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Clinical Classifications Software (CCS) for ICD-9-CM
The CCS is one of the HCUP tools that can be applied to HCUP and other similar databases. These tools are created by AHRQ through a Federal-State-Industry partnership.
Clinical Classifications Software (CCS) for ICD-9-CM

ICD-9-CM codes were frozen in preparation for ICD-10 implementation and regular maintenance of the codes has been suspended. The HCUP Tools for ICD-9-CM should only be used with data for discharges before 10/1/2015.

The Clinical Classifications Software (CCS) for ICD-9-CM is one in a family of databases and software tools developed as part of the Healthcare Cost and Utilization Project (HCUP),a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality. HCUP databases, tools, and software inform decision making at the national, State, and community levels.


The Clinical Classifications Software (CCS) for ICD-9-CM is a diagnosis and procedure categorization scheme that can be employed in many types of projects analyzing data on diagnoses and procedures. CCS is based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), a uniform and standardized coding system. The ICD-9-CM's multitude of codes - over 14,000 diagnosis codes and 3,900 procedure codes - are collapsed into a smaller number of clinically meaningful categories that are sometimes more useful for presenting descriptive statistics than are individual ICD-9-CM codes.

For example, CCS can be used to identify populations for disease- or procedure-specific studies or to develop statistical reports providing information (such as charges and length of stay) about relatively specific conditions. CCS was formerly called the Clinical Classifications for Health Policy Research (CCHPR).

The CCS now includes categories from the Clinical Classifications Software for Mental Health and Substance Abuse (CCS-MHSA). These categories replace the original CCS categories for mental health and substance abuse. More specifically, the CCS single-level software includes the CCS-MHSA general categories, and the CCS multi-level software includes the CCS-MHSA specific categories.

A special archival version of the single-level CCS for diagnoses is available for users doing longitudinal analysis involving past years. This version uses the original CCS format for mental health conditions (65-75), and applies it to the latest ICD-9-CM codes. The archival tool can be found in the ASCII program files download section below.

Empty Categories:
Please note that because of revisions to the CCS, single-level category 150 and multi-level categories and 9.8.1 do not contain any diagnosis codes as of FY 2008. Also, single-level category 260 does not contain any E Codes as of FY 2005.

Suicide E codes: Mechanism of Injury:
Suicide E Codes (external cause of injury codes) are assigned to CCS category 662, "Suicide and Self–Inflicted Injury". However, for users who wish to assign these E codes to a mechanism of injury CCS, an optional CCS category has been provided in the single-level diagnosis tool ($dxref 2013.csv) for each code. These optional CCS categories follow the CDC’s classification of E codes into mechanism of injury categories such as firearm or poisoning, Interested users should simply reassign suicide codes from category 662 to the optional secondary CCS categories as detailed in column five of $dxref 2013.csv. The code below gives an example of the reassignment process. Similar code can be used to reassign the CCS label:

Filename inraw "c:\tools\ccs\$DXREF 2013.csv" ;
/* Make a SAS format Using the Optional */
/* Suicide Mechansism CCS Category. */
/*****************************************/v data new;
      infile inraw dsd dlm=',' end = eof firstobs=3 missover;
         input start : $char5.
              Oldccs : $char4.
              Value1 : $char70.
              Value2 : $char70.
              Label : $char4.
              Value3 : $char70.
         retain hlo "   ";
      fmtname = "$ccs" ;
      type = "   " ;

      if eof then do ;
         start = "   " ;
         vlabel = "   " ;
         hlo = "o";
         output ;
      end ;
proc format cntlin = new ;
/* Reassign CCS to the Optional CCS for */
/* Suicide mechanism using SAS format. */
data test;
      Set ecodedata;
      Ccs = put(ecode,$ccs.)

For more information on the CCS, select to access the CCS Fact Sheet.

For downloading information, select to access the CCS Software and User's guide (which can be viewed in Portable Document Format).

This documentation contains:
  • A brief description of the CCS categorization scheme
  • Electronic files in ASCII format containing the translation of ICD-9-CM diagnosis and procedure codes into CCS categories. Note: There are no new diagnosis or procedure codes for FY 2015.
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The CCS documentation describes the electronic translation files, provides warnings about ICD-9-CM coding changes over time, and summarizes how to use the files.

