ICD-10 Coding of Musculoskeletal Conditions in the Veterans Health Administration.
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ABSTRACT: Objective
We describe the most frequently used musculoskeletal diagnoses in Veterans Health Administration care. We report the number of visits and patients associated with common musculoskeletal International Classification of Diseases (ICD)-10 codes and compare trends across primary and specialty care settings.Design
Secondary analysis of a longitudinal cohort study.Subjects
Veterans included in the Musculoskeletal Diagnosis Cohort with a musculoskeletal diagnosis from October 1, 2015, through September 30, 2017.Methods
We obtained counts and proportions of all musculoskeletal diagnosis codes used and the number of unique patients with each musculoskeletal diagnosis. Diagnosis use was compared between primary and specialty care settings.Results
Of more than 6,400 possible ICD-10 M-codes describing "Diseases of the Musculoskeletal System and Connective Tissue," 5,723 codes were used at least once. The most frequently used ICD-10 M-code was "Low Back Pain" (18.3%), followed by "Cervicalgia" (3.6%). Collectively, the 100 most frequently used codes accounted for 80% of M-coded visit diagnoses, and 95% of patients had at least one of these diagnoses. The most common diagnoses (spinal pain, joint pain, osteoarthritis) were used similarly in primary and specialty care settings.Conclusion
A diverse sample of all available musculoskeletal diagnosis codes were used; however, less than 2% of all possible codes accounted for 80% of the diagnoses used. This trend was consistent across primary and specialty care settings. The most frequently used diagnosis codes describe the types of musculoskeletal conditions, among a large pool of potential diagnoses, that prompt veterans to present to the Veterans Health Administration for musculoskeletal care.
SUBMITTER: Coleman BC
PROVIDER: S-EPMC8783617 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:INTRODUCTION:Healthcare workers account for 10% of the EU's total workforce, with a significant proportion of those employed in hospitals. Musculoskeletal injuries are the predominant group of injuries in healthcare professionals due to the physical demands of their work, such as the mobilization and positioning of the dependent patients. The management of this type of problem should take into account direct and indirect costs, such as periods of incapacity for work due to illness, hiring and training of new employees during periods of absence, reduced levels of productivity and the effects on production and quality of work. OBJECTIVES:1-Characterization of injuries resulting from occupational accidents in hospital workers according to the International Classification of Diseases ICD-10; 2-Identification of the predictive factors of absenteeism duration due to temporary work incapacity in workplace accidents. METHODS:A retrospective observational study was conducted based on the analysis of 1621 cases of work-related accidents of employees of Centro Hospitalar São João from January 2011 to December 2014. An ICD-10 classification code was associated with each of the accident cases, based on pre-established criteria for classification of the specific diagnoses of musculoskeletal injuries. The duration of temporary work incapacity was compared between the categories of sociodemographic variables, among six categories of ICD-10 primary diagnosis (reclassification), and between the two major chapters of ICD-10 classification-chapter XIX (direct trauma) and chapter XIII (indirect trauma-strain injuries). The sociodemographic predictors of the occurrence of strain injuries were determined by logistic regression. A multinomial logistic regression analysis was conducted with selection of duration of work incapacity as the dependent variable. RESULTS:A total of 824 cases of musculoskeletal injuries occurred on hospital premises during the study period, which corresponded to a total of 22159 lost workdays in the context of temporary work incapacity due to work injury. According to the ICD-10 reclassification, the three most frequent diagnostic groups were direct lower limb trauma (n = 230, 27.9%), spinal strain injuries (n = 194, 23.5%) and direct upper limb trauma (n = 174, 21.1%). Significant differences were observed in temporary work incapacity duration among the ICD-10 diagnostic categories: spinal strain injuries were the diagnostic group associated with longer duration of temporary work incapacity, with a median = 14.0 (25-75th percentile: 6.0-35.0). The only variable that demonstrated to be significantly predictive of temporary work incapacity less than or greater than 20 days was the ICD-10 diagnostic group. The regression results revealed a 5-fold increase in risk in the case of spinal strain injuries for temporary work incapacity durations of less than or greater than 20 days (OR = 5.58 and OR = 5.89 respectively). CONCLUSIONS:The study findings support the benefits of the characterization of workplace injuries by medical diagnostic groups, namely in the interpretation of the sequelae of the accidents and the medical contextualization of the accidents. Association of ICD-10characterization can improve the analysis of workplace accidents at an institutional level, and promote the implementation of preventive measures and control of absenteeism.
