scholarly journals Patient safety indicators for England from hospital administrative data: case-control analysis and comparison with US data

BMJ ◽  
2008 ◽  
Vol 337 (oct17 1) ◽  
pp. a1702-a1702 ◽  
Author(s):  
V. S Raleigh ◽  
J. Cooper ◽  
S. A Bremner ◽  
S. Scobie
Keyword(s):  
Patient Safety ◽  
Administrative Data ◽  
Case Control ◽  
Control Analysis ◽  
Patient Safety Indicators ◽  
Hospital Administrative ◽  
Case Control Analysis ◽  
Hospital Administrative Data

scholarly journals Measuring patient safety in New Zealand public hospitals

2021 ◽  
Author(s):  
◽  
Nicholas Bowden
Keyword(s):  
Patient Safety ◽  
Quality Of Care ◽  
New Zealand ◽  
Administrative Data ◽  
Risk Adjustment ◽  
Public Hospitals ◽  
Hospital Administrative ◽  
The Impact ◽  
Hospital Administrative Data

<p>In New Zealand the Ministry of Health recognises quality of care as an integral part of a high performing health system and identifies patient safety as one of the key dimensions of quality. Over recent years a greater emphasis has been placed on improving patient safety mostly as a result of increased awareness around the frequency of medical error and resulting economic cost. However tools used to measure patient safety are limited. In particular the use of hospital administrative data to measure patient safety is scarce and existing safety measures often ignore one of the major issues confronting comparative analyses of hospital safety, risk adjustment to control for the differences in populations hospitals serve.   The objective of this research is to develop comparable measures of patient safety for New Zealand public hospitals. It uses risk adjustment strategies applied to the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) with New Zealand hospital administrative data, the National Minimum Dataset 2001 to 2009. The research employs econometric techniques to address risk adjustment of the PSIs, utilising existing AHRQ models but adapting and re-estimating them with New Zealand administrative data.   The findings from the research indicate that to use the AHRQ PSIs as measures of hospital patient safety in New Zealand, risk adjustment should first be employed to ensure measures are comparable across hospitals and over time. Overall, although the impact of risk adjustment appears to be minor, it has relevance and this should be recognised. Relative hospital performance is affected by risk adjustment. In particular, it has the greatest impact on those hospitals with poor rankings. The research takes us a step closer to being able to confidently measure patient safety and quality of care in New Zealand public hospitals in an innovative way.</p>

scholarly journals Navigating a ship with a broken compass: evaluating standard algorithms to measure patient safety

2016 ◽  
Vol 24 (2) ◽  
pp. 310-315 ◽  
Author(s):  
Jennifer L Hefner ◽  
Timothy R Huerta ◽  
Ann Scheck McAlearney ◽  
Barbara Barash ◽  
Tina Latimer ◽  
...  
Keyword(s):  
Patient Safety ◽  
Administrative Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Vascular Tumor ◽  
Healthcare Research ◽  
Fiscal Year ◽  
Research Attention ◽  
Patient Safety Indicators ◽  
Hospital Administrative

Objective: Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging. Material and Methods: At a 6-hospital academic medical center, a retrospective analysis was conducted of all PSIs flagged in fiscal year 2014. A multidisciplinary PSI Quality Team reviewed each flagged PSI based on quarterly reports. The positive predictive value (PPV, the percent of clinically validated cases) was calculated for 12 PSI categories. The documentation for each reversed case was reviewed to determine the reasons for PSI reversal. Results: Of 657 PSI flags, 185 were reversed. Seven PSI categories had a PPV below 75%. Four broad categories of reasons for reversal were AHRQ algorithm limitations (38%), coding misinterpretations (45%), present upon admission (10%), and documentation insufficiency (7%). AHRQ algorithm limitations included 2 subcategories: an “incident” was inherent to the procedure, or highly likely (eg, vascular tumor bleed), or an “incident” was nonsignificant, easily controlled, and/or no intervention was needed. Discussion: These findings support previous research highlighting administrative data problems. Additionally, AHRQ algorithm limitations was an emergent category not considered in previous research. Herein we present potential solutions to address these issues. Conclusions: If, despite poor validity, US policy continues to rely on PSIs for incentive and penalty programs, improvements are needed in the quality of administrative data and the standardized PSI algorithms. These solutions require national motivation, research attention, and dissemination support.

