The rise of endovascular repair for abdominal, thoracoabdominal, and thoracic aortic aneurysms.

BACKGROUND: Given changes in intervention guidelines and the growing popularity of endovascular treatment for aortic aneurysms, we examined the trends in admissions and repairs of abdominal aortic aneurysms (AAAs), thoracoabdominal aortic aneurysms (TAAAs), and thoracic aortic aneurysms (TAAs). METHODS: We identified all patients admitted with ruptured aortic aneurysms and intact aortic aneurysms repaired in the Nationwide Inpatient Sample between 2004 and 2019. We then examined the use of open, endovascular, and complex endovascular repair (OAR, EVAR, and cEVAR) for each aortic aneurysm location (AAA, TAAA, and TAA), alongside their resulting in-hospital mortality, over time. cEVAR included branched, fenestrated, and physician-modified endografts. RESULTS: 715,570 patients were identified with AAA (87% intact repairs and 13% rupture admissions). Both intact AAA repairs and ruptured AAA admissions decreased significantly between 2004 and 2019 (intact 41,060-34,215, P < .01; ruptured 7175-4625, P = .02). Of all AAA repairs performed in a given year, the use of EVAR increased (2004-2019: intact 45%-66%, P < .01; ruptured 10%-55%, P < .01) as well as cEVAR (2010-2019: intact 0%-23%, P < .01; ruptured 0%-14%, P < .01). Mortality after EVAR of intact AAAs decreased significantly by 29% (2004-2019, 0.73%-0.52%, P < .01), whereas mortality after OAR increased significantly by 16% (2004-2019, 4.4%-5.1%, P < .01). In the study, 27,443 patients were identified with TAAA (80% intact and 20% ruptured). In the same period, intact TAAA repairs trended upward (2004-2019, 1435-1640, P = .055), and cEVAR became the most common approach (2004-2019, 3.8%-72%, P = .055). A total of 141,651 patients were identified with ascending, arch, or descending TAAs (90% intact and 10% ruptured). Intact TAA repairs increased significantly (2004-2019, 4380-10,855, P < .01). From 2017 to 2019, the mortality after OAR of descending TAAs increased and mortality after thoracic endovascular aneurysm repair decreased (2017-2019, OAR 1.6%-3.1%; thoracic endovascular aneurysm repair 5.2%-3.8%). CONCLUSIONS: Both intact AAA repairs and ruptured AAA admissions significantly decreased between 2004 and 2019. The use of endovascular techniques for the repair of all aortic aneurysm locations, both intact and ruptured, increased over the past two decades. Most recently in 2019, 89% of intact AAA repairs, infrarenal through suprarenal, were endovascular (EVAR or cEVAR, respectively). cEVAR alone increased to 23% of intact AAA repairs in 2019, from 0% a decade earlier. In this period of innovation, with many new options to repair aortic aneurysms while maintaining arterial branches, endovascular repair is now used for the majority of all intact aortic aneurysm repairs. Long-term data are needed to evaluate the durability of these procedures.

Parathyroidectomy and Cinacalcet Use in Medicare-Insured Kidney Transplant Recipients.

RATIONALE & OBJECTIVE: Posttransplant hyperparathyroidism is common, and treatment practices are poorly characterized. The goal of this study was to examine the incidence, associations, and outcomes of posttransplant parathyroidectomy and calcimimetic use in a cohort of Medicare-insured US kidney transplant recipients. STUDY DESIGN: Retrospective observational cohort study. SETTING & PARTICIPANTS: We used the US Renal Data System to extract demographic, clinical, and prescription data from Medicare Parts A, B, and D-insured patients who received their first kidney transplant in 2007-2013. We excluded patients with pretransplant parathyroidectomy. PREDICTORS: Calendar year of transplantation and pretransplant patient characteristics. OUTCOME: (1) Incidence of and secular trends in parathyroidectomy and cinacalcet use in the 3 years after transplant; (2) 90-day outcomes after posttransplant parathyroidectomy and cinacalcet initiation. ANALYTICAL APPROACH: Temporal trends and pretransplant correlates of parathyroidectomy and cinacalcet use were assessed using proportional hazards models and multivariable Poisson regression, respectively. RESULTS: The inclusion criteria were met by 30,127 patients, of whom 10,707 used cinacalcet before transplant, 551 underwent posttransplant parathyroidectomy, and 5,413 filled≥1 prescription for cinacalcet. The rate of posttransplant parathyroidectomy was stable over time. By contrast, cinacalcet use increased during the period studied. Long dialysis vintage and pretransplant cinacalcet use were strongly associated with posttransplant parathyroidectomy and cinacalcet use. Roughly 1 in 4 patients were hospitalized within 90 days of posttransplant parathyroidectomy, with hypocalcemia-related diagnoses being the most common complication. Parathyroidectomy (vs cinacalcet initiation) was not associated with an increase in acute kidney injury. LIMITATIONS: We lacked access to laboratory data to help assess the severity of secondary/tertiary hyperparathyroidism. The cohort was limited to Medicare beneficiaries. CONCLUSIONS: Almost one-fifth of our study cohort was treated with parathyroidectomy and/or cinacalcet. Further studies are needed to establish the optimal treatment for posttransplant hyperparathyroidism.

