Specific ICD-9 Codes Research Articles

Agreement Between Injury Severity Scores Calculation Methods Among Older Adults with Traumatic Brain Injury

Research Objectives Medicare administrative data is a valuable resource for understanding post-acute care outcomes of older adults. However, these records lack information about injury severity that is useful for understanding post-acute care among those with TBI. The Injury Severity Score (ISS) reflects anatomic injury severity and is calculated by trauma registries, but can also be calculated from ICD-9 codes available in administrative data. Our objective is to examine the agreement between ICD-9 derived ISS scores and those sourced from trauma registries. Design Design: We linked Medicare administrative data to the National Trauma Data Bank (NTDB) using a Bayesian record linkage algorithm. We then examined the agreement between trauma registry- ISS scores and those calculated from acute and post-acute ICD-9 codes using Injury Categorization Software (ICDPIC) software. Setting U.S. Inpatient Rehabilitation Facilities (IRF) and Skilled Nursing Facilities (SNF). Participants Medicare beneficiaries who discharged to a SNF or an IRF following hospitalization for TBI between 2011 and 2015. Interventions N/A. Main Outcome Measures Injury Severity Score. Results For scores derived from acute claims, the absolute agreement with trauma registry scores was 11.2% (8.3, 14.2), with 41.8% (37.4, 46.2) of scores being within +/- 5 points. Trauma registry sourced ISS scores were more often higher than the ISS from the trauma registry. In the majority of cases ISS scores could not be calculated from post-acute claims, due to a lack of injury specific ICD-9 codes. Conclusions There is limited agreement between trauma registry ISS scores and those calculated from the ICD-9 codes of acute claims. The scores derived from acute claims may have utility for adjustment, but may underestimate anatomic injury severity of older adults with TBI. Post-acute claims lack the detailed injury codes required for calculation of ISS scores. Author(s) Disclosures Co-author Roee Gutman has served as an expert witness for Johnson & Johnson. The authors have no other conflicts of interest to report. Medicare administrative data is a valuable resource for understanding post-acute care outcomes of older adults. However, these records lack information about injury severity that is useful for understanding post-acute care among those with TBI. The Injury Severity Score (ISS) reflects anatomic injury severity and is calculated by trauma registries, but can also be calculated from ICD-9 codes available in administrative data. Our objective is to examine the agreement between ICD-9 derived ISS scores and those sourced from trauma registries. Design: We linked Medicare administrative data to the National Trauma Data Bank (NTDB) using a Bayesian record linkage algorithm. We then examined the agreement between trauma registry- ISS scores and those calculated from acute and post-acute ICD-9 codes using Injury Categorization Software (ICDPIC) software. U.S. Inpatient Rehabilitation Facilities (IRF) and Skilled Nursing Facilities (SNF). Medicare beneficiaries who discharged to a SNF or an IRF following hospitalization for TBI between 2011 and 2015. N/A. Injury Severity Score. For scores derived from acute claims, the absolute agreement with trauma registry scores was 11.2% (8.3, 14.2), with 41.8% (37.4, 46.2) of scores being within +/- 5 points. Trauma registry sourced ISS scores were more often higher than the ISS from the trauma registry. In the majority of cases ISS scores could not be calculated from post-acute claims, due to a lack of injury specific ICD-9 codes. There is limited agreement between trauma registry ISS scores and those calculated from the ICD-9 codes of acute claims. The scores derived from acute claims may have utility for adjustment, but may underestimate anatomic injury severity of older adults with TBI. Post-acute claims lack the detailed injury codes required for calculation of ISS scores.

