Age- and height-dependent bias of underweight and overweight assessment standards for children and adolescents.

Background: Precision in evaluating underweight and overweight status among children and adolescents is paramount for averting health and developmental issues. Existing standards for these assessments have faced scrutiny regarding their validity. This study investigates the age and height dependencies within the international standards set by the International Obesity Task Force (IOTF), relying on body mass index (BMI), and contrasts them with Japanese standards utilizing the percentage of overweight (POW). Method: We scrutinized a comprehensive database comprising 7,863,520 children aged 5-17 years, sourced from the School Health Statistics Research initiative conducted by Japan's Ministry of Education, Culture, Sports, Science, and Technology. Employing the quantile regression method, we dissected the structure of weight-for-height distributions across different ages and sexes, quantifying the potentially biased assessments of underweight and overweight status by conventional criteria. Results: Applying IOFT criteria for underweight assessment revealed pronounced height dependence in males aged 11-13 and females aged 10-11. Notably, a discernible bias emerged, wherein children in the lower 25th percentile were classified as underweight five times more frequently than those in the upper 25th percentile. Similarly, the overweight assessment displayed robust height dependence in males aged 8-11 and females aged 7-10, with children in the lower 25th percentile for height deemed obese four or five times more frequently than their counterparts in the upper 25th percentile. Furthermore, using the Japanese POW criteria for assessment revealed significant age dependence in addition to considerably underestimating the percentage of underweight and overweight cases under the age of seven. However, the height dependence for the POW criterion was smaller than the BMI criterion, and the difference between height classes was less than 3-fold. Conclusion: Our findings underscore the intricacies of age-dependent changes in body composition during the growth process in children, emphasizing the absence of gold standards for assessing underweight and overweight. Careful judgment is crucial in cases of short or tall stature at the same age, surpassing sole reliance on conventional criteria results.

The Association Between Metformin Use and New-Onset ICD Coding of Geographic Atrophy.

Purpose: Metformin has been suggested to protect against the development of age-related macular degeneration (AMD) in multiple observational studies. However, the association between metformin and geographic atrophy (GA), a debilitating subtype of AMD, has not been analyzed. Methods: We conducted a case-control study of patients ages 60 years and older with new-onset International Classification of Diseases (ICD) coding of GA in the Merative MarketScan Commercial and Medicare Databases between 2017 and 2021. Cases were matched with propensity scores estimated by age, region, hypertension, and Charlson Comorbidity Index to a control without GA of the same year. Exposure to metformin was assessed for cases and controls in the year prior to their index visit. Conditional multivariable logistic regression, adjusting for AMD risk factors, was used to calculate odd ratios and 95% confidence intervals (CIs). This study design and analysis were repeated in a sample of patients without diabetes. Results: In the full sample, we identified 10,505 cases with GA and 10,502 matched controls without GA. In total, 1149 (10.9%) cases and 1277 (12.2%) controls were exposed to metformin, and in multivariable regression, metformin decreased the odds of new-onset ICD coding of GA by 12% (95% CI, 0.79-0.99). In the sample of patients without diabetes, we identified 7611 cases with GA and 7608 matched controls without GA. Twenty-nine (0.4%) cases and 63 (0.8%) controls were exposed to metformin, and in multivariable regression, metformin decreased the odds of new-onset ICD coding of GA by 47% (95% CI, 0.33-0.83). Conclusions: Metformin may hold promise as a noninvasive, alternative agent to prevent the development of GA. This finding is notable due to shortcomings in recently approved therapeutics for GA and metformin's overall ease of use and few adverse effects. Additional studies are required to explore our findings further and motivate a clinical trial.

Feasibility of extracting cancer stage and metastasis codes from health insurance claims of outpatients and expressibility in ICD-11: a cross-sectional study using national health insurance data from South Korea.