Assessing the risk of intentional self-harm in montelukast users: an updated Sentinel System analysis using ICD-10 coding.

BACKGROUND: Montelukast prescribing information includes a Boxed Warning issued in March 2020 regarding neuropsychiatric adverse events. A previous Sentinel System study of asthma patients from 2000 to 2015 did not demonstrate an increased risk of intentional self-harm measured using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, with montelukast compared to inhaled corticosteroids (ICS). METHODS: Using a new user cohort study design, we examined intentional self-harm events in patients aged 10 years and older who were incident users of either montelukast or ICS as monotherapy, with a diagnosis of asthma, between October 1, 2015, to June 30, 2022, in the Sentinel System. We measured intentional self-harm using ICD-10-CM codes, which may have better accuracy for capturing suicide attempts than ICD-9-CM codes. We used inverse probability of treatment weighting to balance baseline covariates. We performed subgroup analyses by age group, sex, psychiatric history, and pre/post Boxed Warning era and conducted sensitivity analyses varying type of care setting of the outcome and exposure episode gaps. RESULTS: Among 752,230 and 724,855 patients in the montelukast and ICS exposure groups respectively, we found no association between montelukast use and self-harm compared to ICS use [Hazard Ratio (95% Confidence Interval): 0.96 (0.85, 1.08)]. This finding was consistent across all subgroups, and sensitivity analyses. CONCLUSION: Our results cannot exclude other neuropsychiatric idiosyncratic reactions to montelukast. Compared to the previous Sentinel study, this study identified about double the rate of self-harm events, suggesting a greater sensitivity of ICD-10 codes for measuring self-harm than ICD-9.

Multimorbidity measures from health administrative data using ICD system codes: A systematic review.

BACKGROUND: We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification. METHODS: We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria. RESULTS: Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed. CONCLUSION: There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.

Environmental factors linked to hospital admissions in young children due to acute viral lower respiratory infections: A bidirectional case-crossover study.

OBJECTIVE: This study evaluated the association of the short-term exposure to environmental factors (relative humidity, temperature, NO2, SO2, O3, PM10, and CO) with hospital admissions due to acute viral lower respiratory infections (ALRI) in children under two years before the COVID-19 era. METHODS: We performed a bidirectional case-crossover study in 30,445 children with ALRI under two years of age in the Spanish Minimum Basic Data Set (MBDS) from 2013 to 2015. Environmental data were obtained from Spain's State Meteorological Agency (AEMET). The association was assessed by conditional logistic regression. RESULTS: Lower temperature one week before the day of the event (hospital admission) (q-value = 0.012) and higher relative humidity one week (q-value = 0.003) and two weeks (q-value<0.001) before the day of the event were related to a higher odds of hospital admissions. Higher NO2 levels two weeks before the event were associated with hospital admissions (q-value<0.001). Moreover, higher concentrations on the day of the event for SO2 (compared to lag time of 1-week (q-value = 0.026) and 2-weeks (q-value<0.001)), O3 (compared to lag time of 3-days (q-value<0.001), 1-week (q-value<0.001), and 2-weeks (q-value<0.001)), and PM10 (compared to lag time of 2-weeks (q-value<0.001)) were related to an increased odds of hospital admissions for viral ALRI. CONCLUSION: Short-term exposure to environmental factors (climatic conditions and ambient air contaminants) was linked to a higher likelihood of hospital admissions due to ALRI. Our findings emphasize the importance of monitoring environmental factors to assess the odds of ALRI hospital admissions and plan public health resources.

