Whole-Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection.

BACKGROUND: Most hospitals use traditional infection prevention (IP) methods for outbreak detection. We developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning (ML) of the electronic health record (EHR) to identify undetected outbreaks and the responsible transmission routes, respectively. METHODS: We performed WGS surveillance of healthcare-associated bacterial pathogens from November 2016 to November 2018. EHR ML was used to identify the transmission routes for WGS-detected outbreaks, which were investigated by an IP expert. Potential infections prevented were estimated and compared with traditional IP practice during the same period. RESULTS: Of 3165 isolates, there were 2752 unique patient isolates in 99 clusters involving 297 (10.8%) patient isolates identified by WGS; clusters ranged from 2-14 patients. At least 1 transmission route was detected for 65.7% of clusters. During the same time, traditional IP investigation prompted WGS for 15 suspected outbreaks involving 133 patients, for which transmission events were identified for 5 (3.8%). If EDS-HAT had been running in real time, 25-63 transmissions could have been prevented. EDS-HAT was found to be cost-saving and more effective than traditional IP practice, with overall savings of $192 408-$692 532. CONCLUSIONS: EDS-HAT detected multiple outbreaks not identified using traditional IP methods, correctly identified the transmission routes for most outbreaks, and would save the hospital substantial costs. Traditional IP practice misidentified outbreaks for which transmission did not occur. WGS surveillance combined with EHR ML has the potential to save costs and enhance patient safety.

Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance.

BACKGROUND: Traditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and to determine the responsible transmission routes. METHODS: We performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24-month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm. RESULTS: We identified a cluster of 6 genetically related P. aeruginosa cases that occurred during a 7-month period. The ML algorithm identified gastroscopy as a potential transmission route for 4 of the 6 patients. Manual EHR review confirmed gastroscopy as the most likely route for 5 patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on 4of the 5 patients. Three infections, 2 of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time. CONCLUSIONS: WGS surveillance combined with a ML algorithm of the EHR identified a previously undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.

Outbreak of Vancomycin-resistant Enterococcus faecium in Interventional Radiology: Detection Through Whole-genome Sequencing-based Surveillance.

BACKGROUND: Vancomycin-resistant enterococci (VRE) are a major cause of hospital-acquired infections. The risk of infection from interventional radiology (IR) procedures is not well documented. Whole-genome sequencing (WGS) surveillance of clinical bacterial isolates among hospitalized patients can identify previously unrecognized outbreaks. METHODS: We analyzed WGS surveillance data from November 2016 to November 2017 for evidence of VRE transmission. A previously unrecognized cluster of 10 genetically related VRE (Enterococcus faecium) infections was discovered. Electronic health record review identified IR procedures as a potential source. An outbreak investigation was conducted. RESULTS: Of the 10 outbreak patients, 9 had undergone an IR procedure with intravenous (IV) contrast ≤22 days before infection. In a matched case-control study, preceding IR procedure and IR procedure with contrast were associated with VRE infection (matched odds ratio [MOR], 16.72; 95% confidence interval [CI], 2.01 to 138.73; P = .009 and MOR, 39.35; 95% CI, 7.85 to infinity; P < .001, respectively). Investigation of IR practices and review of the manufacturer's training video revealed sterility breaches in contrast preparation. Our investigation also supported possible transmission from an IR technician. Infection prevention interventions were implemented, and no further IR-associated VRE transmissions have been observed. CONCLUSIONS: A prolonged outbreak of VRE infections related to IR procedures with IV contrast resulted from nonsterile preparation of injectable contrast. The fact that our VRE outbreak was discovered through WGS surveillance and the manufacturer's training video that demonstrated nonsterile technique raise the possibility that infections following invasive IR procedures may be more common than previously recognized.

Statistical outbreak detection by joining medical records and pathogen similarity.

We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines patient exposures, determined from electronic medical records, and pathogen similarity, determined by whole-genome sequencing, to simultaneously identify probable outbreaks and their root-causes. We show how our model can be used to target isolates for whole-genome sequencing, improving outbreak detection and characterization even without comprehensive sequencing. Additionally, we demonstrate how to learn model parameters from reference data of known outbreaks. We demonstrate model performance using semi-synthetic experiments.

