Risk-Stratification of Ischemic Stroke Patients on the Basis of Anatomic Criteria Essential to the Prevention of Hospital-Acquired Conditions and Performance Along Patient Safety Indicators

2013 ◽  
Vol 80 (6) ◽  
pp. 777-779
Author(s):  
J. Scott Pannell ◽  
Alexander A. Khalessi
2015 ◽  
Vol 122 (4) ◽  
pp. 870-875 ◽  
Author(s):  
Kyle M. Fargen ◽  
Dan Neal ◽  
Spiros L. Blackburn ◽  
Brian L. Hoh ◽  
Maryam Rahman

OBJECT The Agency for Healthcare Research and Quality patient safety indicators (PSIs) and the Centers for Medicare and Medicaid Services hospital-acquired conditions (HACs) are publicly reported quality metrics linked directly to reimbursement. The occurrence of PSIs and HACs is associated with increased mortality and hospital costs after stroke. The relationship between insurance status and PSI and HAC rates in hospitalized patients treated for acute ischemic stroke was determined using the Nationwide Inpatient Sample (NIS) database. METHODS The NIS was queried for all hospitalizations involving acute ischemic stroke between 2002 and 2011. The rate of each PSI and HAC was determined by searching the hospital records for ICD-9 codes. The SAS statistical software package was used to calculate rates and perform multivariable analyses to determine the effects of patient variables on the probability of developing each indicator. RESULTS The NIS query revealed 1,507,336 separate patient admissions that had information on both primary payer and hospital teaching status. There were 227,676 PSIs (15.1% of admissions) and 42,841 HACs reported (2.8%). Patient safety indicators occurred more frequently in Medicaid/self-pay/no-charge patients (19.1%) and Medicare patients (15.0%) than in those with private insurance (13.6%; p < 0.0001). In a multivariable analysis, Medicaid, self-pay, or nocharge patients had significantly longer hospital stays, higher mortality, and worse outcomes than those with private insurance (p < 0.0001). CONCLUSIONS Insurance status is an independent predictor of patient safety events after stroke. Private insurance is associated with lower mortality, shorter lengths of stay, and improved clinical outcomes.


2011 ◽  
Vol 35 (3) ◽  
pp. 245 ◽  
Author(s):  
Jude L. Michel ◽  
Diana Cheng ◽  
Terri J. Jackson

Objective. To examine differences between Queensland and Victorian coding of hospital-acquired conditions and suggest ways to improve the usefulness of these data in the monitoring of patient safety events. Design. Secondary analysis of admitted patient episode data collected in Queensland and Victoria. Methods. Comparison of depth of coding, and patterns in the coding of ten commonly coded complications of five elective procedures. Results. Comparison of the mean complication codes assigned per episode revealed Victoria assigns more valid codes than Queensland for all procedures, with the difference between the states being significantly different in all cases. The proportion of the codes flagged as complications was consistently lower for Queensland when comparing 10 common complications for each of the five selected elective procedures. The estimated complication rates for the five procedures showed Victoria to have an apparently higher complication rate than Queensland for 35 of the 50 complications examined. Conclusion. Our findings demonstrate that the coding of complications is more comprehensive in Victoria than in Queensland. It is known that inconsistencies exist between states in routine hospital data quality. Comparative use of patient safety indicators should be viewed with caution until standards are improved across Australia. More exploration of data quality issues is needed to identify areas for improvement. What is known about the topic? Routine data are low cost, accessible and timely but the quality is often questioned. This deters researchers and clinicians from using the data to monitor aspects of quality improvement. Previous studies have reported on the quality of diagnosis coding in Australia but not specifically on the quality of use of the condition-onset flag denoting hospital-acquired conditions. What does this paper add? Few studies have tested the consistency of the data between Australian states. No previous studies have evaluated the comprehensiveness of the coding of hospital-acquired conditions using routine data. This paper compares two states to highlight the differences in the coding of complications, with the aim of improving routine data to support patient safety. What are the implications for practitioners? The results imply more work needs to be done to improve the coding and flagging of complications so the data are valid and comprehensive. Further research should identify problem areas responsible for differences in the data so that training and audit strategies can be developed to improve the collection of this information. Practitioners may then be more confident in using routine coded inpatient data as part of the process of monitoring patient safety.