OBJECTIVES: This study aimed to evaluate the incidence of health insurance claims recording the cancer stage and TNM codes representing tumor extension size (T), lymph node metastasis (N), and distant metastasis (M) for patients diagnosed with cancer and to determine whether this extracted data could be applied to the new ICD-11 codes. DESIGN: A cross-sectional study design was used, with the units of analysis as individual outpatients. Two dependent variables were extraction feasibility of cancer stage and TNM metastasis information from each claim. Expressibility of the two variables in ICD-11 was descriptively analysed. SETTING AND PARTICIPANTS: The study was conducted in South Korea and study participants were outpatients: lung cancer (LC) (46616), stomach cancer (SC) (50103) and colorectal cancer (CC) (54707). The data set consisted of the first health insurance claim of each patient visiting a hospital from 1 July to 31 December 2021. RESULTS: The absolute extraction success rates for cancer stage based on claims with cancer stage was 33.3%. The rates for stage for LC, SC and CC were 30.1%, 35.5% and 34.0%, respectively. The rate for TNM was 11.0%. The relative extraction success rates for stage compared with that for CC (the reference group) were lower for patients with LC (adjusted OR (aOR), 0.803; 95% CI 0.782 to 0.825; p<0.0001) but higher for SC (aOR 1.073; 95% CI 1.046 to 1.101; p<0.0001). The rates of TNM compared that for CC were 40.7% lower for LC (aOR, 0.593; 95% CI 0.569 to 0.617; p<0.0001) and 43.0% lower for SC (aOR 0.570; 95% CI 0.548 to 0.593; p<0.0001). There were limits to expressibility in ICD-11 regarding the detailed cancer stage and TNM metastasis codes. CONCLUSION: Extracting cancer stage and TNM codes from health insurance claims were feasible, but expressibility in ICD-11 codes was limited. WHO may need to create specific cancer stage and TNM extension codes for ICD-11 due to the absence of current rules in ICD-11.

Validation of an international classification of disease, tenth revision, clinical modification (ICD-10-CM) algorithm in identifying severe hypoglycaemia events for real-world studies.

AIM: The transition to the ICD-10-CM coding system has reduced the utility of hypoglycaemia algorithms based on ICD-9-CM diagnosis codes in real-world studies of antidiabetic drugs. We mapped a validated ICD-9-CM hypoglycaemia algorithm to ICD-10-CM codes to create an ICD-10-CM hypoglycaemia algorithm and assessed its performance in identifying severe hypoglycaemia. MATERIALS AND METHODS: We assembled a cohort of Medicare patients with DM and linked electronic health record (EHR) data to the University of North Carolina Health System and identified candidate severe hypoglycaemia events from their Medicare claims using the ICD-10-CM hypoglycaemia algorithm. We confirmed severe hypoglycaemia by EHR review and computed a positive predictive value (PPV) of the algorithm to assess its performance. We refined the algorithm by removing poor performing codes (PPV ≤0.5) and computed a Cohen's κ statistic to evaluate the agreement of the EHR reviews. RESULTS: The algorithm identified 642 candidate severe hypoglycaemia events, and we confirmed 455 as true severe hypoglycaemia events, PPV of 0.709 (95% confidence interval: 0.672, 0.744). When we refined the algorithm, the PPV increased to 0.893 (0.862, 0.918) and missed <2.42% (<11) true severe hypoglycaemia events. Agreement between reviewers was high, κ = 0.93 (0.89, 0.97). CONCLUSIONS: We translated an ICD-9-CM hypoglycaemia algorithm to an ICD-10-CM version and found its performance was modest. The performance of the algorithm improved by removing poor performing codes at the trade-off of missing very few severe hypoglycaemia events. The algorithm has the potential to be used to identify severe hypoglycaemia in real-world studies of antidiabetic drugs.

Distribution and frequency of clinical criteria and rating scales for diagnosis and assessment of catatonia in different study types.

BACKGROUND: A comprehensive assessment of catatonic symptoms is decisive for diagnosis, neuronal correlates, and evaluation of treatment response and prognosis of catatonia. Studies conducted so far used different cut-off criteria and clinical rating scales to assess catatonia. Therefore, the main aim of this study was to examine the frequency and distribution of diagnostic criteria and clinical rating scales for assessing catatonia that were used in scientific studies so far. METHODS: We conducted a systematic review using PubMed searching for articles using catatonia rating scales/criteria published from January 1st 1952 (introduction of catatonic schizophrenia to first edition of the Diagnostic and Statistical Manual of Mental Disorders [DSM]) up to December 5th, 2022. RESULTS: 1928 articles were considered for analysis. 1762 (91,39 %) studies used one and 166 (8,61 %) used ≥2 definitions of catatonia. However, 979 (50,7 %) articles did not report any systematic assessment of catatonia. As for clinical criteria, DSM criteria were used by the majority of studies (n = 290; 14.0 %), followed by International Classification of Diseases (ICD) criteria (n = 61; 2.9 %). The Bush-Francis Catatonia Rating Scale (BFCRS) was found to be by far the most frequently utilized scale (n = 464; 22.4 % in the respective years), followed by Northoff Catatonia Rating Scale (NCRS) (n = 31; 1.5 % in the respective years). CONCLUSION: DSM and ICD criteria as well as BFCRS and NCRS were most frequently utilized and can therefore be recommended as valid instruments for the assessment of catatonia symptomatology.