| S-EPMC6294350 | biostudies-literature
Project description:BackgroundThe International Classification of Diseases, 10th Revision (ICD-10) has been widely used to describe the diagnosis information of patients. Automatic ICD-10 coding is important because manually assigning codes is expensive, time consuming and error prone. Although numerous approaches have been developed to explore automatic coding, few of them have been applied in practice. Our aim is to construct a practical, automatic ICD-10 coding machine to improve coding efficiency and quality in daily work.MethodsIn this study, we propose the use of regular expressions (regexps) to establish a correspondence between diagnosis codes and diagnosis descriptions in outpatient settings and at admission and discharge. The description models of the regexps were embedded in our upgraded coding system, which queries a diagnosis description and assigns a unique diagnosis code. Like most studies, the precision (P), recall (R), F-measure (F) and overall accuracy (A) were used to evaluate the system performance. Our study had two stages. The datasets were obtained from the diagnosis information on the homepage of the discharge medical record. The testing sets were from October 1, 2017 to April 30, 2018 and from July 1, 2018 to January 31, 2019.ResultsThe values of P were 89.27 and 88.38% in the first testing phase and the second testing phase, respectively, which demonstrate high precision. The automatic ICD-10 coding system completed more than 160,000 codes in 16 months, which reduced the workload of the coders. In addition, a comparison between the amount of time needed for manual coding and automatic coding indicated the effectiveness of the system-the time needed for automatic coding takes nearly 100 times less than manual coding.ConclusionsOur automatic coding system is well suited for the coding task. Further studies are warranted to perfect the description models of the regexps and to develop synthetic approaches to improve system performance.
| S-EPMC7157985 | biostudies-literature
Project description:BackgroundWhile potentially timesaving, there is no program to automatically transform diagnosis codes of the ICD-10 German modification (ICD-10-GM) into the injury severity score (ISS).ObjectiveTo develop a mapping method from ICD-10-GM into ICD-10 clinical modification (ICD-10-CM) to calculate the abbreviated injury scale (AIS) and ISS of each patient using the ICDPIC-R and to compare the manually and automatically calculated scores.MethodsBetween January 2019 and June 2021, the most severe AIS of each body region and the ISS were manually calculated using medical documentation and radiology reports of all major trauma patients of a German level I trauma centre. The ICD-10-GM codes of these patients were exported from the electronic medical data system SAP, and a Java program was written to transform these into ICD-10-CM codes. Afterwards, the ICDPIC-R was used to automatically generate the most severe AIS of each body region and the ISS. The automatically and manually determined ISS and AIS scores were then tested for equivalence.ResultsStatistical analysis revealed that the manually and automatically calculated ISS were significantly equivalent over the entire patient cohort. Further sub-group analysis, however, showed that equivalence could only be demonstrated for patients with an ISS between 16 and 24. Likewise, the highest AIS scores of each body region were not equal in the manually and automatically calculated group.ConclusionThough achieving mapping results highly comparable to previous mapping methods of ICD-10-CM diagnosis codes, it is not unrestrictedly possible to automatically calculate the AIS and ISS using ICD-10-GM codes.
