A comparison of comorbidities obtained from hospital administrative data and medical charts in older patients with pneumonia

Antiplatelet Agents and Oral Anticoagulant Use in Patients with Atrial Fibrillation and Carotid Artery Disease After First-Time Ischaemic Stroke

INTRODUCTION

People with atrial fibrillation (AF) frequently have competing mechanisms for ischaemic stroke, including extracranial carotid atherosclerosis. The objective of this study was to determine associations between use of oral anticoagulants (OACs) plus antiplatelet agents (APA) after ischaemic stroke and outcomes for patients with AF and carotid artery disease.

PATIENTS AND METHODS

A retrospective cohort study was conducted. Participants receiving OACs with or without APA were propensity score-matched for age, sex, ethnicity, co-morbidities and presence of cardiac and vascular implants and grafts. Outcomes were 1-year mortality, recurrent stroke and major bleeding.

RESULTS

Of 5708 patients, 24.1% (n=1628) received non-vitamin K antagonist OACs (NOACs) with no APA, 26.0% (n=1401) received NOACs plus APA, 20.7% (n=1243) received warfarin without APA and 29.2% (n=1436) received warfarin plus APA. There was no significant difference in risk of recurrent stroke between the groups. Compared to receiving NOACs without APA, receiving warfarin plus APA was associated with a higher risk of mortality (hazard ratio (HR) 1.51 (95% confidence interval (CI) 1.20, 1.89)) and major bleeding (HR 1.66 (95% CI 1.40, 1.96)). Receiving NOACs plus APA was also associated with a higher risk of major bleeding compared to NOACs without APA (HR 1.27 (95% CI 1.07, 1.51), respectively).

CONCLUSIONS

The results suggest for patients with AF and carotid artery disease after ischaemic stroke, receiving NOACs without APA is associated with a lower risk of major bleeding with no negative impact on recurrent stroke or mortality. Evidence from randomised trials is needed to confirm this finding.

Accuracy of heart failure ascertainment using routinely collected healthcare data: a systematic review and meta-analysis

BACKGROUND

Ascertainment of heart failure (HF) hospitalizations in cardiovascular trials is costly and complex, involving processes that could be streamlined by using routinely collected healthcare data (RCD). The utility of coded RCD for HF outcome ascertainment in randomized trials requires assessment. We systematically reviewed studies assessing RCD-based HF outcome ascertainment against "gold standard" (GS) methods to study the feasibility of using such methods in clinical trials.

METHODS

Studies assessing International Classification of Disease (ICD) coded RCD-based HF outcome ascertainment against GS methods and reporting at least one agreement statistic were identified by searching MEDLINE and Embase from inception to May 2021. Data on study characteristics, details of RCD and GS data sources and definitions, and test statistics were reviewed. Summary sensitivities and specificities for studies ascertaining acute and prevalent HF were estimated using a bivariate random effects meta-analysis. Heterogeneity was evaluated using I2 statistics and hierarchical summary receiver operating characteristic (HSROC) curves.

RESULTS

A total of 58 studies of 48,643 GS-adjudicated HF events were included in this review. Strategies used to improve case identification included the use of broader coding definitions, combining multiple data sources, and using machine learning algorithms to search free text data, but these methods were not always successful and at times reduced specificity in individual studies. Meta-analysis of 17 acute HF studies showed that RCD algorithms have high specificity (96.2%, 95% confidence interval [CI] 91.5-98.3), but lacked sensitivity (63.5%, 95% CI 51.3-74.1) with similar results for 21 prevalent HF studies. There was considerable heterogeneity between studies.

CONCLUSIONS

RCD can correctly identify HF outcomes but may miss approximately one-third of events. Methods used to improve case identification should also focus on minimizing false positives.

Outcomes in patients with ischaemic stroke undergoing endovascular thrombectomy: Impact of atrial fibrillation

OBJECTIVES

Endovascular thrombectomy (EVT) is associated with good clinical outcomes in ischaemic stroke, but the risk of intracerebral haemorrhage (ICH) and mortality remains common following ischaemic stroke. The effect of concomitant atrial fibrillation (AF) on clinical outcomes following acute ischaemic stroke in patients receiving EVT remains unclear. The aim is to investigate associations between AF and intracerebral haemorrhage and all-cause mortality at 90 days in patients with ischaemic stroke undergoing EVT.

MATERIALS AND METHODS

A retrospective cohort was conducted using TriNetX, a global health research network. The network was searched for people aged ≥18 years with ischaemic stroke, EVT and AF recorded in electronic medical records between 01/09/2018 and 01/09/2021. These patients were compared to controls with ischaemic stroke, EVT and no AF. Propensity score matching for age, sex, race, comorbidities, National Institutes of Health Stroke Scale (NIHSS) scores, and prior use of anticoagulation was used to balance the cohorts with and without AF.

RESULTS

In total 3,106 patients were identified with history of ischaemic stroke treated by EVT. After propensity-score matching, 832 patients (mean age 68 ± 13; 47% female) with ischaemic stroke, EVT and AF, were compared to 832 patients (mean age 67 ± 12; 47% female) with ischaemic stroke, EVT and no history of AF. In the cohort with AF, 11.5% (n = 96) experienced ICH within 90 days following EVT, compared with 12.3% (n = 103) in patients without AF (Odds Ratio (OR) 0.92, 95% confidence interval (CI) 0.68-1.24; p = 0.59). In the patients with AF, mortality within 90 days following EVT was 18.7% (n = 156), compared with 22.5% in patients without AF (n = 187) (OR 0.79, 95% CI 0.63-1.01; p = 0.06).

CONCLUSION

In patients with ischaemic stroke undergoing EVT, AF was not significantly associated with intracerebral haemorrhage or all-cause mortality at 90-day follow-up.

Verification of administrative data to measure palliative care at terminal hospital stays

BACKGROUND

Administrative data and clinician documentation have not been directly compared for reporting palliative care, despite concerns about under-reporting.

OBJECTIVE

The aim of this study was to verify the use of routinely collected administrative data for reporting in-hospital palliation and to examine factors associated with coded palliative care in hospital administrative data.

METHOD

Hospital administrative data and inpatient palliative care activity documented in medical records were compared for patients dying in hospital between 1 July 2017 and 31 December 2017. Coding of palliative care in administrative data is based on hospital care type coded as "palliative care" and/or assignment of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) palliative care diagnosis code Z51.5. Medical records were searched for specified keywords, which, read in context, indicated a palliative approach to care. The list of keywords (palliative, end of life, comfort care, cease observations, crisis medications, comfort medications, syringe driver, pain or symptom management, no cardiopulmonary resuscitation, advance medical plan/resuscitation plan, deteriorating, agitation, restless and delirium) was developed in consultation with seven local clinicians specialising in palliative care or geriatric medicine.

RESULTS

Of the 576 patients who died in hospital, 246 were coded as having received palliative care, either solely by the ICD-10-AM diagnosis code Z51.5 (42%) or in combination with a "palliative care" care type (58%). Just over one-third of dying patients had a palliative care specialist involved in their hospital care. Involvement of a palliative care specialist and a cancer diagnosis substantially increased the odds of a Z51.5 code (odds ratio = 11 and 4, respectively). The majority of patients with a "syringe driver" or identified as being at the "end of life" were assigned a Z51.5 code (73.5% and 70.5%, respectively), compared to 53.8% and 54.7%, respectively, for "palliative" or "comfort care." For each keyword indicating a palliative approach to care, the Z51.5 code was more likely to be assigned if the patient had specialist palliative care input or if they had cancer.

CONCLUSION

Our results suggest administrative data under-represented in-hospital palliative care, at least partly due to medical record documentation that failed to meet ICD-10-AM coding criteria. Collaboration between clinicians and coders can enhance the quality of records and, consequently, administrative data.