National patterns in the use of International Statistical Classification of Diseases and Health Related Problems, tenth revision Z codes in ambulatory surgery from 2016 to 2019.

BACKGROUND: In the tenth revision of the International Statistical Classification of Disease and Health Related Problems (ICD-10), Z codes were added to improve documentation and understanding of health-related social needs. We estimated national Z code use in the ambulatory surgery setting from 2016 to 2019. METHODS: Using the Nationwide Ambulatory Surgery Sample (NASS), we identified encounters for ambulatory surgery with an ICD-10 code between Z55.0 and Z65.9. Data were stratified by Z code domains from the Centers for Medicare and Medicaid Services (CMS). RESULTS: This analysis of 41,827 ambulatory surgery encounters with documented Z codes found that the most documented determinants of health related to multiparity or unwanted pregnancy, homelessness, and incarceration. There was a 16.1% increase in the use of Z codes from 2016 to 2019. CONCLUSION: Rates of Z code use in the ambulatory surgery setting are increasing with current documentation serving as a specific but not sensitive measure of socioeconomic need.

Trends in Neonatal Opioid Withdrawal Syndrome and Opioid Exposure Diagnoses Among Infants With Private Health Insurance, 2016-2021: Introduction of the P04.14 ICD-10-CM Code.

OBJECTIVE: The opioid epidemic has led to a surge in diagnoses of neonatal opioid withdrawal syndrome (NOWS). Many states track the incidence of NOWS by using the P96.1 International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code for "neonatal withdrawal symptoms from maternal use of drugs of addiction." In October 2018, an ICD-10-CM code for neonatal opioid exposure (P04.14) was introduced. This code can be used when an infant is exposed to opioids in utero but does not have clinically significant withdrawal symptoms. We analyzed the effect of the P04.14 code on the incidence rate of NOWS (P96.1) and "other" neonatal drug exposure diagnoses (P04.49). METHODS: We used private health insurance data collected for infants in the United States from the first quarter of 2016 through the third quarter of 2021 to describe incidence rates for each code over time and examine absolute and percentage changes before and after the introduction of code P04.14. RESULTS: The exclusive use of code P96.1 declined from an incidence rate per 1000 births of 1.08 in 2016-2018 to 0.70 in 2019-2021, a -35.7% (95% CI, -47.6% to -23.8%) reduction. Use of code P04.49 only declined from an incidence rate of 2.34 in 2016-2018 to 1.64 in 2019-2021, a -30.0% (95% CI, -36.4% to -23.7%) reduction. Use of multiple codes during the course of treatment increased from an average incidence per 1000 births of 0.56 in 2016-2018 to 0.79 in 2019-2021, a 45.5% (95% CI, 24.8%-66.1%) increase. CONCLUSION: The introduction of ICD-10-CM code P04.14 altered the use of other neonatal opioid exposure codes. The use of multiple codes increased, indicating that some ambiguity may exist about which ICD-10-CM code is most appropriate for a given set of symptoms.

Validation of an ICD-10 case-finding algorithm for endometrial cancer in US insurance claims.