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The HCUP CCS tool is used in the risk adjustment approach for CMS' readmission measures that are now part of the Hospital Readmissions Reduction Program (HRRP).

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Note: : There are no new diagnosis or procedure codes for FY 2015.

Shift-click from this Web page: Your browser may support loading the files for CCS and the Software and User's Guide from this Web page. To download the files from this Web page, click on the following links with the right mouse button and select "Save Link As" (Netscape) or "Save Target As" (Internet Explorer). After saving a file, find the file by using Windows® Explorer (Windows® 98/95/NT) or File Manager (Windows® 3.x) and then open it by double-clicking on it.

CCS Information

2015 CCS (ICD-9-CM) Software and User's Guide (PDF file, 250 KB)

Appendix A: Single-Level Diagnoses (txt file, 106 KB).

Appendix B: Single-Level Procedures (txt file, 37 KB).

Appendix C: Multi-Level Diagnoses (txt file, 184 KB).

Appendix D: Multi-Level Procedures (txt file, 111 KB).

CCS Category Names (Full Labels) (PDF file, 172 KB).

ASCII CCS Program Files for Use with SAS, STATA, or SPSS

Single Level CCS (ZIP file, 201 KB).

Multi-Level CCS (ZIP file, 104 KB).

Archival Single-Level CCS for Diagnoses (CSV file, 825 KB).

Stata CCS Program Files

Single-Level Diagnosis CCS Categories (ZIP file, 17 KB)

Single-Level Procedures CCS Categories (ZIP file, 14 KB)

Multi-Level Diagnoses CCS Categories (ZIP file, 10 KB)

Multi-Level Procedures CCS Categories (ZIP file, 10 KB)

History of ICD Code Corrections Made to the Single-Level CCS

ICD Code Corrections (PDF file, 245 KB)

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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): 1253-1262(10), October 2003.

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, 2010.

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: 55-63, 2001.

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): 187, February 2004. 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):284-9, May 2011.

Cook CB, Tsui C, Ziemer DC, Naylor DB, Miller WJ. Common reasons for hospitalization among adult patients with diabetes. Endocrine Practice, 12(4):363-70, July-August 2006.

Chou L. Estimating medical costs of gastroenterological diseases. World Journal of Gastroenterology, 10(2): 273-278, January 15, 2004.

Cook CB, Tsui C, Ziemer DC, Naylor DB, Miller WJ. Common reasons for hospitalization among adult patients with diabetes. Endocrine Practice, 12(4):363-70, July-August 2006.

Cowen ME, Strawderman RL. Quantifying the physician contribution to managed care pharmacy expenses. A random effects approach. Medical Care, 40(8):651-61, August 2002.

Cox, Cynthia; Dunn, Abe; Rittmueller, Lindsey; Whitmire, Bryn. A new way of measuring health costs sheds light on recent health spending trends. Exit Disclaimer (Accessed March 31, 2016.)

Davies BJ, Allareddy V, Konety BR. Effect of postcystectomy infectious complications on cost, length of stay, and mortality. Urology, 73(3):598-602, March 2009, Epub January 23, 2009.

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):2168-78, Oct 2015.

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):703-9, November 2009.

Dismuke CE. Underreporting of computed tomography and magnetic resonance imaging procedures in inpatient claims data. Medical Care, 43(7):713-717, July 2005.

Duffy, ME. The Agency for Healthcare Research and Quality: a valuable resource for evidence-based practice. Clinical Nurse Specialist, 19(3):117-120, May/June 2005.

Duffy SQ. "Substance Use and Mental Disorder Discharges from U.S. Community Hospitals in the Early 1990s, Revisited," Health Services Utilization by Individuals with Substance Abuse and Mental Disorders. December 2004. (Accessed November 17, 2005.)

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):625-34, 2002.

Farquhar CM, Steiner CA. Hysterectomy rates in the United States 1990-1997. Obstetrics & Gynecology, 99(2): 229-234, February 2002.

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):11-8, January-February 2008.

Fortino A. L’Utilizzo Degli ACC (CCS) Nella Rappresentazione Della Casistica Di Ricovero Ospedaliero. Ministero della Salute - Direzione Generale della Programmazione Sanitaria. (Accessed November 17, 2005.)

