Most commonly used unspecified ICD-10 codes and the missing specification

Most commonly used unspecified ICD-10 codes and the missing specification

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Purpose To determine the financial and clinical impact of conversion from International Classification of Disease, 9th revision (ICD-9) to ICD-10 coding. Design Retrospective, database study. Materials and methods Monthly billing and coding data from 44,564 billable patient encounters at an academic ophthalmology practice were analyzed by subspec...

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... biggest changes were seen in glaucoma and refractive diagnoses (Figure 1). Codes were most often considered unspecified due to lack of laterality, disease type, or stage (Table 4). ...

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... In one post-ICD-10 implementation audit, it was found that one of the most significant challenges for coders was selecting the correct character in the 3rd position (Root Operation), the 4th position (Body Part), and the 5th position (Approach) of an ICD-10-PCS code [8]. While little evidence exists to suggest that reimbursement was significantly impacted by the transition, in some practices, a statistical increase in the codingrelated denials was noted [9]. A few of the post-transition qualitative studies concluded that training and education were critical in overcoming many of the previously anticipated challenges [6,10]. ...
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Background Transitioning from an old medical coding system to a new one can be challenging, especially when the two coding systems are significantly different. The US experienced such a transition in 2015. Objective This research aims to introduce entropic measures to help users prepare for the migration to a new medical coding system by identifying and focusing preparation initiatives on clinical concepts with more likelihood of adoption challenges. Methods Two entropic measures of coding complexity are introduced. The first measure is a function of the variation in the alphabets of new codes. The second measure is based on the possible number of valid representations of an old code. Results A demonstration of how to implement the proposed techniques is carried out using the 2015 mappings between ICD-9-CM and ICD-10-CM/PCS. The significance of the resulting entropic measures is discussed in the context of clinical concepts that were likely to pose challenges regarding documentation, coding errors, and longitudinal data comparisons. Conclusion The proposed entropic techniques are suitable to assess the complexity between any two medical coding systems where mappings or crosswalks exist. The more the entropy, the more likelihood of adoption challenges. Users can utilize the suggested techniques as a guide to prioritize training efforts to improve documentation and increase the chances of accurate coding, code validity, and longitudinal data comparisons.
... A recent report indicated the use of ICD-10 codes saw an increased utilization of "unspecified codes" thereby potentially leading to conflated rates of diagnoses. 18 To avoid potential overestimation of incidence, comparison of ICD-9 and ICD-10 diagnostic rates were conducted and only primary OSA and insomnia diagnosis data (ICD-9/10: 327.23/G47.33 and ICD-9/10: 327.00/F51.01 and G47.0 respectively) were drawn and analyzed. ...
... Alternatively, service members in the Army presented with more observed cases (n = 192,840) than expected (n = 147,286). Caldwell et al. 5,18 While there is a perception in the lay press that service members may pursue the diagnosis of sleep apnea because of the potential for medical disability compensation, 20 our study offers potential insight into this. The findings that insomnia and OSA had similar, marked increases in incidences over the study period even though the Veteran's Administration does not provide a similar medical disability compensation for insomnia, suggests that this is not OSA specific. ...
Article
Study objectives: Epidemiologic studies of obstructive sleep apnea (OSA) and insomnia in the U.S. military are limited. The primary aim of this study was to report and compare OSA and insomnia diagnoses in active duty United States military service members. Method: Data and service branch densities used to derive the expected rates of diagnoses on insomnia and OSA were drawn from the Defense Medical Epidemiology Database. Single sample Chi-Square goodness of fit tests and independent samples t-tests were conducted to address the aims of the study. Results: Between 2005 and 2019, incidence rates of OSA and insomnia increased from 11 to 333 and 6 to 272 (per 10,000) respectively. Service members in the Air Force, Navy, and Marines were diagnosed with insomnia and OSA below expected rates, while those in the Army had higher than expected rates (p < .001). Female service members were underdiagnosed in both disorders (p < .001). Comparison of diagnoses following the transition from ICD 9 to 10 codes revealed significant differences in the amounts of OSA diagnoses only (p < .05). Conclusion: Since 2005, incidence rates of OSA and insomnia have markedly increased across all branches of the U.S. military. Despite similar requirements for overall physical and mental health and resilience, service members in the Army had higher rates of insomnia and OSA. This unexpected finding may relate to inherent differences in the branches of the military or the role of the Army in combat operations. Future studies utilizing military-specific data and directed interventions are required to reverse this negative trend.
... While little evidence exists to suggest that reimbursement was significantly impacted by the transition, in some practices, a statistical increase in the coding-related denials was noted [9]. A few of the post-transition qualitative studies concluded that training and education were critical in overcoming many of the previously anticipated challenges [6,10]. ...