Prevalence of Polytrauma Clinical Triad Among Active Duty Service Members

The polytrauma clinical triad (PCT), encompassing traumatic brain injury, PTSD, and chronic pain, has been identified as a significant concern in the Military Health System (MHS). Conditions in this triad mutually reinforce one another and can pose a significant challenge to treatment for patients and providers. Polytrauma clinical triad has previously been studied in deployed veterans but remains understudied in the active duty military population. Therefore, this novel study seeks to determine the prevalence of PCT among active duty service members and to identify the subpopulations most at risk for PCT. This cross-section study used the MHS Data Repository in order to retrospectively review all administrative claim data for active duty service members within the Army, Navy, Air Force, and Marine Corps from fiscal years 2010 to 2015. Specific ICD-9 codes were extracted that correlated with traumatic brain injury, PTSD, and chronic pain to determine the risk of PCT. We used logistic regression to compare individuals presenting with the PCT conditions to those service members without any of the PCT diagnoses codes. The study identified 2,441,698 active duty service members eligible for inclusion. The prevalence of all three conditions of PCT was 5.99 per 1,000 patients. Patients with PCT were most likely to be 20-29 years old (52.15%), male (89.83%), White (59.07%), married (64.18%), Junior Enlisted (55.27%), and serving in the Army (74.71%). This study is the first to identify the risk of PCT in the active duty military population. Awareness of the risk and subsequent prompt identification of the triad will enable treatment through an integrated, team approach, which should alleviate potential patient suffering and improve the efficiency of care and readiness of service members.

High Diagnostic Uncertainty and Inaccuracy in Adult Emergency Department Patients With Dyspnea: A National Database Analysis.

High Diagnostic Uncertainty and Inaccuracy in Adult Emergency Department Patients With Dyspnea: A National Database Analysis.

Which OTCs may have potential CVD risk?

Which OTCs may have potential CVD risk?

Association of Postoperative Readmissions With Surgical Quality Using a Delphi Consensus Process to Identify Relevant Diagnosis Codes

Postoperative readmission data are used to measure hospital performance, yet the extent to which these readmissions reflect surgical quality is unknown. To establish expert consensus on whether reasons for postoperative readmission are associated with the quality of surgery in the index admission. In a modified Delphi process, a panel of 14 experts in medical and surgical readmissions comprising physicians and nonphysicians from Veterans Affairs (VA) and private-sector institutions reviewed 30-day postoperative readmissions from fiscal years 2008 through 2014 associated with inpatient surgical procedures performed at a VA medical center between October 1, 2007, and September 30, 2014. The consensus process was conducted from January through May 2017. Reasons for readmission were grouped into categories based on International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Panelists were given the proportion of readmissions coded by each reason and median (interquartile range) days to readmission. They answered the question, "Does the readmission reason reflect possible surgical quality of care problems in the index admission?" on a scale of 1 (never related) to 5 (directly related) in 3 rounds of consensus building. The consensus process was completed in May 2017 and data were analyzed in June 2017. Consensus on proportion of ICD-9-coded readmission reasons that reflected quality of surgical procedure. In 3 Delphi rounds, the 14 panelists achieved consensus on 50 reasons for readmission; 12 panelists also completed group telephone calls between rounds 1 and 2. Readmissions with diagnoses of infection, sepsis, pneumonia, hemorrhage/hematoma, anemia, ostomy complications, acute renal failure, fluid/electrolyte disorders, or venous thromboembolism were considered associated with surgical quality and accounted for 25 521 of 39 664 readmissions (64% of readmissions; 7.5% of 340 858 index surgical procedures). The proportion of readmissions considered to be not associated with surgical quality varied by procedure, ranging from to 21% (613 of 2331) of readmissions after lower-extremity amputations to 47% (745 of 1598) of readmissions after cholecystectomy. One-third of postoperative readmissions are unlikely to reflect problems with surgical quality. Future studies should test whether restricting readmissions to those with specific ICD-9 codes might yield a more useful quality measure.

Chest pain syndromes are associated with high rates of recidivism and costs in young United States Veterans.