2013 ◽  
Vol 119 (6) ◽  
pp. 1633-1640 ◽  
Author(s):  
Kyle M. Fargen ◽  
Dan Neal ◽  
Maryam Rahman ◽  
Brian L. Hoh

Object The Agency for Healthcare Research and Quality (AHRQ) patient safety indicators (PSIs) and the Centers for Medicare and Medicaid Services hospital-acquired conditions (HACs) are publicly reported metrics used to gauge the quality of health care provided by health care institutions. To better understand the prevalence of these events in hospitalized patients treated for ruptured cerebral aneurysms, the authors determined the incidence rates of PSIs and HACs among patients with a diagnosis of subarachnoid hemorrhage and procedure codes for either coiling or clipping in the Nationwide Inpatient Sample database. Methods The authors queried the Nationwide Inpatient Sample database, part of the AHRQ's Healthcare Cost and Utilization Project, for all hospitalizations between 2002 and 2010 involving coiling or clipping of ruptured cerebral aneurysms. The incidence rate of each PSI and HAC was determined by searching the hospital records for ICD-9 codes. The authors used the SAS statistical software package to calculate incidence rates and perform multivariate analyses to determine the effects of patient variables on the probability of developing each indicator. Results There were 62,972 patient admissions with a diagnosis code of subarachnoid hemorrhage between the years 2002 and 2010; 10,274 (16.3%) underwent clipping and 8248 (13.1%) underwent endovascular coiling. A total of 6547 PSI and HAC events occurred within the 10,274 patients treated with clipping; at least 1 PSI or HAC occurred in 47.9% of these patients. There were 5623 total PSI and HAC events among the 8248 patients treated with coils; at least 1 PSI or HAC occurred in 51.0% of coil-treated patients. Age, sex, comorbidities, hospital size, and hospital type had statistically significant associations with indicator occurrence. Compared with patients without events, those treated by either clipping or coiling and had at least 1 PSI during their hospitalization had significantly longer lengths of stay (p < 0.001), higher hospital costs (p < 0.001), and higher in-hospital mortality rates (p < 0.001). Conclusions These results estimate baseline national rates of PSIs and HACs in patients treated for ruptured cerebral aneurysms. These data may be used to gauge individual institutional quality of care and patient safety metrics in comparison with national data.


2013 ◽  
Vol 119 (4) ◽  
pp. 966-973 ◽  
Author(s):  
Kyle M. Fargen ◽  
Maryam Rahman ◽  
Dan Neal ◽  
Brian L. Hoh

Object The Agency for Healthcare Research and Quality (AHRQ) patient safety indicators (PSIs) and the Centers for Medicare and Medicaid Services hospital-acquired conditions (HACs) are metrics used to gauge the quality of health care provided by health care institutions. The PSIs and HACs are publicly reported metrics and are directly linked to reimbursement for services. To better understand the prevalence of these adverse events in hospitalized patients treated for unruptured cerebral aneurysms, the authors determined the incidence rates of PSIs and HACs among patients with a diagnosis of unruptured aneurysm in the Nationwide Inpatient Sample (NIS) database. Methods The NIS, part of the AHRQ's Healthcare Cost and Utilization Project, was queried for all hospitalizations between 2002 and 2010 involving coiling or clipping of unruptured cerebral aneurysms. The incidence rate for each PSI and HAC was determined by searching the hospital records for ICD-9 codes. The SAS statistical software package was used to calculate incidences and perform multivariate analyses to determine the effects of patient variables on the probability of each indicator developing. Results There were 54,589 hospitalizations involving unruptured cerebral aneurysms in the NIS database for the years 2002–2010; 8314 patients (15.2%) underwent surgical clipping and 9916 (18.2%) were treated with endovascular coiling. One thousand four hundred ninety-two PSI and HAC events occurred among the 8314 patients treated with clipping; at least 1 PSI or HAC occurred in 14.6% of these patients. There were 1353 PSI and HAC events among the 9916 patients treated with coiling; at least 1 PSI or HAC occurred in 10.9% of these patients. Age, sex, and comorbidities had statistically significant associations with an adverse event. Compared with the patients having no adverse event, those having at least 1 PSI during their hospitalizations had significantly longer hospital stays (p < 0.0001), higher hospital costs (p < 0.0001), and higher mortality rates (p < 0.0001). Conclusions These results estimate baseline national rates of PSIs and HACs in patients with unruptured cerebral aneurysms. These data may be used to gauge individual institutional quality of care and patient safety metrics in comparison with national data.


2012 ◽  
Vol 78 (7) ◽  
pp. 749-754 ◽  
Author(s):  
Kevin E. Behrns ◽  
Darwin Ang ◽  
Huazi Liu ◽  
Steven J. Hughes ◽  
Holly Creel ◽  
...  

