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      Validity of AHRQ patient safety indicators derived from ICD-10 hospital discharge abstract data (chart review study)

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          Abstract

          Objective

          To assess if the Agency for Healthcare Research and Quality  patient safety indictors (PSIs) could be used for case findings in the International Classification of Disease 10th revision (ICD-10) hospital discharge abstract data.

          Design

          We identified and randomly selected 490 patients with a foreign body left during a procedure (PSI 5—foreign body), selected infections (IV site) due to medical care (PSI 7—infection), postoperative pulmonary embolism (PE) or deep vein thrombosis (DVT; PSI 12—PE/DVT), postoperative sepsis (PSI 13—sepsis)and accidental puncture or laceration (PSI 15—laceration) among patients discharged from three adult acute care hospitals in Calgary, Canada in 2007 and 2008. Their charts were reviewed for determining the presence of PSIs and used as the reference standard, positive predictive value (PPV) statistics were calculated to determine the proportion of positives in the administrative data representing ‘true positives’.

          Results

          The PPV for PSI 5—foreign body was 62.5% (95% CI 35.4% to 84.8%), PSI 7—infection was 79.1% (67.4% to 88.1%), PSI 12—PE/DVT was 89.5% (66.9% to 98.7%), PSI 13—sepsis was 12.5% (1.6% to 38.4%) and PSI 15—laceration was 86.4% (75.0% to 94.0%) after excluding those who presented to the hospital with the condition.

          Conclusions

          Several PSIs had high PPV in the ICD administrative data and are thus powerful tools for true positive case finding. The tools could be used to identify potential cases from the large volume of admissions for verification through chart reviews. In contrast, their sensitivity has not been well characterised and users of PSIs should be cautious if using them for ‘quality of care reporting’ presenting the rate of PSIs because under-coded data would generate falsely low PSI rates.

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          Most cited references17

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          Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.

          The goal of this study was to assess the validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data and to determine whether there were improvements in the validity of coding for clinical conditions compared with ICD-9 Clinical Modification (ICD-9-CM) data. We reviewed 4,008 randomly selected charts for patients admitted from January 1 to June 30, 2003 at four teaching hospitals in Alberta, Canada to determine the presence or absence of 32 clinical conditions and to assess the agreement between ICD-10 data and chart data. We then re-coded the same charts using ICD-9-CM and determined the agreement between the ICD-9-CM data and chart data for recording those same conditions. The accuracy of ICD-10 data relative to chart data was compared with the accuracy of ICD-9-CM data relative to chart data. Sensitivity values ranged from 9.3 to 83.1 percent for ICD-9-CM and from 12.7 to 80.8 percent for ICD-10 data. Positive predictive values ranged from 23.1 to 100 percent for ICD-9-CM and from 32.0 to 100 percent for ICD-10 data. Specificity and negative predictive values were consistently high for both ICD-9-CM and ICD-10 databases. Of the 32 conditions assessed, ICD-10 data had significantly higher sensitivity for one condition and lower sensitivity for seven conditions relative to ICD-9-CM data. The two databases had similar sensitivity values for the remaining 24 conditions. The validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions was generally similar though validity differed between coding versions for some conditions. The implementation of ICD-10 coding has not significantly improved the quality of administrative data relative to ICD-9-CM. Future assessments like this one are needed because the validity of ICD-10 data may get better as coders gain experience with the new coding system.
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            The development, evolution, and modifications of ICD-10: challenges to the international comparability of morbidity data.

            The United States is about to make a major nationwide transition from ICD-9-CM coding of hospital discharges to ICD-10-CM, a country-specific modification of the World Health Organization's ICD-10. As this transition occurs, the WHO is already in the midst of developing ICD-11. Given this context, we undertook this review to discuss: (1) the history of the International Classification of Diseases (a core information "building block" for health systems everywhere) from its introduction to the current era of ICD-11 development; (2) differences across country-specific ICD-10 clinical modifications and the challenges that these differences pose to the international comparability of morbidity data; (3) potential strategic approaches to achieving better international ICD-11 comparability. A literature review and stakeholder consultation was carried out. The various ICD-10 clinical modifications (ICD-10-AM [Australia], ICD-10-CA [Canada], ICD-10-GM [Germany], ICD-10-TM [Thailand], ICD-10-CM [United States]) were compared. These ICD-10 modifications differ in their number of codes, chapters, and subcategories. Specific conditions are present in some but not all of the modifications. ICD-11, with a similar structure to ICD-10, will function in an electronic health records environment and also provide disease descriptive characteristics (eg, causal properties, functional impact, and treatment). The threat to the comparability of international clinical morbidity is growing with the development of many country-specific ICD-10 versions. One solution to this threat is to develop a meta-database including all country-specific modifications to ensure more efficient use of people and resources, decrease omissions and errors but most importantly provide a platform for future ICD updates.
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              Validity of selected AHRQ patient safety indicators based on VA National Surgical Quality Improvement Program data.

              To examine the criterion validity of the Agency for Health Care Research and Quality (AHRQ) Patient Safety Indicators (PSIs) using clinical data from the Veterans Health Administration (VA) National Surgical Quality Improvement Program (NSQIP). Fifty five thousand seven hundred and fifty two matched hospitalizations from 2001 VA inpatient surgical discharge data and NSQIP chart-abstracted data. We examined the sensitivities, specificities, positive predictive values (PPVs), and positive likelihood ratios of five surgical PSIs that corresponded to NSQIP adverse events. We created and tested alternative definitions of each PSI. FY01 inpatient discharge data were merged with 2001 NSQIP data abstracted from medical records for major noncardiac surgeries. Sensitivities were 19-56 percent for original PSI definitions; and 37-63 percent using alternative PSI definitions. PPVs were 22-74 percent and did not improve with modifications. Positive likelihood ratios were 65-524 using original definitions, and 64-744 using alternative definitions. "Postoperative respiratory failure" and "postoperative wound dehiscence" exhibited significant increases in sensitivity after modifications. PSI sensitivities and PPVs were moderate. For three of the five PSIs, AHRQ has incorporated our alternative, higher sensitivity definitions into current PSI algorithms. Further validation should be considered before most of the PSIs evaluated herein are used to publicly compare or reward hospital performance.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2013
                10 October 2013
                : 3
                : 10
                : e003716
                Affiliations
                [1 ]Department of Community Health Sciences, University of Calgary , Calgary, Alberta, Canada
                [2 ]Faculty of Nursing, University of Calgary , Calgary, Alberta, Canada
                [3 ]Alberta Health Services, Calgary, Alberta, Canada
                [4 ]Department of Medicine, University of Calgary , Calgary, Alberta, Canada
                Author notes
                [Correspondence to ] Dr Hude Quan; hquan@ 123456ucalgary.ca
                Article
                bmjopen-2013-003716
                10.1136/bmjopen-2013-003716
                3796280
                24114372
                37f51ac2-5ac7-471e-b52c-1f592afa5161
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/

                History
                : 6 August 2013
                : 28 August 2013
                : 8 September 2013
                Categories
                Health Services Research
                Research
                1506
                1704
                1702
                1704
                1692

                Medicine
                epidemiology
                Medicine
                epidemiology

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