| S-EPMC8432850 | biostudies-literature
Project description:OBJECTIVE: To compare Veterans Health Administration (VA) patients, non-VA-using veterans, and nonveterans, separated by urban/rural residence and age group, on their use of major categories of medical care and payment sources. DATA SOURCE: Expenditures for health care-using men in Medical Expenditure Panel Surveys from 1996 through 2004. STUDY DESIGN: Retrospective, cross-sectional analysis. DATA COLLECTION/EXTRACTION METHODS: Controlling for demographics, health status, and insurance, we compared groups on population-weighted expenditures for inpatient, hospital-based outpatient, office-based, pharmacy, and other care, by major payers (self/family, private insurance, Medicare, other sources, and VA). RESULTS: VA users received most of their health care outside of the VA system, paid through private insurance or Medicare; self-payments were substantial. VA users under 65 reported worse health if they were rural residents but also lower expenditures overall and less care through private insurance. CONCLUSIONS: VA health care users get most of their medical care from non-VA providers. Working-age VA users have less insurance coverage and rely more on VA care if they live in rural areas.
| S-EPMC2754556 | biostudies-other
Project description:ImportanceLow-value care is associated with harm among patients and with wasteful health care spending but has not been well characterized in the Veterans Health Administration.ObjectivesTo characterize the frequency of and variation in low-value diagnostic testing for 4 common conditions at Veterans Affairs medical centers (VAMCs) and to examine the correlation between receipt of low-value testing for each condition.Design, setting, and participantsThis retrospective cohort study used Veterans Health Administration data from 127 VAMCs from fiscal years 2014 to 2015. Data were analyzed from April 2018 to March 2020.ExposuresContinuous enrollment in Veterans Health Administration during fiscal year 2015.Main outcomes and measuresReceipt of low-value testing for low back pain, headache, syncope, and sinusitis. For each condition, sensitive and specific criteria were used to evaluate the overall frequency and range of low-value testing, adjusting for sociodemographic and VAMC characteristics. VAMC-level variation was calculated using median adjusted odds ratios. The Pearson correlation coefficient was used to evaluate the degree of correlation between low-value testing for each condition at the VAMC level.ResultsAmong 1 022 987 veterans, the mean (SD) age was 60 (16) years, 1 008 336 (92.4%) were male, and 761 485 (69.8%) were non-Hispanic White. A total of 343 024 veterans (31.4%) were diagnosed with low back pain, 79 176 (7.3%) with headache, 23 776 (2.2%) with syncope, and 52 889 (4.8%) with sinusitis. With the sensitive criteria, overall and VAMC-level low-value testing frequency varied substantially across conditions: 4.6% (range, 2.7%-10.1%) for sinusitis, 12.8% (range, 8.6%-22.6%) for headache, 18.2% (range, 10.9%-24.6%) for low back pain, and 20.1% (range, 16.3%-27.7%) for syncope. With the specific criteria, the overall frequency of low-value testing across VAMCs was 2.4% (range, 1.3%-5.1%) for sinusitis, 8.6% (range, 6.2%-14.6%) for headache, 5.6% (range, 3.6%-7.7%) for low back pain, and 13.3% (range, 11.3%-16.8%) for syncope. The median adjusted odds ratio ranged from 1.21 for low back pain to 1.40 for sinusitis. At the VAMC level, low-value testing was most strongly correlated for syncope and headache (ρ = 0.56; P < .001) and low back pain and headache (ρ = 0.48; P < .001).Conclusions and relevanceIn this cohort study, low-value diagnostic testing was common, varied substantially across VAMCs, and was correlated between veterans' receipt of different low-value tests at the VAMC level. The findings suggest a need to address low-value diagnostic testing, even in integrated health systems, with robust utilization management practices.
