Magnitude of Impact, Overall and on Subspecialties, of Transitioning in Radiology from ICD-9 to ICD-10 Codes.

PURPOSE: Converting the nation's International Classification of Diseases (ICD) diagnosis coding system, from 14,025 ICD-9 to 69,823 ICD-10 codes, is projected to have enormous financial and operational implications. We aimed to assess the magnitude of impact that this code conversion will have on radiology claims. METHODS: The most frequently billed ICD-9 diagnosis codes for 588,523 radiology claims from five hospitals and affiliated outpatient sites during a 12-month period were mapped to matching ICD-10 codes using a Medicare-endorsed tool. The code-conversion impact factor was calculated for the entire radiology system, and each individual subspecialty division. RESULTS: Of all ICD-9 codes, only 3,407 (24.3%) were used to report any primary diagnosis. Of all claims, 50% were billed using just 37 (0.3%) primary codes; 75% with 131 (0.5%), and 90% with 348 (2.5%). Those 348 ICD-9 codes mapped onto 2,048 ICD-10 codes (5.9-fold impact), representing just 2.9% of all ICD-10 codes. By subspecialty, the conversion impact factor varied greatly, from 1.1 for breast (11 ICD-9 to 12 ICD-10 codes) to 28.8 for musculoskeletal imaging (146 to 4,199). The community division, reflecting a general practice mix, saw a conversion impact factor of 5.8 (254 to 1,471). CONCLUSIONS: Fewer than 3% of all ICD-9 and ICD-10 codes are used to report an overwhelming majority of all radiology claims. Although the number of commonly used codes will expand 5.9-fold overall, musculoskeletal imaging will experience a projected 28.8-fold explosion. Radiology practices should target their ICD educational and operational conversion efforts in an evidence-based manner.

ICD90CM claims data are insufficient for influenza surveillance.

Influenza and Influenza like illness are representative of a class of epidemic infectious diseases that have important public health implications. Early detection via Biosurveillance can speed life saving public heath responses. In the United States Biosurveillance is typically conducted using ICD9 coded visit diagnoses and uncoded chief complaint data. To determine the accuracy of ICD9 diagnoses using laboratory confirmed cases as the gold standard. We determined the sensitivity and specificity of ICD9 in detecting laboratory confirmed vs unconfirmed Influenza. ICD9-CM had a low 66.2% Positive Predictive Value (precision) for Influenza and a low 45.6% Sensitivity (recall) for Influenza. ICD9-CM proved insufficient alone for use in biosurveillance.

Office-based procedures among urban and rural family physicians in Ontario.

OBJECTIVE: To compare FP and GP performance of office-based procedures between urban and rural practices. DESIGN: Descriptive cohort study using health administrative data. SETTING: Ontario. PARTICIPANTS: All FPs and GPs who billed the Ontario Health Insurance Plan for at least 1 office-based procedure between January 1 and December 31, 2006 (N = 8648). MAIN OUTCOME MEASURES: Ontario Health Insurance Plan billings for office-based procedures were adjusted by full-time equivalent (FTE) so that the means are for 1 FTE. Office-based procedures were grouped into 1) surgical procedures, 2) injections and immunizations, 3) electrocardiograms (ECGs), and 4) venipunctures and laboratory tests. The analyses were stratified for FP and GP age, sex, rurality of practice, and participation in a primary care model. RESULTS: There were no substantial differences between FPs and GPs in rural practices compared with those in more urban practices with respect to surgical procedures. Rural FPs and GPs had lower mean numbers of injections and immunizations, ECGs, and venipunctures and laboratory tests than FPs and GPs practising in urban areas. Family physicians and GPs in primary care models had a lower mean number of surgical procedures but a higher adjusted mean number of injections and immunizations, ECGs, and venipunctures and laboratory tests. CONCLUSION: For those procedures that are not dependent on specialist backup or access to more advanced technology, there were no substantial differences between rural and urban FPs and GPs. All comprehensive FPs and GPs should be able to provide these services to their patients. Training programs for all family medicine residents should ensure future FPs and GPs are able to perform these procedures.

Ambulatory Patient Groups, Version 3.0--a classification system for payment of ambulatory visits.

The Ambulatory Patient Groups (APGs) are a patient classification system that was designed to be used as the basis of an Outpatient Prospective Payment System (OPPS). Although 6 major non-Medicare payers had implemented an APG-based OPPS between 1995 and 2000, the implementation of the Ambulatory Payment Classification (APC)-based Medicare OPPS shifted the focus of outpatient payment reform among payers to APC-based systems. Unfortunately, the APC OPPS is not really a prospective payment system and has become essentially a variant of a fee-for-service system. As a result, most major non-Medicare payers have rejected APCs as a model for outpatient payment reform and a renewed interest in the original APG OPPS design has occurred. This article reviews the basic components of an OPPS, compares and contrasts an APG- and APC-based OPPS, describes the differences between APG, Version 2.0, and APG, Version 3.0, and summarizes the key policy decisions payers will need to make in implementing an OPPS.

Admitting a patient "to" observation or "for" observation--what is the difference?

Coding and billing of a patient placed in "observation" status can be confusing, especially in a busy Emergency Department. If physicians know the rules related to observation status, they can avoid denials or accusations of false claims. Documenting either "admit to observation" or "admit for observation" can be interpreted differently for admission status and billing services. From a billing prospective, writing "admit for observation" would be interpreted as an inpatient admission (if the documentation throughout the medical record is consistent with inpatient status). If the order states "admit to observation," this normally would be interpreted as an order for outpatient observation. Physicians are encouraged to write admission orders that clearly state the level of services intended; for example, wording such as "place in outpatient observation" or "admit as inpatient," to clearly convey the physician's intent.