A global multicenter propensity-matched analysis of mortality risk and palliative care referral due to cirrhosis in hospitalized patients with COVID-19

BACKGROUND AND AIM

A few recent studies identified cirrhosis as a risk factor for high mortality in patients with coronavirus disease-19 (COVID-19). Palliative care is less often involved in the management of cirrhosis. We analyzed a global multicenter database to study the risk of mortality and palliative care referrals in patients with COVID-19 and cirrhosis.

METHODS

A federated cloud-based network (TriNetX) data from 50 health-care organizations across the globe were analyzed retrospectively. Patients with COVID-19 aged from 18 years to 90 years were identified between January 20, 2020, and November 16, 2020.

RESULTS

A total of 1969 patients (Group A) with COVID-19 and cirrhosis and 169,257 patients with COVID-19 alone (Group B) were studied. The two groups had a similar occurrence of other comorbid diseases. In a propensity-matched analysis, the mortality rate in Group A (8.9%) was significantly higher than Group B (5.6%), hazard ratio (95% confidence interval) for mortality with cirrhosis was 1.59 (1.26-1.99) (P = 0.01). The occurrence of palliative care referrals in Group A (4.1%) was significantly higher than Group B (2.0%), hazard ratio (95% confidence interval) with cirrhosis was 2.02 (1.39-2.94) (P = 0.01).

CONCLUSION

Mortality rate and palliative care referrals were higher in patients with cirrhosis and COVID-19 compared to those with COVID-19 alone. This increased occurrence of palliative care referrals compared to the general trend in cirrhotic patients probably indicates increased awareness of COVID-19 as a life-threatening condition.

RELEVANCE FOR PATIENTS

Cirrhosis should be identified as a high-risk condition that may require palliative care referral in hospitalized patients with COVID-19. Hospital resource utilization and cost-analysis modeling should anticipate the need for palliative care referrals as a significant outcome in patients with cirrhosis who are hospitalized with COVID-19.

Stroke in Older Adults Living in Care Homes: Results From a National Data Linkage Study in Wales

OBJECTIVES

To determine the proportion of older people moving to care homes with a recent stroke, incidence of stroke after moving to a care home, mortality following stroke, and secondary stroke prevention management in older care home residents.

DESIGN

Retrospective cohort study using population-scale individual-level linked data sources between 2003 and 2018 in the Secure Anonymized Information Linkage (SAIL) Databank.

SETTING AND PARTICIPANTS

People age ≥65 years residing in long-term care homes in Wales.

METHODS

Competing risk models and logistic regression models were used to examine the association between prior stroke, incident stroke, and mortality following stroke.

RESULTS

Of 86,602 individuals, 7.0% (n = 6055) experienced a stroke in the 12 months prior to care home entry. The incidence of stroke within 12 months after entry to a care home was 26.2 per 1000 person-years [95% confidence interval (CI) 25.0, 27.5]. Previous stroke was associated with higher risk of incident stroke after moving to a care home (subdistribution hazard ratio 1.83, 95% CI 1.57, 2.13) and 30-day mortality following stroke (odds ratio 2.18, 95% CI 1.59, 2.98). Severe frailty was not significantly associated with risk of stroke or 30-day mortality following stroke. Secondary stroke prevention included statins (50.5%), antiplatelets (61.2%), anticoagulants (52.4% of those with atrial fibrillation), and antihypertensives (92.1% of those with hypertension).

CONCLUSIONS AND IMPLICATIONS

At the time of care home entry, individuals with history of stroke in the previous 12 months are at a higher risk of incident stroke and mortality following an incident stroke. These individuals are frequently not prescribed medications for secondary stroke prevention. Further evidence is needed to determine the optimal care pathways for older people living in long-term care homes with history of stroke.

Stroke-Heart Syndrome: Incidence and Clinical Outcomes of Cardiac Complications Following Stroke

BACKGROUND

The risk of major adverse cardiovascular events is substantially increased following a stroke. Although exercise-based cardiac rehabilitation has been shown to improve prognosis following cardiac events, it is not part of routine care for people following a stroke. We, therefore, investigated the association between cardiac rehabilitation and major adverse cardiovascular events for people following a stroke. Following a stroke, individuals have an increased risk of new-onset cardiovascular complications. However, the incidence and long-term clinical consequence of newly diagnosed cardiovascular complications following a stroke is unclear. The aim of the present study was to investigate the incidence and long-term clinical outcomes of newly diagnosed cardiovascular complications following incident ischemic stroke.

METHODS

A retrospective cohort study was conducted using anonymized electronic medical records from 53 participating health care organizations. Patients with incident ischemic stroke aged ≥18 years with 5 years of follow-up were included. Patients who were diagnosed with new-onset cardiovascular complications (heart failure, severe ventricular arrhythmia, atrial fibrillation, ischemic heart disease, Takotsubo syndrome) within 4-weeks (exposure) of incident ischemic stroke were 1:1 propensity score-matched (age, sex, ethnicity, comorbidities, cardiovascular care) with ischemic stroke patients who were not diagnosed with a new-onset cardiovascular complication (control). Logistic regression models produced odds ratios (OR) with 95% CIs for 5-year incidence of all-cause mortality, recurrent stroke, hospitalization, and acute myocardial infarction.

RESULTS

Of 365 383 patients with stroke with 5-year follow-up: 11.1% developed acute coronary syndrome; 8.8% atrial fibrillation/flutter; 6.4% heart failure; 1.2% severe ventricular arrythmias; and 0.1% Takotsubo syndrome within 4 weeks of incident ischemic stroke. Following propensity score matching, odds of 5-year all-cause mortality were significantly higher in stroke patients with acute coronary syndrome (odds ratio, 1.49 [95% CI, 1.44-1.54]), atrial fibrillation/flutter (1.45 [1.40-1.50]), heart failure (1.83 [1.76-1.91]), and severe ventricular arrhythmias (2.08 [1.90-2.29]), compared with matched controls. Odds of 5-year rehospitalization and acute myocardial infarction were also significantly higher for patients with stroke diagnosed with new-onset cardiovascular complications. Takotsubo syndrome was associated with significantly higher odds of 5-year composite major adverse cardiovascular events (1.89 [1.29-2.77]). Atrial fibrillation/flutter was the only new-onset cardiac complication associated with significantly higher odds of recurrent ischemic stroke at 5 years (1.10 [1.07-1.14]).

CONCLUSIONS

New-onset cardiovascular complications diagnosed following an ischemic stroke are very common and associate with significantly worse 5-year prognosis in terms of major adverse cardiovascular events. People with stroke and newly diagnosed cardiovascular complications had >50% prevalence of recurrent stroke at 5 years.

Comparative 1-Year Outcomes of Invasive Staphylococcus aureus Infections Among Persons With and Without Drug Use: An Observational Cohort Study

BACKGROUND

Persons who use drugs (PWUD) face substantial risk of Staphylococcus aureus infections. Limited data exist describing clinical and substance use characteristics of PWUD with invasive S. aureus infections or comparing treatment and mortality outcomes in PWUD vs non-PWUD. These are needed to inform optimal care for this marginalized population.

METHODS

We identified adults hospitalized from 2013 to 2018 at 2 medical centers in San Francisco with S. aureus bacteremia or International Classification of Diseases-coded diagnoses of endocarditis, epidural abscess, or vertebral osteomyelitis with compatible culture. In addition to demographic and clinical characteristic comparison, we constructed multivariate Cox proportional hazards models for 1-year infection-related readmission and mortality, adjusted for age, race/ethnicity, housing, comorbidities, and methicillin-resistant S. aureus (MRSA).

RESULTS

Of 963 hospitalizations for S. aureus infections in 946 patients, 372 of 963 (39%) occurred in PWUD. Among PWUD, heroin (198/372 [53%]) and methamphetamine use (185/372 [50%]) were common. Among 214 individuals using opioids, 98 of 214 (46%) did not receive methadone or buprenorphine. PWUD had lower antibiotic completion than non-PWUD (70% vs 87%; P < .001). While drug use was not associated with increased mortality, 1-year readmission for ongoing or recurrent infection was double in PWUD vs non-PWUD (28% vs 14%; adjusted hazard ratio [aHR], 2.0 [95% confidence interval {CI}: 1.3-2.9]). MRSA was independently associated with 1-year readmission for infection (aHR, 1.5 [95% CI: 1.1-2.2]).