BackgroundRecurrent chest pain is common in patients with and without coronary artery disease. The prevalence and burden of these symptoms on healthcare is unknown.ObjectivesTo compare chest pain return visits (recidivism) in patients with unexplained chest pain (UCP) against reference group of patients with coronary artery disease (CAD) and estimate the annual cost of recurrent chest pain.MethodsIn a retrospective cohort study, a Veteran Affairs (VA) administrative and clinical database of Veterans who were deployed to or served in support of the wars in Iraq or Afghanistan was queried for first disease specific ICD-9 code to form two cohorts (UCP or CAD). Patients were followed between 09/2001-09/2010 for the first and cumulative return visits for UCP or cardiac pain (ACS or angina) to clinic, emergency department or admission; or for all-cause death. Time to return was analyzed using Cox regression and negative binomial models and adjusted for age, gender, race, marital status, and risk factors (hypertension, hyperlipidemia, diabetes, smoking and obesity). Direct total costs included inpatient, outpatient and fee basis (non-VA) costs.ResultsOf 749,036 patients, 20,521 had UCP and 5303 had CAD. UCP patients were young and had a lower burden of risk factors than CAD cohort (p < .01). Yet, these patients were likely to return earlier with any chest pain (adjusted Hazard Ratio [aHR] = 1.76; 95 % CI 1.65-1.88); or unexplained chest pain than CAD patients (aHR: 1.89; 95 % CI 1.77-2.01). UCP patients were also likely to return more frequently for any chest pain (aRate Ratio = 1.54; 95 % CI 1.43-1.64) or UCP than CAD patients (aRR =2.63; 95 % CI 2.43-2.87). Per 100 patients, the 1-year cumulative returns were 37 visits for reference group and 45 visits for UCP cohort. The annual costs for chest pain averaged $69,009 for CAD and $57,336 for UCP patients (log geometric mean ratio=1.25; 95 % CI 1.18-1.32).ConclusionChest pain recidivism is common and costly even in patients without known CAD. We need evidence-based guidelines for these patients to minimize returns.Electronic supplementary materialThe online version of this article (doi:10.1186/s12875-015-0287-9) contains supplementary material, which is available to authorized users.

Challenges in Surveillance for Chikungunya Virus (CHIKV) Infection

We describe challenges and lessons learned using biosurveillance methods for identifying Chikungunya (CHIKV) infections. Surveillance was performed using VA ESSENCE, electronic laboratory data and facility reports. As of Aug. 14, 2014, 21 confirmed/probable cases were identified at 10 hospitals. The principal challenges were lack of a specific ICD-9 code for CHIKV, use of non-specific symptom codes at initial and subsequent encounters, lack of CHIKV testing, long turn-around times for results, poor uniformity in test names, and infection control not being notified of suspected/confirmed CHIKV cases. Based on our experience, a combination surveillance strategy using multiple data sources is essential for CHIKV detection.

Anesthetic-related Neurotoxicity in the Young and Outcome Measures

Anesthetic-related Neurotoxicity in the Young and Outcome Measures

P033: Incidence estimate of Clostridium difficile infection in Emilia-Romagna Region by linkage of administrative and laboratory data

Methods We linked regional data of PHDF and labs by anonymous patient code and we considered only public hospitals with at least 1 identified positive lab test for CD. CDI was defined as follows: “Confirmed case” (Cc) where a specific ICD9 code (00845) was present on the PHDF or an unspecific code for diarrhoea (or intestinal infection) and positivity for CD toxin was retrieved from the lab; “Probable case” (Pc) where either a specific ICD9 code without positivity for CD toxin test or exclusively CD toxin positivity was present. We considered only people older than 1 year and incidence was calculated both for all inpatients and for residents in ER. By linking dates of hospital admission and discharge and date of lab testing we defined CDI as hospital-acquired (HA: >2 days from admission within 28 day from discharge), community-acquired (CA: within 2 days from admission and after 84 days from possible previous discharge, or none admission) or indeterminate (IA: all the remaining cases with hospitalization and lab test).

Severe Sepsis Cohorts Derived From Claims-Based Strategies Appear to be Biased Toward a More Severely Ill Patient Population*

The epidemiology of severe sepsis is derived from administrative databases that rely on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes to select cases. We compared the sensitivity of two code abstraction methods in identifying severe sepsis cases using a severe sepsis registry. Single-center retrospective cohort study. Tertiary care, Academic, University Hospital. One thousand seven hundred thirty-five patients with severe sepsis or septic shock. None. Proportion identified as severe sepsis using two code abstraction methods: 1) the new specific ICD-9 codes for severe sepsis and septic shock, and 2) a validated method requiring two ICD-9 codes for infection and end-organ dysfunction. Multivariable logistic regression was performed to determine sociodemographics and clinical characteristics associated with documentation and coding accuracy. The strategy combining a code for infection and end-organ dysfunction was more sensitive in identifying cases than the method requiring specific ICD-9 codes for severe sepsis or septic shock (47% vs. 21%). Elevated serum lactate level (p<0.001), ICU admission (p<0.001), presence of shock (p<0.001), bacteremia as the source of sepsis (p=0.02), and increased Acute Physiology and Chronic Health Evaluation II score (p<0.001) were independently associated with being appropriately documented and coded. The 28-day mortality was significantly higher in those who were accurately documented/coded (41%, compared with 14% in those who were not, p<0.001), reflective of a more severe presentation on admission. Patients admitted with severe sepsis and septic shock were incompletely documented and under-coded, using either ICD-9 code abstracting method. Documentation of subsequent coding of severe sepsis was more common in more severely ill patients. These findings are important when evaluating current national estimates and when interpreting epidemiologic studies of severe sepsis as cohorts derived from claims-based strategies appear to be biased toward a more severely ill patient population.