Neighborhood environmental factors linked to hospitalizations of older people for viral lower respiratory tract infections in Spain: a case-crossover study.

BACKGROUND: Lower respiratory tract viral infection (LRTI) is a significant cause of morbidity-mortality in older people worldwide. We analyzed the association between short-term exposure to environmental factors (climatic factors and outdoor air pollution) and hospital admissions with a viral LRTI diagnosis in older adults. METHODS: We conducted a bidirectional case-crossover study in 6367 patients over 65 years of age with viral LRTI and residential zip code in the Spanish Minimum Basic Data Set. Spain's State Meteorological Agency was the source of environmental data. Associations were assessed using conditional logistic regression. P-values were corrected for false discovery rate (q-values). RESULTS: Almost all were hospital emergency admissions (98.13%), 18.64% were admitted to the intensive care unit (ICU), and 7.44% died. The most frequent clinical discharge diagnosis was influenza (90.25%). LRTI hospital admissions were more frequent when there were lower values of temperature and O3 and higher values of relative humidity and NO2. The regression analysis adjusted by temperatures and relative humidity showed higher concentrations at the hospital admission for NO2 [compared to the lag time of 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)] and O3 [compared to the lag time of 3-days (q-value< 0.001), 1-week (q-value< 0.001), and 2-weeks (q-value< 0.001)] were related to a higher odds of hospital admissions due to viral LRTI. Moreover, higher concentrations of PM10 at the lag time of 1-week (q-value = 0.023) and 2-weeks (q-value = 0.002), and CO at the lag time of 3-days (q-value = 0.023), 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)], compared to the day of hospitalization, were related to a higher chances of hospital admissions with viral LRTI. CONCLUSION: Unfavorable environmental factors (low temperatures, high relative humidity, and high concentrations of NO2, O3, PM10, and CO) increased the odds of hospital admissions with viral LRTI among older people, indicating they are potentially vulnerable to these environmental factors.

Which ICD-9 codes were assigned for malignant mesothelioma in the mortality data in the United States before the ICD-10 was introduced?

BACKGROUND: Malignant mesothelioma (MM) is rare and fatal; survival in most cases is only about one year. Mortality rate is, therefore, a good proxy measure of incidence rate. However, the specific International Classification of Diseases (ICD) code for MM was not available until the Tenth Revision ICD (ICD-10). Little is known on which Ninth Revision ICD (ICD-9) codes were assigned for MM in the ICD-9 era. METHODS: We used a 1996 double-coded mortality file compiled by the National Center for Health Statistics to calculate the detection rate (DR) and confirmation rate (CR) of selected ICD-9 codes. RESULTS: Of 2386 decedents whose underlying cause of death was MM (ICD-10 code C45), the DR (deaths) of corresponding ICD-9 code was 57% (1365) for code 199 "malignant neoplasm without specification of site;" 19% (448) for code 162.9 "malignant neoplasm of trachea, bronchus, and lung, unspecified;" 13% (310) for code 163 "malignant neoplasm of pleura;" and 11% (271) for other codes. The CR (deaths) for the aforementioned three ICD-9 codes were 4.0% (1365/33,942), 0.3% (448/150,342), and 70.8% (310/438), respectively. CONCLUSIONS: The three ICD-9 codes (199, 162.9, and 163) were the most commonly used codes for MM and composed nine-tenths of all MM deaths in the years before the ICD-10 was introduced. Using only ICD-9 code 163, the code most often used as the surrogate measure of MM in mortality studies in the ICD-9 era, capture may have been only 13% of all MM deaths in the US, and the estimated number of MM deaths missed in 1996 would be 2086.

Effect of ICD-9-CM to ICD-10-CM coding system transition on identification of common conditions: An interrupted time series analysis.

