Icd 9 codes database

Icd 9 codes database DEFAULT

Diagnostic Code Descriptions (ICD-9)

All claims submitted by physicians to the Medical Services Plan (MSP) must include a diagnostic code. This information allows MSP to verify claims and generate statistics about causes of illness and death. The diagnostic codes used by MSP are based on the ninth revision of the International Classification of Diseases developed by the World Health Organization, commonly referred to as ICD9.

Note: when entering the diagnostic code into a claim record, be sure to left justify the code without the decimal point, but including leading zeros, and blank fill remaining spaces. Decimal points and other special characters are not recognized by the Teleplan system and will cause claims to be rejected. For more information, see the Teleplan Specifications manual (PDF, MB).

MSP's Index and Guide to 3-Digit and 4-Digit Diagnostic Code Descriptions is listed below by section.

Index (PDF, 38KB) 
-  Infection and Parasitic Diseases (PDF, 46KB)
- Neoplasms (PDF, 41KB)
- Endocrine, Nutritional and Metabolic Diseases and Immunity Disorders (PDF, 19KB)
- Diseases of Blood and Blood Forming Organs (PDF, 10KB)
- Mental Disorders (PDF, 15KB)
- Diseases of Nervous System and Sense Organs (PDF, 52KB)
- Diseases of the Circulatory System (PDF, 23KB)
- Diseases of the Respiratory System (PDF, 16KB)
- Diseases of the Digestive System (PDF, 24KB)
- Diseases of the Genitourinary System (PDF, 26KB)
- Complications of Pregnancy, Childbirth and the Puerperium (PDF, 30KB)
- Diseases of the Skin and Subcutaneous Tissue (PDF, 13KB)
- Diseases of the Musculoskeletal System and Connective Tissue (PDF, 25KB)
- Congenital Anomalies (PDF, KB)
- Certain Conditions Originating in the Perinatal Period (PDF, KB)
- Symptoms, Signs and Ill-defined Conditions (PDF, KB)
-  Injury and Poisoning (PDF, MB)
V01 - VSupplementary Factors Influencing Health Status and Contact with Health Services (PDF, 47KB)

Additional Diagnostic Codes (PDF, 9KB)

Sours: https://www2.gov.bc.ca/gov/content/health/practitioner-professional-resources/msp/physicians/diagnostic-code-descriptions-icd-9

For examples of how CCS has been used, see the following publications:

Ash AS, Posner MA, Speckman J; Franco S; Yacht AC; Bramwell L. Using claims data to examine mortality trends following hospitalization for heart attack in Medicare. Health Services Research, 38(5): (10), October

Alshekhlee A, Horn C, Jung R, Alawi AA, Cruz-Flores S. In-Hospital Mortality in Acute Ischemic Stroke Treated With Hemicraniectomy in US Hospitals. Journal of stroke and cerebrovascular diseases, June 22, http://www.ncbi.nlm.nih.gov/pubmed/

Bao Y, Sturm R. How do trends for behavioral health inpatient care differ from medical inpatient care in U.S. community hospitals? Journal of Mental Health Policy and Economics, 4: ,

Bynum JP, Rabins PV, Weller W, Niefeld, M, Anderson GF, Wu AW. The relationship between a dementia diagnosis, chronic illness, Medicare expenditures, and hospital use. Journal of the American Geriatrics Society, 52(2): , February https://www.ncbi.nlm.nih.gov/pubmed/Exit Disclaimer

Chi MJ, Lee CY, Wu SC. The prevalence of chronic conditions and medical expenditures of the elderly by chronic condition indicator (CCI). Arch Gerontol Geriatr, 52(3), May https://www.ncbi.nlm.nih.gov/pubmed/

Cook CB, Tsui C, Ziemer DC, Naylor DB, Miller WJ. Common reasons for hospitalization among adult patients with diabetes. Endocrine Practice, 12(4), July-August http://www.ncbi.nlm.nih.gov/pubmed/

Chou L. Estimating medical costs of gastroenterological diseases. World Journal of Gastroenterology, 10(2): , January 15,

Cook CB, Tsui C, Ziemer DC, Naylor DB, Miller WJ. Common reasons for hospitalization among adult patients with diabetes. Endocrine Practice, 12(4), July-August http://www.ncbi.nlm.nih.gov/pubmed/

Cowen ME, Strawderman RL. Quantifying the physician contribution to managed care pharmacy expenses. A random effects approach. Medical Care, 40(8), August

Cox, Cynthia; Dunn, Abe; Rittmueller, Lindsey; Whitmire, Bryn. A new way of measuring health costs sheds light on recent health spending trends. http://www.healthsystemtracker.org/insight/a-new-way-of-measuring-health-costs-sheds-light-on-recent-health-spending-trends/Exit Disclaimer(Accessed March 31, )