Economic Impact of Ventilator-Associated Pneumonia in a Large Matched Cohort

To evaluate the economic impact of ventilator-associated pneumonia (VAP) on length of stay and hospital costs. Design. Retrospective matched cohort study. Premier database of hospitals in the United States. Eligible patients were admitted to intensive care units (ICUs), received mechanical ventilation for ≥2 calendar-days, and were discharged between October 1, 2008, and December 31, 2009. VAP was defined by International Classification of Diseases, Ninth Revision (ICD-9), code 997.31 and ventilation charges for ≥2 calendar-days. We matched patients with VAP to patients without VAP by propensity score on the basis of demographics, administrative data, and severity of illness. Cost was based on provider perspective and procedural cost accounting methods. Of 88,689 eligible patients, 2,238 (2.5%) had VAP; the incidence rate was 1.27 per 1,000 ventilation-days. In the matched cohort, patients with VAP ([Formula: see text]) had longer mean durations of mechanical ventilation (21.8 vs 10.3 days), ICU stay (20.5 vs 11.6 days), and hospitalization (32.6 vs 19.5 days; all [Formula: see text]) than patients without VAP ([Formula: see text]). Mean hospitalization costs were $99,598 for patients with VAP and $59,770 for patients without VAP ([Formula: see text]), resulting in an absolute difference of $39,828. Patients with VAP had a lower in-hospital mortality rate than patients without VAP (482/2,144 [22.5%] vs 630/2,144 [29.4%]; [Formula: see text]). Our findings suggest that VAP continues to occur as defined by the new specific ICD-9 code and is associated with a statistically significant resource utilization burden, which underscores the need for cost-effective interventions to minimize the occurrence of this complication.

PS2-36: Population-based Evaluation of Patients with Methicillin-resistant Staphylococcus aureus (MRSA) Infection in Relation to Animal Feeding Operations in Pennsylvania

the ethnic/racial composition of the PCP and community samples showed that once these differences were controlled, PCPs showed less pro-White bias than the community members. Both groups reported little explicit bias (Cohen's d=0.04), with most participants reporting they felt similarly toward the ethnic/racial groups. Conclusions: Numerous studies have shown that implicit ethnic/racial attitudes in the U.S. generally favor Whites over other ethnic/racial groups. The current study finds that implicit attitudes among PCPs and community members in the Denver metro area are no exception. Despite these general trends, this study also shows that people are not all the same, with some individuals demonstrating strong pro-Latino or pro-African American bias while others show strong pro-White bias. Phase two of the study will begin to investigate whether such biases are related to patient care and hypertension control. Background/Aims: New MRSA strains and epidemiologic patterns of infection have emerged in the past decade, with community-associated patterns now dominant. In Europe, these new community strains have been linked to animal feeding operations (AFOs), raising concerns about the widespread use of non-therapeutic antibiotics in animal feeds. No prior population-based studies have evaluated the risk of MRSA infection in relation to AFOs in the U.S. Methods: We used Geisinger Clinic electronic health record data from 2001 to February 2010 on all primary care patients (n = 440,000). Three groups of patients were identified using specific ICD-9 codes: (1) Community-onset MRSA (CO-MRSA) without risk factors (i.e., infection diagnosed as an outpatient, no antibiotics or hospitalizations in the prior year, no household contacts, no history of MRSA colonization); (2) Hospital-onset MRSA (HO-MRSA) with risk factors (i.e., diagnosed in the hospital with at least one MRSA risk factor); and (3) Skin infection (e.g., cellulitis, carbuncle, skin abscess) without MRSA infection or colonization history and without MRSA risk factors. MRSA cases were frequency- matched to controls with no history of MRSA or risk factors. Information on concentrated animal feeding operations (CAFOs) were obtained from the Pennsylvania Department of Environmental Protection, and included data on animal species (e.g., swine, dairy cattle, chickens), counts, animal equivalent units (AEUs), farm acreage, and manure generated, exported, and stored. Measures of density (e.g., AEUs per sq. mi. in township) and accessibility (e.g., distance from residence to nearest CAFO, gravity models) were derived and used in logistic regression models comparing the four groups. Results: A total of 1926 MRSA cases were identified from 2003 to 2010. Of these, 1058 (55%) were identified in outpatient records, 530 (28%) from inpatient records, and 290 (15%) from medication orders. Inpatient cases increased from 2 in 2003 to 88 in 2005, remained at the same frequency through 2008, and then increased to 116 in 2009. In contrast, outpatient cases increased steadily from 4 in 2003 to a peak of 325 in 2008. Conclusions: The data clearly show a steady increase in the incidence of CO-MRSA in this region. Relations with AFOs will be presented and discussed.