PURPOSE: To evaluate the positive predictive value (PPV) of an endometrial cancer case finding algorithm using International Classification of Disease 10th revision Clinical Modification (ICD-10-CM) diagnosis codes from US insurance claims for implementation in a planned post-marketing safety study. Two algorithm variants were evaluated. METHODS: Provisional incident endometrial cancer cases were identified from 2016 through 2020 among women aged ≥50 years. One algorithm variant used diagnosis codes for malignant neoplasms of uterine sites (C54.x), excluding C54.2 (malignant neoplasm of myometrium); the other used only C54.1 (malignant neoplasm of endometrium). A random sample of medical records of recent incident provisional cases (2018-2020) was requested for adjudication. Confirmed cases showed biopsy evidence of endometrial cancer, documentation of cancer staging, or hysterectomy following diagnosis. We estimated the PPV of the variants with 95% confidence intervals (CI) excluding cases that had insufficient information. RESULTS: Of 294 provisional cases adjudicated, 85% were from outpatient settings (n = 249). Mean age at diagnosis was 69.3 years. Among the 294 adjudicated cases (identified with the broader algorithm variant), the same 223 were confirmed endometrial cancer cases by both algorithm variants. The PPV (95% CI) for the broader algorithm variant was 84.2% (79.2% and 88.3%), and for the variant using only C54.1 was 85.8% (80.9% and 89.8%). CONCLUSION: We developed and validated an algorithm using ICD-10-CM diagnosis codes to identify endometrial cancer cases in health insurance claims with a sufficiently high PPV to use in a planned post-marketing safety study.

Association of ICD-10 Clinical Modification Codes for Social Determinants of Health with Surgical Outcomes and Hospital Charges Among Cancer Patients.

INTRODUCTION: We sought to characterize the impact of social determinants of health (SDOH)-related codes on outcomes among patients with a cancer diagnosis. METHODS: Patients diagnosed with lung, pancreas, colon, or rectal cancer between 2017 and 2020 were identified in the California Department of Healthcare Access and Information Patient Discharge Database. Data on concomitant SDOH-related codes (International Classification of Diseases, Tenth Revision [ICD-10] Z55-Z65) designating health hazards related to socioeconomic and psychosocial circumstances were obtained. The association of these SDOH codes with postoperative outcomes was evaluated. RESULTS: Among 10,421 patients who underwent an operation from 2017 to 2020, median age was 66 years (interquartile range [IQR] 56-75) and nearly half of the cohort was male (n = 551,252.9%). In total, 102 (1%) patients had a concurrent ICD-10 SDOH diagnosis. After controlling for competing risk factors, the risk-adjusted probability of in-hospital death was 4.1% (95% confidence interval [CI] 1.0-7.2) among patients with an SDOH diagnosis compared with 2.9% (95% CI 2.5-3.2) among patients without an SDOH diagnosis (odds ratio [OR] 1.52, 95% CI 0.63-3.66; p = 0.258); postoperative complications were 27.0% (95% CI 20.0-34.1) compared with 24.9% (95% CI 24.1-25.6) among patients without an SDOH diagnosis (OR 1.15, 95% CI 0.73-1.82; p = 0.141), and length of stay was 10.6 days (95% CI 10.0-11.2) compared with 9.4 days (95% CI 9.3-9.5) among patients without an SDOH diagnosis. Patients with an SDOH diagnosis had a 5.19 (95% CI 3.23-8.34; p < 0.005) higher odds of being discharged to a skilled nursing facility versus patients without an SDOH diagnosis. CONCLUSION: Uptake and utilization of ICD-10 SDOH was 1% among California patients with lung, pancreas, colon, or rectal cancer. Patients with a concomitant ICD-10 SDOH code had longer length of stay and had higher odds of being discharged to a skilled nursing facility.

Association of social determinants of health International Classification of Disease, Tenth Edition clinical modification codes with outcomes for emergency general surgery and trauma admissions.