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Background Transitioning from an old medical coding system to a new one can be challenging, especially when the two coding systems are significantly different. The US experienced such a transition in 2015. Objective This research aims to introduce entropic measures to help users prepare for the migration to a new medical coding system by identifying and focusing preparation initiatives on clinical concepts with more likelihood of adoption challenges. Methods Two entropic measures of coding complexity are introduced. The first measure is a function of the variation in the alphabets of new codes. The second measure is based on the possible number of valid representations of an old code. Results A demonstration of how to implement the proposed techniques is carried out using the 2015 mappings between ICD-9-CM and ICD-10-CM/PCS. The significance of the resulting entropic measures is discussed in the context of clinical concepts that were likely to pose challenges regarding documentation, coding errors, and longitudinal data comparisons. Conclusion The proposed entropic techniques are suitable to assess the complexity between any two medical cod ing systems where mappings or crosswalks exist. The more the entropy, the more likelihood of adoption challenges. Users can utilize the suggested techniques as a guide to prioritize training efforts to improve doc umentation and increase the chances of accurate coding, code validity, and longitudinal data comparisons.
... These improvements included more specific data for track-ing public health conditions, conducting epidemiological research, as well as the potential for enhancing clinical decision-making and payment/reimbursement systems. 1 , 3 Although the CDC stated the intended advantages of the new classification system, only a few authors have published results assessing the improvements in data specificity and diagnostic coding since the conversion. [4][5][6][7] In 2017, researchers using Veterans Affairs data analyzed the impact the conversion to ICD-10-CM had on the recording of the overall epidemiology of chronic conditions and mortality statistics. 8 Additionally, one group has evaluated the change in reimbursements and insurance denials associated with the conversion in an ophthalmology practice. ...
... 8 Additionally, one group has evaluated the change in reimbursements and insurance denials associated with the conversion in an ophthalmology practice. 5 Both of these studies highlighted a tendency for coding to capture similar prevalence of conditions diagnosed; however, the ophthalmology study found a trend in which providers used a higher frequency of less specific or unspecified codes upon conversion to the ICD-10 coding system. Cross-mapping of spinal conditions that comprise the category "Dorsopathies "; note that deformity codes are excluded from ICD-9 or ICD-10 groups. ...
... 6 Also, in ophthalmology, Hellman et al. found that in an academic ophthalmology practice, the conversion to ICD-10 was associated with a bias toward unspecified codes. 5 Consistent with the study hypothesis, the lack of usage of the full breadth of codes (number of codes and specificity of codes) is clearly a limitation to the objectives of introducing ICD-10. Clinical treatment algorithms cannot take advantages of the granular nature of ICD-10 if the specific codes are not used. ...
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Background The transition from International Classification of Diseases, 9th Edition (ICD-9) to the 10th edition (ICD-10) in 2015 increased the number and specificity of diagnostic codes with the goal of facilitating clinical care and research possibilities. Considering the potential to default to less specified ICD-10 codes, the current study evaluated the number of codes utilized for spine-related conditions before versus after the transition to ICD-10. Methods The numbers of patients with an index encounter for a primary spine-related non-deformity diagnosis codes indexed as “dorsopathies” were abstracted from the Humana PearlDiver dataset. As the transition from ICD-9 to ICD-10 occurred in 2015, the current study compared the year prior (ICD-9) to the year after (ICD-10). The number of ICD-9 and ICD-10 codes was assessed, and distribution of utilization was compared using the Kolmogorov-Smirnov test. Results In 2014, 848,623 patients were assigned one of the 100 unique ICD-9 dorsopathy codes, of which 17 codes (17% of available codes) were used for more than 1% of the patients. In 2016, 840,310 patients were assigned one of the 504 unique ICD-10 dorsopathy codes, of which 21 (4% of available codes) were used for more than 1% of the patients. The top 20 codes in 2014 (ICD-9) and the top 20 codes in 2016 (ICD-10) both represented the majority of the patient population and were not statistically differently represented (p = 0.819). Further, analysis of ICD-10 codes demonstrated a clear bias toward utilizing less specified codes. Conclusions Despite a five-fold increase in available diagnostic codes for spine conditions in ICD-10, in the year after implementation providers continued to select a small proportion of less specific diagnostic codes when treating spine patients.
... 11 A retrospective study of a mid-sized-10 physicians, 1 coder, 6 administrators-ophthalmology practice similarly found that coder efficiency was reduced 4 months after the October 2015 ICD-10 implementation, but it had returned to baseline in the following 8 months. 12 The same study found no change in clinical volume when comparing the periods 12 months before and after ICD-10 implementation, which was attributed to the practice's use of a certified coding team, which decreases the amount of physician time needed for coding. 12 Physicians Foundation's April-June 2016 biennial survey of American physicians registered with the American Medical Association also found that approximately 43% of 17 236 physician respondents reported that ICD-10 detracted from practice efficiency, while 6% reported that it improved efficiency. ...