Cost and patterns of care among patients with advanced non-melanoma skin cancer.

e16517 Background: Few studies examine health care utilization (HCU) and cost among basal cell carcinoma (BCC) patients. Although BCC has no specific ICD-9 code, it is known to constitute ~80% of all non-melanoma skin cancers (NMSC). More than 1 million new cases of NMSC were reported in the US in 2010, and there were ~1000 deaths due to NMSC. Methods: A claims-based analysis was conducted using data from January 2002 to March 2010 from a national commercial health insurer. Patients with ≥ 2 claims with a NMSC diagnosis (ICD-9-CM 173.xx) at least 60 days apart, or at least 1 claim for a skin cancer-specific excision with diagnosis code 173.xx were identified. Those with additional primary cancers were excluded. Patients were grouped into 1 of 3 cohorts: metastatic, locally advanced (LA), or “all other.” Metastatic patients had ≥ 2 claims with a metastasis code (ICD-9-CM 196.xx-198.xx) at least 30 days apart. LA patients had ≥ 2 visits with a medical oncologist, ≥ 1 diagnostic imaging service, ≥2 services for radiation therapy or ≥1 visit to 2 or more physician specialties. The remaining patients were “all other.” The time of first NMSC or metastatic disease diagnosis was considered the index date. Total HCU and average per-patient per-month (PPPM) costs during follow-up were estimated. Results: Among 188,795 patients, 155 (0.1%), 2,412 (1.3%) and 186,228 (98.6%) patients, were identified as metastatic, LA or “all other,” respectively with an overall mean follow-up of 917 days. Compared to “all others,” metastatic and LA patients were significantly older and had a higher baseline Charlson comorbidity index (0.64 vs. 2.08 and 1.46 respectively, p-value <0.01). Compared to “all others” and LA patients, more metastatic patients had inpatient stays (19% and 30% vs. 48% respectively, p-value <0.01) and emergency room visits (37% and 43% vs. 55% respectively, p-value <0.01). In addition, total PPPM costs for LA and metastatic patients were ~2x or ~3x higher, respectively, than costs for “all others (p-value <0.01). Conclusions: HCU and cost for NMSC (which includes ~80% BCC) increases significantly as disease advances. Effective treatment could reduce this burden.

Medical and cost burden of atherosclerosis among patients treated in routine clinical practice

