scholarly journals Multicenter Study of Surveillance for Hospital-Onset Clostridium difficile Infection by the Use of ICD-9-CM Diagnosis Codes

2010 ◽  
Vol 31 (3) ◽  
pp. 262-268 ◽  
Author(s):  
Erik R. Dubberke ◽  
Anne M. Butler ◽  
Deborah S. Yokoe ◽  
Jeanmarie Mayer ◽  
Bala Hota ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
International Classification Of Diseases ◽  
Discharge Diagnosis ◽  
Linear Regression Models ◽  
Diagnosis Code ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Toxin Assay ◽  
Present On Admission

Objective.To compare incidence of hospital-onset Clostridium difficile infection (CDI) measured by the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes with rates measured by the use of electronically available C. difficile toxin assay results.Methods.Cases of hospital-onset CDI were identified at 5 US hospitals during the period from July 2000 through June 2006 with the use of 2 surveillance definitions: positive toxin assay results (gold standard) and secondary ICD-9-CM discharge diagnosis codes for CDI. The x2 test was used to compare incidence, linear regression models were used to analyze trends, and the test of equality was used to compare slopes.Results.Of 8,670 cases of hospital-onset CDI, 38% were identified by the use of both toxin assay results and the ICD-9-CM code, 16% by the use of toxin assay results alone, and 45% by the use of the ICD-9-CM code alone. Nearly half (47%) of cases of CDI identified by the use of a secondary diagnosis code alone were community-onset CDI according to the results of the toxin assay. The rate of hospital-onset CDI found by use of ICD-9-CM codes was significantly higher than the rate found by use of toxin assay results overall (P<.001), as well as individually at 3 of the 5 hospitals (P<.001 for all). The agreement between toxin assay results and the presence of a secondary ICD-9-CM diagnosis code for CDI was moderate, with an overall k value of 0.509 and hospital-specific k values of 0.489–0.570. Overall, the annual increase in CDI incidence was significantly greater for rates determined by the use of ICD-9-CM codes than for rates determined by the use of toxin assay results (P = .006).Conclusions.Although the ICD-9-CM code for CDI seems to be adequate for measuring the overall CDI burden, use of the ICD-9-CM discharge diagnosis code for CDI, without present-on-admission code assignment, is not an acceptable surrogate for surveillance for hospital-onset CDI.

Review of Current Literature on the Economic Burden of Clostridium difficile Infection

2009 ◽  
Vol 30 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Erik R. Dubberke ◽  
Albert I. Wertheimer
Keyword(s):  
Clostridium Difficile ◽  
Economic Burden ◽  
International Classification Of Diseases ◽  
The United States ◽  
Diagnosis Code ◽  
Number Of Patients ◽  
Classification Of Diseases ◽  
Control And Prevention ◽  
Healthcare Associated

Clostridium difficile is well recognized as the most common infectious cause of healthcare-associated diarrhea. Since 2000, this pathogen has demonstrated an increased propensity to cause more frequent and virulent illness that is often refractory to treatment. An analysis by the Centers for Disease Control and Prevention revealed that, in the United States, the number of patients discharged from hospitals who received the International Classification of Diseases, Ninth Revision discharge diagnosis code for C. difficile infection (CDI) more than doubled from 2000 to 2003. Unpublished data indicate that this trend has continued and that more than 250,000 US hospitalizations were associated with CDI in 2005. A previously uncommon hypervirulent strain of C. difficile is thought to contribute, in part, to the dramatic increase in the incidence and severity of the infection. Although the economic impact of the disease is believed to be profound and is expected to increase, data on the costs associated with CDI are scarce. To more completely assess its economic burden, we performed a review of available literature that reported costs associated with the infection.

scholarly journals Validity of the International Classification of Diseases, 10th revision discharge diagnosis codes for hyponatraemia in the Danish National Registry of Patients

BMJ Open ◽  
2014 ◽  
Vol 4 (4) ◽  
pp. e004956 ◽  
Author(s):  
Louise Holland-Bill ◽  
Christian Fynbo Christiansen ◽  
Sinna Pilgaard Ulrichsen ◽  
Troels Ring ◽  
Jens Otto Lunde Jørgensen ◽  
...  
Keyword(s):  
International Classification Of Diseases ◽  
National Registry ◽  
International Classification ◽  
Discharge Diagnosis ◽  
Diagnosis Codes ◽  
Classification Of Diseases

scholarly journals Association Between Diagnosis Code Expansion and Changes in 30‐Day Risk‐Adjusted Outcomes for Cardiovascular Diseases