CONCLUSIONS

Compared to non-PWUD, PWUD with invasive S. aureus infections had lower rates of antibiotic completion and twice the risk of infection persistence/recurrence at 1 year. Among PWUD, both opioid and stimulant use were common. Models for combined treatment of substance use disorders and infections, particularly MRSA, are needed.

Outcomes of left atrial appendage occlusion vs. non-vitamin K antagonist oral anticoagulants in atrial fibrillation

BACKGROUND

The effects of left atrial appendage (LAA) occlusion compared to non-vitamin K antagonist oral anticoagulant (NOAC) therapy in patients with atrial fibrillation (AF) remain unknown.

AIMS

We aimed to evaluate the outcomes in patients with AF who received LAA occlusion vs. NOAC therapy.

METHODS

We utilised data from TriNetX which is a global federated health research network currently containing data for 88.5 million patients. ICD-10 codes were employed to identify AF patients treated with either LAA occlusion or NOAC between 1st December 2010 and 17th January 2019. Clinical outcomes of interest were analysed up to 2 years.

RESULTS

108,697 patients were included. Patients who underwent LAA occlusion were younger, more likely to be white Caucasian and male, had a greater incidence of comorbidities, and were less likely to be prescribed other cardiovascular medications. Using propensity score matching, the risk of all-cause mortality was significantly lower among patients who received LAA occlusion compared to NOAC therapy [1.51% vs. 5.60%, RR 0.27 (95% CI 0.14-0.54)], but there were no statistical differences in the composite thrombotic or thromboembolic events [8.17% vs. 7.72%, RR 1.06 (95% CI 0.73-1.53)], ischaemic stroke or TIA [4.69% vs. 5.45%, RR 0.86 (95% CI 0.54-1.38)], venous thromboembolism [1.66% vs. 1.51%, RR 1.10 (95% CI 0.47-2.57)] and intracranial haemorrhage [1.51% vs. 1.51%, RR 1.00 (95% CI 0.42-2.39)].

CONCLUSION

Overall, LAA occlusion might be a suitable alternative to NOAC therapy for stroke prevention in patients with AF.

Atrial Fibrillation in Patients With Cardiomyopathy: Prevalence and Clinical Outcomes From Real-World Data

Background

Cardiomyopathy is a common cause of atrial fibrillation (AF) and may also present as a complication of AF. However, there is a scarcity of evidence of clinical outcomes for people with cardiomyopathy and concomittant AF. The aim of the present study was therefore to characterize the prevalence of AF in major subtypes of cardiomyopathy and investigate the impact on important clinical outcomes.

Methods and Results

A retrospective cohort study was conducted using electronic medical records from a global federated health research network, with data primarily from the United States. The TriNetX network was searched on January 17, 2021, including records from 2002 to 2020, which included at least 1 year of follow‐up data. Patients were included based on a diagnosis of hypertrophic, dilated, or restrictive cardiomyopathy and concomitant AF. Patients with cardiomyopathy and AF were propensity‐score matched for age, sex, race, and comorbidities with patients who had a cardiomyopathy only. The outcomes were 1‐year mortality, hospitalization, incident heart failure, and incident stroke. Of 634 885 patients with cardiomyopathy, there were 14 675 (2.3%) patients with hypertrophic, 90 117 (7.0%) with restrictive, and 37 685 (5.9%) with dilated cardiomyopathy with concomitant AF. AF was associated with significantly higher odds of all‐cause mortality (odds ratio [95% CI]) for patients with hypertrophic (1.26 [1.13–1.40]) and dilated (1.36 [1.27–1.46]), but not restrictive (0.98 [0.94–1.02]), cardiomyopathy. Odds of hospitalization, incident heart failure, and incident stroke were significantly higher in all cardiomyopathy subtypes with concomitant AF. Among patients with AF, catheter ablation was associated with significantly lower odds of all‐cause mortality at 12 months across all cardiomyopathy subtypes.

Conclusions

Findings of the present study suggest AF may be highly prevalent in patients with cardiomyopathy and associated with worsened prognosis. Subsequent research is needed to determine the usefulness of screening and multisdisciplinary treatment of AF in this population.

Prevalence and clinical outcomes of myocarditis and pericarditis in 718,365 COVID-19 patients

BACKGROUND

COVID-19 has a wide spectrum of cardiovascular sequelae including myocarditis and pericarditis; however, the prevalence and clinical impact are unclear. We investigated the prevalence of new-onset myocarditis/pericarditis and associated adverse cardiovascular events in patients with COVID-19.

METHODS AND RESULTS

A retrospective cohort study was conducted using electronic medical records from a global federated health research network. Patients were included based on a diagnosis of COVID-19 and new-onset myocarditis or pericarditis. Patients with COVID-19 and myocarditis/pericarditis were 1:1 propensity score matched for age, sex, race and comorbidities to patients with COVID-19 but without myocarditis/pericarditis. The outcomes of interest were 6-month all-cause mortality, hospitalisation, cardiac arrest, incident heart failure, incident atrial fibrillation and acute myocardial infarction, comparing patients with and without myocarditis/pericarditis. Of 718,365 patients with COVID-19, 35,820 (5.0%) developed new-onset myocarditis and 10,706 (1.5%) developed new-onset pericarditis. Six-month all-cause mortality was 3.9% (n = 702) in patients with myocarditis and 2.9% (n = 523) in matched controls (p < .0001), odds ratio 1.36 (95% confidence interval (CI): 1.21-1.53). Six-month all-cause mortality was 15.5% (n = 816) for pericarditis and 6.7% (n = 356) in matched controls (p < .0001), odds ratio 2.55 (95% CI: 2.24-2.91). Receiving critical care was associated with significantly higher odds of mortality for patients with myocarditis and pericarditis. Patients with pericarditis seemed to associate with more new-onset cardiovascular sequelae than those with myocarditis. This finding was consistent when looking at pre-COVID-19 data with pneumonia patients.

CONCLUSIONS

Patients with COVID-19 who present with myocarditis/pericarditis associate with increased odds of major adverse events and new-onset cardiovascular sequelae.

Cardiac rehabilitation and all-cause mortality in patients with heart failure: a retrospective cohort study

AIMS 

Despite the benefits of exercise training in the secondary prevention of cardiovascular disease, there are conflicting findings for the impact of exercise-based cardiac rehabilitation (CR) on mortality for patients with heart failure (HF). The aim of this study was therefore to investigate the association of exercise-based CR with all-cause mortality, hospitalisation, stroke, and atrial fibrillation in patients with heart failure.

METHODS AND RESULTS

A retrospective cohort study was conducted which utilized a global federated health research network, primarily in the USA. Patients with a diagnosis of HF were compared between those with and without an electronic medical record of CR and/or exercise programmes within 6 months of an HF diagnosis. Patients with HF undergoing exercise-based CR were propensity score matched to HF patients without exercise-based CR by age, sex, race, comorbidities, medications, and procedures (controls). We ascertained 2-year incidence of all-cause mortality, hospitalization, stroke, and atrial fibrillation. Following propensity score matching, a total of 40 364 patients with HF were identified. Exercise-based CR was associated with 42% lower odds of all-cause mortality [odds ratio 0.58, 95% confidence interval (CI): 0.54-0.62], 26% lower odds of hospitalization (0.74, 95% CI 0.71-0.77), 37% lower odds of incident stroke (0.63, 95% CI 0.51-0.79), and 53% lower odds of incident atrial fibrillation (0.47, 95% CI 0.4-0.55) compared to controls, after propensity score matching. The beneficial association of CR and exercise on all-cause mortality was consistent across all subgroups, including patients with HFrEF (0.52, 95% CI 0.48-0.56) and HFpEF (0.65, 95% CI 0.60-0.71).