scholarly journals Measuring patient safety in New Zealand public hospitals

2021 ◽  
Author(s):  
◽  
Nicholas Bowden
Keyword(s):  
Patient Safety ◽  
Quality Of Care ◽  
New Zealand ◽  
Administrative Data ◽  
Risk Adjustment ◽  
Public Hospitals ◽  
Hospital Administrative ◽  
The Impact ◽  
Hospital Administrative Data

<p>In New Zealand the Ministry of Health recognises quality of care as an integral part of a high performing health system and identifies patient safety as one of the key dimensions of quality. Over recent years a greater emphasis has been placed on improving patient safety mostly as a result of increased awareness around the frequency of medical error and resulting economic cost. However tools used to measure patient safety are limited. In particular the use of hospital administrative data to measure patient safety is scarce and existing safety measures often ignore one of the major issues confronting comparative analyses of hospital safety, risk adjustment to control for the differences in populations hospitals serve.   The objective of this research is to develop comparable measures of patient safety for New Zealand public hospitals. It uses risk adjustment strategies applied to the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) with New Zealand hospital administrative data, the National Minimum Dataset 2001 to 2009. The research employs econometric techniques to address risk adjustment of the PSIs, utilising existing AHRQ models but adapting and re-estimating them with New Zealand administrative data.   The findings from the research indicate that to use the AHRQ PSIs as measures of hospital patient safety in New Zealand, risk adjustment should first be employed to ensure measures are comparable across hospitals and over time. Overall, although the impact of risk adjustment appears to be minor, it has relevance and this should be recognised. Relative hospital performance is affected by risk adjustment. In particular, it has the greatest impact on those hospitals with poor rankings. The research takes us a step closer to being able to confidently measure patient safety and quality of care in New Zealand public hospitals in an innovative way.</p>

scholarly journals Thin-flap (sub-Bowman keratomileusis) versus thick-flap laser in situ keratomileusis for moderate to high myopia: Case-control analysis

2008 ◽  
Vol 34 (12) ◽  
pp. 2073-2078 ◽  
Author(s):  
Dimitri T. Azar ◽  
Ramon C. Ghanem ◽  
Jose de la Cruz ◽  
Joelle A. Hallak ◽  
Takashi Kojima ◽  
...  
Keyword(s):  
High Myopia ◽  
Case Control ◽  
Laser In Situ Keratomileusis ◽  
Control Analysis ◽  
Case Control Analysis

A case control analysis investigating risk factors and outcomes for nephrocalcinosis and renal calculi in neonates

2017 ◽  
Vol 13 (4) ◽  
pp. 356.e1-356.e5 ◽  
Author(s):  
Melissa Huynh ◽  
Roderick Clark ◽  
Jenny Li ◽  
Guido Filler ◽  
Sumit Dave
Keyword(s):  
Risk Factors ◽  
Renal Calculi ◽  
Case Control ◽  
Control Analysis ◽  
Case Control Analysis

Genetic variants in GTF2H1 and risk of lung cancer: A case–control analysis in a Chinese population

Lung Cancer ◽  
2009 ◽  
Vol 63 (2) ◽  
pp. 180-186 ◽  
Author(s):  
Wenting Wu ◽  
Hongliang Liu ◽  
Rong Lei ◽  
Dan Chen ◽  
Shuyu Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Genetic Variants ◽  
Chinese Population ◽  
Case Control ◽  
Control Analysis ◽  
Case Control Analysis
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