Diagnosis code

In health care, diagnosis codes are used as a tool to group and identify diseases, disorders, symptoms, poisonings, adverse effects of drugs & chemicals, injuries and other reasons for patient encounters. Diagnostic coding is the translation of written descriptions of diseases, illnesses and injuries into codes from a particular classification. In medical classification, diagnosis codes are used as part of the clinical coding process alongside intervention codes. Both diagnosis and intervention codes are assigned by a health professional trained in medical classification such as a clinical coder or Health Information Manager.[1]

Several diagnosis classification systems have been implemented to various degrees of success across the world. The various classifications have a focus towards a particular patient encounter type such as emergency, inpatient, outpatient, mental health as well as surgical care. The International Statistical Classification of Diseases and Related Health Problems (ICD) is one of the most widely used classification systems for diagnosis coding as it allows comparability and use of mortality and morbidity data.[2]

As the knowledge of health and medical advances arise, the diagnostic codes are generally revised and updated to match the most up to date current body of knowledge in the field of health. The codes may be quite frequently revised as new knowledge is attained. DSM (see below) changes some of its coding to correspond to the codes in ICD. In 2005, for example, DSM changed the diagnostic codes for circadian rhythm sleep disorders from the 307-group to the 327-group; the new codes reflect the moving of these disorders from the Mental Disorders section to the Neurological section in the ICD [3]

Diagnostic coding systems

A number of diagnostic coding systems are implemented across the world to code the stay of patients within a typical health setting, such as a hospital. The following table provides a basic list of the coding systems in use as of approximately 2010:

Classification System Detail
ICD-9-CM Volumes 1 and 2 only. Volume 3 contains Procedure codes
ICD-10 The international standard since about 1998
ICPC-2 Also includes reasons for encounter (RFE), procedure codes and process of care
International Classification of Sleep Disorders
NANDA
Diagnostic and Statistical Manual of Mental Disorders Primarily psychiatric disorders
Online Mendelian Inheritance in Man Genetic diseases
Read code Used throughout United Kingdom General Practice computerised records
Systematized Nomenclature of Medicine (SNOMED) D Axis

Financial aspects of diagnostic coding

Diagnosis codes are generally used as a representation of admitted episodes in health care settings. The principal diagnosis, additional diagnoses alongside intervention codes essentially depict a patient's admission to a hospital.[4]

Diagnoses codes are subjected to ethical considerations as they contribute to the total coded medical record in health services areas such as a hospital. Hospitals that are based on Activity Based Funding and Diagnoses-Related Group Classification systems are often subjected to high end decision making that could affect the outcome of funding. It’s important to look at the scope of diagnoses codes in terms of their application in finance. The diagnoses codes in particular the Principal Diagnoses and Additional Diagnoses can significantly affect the total funding that a hospital may receive for any patient admitted.[5]

Ethically, this highlights the fact that the assignment of the diagnoses code can be influenced by a decision to maximize reimbursement of funding. For example, when looking at the activity based funding model used in the public hospital system in Victoria the total coded medical record is responsible for its reflected funding. These decisions also affect clinical documentation by physicians as recommendations from a Health Information Service can directly affect how a clinician may document a condition that a patient may have. The difference between the codes assigned for confusion and delirium can alter a hospitals DRG assignment as delirium is considered a higher level code than confusion within the ICD-10 coding hierarchy in terms of severity. A clinical coder or Health Information Manager may feel obliged to maximize funding above the ethical requirement to be honest within their diagnostic coding; this highlights the ethical standpoint of diagnoses codes as they should be reflective of a patient’s admission.[6]

Factors affecting accuracy in diagnostic coding

Accuracy is a major component in diagnoses codes. The accurate assignment of diagnoses codes in clinical coding is essential in order to effectively depict a patients stay within a typical health service area. A number of factors can contribute to the overall accuracy coding which includes medical record legibility, physician documentation, clinical coder experience, financial decision making, miscoding, as well as classification system limitations.