... 12 The same study found no change in clinical volume when comparing the periods 12 months before and after ICD-10 implementation, which was attributed to the practice's use of a certified coding team, which decreases the amount of physician time needed for coding. 12 Physicians Foundation's April-June 2016 biennial survey of American physicians registered with the American Medical Association also found that approximately 43% of 17 236 physician respondents reported that ICD-10 detracted from practice efficiency, while 6% reported that it improved efficiency. 13 A Healthcare Billing and Management Association member survey, 14 conducted in February 2016, addressed changes in staffing. ...
... 13 A retrospective study of an academic ophthalmology practice found that per 100 visits, coding-related denials, charges denied, and percentage of charges denied nearly doubled; however, there was no change in total revenue based on an analysis of data 12 months before and after the October 2015 ICD-10 conversion. 12 The transaction-processing firm Change Healthcare reported that 5% of their clients had a time to bill increase greater than 5 days based on a November 2015 survey; however, for two-thirds of their clients, time to bill did not change. 20 Coding accuracy A few studies suggest coding accuracy may have been impacted as a result of the ICD-10-CM/PCS transition. ...
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Objectives The United States transitioned to the tenth version of the International Classification of Diseases (ICD) system (ICD-10) for mortality coding in 1999 and to the International Classification of Diseases, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) on October 1, 2015. The purpose of this study was to conduct a narrative literature review to better understand the impact of the implementation of ICD-10/ICD-10-CM/PCS. Materials and Methods We searched English-language articles in PubMed, Web of Science, and Business Source Complete and reviewed websites of relevant professional associations, government agencies, research groups, and ICD-10 news aggregators to identify literature on the impact of the ICD-10/ICD-10-CM/PCS transition. We used Google to search for additional gray literature and used handsearching of the references of the most on-target articles to help ensure comprehensiveness. Results Impact areas reported in the literature include: productivity and staffing, costs, reimbursement, coding accuracy, mapping between ICD versions, morbidity and mortality surveillance, and patient care. With the exception of morbidity and mortality surveillance, quantitative studies describing the actual impact of the ICD-10/ICD-10-CM/PCS implementation were limited and much of the literature was based on the ICD-10-CM/PCS transition rather than the earlier conversion to ICD-10 for mortality coding. Discussion This study revealed several gaps in the literature that limit the ability to draw reliable conclusions about the overall impact, positive or negative, of moving to ICD-10/ICD-10-CM/PCS in the United States. Conclusion These knowledge gaps present an opportunity for future research and knowledge sharing and will be important to consider when planning for ICD-11.
... A number of US studies have evaluated the financial impact or differences in incidence or prevalence of adverse health outcomes between the period before and after the transition to ICD-10-CM (Hellman, Lim, Leung, Blount, & Yiu, 2018;Inscore, Gonzales, Rennix, & Jones, 2018;Panozzo et al., 2018). However, the effect of this transition on birth defects prevalence and trends has not been explored. ...
Article
Background: Many public health surveillance programs utilize hospital discharge data in their estimation of disease prevalence. These databases commonly use the International Classification of Diseases (ICD) coding scheme, which transitioned from the ICD-9 clinical modification (ICD-9-CM) to ICD-10-CM on October 1, 2015. This study examined this transition's impact on the prevalence of major birth defects among infant hospitalizations. Methods: Using data from the Agency for Health Care Research and Quality-sponsored National Inpatient Sample, hospitalizations during the first year of life with a discharge date between January 1, 2012 and December 31, 2016 were used to estimate the monthly national hospital prevalence of 46 birth defects for the ICD-9-CM and ICD-10-CM timeframes separately. Survey-weighted Poisson regression was used to estimate 95% confidence intervals for each hospital prevalence. Interrupted time series framework and corresponding segmented regression was used to estimate the immediate change in monthly hospital prevalence following the ICD-9-CM to ICD-10-CM transition. Results: Between 2012 and 2016, over 21 million inpatient hospitalizations occurred during the first year of life. Among the 46 defects studied, statistically significant decreases in the immediate hospital prevalence of five defects and significant increases in the immediate hospital prevalence of eight defects were observed after the ICD-10-CM transition. Conclusions: Changes in prevalence were expected based on changes to ICD-10-CM. Observed changes for some conditions may result from variation in monthly hospital prevalence or initial unfamiliarity of coders with ICD-10-CM. These findings may help birth defects surveillance programs evaluate and interpret changes in their data related to the ICD-10-CM transition.