Mortality, length of stay (LOS), patient safety indicators (PSIs), and hospital-acquired conditions (HACs) are routinely reported by the University HealthSystem Consortium (UHC) to measure quality at academic health centers. We hypothesized that a clinical quality measurable goal assigned to individual faculty members would decrease UHC measures of mortality, LOS, PSIs, and HACs. For academic year (AY) 2010–2011, faculty members received a clinical quality goal related to mortality, LOS, PSIs, and HACs. The quality metric constituted 25 per cent of each faculty member's annual evaluation clinical score, which is tied to compensation. The outcomes were compared before and after goal assignment. Outcome data on 6212 patients from AY 2009–2010 were compared with 6094 patients from AY 2010–2011. The mortality index (0.89 vs 0.93; P = 0.73) was not markedly different. However, the LOS index decreased from 1.01 to 0.97 ( P = 0.011), and department-wide PSIs decreased significantly from 285 to 162 ( P = 0.011). Likewise, HACs decreased from 54 to 18 ( P = 0.0013). Seven (17.9%) of 39 faculty had quality grades that were average or below. Quality goals assigned to individual faculty members are associated with decreased average LOS index, PSIs, and HACs. Focused, relevant quality assignments that are tied to compensation improve patient safety and outcomes.


2013 ◽  
Vol 22 (8) ◽  
pp. e582-e589 ◽  
Author(s):  
Amelia K. Boehme ◽  
Andre D. Kumar ◽  
Adrianne M. Dorsey ◽  
James E. Siegler ◽  
Monica S. Aswani ◽  
...  

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Hanadi Hamadi ◽  
Shalmali R. Borkar ◽  
LaRee Moody DHA ◽  
Aurora Tafili ◽  
J. Scott Wilkes ◽  
...  

Author(s):  
Shihab Masrur ◽  
Eric E Smith ◽  
Mathew Reeves ◽  
Xin Zhao ◽  
DaiWai Olson ◽  
...  

National guidelines recommend dysphagia screening (DS) before any oral intake in hospitalized stroke patients to reduce the risk of hospital-acquired pneumonia (HAP). We examined the relationship between DS and HAP in acute ischemic stroke patients in the Get With the Guidelines-Stroke (GWTG-S) program. Methods: Data from 1251 GWTG-S hospitals from 04/01/2003 to 03/01/2009 were analyzed. GWTG-S defines HAP as a clinical diagnosis of pneumonia requiring antibiotics. Use of a bedside, evidence-based swallow screen prior to any oral intake qualified as a DS. Univariate analyses (chi-square for categorical variables or Wilcoxon for continuous variables) and multivariate logistic regression analyses were performed to examine the relationship between DS and HAP, adjusting for patient and hospital characteristics Results: Among 365,726 ischemic stroke patients, 213097 (59.83%) underwent DS, and 25,166 (6.88%) developed HAP. When compared to patients without pneumonia ( Table 1 ), patients with HAP were older and more frequently had CAD/MI, diabetes, prior stroke/TIA, dyslipidemia, atrial fibrillation. They, underwent DS less often, and had increased length of stay, morbidity and in-hospital mortality. Among the subgroup who had NIHSS recorded (n=160,837, 44%), HAP patients had higher median NIHSS (13 vs. 5). Among patients with NIHSS<2, 3.3% developed HAP. In multivariate analysis, factors independently associated with a lower risk of HAP were DS (OR 0.86 [0.83-0.90]), female (OR 0.83 [0.81-0.85]), dyslipidemia (OR 0.84 [0.82-0.86]), and hypertension (OR 0.96 [0.94-0.98]). Discussion: Our data suggests that dysphagia screening is associated with a lower likelihood of HAP, but screening rates remain low. Strategies that increase the rate of dysphagia screening among all stroke patients, even those with mild strokes, should be more broadly implemented. Prospective validation of these findings is warranted. Table 1. Unadjusted associations between patient and hospital characteristics and clinical outcomes Overall(% or value) HAP(% or value) No HAP(% or value) Study Population 365726 (100%) 25166(6.9%) 340560(93.1%) Age (years) Median (IQR) 73(61, 82) 77(66, 85) 73(61,82) Female 52.5 49.2 52.8 Dysphagia Screen Performed 59.8 54.8 60.2 In Hospital Death 5.7 18.1 4.8 P-values are <.0001 for all comparisons and are based on Chi-square test (for dichotomous and nominal factors) or Wilcoxon test (for ordinal and continuous factors)


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