PURPOSE: To evaluate the effect of diagnostic coding system transition on the identification of common conditions recorded in Taiwan's national claims database. METHODS: Using the National Health Insurance Research Database, we estimated the 3-month prevalence of recorded diagnosis of 32 conditions based on the ICD-9-CM codes in 2014-2015 and the ICD-10-CM codes in 2016-2017. Two algorithms were assessed for ICD-10-CM: validated ICD-10 codes in the literature and codes translated from ICD-9-CM using an established mapping algorithm. We used segmented regression analysis on time-series data to examine changes in the 3-month prevalence (both level and trend) before and after the ICD-10-CM implementation. RESULTS: Significant changes in the level were found in 19 and 11 conditions when using the ICD-10 codes from the literature and mapping algorithm, respectively. The conditions with inconsistent levels by both of the algorithms were valvular heart disease, peripheral vascular disease, mild liver disease, moderate to severe liver disease, metastatic cancer, rheumatoid arthritis and collagen vascular diseases, coagulopathy, blood loss anemia, deficiency anemia, alcohol abuse, and psychosis. Nine conditions had significant changes in the trend when using the ICD-10 codes from the literature or mapping algorithm. CONCLUSIONS: Less than half of the 32 conditions studied had a smooth transition between the ICD-9-CM and ICD-10-CM coding systems. Researchers should pay attention to the conditions where the coding definitions result in inconsistent time series estimates.

Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases-10 coding system: A brief review.

BACKGROUND AND PURPOSE: The transition from International Classification of Diseases, 9th revision, clinical modification (ICD-9-CM) to ICD-10-CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition. METHODS: We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD-9-CM and ICD-10-CM eras by visual inspection. RESULTS: We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time-series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD-9-CM and ICD-10-CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency. CONCLUSIONS: Researchers using ICD-10-CM algorithms obtained by standardized mappings from ICD-9-CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates. KEY POINTS: We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) and ICD-10-CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic). More than a third of the 140 time-series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence. Studies using ICD-9-CM-based algorithms mapped to ICD-10-CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.

Increasing Sepsis Rates in the United States: Results From National Inpatient Sample, 2005 to 2014.

OBJECTIVES: To examine the trends in hospitalization rates, mortality, and costs for sepsis during the years 2005 to 2014. METHODS: This was a retrospective serial cross-sectional analysis of patients ≥18 years admitted for sepsis in National Inpatient Sample. Trends in sepsis hospitalizations were estimated, and age- and sex-adjusted rates were calculated for the years 2005 to 2014. RESULTS: There were 541 694 sepsis admissions in 2005 and increased to 1 338 905 in 2014. Sepsis rates increased significantly from 1.2% to 2.7% during the years 2005 to 2014 (relative increase: 123.8%; P trend < .001). However, the relative increase changed by 105.8% (P trend < .001) after adjusting for age and sex and maintained significance. Although total cost of hospitalization due to sepsis increased significantly from US$22.2 to US$38.1 billion (P trend < .001), the mean hospitalization cost decreased significantly from US$46,470 to US$29,290 (P trend < .001). CONCLUSIONS: Hospitalizations for sepsis increased during the years 2005 to 2014. Our study paradoxically found declining rates of in-hospital mortality, length of stay, and mean hospitalization cost for sepsis. These findings could be due to biases introduced by International Classification of Diseases, Ninth Revision, Clinical Modification coding rules and increased readmission rates or alternatively due to increased awareness and surveillance and changing disposition status. Standardized epidemiologic registries should be developed to overcome these biases.

The recording and prevalence of Inflammatory bowel disease in girls' primary care medical Spanish records.

PURPOSE: Inflammatory bowel disease (IBD) recording validation among girls in the Spanish Primary Care Database For Pharmacoepidemiological Research (BIFAP). METHODS: In this observational study, girls aged 9 to 18 years registered in BIFAP between 2002 and 2016, were followed up until there was a recorded IBD diagnosis or a referral to specialist indicating IBD. Anonymized profiles were reviewed to retrieve diagnosis confirmation (a positive colonoscopy or biopsy, specialist, or physician's comments mentioning the IBD diagnosis) or discarding (negative procedure results, alternative diagnosis, or family history). "possible" IBD were profiles missing that evidence, or had suspected IBD. The prescriptions of intestinal anti-inflammatory agents, azatioprine, and mercaptopurine were collected. The prevalence of IBD was estimated after review. RESULTS: Out of 480 634 girls, 323 had a first ever recorded IBD, of which, 37.8% (N = 122) were "confirmed" incident IBD diagnosis, 19.8% (N = 64) discarded and 38.7% (N = 125) "possible" IBD. Additionally, 12 IBD records (3.7%) referred to prevalent IBD. Prescriptions were recorded in 94.3% (confirmed), 63.2% (possible), 83.3% (prevalent), and 3.1% (discarded) IBD cases. Prevalence was 52.83 "confirmed" or 93.58/105 girls when "possible" IBD were added. CONCLUSIONS: For a third of the girls, the first recorded IBD included evidence confirming the diagnosis while most of those with missing evidence had treatment indicated for IBD. For research focused in sensitivity, an algorithm including "possible" plus "confirmed" episodes is recommended, whereas only "confirmed" to guarantee higher predictive value. Prevalence suggests that IBD is not a rare disease among girls.

