified in 3261 (30.42% females) and NV-HAP was identified in 17 069 (36.58% females). The incidence of all types of pneumonia was higher amongst males (CAP: incidence rate ratio [IRR] 1.05, 95% CI 1.03-1.06; VAP: IRR 1.36, 95% CI 1.26-1.46; and NV-HAP: IRR 1.16, 95% CI 1.14-1.18). The crude in-hospital mortality (IHM) rate for CAP was 11.44% in females and 11.80% in males (P = .005); for VAP IHM, the rate was approximately 35% in patients of both genders and for NV-HAP IHM, the rate was 23.97% for females and 26.40% for males (P < .001). After multivariable adjustment, in patients of both genders, older age and comorbidities were factors associated with IHM in the three types of pneumonia analysed. Female gender was a risk factor for IHM after VAP (OR 1.24; 95% CI 1.06-1.44), and no gender differences were found for CAP or NV-HAP.

CONCLUSIONS

Our findings show a difference between females and males, with females presenting a lower incidence of all types of pneumonia. However, female gender was a risk factor for IHM after VAP.

Characterizing Clostridioides difficile infections and hospital exposures in California using surveillance and administrative data, 2014-2015

OBJECTIVE

To evaluate a method to identify hospitals contributing to Clostridioides difficile infections (CDI) at subsequent hospitalizations.

DESIGN

Retrospective cohort study.

METHODS

We merged 2014-2015 National Healthcare Safety Network (NHSN) inpatient CDI laboratory-identified events with hospital patient discharge data. For patients with incident community-onset CDI (CO CDI), we identified immediately preceding admissions (within 12 weeks) unrelated to CDI at different (exposure) hospitals. We calculated an exposure rate, and we selected hospitals with the highest (90th-100th percentile) rates by hospital type and compared these rates with reported standardized infection ratios (SIR) for CDI.

RESULTS

We successfully matched 44,691 of 58,842 NHSN CDI records (76.0%) with a hospital discharge record. Among 36,215 unique matched records, 5,234 (14.5%) had an admission not related to CDI within 12 weeks prior to an incident CO CDI event, and 1,574 of these admissions (30.1%) occurred in a different hospital. For 33 hospitals with an exposure ranking within the 90th-100th percentile, CDI SIRs for 22 (66.7%) were not significantly different; 3 (9.1%) were lower; and 8 (24.2%) were higher than the national baseline. Also, 12 (36.4%) had an SIR ≤1.0.

CONCLUSIONS

The identification of high-ranked exposure hospitals presents an alternative to SIR for measuring the contribution of hospitals to the CDI burden across the continuum of care. Further exploration of the potential factors leading to high exposure rank, such as antibiotic use and infection control practices, is indicated and may inform CDI prevention outreach to healthcare facilities and provider networks in California and elsewhere.

Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV

Background

Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed.

Methods

We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP.

Results

Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480-487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted.

Conclusions

ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH.

Capturing adverse events in elective orthopedic surgery: comparison of administrative, surgeon and reviewer reporting

Summary

Ensuring adverse event (AE) recording is standardized and accurate is paramount for patient safety. In this discussion, we outline our comparison of AE data collected by orthopedic surgeons and independent clinical reviewers using the Spine Adverse Events Severity System (SAVES) and Orthopedic Surgical Adverse Events Severity System (OrthoSAVES) against AE data recorded by hospital administrative discharge abstract coders. In 164 spine, hip, knee and shoulder patients, reviewers recorded significantly more AEs than coders, and coders recorded significantly more AEs than surgeons. The AEs were recorded similarly by reviewers using SAVES and OrthoSAVES in 48 spine patients. Despite our small sample size and use of different AE tools, we believe it is important to highlight that coders, surgeons and reviewers recorded AEs differently. While further investigations on its utility and cost-effectiveness are necessary, we assert that it is feasible to use Ortho-SAVES to prospectively record AEs across all orthopedic subspecialties.

Sepsis in the Context of Nonventilator Hospital-Acquired Pneumonia

BACKGROUND

Sepsis is a leading cause of mortality among hospitalized patients and is the most expensive condition affecting the US health care system. Pneumonia is associated with about half of sepsis cases, yet limited research has described the incidence of sepsis in the context of nonventilator hospital-acquired pneumonia (NV-HAP). Persons with NV-HAP who are at risk for sepsis must be identified so that interventions to reduce the burden of NV-HAP and improve outcomes among patients with sepsis can be designed.

OBJECTIVE

To determine the proportion of persons with NV-HAP in whom sepsis develops and to describe the demographic and clinical characteristics of persons with NV-HAP in whom sepsis develops.

METHODS

In this retrospective, population-based study, data were extracted from the National Inpatient Sample from the 2012 Healthcare Cost and Utilization Project dataset. International Classification of Diseases, Ninth Revision, Clinical Modification codes were used to identify adult patients at least 18 years of age who had a stay of at least 48 hours, had no documented diagnosis of ventilator-associated pneumonia, and had secondary diagnoses of both NV-HAP and sepsis, neither of which was present on admission.

