Which icd 10 cm chapter was not reorganized

Figure 3 shows monthly diagnostic category prevalence rates for 6 selected pregnancy-related categories. Additional pregnancy-related categories are included in eFigure 3 in the Supplement.

Our clinical review noted that the number of obstetrical codes doubled in ICDCM vs ICDCM and that the ICDCM coding system was restructured to remove designation of antepartum, delivery, and postpartum status and to add separate codes to indicate weeks of gestation for ongoing pregnancies or pregnancy results for individuals who are no longer pregnant.

Among HHS-HCCs, some conditions, such as breech presentation and previous cesarean delivery, were removed from the category for completed pregnancies with complications, contributing to declines in the prevalence of these diagnostic categories. In contrast, the AHRQ-CCS system adapted to the increased detail and restructuring of the obstetrical codes by adding many more specific codes to its existing categories, resulting in abrupt increases in their prevalence at the ICDCM transition.

Findings from sensitivity analyses were broadly consistent with the main analyses. These included using monthly counts of diagnoses in each category as the primary outcome, not using the HHS filtering logic, and substituting the HHS-HCC software for the version to set the diagnostic category mappings.

Our interrupted time series analysis and cross-sectional study of commercial claims from to revealed striking changes in levels and trends for many diagnostic categories associated with the transition to ICDCM. Our clinical review found that abrupt level changes were largely due to different decisions about which codes to include or exclude in post— ICDCM diagnostic categories, such as diabetes coded jointly with hypoglycemia or hyperglycemia leading to a complicated diabetes category, non-STEMI being included or not in the AMI category, and breech presentation leading to classification or not as a complication of pregnancy.

We also identified some changes in coding instructions and coding practice that may have affected disease prevalence trend rates. For certain conditions, the new, more specific ICDCM codes were rarely used in and but began to appear more regularly in For example, the strong upward trend in diabetes with acute and chronic complications is partially due to increasing use of codes for drug or chemical induced diabetes not available in ICDCM.

Likewise, refined codes, such as STEMI myocardial infarction of anterior wall available starting in , only began to appear in , and many new codes for preeclampsia introduced in were infrequently used before Our findings have important implications for interpreting differences in billing-code-derived disease prevalence over time.

For epidemiology, it is critical to distinguish between changes in actual disease prevalence and changes in coding behaviors and mappings, which are often responsible for observed changes in coded prevalence. We have seen that 3 separate, widely used classification systems made different distinctions that affected apparent diagnostic category prevalence. Given that HHS payment formulas rely on the prevalence of HCC categories to set billions of dollars in payments, our finding of many large artifactual changes in diagnostic category prevalence has potentially large implications for reimbursement.

Because the ACA uses risk adjustment to reallocate the available funds among plans in a given region rather than to decide on the size of the funds available as is done in Medicare Advantage and Part D , changes in diagnostic category prevalence may have had less financial effect in the marketplace than in Medicare Advantage. Classifications used for bonus or performance evaluation are also vulnerable to large changes in level or trend when preexisting ICDCM —derived formulas are used across the ICDCM transition.

In addition, claims-based analyses of disease prevalence may also be misleading if changes in the underlying classification system are not recognized. Our study used the earliest mappings accommodating all valid diagnoses for the included classification systems. In the meantime, it is important to understand the current mappings that will continue to be used to set payments and evaluate performance for several more years.

This study has several limitations. First, we only examined the association of diagnostic category prevalence with the ICDCM transition for individuals younger than 65 years who were privately insured by employer-sponsored insurance, a population mostly enrolled in relatively generous health plans. Coding patterns and discontinuities in frequencies of diagnostic categories may not generalize to individuals covered by other insurers eg, the ACA marketplace, Medicare, and Medicaid.

Many health care practitioners have been encouraged by their institutions to maximize the capture of patient complexity in their billing. However, our study data came from commercial plans whose payments are rarely risk adjusted for disease prevalence. Second, we did not examine changes at the ICDCM transition on coding for particular conditions for specific patients or in category prevalence based on other sources of diagnoses, such as electronic medical records.

Third, we used a piecewise linear model to look for changes in level and trend, but for some categories in which diagnostic category prevalence trends are not linear, our model may find changes at the transition when a nonlinear model would not. The findings of this interrupted time series analysis and cross-sectional study suggest that the transition to ICDCM in October was associated with changes in levels and trends for most diagnostic categories in 3 common diagnostic classification systems.