| S-EPMC7509631 | biostudies-literature
Project description:ObjectiveVeterans, especially those residing in rural areas, continue to underutilize mental health care. This longitudinal study assessed attitudes relevant to seeking mental health care services from the Veterans Health Administration (VHA) over 12 months, adjusting for residence.MethodsA questionnaire addressing attitudes, sociodemographic factors, residence, place identity, perceived health status and needs, and structural barriers was administered by telephone to 752 veterans with previous VHA service use. Service use data were obtained from a VHA database.ResultsIn adjusted models, four attitudes were significantly associated with underuse of VHA mental health care (no use vs. any use; no use vs. nonsustained use vs. sustained use). Higher levels of mistrust of others (adjusted odds ratio [AOR]=1.06, p=0.046), emotional stoicism (AOR=1.08, p=0.003), belief in the self-resolving nature of mental health problems (AOR=1.91, p=0.015), and belief in the efficacy of religious counseling for such problems (AOR=1.09, p=0.022) were associated with no subsequent service use versus any use. Place identity (suburban), older age, and greater need were associated with greater odds of VHA use. For the comparison of no use versus sustained use, women had lower odds of no use (AOR=0.49, p<0.001); similarly, women had lower odds of nonsustained use versus sustained use (AOR=0.45, p<0.001).ConclusionsThe association of potentially modifiable attitudes with underuse of VHA mental health services suggests that attitudes offer useful targets for efforts to increase mental health care use. That these attitudes were influential regardless of residence suggests that programs addressing attitudinal barriers can be broadly targeted.
| S-EPMC8638372 | biostudies-literature
Project description:BackgroundWe aimed to estimate the impact of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding transition on traumatic injury-related hospitalization trends among young adults across a geographically and demographically diverse group of U.S. states.MethodsInterrupted time series analyses were conducted using statewide inpatient databases from 12 states and including traumatic injury-related hospitalizations in adults aged 19-44?years in 2011-2017. Segmented regression models were used to estimate the impact of the October 2015 coding transition on external cause of injury (ECOI) completeness (percentage of hospitalizations with a documented ECOI code) and on population-level rates of injury-related hospitalizations by nature, intent, mechanism, and severity of injury.ResultsThe transition to ICD-10-CM was associated with a drop in ECOI completion in the transition month (-?3.7%; P?<?.0001), but there was no significant change in the positive trend in ECOI completion from the pre- to post-transition periods. There were significant increases post-transition in the measured rates of hospitalization for traumatic brain injury (TBI), unintentional injury, mild injury (injury severity score (ISS) <?9), and injuries caused by drowning, firearms, machinery, other pedestrian, suffocation, and unspecified mechanism. Conversely, there were significant decreases in October 2015 in the rates of hospitalization for assault, injuries of undetermined intent, injuries of moderate severity (ISS 9-15), and injuries caused by fire/burn, other pedal cyclist, other transportation, natural/environmental, and other specified mechanism. A significant increase in the percentage of hospitalizations classified as resulting from severe injury (ISS?>?15) was observed when the general equivalence mapping maximum severity method for converting ICD-10-CM codes to ICD-9-CM codes was used. State-specific results for the outcomes of ECOI completion and TBI-related hospitalization rates are provided in an online supplement.ConclusionsThe U.S. transition from ICD-9-CM to ICD-10-CM coding led to a significant decrease in ECOI completion and several significant changes in measured rates of injury-related hospitalizations by injury intent, mechanism, nature, and severity. The results of this study can inform the design and analysis of future traumatic injury-related health services research studies that use both ICD-9-CM and ICD-10-CM coded data.Level of evidenceII (Interrupted Time Series).
| S-EPMC7830822 | biostudies-literature
Project description:ObjectiveThis study examines the impact of the transition from ICD-9-CM to ICD-10-CM diagnosis coding on the recording of mental health disorders in electronic health records (EHRs) and claims data in ten large health systems. We present rates of these diagnoses across two years spanning the October 2015 transition.MethodsMental health diagnoses were identified from claims and EHR data at ten health care systems in the Mental Health Research Network (MHRN). Corresponding ICD-9-CM and ICD-10-CM codes were compiled and monthly rates of people receiving these diagnoses were calculated for one year before and after the coding transition.ResultsFor seven of eight diagnostic categories, monthly rates were comparable during the year before and the year after the ICD-10-CM transition. In the remaining category, psychosis excluding schizophrenia spectrum disorders, aggregate monthly rates of decreased markedly with the ICD-10-CM transition, from 48 to 33 per 100,000. We propose that the change is due to features of General Equivalence Mappings (GEMS) embedded in the EHR.ConclusionsFor most mental health conditions, the transition to ICD-10-CM appears to have had minimal impact. The decrease seen for psychosis diagnoses in these health systems is likely due to changes associated with EHR implementation of ICD-10-CM coding rather than an actual change in disease prevalence. It is important to consider the impact of the ICD-10-CM transition for all diagnostic criteria used in research studies, quality measurement, and financial analysis during this interval.