RESULTS

In the 2012 calendar year, 119 075 adults had NV-HAP develop; sepsis developed in 36.3% of these cases. Male and black patients were overrepresented in the sample, and patients had a mean of 7 comorbid conditions (SD, 3.3).

CONCLUSIONS

Sepsis in the context of NV-HAP is a key concern. Additional research is needed to identify factors associated with the development of sepsis among patients with NV-HAP.

An ethnographic study of improving data collection and completeness in large-scale data exercises

Background: Large-scale data collection is an increasingly prominent and influential feature of efforts to improve healthcare delivery, yet securing the involvement of clinical centres and ensuring data comprehensiveness often proves problematic. We explore how improvements in both data submission and completion rates were achieved during a crucial period of the evolution of two large-scale data exercises. Methods:  As part of an evaluation of a quality improvement programme, we conducted an ethnographic study involving 90 interviews and 47 days of non-participant observation of two UK national clinical audits in a period before submission of data on adherence to clinical standards became mandatory. Results: Critical to the improvements in submission and completion rates in the two exercises were the efforts of clinical leaders to refigure "data work" as a professionalization strategy. Using a series of strategic manoeuvres, leaders constructed a cultural account that tied the fortunes of the healthcare professions to the submission of high-quality data, proposing that it would demonstrate responsibility, transparency, and alignment with the public interest. In so doing, clinical leadership deployed tactics that might have been seen as unwarranted managerial aggression had they been imposed by parties external to the profession. Many residual challenges were linked not to principled objection by clinicians, but to mundane problems and frustrations in obtaining, recording, and submitting data. The cultural framing of data work as a professional duty was important to resolving its status as an abject form of labour. Conclusions: Improving data quality in large-scale exercises is possible, but requires cooperation with clinical centres. Enabling professional leadership of data work may offer some significant advantages, but attention is also needed to mundane and highly consequential obstacles to participation in data collection.

Randomised controlled trial of a theory-based intervention to prompt front-line staff to take up the seasonal influenza vaccine

OBJECTIVE

To evaluate the effectiveness of reminder letters informed by social normative theory (a type of 'nudge theory') on uptake of seasonal influenza vaccination by front-line hospital staff.

DESIGN

Individually randomised controlled trial.

SETTING

A large acute care hospital in England.

PARTICIPANTS

Front-line staff employed by the hospital (n=7540) were randomly allocated to one of four reminder types in a factorial design.

INTERVENTIONS

The standard letter included only general information directing the staff to take up the vaccine. A second letter highlighted a type of social norm based on peer comparisons. A third letter highlighted a type of social norm based on an appeal to authority. A fourth letter included a combination of the social norms.

MAIN OUTCOME MEASURE

The proportion of hospital staff vaccinated on-site.

RESULTS

Vaccine coverage was 43% (812/1885) in the standard letter group, 43% (818/1885) in the descriptive norms group, 43% (814/1885) in the injunctive norms group and 43% (812/1885) in the combination group. There were no statistically significant effects of either norm or the interaction. The OR for the descriptive norms factor is 1.01 (0.89-1.15) in the absence of the injunctive norms factor and 1.00 (0.88-1.13) in its presence. The OR for the injunctive norms factor is 1.00 (0.88-1.14) in the absence of the descriptive norms factor and 0.99 (0.87-1.12) in its presence.

CONCLUSIONS

We find no evidence that the uptake of the seasonal influenza vaccination is affected by reminders using social norms to motivate uptake.

Randomised controlled trial of a theory-based intervention to prompt front-line staff to take up the seasonal influenza vaccine

Objective

To evaluate the effectiveness of reminder letters informed by social normative theory (a type of ‘nudge theory’) on uptake of seasonal influenza vaccination by front-line hospital staff.

Design

Individually randomised controlled trial.

Setting

A large acute care hospital in England.

Participants

Front-line staff employed by the hospital (n=7540) were randomly allocated to one of four reminder types in a factorial design.

Interventions

The standard letter included only general information directing the staff to take up the vaccine. A second letter highlighted a type of social norm based on peer comparisons. A third letter highlighted a type of social norm based on an appeal to authority. A fourth letter included a combination of the social norms.

Main outcome measure

The proportion of hospital staff vaccinated on-site.

Results

Vaccine coverage was 43% (812/1885) in the standard letter group, 43% (818/1885) in the descriptive norms group, 43% (814/1885) in the injunctive norms group and 43% (812/1885) in the combination group. There were no statistically significant effects of either norm or the interaction. The OR for the descriptive norms factor is 1.01 (0.89–1.15) in the absence of the injunctive norms factor and 1.00 (0.88–1.13) in its presence. The OR for the injunctive norms factor is 1.00 (0.88–1.14) in the absence of the descriptive norms factor and 0.99 (0.87–1.12) in its presence.

Conclusions

We find no evidence that the uptake of the seasonal influenza vaccination is affected by reminders using social norms to motivate uptake.

Effect of data validation audit on hospital mortality ranking and pay for performance

Background

Quality improvement and epidemiology studies often rely on database codes to measure performance or impact of adjusted risk factors, but how validity issues can bias those estimates is seldom quantified.