2021 ◽  
Author(s):  
Lauren Gilstrap ◽  
Rishi K. Wadhera ◽  
Andrea M. Austin ◽  
Stephen Kearing ◽  
Karen E. Joynt Maddox ◽  
...  
Keyword(s):  
Logistic Regression ◽  
International Classification Of Diseases ◽  
Fee For Service ◽  
Readmission Rates ◽  
Difference In Differences ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Changes In Risk ◽  
The Impact

BACKGROUND In January 2011, Centers for Medicare and Medicaid Services expanded the number of inpatient diagnosis codes from 9 to 25, which may influence comorbidity counts and risk‐adjusted outcome rates for studies spanning January 2011. This study examines the association between (1) limiting versus not limiting diagnosis codes after 2011, (2) using inpatient‐only versus inpatient and outpatient data, and (3) using logistic regression versus the Centers for Medicare and Medicaid Services risk‐standardized methodology and changes in risk‐adjusted outcomes. METHODS AND RESULTS Using 100% Medicare inpatient and outpatient files between January 2009 and December 2013, we created 2 cohorts of fee‐for‐service beneficiaries aged ≥65 years. The acute myocardial infarction cohort and the heart failure cohort had 578 728 and 1 595 069 hospitalizations, respectively. We calculate comorbidities using (1) inpatient‐only limited diagnoses, (2) inpatient‐only unlimited diagnoses, (3) inpatient and outpatient limited diagnoses, and (4) inpatient and outpatient unlimited diagnoses. Across both cohorts, International Classification of Diseases, Ninth Revision ( ICD‐9 ) diagnoses and hierarchical condition categories increased after 2011. When outpatient data were included, there were no significant differences in risk‐adjusted readmission rates using logistic regression or the Centers for Medicare and Medicaid Services risk standardization. A difference‐in‐differences analysis of risk‐adjusted readmission trends before versus after 2011 found that no significant differences between limited and unlimited models for either cohort. CONCLUSIONS For studies that span 2011, researchers should consider limiting the number of inpatient diagnosis codes to 9 and/or including outpatient data to minimize the impact of the code expansion on comorbidity counts. However, the 2011 code expansion does not appear to significantly affect risk‐adjusted readmission rate estimates using either logistic or risk‐standardization models or when using or excluding outpatient data.

scholarly journals Use of Diagnosis Codes and/or Wound Culture Results for Surveillance of Surgical Site Infection after Mastectomy and Breast Reconstruction

2010 ◽  
Vol 31 (05) ◽  
pp. 544-547 ◽  
Author(s):  
Margaret A. Olsen ◽  
Victoria J. Fraser
Keyword(s):  
Surgical Site Infection ◽  
Claims Data ◽  
Breast Surgery ◽  
International Classification Of Diseases ◽  
Site Infection ◽  
Wound Culture ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Major Breast

We compared surveillance of surgical site infection (SSI) after major breast surgery by using a combination of International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes and microbiology-based surveillance. The sensitivity of the coding algorithm for identification of SSI was 87.5%, and the sensitivity of wound culture for identification of SSI was 78.1%. Our results suggest that SSI surveillance can be reliably performed using claims data.

The prevalence of localised scleroderma in childhood assessed in the administrative claims data from the United States

2018 ◽  
Vol 4 (1) ◽  
pp. 77-78
Author(s):  
Timothy Beukelman ◽  
Fenglong Xie ◽  
Ivan Foeldvari
Keyword(s):  
United States ◽  
Systemic Sclerosis ◽  
Claims Data ◽  
International Classification Of Diseases ◽  
The United States ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Diagnosis Codes ◽  
Classification Of Diseases

Juvenile localised scleroderma is believed an orphan autoimmune disease, which occurs 10 times more often than systemic sclerosis in childhood and is believed to have a prevalence of 1 per 100,000 children. To gain data regarding the prevalence of juvenile localised scleroderma, we assessed the administrative claims data in the United States using the International Classification of Diseases, Ninth Revision diagnosis codes. We found an estimated prevalence in each year ranging from 3.2 to 3.6 per 10,000 children. This estimate is significantly higher as found in previous studies.