Clinical Outcomes and Mortality Impact of Hyperbaric Oxygen Therapy in Patients With Carbon Monoxide Poisoning.

OBJECTIVES: Carbon monoxide poisoning affects 50,000 per year in the United States alone. Mortality is approximately 3%, and up to 40% of survivors suffer from permanent neurocognitive and affective deficits. Hyperbaric oxygen therapy has shown benefit on reducing the long-term neurologic sequelae of carbon monoxide poisoning but has not demonstrated improved survival. The objective of this study is to assess the efficacy of hyperbaric oxygen for acute and long-term mortality in carbon monoxide poisoning using a large clinical databank. DESIGN: Retrospective analysis. SETTING: University of Pittsburgh Medical Center healthcare system (Pittsburgh, PA). PATIENTS: One-thousand ninety-nine unique encounters of adult patients with carbon monoxide poisoning. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Baseline demographics, laboratory values, hospital charge transactions, discharge disposition, and clinical information from charting were obtained from the electronic medical record. In propensity-adjusted analysis, hyperbaric oxygen therapy was associated with a reduction in inpatient mortality (absolute risk reduction, 2.1% [3.7-0.9%]; p = 0.001) and a reduction in 1-year mortality (absolute risk reduction, 2.1% [3.8-0.4%]; p = 0.013). CONCLUSIONS: These data demonstrate that hyperbaric oxygen is associated with reduced acute and reduced 1-year mortality. Further studies are needed on the mortality effects of hyperbaric oxygen therapy in carbon monoxide poisoning.

Estimating the cost of skin cancer detection by dermatology providers in a large health care system.

BACKGROUND: Data on the cost and efficiency of skin cancer detection through total body skin examination are scarce. OBJECTIVE: To determine the number needed to screen (NNS) and biopsy (NNB) and cost per skin cancer diagnosed in a large dermatology practice in patients undergoing total body skin examination. METHODS: This is a retrospective observational study. RESULTS: During 2011-2015, a total of 20,270 patients underwent 33,647 visits for total body skin examination; 9956 lesion biopsies were performed yielding 2763 skin cancers, including 155 melanomas. The NNS to detect 1 skin cancer was 12.2 (95% confidence interval [CI] 11.7-12.6) and 1 melanoma was 215 (95% CI 185-252). The NNB to detect 1 skin cancer was 3.0 (95% CI 2.9-3.1) and 1 melanoma was 27.8 (95% CI 23.3-33.3). In a multivariable model for NNS, age and personal history of melanoma were significant factors. Age switched from a protective factor to a risk factor at 51 years of age. The estimated cost per melanoma detected was $32,594 (95% CI $27,326-$37,475). LIMITATIONS: Data are from a single health care system and based on physician coding. CONCLUSION: Melanoma detection through total body skin examination is most efficient in patients ≥50 years of age and those with a personal history of melanoma. Our findings will be helpful in modeling the cost effectiveness of melanoma screening by dermatologists.

Risk Factors for Hidradenitis Suppurativa in Patients with Inflammatory Bowel Disease.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder characterized by recurrent nodules, abscesses, and sinus tracts that can be debilitating and significantly impair quality of life. Small studies and case reports have suggested a possible association between HS and inflammatory bowel disease (IBD). AIMS: We performed a case-control study to further characterize IBD patients with HS in terms of smoking status, BMI, sites affected by HS, IBD type and features, and IBD medication history. METHODS: A total of 38 patients with HS and IBD were identified and matched on age, gender, and IBD type to 136 controls with IBD but not HS. Clinical characteristics of interest were obtained through extensive review of the electronic health record. RESULTS: Among patients with HS and IBD, the most common sites affected by HS were the inguinal, perianal, and axillary regions. Relative to patients with IBD alone, patients with HS and IBD were nearly six times more likely to be current smokers (p < 0.01) and nearly 11 times more likely to be obese (p < 0.01). Patients with HS and Crohn's were significantly more likely to have ileocolonic and perianal disease than patients with CD only (OR 8.31, 95% CI 2.90-23.80 and OR 2.85, 95% CI 1.19-6.81, respectively; p < 0.01 for both). CONCLUSIONS: Relative to patients with IBD who do not develop HS, patients with IBD and HS are more likely to be overweight or obese, to be former or current smokers, and to have ileocolonic and/or perianal disease.