Objectives

To evaluate whether and how much interhospital administrative coding variations influence a typical performance measure (adjusted mortality) and potential incentives based on it.

Design

National cross-sectional study comparing hospital mortality ranking and simulated pay-for-performance incentives before/after recoding discharge abstracts using medical records.

Setting

Twenty-four public and private hospitals located in France

Participants

All inpatient stays from the 78 deadliest diagnosis-related groups over 1 year.

Interventions

Elixhauser and Charlson comorbidities were derived, and mortality ratios were computed for each hospital. Thirty random stays per hospital were then recoded by two central reviewers and used in a Bayesian hierarchical model to estimate hospital-specific and comorbidity-specific predictive values. Simulations then estimated shifts in adjusted mortality and proportion of incentives that would be unfairly distributed by a typical pay-for-performance programme in this situation.

Main outcome measures

Positive and negative predictive values of routine coding of comorbidities in hospital databases, variations in hospitals’ mortality league table and proportion of unfair incentives.

Results

A total of 70 402 hospital discharge abstracts were analysed, of which 715 were recoded from full medical records. Hospital comorbidity-level positive predictive values ranged from 64.4% to 96.4% and negative ones from 88.0% to 99.9%. Using Elixhauser comorbidities for adjustment, 70.3% of hospitals changed position in the mortality league table after correction, which added up to a mean 6.5% (SD 3.6) of a total pay-for-performance budget being allocated to the wrong hospitals. Using Charlson, 61.5% of hospitals changed position, with 7.3% (SD 4.0) budget misallocation.

Conclusions

Variations in administrative data coding can bias mortality comparisons and budget allocation across hospitals. Such heterogeneity in data validity may be corrected using a centralised coding strategy from a random sample of observations.

Effectiveness of a multistate quality improvement campaign in reducing risk of surgical site infections following hip and knee arthroplasty

BACKGROUND

Quality improvement (QI) campaigns appear to increase use of evidence-based practices, but their effect on health outcomes is less well studied.

OBJECTIVE

To assess the effect of a multistate QI campaign (Project JOINTS, Joining Organizations IN Tackling SSIs) that used the Institute for Healthcare Improvement's Rapid Spread Network to promote adoption of evidence-based surgical site infection (SSI) prevention practices.

METHODS

We analysed rates of SSI among Medicare beneficiaries undergoing hip and knee arthroplasty during preintervention (May 2010 to April 2011) and postintervention (November 2011 to September 2013) periods in five states included in a multistate trial of the Project JOINTS campaign and five matched comparison states. We used generalised linear mixed effects models and a difference-in-differences approach to estimate changes in SSI outcomes.

RESULTS

125 070 patients underwent hip arthroplasty in 405 hospitals in intervention states, compared with 131 787 in 525 hospitals in comparison states. 170 663 patients underwent knee arthroplasty in 397 hospitals in intervention states, compared with 196 064 in 518 hospitals in comparison states. After the campaign, patients in intervention states had a 15% lower odds of developing hip arthroplasty SSIs (OR=0.85, 95% CI 0.75 to 0.96, p=0.01) and a 12% lower odds of knee arthroplasty SSIs than patients in comparison states (OR=0.88, 95% CI 0.78 to 0.99, p=0.04).

CONCLUSIONS

A larger reduction of SSI rates following hip and knee arthroplasty was shown in intervention states than in matched control states.

Risk of Clostridium difficile Infection in Patients With Celiac Disease: A Population-Based Study

OBJECTIVES

Patients with celiac disease are at increased risk for infections such as tuberculosis, influenza, and pneumococcal pneumonia. However, little is known about the incidence of Clostridium difficile infection (CDI) in patients with celiac disease.

METHODS

We identified patients with celiac disease based on intestinal biopsies submitted to all pathology departments in Sweden over a 39-year period (from July 1969 through February 2008). We compared risk of CDI (based on stratified Cox proportional hazards models) among patients with celiac disease vs. without celiac disease (controls) matched by age, sex, and calendar period.

RESULTS

We identified 28,339 patients with celiac disease and 141,588 controls; neither group had a history of CDI. The incidence of CDI was 56/100,000 person-years among patients with celiac disease and 26/100,000 person-years among controls, yielding an overall hazard ratio (HR) of 2.01 (95% confidence interval (CI), 1.64-2.47; P<0.0001). The risk of CDI was highest in the first 12 months after diagnosis of celiac disease (HR, 5.20; 95% CI, 2.81-9.62; P<0.0001), but remained high, compared to that of controls, 1-5 years after diagnosis (HR, 1.85; 95% CI, 1.22-2.81; P=0.004). Among 493 patients with CDI, antibiotic data were available for 251; there were no significant differences in prior exposures to antibiotics between patients with celiac disease and controls.

CONCLUSIONS

In a large population-based cohort study, patients with celiac disease had significantly higher incidence of CDI than controls. This finding is consistent with prior findings of higher rates of other infections in patients with celiac disease, and suggests the possibility of altered gut immunity and/or microbial composition in patients with celiac disease.