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      Validity of diagnoses, procedures, and laboratory data in Japanese administrative data

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          Abstract

          Background

          Validation of recorded data is a prerequisite for studies that utilize administrative databases. The present study evaluated the validity of diagnoses and procedure records in the Japanese Diagnosis Procedure Combination (DPC) data, along with laboratory test results in the newly-introduced Standardized Structured Medical Record Information Exchange (SS-MIX) data.

          Methods

          Between November 2015 and February 2016, we conducted chart reviews of 315 patients hospitalized between April 2014 and March 2015 in four middle-sized acute-care hospitals in Shizuoka, Kochi, Fukuoka, and Saga Prefectures and used them as reference standards. The sensitivity and specificity of DPC data in identifying 16 diseases and 10 common procedures were identified. The accuracy of SS-MIX data for 13 laboratory test results was also examined.

          Results

          The specificity of diagnoses in the DPC data exceeded 96%, while the sensitivity was below 50% for seven diseases and variable across diseases. When limited to primary diagnoses, the sensitivity and specificity were 78.9% and 93.2%, respectively. The sensitivity of procedure records exceeded 90% for six procedures, and the specificity exceeded 90% for nine procedures. Agreement between the SS-MIX data and the chart reviews was above 95% for all 13 items.

          Conclusion

          The validity of diagnoses and procedure records in the DPC data and laboratory results in the SS-MIX data was high in general, supporting their use in future studies.

          Highlights

          • Validity of DPC and SS-MIX data was tested using chart review results as references.

          • Specificity of DPC diagnoses was high; sensitivity was low and varied by conditions.

          • Procedure records in DPC data were highly sensitive and specific.

          • Accuracy of SS-MIX laboratory data exceeded 95% in all 13 items examined.

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          Most cited references19

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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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            Comparison of coding of heart failure and comorbidities in administrative and clinical data for use in outcomes research.

            Despite the potential usefulness of administrative databases for evaluating outcomes, coding of heart failure and associated comorbidities have not been definitively compared with clinical data. To compare the predictive value of heart failure diagnoses and secondary conditions identified in a large administrative database with chart-based records. The authors studied 1808 patient records sampled from 14 acute care hospitals and compared clinically recorded data with administrative records from the Canadian Institute for Health Information. The impact of comorbidity coding in the administrative data set according to the Charlson classification was examined in models of 30-day mortality. The positive predictive value (PPV) of a primary diagnosis ICD-9 428 was 94.3% using the Framingham criteria and 88.6% using criteria previously validated with pulmonary capillary wedge pressure. There was reduced prevalence of secondary comorbid conditions in administrative data in comparison with clinical chart data. The specificities and PPV/negative predictive values of administratively identified index comorbidities were high. The sensitivities of index comorbidities were low, but were enhanced by examination of hospitalizations within 1 year prior to the index heart failure admission. Using information from prior hospitalizations modestly enhanced 30-day mortality model performance; however, the odds ratio point estimates of the index and enhanced administrative data sets were consistent with the clinical model. The ICD-9 428 primary diagnosis is highly predictive of heart failure using clinical criteria. Examination of hospitalization data up to 1 year prior to the index admission improves comorbidity detection and may provide enhancements to future studies of heart failure mortality.
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              Validity of procedure codes in International Classification of Diseases, 9th revision, clinical modification administrative data.

              Administrative hospital discharge data are widely used to assess quality of care in patients undergoing certain procedures. However, little is known about the validity of administrative coding of procedure data. We conducted a detailed chart review to evaluate the accuracy and completeness of information on procedures in administrative data. We randomly selected 1200 hospital separations in the period April 1, 1996, to March 31, 1997, from administrative discharge data of 3 acute adult hospitals in Calgary, Alberta, Canada. Each separation record in administrative data contains up to 10 procedure coding fields. The corresponding medical charts were reviewed for recording presence or absence of procedures. We then determined sensitivity to quantify the accuracy of coding presence of procedures in administrative data when these are present in the chart data (criterion standard). The agreement between the 2 databases varied greatly across 35 procedures studied. The sensitivity ranged from 0% to 94%. Of 6 major procedures studied, validity of coding was generally good, with 5 procedures having coding sensitivity of 69% and over and only 1 (lysis of peritoneal adhesion) with a low sensitivity of 41%. In contrast, many minor procedures had low sensitivities. Of 29 minor procedures studied, sensitivity was lower than 50% for 15 procedures, between 50% and 79% for 10, and 80% and over for 4. Validity of information on procedures in administrative discharge data appears to be related to type of procedures. Major procedures that are usually performed in operating rooms are reasonably well-coded. Meanwhile, minor procedures that are routinely performed on wards or in radiology departments are generally undercoded.
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                Author and article information

                Contributors
                Journal
                J Epidemiol
                J Epidemiol
                Journal of Epidemiology
                Elsevier
                0917-5040
                1349-9092
                27 January 2017
                October 2017
                27 January 2017
                : 27
                : 10
                : 476-482
                Affiliations
                [a ]Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan
                [b ]Department of Clinical Data Management and Research, Clinical Research Center, National Hospital Organization Headquarters, Tokyo, Japan
                [c ]Quality Management Center, Medical Hospital, Tokyo Medical and Dental University, Tokyo, Japan
                [d ]Department of Health Policy and Informatics, Tokyo Medical and Dental University, Graduate School of Medicine, Tokyo, Japan
                Author notes
                []Corresponding author. Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.Department of Clinical Epidemiology and Health EconomicsSchool of Public HealthThe University of Tokyo7-3-1 HongoBunkyo-kuTokyo113-0033Japan yamana-tky@ 123456umin.ac.jp
                Article
                S0917-5040(17)30003-5
                10.1016/j.je.2016.09.009
                5602797
                28142051
                19124d20-1157-474c-bfb8-29eaff61ddb0
                © 2017 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 6 May 2016
                : 27 September 2016
                Categories
                Original Article

                administrative data,validation,diagnosis,procedure,laboratory data

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