Fry DE, Pine M, Jones BL, Meimban RJ. Adverse outcomes in surgery: redefinition of postoperative complications American Journal of Surgery, 197(4):479-84, April 2009.

Fry DE, Pine M, Jones BL, Meimban RJ. Control charts to identify adverse outcomes in elective colon resection. American Journal of Surgery, 203(3):392-6, March 2012.

Guthery SL, Hutchings C, Dean JM, Hoff C. National estimates of hospital utilization by children with gastrointestinal disorders: analysis of the 1997 kids' inpatient database. The Journal of Pediatrics, 144(5):589-94, May 2004.

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):1970-6, October 2013.

Kannan VC, Andriamalala CN, Reynolds TA. The burden of acute disease in Mahajanga, Madagascar - a 21 month study. PLos One, 10(3):e0119029, Mar 2015.

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):157-65, Feb 2015.;jsessionid=8F79E451E767340DDBA67A93AAFEE2A4.f04t01.

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 2000 KIDS Inpatient Database. Pediatrics, 118(1):e167-73, July 2006, Epub 2006 Jun 12.

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):494-505, March 2009.

Magnan, Elizabeth. Algorithm for Identifying Patients with Multiple Chronic Conditions (Multimorbidity). Exit Disclaimer (accessed June 1st, 2015).

Missouri Department of Health and Senior Services, Emergency Room MICA Statistics. Exit Disclaimer (Accessed November 17, 2005.)

Murphy AJ, Axt JR, Lovvorn HN, 3rd. Associations between pediatric choledochal cysts, biliary atresia, and congenital cardiac anomalies. J Surg Res, 177(2):e59-63, October 2012.

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):640-5, December 2012.

Pressley JC, Barlow B. Child and adolescent injury as a result of falls from buildings and structures. Injury Prevention. 11; 267-273, 2005. 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):580-7, June 2008, Epub February 14, 2008.

Robinson JW. Regression tree boosting to adjust health care cost predictions for diagnostic mix. Health services research, 43(2):755-7, April 2008.

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, 1988-2010. Public Health, 129(2):173-81, Feb 2015.

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):689-96, July 2013.

Salvin, JW, Laussen, PC, Thiagarajan, RR. ECMO following cardiac surgery from the KID 2000 database. Pediatric Critical Care Medicine, 6(3):398, May 2005.

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 2001 abstract. (Accessed November 17, 2005.)

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 2004; 6(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):455-463, June 2014.

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):133-139, Sep 2014.

Thompson DA, Makary MA, Dorman T, Pronovost PJ. Clinical and economic outcomes of hospital acquired pneumonia in intra-abdominal surgery patients. Annals of Surgery, 243(4):547-52, April 2006.

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): 291-297, 2004.

Williams KA, Buechner JS. "Hospitalizations for Mental Health and Substance Abuse," Health By Numbers, 5(10), October 2003. (Accessed November 17, 2005.)

Yu W, Ravelo A, Wagner T, Barnett P. The relationships among age, chronic conditions, and healthcare costs. The American Journal of Managed Care, 10:909-916, 2004.

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, 1998, 36:1108-1113.

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; 1996. AHCPR Pub. No. 96-0047.

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; 1996. AHCPR Pub. No. 96 0017.

Elixhauser A, Steiner CA, Whittington C, et al. Clinical classifications for health policy research: Hospital inpatient statistics, 1995. Healthcare Cost and Utilization Project, HCUP 3 Research Note. Rockville, MD: Agency for Health Care Policy and Research; 1998. AHCPR Pub. No. 98-0049.

Elixhauser A, Steiner CA. Hospital inpatient statistics, 1996. Healthcare Cost and Utilization Project (HCUP) Research Note. Rockville, MD: Agency for Health Care Policy and Research; 1999. AHCPR Pub. No. 99-0034.

CCS categories are also used in HCUPnet, an online resource for national hospital stays.
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Questions regarding the CCS may be directed to HCUP User Support through the following channels:
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Internet Citation: HCUP CCS. Healthcare Cost and Utilization Project (HCUP). March 2017. Agency for Healthcare Research and Quality, Rockville, MD.
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Last modified 3/6/17