Downstream consequences of melanoma screening in a community practice setting: First results.

BACKGROUND: Population-based screening for the early detection of melanoma holds great promise for reducing melanoma mortality, but evidence is needed to determine whether benefits outweigh risks. Skin surgeries and dermatology visits after screening were assessed to indicate potential physical, psychological, and financial consequences. METHODS: Targeted primary care providers (PCPs) at the University of Pittsburgh Medical Center were trained to detect early melanoma using the INFORMED (INternet course FOR Melanoma Early Detection) program. The authors analyzed aggregated administrative data describing 3 groups of patients aged ≥35 years who had received an annual physical examination by PCPs: group A1 included patients of PCPs from the group with the highest percentage of INFORMED-trained providers, group A2 included patients of PCPs from the group with a lower percentage of INFORMED-trained providers, and group B included patients of PCPs without INFORMED training. RESULTS: INFORMED-trained PCPs screened 1572 of 16,472 patients in groups A1 or A2 and none of the 56,261 patients in group B. In group A1, there was a 79% increase (95% confidence interval, 15%-138%) in melanoma diagnoses noted; no increase was observed for the other groups, and no substantial increase in skin surgeries or dermatology visits occurred in any group. CONCLUSIONS: A large-scale melanoma screening using the INFORMED program was conducted in Pennsylvania. To the best of the authors' knowledge, the current study is the first analysis of downstream results and the findings indicate increased melanoma diagnoses but little impact on skin surgeries or dermatology visits. This result provides some reassurance that such efforts can be conducted without major adverse consequences, at least as measured by these parameters, and therefore should be considered for more widespread use. Cancer 2016;122:3152-6. © 2016 American Cancer Society.

Hepatic steatosis in diabetic patients does not predict adverse liver-related or cardiovascular outcomes.

BACKGROUND & AIMS: Steatosis is a defining feature of nonalcoholic fatty liver disease (NAFLD). However, evidence that severity of steatosis can predict adverse outcomes in NAFLD or nonalcoholic steatohepatitis (NASH) is lacking. The aim of this study was to determine whether steatosis assessed by computed tomography (CT) imaging predicts adverse outcomes in diabetic patients at risk for NAFLD/NASH. METHODS: We studied deaths, liver-related and cardiovascular adverse outcomes in a 5-year retrospective observational cohort of 2343 type 2 diabetic patients in a large care network who had noncontrast CT imaging for clinical indications. We measured steatosis by subtraction of spleen from liver attenuation, a method that showed low sensitivity (0.417) and high specificity (0.882) compared with histopathological scoring. We evaluated outcomes prediction using multivariate Cox proportional hazards modelling of steatosis both as a categorical (≥ 30%) and continuous variable. RESULTS: Steatosis ≥ 30% was present in 233 (9.9%) of the cohort at baseline. Over 5 years, there were 372 total deaths, 18 liver-related and 99 cardiovascular deaths, 48 liver transplants, 51 occurrences of hepatic encephalopathy, 41 hepatocellular carcinomas, 653 myocardial infarctions, 66 strokes, 180 occurrences of angina, 735 occurrences of arrhythmia and 772 occurrences of congestive heart failure. Steatosis had no predictive value for any adverse outcome. Patients with steatosis averaged 8 years younger than those without it. Age had a strong covariate influence on occurrence of total deaths, cardiovascular deaths, myocardial infarctions, arrhythmias and congestive heart failure. CONCLUSION: Although steatosis on imaging is often the abnormality that triggers diagnosis and assessment of NAFLD/NASH, it lacks predictive value for adverse clinical outcomes.

Heart-Brain 346-7 Score: the development and validation of a simple mortality prediction score for carbon monoxide poisoning utilizing deep learning.