Environmental factors are associated with hospital admissions for sepsis-related pneumonia: A bidirectional case-crossover design.

OBJECTIVE: Pneumonia is a common cause of morbidity and sepsis worldwide, mainly in the elderly. We evaluated the impact of short-term exposure to environmental factors on hospital admissions for sepsis-related pneumonia in a nationwide study in Spain. METHODS: We conducted a bidirectional case-crossover study in patients who had sepsis-related pneumonia in 2013. Data were obtained from the Minimum Basic Data Set (MBDS) and the State Meteorological Agency (AEMET) of Spain. Conditional logistic regressions were used to evaluate the association between environmental factors (temperature, relative humidity, NO2, SO2, O3, PM10, and CO) and hospital admissions with sepsis-related pneumonia. RESULTS: A total of 3,262,758 hospital admissions were recorded in the MBDS, of which, 253,467 were patients with sepsis. Among those, 67,443 had sepsis-related pneumonia and zip code information. We found inverse associations [adjusted odds ratio (aOR) values < 1] between short-term exposure to temperature and hospital admissions for sepsis-related pneumonia. Moreover, short-term exposure to higher levels of relative humidity, NO2, SO2, O3, PM10, and CO were directly associated (aOR values > 1) with a higher risk of hospital admissions for sepsis-related pneumonia. Overall, the impact of environmental factors was more prominent with increasing age, mainly among the elderly aged 65 or over. CONCLUSION: Short-term exposure to environmental factors (temperature, relative humidity, NO2, SO2, O3, CO, and PM10) was associated with a higher risk of hospital admissions for sepsis-related pneumonia. Our findings support the role of environmental factors in monitoring the risk of hospital admissions for sepsis-related pneumonia and can help plan and prepare public health resources.

Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data.

BACKGROUND: Quantifying the burden of multimorbidity for healthcare research using administrative data has been constrained. Existing measures incompletely capture chronic conditions of relevance and are narrowly focused on risk-adjustment for mortality, healthcare cost or utilization. Moreover, the measures have not undergone a rigorous review for how accurately the components, specifically the International Classification of Diseases, Ninth Revision (ICD-9) codes, represent the chronic conditions that comprise the measures. We performed a comprehensive, structured literature review of research studies on the accuracy of ICD-9 codes validated using external sources across an inventory of 81 chronic conditions. The conditions as a weighted measure set have previously been demonstrated to impact not only mortality but also physical and mental health-related quality of life. METHODS: For each of 81 conditions we performed a structured literature search with the goal to identify 1) studies that externally validate ICD-9 codes mapped to each chronic condition against an external source of data, and 2) the accuracy of ICD-9 codes reported in the identified validation studies. The primary measure of accuracy was the positive predictive value (PPV). We also reported negative predictive value (NPV), sensitivity, specificity, and kappa statistics when available. We searched PubMed and Google Scholar for studies published before June 2019. RESULTS: We identified studies with validation statistics of ICD-9 codes for 51 (64%) of 81 conditions. Most of the studies (47/51 or 92%) used medical chart review as the external reference standard. Of the validated using medical chart review, the median (range) of mean PPVs was 85% (39-100%) and NPVs was 91% (41-100%). Most conditions had at least one validation study reporting PPV ≥70%. CONCLUSIONS: To help facilitate the use of patient-centered measures of multimorbidity in administrative data, this review provides the accuracy of ICD-9 codes for chronic conditions that impact a universally valued patient-centered outcome: health-related quality of life. These findings will assist health services studies that measure chronic disease burden and risk-adjust for comorbidity and multimorbidity using patient-centered outcomes in administrative data.