These 2 classification systems have been widely adopted by health care organizations for many purposes. Given the frequent, large discontinuities in diagnostic category prevalence rates that we identified, predictive models and diagnostic category mappings developed for ICDCM should be refined for ICDCM data to avoid unintended consequences for health care payment, performance assessment, or disease surveillance. Published: April 8, Corresponding Author: Randall P.

Author Contributions: Dr Ellis and Ms Song had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Conflict of Interest Disclosures: Dr Hsu reported receiving grants from the Agency for Healthcare Research and Quality during the conduct of the study. No other disclosures were reported. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

Dr Hsu, visual abstract editor for JAMA Network Open , was not involved in the editorial review of or the decision to publish this article. Additional Contributions: Brian C. They were supported by funding from this study but did not meet criteria for authorship. Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy Continue.

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This Issue. Views 3, Citations 6. Fracture healing, infection, and amputation rates correlate with the degree of soft tissue injury by Gustilo and helps determine the prognosis. In ICDCM a fracture not indicated as displaced or nondisplaced should be coded to displaced, and a fracture not designated as open or closed should be coded to closed. While the classification defaults to displaced for fractures, it is very important that complete documentation is encouraged.

However the treatment for nondisplaced fractures is coded to the procedure performed, such as casting Immobilization or inserting a pin Insertion.

A patient has a displaced, closed fracture of the greater trochanter of the right femur S The following codes would be assigned for this case all examples presume routine healing :.

The aftercare Z codes should not be used for aftercare for injuries or poisonings. The appropriate seventh characters are provided to identify this subsequent care. For aftercare of an injury, coders should assign the acute injury code with the appropriate seventh character "D" or expanded choices for fractures for subsequent encounter. This change will be significant for those post-acute settings that provide subsequent care for injuries.

Currently V codes are used to report physical therapy and other aftercare of fractures and injuries such as removing casts and dressings. Codes in categories T36—T65 are combination codes that include substances related to adverse effects, poisonings, toxic effects, and underdosing, as well as the external cause.

No additional external cause code is required for poisonings, toxic effects, adverse effects, and underdosing codes. ICDCM includes a table of drugs and chemicals; however, the columns have been restructured to group all poisoning columns together, followed by adverse effect and underdosing.

Coding professionals must refer back to the tabular list rather than coding directly from the table of drugs and chemicals.

Coding professionals may assign as many codes as necessary to describe all drugs and medicinal or biological substances. If two or more drugs and medicinal or biological substances are reported, code each individually unless the combination code is listed in the table of drugs and chemicals. Sequencing of codes from categories T36—T65 depends on the type of encounter.

The guidelines indicate the correct sequencing, but these notes are also found at the Tabular to guide the correct coding and sequencing. Coders should assign the appropriate code for adverse effect e. Use additional codes for all manifestations of adverse effects. Examples of manifestations are tachycardia, delirium, gastrointestinal hemorrhaging, vomiting, hypokalemia, hepatitis, kidney failure, or respiratory failure. The sequencing for coding an adverse effect is the nature of the adverse effect followed by the appropriate code for the adverse effect of the drug TT An example of the sequencing for an adverse effect is:.

When coding a poisoning or reaction to the improper use of a medication e. The sequencing for a toxic effect of substances chiefly nonmedicinal as to source TT65 is the same as for coding poisonings. Poisoning codes have an associated intent: accidental, intentional self-harm, assault, and undetermined. Use additional code s for all manifestations of poisonings. When no intent of poisoning is indicated, code to accidental.

Undetermined intent is only for use when there is specific documentation in the record that the intent of the poisoning cannot be determined. An example of the sequencing for a poisoning is:. It refers to taking less of a medication than is prescribed by a provider or a manufacturer's instruction.

For underdosing, assign the code from categories T36—T50 fifth or sixth character "6". Codes for underdosing should never be assigned as principal or first-listed codes. If a patient has a relapse or exacerbation of the medical condition for which the drug is prescribed because of the reduction in dose, then the medical condition should be coded.

Codes for noncompliance Z An example of the sequencing for underdosing is:. An exacerbation of congestive heart failure, the patient did not take his prescribed Lasix because of finances. ICDCM distinguishes between burns and corrosions. Burn codes apply to thermal burns except sunburns that come from a heat source, such as fire or hot appliance. They include electricity and radiation burns. Corrosions are burns due to chemicals.