BACKGROUND: Patients with Acute Care Surgery needs (ie, emergency general surgery diagnosis or trauma admission) are at particularly high risk for nonmedical patient-related factors that can be important drivers of healthcare outcomes. These social determinants of health are typically ascertained at the geographic area level (ie, county or neighborhood) rather than at the individual patient level. Recently, the International Classification of Diseases Tenth Revision, Tenth Edition created codes to capture health hazards related to patient socioeconomic and psychosocial circumstances. We sought to characterize the impact of these social determinants of health-related codes on perioperative outcomes among patients with acute care surgery needs. METHODS: Patients diagnosed between 2017 and 2020 with acute care surgery needs (ie, emergency general surgery diagnosis or a trauma admission) were identified in the California Department of Healthcare Access and information Patient Discharge database. Data on concomitant social determinants of health-related codes (International Classification of Diseases Tenth Revision, Tenth Edition Z55-Z65), which designated health hazards related to socioeconomic and psychosocial (socioeconomic and psychosocial, respectively) circumstances, were obtained. After controlling for patient factors, including age, sex, race, payer type, and admitting hospital, the association of socioeconomic and psychosocial codes with perioperative outcomes and hospital disposition was analyzed. RESULTS: Among 483,280 with an acute care surgery admission (emergency general surgery: n = 289,530, 59.9%; trauma: n = 193,705, 40.1%) mean age was 56.5 years (standard deviation: 21.5) and 271,911 (56.3%) individuals were male. Overall, 16,263 (3.4%) patients had a concomitant socioeconomic and psychosocial diagnosis code. The percentage of patients with a concurrent social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis increased throughout the study period from 2.6% in 2017 to 4.4% in 2020. Patients that were male (odds ratio 1.89; 95% confidence interval 1.82, 1.96), insured by Medicaid (odds ratio 5.43; 95% confidence interval 5.15, 5.72) or self-pay (odds ratio 3.04; 95% confidence interval 2.75, 3.36) all had higher odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. Black race did not have a significant association with an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis (odds ratio 0.99; 95% confidence interval 0.94, 1.04); however, Hispanic (odds ratio 0.44; 95% confidence interval 0.43, 0.46) and Asian (odds ratio 0.40; 95% confidence interval 0.36, 0.44) race/ethnicity was associated with a lower odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. After controlling for competing risk factors on multivariable analyses, the risk-adjusted probability of hospital postoperative death was 3.1% (95% confidence interval 2.8, 3.4) among patients with a social determinants of health diagnosis versus 5.9% (95% confidence interval 5.9, 6.0) (odds ratio 0.48; 95% confidence interval 0.44, 0.54) among patients without a social determinants of health diagnosis. Risk-adjusted complications were 26.7% (95% confidence interval 26.1, 37.3) among patients with a social determinants of health diagnosis compared with 31.9% (95% confidence interval 31.7, 32.0) (odds ratio 0.74; 95% confidence interval 0.71, 0.77) among patients without a social determinants of health diagnosis. CONCLUSION: International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code use was low, with only 3.4% of patients having documentation of a socioeconomic and psychosocial circumstance. The presence of an International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code was not associated with greater odds of complications or death; however, it was associated with longer length of stay and higher odds of being discharged to a skilled nursing facility.

Association Between ICD-10 Codes for Social Needs and Subsequent Emergency and Inpatient Use.

BACKGROUND: International Classification of Diseases, 10th revision Z codes capture social needs related to health care encounters and may identify elevated risk of acute care use. OBJECTIVES: To examine associations between Z code assignment and subsequent acute care use and explore associations between social need category and acute care use. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: Adults continuously enrolled in a commercial or Medicare Advantage plan for ≥15 months (12-month baseline, 3-48 month follow-up). OUTCOMES: All-cause emergency department (ED) visits and inpatient admissions during study follow-up. RESULTS: There were 352,280 patients with any assigned Z codes and 704,560 sampled controls with no Z codes. Among patients with commercial plans, Z code assignment was associated with a 26% higher rate of ED visits [adjusted incidence rate ratio (aIRR) 1.26, 95% CI: 1.25-1.27] and 42% higher rate of inpatient admissions (aIRR 1.42, 95% CI: 1.39-1.44) during follow-up. Among patients with Medicare Advantage plans, Z code assignment was associated with 42% (aIRR 1.42, 95% CI: 1.40-1.43) and 28% (aIRR 1.28, 95% CI: 1.26-1.30) higher rates of ED visits and inpatient admissions, respectively. Within the Z code group, relative to community/social codes, socioeconomic Z codes were associated with higher rates of inpatient admissions (commercial: aIRR 1.10, 95% CI: 1.06-1.14; Medicare Advantage: aIRR 1.24, 95% CI 1.20-1.27), and environmental Z codes were associated with lower rates of both primary outcomes. CONCLUSIONS: Z code assignment was independently associated with higher subsequent emergency and inpatient utilization. Findings suggest Z codes' potential utility for risk prediction and efforts targeting avoidable utilization.

Using a severity threshold to improve occupational injury surveillance: Assessment of a severe traumatic injury-based occupational health indicator across the International Classification of Diseases lexicon transition.