CONCLUSION 

Exercise-based CR was associated with lower odds of all-cause mortality, hospitalizations, incident stroke, and incident atrial fibrillation at 2-year follow-up for patients with HF (including patients with HFrEF and HFpEF).

Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020-March 2021

INTRODUCTION

Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness.

METHODS

We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions.

RESULTS

Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions).

CONCLUSION

Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

Exercise-Based Cardiac Rehabilitation and All-Cause Mortality Among Patients With Atrial Fibrillation

Background

There is limited evidence of long‐term impact of exercise‐based cardiac rehabilitation (CR) on clinical end points for patients with atrial fibrillation (AF). We therefore compared 18‐month all‐cause mortality, hospitalization, stroke, and heart failure in patients with AF and an electronic medical record of exercise‐based CR to matched controls.

Methods and Results

This retrospective cohort study included patient data obtained on February 3, 2021 from a global federated health research network. Patients with AF undergoing exercise‐based CR were propensity‐score matched to patients with AF without exercise‐based CR by age, sex, race, comorbidities, cardiovascular procedures, and cardiovascular medication. We ascertained 18‐month incidence of all‐cause mortality, hospitalization, stroke, and heart failure. Of 1 366 422 patients with AF, 11 947 patients had an electronic medical record of exercise‐based CR within 6‐months of incident AF who were propensity‐score matched with 11 947 patients with AF without CR. Exercise‐based CR was associated with 68% lower odds of all‐cause mortality (odds ratio, 0.32; 95% CI, 0.29–0.35), 44% lower odds of rehospitalization (0.56; 95% CI, 0.53–0.59), and 16% lower odds of incident stroke (0.84; 95% CI, 0.72–0.99) compared with propensity‐score matched controls. No significant associations were shown for incident heart failure (0.93; 95% CI, 0.84–1.04). The beneficial association of exercise‐based CR on all‐cause mortality was independent of sex, older age, comorbidities, and AF subtype.

Conclusions

Exercise‐based CR among patients with incident AF was associated with lower odds of all‐cause mortality, rehospitalization, and incident stroke at 18‐month follow‐up, supporting the provision of exercise‐based CR for patients with AF.

Prevalence of atrial fibrillation and outcomes in older long-term care residents: a systematic review

BACKGROUND

anticoagulation is integral to stroke prevention for atrial fibrillation (AF), but there is evidence of under-treatment in older people in long-term care (LTC).

OBJECTIVE

to synthesise evidence on the prevalence and outcomes (stroke, mortality or bleeding) of AF in LTC and the factors associated with the prescription of anticoagulation.

METHODS

studies were identified from Medline, CINAHL, PsycINFO, Scopus and Web of Science from inception to 31 October 2019. Two reviewers independently applied the selection criteria and assessed the quality of studies using the Newcastle Ottawa Scale.

RESULTS

twenty-nine studies were included. Prevalence of AF was reported in 21 studies, ranging from 7 to 38%. Two studies reported on outcomes based on the prescription of anticoagulation or not; one reported a reduction in the ischaemic stroke event rate associated with anticoagulant (AC) prescription (2.84 per 100 person years, 95% confidence interval [CI]: 1.98-7.25 versus 3.95, 95% CI: 2.85-10.08) and a non-significant increase in intracranial haemorrhage rate (0.71 per 100 person years, 95% CI: 0.29-2.15 versus 0.65, 95% CI: 0.29-1.93). The second study reported a 76% lower chance of ischaemic stroke with AC prescription and a low incidence of bleeding (n = 4 events). Older age, dementia/cognitive impairment and falls/falls risk were independently associated with the non-prescription of anticoagulation. Conversely, previous stroke/transient ischaemic attack and thromboembolism were independently associated with an increased prescription of anticoagulation.

CONCLUSION

estimates of AF prevalence and factors associated with AC prescription varied extensively. Limited data on outcomes prevent the drawing of definitive conclusions. We recommend panel data collection and systems for linkage to create longitudinal cohorts to provide more robust evidence.

Higher Mortality of Ischaemic Stroke Patients Hospitalized with COVID-19 Compared to Historical Controls

INTRODUCTION

Increasing evidence suggests patients with coronavirus disease 2019 (COVID-19) may develop thrombosis and thrombosis-related complications. Some previous evidence has suggested COVID-19-associated strokes are more severe with worse outcomes for patients, but further studies are needed to confirm these findings. The aim of this study was to determine the association between COVID-19 and mortality for patients with ischaemic stroke in a large multicentre study.

METHODS

A retrospective cohort study was conducted using electronic medical records of inpatients from 50 healthcare organizations, predominately from the USA. Patients with ischaemic stroke within 30 days of COVID-19 were identified. COVID-19 was determined from diagnosis codes or a positive test result identified with CO-VID-19-specific laboratory codes between January 20, 2020, and October 1, 2020. Historical controls with ischaemic stroke without COVID-19 were identified in the period January 20, 2019, to October 1, 2019. 1:1 propensity score matching was used to balance the cohorts with and without CO-VID-19 on characteristics including age, sex, race and comorbidities. Kaplan-Meier survival curves for all-cause 60-day mortality by COVID-19 status were produced.

RESULTS

During the study period, there were 954 inpatients with ischaemic stroke and COVID-19. During the same time period in 2019, there were 48,363 inpatients with ischaemic stroke without COVID-19 (historical controls). Compared to patients with ischaemic stroke without COVID-19, patients with ischaemic stroke and COVID-19 had a lower mean age, had a lower prevalence of white patients, a higher prevalence of black or African American patients and a higher prevalence of hypertension, previous cerebrovascular disease, diabetes mellitus, ischaemic heart disease, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease, liver disease, neoplasms, and mental disorders due to known physiological conditions. After propensity score matching, there were 952 cases and 952 historical controls; cases and historical controls were better balanced on all included characteristics (all p > 0.05). After propensity score matching, Kaplan-Meier survival analysis showed the survival probability was significantly lower in ischaemic stroke patients with COVID-19 (78.3% vs. 91.0%, log-rank test p < 0.0001). The odds of 60-day mortality were significantly higher for patients with ischaemic stroke and COVID-19 compared to the propensity score-matched historical controls (odds ratio: 2.51 [95% confidence interval 1.88-3.34]).

DISCUSSION/CONCLUSIONS

Ischaemic stroke patients with COVID-19 had significantly higher 60-day all-cause mortality compared to propensity score-matched historical controls (ischaemic stroke patients without COVID-19).

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.

Atrial fibrillation and the risk of 30-day incident thromboembolic events, and mortality in adults ≥ 50 years with COVID-19

BACKGROUND

There are limited data on the outcomes of adults with coronavirus disease 2019 (COVID-19) and atrial fibrillation (AF). The objectives were to (i) examine associations between AF, 30-day thromboembolic events and mortality in adults with COVID-19 and (ii) examine associations between COVID-19, 30-day thromboembolic events and mortality in adults with AF.

METHODS

A study was conducted using a global federated health research network. Adults aged ≥50 years who presented to 41 participating healthcare organizations between 20 January 2020 and 1 September 2020 with COVID-19 were included.

RESULTS

For the first objective, 6589 adults with COVID-19 and AF were propensity score matched for age, gender, race, and comorbidities to 6589 adults with COVID-19 without AF. The survival probability was significantly lower in adults with COVID-19 and AF compared to matched adults without AF (82.7% compared to 88.3%, Log-Rank test P < .0001; Risk Ratio (95% confidence interval) 1.61 (1.46, 1.78)) and risk of thromboembolic events was higher in patients with AF (9.9% vs 7.0%, Log-Rank test P < .0001; Risk Ratio (95% confidence interval) 1.41 (1.26, 1.59)). For the second objective, 2454 adults with AF and COVID-19 were propensity score matched to 2454 adults with AF without COVID-19. The survival probability was significantly lower for adults with AF and COVID-19 compared to adults with AF without COVID-19, but there was no significant difference in risk of thromboembolic events.