Article
Purpose When International Classification of Disease (ICD) version 9 (ICD-9) transitioned to ICD-10, there was a marked increase in the complexity of ICD codes with potential for improved specificity in clinical database research. The purpose of this study was to characterize the accuracy of coding for stage of diabetic retinopathy (DR) and DR-related complications (including vitreous hemorrhage, retinal detachment, and neovascular glaucoma) during this transition. Design Retrospective chart review of 3 time periods corresponding to the use of: ICD-9 (2014-2015), “early” use of ICD-10 (2015-2016), and “late” use of ICD-10 (2018-2019). Subjects Patients 18 years or older with a diagnosis of diabetic retinopathy at a multispecialty academic institution Methods Positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, and kappa (κ) statistics were generated for each diagnosis. Generalized estimating equations (GEE) models were used to assess the significance of the variables. Main Outcome Measure The main outcome was the proportion of agreement between the ICD code and documented chart standard for stage of DR and DR-related complications. Results 600 patients were included in the study (average age 61 years, range 25-93). Overall, there was substantial agreement between the ICD codes for stage of DR and documented standard (κ = 0.66). The proportion of ICD codes in agreement with the documented standard diagnosis increased with time: 66.5%, 78.5%, and 83.3% for ICD-9, “early” ICD-10, and “late” ICD-10, respectively. The odds of agreement were 2.67 (95% confidence interval (CI): 1.49 – 4.76, p<0.001) and 3.96 (95%CI: 2.34 – 6.69, p<0.0001) times greater for “early” and “late” ICD-10 codes compared to ICD-9. Looking at specific codes, the overall PPV/NPV/sensitivity/specificity for NPDR and PDR were excellent (>90%). The odds of agreement were 19.70 (95% CI: 11.54 – 33.64, p<0.0001) times greater for proliferative diabetic retinopathy than nonproliferative diabetic retinopathy. Compared to the stage of DR, DR-related diagnoses were overall less accurately coded (κ = 0.61, 0.48, 0.52 for vitreous hemorrhage, retinal detachment, and neovascular glaucoma). Conclusions Coding in ICD-10 is more accurate than ICD-9, particularly for proliferative diabetic retinopathy compared to nonproliferative diabetic retinopathy. The increased accuracy emphasizes the potential for ICD-10 coding to be used effectively in database research.
Article
Purpose: The Centers for Medicare and Medicaid Services (CMS) mandated the transition from ICD-9 to ICD-10 codes on October 1, 2015. Postmarketing surveillance of newly marketed drugs, including novel biologics and biosimilars, requires a robust approach to convert ICD-9 to ICD-10 codes for study variables. We examined three mapping methods for health conditions (HCs) of interest to the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) and compared their prevalence. Methods: Using CMS General Equivalence Mappings, we applied forward-backward mapping (FBM) to 108 HCs and secondary mapping (SM) and tertiary mapping (TM) to seven preselected HCs. A physician reviewed the mapped ICD-10 codes. The prevalence of the 108 HCs defined by ICD-9 versus ICD-10 codes was examined in BBCIC's distributed research network (September 1, 2012 to March 31, 2018). We visually assessed prevalence trends of these HCs and applied a threshold of 20% level change in ICD-9 versus ICD-10 prevalence. Results: Nearly four times more ICD-10 codes were mapped by SM and TM than FBM, but most were irrelevant or nonspecific. For conditions like myocardial infarction, SM or TM did not generate additional ICD-10 codes. Through visual inspection, one-fifth of the HCs had inconsistent ICD-9 versus ICD-10 prevalence trends. 13% of HCs had a level change greater than +/-20%. Conclusion: FBM is generally the most efficient way to convert ICD-9 to ICD-10 codes, yet manual review of converted ICD-10 codes is recommended even for FBM. The lack of existing guidance to compare the performance of ICD-9 with ICD-10 codes led to challenges in empirically determining the quality of conversions.
Article
Introduction: ICD is currently the most widely used terminology to code diagnosis and procedures. The transition from ICD-9-CM to ICD-10-CM became effective on October 1, 2015 in US and many other countries. Projects that use this codification for research purposes, requires advanced methods to exploit data with both versions of ICD. Although the General Equivalence Mappings (GEMs), provided by the Centers for Medicare and Medicaid Services, might help to overcome these challenges, their direct use as translation mappings is not possible, mostly due to the further specificity of ICD-10-CM concepts. Objective: We propose a methodology to generate an extended version of ICD-10-CM with selected ICD-9-CM diagnosis codes. Methods: The extension was generated using the GEMs relations between concepts of both terminologies and the hierarchical relations of ICD-10-CM. Results: This extended ICD-10-CM, together with modifications to the mapping of ICD-9-CM concepts that were not inserted, allows the generation of an improved translation of legacy data, raising the number of 1-to-1 correspondences by +13.81%. Conclusion: The extended ICD-10-CM enables the accurate integration of ICD-9-CM and ICD-10-CM diagnosis data into a single terminology. With such analysis of data possible without having to specify both ICD-9-CM and ICD-10-CM separately for each query.