Davies BJ, Allareddy V, Konety BR. Effect of postcystectomy infectious complications on cost, length of stay, and mortality. Urology, 73(3), March , Epub January 23, http://www.ncbi.nlm.nih.gov/pubmed/

Derrington TM, Bernstein J, Belanoff C, Cabral HJ, Babakhanlou-Chase H, Diop H, Evans SR, Kotelchuck M. Refining measurement of substance use disorders among women of child-bearing age using hospital records: The development of the Explicit-Mention Substance Abuse Need for Treatment in Women (EMSANT-W) algorithm. Matern Child Health J, 19(10), Oct https://www.ncbi.nlm.nih.gov/pubmed/

Dinan MA, Chou CH, Hammill BG, Graham FL, Schulman KA, Telen MJ, Reed SD. Outcomes of inpatients with and without sickle cell disease after high-volume surgical procedures. American journal of hematology, 84(11), November http://www.ncbi.nlm.nih.gov/pubmed/

Dismuke CE. Underreporting of computed tomography and magnetic resonance imaging procedures in inpatient claims data. Medical Care, 43(7), July https://www.ncbi.nlm.nih.gov/pubmed/

Duffy, ME. The Agency for Healthcare Research and Quality: a valuable resource for evidence-based practice. Clinical Nurse Specialist, 19(3), May/June

Duffy SQ. "Substance Use and Mental Disorder Discharges from U.S. Community Hospitals in the Early s, Revisited," Health Services Utilization by Individuals with Substance Abuse and Mental Disorders. December (Accessed November 17, )

Farquhar CM, Naoom S, Steiner CA. The impact of endometrial ablation on hysterectomy rates in women with benign uterine conditions in the United States. Int J Technol Assess Health Care, 18(3), https://www.ncbi.nlm.nih.gov/pubmed/

Farquhar CM, Steiner CA. Hysterectomy rates in the United States Obstetrics & Gynecology, 99(2): , February

Fogerty MD, Abumrad NN, Nanney L, Arbogast PG, Poulose B, Barbul A. Risk factors for pressure ulcers in acute care hospitals. Wound repair and regeneration, 16(1), January-February http://www.ncbi.nlm.nih.gov/pubmed/

Fortino A. L�Utilizzo Degli ACC (CCS) Nella Rappresentazione Della Casistica Di Ricovero Ospedaliero. Ministero della Salute - Direzione Generale della Programmazione Sanitaria. http://www.salute.gov.it/imgs/C_17_pubblicazioni__allegato.pdf. (Accessed November 17, )

Fry DE, Pine M, Jones BL, Meimban RJ. Adverse outcomes in surgery: redefinition of postoperative complications American Journal of Surgery, (4), April https://www.ncbi.nlm.nih.gov/pubmed/

Fry DE, Pine M, Jones BL, Meimban RJ. Control charts to identify adverse outcomes in elective colon resection. American Journal of Surgery, (3), March https://www.ncbi.nlm.nih.gov/pubmed/

Guthery SL, Hutchings C, Dean JM, Hoff C. National estimates of hospital utilization by children with gastrointestinal disorders: analysis of the kids' inpatient database. The Journal of Pediatrics, (5), May http://www.ncbi.nlm.nih.gov/pubmed/

Goz V, Weinreb JH, McCarthy I, Schwab F, Lafage V, Errico TJ. Perioperative complications and mortality after spinal fusions: analysis of trends and risk factors. Spine, 38(22), October https://www.ncbi.nlm.nih.gov/pubmed/

Kannan VC, Andriamalala CN, Reynolds TA. The burden of acute disease in Mahajanga, Madagascar - a 21 month study. PLos One, 10(3):e, Mar https://www.ncbi.nlm.nih.gov/pmc/articles/PMC/.

Kindermann DR, Mutter RL, Houchens RL, Barrett ML, Pines JM. Emergency department transfers and transfer relationships in United States hospitals. Acad Emerg Med, 22(2), Feb http://onlinelibrary.wiley.com/doi//acem/abstract;jsessionid=8F79EEDDBA67A93AAFEE2A4.f04t

Kourtis AP, Paramsothy P, Posner SF, Meikle SF, Jamieson DJ. National estimates of hospital use by children with HIV infection in the United States: analysis of data from the KIDS Inpatient Database. Pediatrics, (1):e, July , Epub Jun http://www.ncbi.nlm.nih.gov/pubmed//.

