Dataset Information

Modelling Estimates of Norovirus Disease in Patients with Chronic Medical Conditions.

ABSTRACT:

Background

The burden of disease due to norovirus infection has been well described in the general United States population, but studies of norovirus occurrence among persons with chronic medical conditions have been limited mostly to the immunocompromised. We assessed the impact of norovirus gastroenteritis on health care utilization in US subjects with a range of chronic medical conditions.

Methods

We performed a retrospective cohort study using MarketScan data from July 2002 to December 2013, comparing the rates of emergency department visits, outpatient visits and hospitalizations among patients with chronic conditions (renal, cardiovascular, respiratory, immunocompromising, gastrointestinal, hepatic/pancreatic and neurological conditions and diabetes) with those in a healthy population. We estimated the rates of these outcomes due to norovirus gastroenteritis using an indirect modelling approach whereby cases of gastroenteritis of unknown cause and not attributed to a range of other causes were assumed to be due to norovirus.

Results

Hospitalization rates for norovirus gastroenteritis were higher in all of the risk groups analyzed compared with data in otherwise healthy subjects, ranging from 3.2 per 10,000 person-years in persons with chronic respiratory conditions, to 23.1 per 10,000 person-years in persons with chronic renal conditions, compared to 2.1 per 10,000 among persons without chronic conditions. Over 51% of all norovirus hospitalizations occurred in the 37% of the population with some form of chronic medical condition. Outpatient visits for norovirus gastroenteritis were also increased in persons with chronic gastrointestinal or immunocompromising conditions.

Conclusion

Norovirus gastroenteritis leads to significantly higher rates of healthcare utilization in patients with a chronic medical condition compared to patients without any such condition.

SUBMITTER: Verstraeten T

PROVIDER: S-EPMC4954678 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Modelling Estimates of Norovirus Disease in Patients with Chronic Medical Conditions.

Verstraeten Thomas T Jiang Baoguo B Weil John G JG Lin Jennifer H JH

PloS one 20160720 7

<h4>Background</h4>The burden of disease due to norovirus infection has been well described in the general United States population, but studies of norovirus occurrence among persons with chronic medical conditions have been limited mostly to the immunocompromised. We assessed the impact of norovirus gastroenteritis on health care utilization in US subjects with a range of chronic medical conditions.<h4>Methods</h4>We performed a retrospective cohort study using MarketScan data from July 2002 to ...[more]

PMID: 27438335

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Project description:BACKGROUND: Although it is widely accepted that adults with immunocompromising conditions are at greatly increased risk of pneumococcal infection, the extent of risk among immunocompetent adults with chronic medical conditions is less certain, particularly in the current era of universal vaccination of children with pneumococcal conjugate vaccines. METHODS: We conducted a retrospective cohort study using data from 3 healthcare claims repositories (2006-2010) to compare rates of pneumococcal disease in immunocompetent adults with chronic medical conditions ("at-risk") and immunocompromised adults ("high-risk"), with rates in adults without these conditions ("healthy"). Risk profiles and episodes of pneumococcal disease-all-cause pneumonia, pneumococcal pneumonia, and invasive pneumococcal disease (IPD)-were ascertained from diagnosis, procedure, and drug codes. RESULTS: Rates of all-cause pneumonia among at-risk persons aged 18-49 years, 50-64 years, and ?65 years were 3.2 (95% confidence interval [CI], 3.1-3.2), 3.1 (95% CI, 3.1-3.1), and 3.0 (95% CI, 3.0-3.0) times the rates in age-matched healthy counterparts, respectively. We identified rheumatoid arthritis, systemic lupus erythematosus, Crohn's disease, and neuromuscular or seizure disorders as additional at-risk conditions for pneumococcal disease. Among persons with at-risk conditions, the rate of all-cause pneumonia substantially increased with the accumulation of concurrent at-risk conditions (risk stacking): among persons 18-49 years, rate ratios increased from 2.5 (95% CI, 2.5-2.5) in those with 1 at-risk condition to 6.2 (95% CI, 6.1-6.3) in those with 2 conditions, and to 15.6 (95% CI, 15.3-16.0) in those with ?3 conditions. Findings for pneumococcal pneumonia and IPD were similar. CONCLUSIONS: Despite widespread use of pneumococcal conjugate vaccines, rates of pneumonia and IPD remain disproportionately high in adults with at-risk conditions, including those with conditions not currently included in the Advisory Committee on Immunization Practices' guidelines for prevention and those with multiple at-risk conditions.

Project description:ObjectivesEvolution of multiple chronic conditions (MCC) follows a complex stochastic process, influenced by several factors including the inter-relationship of existing conditions, and patient-level risk factors. Nearly 20% of citizens aged 18 years and older are burdened with two or more (multiple) chronic conditions (MCC). Treatment for people living with MCC currently accounts for an estimated 66% of the Nation's healthcare costs. However, it is still not known precisely how MCC emerge and accumulate among individuals or in the general population. This study investigates major patterns of MCC transitions in a diverse population of patients and identifies the risk factors affecting the transition process.MethodsA Latent regression Markov clustering (LRMCL) algorithm is proposed to identify major transitions of four MCC that include hypertension (HTN), depression, Post- Traumatic Stress Disorder (PTSD), and back pain. A cohort of 601,805 individuals randomly selected from the population of Iraq and Afghanistan war Veterans (IAVs) who received VA care during three or more years between 2002-2015, is used for training the proposed LRMCL algorithm.ResultsTwo major clusters of MCC transition patterns with 78% and 22% probability of membership respectively were identified. The primary cluster demonstrated the possibility of improvement when the number of MCC is small and an increase in probability of MCC accumulation as the number of co- morbidities increased. The second cluster showed stability (no change) of MCC overtime as the major pattern. Age was the most significant risk factor associated with the most probable cluster for each IAV.ConclusionsThese findings suggest that our proposed LRMCL algorithm can be used to describe and understand MCC transitions, which may ultimately allow healthcare systems to support optimal clinical decision- making. This method will be used to describe a broader range of MCC transitions in this and non-VA populations, and will add treatment information to see if models including treatments and MCC emergence can be used to support clinical decision-making in patient care.

Dataset Information

Modelling Estimates of Norovirus Disease in Patients with Chronic Medical Conditions.

Background

Methods

Results

Conclusion

Publications

Modelling Estimates of Norovirus Disease in Patients with Chronic Medical Conditions.

Similar Datasets

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