CONCLUSIONS

AF could be an important risk factor for short-term mortality with COVID-19, and COVID-19 may increase risk of short-term mortality amongst adults with AF.

Comorbidities associated with mortality in 31,461 adults with COVID-19 in the United States: A federated electronic medical record analysis

BACKGROUND

At the beginning of June 2020, there were nearly 7 million reported cases of coronavirus disease 2019 (COVID-19) worldwide and over 400,000 deaths in people with COVID-19. The objective of this study was to determine associations between comorbidities listed in the Charlson comorbidity index and mortality among patients in the United States with COVID-19.

METHODS AND FINDINGS

A retrospective cohort study of adults with COVID-19 from 24 healthcare organizations in the US was conducted. The study included adults aged 18-90 years with COVID-19 coded in their electronic medical records between January 20, 2020, and May 26, 2020. Results were also stratified by age groups (<50 years, 50-69 years, or 70-90 years). A total of 31,461 patients were included. Median age was 50 years (interquartile range [IQR], 35-63) and 54.5% (n = 17,155) were female. The most common comorbidities listed in the Charlson comorbidity index were chronic pulmonary disease (17.5%, n = 5,513) and diabetes mellitus (15.0%, n = 4,710). Multivariate logistic regression analyses showed older age (odds ratio [OR] per year 1.06; 95% confidence interval [CI] 1.06-1.07; p < 0.001), male sex (OR 1.75; 95% CI 1.55-1.98; p < 0.001), being black or African American compared to white (OR 1.50; 95% CI 1.31-1.71; p < 0.001), myocardial infarction (OR 1.97; 95% CI 1.64-2.35; p < 0.001), congestive heart failure (OR 1.42; 95% CI 1.21-1.67; p < 0.001), dementia (OR 1.29; 95% CI 1.07-1.56; p = 0.008), chronic pulmonary disease (OR 1.24; 95% CI 1.08-1.43; p = 0.003), mild liver disease (OR 1.26; 95% CI 1.00-1.59; p = 0.046), moderate/severe liver disease (OR 2.62; 95% CI 1.53-4.47; p < 0.001), renal disease (OR 2.13; 95% CI 1.84-2.46; p < 0.001), and metastatic solid tumor (OR 1.70; 95% CI 1.19-2.43; p = 0.004) were associated with higher odds of mortality with COVID-19. Older age, male sex, and being black or African American (compared to being white) remained significantly associated with higher odds of death in age-stratified analyses. There were differences in which comorbidities were significantly associated with mortality between age groups. Limitations include that the data were collected from the healthcare organization electronic medical record databases and some comorbidities may be underreported and ethnicity was unknown for 24% of participants. Deaths during an inpatient or outpatient visit at the participating healthcare organizations were recorded; however, deaths occurring outside of the hospital setting are not well captured.

CONCLUSIONS

Identifying patient characteristics and conditions associated with mortality with COVID-19 is important for hypothesis generating for clinical trials and to develop targeted intervention strategies.

Validation and Comparison of a Modified Elixhauser Index for Predicting In-Hospital Mortality in Italian Internal Medicine Wards

Purpose

Burden of comorbidities appears to be related to clinical outcomes in hospitalized patients. Clinical stratification of admitted patients could be obtained calculating a comorbidity score, which represents the simplest way to identify the severity of patients' clinical conditions and a practical approach to assess prevalent comorbidities. Our aim was to validate a modified Elixhauser score for predicting in-hospital mortality (IHM) in internal medicine admissions and to compare it with a different one derived from clinical data previously used in a similar setting, having a good prognostic accuracy.

Patients and Methods

A single-center retrospective study enrolled all patients admitted to internal medicine department between January and June 2016. A modified Elixhauser score was calculated from chart review and administrative data; moreover, a second prognostic index was calculated from chart review only. Comorbidity scores were compared using c-statistic.

Results

We analyzed 1614 individuals without selecting the reason for admission, 224 (13.9%) died during hospital stay. Deceased subjects were older (83.3±9.1 vs 78.4±13.5 years; p<0.001) and had higher burden of comorbidities. The modified Elixhauser score calculated by administrative data and by chart review and the comparator one was 18.13±9.36 vs 24.43±11.27 vs 7.63±3.3, respectively, and the c-statistic was 0.758 (95% CI 0.727-0.790), 0.811 (95% CI 0.782-0.840) and 0.740 (95% CI 0.709-0.771), respectively.

Conclusion

The new modified Elixhauser score showed a similar performance to a previous clinical prognostic index when it was calculated using administrative data; however, its performance improved if calculation was based on chart review.

Reliability of comorbidity scores derived from administrative data in the tertiary hospital intensive care setting: a cross-sectional study

Background

Hospital reporting systems commonly use administrative data to calculate comorbidity scores in order to provide risk-adjustment to outcome indicators.

Objective

We aimed to elucidate the level of agreement between administrative coding data and medical chart review for extraction of comorbidities included in the Charlson Comorbidity Index (CCI) and Elixhauser Index (EI) for patients admitted to the intensive care unit of a university-affiliated hospital.

Method

We conducted an examination of a random cross-section of 100 patient episodes over 12 months (July 2012 to June 2013) for the 19 CCI and 30 EI comorbidities reported in administrative data and the manual medical record system. CCI and EI comorbidities were collected in order to ascertain the difference in mean indices, detect any systematic bias, and ascertain inter-rater agreement.

Results

We found reasonable inter-rater agreement (kappa (κ) coefficient ≥0.4) for cardiorespiratory and oncological comorbidities, but little agreement (κ<0.4) for other comorbidities. Comorbidity indices derived from administrative data were significantly lower than from chart review: −0.81 (95% CI − 1.29 to − 0.33; p=0.001) for CCI, and −2.57 (95% CI −4.46 to −0.68; p=0.008) for EI.

Conclusion

While cardiorespiratory and oncological comorbidities were reliably coded in administrative data, most other comorbidities were under-reported and an unreliable source for estimation of CCI or EI in intensive care patients. Further examination of a large multicentre population is required to confirm our findings.

The Relative Ability of Comorbidity Ascertainment Methodologies to Predict In-Hospital Mortality Among Hospitalized Community-acquired Pneumonia Patients

BACKGROUND

Despite widespread use of comorbidities for population health descriptions and risk adjustment, the ideal method for ascertaining comorbidities is not known. We sought to compare the relative value of several methodologies by which comorbidities may be ascertained.

METHODS

This is an observational study of 1596 patients admitted to the University of Chicago for community-acquired pneumonia from 1998 to 2012. We collected data via chart abstraction, administrative data, and patient report, then performed logistic regression analyses, specifying comorbidities as independent variables and in-hospital mortality as the dependent variable. Finally, we compared area under the curve (AUC) statistics to determine the relative ability of each method of comorbidity ascertainment to predict in-hospital mortality.

RESULTS

Chart review (AUC, 0.72) and administrative data (Charlson AUC, 0.83; Elixhauser AUC, 0.84) predicted in-hospital mortality with greater fidelity than patient report (AUC, 0.61). However, multivariate logistic regression analyses demonstrated that individual comorbidity derivation via chart review had the strongest relationship with in-hospital mortality. This is consistent with prior literature suggesting that administrative data have inherent, paradoxical biases with important implications for risk adjustment based solely on administrative data.

CONCLUSIONS

Although comorbidities derived through administrative data did produce an AUC greater than chart review, our analyses suggest a coding bias in several comorbidities with a paradoxically protective effect. Therefore, chart review, while labor and resource intensive, may be the ideal method for ascertainment of clinically relevant comorbidities.

Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases

BACKGROUND

The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basic DRG structure by incorporating four severity of illness (SOI) levels, which are used for determining hospital payment. A comprehensive report of all relevant diagnoses, namely the patient's underlying co-morbidities, is a key factor for ensuring that SOI determination will be adequate.