| S-EPMC6484373 | biostudies-literature
Project description:Chronic overlapping pain conditions (COPCs) are a set of painful chronic conditions characterized by high levels of co-occurrence. It has been hypothesized that COPCs co-occur in many cases because of common neurobiological vulnerabilities. In practice, most research on COPCs has focused upon a single index condition with little effort to assess comorbid painful conditions. This likely means that important phenotypic differences within a sample are obscured. The International Classification of Diseases (ICD) coding system contains many diagnostic classifications that may be applied to individual COPCs, but there is currently no agreed upon set of codes for identifying and studying each of the COPCs. Here we seek to address this issue through three related projects 1) we first compile a set of ICD-10 codes from expert panels for ten common COPCs, 2) we then use natural language searches of medical records to validate the presence of COPCs in association with the proposed expert codes, 3) finally, we apply the resulting codes to a large administrative medical database to derive estimates of overlap between the ten conditions as a demonstration project. The codes presented can facilitate administrative database research on COPCs. PERSPECTIVE: This article presents a set of ICD-10 codes that researchers can use to explore the presence and overlap of COPCs in administrative databases. This may serve as a tool for estimating samples for research, exploring comorbidities, and treatments for individual COPCs, and identifying mechanisms associated with their overlap.
| S-EPMC8177096 | biostudies-literature
Project description:INTRODUCTION:This clinical demonstration trial compared the effectiveness of the Veterans Affairs Diabetes Prevention Program (VA-DPP) with an evidence-based usual care weight management program (MOVE!®) in the Veterans Health Administration health system. DESIGN:Prospective, pragmatic, non-randomized comparative effectiveness study of two behavioral weight management interventions. SETTING/PARTICIPANTS:Obese/overweight Veterans with prediabetes were recruited from three geographically diverse VA sites between 2012 and 2014. INTERVENTION:VA-DPP included 22 group-based intensive lifestyle change sessions. MAIN OUTCOME MEASURES:Weight change at 6 and 12 months, hemoglobin A1c (HbA1c) at 12 months, and VA health expenditure changes at 15 months were assessed using VA electronic health record and claims data. Between- and within-group comparisons for weight and HbA1c were done using linear mixed-effects models controlling for age, gender, race/ethnicity, baseline outcome values, and site. Analyses were conducted in 2015-2016. RESULTS:A total of 387 participants enrolled (273 VA-DPP, 114 MOVE!). More VA-DPP participants completed at least one (73.3% VA-DPP vs 57.5% MOVE! p=0.002); four (57.5% VA-DPP vs 42.5% MOVE!, p=0.007); and eight or more sessions (42.5% VA-DPP vs 31% MOVE!, p=0.035). Weight loss from baseline was significant at both 6 (p<0.001) and 12 months (p<0.001) for VA-DPP participants, but only significant at 6 months for MOVE! participants (p=0.004). Between groups, there were significant differences in 6-month weight loss (-4.1 kg VA-DPP vs -1.9 kg MOVE!, p<0.001), but not 12-month weight loss (-3.4 kg VA-DPP vs -2.0 kg MOVE!, p=0.16). There were no significant differences in HbA1c change or outpatient, inpatient, and total VA expenditures. CONCLUSIONS:VA-DPP participants had higher participation rates and weight loss at 6 months, but similar weight, HbA1c, and health expenditures at 12 months compared to MOVE! PARTICIPANTS:Features of VA-DPP may help enhance the capability of MOVE! to reach a larger proportion of the served population and promote individual-level weight maintenance.
| S-EPMC6699500 | biostudies-literature