Lee BJ, Mackey-Bilaver L, Goerge RM. The Patterns of Food Stamp and WIC Participation and Their Effects on Health of Low-Income Children. Chapin Hall Center for Children at the University of Chicago.

Machnicki G, Pinsky B, Takemoto S, Balshaw R, Salvalaggio PR, Buchanan PM, Irish W, Bunnapradist S, Lentine KL, Burroughs TE, Brennan DC, Schnitzler MA. Predictive ability of pretransplant comorbidities to predict long-term graft loss and death. American journal of transplantation, 9(3), March https://www.ncbi.nlm.nih.gov/pubmed/

Magnan, Elizabeth. Algorithm for Identifying Patients with Multiple Chronic Conditions (Multimorbidity).http://www.hipxchange.org/comorbiditiesExit Disclaimer(accessed June 1st, ).

Missouri Department of Health and Senior Services, Emergency Room MICA Statistics. (Accessed November 17, )

Murphy AJ, Axt JR, Lovvorn HN, 3rd. Associations between pediatric choledochal cysts, biliary atresia, and congenital cardiac anomalies. J Surg Res, (2):e, October https://www.ncbi.nlm.nih.gov/pmc/articles/PMC/pdf/nihmspdf.

Patil CG, Alexander AL, Hayden Gephart MG, Lad SP, Arrigo RT, Boakye M. A population-based study of inpatient outcomes after operative management of nontraumatic intracerebral hemorrhage in the United States. World Neurosurg, 78(6), December https://www.ncbi.nlm.nih.gov/pubmed/

Pressley JC, Barlow B. Child and adolescent injury as a result of falls from buildings and structures. Injury Prevention. 11; , http://ip.bmjjournals.com/cgi/reprint/11/5/ Exit Disclaimer

Radley DC, Gottlieb DJ, Fisher ES, Tosteson AN. Comorbidity risk-adjustment strategies are comparable among persons with hip fracture. Journal of clinical epidemiology, 61(6), June , Epub February 14, http://www.ncbi.nlm.nih.gov/pubmed/

Robinson JW. Regression tree boosting to adjust healthcare cost predictions for diagnostic mix. Health services research, 43(2), April http://www.ncbi.nlm.nih.gov/pubmed/

Rosenbaum BP, Kshettry VT, Kelly ML, Weil RJ. Diagnoses associated with the greatest years of political life lost for in-hospital deaths in the United States, Public Health, (2), Feb https://www.ncbi.nlm.nih.gov/pubmed/

Saber Tehrani AS, Coughlan D, Hsieh YH, Mantokoudis G, Korley FK, Kerber K. Rising annual costs of dizziness presentations to U.S. emergency departments. Academy of Emergency Medicine, 20(7), July https://www.ncbi.nlm.nih.gov/pubmed/

Salvin, JW, Laussen, PC, Thiagarajan, RR. ECMO following cardiac surgery from the KID database. Pediatric Critical Care Medicine, 6(3), May

Stukenborg G, Wagner DP, Dembling BP, Connors AF. A Method for Assessing the Risk of Influenza Attributable Rehospitalization. Academy for Health Services Research and Health Policy Annual Meeting abstract. (Accessed November 17, )

Swartz SH, Cowan TM, Batista IA. Using claims data to examine patients using practice-based Internet communication: Is there a clinical digital divide? Journal of Medical Internet Research; 6(1):e1. http://www.jmir.org//1/e1/. Exit Disclaimer

Tabak YP, Sun X, Nunez CM, Johannes RS. Using electronic health record data to develop inpatient mortality predictive model: Acute Laboratory Risk of Mortality Score (ALaRMS). Journal of the American Medical Informatics Association: JAMIA, 21(3), June https://www.ncbi.nlm.nih.gov/pmc/articles/PMC/pdf/amiajnlpdf.

Talsma A, Jones K, Guo Y, Wilson D, Campbell DA. The relationship between nurse staffing and failure to rescue: where does it matter most? Journal of patient safety, 10(3), Sep https://www.ncbi.nlm.nih.gov/pubmed/

Thompson DA, Makary MA, Dorman T, Pronovost PJ. Clinical and economic outcomes of hospital acquired pneumonia in intra-abdominal surgery patients. Annals of Surgery, (4), April http://www.ncbi.nlm.nih.gov/pubmed/

Wheeler EC, Klemm P, Hardie T, Plowfield L, Birney M, Polek C, Lynch KG. Racial disparities in hospitalized elderly patients with chronic heart failure. Journal of Transcultural Nursing, 15(4): ,

Williams KA, Buechner JS. "Hospitalizations for Mental Health and Substance Abuse," Health By Numbers, 5(10), October (Accessed November 17, )