BACKGROUND: Traumatic injury is a leading cause of death and disability among US workers. Severe injuries are less subject to systematic ascertainment bias related to factors such as reporting barriers, inpatient admission criteria, and workers' compensation coverage. A state-based occupational health indicator (OHI #22) was initiated in 2012 to track work-related severe traumatic injury hospitalizations. After 2015, OHI #22 was reformulated to account for the transition from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM. This study describes rates and trends in OHI #22, alongside corresponding metrics for all work-related hospitalizations. METHODS: Seventeen states used hospital discharge data to calculate estimates for calendar years 2012-2019. State-panel fixed-effects regression was used to model linear trends in annual work-related hospitalization rates, OHI #22 rates, and the proportion of work-related hospitalizations resulting from severe injuries. Models included calendar year and pre- to post-ICD-10-CM transition. RESULTS: Work-related hospitalization rates showed a decreasing monotonic trend, with no significant change associated with the ICD-10-CM transition. In contrast, OHI #22 rates showed a monotonic increasing trend from 2012 to 2014, then a significant 50% drop, returning to a near-monotonic increasing trend from 2016 to 2019. On average, OHI #22 accounted for 12.9% of work-related hospitalizations before the ICD-10-CM transition, versus 9.1% post-transition. CONCLUSIONS: Although hospital discharge data suggest decreasing work-related hospitalizations over time, work-related severe traumatic injury hospitalizations are apparently increasing. OHI #22 contributes meaningfully to state occupational health surveillance efforts by reducing the impact of factors that differentially obscure minor injuries; however, OHI #22 trend estimates must account for the ICD-10-CM transition-associated structural break in 2015.

Optimal Definition of Pancreaticoduodenectomy in the International Classification of Diseases, 10th Revision, Procedure Coding System.

BACKGROUND: The implementation of the International Classification of Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) has created difficulty in identifying certain procedures, including pancreaticoduodenectomy. We sought to evaluate which combinations of ICD-10-PCS codes best identify pancreaticoduodenectomy. STUDY DESIGN: We used 2017-2018 Medicare data to identify acute care hospitalization claims of beneficiaries with both ICD-10-PCS and Current Procedural Terminology (CPT) codes available. We developed 12 candidate ICD-10-PCS definitions of pancreaticoduodenectomy and evaluated their test characteristics in identifying hospitalizations involving CPT codes 48150, 48152, 48153, 48154, or 48155 as the criterion standard. We selected one candidate definition with the best balance of test characteristics, then performed decision tree analysis and evaluated the conditional marginal sensitivity and positive predictive value of each individual code to understand which were most informative. RESULTS: Among 964,613 hospitalization claims from 4648 hospitals, 385 claims from 217 hospitals involved a CPT code for pancreaticoduodenectomy. The ICD-10-PCS definition with the best balance had a sensitivity of 92.2% (95% CI: 89.2%-94.4%), specificity of 99.9977% (95% CI: 99.9961%-99.9984%), positive predictive value of 93.7% (95% CI: 90.3%-95.9%), and negative predictive value of 99.9969% (95% CI: 99.9955%-99.9978%). The most informative procedure codes involved open nondiagnostic excision or resection of the duodenum (0DB90ZZ and 0DT90ZZ) and pancreas (0FBG0ZZ and 0FTG0ZZ). CONCLUSION: An ICD-10-PCS definition of pancreaticoduodenectomy using codes for (1) open or percutaneous endoscopic excision or resection of the pancreas and (2) similar codes for the duodenum, consistent with coding guidelines, has satisfactory test characteristics. We suggest researchers consider such characteristics in defining pancreaticoduodenectomy using ICD-10-PCS.

A National Snapshot of Social Determinants of Health Documentation in Emergency Departments.