OBJECTIVE

In this study, we aimed to characterise the individual impact of co-morbidities on APR-DRG classification and hospital funding in the context of respiratory and cardiovascular diseases.

METHODS

Using 6 years of coded clinical data from a nationwide Portuguese inpatient database and support vector machine (SVM) models, we simulated and explored the APR-DRG classification to understand its response to individual removal of Charlson and Elixhauser co-morbidities. We also estimated the amount of hospital payments that could have been lost when co-morbidities are under-reported.

RESULTS

In our scenario, most Charlson and Elixhauser co-morbidities did considerably influence SOI determination but had little impact on base APR-DRG assignment. The degree of influence of each co-morbidity on SOI was, however, quite specific to the base APR-DRG. Under-coding of all studied co-morbidities led to losses in hospital payments. Furthermore, our results based on the SVM models were consistent with overall APR-DRG grouping logics.

CONCLUSION AND IMPLICATIONS

Comprehensive reporting of pre-existing or newly acquired co-morbidities should be encouraged in hospitals as they have an important influence on SOI assignment and thus on hospital funding. Furthermore, we recommend that future guidelines to be used by medical coders should include specific rules concerning coding of co-morbidities.

Predicting need for advanced illness or palliative care in a primary care population using electronic health record data

Timely outreach to individuals in an advanced stage of illness offers opportunities to exercise decision control over health care. Predictive models built using Electronic health record (EHR) data are being explored as a way to anticipate such need with enough lead time for patient engagement. Prior studies have focused on hospitalized patients, who typically have more data available for predicting care needs. It is unclear if prediction driven outreach is feasible in the primary care setting. In this study, we apply predictive modeling to the primary care population of a large, regional health system and systematically examine the impact of technical choices, such as requiring a minimum number of health care encounters (data density requirements) and aggregating diagnosis codes using Clinical Classifications Software (CCS) groupings to reduce dimensionality, on model performance in terms of discrimination and positive predictive value. We assembled a cohort of 349,667 primary care patients between 65 and 90 years of age who sought care from Sutter Health between July 1, 2011 and June 30, 2014, of whom 2.1% died during the study period. EHR data comprising demographics, encounters, orders, and diagnoses for each patient from a 12 month observation window prior to the point when a prediction is made were extracted. L1 regularized logistic regression and gradient boosted tree models were fit to training data and tuned by cross validation. Model performance in predicting one year mortality was assessed using held-out test patients. Our experiments systematically varied three factors: model type, diagnosis coding, and data density requirements. We found substantial, consistent benefit from using gradient boosting vs logistic regression (mean AUROC over all other technical choices of 84.8% vs 80.7% respectively). There was no benefit from aggregation of ICD codes into CCS code groups (mean AUROC over all other technical choices of 82.9% vs 82.6% respectively). Likewise increasing data density requirements did not affect discrimination (mean AUROC over other technical choices ranged from 82.5% to 83%). We also examine model performance as a function of lead time, which is the interval between death and when a prediction was made. In subgroup analysis by lead time, mean AUROC over all other choices ranged from 87.9% for patients who died within 0 to 3 months to 83.6% for those who died 9 to 12 months after prediction time.

Multimorbidity in Australia: Comparing estimates derived using administrative data sources and survey data

Background

Estimating multimorbidity (presence of two or more chronic conditions) using administrative data is becoming increasingly common. We investigated (1) the concordance of identification of chronic conditions and multimorbidity using self-report survey and administrative datasets; (2) characteristics of people with multimorbidity ascertained using different data sources; and (3) whether the same individuals are classified as multimorbid using different data sources.

Methods

Baseline survey data for 90,352 participants of the 45 and Up Study—a cohort study of residents of New South Wales, Australia, aged 45 years and over—were linked to prior two-year pharmaceutical claims and hospital admission records. Concordance of eight self-report chronic conditions (reference) with claims and hospital data were examined using sensitivity (Sn), positive predictive value (PPV), and kappa (κ).The characteristics of people classified as multimorbid were compared using logistic regression modelling.

Results

Agreement was found to be highest for diabetes in both hospital and claims data (κ = 0.79, 0.78; Sn = 79%, 72%; PPV = 86%, 90%). The prevalence of multimorbidity was highest using self-report data (37.4%), followed by claims data (36.1%) and hospital data (19.3%). Combining all three datasets identified a total of 46 683 (52%) people with multimorbidity, with half of these identified using a single dataset only, and up to 20% identified on all three datasets. Characteristics of persons with and without multimorbidity were generally similar. However, the age gradient was more pronounced and people speaking a language other than English at home were more likely to be identified as multimorbid by administrative data.

Conclusions

Different individuals, with different combinations of conditions, are identified as multimorbid when different data sources are used. As such, caution should be applied when ascertaining morbidity from a single data source as the agreement between self-report and administrative data is generally poor. Future multimorbidity research exploring specific disease combinations and clusters of diseases that commonly co-occur, rather than a simple disease count, is likely to provide more useful insights into the complex care needs of individuals with multiple chronic conditions.

Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients

PURPOSE

This study compared the Charlson comorbidity index (CCI) information derived from chart review and administrative systems to assess the completeness and agreement between scores, evaluate the capacity to predict 30-day and 1-year mortality in intensive care unit (ICU) patients, and compare the predictive capacity with that of the Simplified Acute Physiology Score (SAPS) II model.

PATIENTS AND METHODS

Using data from 959 patients admitted to a general ICU in a Norwegian university hospital from 2007 to 2009, we compared the CCI score derived from chart review and administrative systems. Agreement was assessed using % agreement, kappa, and weighted kappa. The capacity to predict 30-day and 1-year mortality was assessed using logistic regression, model discrimination with the c-statistic, and calibration with a goodness-of-fit statistic.

RESULTS

The CCI was complete (n=959) when calculated from chart review, but less complete from administrative data (n=839). Agreement was good, with a weighted kappa of 0.667 (95% confidence interval: 0.596-0.714). The c-statistics for categorized CCI scores from charts and administrative data were similar in the model that included age, sex, and type of admission: 0.755 and 0.743 for 30-day mortality, respectively, and 0.783 and 0.775, respectively, for 1-year mortality. Goodness-of-fit statistics supported the model fit.

CONCLUSION

The CCI scores from chart review and administrative data showed good agreement and predicted 30-day and 1-year mortality in ICU patients. CCI combined with age, sex, and type of admission predicted mortality almost as well as the physiology-based SAPS II.

Thirty-Day Hospital Revisit Rates and Factors Associated With Revisits in Patients Undergoing Septorhinoplasty

Importance

Estimates of the 30-day hospital revisit rate following septorhinoplasty and the risk factors associated with revisits are unknown in the current literature. Surgical 30-day readmission rates are important to establish, as they are increasingly used as a quality care metric and can incur future financial penalties from third-party payers and government agencies.

Objective

To determine the rate of 30-day hospital revisits following septorhinoplasty and the risk factors associated with revisits.

Design, Setting, and Participants

A retrospective cohort analysis was conducted of 175 842 patients undergoing septorhinoplasty between January 1, 2005, and December 31, 2009, using data from the Healthcare Cost and Utilization Project state inpatient database, state ambulatory surgery database, and state emergency department database from California, Florida, and New York. Information on revisits for these patients was collected from the 3 databases between January 1, 2005, and December 31, 2012. Data analysis was conducted from September 1, 2014, to May 1, 2015.

Main Outcomes and Measures

Hospital revisits within 30 days after an index septorhinoplasty and the primary diagnosis at the time of the revisit were the main outcome measures. The revisit rate was calculated within subgroups of patients based on different demographic and clinical characteristics. A multivariable model was then used to determine independent risk factors for the occurrence of a hospital revisit within 30 days of the septorhinoplasty procedure.