INTRODUCTION: Acute mortality from carbon monoxide poisoning is 1-3%. The long-term mortality risk of survivors of carbon monoxide poisoning is doubled compared to age-matched controls. Cardiac involvement also increases mortality risk. We built a clinical risk score to identify carbon monoxide-poisoned patients at risk for acute and long-term mortality. METHODS: We performed a retrospective analysis. We identified 811 adult carbon monoxide-poisoned patients in the derivation cohort, and 462 adult patients in the validation cohort. We utilized baseline demographics, laboratory values, hospital charge transactions, discharge disposition, and clinical charting information in the electronic medical record in Stepwise Akaike's Information Criteria with Firth logistic regression to determine optimal parameters to create a prediction model. RESULTS: In the derivation cohort, 5% had inpatient or 1-year mortality. Three variables following the final Firth logistic regression minimized Stepwise Akaike's Information Criteria: altered mental status, age, and cardiac complications. The following predict inpatient or 1-year mortality: age > 67, age > 37 with cardiac complications, age > 47 with altered mental status, or any age with cardiac complications and altered mental status. The sensitivity of the score was 82% (95% confidence interval: 65-92%), the specificity was 80% (95% confidence interval: 77-83%), negative predictive value was 99% (95% confidence interval: 98-100%), positive predictive value 17% (95% confidence interval: 12-23%), and the area under the receiver operating characteristic curve was 0.81 (95% confidence interval: 0.74-0.87). A score above the cut-off point of -2.9 was associated with an odds ratio of 18 (95% confidence interval: 8-40). In the validation cohort (462 patients), 4% had inpatient death or 1-year mortality. The score performed similarly in the validation cohort: sensitivity was 72% (95% confidence interval: 47-90%), specificity was 69% (95% confidence interval: 63-73%), negative predictive value was 98% (95% confidence interval: 96-99%), positive predictive value was 9% (95% confidence interval: 5-15%) and the area under the receiver operating characteristic curve was 0.70 (95% confidence interval: 60%-81%). CONCLUSIONS: We developed and validated a simple, clinical-based scoring system, the Heart-Brain 346-7 Score to predict inpatient and long-term mortality based on the following: age > 67, age > 37 with cardiac complications, age > 47 with altered mental status, or any age with cardiac complications and altered mental status. With further validation, this score will hopefully aid decision-making to identify carbon monoxide-poisoned patients with higher mortality risk.

A longitudinal examination of patient portal use on glycemic control among patients with uncontrolled type 2 diabetes.

AIM: This study examined glycemia level over a 2-year period between portal users and non-users. METHODS: This retrospective cohort study used data from electronic health records (EHRs) of a large academic medical center and its ancillary patient portal. A total of 15,528 patients with uncontrolled type 2 diabetes mellitus (T2DM) were included. Using propensity score matching (PSM), portal users and non-users were balanced on demographic and clinical characteristics. Mixed-effects polynomial regression modeling was employed to evaluate the HbA1c change over time between groups. RESULTS: The patient sample was 85.9% (13,333) white and 52.5% (7375) male. On average, patients were 62.8 (SD, 11.7) years old and with obesity (mean BMI: 34.2 ± 7.2 kg/m2) with uncontrolled T2DM (initial HbA1c: 8.5 ± 1.5%). After PSM, portal users (n = 4924) and non-users (n = 4924) were matched on all variables except for the insurance. The mixed-effects modeling showed a nonlinear decrease of HbA1c in both groups over time. A significant interaction was observed with a greater decline, followed by a smaller rise of HbA1c in portal users than non-users. CONCLUSIONS: The use of the patient portal was significantly associated with a lower HbA1c. This finding supports patient portals as a promising tool for improving clinical outcomes in patients with uncontrolled T2DM.

Systematic detection of horizontal gene transfer across genera among multidrug-resistant bacteria in a single hospital.