Does state malpractice environment affect outcomes following spinal fusions? A robust statistical and machine learning analysis of 549,775 discharges following spinal fusion surgery in the United States.

OBJECTIVE: Spine surgery is especially susceptible to malpractice claims. Critics of the US medical liability system argue that it drives up costs, whereas proponents argue it deters negligence. Here, the authors study the relationship between malpractice claim density and outcomes. METHODS: The following methods were used: 1) the National Practitioner Data Bank was used to determine the number of malpractice claims per 100 physicians, by state, between 2005 and 2010; 2) the Nationwide Inpatient Sample was queried for spinal fusion patients; and 3) the Area Resource File was queried to determine the density of physicians, by state. States were categorized into 4 quartiles regarding the frequency of malpractice claims per 100 physicians. To evaluate the association between malpractice claims and death, discharge disposition, length of stay (LOS), and total costs, an inverse-probability-weighted regression-adjustment estimator was used. The authors controlled for patient and hospital characteristics. Covariates were used to train machine learning models to predict death, discharge disposition not to home, LOS, and total costs. RESULTS: Overall, 549,775 discharges following spinal fusions were identified, with 495,640 yielding state-level information about medical malpractice claim frequency per 100 physicians. Of these, 124,425 (25.1%), 132,613 (26.8%), 130,929 (26.4%), and 107,673 (21.7%) were from the lowest, second-lowest, second-highest, and highest quartile states, respectively, for malpractice claims per 100 physicians. Compared to the states with the fewest claims (lowest quartile), surgeries in states with the most claims (highest quartile) showed a statistically significantly higher odds of a nonhome discharge (OR 1.169, 95% CI 1.139-1.200), longer LOS (mean difference 0.304, 95% CI 0.256-0.352), and higher total charges (mean difference [log scale] 0.288, 95% CI 0.281-0.295) with no significant associations for mortality. For the machine learning models-which included medical malpractice claim density as a covariate-the areas under the curve for death and discharge disposition were 0.94 and 0.87, and the R2 values for LOS and total charge were 0.55 and 0.60, respectively. CONCLUSIONS: Spinal fusion procedures from states with a higher frequency of malpractice claims were associated with an increased odds of nonhome discharge, longer LOS, and higher total charges. This suggests that medicolegal climate may potentially alter practice patterns for a given spine surgeon and may have important implications for medical liability reform. Machine learning models that included medical malpractice claim density as a feature were satisfactory in prediction and may be helpful for patients, surgeons, hospitals, and payers.

Derivation and validation of a computable phenotype for acute decompensated heart failure in hospitalized patients.

BACKGROUND: With higher adoption of electronic health records at health-care centers, electronic search algorithms (computable phenotype) for identifying acute decompensated heart failure (ADHF) among hospitalized patients can be an invaluable tool to enhance data abstraction accuracy and efficacy in order to improve clinical research accrual and patient centered outcomes. We aimed to derive and validate a computable phenotype for ADHF in hospitalized patients. METHODS: We screened 256, 443 eligible (age > 18 years and with prior research authorization) individuals who were admitted to Mayo Clinic Hospital in Rochester, MN, from January 1, 2006, through December 31, 2014. Using a randomly selected derivation cohort of 938 patients, several iterations of a free-text electronic search were developed and refined. The computable phenotype was subsequently validated in an independent cohort 100 patients. The sensitivity and specificity of the computable phenotype were compared to the gold standard (expert review of charts) and International Classification of Diseases-9 (ICD-9) codes for Acute Heart Failure. RESULTS: In the derivation cohort, the computable phenotype achieved a sensitivity of 97.5%, and specificity of 100%, whereas ICD-9 codes for Acute Heart Failure achieved a sensitivity of 47.5% and specificity of 96.7%. When all Heart Failure codes (ICD-9) were used, sensitivity and specificity were 97.5 and 86.6%, respectively. In the validation cohort, the sensitivity and specificity of the computable phenotype were 100 and 98.5%. The sensitivity and specificity for the ICD-9 codes (Acute Heart Failure) were 42 and 98.5%. Upon use of all Heart Failure codes (ICD-9), sensitivity and specificity were 96.8 and 91.3%. CONCLUSIONS: Our results suggest that using computable phenotype to ascertain ADHF from the clinical notes contained within the electronic medical record are feasible and reliable. Our computable phenotype outperformed ICD-9 codes for the detection of ADHF.