Results

In total, 11 456 of 175 842 patients (6.5%) who underwent septorhinoplasty procedures revisited the hospital within 30 days of the procedure. Most of these revisits (6353 [55.5%]) were to the emergency department. The most common primary diagnosis was bleeding or epistaxis, occurring in 2150 patients (1.2%). Multivariable logistic regression showed that patients aged 41 to 65 years (adjusted odds ratio [aOR], 1.09; 99% CI, 1.02-1.16) or older than 65 years (aOR, 1.23; 99% CI, 1.06-1.43) had an increased revisit rate, as did black patients (aOR, 1.39; 99% CI, 1.16-1.66); those with Medicare (aOR, 1.55; 99% CI, 1.32-1.81) and Medicaid (aOR, 1.63; 99% CI, 1.33-2.01); those with diagnoses of autoimmune disorders or immunodeficiency (aOR, 2.69; 99% CI, 1.20-6.03), coagulopathy (aOR, 2.06; 99% CI, 1.33-3.20), anxiety (aOR, 1.79; 99% CI, 1.55-2.07), and alcohol use (aOR, 1.70; 99% CI, 1.35-2.14); and those who had a conchal cartilage graft (aOR, 2.01; 99% CI, 1.29-3.14).

Conclusions and Relevance

The study results suggest that patients with more medical comorbidities and lower socioeconomic status most commonly returned to the emergency department for surgical complications, such as bleeding or epistaxis, in the 30-day period after the procedure. These data provide valuable preoperative counseling information for patients and physicians. In addition, this study provides data to third-party payers or government agencies in which postprocedure readmissions in the 30-day period are used as a quality care metric affecting reimbursements and financial penalties.

Level of Evidence

3.

Administrative data is as good as medical chart review for comorbidity ascertainment in patients with infections in Singapore

The Charlson comorbidity index (CCI) is widely used for control of confounding from comorbidities in epidemiological studies. International Classification of Diseases (ICD)-coded diagnoses from administrative hospital databases is potentially an efficient way of deriving CCI. However, no studies have evaluated its validity in infectious disease research. We aim to compare CCI derived from administrative data and medical record review in predicting mortality in patients with infections. We conducted a cross-sectional study on 199 inpatients. Correlation analyses were used to compare comorbidity scores from ICD-coded administrative databases and medical record review. Multivariable regression models were constructed and compared for discriminatory power for 30-day in-hospital mortality. Overall agreement was fair [weighted kappa 0·33, 95% confidence interval (CI) 0·23-0·43]. Kappa coefficient ranged from 0·17 (95% CI 0·01-0·36) for myocardial infarction to 0·85 (95% CI 0·59-1·00) for connective tissue disease. Administrative data-derived CCI was predictive of CCI ⩾5 from medical record review, controlling for age, gender, resident status, ward class, clinical speciality, illness severity, and infection source (C = 0·773). Using the multivariable model comprising age, gender, resident status, ward class, clinical speciality, illness severity, and infection source to predict 30-day in-hospital mortality, administrative data-derived CCI (C = 0·729) provided a similar C statistic as medical record review (C = 0·717, P = 0·8548). In conclusion, administrative data-derived CCI can be used for assessing comorbidities and confounding control in infectious disease research.

Accuracy of clinician-clinical coder information handover following acute medical admissions: implication for using administrative datasets in clinical outcomes management

BACKGROUND

We evaluated the accuracy, limitations and potential sources of improvement in the clinical utility of the administrative dataset for acute medicine admissions.

METHODS

Accuracy of clinical coding in 8888 patient discharges following an emergency medical hospital admission to a teaching hospital and a district hospital over 3 years was ascertained by a coding accuracy audit team in respect of the primary and secondary diagnoses, morbidities and financial variance.

RESULTS

There was at least one change to the original coding in 4889 admissions (55%) and to the primary diagnosis of at least one finished consultant episodes of 1496 spells (16.8%). There were significant changes in the number of secondary diagnoses and the Charlson morbidity index following the audit. Charlson score increased in 8.2% and decreased in 2.3% of patients. An income variance of £816 977 (+5.0%) or £91.92 per patient was observed.

CONCLUSIONS

The importance and applications of coded healthcare big data within the NHS is increasing. The accuracy of coding is dependent on high-fidelity information transfer between clinicians and coders, which is prone to subjectivity, variability and error. We recommend greater involvement of clinicians as part of multidisciplinary teams to improve data accuracy, and urgent action to improve abstraction and clarity of assignment of strategic diagnoses like pneumonia and renal failure.

Which information source is best? Concordance between patient report, clinician report and medical records of patient co-morbidity and adjuvant therapy health information

RATIONALE, AIM AND OBJECTIVES

Previous studies investigating agreement between data sources for co-morbidity and adjuvant therapy information have suggested agreement varies depending on how the information is collected. The aim of this study was to compare agreement among three data sources: patient report, clinician report and medical record.

METHOD

Data were collected as part of a nurse-delivered telephone intervention (the CONNECT programme). Patient report was collected using a self-administered questionnaire. Clinician report was collected from the patient's treating surgeon. Medical record information was extracted by a member of the research team. The proportion of specific agreement [positive (PA) and negative agreement (NA)] and Kappa statistics were calculated.

RESULTS

The study sample comprised 756 surgical patients with colorectal cancer. For the majority of co-morbidities the lowest level of agreement was found between the patient and clinician (PA 0.29-0.64, Kappa values ranged from 0.22 to 0.58). The highest agreement and Kappa values for co-morbidities were generally found between the patient report and medical record (PA 0.36-0.80 and NA 0.92-0.99; Kappa 0.34-0.77). There was good agreement between patient and clinician reports for receipt adjuvant therapy {Kappa 0.78 [confidence interval (CI) 0.72-0.84] and 0.84 [CI 0.80-0.88], respectively; PA 0.87 and 0.92, respectively}. No consistent pattern in the predictors of non-agreement was found.

CONCLUSION

Given there was higher agreement between patient report and medical record review, the use of patient self-report questionnaires to ascertain co-morbid conditions remains a valid method for health services research.

Variation in the recording of common health conditions in routine hospital data: study using linked survey and administrative data in New South Wales, Australia

OBJECTIVES

To investigate the nature and potential implications of under-reporting of morbidity information in administrative hospital data.

SETTING AND PARTICIPANTS

Retrospective analysis of linked self-report and administrative hospital data for 32,832 participants in the large-scale cohort study (45 and Up Study), who joined the study from 2006 to 2009 and who were admitted to 313 hospitals in New South Wales, Australia, for at least an overnight stay, up to a year prior to study entry.

OUTCOME MEASURES

Agreement between self-report and recording of six morbidities in administrative hospital data, and between-hospital variation and predictors of positive agreement between the two data sources.

RESULTS

Agreement between data sources was good for diabetes (κ=0.79); moderate for smoking (κ=0.59); fair for heart disease, stroke and hypertension (κ=0.40, κ=0.30 and κ =0.24, respectively); and poor for obesity (κ=0.09), indicating that a large number of individuals with self-reported morbidities did not have a corresponding diagnosis coded in their hospital records. Significant between-hospital variation was found (ranging from 8% of unexplained variation for diabetes to 22% for heart disease), with higher agreement in public and large hospitals, and hospitals with greater depth of coding.

CONCLUSIONS

The recording of six common health conditions in administrative hospital data is highly variable, and for some conditions, very poor. To support more valid performance comparisons, it is important to stratify or control for factors that predict the completeness of recording, including hospital depth of coding and hospital type (public/private), and to increase efforts to standardise recording across hospitals. Studies using these conditions for risk adjustment should also be cautious of their use in smaller hospitals.

Assessing surgical site infection risk factors using electronic medical records and text mining

Text mining techniques to detect surgical site infections (SSI) in unstructured clinical notes were used to improve SSI detection. In conjuction with data from an integrated electronic medical record, all of the 22 SSIs detected by traditional hospital-based surveillance were found using text mining, along with an additional 37 SSIs not detected by traditional surveillance.