Multidrug-resistant bacteria pose a serious health threat, especially in hospitals. Horizontal gene transfer (HGT) of mobile genetic elements (MGEs) facilitates the spread of antibiotic resistance, virulence, and environmental persistence genes between nosocomial pathogens. We screened the genomes of 2173 bacterial isolates from healthcare-associated infections from a single hospital over 18 months, and identified identical nucleotide regions in bacteria belonging to distinct genera. To further resolve these shared sequences, we performed long-read sequencing on a subset of isolates and generated highly contiguous genomes. We then tracked the appearance of ten different plasmids in all 2173 genomes, and found evidence of plasmid transfer independent from bacterial transmission. Finally, we identified two instances of likely plasmid transfer within individual patients, including one plasmid that likely transferred to a second patient. This work expands our understanding of HGT in healthcare settings, and can inform efforts to limit the spread of drug-resistant pathogens in hospitals.

Bacteria are able to pass each other genes that make them invulnerable to antibiotics. This exchange of genetic material, also called horizontal gene transfer, can turn otherwise harmless bacteria into drug-resistant 'superbugs'. This is particularly problematic in hospitals, where bacteria use horizontal gene transfer to become resistant to several antibiotics and disinfectants at once, leading to serious infections that are difficult to treat. How can scientists stop bacteria from sharing genes with one another? To answer this question, first it is important to understand how horizontal gene transfer happens in the bacteria that cause infections in hospitals. To this end, Evans et al. examined the genomes of over 2000 different bacteria, collected from a hospital over 18 months, for signs of horizontal transfer. First the experiments identified the genetic material that had potentially been transferred between bacteria, also known as 'mobile genetic elements'. Next, Evans et al. examined the data of patients who had been infected with the bacteria carrying these mobile genetic elements to see whether horizontal transfer might have happened in the hospital. By combining genomics with patient data, it was determined that many of the mobile genetic elements identified were likely being shared among hospital bacteria. One of the mobile genetic elements identified was able to provide resistance to several drugs, and appeared to have been horizontally transferred between bacteria infecting two separate patients. The findings of Evans et al. show that the horizontal transfer of mobile genetic elements in hospital settings is likely frequent, but complex and difficult to study with current methods. The results of this study show how these events can now be tracked and analyzed, which may lead to new strategies for controlling the spread of antibiotic resistance.

High frequency of rifampin resistance identified in an epidemic Clostridium difficile clone from a large teaching hospital.

BACKGROUND: Rifampin is used as adjunctive therapy for Clostridium difficile-associated disease, and the drug's derivative, rifaximin, has emerged as an attractive antimicrobial for treatment of C. difficile-associated disease. Rifampin resistance in C. difficile strains has been reported to be uncommon. METHODS: We examined the prevalence of rifampin resistance among 470 C. difficile isolates (51.1% during 2001-2002 and 48.9% during 2005) from a large teaching hospital. Rifampin sensitivity was performed using E-test. The epidemic BI/NAP1 C. difficile clone was identified by tcdC genotyping and multilocus variable number of tandem repeats analysis. A 200-base pair fragment of the rpoB gene was sequenced for 102 isolates. Data on rifamycin exposures were obtained for all patients. RESULTS: Rifampin resistance was observed in 173 (36.8%) of 470 recovered isolates and 167 (81.5%) of 205 of epidemic clone isolates (P < .001). Six rpoB genotypes were associated with rifampin resistance. Of 8 patients exposed to rifamycins, 7 had rifampin-resistant C. difficile, compared with 166 of 462 unexposed patients (relative risk, 2.4; 95% confidence interval, 1.8-3.3). CONCLUSIONS: Rifampin resistance is common among epidemic clone C. difficile isolates at our institution. Exposure to rifamycins before the development of C. difficile-associated disease was a risk factor for rifampin-resistant C. difficile infection. The use of rifaximin may be limited for treatment of C. difficile-associated disease at our institution.

Improved outcomes with routine respiratory therapist evaluation of non-intensive-care-unit surgery patients.