Yu W, Ravelo A, Wagner T, Barnett P. The relationships among age, chronic conditions, and healthcare costs. The American Journal of Managed Care, ,

AHRQ Publications:

The CCS is used in AHRQ publications including:

References from Original CCS Documentation:

Cowen ME, Dusseau DJ, Toth BG, et al. Casemix adjustment of managed care claims data using the clinical classifications for health policy research method. Medical Care,,

Duffy SQ, Elixhauser A, Sommers JP. Diagnosis and procedure combinations in hospital inpatient data.Healthcare Cost and Utilization Project (HCUP 3) Research Note 5. Rockville, MD: Agency for Health Care Policy and Research; AHCPR Pub. No.

Elixhauser A, McCarthy EM. Clinical classifications for health policy research, version 2: Hospital inpatient statistics.Healthcare Cost and Utilization Project (HCUP 3) Research Note 1. Rockville, MD: Agency for Health Care Policy and Research; AHCPR Pub. No. 96

Elixhauser A, Steiner CA, Whittington C, et al. Clinical classifications for health policy research: Hospital inpatient statistics, Healthcare Cost and Utilization Project, HCUP 3 Research Note. Rockville, MD: Agency for Health Care Policy and Research; AHCPR Pub. No.

Elixhauser A, Steiner CA. Hospital inpatient statistics, Healthcare Cost and Utilization Project (HCUP) Research Note. Rockville, MD: Agency for Health Care Policy and Research; AHCPR Pub. No.

CCS categories are also used in HCUPnet,an online resource for national hospital stays.
Sours: https://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
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Inaccuracy of the International Classification of Diseases (ICDCM) in identifying the diagnosis of ischemic cerebrovascular disease

In administrative databases the International Classification of Diseases, Version 9, Clinical Modification (ICDCM) is often used to identify patients with specific diagnoses. However, certain conditions may not be accurately reflected by the ICD-9 codes. We assessed the accuracy of ICD-9 coding for cerebrovascular disease by comparing ICD-9 codes in an administrative database with clinical findings ascertained from medical record abstractions. We selected patients with ICD-9 diagnostic codes of through (in either the primary or secondary positions) from an administrative database of patients hospitalized in five academic medical centers in Medical records of the selected patients were reviewed by trained medical abstractors, and the patients' clinical conditions during the admission (stroke, TIA, asymptomatic) were recorded, as well as any history of cerebrovascular symptoms. Results of the medical record review were compared with the ICD-9 codes from the administrative database. More than 85% of those patients with the ICD-9 code were asymptomatic for the index admission. More than one-third of these asymptomatic patients did not undergo either cerebral angiography or carotid endarterectomy. For ICD-9 code , 85% of patients were classified as having a stroke and for ICD-9 code , 77% had TIAs. For code , 77% of patients were classified as having strokes. Limiting the identifying ICD-9 code to the primary position increased the likelihood of agreement with the medical record review. The ICD-9 coding scheme may be inaccurate in the classification of patients with ischemic cerebrovascular disease. Its limitations must be recognized in the analyses of administrative databases selected by using ICD-9 codes through

Sours: https://pubmed.ncbi.nlm.nih.gov//

International Classification of Diseases,Ninth Revision, Clinical Modification (ICDCM)

The International Classification of Diseases, Ninth Revision, Clinical Modification (ICDCM) is based on the World Health Organization’s Ninth Revision, International Classification of Diseases (ICD-9). ICDCM is the official system of assigning codes to diagnoses and procedures associated with hospital utilization in the United States. The ICD-9 was used to code and classify mortality data from death certificates until , when use of ICD for mortality coding started.

The ICDCM consists of:

  • a tabular list containing a numerical list of the disease code numbers in tabular form;
  • an alphabetical index to the disease entries; and
  • a classification system for surgical, diagnostic, and therapeutic procedures (alphabetic index and tabular list).

The National Center for Health Statistics (NCHS) and the Centers for Medicare and Medicaid ServicesExternal are the U.S. governmental agencies responsible for overseeing all changes and modifications to the ICDCM.

ICDCM on CD-ROM

The ICDCM Rom is unavailable.

Rich Text Format (RTF) Files

A version in Rich Text Format (RTF) of the edition is available for downloading from the Centers for Disease Control and Prevention’s (CDC)/FTP server.

ICDCM Files via FTP

ICDCM Addenda, Conversion Table, and Guidelines

Other Documents

Sours: https://www.cdc.gov/nchs/icd/icd9cm.htm

Codes database 9 icd

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ICD-10 Coding — Crosswalking ICD-9 to ICD-10

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Now discussing:

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