Medical record legibility

The legibility of a medical record is a contributing factor in the accuracy of diagnostic coding. The assigned proxy that is extracting information from the medical record is dependent on the quality of the medical record. Factors that contribute to a medical records quality are physician documentation, handwriting legibility, compilation of forms, duplication and inaccurate patient data. For example, if a clinical coder or Health Information Manager was extracting data from a medical record in which the principal diagnoses was unclear due to illegible handwriting, the health professional would have to contact the physician responsible for documenting the diagnoses in order to correctly assign the code. In Australia, the legibility of records has been sufficiently maintained due to the implementation of highly detailed standards and guidelines which aim to improve the legibility of medical records. In particular the paper medical record standard 'AS 2828' created by Standards Australia focuses on a few key areas that are critical to maintaining a legible paper medical record.[7]

The following criteria should be used as a guideline when creating a medical record specific to the aid of providing clear documentation for diagnostic coding. In particular the legibility of a medical record is dependent on 

  1. Durability: If a medical record wasn't durable, overtime if a coder was to revisit the record and it wasn't legible it wouldn't be feasible to code from that record.
  2. Ready Identification: A coder must be able to identify the exact record being coded in order to effectively extract diagnoses codes.
  3. Reproducible: A coder would need to make sure that the record is reproducible in that copies can be made to aid in effective coding.[8]
Clinical coder experience

The experience of the health professional coding a medical record is an essential variable that must be accounted for when analysing the accuracy of coding. Generally a coder with years of experience is able to extract all the relevant information from a medical record whether it is paper, scanned or semi-electronic. The diagnoses codes selected from the extraction are generally compiled and sequenced in order to represent the admission. An experienced coder may incorrectly assign codes due a lack of application of a classification systems relevant standards. An example to highlight clinical coding experience would be the standard within the Australian Coding Standards 0010 General Abstraction Guidelines.[9] These guidelines indicate that a coder must seek further detail within a record in order to correctly assign the correct diagnoses code. An inexperienced coder may simply just use the description from the discharge summary such as Infarction and may not use the correct detail which could be further found within the details of the medical record. This directly relates to the accuracy of diagnoses codes as the experience of the health professional coder is significant in its accuracy and contribution to finance.[10]

Weaknesses in diagnostic coding

Generally, coding is a concept of modeling reality with reduced effort, but with physical copying.

See also

References

  1. Hazelwood, A (2005). ICD-9-CM Diagnostic Coding and Reimbursement for Physician Services 2006 Edition (PDF). United States of America: American Health Information Management Association. p. 2.
  2. Steindel, S (20 May 2010). "International classification of diseases, 10th edition, clinical modification and procedure coding system: descriptive overview of the next generation HIPAA code sets". Journal of American Medical Informatics Association. 17 (3): 274–282. doi:10.1136/jamia.2009.001230. PMC 2995704Freely accessible. PMID 20442144.
  3. First, M (2005). "New Diagnostic Codes for Sleep Disorders". American Psychiatric Association. Retrieved 2008-08-08.
  4. "Victorian Hospital Admission Policy" (PDF). Department of Health. Retrieved 25 May 2013.
  5. Uzkuraitis, C; Hastings, K.; Torney, B. (2010). "Casemix funding optimisation: working together to make the most of every episode". Health Information Management Journal. 39 (3): 47–49.
  6. Lowe, A. "Casemix accounting systems and medical coding Organisational actors balanced on leaky black boxes". Journal of Organizational Change Management. 14 (1): 79–100. Retrieved 25 May 2013.
  7. Cheng, Ping; Gilchrist, Annette; Robinson, Kevin M; Paul, Lindsay (March 2009). "The Risk and Consequences of Clinical Miscoding Due to Inadequate Medical Documentation: A Case Study of the Impact on Health Services Funding". Health Information Management Journal. 38 (1): 35–46. doi:10.1177/183335830903800105. PMID 19293434.
  8. Standards, Australia. "Paper-based Health Record" (PDF). Standards Australia. Archived from the original (PDF) on March 5, 2016. Retrieved 30 May 2013.
  9. "OVERVIEW OF ICD-10-AM/ACHI/ACS". University of Wollongong. Retrieved 29 May 2013.
  10. O'Malley, K; Cook, K.; Price, M.; Wildes, K.; Hurdle, J.; Ashton, C. (2005). "Measuring Diagnoses: ICD Code Accuracy". Health Services Research. 40 (5): 1620–1639. doi:10.1111/j.1475-6773.2005.00444.x. PMC 1361216Freely accessible. PMID 16178999. Retrieved 25 May 2013.
  11. Towards Semantic Interoperability in Healthcare
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