BACKGROUND: Respiratory therapist (RT) driven protocols decrease ventilator days and resource utilization in the intensive care unit (ICU). Protocols have been studied in non-ICU settings, but their effect on mortality has been incompletely studied. METHODS: In our neurosurgery step-down, trauma/surgery step-down, and trauma/surgery general units we initiated an RT-driven evaluate-and-treat protocol that included a standardized, quantitative, RT-driven patient-assessment scale and protocolized interventions. Before and after initiation of the protocol we collected data on non-ICU patients at risk for pulmonary complications. RESULTS: The patient groups before (n = 2,230) and after (n = 2,805) protocol initiation were well matched in age, sex, Charlson score, and admitting service. Most of the patients, whether assessed by a physician or an RT, were deemed to have low risk of pulmonary complications and did not require any respiratory treatments. The number of respiratory treatments increased after protocol initiation, but the patients who received respiratory treatments after protocol initiation had shorter ICU stay and hospital stay, and lower total hospital costs than those who received respiratory treatments before protocol initiation. There was a nonsignificant trend toward lower mortality after protocol initiation. CONCLUSIONS: Our RT-evaluate-and-treat protocol for non-ICU surgery patients was associated with more patients receiving respiratory treatments but decreased ICU and hospital stay and lower total hospital costs. Routine RT-driven assessment of non-ICU patients may reduce pulmonary complications in high-risk patients.

Economic burden of not recognizing panic disorder in the emergency department.

The objective of this cohort study was to examine the diagnostic patterns and resource utilization of patients presenting to the Emergency Department with chest pain of unknown origin who may be experiencing a panic attack. Patients were excluded if they had coronary artery disease. In the 155 patients meeting study criteria, unspecified chest pain (78%) was the most common diagnostic code assigned. Total charges for the index hospitalization were $1,263,391 (median/visit = $7340). During the 1-year follow-up, 41% of patients had at least one repeat hospital visit and generated $1.6 million in charges. Patients on Medicare or Medicaid were more likely to have multiple hospital visits during the follow-up (odds ratio = 11.7). In conclusion, Emergency Department patients admitted with non-cardiac chest pain account for a significant amount of hospital resource use.

Use of a Patient Portal for Engaging Patients with Type 2 Diabetes: Patterns and Prediction.

Background: Patient portals empower patients by providing access to their health information and facilitating communication with care providers. This study aimed to examine the usage patterns of a patient portal offered as part of an electronic health record and to identify predictors of portal use among patients with type 2 diabetes (T2DM). Methods: A 2-year retrospective cohort study was performed using outpatient data from the health care system and its patient portal. Demographic and clinical data from 38,399 T2DM patients were analyzed. Descriptive statistics were used to summarize portal usage patterns. Binary logistic regression was employed to examine predictors and two-way interactions associated with portal use. Results: Almost one-third of patients (n = 12,615; 32.9%, 95% confidence interval: [32.38%-33.32%]) had used the portal for a mean 2.5 ± 1.9 years before the study period. Portal use was higher on weekdays than on weekends (P < 0.001). An increase in portal use was observed in response to e-mail reminders. A nonlinear relationship between age and portal use was observed and depended on several other predictors (P's < 0.05). Patients living in more rural areas with low income were at lower odds to use the portal (P = 0.021), and this finding also applied to nonwhites with low income (P < 0.001). More chronic conditions and a higher initial glycated hemoglobin value were associated with portal use (P = 0.014). Conclusions: The patient portal usage remained relatively stable over the 2-year period. A combination of factors was associated with an individual's patient portal use. Patient engagement in portal use can be facilitated through a proactive approach by health care providers.

Association of Short Sleep Duration and Atrial Fibrillation.

BACKGROUND: Short sleep may be a risk factor for atrial fibrillation. However, previous investigations have been limited by lack of objective sleep measurement and small sample size. We sought to determine the association between objectively measured sleep duration and atrial fibrillation. METHODS: All 31,079 adult patients undergoing diagnostic polysomnography from 1999 to 2015 at multiple sites within a large hospital network were identified from electronic medical records. Prevalent atrial fibrillation was identified by continuous ECG during polysomnography. Incident atrial fibrillation was identified by diagnostic codes and 12-lead ECGs. Logistic regression and Cox proportional hazards modeling were used to examine the association of sleep duration and atrial fibrillation prevalence and incidence, respectively, adjusting for age, sex, BMI, hypertension, coronary artery disease, cerebrovascular disease, peripheral vascular disease, heart failure, and sleep apnea severity. RESULTS: We identified 404 cases of prevalent atrial fibrillation among 30,061 individuals (mean age ± SD, 51.0 ± 14.5 years; 51.6% women) undergoing polysomnography. After adjustment, each 1-h reduction in sleep duration was associated with a 1.17-fold (95% CI, 1.11-1.30) increased risk of prevalent atrial fibrillation. Among 27,589 patients without atrial fibrillation at baseline, we identified 1,820 cases of incident atrial fibrillation over 4.6 years median follow-up. After adjustment, each 1-h reduction in sleep duration was associated with a 1.09-fold (95% CI, 1.05-1.13) increased risk for incident atrial fibrillation. CONCLUSIONS: Short sleep duration is independently associated with prevalent and incident atrial fibrillation. Further research is needed to determine whether interventions to extend sleep can lower atrial fibrillation risk.