Concordance between administrative health data and medical records for diabetes status in coronary heart disease patients: a retrospective linked data study

BACKGROUND

Administrative data are a valuable source of estimates of diabetes prevalence for groups such as coronary heart disease (CHD) patients. The primary aim of this study was to measure concordance between medical records and linked administrative health data for recording diabetes in CHD patients, and to assess temporal differences in concordance. Secondary aims were to determine the optimal lookback period for identifying diabetes in this patient group, whether concordance differed for Indigenous people, and to identify predictors of false positives and negatives in administrative data.

METHODS

A population representative sample of 3943 CHD patients hospitalized in Western Australia in 1998 and 2002-04 were selected, and designated according to the International Classification of Diseases (ICD) version in use at the time (ICD-9 and ICD-10 respectively). Crude prevalence and concordance were compared for the two samples. Concordance measures were estimated from administrative data comparing diabetes status recorded on the selected CHD admission ('index admission') and on any hospitalization in the previous 1, 2, 5, 10 or 15 years, against hospital medical records. Potential modifiers of agreement were determined using chi-square tests and multivariable logistic regression models.

RESULTS

Identification of diabetes on the index CHD admission was underestimated more in the ICD-10 than ICD-9 sample (sensitivity 81.5% versus 91.1%, underestimation 15.1% versus 4.4% respectively). Sensitivity increased to 89.6% in the ICD-10 period using at least 10 years of hospitalization history. Sensitivity was higher and specificity lower in Indigenous patients, and followed a similar pattern of improving concordance with increasing lookback period. Characteristics associated with false negatives for diabetes on the index CHD hospital admission were elective admission, in-hospital death, principal diagnosis, and in the ICD-10 period only, fewer recorded comorbidities.

CONCLUSIONS

The accuracy of identifying diabetes status in CHD patients is improved in linked administrative health data by using at least 10 years of hospitalization history. Use of this method would reduce bias when measuring temporal trends in diabetes prevalence in this patient group. Concordance measures are as reliable in Indigenous as non-Indigenous patients.

Accuracy of the Charlson index comorbidities derived from a hospital electronic database in a teaching hospital in Saudi Arabia

Hospital management and researchers are increasingly using electronic databases to study utilization, effectiveness, and outcomes of healthcare provision. Although several studies have examined the accuracy of electronic databases developed for general administrative purposes, few studies have examined electronic databases created to document the care provided by individual hospitals. In this study, we assessed the accuracy of an electronic database in a major teaching hospital in Eastern Province, Saudi Arabia, in documenting the 17 comorbidities constituting the Charlson index as recorded in paper charts by care providers. Using the hospital electronic database, the researchers randomly selected the data for 1,019 patients admitted to the hospital and compared the data for accuracy with the corresponding paper charts. Compared with the paper charts, the hospital electronic database did not differ significantly in prevalence for 9 conditions but differed from the paper charts for 8 conditions. The kappa (K) values of agreement ranged from a high of 0.91 to a low of 0.09. Of the 17 comorbidities, the electronic database had substantial or excellent agreement for 10 comorbidities relative to paper chart data, and only one showed poor agreement. Sensitivity ranged from a high of 100.0 percent to a low of 6.0 percent. Specificity for all comorbidities was greater than 93 percent. The results suggest that the hospital electronic database reasonably agrees with patient chart data and can have a role in healthcare planning and research. The analysis conducted in this study could be performed in individual institutions to assess the accuracy of an electronic database before deciding on its utility in planning or research.

Risk factors for readmission of orthopaedic surgical patients

BACKGROUND

Reducing hospital readmissions has become a priority in the development of policies aimed at patient safety and cost reduction. Evaluating the incidence of rehospitalization of orthopaedic surgical patients could help to identify targets for more efficient perioperative care. We addressed two questions: What is the incidence of thirty-day readmission for orthopaedic patients at an academic hospital? Can any risk factors for readmission be identified among rehospitalized patients?

METHODS

This is a retrospective cohort study examining 3264 orthopaedic surgical admissions during two fiscal years from the hospital's quality-improvement database. Cases of patients with unplanned readmission within thirty days were subjected to univariate and multivariate analysis to determine the odds ratio (OR) for readmission. Further descriptive analysis was performed with use of electronic medical record data from the cohort of readmitted patients.

RESULTS

The estimated cumulative incidence of unplanned thirty-day readmissions was 4.2% (i.e., 138 of the 3261 patients who were eligible for the study). Multivariate analysis indicated that marital status of "widowed" significantly increased the risk of readmission (OR, 1.846; 95% confidence interval [CI], 1.070 to 3.184; p = 0.03). Race significantly increased the odds of readmission in patients identified as African-American (OR, 2.178; 95% CI, 1.077 to 4.408; p = 0.03), or American Indian or Alaskan Native race (OR, 3.550; 95% CI, 1.429 to 8.815; p = 0.006). The risk of readmission was significant at p &lt; 0.10 (OR 1.547; 95% CI, 0.941 to 2.545; p = 0.09) for patients with Medicaid insurance. Any intensive care unit stay gave the highest OR of readmission (OR, 2.356; 95% CI, 1.361 to 4.079; p = 0.002) for all demographic groups. Mean length of hospital stay was significantly longer, 5.9 days in the unplanned readmission group compared with 3.6 days for non-readmitted patients (OR, 1.038; 95% CI, 1.014 to 1.062; p = 0.002). Chart review of readmitted patients showed that 102 readmissions (73.9%) were classified as surgical; of these, thirty-five readmission events (34.3%) were for infection at the surgical site.

CONCLUSIONS

Longer length of hospital stay or admission to the intensive care unit significantly increased the likelihood of thirty-day readmission, regardless of demographics or discharge disposition. Marital status, Medicaid insurance status, and race may indicate how a patient's social and economic resources can impact his or her risk of being readmitted to the hospital.

LEVEL OF EVIDENCE

Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Comparison of measures of comorbidity for predicting disability 12-months post-injury

BACKGROUND

Understanding the factors that impact on disability is necessary to inform trauma care and enable adequate risk adjustment for benchmarking and monitoring. A key consideration is how to adjust for pre-existing conditions when assessing injury outcomes, and whether the inclusion of comorbidity is needed in addition to adjustment for age. This study compared different approaches to modelling the impact of comorbidity, collected as part of the routine hospital episode data, on disability outcomes following orthopaedic injury.

METHODS

12-month Glasgow Outcome Scale - Extended (GOS-E) outcomes for 13,519 survivors to discharge were drawn from the Victorian Orthopaedic Trauma Outcomes Registry, a prospective cohort study of admitted orthopaedic injury patients. ICD-10-AM comorbidity codes were mapped to four comorbidity indices. Cases with a GOS-E score of 7-8 were considered "recovered". A split dataset approach was used with cases randomly assigned to development or test datasets. Logistic regression models were fitted with "recovery" as the outcome and the performance of the models based on each comorbidity index (adjusted for injury and age) measured using calibration (Hosmer-Lemshow (H-L) statistics and calibration curves) and discrimination (Area under the Receiver Operating Characteristic (AUC)) statistics.

RESULTS

All comorbidity indices improved model fit over models with age and injuries sustained alone. None of the models demonstrated acceptable model calibration (H-L statistic p < 0.05 for all models). There was little difference between the discrimination of the indices for predicting recovery: Charlson Comorbidity Index (AUC 0.70, 95% CI: 0.68, 0.71); number of ICD-10 chapters represented (AUC 0.70, 95% CI: 0.69, 0.72); number of six frequent chronic conditions represented (AUC 0.70, 95% CI: 0.69, 0.71); and the Functional Comorbidity Index (AUC 0.69, 95% CI: 0.68, 0.71).

CONCLUSIONS

The presence of ICD-10 recorded comorbid conditions is an important predictor of long term functional outcome following orthopaedic injury and adjustment for comorbidity is indicated when assessing risk-adjusted functional outcomes over time or across jurisdictions.