Use of International Classification of Diseases, Ninth Revision Clinical Modification Codes and Medication Use Data to Identify Nosocomial Clostridium difficile Infection

2009 ◽  
Vol 30 (11) ◽  
pp. 1070-1076 ◽  
Author(s):  
Mia Schmiedeskamp ◽  
Spencer Harpe ◽  
Ronald Polk ◽  
Michael Oinonen ◽  
Amy Pakyz
Keyword(s):  
Drug Therapy ◽  
Clostridium Difficile ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Adult Patients ◽  
Classification Of Diseases ◽  
Sensitivity Specificity

Objective.The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for Clostridium difficile infection (CDI) is used for surveillance of CDI. However, the ICD-9-CM code alone cannot separate nosocomial cases from cases acquired outside the institution. The purpose of this study was to determine whether combining the ICD-9-CM code with medication treatment data for CDI in hospitalized patients could enable us to distinguish between patients with nosocomial CDI and patients who were admitted with CDI. The primary objective was to compare the sensitivity, specificity, and predictive value of using the combination of ICD-9-CM code for CDI and CDI treatment records to identify cases of nosocomial CDI with the sensitivity, specificity, and predictive value of using the ICD-9-CM code alone.Design.Validation sample cross-sectional study.Setting.Academic health center.Methods.Administrative claims data from July 1, 2004, to June 30, 2005, were queried to identify adults discharged with an ICD-9-CM code for CDI and to find documentation of CDI therapy with oral vancomycin or metronidazole. Laboratory and medical records were queried to identify symptomatic CDI toxin-positive adult patients with nosocomial CDI and were compared with records of patients whose cases were predicted to be nosocomial by means of ICD-9-CM code and CDI therapy data.Results.Of 23,920 adult patients discharged from the hospital, 62 had nosocomial CDI according to symptoms and toxin assay. The sensitivity of the ICD-9-CM code alone for identifying nosocomial CDI was 96.8%, the specificity was 99.6%, the positive predictive value was 40.8%, and the negative predictive value was 100%. When CDI drug therapy was included with the ICD-9-CM code, the sensitivity ranged from 58.1% to 85.5%, specificity was virtually unchanged, and the range in positive predictive value was 37.9%–80.0%.Conclusion.Combining the ICD-9-CM code for CDI with drug therapy information increased the positive predictive value for nosocomial CDI but decreased the sensitivity.

Evaluation of International Classification of Diseases, Ninth Revision, Clinical Modification Codes for Reporting Methicillin-Resistant Staphylococcus aureus Infections at a Hospital in Illinois

2010 ◽  
Vol 31 (05) ◽  
pp. 463-468 ◽  
Author(s):  
Melissa K. Schaefer ◽  
Katherine Ellingson ◽  
Craig Conover ◽  
Alicia E. Genisca ◽  
Donna Currie ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Care Hospital ◽  
Methicillin Resistant ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Mrsa Infection ◽  
Healthcare Associated

Background. States, including Illinois, have passed legislation mandating the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for reporting healthcare-associated infections, such as methicillin-resistant Staphylococcus aureus (MRSA). Objective. To evaluate the sensitivity of ICD-9-CM code combinations for detection of MRSA infection and to understand implications for reporting. Methods. We reviewed discharge and microbiology databases from July through August of 2005, 2006, and 2007 for ICD-9-CM codes or microbiology results suggesting MRSA infection at a tertiary care hospital near Chicago, Illinois. Medical records were reviewed to confirm MRSA infection. Time from admission to first positive MRSA culture result was evaluated to identify hospital-onset MRSA (HO-MRSA) infections. The sensitivity of MRSA code combinations for detecting confirmed MRSA infections was calculated using all codes present in the discharge record (up to 15); the effect of reviewing only 9 diagnosis codes, the number reported to the Centers for Medicare and Medicaid Services, was also evaluated. The sensitivity of the combination of diagnosis codes for detection of HO-MRSA infections was compared with that for community-onset MRSA (CO-MRSA) infections. Results. We identified 571 potential MRSA infections with the use of screening criteria; 403 (71%) were confirmed MRSA infections, of which 61 (15%) were classified as HO-MRSA. The sensitivity of MRSA code combinations was 59% for all confirmed MRSA infections when 15 diagnoses were reviewed compared with 31% if only 9 diagnoses were reviewed (P &lt; .001). The sensitivity of code combinations was 33% for HO-MRSA infections compared with 62% for CO-MRSA infections (P &lt; .001). Conclusions. Limiting analysis to 9 diagnosis codes resulted in low sensitivity. Furthermore, code combinations were better at revealing CO-MRSA infections than HO-MRSA infections. These limitations could compromise the validity of ICD-9-CM codes for interfacility comparisons and for reporting of healthcare-associated MRSA infections.

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