Assessing Patterns of Palliative Care Referral and Location of Death in Patients with Idiopathic Pulmonary Fibrosis: A Sixteen-Year Single-Center Retrospective Cohort Study.

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with an unpredictable course and a median survival of three to four years. This timeline challenges providers to approach diagnosis, oxygen therapy, rehabilitation, transplantation, and end-of-life discussions in limited encounters. There is currently no widely accepted guideline for determining when IPF patients should be referred to palliative care (PC). Objective: We sought to describe the patient and clinical factors associated with PC referral, as well as its impact on mortality and location of death. We also aimed to examine temporal trends in PC referral in this population. Materials and Methods: Patient data were retrospectively extracted from the health system repository of our specialty referral center for all new IPF patients evaluated between 2000 and 2016 (n = 828). Exclusion criteria included transplant recipients and patients who did not have IPF. Results: One hundred twelve (13.5%) IPF patients received formal PC referral. Recipients were older at diagnosis (72 years vs. 69 years, p < 0.001), had higher frequency of Charlson Comorbidity Index ≥1 (55% vs. 42%, p = 0.011), resided closer to our institution (16 miles vs. 54 miles, p < 0.001), and had a higher number of total outpatient visits (7 vs. 4, p < 0.001). PC was associated with less in-hospital death (44% vs. 60%, p = 0.006) and more in-home and hospice death (56% vs. 40%, p = 0.006). Conclusions: IPF patients referred to PC were older with more severe comorbidities, resided closer to our specialty referral center, and had more outpatient follow-up. This was associated with more in-home and hospice deaths. The patient-provider relationship and frequency of follow-up visits likely play important roles in the introduction of end-of-life discussions.

Automated data mining of the electronic health record for investigation of healthcare-associated outbreaks.

BACKGROUND: Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak. METHODS: We retrospectively analyzed 9 hospital outbreaks that occurred during 2011-2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time. RESULTS: Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively. CONCLUSIONS: Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.

Patient Portal Use in Diabetes Management: Literature Review.

BACKGROUND: Health information technology tools (eg, patient portals) have the potential to promote engagement, improve patient-provider communication, and enhance clinical outcomes in the management of chronic disorders such as diabetes mellitus (DM). OBJECTIVES: The aim of this study was to report the findings of a literature review of studies reporting patient portal use by individuals with type 1 or type 2 DM. We examined the association of the patient portal use with DM-related outcomes and identified opportunities for further improvement in DM management. METHODS: Electronic literature search was conducted through PubMed and PsycINFO databases. The keywords used were "patient portal*," "web portal," "personal health record," and "diabetes." Inclusion criteria included (1) published in the past 10 years, (2) used English language, (3) restricted to age ≥18 years, and (4) available in full text. RESULTS: This review included 6 randomized controlled trials, 16 observational, 4 qualitative, and 4 mixed-methods studies. The results of these studies revealed that 29% to 46% of patients with DM have registered for a portal account, with 27% to 76% of these patients actually using the portal at least once during the study period. Portal use was associated with the following factors: personal traits (eg, sociodemographics, clinical characteristics, health literacy), technology (eg, functionality, usability), and provider engagement. Inconsistent findings were observed regarding the association of patient portal use with DM-related clinical and psychological outcomes. CONCLUSIONS: Barriers to use of the patient portal were identified among patients and providers. Future investigations into strategies that engage both physicians and patients in use of a patient portal to improve patient outcomes are needed.