INTRODUCTION: Documentation and measurement of social determinants of health (SDoH) are critical to clinical care and to healthcare delivery system reforms targeting health equity. The SDoH are codified in the International Classification of Disease 10th Rev (ICD-10) Z codes. However, Z codes are listed in only 1-2% of inpatient charts. Little is known about the frequency of Z code utilization specifically among emergency department (ED) patient populations nationally. METHODS: This was a repeated cross-sectional analysis of ED visit data in the United States from the Nationwide Emergency Department Sample from 2016-2019. We characterized the use of Z codes and described associations between Z code use and patient- and hospital-level factors including the following: age; gender; race; insurance status; ED disposition; ED size; hospital urban-rural status; ownership; and clinical conditions. We calculated unadjusted odds ratios for likelihood of Z code reporting for each ED visit. RESULTS: Of approximately 140 million ED visits per year, 0.65% had an associated Z code in 2016, rising to 1.17% by 2019. Visits were more likely to have an associated Z code for adults age <65, male, Black, Medicaid or self-pay patients, and patients admitted to the hospital. Larger EDs, those in metropolitan areas, academic centers, and government-run hospitals were more likely to report Z codes. The most commonly associated clinical conditions were as follows: schizophrenia spectrum and other psychotic disorders; depressive disorder; and alcohol-related disorders. CONCLUSION: There is a paucity of Z code documentation in the health records of ED patients, although use is uptrending. Further research is warranted to better understand the drivers of clinicians' use of Z codes and to improve on their utility.

A practical strategy to use the ICD-11 for morbidity coding in the United States without a clinical modification.

OBJECTIVE: The aim of this study was to derive and evaluate a practical strategy of replacing ICD-10-CM codes by ICD-11 for morbidity coding in the United States, without the creation of a Clinical Modification. MATERIALS AND METHODS: A stepwise strategy is described, using first the ICD-11 stem codes from the Mortality and Morbidity Statistics (MMS) linearization, followed by exposing Foundation entities, then adding postcoordination (with existing codes and adding new stem codes if necessary), with creating new stem codes as the last resort. The strategy was evaluated by recoding 2 samples of ICD-10-CM codes comprised of frequently used codes and all codes from the digestive diseases chapter. RESULTS: Among the 1725 ICD-10-CM codes examined, the cumulative coverage at the stem code, Foundation, and postcoordination levels are 35.2%, 46.5% and 89.4% respectively. 7.1% of codes require new extension codes and 3.5% require new stem codes. Among the new extension codes, severity scale values and anatomy are the most common categories. 5.5% of codes are not one-to-one matches (1 ICD-10-CM code matched to 1 ICD-11 stem code or Foundation entity) which could be potentially challenging. CONCLUSION: Existing ICD-11 content can achieve full representation of almost 90% of ICD-10-CM codes, provided that postcoordination can be used and the coding guidelines and hierarchical structures of ICD-10-CM and ICD-11 can be harmonized. The various options examined in this study should be carefully considered before embarking on the traditional approach of a full-fledged ICD-11-CM.

Diagnostic rate estimation from Medicare records: Dependence on claim numbers and latent clinical features.

OBJECTIVE: International Classification of Disorders version 10 (ICD-10) codes contribute heavily to healthcare data. Medicare claims and other data-sources are used to constitute study populations and appraise healthcare processes. How variability in claims-per-beneficiary impacts diagnostic determinations is inadequately understood. The objective of this study is so assess distributional properties of Medicare claims, and examine claim rates impact on code utilization and rate determinations. METHODS: The study population was Medicare beneficiaries aged 75-79.99 with claim(s) in the 5% standard analytical Carrier and Outpatient files, alive and participating in Medicare part B for all 12 months of 2017. Medicare beneficiary files were processed to create records containing all ICD-10 codes specified, key demographics, Part B and vital status, and the total claims for each 2017 beneficiary. Claim number cohorts were characterized. RESULTS: Beneficiaries meeting inclusion criteria totaled 221,625, these having 7,617,503 claims; 96.4% had between 1 and 120 claims. Median claims were 24 for males (females 25); modal claims were 11 (13). Average distinct codes per beneficiary increased with claims number. The assignment of ICD-10 codes, i.e., 'diagnostic rate estimates' (DRE), increased as claim numbers increased for most codes among those most commonly utilized. For some conditions, mostly benign and age-related, DREs plateaued as claim numbers increased. For other conditions, typically associated with clinical acuity, e.g., chest pain, DREs increased steeply with claims. CONCLUSIONS: Older adult Medicare beneficiaries aged 75-80 exhibited varying claims activity over the course of a year. Although DRE dependence on claim numbers varies across ICD-10 codes, rate estimates are higher for beneficiaries with claim numbers above the median.

Translation of a Claims-Based Frailty Index From the International Classification of Diseases, Ninth Revision, Clinical Modification to the Tenth Revision.