Birth defects in Taiwan: A 10-year nationwide population-based, cohort study.

BACKGROUND/PURPOSE: Birth defects (BDs) are main causes of mortality and disability in infants and children. The aims of this study were to analyze the prevalence, types and risk factors of BDs in Taiwan. METHODS: Data of all births (including live and stillbirths), types, characteristics, and associated risk factors of BDs were obtained from the National Birth Registry and National Health Insurance Research Data base in Taiwan between 2005 and 2014. Birth defects were coded according to International Classification of Diseases 9th Revision-Clinical Modification codes 740-759. RESULTS: A total of 55,299 infants were diagnosed as having BDs among 2,033,004 births. The prevalence of BDs was 271.66 per 10,000 births. The prevalence of BDs did not change significantly between 2005 and 2014, there was a higher birth rate and lower BDs in 2012 (year of dragon) in Taiwan. The most common type of BDs was cardiovascular abnormalities, and ventricular septal defect was the most common disease. Extreme maternal age (<18 years or ≧30 years), preterm, and low birth weight were associated with BDs. Maternal diseases associated with BDs included hypertension, cardiovascular diseases, renal diseases, genitourinary infections, anemia, mental disorders, and diabetes mellitus. CONCLUSION: The prevalence of BDs was 271.66 per 10,000 births. The most common types of BDs were cardiovascular abnormalities. If we can reduce maternal chronic diseases, we will decrease the prevalence of BDs.

The Inaccuracy of ICD-10 Coding in Revision Total Hip Arthroplasty and Its Implication on Revision Data.

BACKGROUND: The International Statistical Classification of Diseases, 10th Revision (ICD-10), was adopted by the United States on October 1, 2015 and expanded coding from 3800 codes with the International Statistical Classification of Diseases, Ninth Revision, procedure code system (ICD-9-PCS) to 73,000. The increase in number of codes was designed to create more accurate representations of procedures like revision total hip arthroplasties (rTHAs). However, many worry that the increased complexity leads to more inaccurate coding. The purpose of this study is to determine the accuracy of ICD-10-PCS coding for rTHA and discuss the implications on registry data. METHODS: The rTHA databases at 2 large, academic medical centers were retrospectively reviewed for all rTHAs between October 1, 2015 and July 3, 2019. The laterality and specific revised components were recorded and compared with the ICD-10-PCS codes used for each procedure. The accuracy of ICD-10-PCS codes relative to the surgical record was determined using coding guidelines published by the American Joint Replacement Registry (AJRR). RESULTS: Overall, 895 cases were reviewed. Replacement coding was 22% accurate (195 of 895). For removal and replacement coding, accuracy dropped to 17% (152 of 895). All procedures had at least 1 rTHA trigger code that would signify correctly to AJRR that an rTHA occurred. CONCLUSION: In this study, the percent of correctly coded rTHA was low. All rTHA procedures had at least 1 AJRR trigger code; therefore, an rTHA would have been appropriately captured by AJRR. But these inaccuracies should make one pause when using ICD-10-PCS procedural data to try to evaluate specific rTHA details from administrative claims databases and ward against expanding ICD-10-PCS as a means to collect implant survival and registry data.

Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records.

The International Statistical Classification of Disease and Related Health Problems (ICD) is an international standard system for categorizing and reporting diseases, injuries, disorders, and health conditions. Most previously-proposed disease predicting systems need clinical information collected by the medical staff from the patients in hospitals. In this paper, we propose a deep learning algorithm to classify disease types and identify diagnostic codes by using only the subjective component of progress notes in medical records. In this study, we have a dataset, consisting of about one hundred and sixty-eight thousand medical records, from a medical center, collected during 2003 and 2017. First, we apply standard text processing procedures to parse the sentences and word embedding techniques for vector representations. Next, we build a convolution neural network model on the medical records to predict the ICD-9 code by using a subjective component of the progress note. The prediction performance is evaluated by ten-fold cross-validation and yields an accuracy of 0.409, recall of 0.409 and precision of 0.436. If we only consider the "chapter match" of ICD-9 code, our model achieves an accuracy of 0.580, recall of 0.580, and precision of 0.582. Since our diagnostic code prediction model is solely based on subjective components (mainly, patients' self-report descriptions), the proposed approach could serve as a remote and self-diagnosis assistance tool, prior to seeking medical advice or going to the hospital. In addition, our work may be used as a primary evaluation tool for discomfort in the rural area where medical resources are restricted.

