Aronsky D, Haug PJ, Lagor C, Dean NC. Accuracy of administrative data for identifying patients with pneumonia
Department of Biomedical Informatics & Emergency Medicine, Vanderbilt University, 2209 Garland Avenue, Nashville, TN 37232, USA. American Journal of Medical Quality
(Impact Factor: 1.25).
11/2005; 20(6):319-28. DOI: 10.1177/1062860605280358
The goal of this study was to determine the accuracy and the impact of 5 different claims-based pneumonia definitions. Three International Classification of Diseases, Version 9, (ICD-9), and 2 diagnosis-related group (DRG)-based case identification algorithms were compared against an independent, clinical pneumonia reference standard. Among 10748 patients, 272 (2.5%) had pneumonia verified by the reference standard. The sensitivity of claims-based algorithms ranged from 47.8% to 66.2%. The positive predictive values ranged from 72.6% to 80.8%. Patient-related variables were not significantly different from the reference standard among the 3 ICD-9-based algorithms. DRG-based algorithms had significantly lower hospital admission rates (57% and 65% vs 73.2%), lower 30-day mortality (5.0% and 5.8% vs 10.7%), shorter length of stay (3.9 and 4.1 days vs 5.6 days), and lower costs (USD $4543 and USD $5159 vs USD $8585). Claims-based identification algorithms for defining pneumonia in administrative databases are imprecise. ICD-9-based algorithms did not influence patient variables in our population. Identifying pneumonia patients with DRG codes is significantly less precise.
Available from: PubMed Central
- "We identified cases using ICD9-CM codes from the 5 discharge diagnosis codes from all hospitalizations during the study period. Cases were selected according to the following criteria: an adult (age >18 yrs) hospitalized with a first discharge diagnosis of pneumonia (480–483, 485–487) or aspiration pneumonia (507), or a patient with a secondary diagnosis of pneumonia (480–483, 485–487) in combination with a primary diagnosis of respiratory failure (518.8) or sepsis (038).20 Patients were excluded if they had less than 1 year of continuous records in the NHI before developing pneumonia or if their record had no information on sex. "
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Recent studies have shown that use of angiotensin-converting enzyme (ACE) inhibitors may decrease pneumonia risk in various populations. We investigated the effect of ACE inhibitors and angiotensin II receptor blockers (ARBs) on pneumonia hospitalization in the general population of Taiwan.
We conducted a case-crossover study using the Taiwan Longitudinal Health Insurance Database for the year 2005. Data from patients hospitalized for the first time for pneumonia during 1997–2007 were analyzed. The case period was defined as the 30 days before admission; the periods 90 to 120 days and 180 to 210 days before admission were used as control periods. Prescribing status of ACE inhibitors and ARBs during the 3 periods was assessed for each patient. Conditional logistic regression was used to estimate the odds ratio (OR) for pneumonia associated with use of ACE inhibitors and ARBs.
We identified 10 990 cases of hospitalization for new pneumonia. After adjustment for time-variant confounding factors, pneumonia was not associated with use of ACEI or ARBS: the ORs were 0.99 (95% CI, 0.81–1.21) and 0.96 (0.72–1.28), respectively. No association was seen for cumulative defined daily doses (DDDs), as compared with nonusers, for 0 to 30, 31 to 60, or more than 60 DDDs. The results were found to be robust in sensitivity analysis.
Neither the use nor cumulative dose of ACE inhibitors or ARBs was associated with pneumonia among the Taiwanese general population.
Journal of Epidemiology 08/2013; 23(5). DOI:10.2188/jea.JE20120112 · 3.02 Impact Factor
Available from: Andrew Dick
- "(pneumonia cases with a bacterial diagnosis code) . These ICD-9-CM codes have been used in previous research and the 038 codes for septicemia and the 482 codes for pneumonia have been validated with a specificity and positive predictive value of 99% and 89%, and 99% and 85%, respectively [3,7,18]. "
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Hospital associated infections are major problems, which are increasing in incidence and very costly. However, most research has focused only on measuring consequences associated with the initial hospitalization. We explored the long-term consequences of infections in elderly Medicare patients admitted to an intensive care unit (ICU) and discharged alive, focusing on: sepsis, pneumonia, central-line-associated bloodstream infections (CLABSI), and ventilator-associated pneumonia (VAP); the relationships between the infections and long-term survival and resource utilization; and how resource utilization was related to impending death during the follow up period.
Clinical data and one year pre- and five years post-index hospitalization Medicare records were examined. Hazard ratios (HR) and healthcare utilization incidence ratios (IR) were estimated from state of the art econometric models. Patient demographics (i.e., age, gender, race and health status) and Medicaid status (i.e., dual eligibility) were controlled for in these models.
In 17,537 patients, there were 1,062 sepsis, 1,802 pneumonia, 42 CLABSI and 52 VAP cases. These subjects accounted for 62,554 person-years post discharge. The sepsis and CLABSI cohorts were similar as were the pneumonia and VAP cohorts. Infection was associated with increased mortality (sepsis HR = 1.39, P < 0.01; and pneumonia HR = 1.58, P < 0.01) and the risk persisted throughout the follow-up period. Persons with sepsis and pneumonia experienced higher utilization than controls (e.g., IR for long-term care utilization for those with sepsis ranged from 2.67 to 1.93 in years 1 through 5); and, utilization was partially related to impending death.
The infections had significant and lasting adverse consequences among the elderly. Yet, many of these infections may be preventable. Investments in infection prevention interventions are needed in both community and hospitals settings.
BMC Health Services Research 11/2012; 12(1):432. DOI:10.1186/1472-6963-12-432 · 1.71 Impact Factor
Available from: Dana Mukamel
- "Patients with sepsis, pneumonia, Staphylococcus infections, or Clostridium difficile associated disease (CDAD) were classified as having an HAI. We used previously published criteria for identifying HAIs using ICD-9-CM codes (Table 1) [25-29]. Patients with length-of-stay less than 3 days were excluded from analyses based on HAIs. "
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ABSTRACT: The enormous fiscal pressures facing trauma centers may lead trauma centers to reduce nurse staffing and to make increased use of less expensive and less skilled personnel. The impact of nurse staffing and skill mix on trauma outcomes has not been previously reported. The goal of this study was to examine whether nurse staffing levels and nursing skill mix are associated with trauma patient outcomes.
We used data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to perform a cross-sectional study of 70,142 patients admitted to 77 Level I and Level II centers. Logistic regression models were used to examine the association between nurse staffing measures and (1) mortality, (2) healthcare associated infections (HAI), and (3) failure-to-rescue. We controlled for patient risk factors (age, gender, injury severity, mechanism of injury, comorbidities) and hospital structural characteristics (trauma center status - Level I versus Level II, hospital size, ownership, teaching status, technology level, and geographic region).
A 1% increase in the ratio of licensed practical nurse (LPN) to total nursing time was associated with a 4% increase in the odds of mortality (adj OR 1.04; 95% CI: 1.02-1.06; p = 0.001) and a 6% increase in the odds of sepsis (adj OR 1.06: 1.03-1.10; p < 0.001). Hospitals in the highest quartile of LPN staffing had 3 excess deaths (95% CI: 1.2, 5.1) and 5 more episodes of sepsis (95% CI: 2.3, 7.6) per 1000 patients compared to hospitals in the lower quartile of LPN staffing.
Higher hospital LPN staffing levels are independently associated with slightly higher rates of mortality and sepsis in trauma patients admitted to Level I or Level II trauma centers.
BMC Health Services Research 08/2012; 12(1):247. DOI:10.1186/1472-6963-12-247 · 1.71 Impact Factor
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