Health Language Blog

Medical Billing and Coding:  Exciting Changes Ahead

Posted on 07/20/16 | Comments

 

It’s an interesting time to be in healthcare, especially medical billing and coding! Over the next few years we will see major changes that will help us spend our healthcare dollars more wisely, and keep people healthier. These changes will have a profound impact on patients’ and physicians’ daily lives.

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Topics: ICD-10, Coding Challenges, LOINC & SNOMED, EHR, CPT, ACA, billing, icd-9

Three Considerations When Mapping Your Lab Catalogue

Posted on 06/03/13 | Comments

Logical Observation Identifiers Names and Codes (LOINC®) has been named as a standard in both Stage One and Stage Two Meaningful Use.  Earlier posts have discussed the utility and importance of LOINC as a standard.  LOINC has been used sporadically by some organizations, but full use of LOINC is coming into its own. 

As with the journey of a thousand miles, taking that first step on the catalog mapping project is truly the hardest part. To make your journey a bit easier, here are three first steps to consider: 

  • Do you understand LOINC?
  • Do you understand data?
  • What are the right resources and tools to use?
1.     Understanding LOINC

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Topics: Meaningful use, LOINC, Meaningful use stage 2, Meaningful use requirements, Coding Challenges, lab cataloguing

Terminology & Analytic Challenges for Accountable Care Organizations

Posted on 05/15/13 | Comments

Terminology__Analytic_Challenges_for_Accountable_Care_Organizations_(ACOs)

As the United States strives to get more value out of its health care expenditures, Accountable Care Organizations (ACOs) make sense. As both a clinician and a consumer of health services, I’m enthusiastic about providers, hospitals, and health plans jointly taking responsibility for providing holistic, coordinated, effective and efficient care. But given the at-risk nature of payments to ACOs, only organizations with the right scale of providers and patients – and the right information technology resources – are positioned to be successful ACOs.

ACOs need to analyze diverse streams of health information. Many organizations already make excellent use of administrative and claims data. As the quality of care is further emphasized in the ACO model, organizations increasingly need to analyze clinical data as well. These data are likely to come from a variety of EHRs using different data representations. For example:

  • Lab data can be crucial indicators of quality of care (for instance, hemoglobin A1c in diabetes, microbiology data for surveillance of postoperative infections). In today’s world, these data are largely represented as local laboratory codes. Although Meaningful Use 2 (MU-2) should increase the availability of LOINC-encoded laboratory results, organizations can’t wait for MU-2 to mine the wealth of laboratory data in existence.
  • For patients with chronic diseases, providing personalized support on medication use will be key to improving quality and outcomes. ACOs don’t just need to know whether doctors prescribed the right drugs – they need to know whether patients with chronic diseases are filling those drugs, and if not, why not? With electronic prescribing, organizations can access burgeoning data on drugs prescribed and drugs actually dispensed. But these data often come in incompatible proprietary formats (Medi-Span, FDB, Multum) that need to be reconciled.

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Topics: Analytics, Coding Challenges, terminology services, health information, medical data

A Guide to Different Types of Data that Need to be Normalized

Posted on 01/29/13 | Comments

Practicing internal medicine in an academic medical center, I’ve found that maintaining a concise and complete active problem list for patients is becoming a mark of “good citizenship.” Trying to maintain a problem-oriented medical record certainly isn’t new, but in the days of shadow charts and siloed systems, updating an institutional problem list for patients was mostly a matter of good intentions and meeting accreditation requirements. Now that my colleagues and I share a truly comprehensive EHR, the problem list is something we rely on every day in providing comprehensive and well-coordinated care. We’re also beginning to see the problem list get even more visibility as it becomes the basis for electronic quality measures on our performance and our institution’s.

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Topics: LOINC, Coding Challenges, RxNorm

The Significance of Normalizing Your Data to the Future of Healthcare

Posted on 01/24/13 | Comments

On January 10, the Centers for Medicare and Medicaid Services (CMS) announced the formation of 106 new Accountable Care Organizations (ACOs), bringing the grand total to more than 250 ACOs. Comprised of physicians, hospitals and health systems, each of these ACOs must be able to exchange data on the designated population of Medicare patients included in the CMS program. What’s more, they need to be able to analyze the data to determine if they are meeting 33 distinct quality measures concerning care coordination, patient safety, preventive health services, at-risk populations, and patient/caregiver experience of care.

However, if the stakeholders in these ACOs aren’t all sharing and analyzing data that uses the same data terminologies, their success could be impacted. This is where data “normalization” comes in. It can greatly improve operational efficiencies and patient outcomes not just for ACOs, but for all healthcare providers and payers nationwide.

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Topics: Meaningful use, ICD-10, HIE, Coding Challenges, Data Warehousing