A comparison of reintervention rates after endovascular aneurysm repair between the Vascular Quality Initiative registry, Medicare claims, and chart review.

OBJECTIVE: The accurate measurement of reintervention after endovascular aneurysm repair (EVAR) is critical during postoperative surveillance. The purpose of this study was to compare reintervention rates after EVAR from three different data sources: the Vascular Quality Initiative (VQI) alone, VQI linked to Medicare claims (VQI-Medicare), and a "gold standard" of clinical chart review supplemented with telephone interviews. METHODS: We reviewed the medical records of 729 patients who underwent EVAR at our institution between 2003 and 2013. We excluded patients without follow-up reported to the VQI (n = 68 [9%]) or without Medicare claims information (n = 114 [16%]). All patients in the final analytic cohort (n = 547) had follow-up information available from all three data sources (VQI alone, VQI linked to Medicare, and chart review). We then compared reintervention rates between the three data sources. Our primary end points were the agreement between the three data sources and the Kaplan-Meier estimated rate of reintervention at 1 year, 2 years, and 3 years after EVAR. For gold standard assessment, we supplemented chart review with telephone interview as necessary to assess reintervention. RESULTS: VQI data alone identified 12 reintervention events in the first year after EVAR. Chart review confirmed all 12 events and identified 18 additional events not captured by the VQI. VQI-Medicare data successfully identified all 30 of these events within the first year. VQI-Medicare also documented four reinterventions in this time period that did not occur on the basis of patient interview (4/547 [0.7%]). The agreement between chart review and VQI-Medicare data at 1 year was excellent (κ = 0.93). At 3 years, there were 81 (18%) reinterventions detected by VQI-Medicare and 70 (16%) detected by chart review for a sensitivity of 92%, specificity of 96%, and κ of 0.80. Kaplan-Meier survival analysis demonstrated similar reintervention rates after 3 years between VQI-Medicare and chart review (log-rank, P = .59). CONCLUSIONS: Chart review after EVAR demonstrated a 6% 1-year and 16% 3-year reintervention rate, and almost all (92%) of these events were accurately captured using VQI-Medicare data. Linking VQI data with Medicare claims allows an accurate assessment of reintervention rates after EVAR without labor-intensive physician chart review.

Validating an algorithm for multiple myeloma based on administrative data using a SEER tumor registry and medical record review.

PURPOSE: Large numbers of multiple myeloma patients can be studied in real-world clinical settings using administrative databases. The validity of these studies is contingent upon accurate case identification. Our objective was to develop and evaluate algorithms to use with administrative data to identify multiple myeloma cases. METHODS: Patients aged ≥18 years with ≥1 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for multiple myeloma (203.0x) were identified at two study sites. At site 1, several algorithms were developed and validated by comparing results to tumor registry cases. An algorithm with a reasonable positive predictive value (PPV) (0.81) and sensitivity (0.73) was selected and then validated at site 2 where results were compared with medical chart data. The algorithm required that ICD-9-CM codes 203.0x occur before and after the diagnostic procedure codes for multiple myeloma. RESULTS: At site 1, we identified 1432 patients. The PPVs of algorithms tested ranged from 0.54 to 0.88. Sensitivities ranged from 0.30 to 0.88. At site 2, a random sample (n = 400) was selected from 3866 patients, and medical charts were reviewed by a clinician for 105 patients. Algorithm PPV was 0.86 (95% CI, 0.79-0.92). CONCLUSIONS: We identified cases of multiple myeloma with adequate validity for claims database analyses. At least two ICD-9-CM diagnosis codes 203.0x preceding diagnostic procedure codes for multiple myeloma followed by ICD-9-CM codes within a specific time window after diagnostic procedure codes were required to achieve reasonable algorithm performance.