The Faurot frailty index (FFI) is a validated algorithm that uses enrollment and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-based billing information from Medicare claims data as a proxy for frailty. In October 2015, the US health-care system transitioned from the ICD-9-CM to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). Applying the Centers for Medicare and Medicaid Services General Equivalence Mappings, we translated diagnosis-based frailty indicator codes from the ICD-9-CM to the ICD-10-CM, followed by manual review. We used interrupted time-series analysis of Medicare data to assess the comparability of the pre- and posttransition FFI scores. In cohorts of beneficiaries enrolled in January 2015-2017 with 8-month frailty look-back periods, we estimated associations between the FFI and 1-year risk of aging-related outcomes (mortality, hospitalization, and admission to a skilled nursing facility). Updated indicators had similar prevalences as pretransition definitions. The median FFI scores and interquartile ranges (IQRs) for the predicted probability of frailty were similar before and after the International Classification of Diseases transition (pretransition: median, 0.034 (IQR, 0.02-0.07); posttransition: median, 0.038 (IQR, 0.02-0.09)). The updated FFI was associated with increased risks of mortality, hospitalization, and skilled nursing facility admission, similar to findings from the ICD-9-CM era. Studies of medical interventions in older adults using administrative claims should use validated indices, like the FFI, to mitigate confounding or assess effect-measure modification by frailty.

Acute exacerbation of chronic obstructive pulmonary disease in United States emergency departments, 2010-2018.

OBJECTIVES: Little is known about the recent status of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the U.S. emergency department (ED). This study aimed to describe the disease burden (visit and hospitalization rate) of AECOPD in the ED and to investigate factors associated with the disease burden of AECOPD. METHODS: Data were obtained from the National Hospital Ambulatory Medical Care Survey (NHAMCS), 2010-2018. Adult ED visits (aged 40 years or above) with AECOPD were identified using International Classification of Diseases codes. Analysis used descriptive statistics and multivariable logistic regression accounting for NHAMCS's complex survey design. RESULTS: There were 1,366 adult AECOPD ED visits in the unweighted sample. Over the 9-year study period, there were an estimated 7,508,000 ED visits for AECOPD, and the proportion of AECOPD visits in the entire ED population remained stable at approximately 14 per 1,000 visits. The mean age of these AECOPD visits was 66 years, and 42% were men. Medicare or Medicaid insurance, presentation in non-summer seasons, the Midwest and South regions (vs. Northeast), and arrival by ambulance were independently associated with a higher visit rate of AECOPD, whereas non-Hispanic black or Hispanic race/ethnicity (vs. non-Hispanic white) was associated with a lower visit rate of AECOPD. The proportion of AECOPD visits that were hospitalized decreased from 51% to 2010 to 31% in 2018 (p = 0.002). Arrival by ambulance was independently associated with a higher hospitalization rate, whereas the South and West regions (vs. Northeast) were independently associated with a lower hospitalization rate. The use of antibiotics appeared to be stable over time, but the use of systemic corticosteroids appeared to increase with near statistical significance (p = 0.07). CONCLUSIONS: The number of ED visits for AECOPD remained high; however, hospitalizations for AECOPD appeared to decrease over time. Some patients were disproportionately affected by AECOPD, and certain patient and ED factors were associated with hospitalizations. The reasons for decreased ED admissions for AECOPD deserve further investigation.

[Chronic pain : from symptom to disease]. / La douleur chronique : du symptôme à la maladie.

At last, chronic pain, with its consequences and impact for patients and society, is now considered as a disease in its own in the 11th revision of the international classification of diseases (ICD). We present here in the light of two clinical cases, why the diagnosis of chronic primary pain is useful and how to utilize these new codes. We hope to rapidly see the awaited impact on the healthcare system (from the patient care to insurance issues), as on research and teaching.

La douleur chronique avec ses conséquences et son impact pour les patients et la société est enfin considérée comme une maladie à part entière dans la 11e révision de la Classification internationale des maladies (CIM). Nous présentons ici, à l'aide de deux vignettes, l'utilité du diagnostic de douleur chronique primaire et la façon d'utiliser les nouveaux codes. Nous espérons que l'impact attendu soit rapidement visible tant sur le système de santé (de la prise en charge des patients aux questions assécurologiques), que sur la recherche et l'enseignement.