Objective:This investigation estimated medical costs attributable to treatment of patients diagnosed with atherosclerosis in routine US clinical practice.Methods:Using Medstat MarketScan claims data, direct costs of care and rates of cardiovascular (CV) events (i.e., myocardial infarction, stroke, revascularization) were examined for patients ≥18 years of age with and without a diagnostic code for atherosclerosis from 1/1/2002 through 12/31/2004. Patients with an atherosclerosis ICD-9 code who had no history of CV events in the preceding 12 months (n = 75,469) were evaluated. A comparison cohort (n = 238,702) was matched on age, gender, geographic region, enrollment time period, and Charlson comorbidity index to estimate incremental costs attributable to atherosclerosis. Differences between patient groups were tested for CV event rates per 1,000 patients and monthly costs for 6 and 12 months before and after diagnosis.Results:Patients had a mean age of 58 years, 52% men, and a comorbidity index of 0.49. Patients diagnosed with atherosclerosis had significantly higher (p < 0.001) rates of CV events (240/1000) after diagnosis, compared with patients without atherosclerosis (32/1000). Mean direct cost of care for patients diagnosed with atherosclerosis was $579/month for 12 months before and $1,074/month for 12 months after diagnosis, an 85% increase. Change in mean annual costs pre/post-index date was $5,232 ($436/month) higher among patients with than those without atherosclerosis (p < 0.001).Limitations:The study population was restricted to patients with diagnosed clinical atherosclerosis based on specific ICD-9 codes. Matching of the patient cohorts was based on observed characteristics and other unobserved differences may exist.Conclusions:Patients with diagnosed atherosclerosis incur significant clinical and economic burden, indicating a need for earlier diagnosis and treatment of atherosclerosis to help in reducing this burden.

Surveillance of Surgical-Site Infections: The World Coming Together?

Surgical-site infections (SSIs) are associated with substantial risk of morbidity, resulting in prolongation of hospital stay and monetary costs attributable to the infection.1-3 Reporting surgeon-specific SSI rates back to the surgeon has been shown in a number of studies to reduce SSI rates significantly, with appropriate cautions.4-7 Because of this, several countries have recently examined and reported their SSI experience.8-13 This issue of the Journal brings another article for consideration.14 This article describes the first year of the Dutch national surveillance of SSIs and risk factors. The results, while preliminary, show many of the same findings seen in other studies: ● There are multiple risk factors for SSIs. The Dutch study found age, preoperative length of stay, wound class, anesthesia score, and duration of surgery to be independently important risk factors for SSIs when all procedures were pooled together for analysis. ● Risk factors vary by procedure. The nature and relative importance of the risk factors differed when individual procedures were examined in the Dutch PREZIES (Preventie van Ziekenhuisinfecties door Surveillance [Prevention of Nosocomial Infections Through Surveillance]) Project. ● SSIs are very costly to the healthcare system. The Dutch study found an attributable increased length of stay of 8.2 days for patients with SSIs. In any nation, an additional week or so of hospitalization is expensive. It should not be surprising that so many countries are attempting to monitor this infection. However, the efforts of Geubbels and colleagues point out the difficulties with which all countries struggle in doing so. These include monitoring a national representation based upon a probability sampling of procedures; cooperation of hospitals and, in particular, surgeons; adequate sample size for certain surgical procedures; accuracy of data, especially with regard to postdischarge surveillance; and, ultimately, validity of comparisons with other SSI rates. Despite the difficulties, the Dutch study specifically points out the feasibility of such a surveillance system. The study also confirmed that many of the risk factors from the Basic SSI Risk Index used in the Centers for Disease Control and Prevention (CDC)’s National Nosocomial Infections Surveillance (NNIS) System were risk factors in The Netherlands. Further, there was close correlation of the 75th percentile of duration of surgery between the Dutch system and the NNIS system for similar group procedures. In general, if differences existed, they were minor, with the NNIS durations tending to be longer (Table). The differences may be due simply to smaller sample size and thus poorer estimates for the 75th percentiles in the PREZIES Network compared to the NNIS System; the distributions of the specific ICD-9 codes may have been different for the procedures (which are grouped codes in both systems); the actual measure of duration of surgery may have differed slightly between The Netherlands and the United States; or Dutch surgeons may have been slightly faster at operating. The reasons for the differences in duration of surgery are not any clearer than the reasons for differences in the SSI rates. Thus, even for the simplest of variables, duration of surgery, comparisons across surveillance systems are difficult; only where enormous differences occur can conclusions be drawn. For example, a comparison of surveillance systems for SSIs in Belgium and The Netherlands found an extraordinary difference in the use of antimicrobial prophylaxis for herniorrhaphies (3.7% in The Netherlands vs 41.9% in Belgium).15 This observation led directly to closer examination of antimicrobial prophylaxis in Belgium.16 More recently, at the 4th Decennial International Conference on Nosocomial and Healthcare-Associated