DATA COLLECTION GUIDE Colorectal Cancer Screening 2015 (07/01/2014 to 06/30/2015 Dates of Service) 1
Table of Contents Overview of the Process and Timeline 3 Measure Specifications 4 Summary of Changes 5 Codes to Identify Patients who underwent Colorectal Cancer Screening Tests 8 Table 1: CPT Procedure Codes for Identifying Colonoscopies 8 Table 2: ICD-9 Procedure Codes for Identifying Colonoscopies 9 Table 3: HCPCS Codes for Identifying Colonoscopies 9 Table 4: CPT Procedure Codes for Identifying Sigmoidoscopies 9 Table 5: ICD-9 Procedure Codes for Identifying Sigmoidoscopies 10 Table 6: HCPCS Codes for Identifying Sigmoidoscopies 10 Table 7: CPT Procedure Codes for Identifying Stool Tests 11 Table 8: HCPCS Codes for Identifying Stool Tests 11 Table 9: LOINC Codes for identifying stool tests 11 Codes Used to Identify Patients who Meet Exclusion Criteria 12 Table 10: CPT Procedure Codes for Identifying Total Colectomy 12 Table 11: ICD-9 Procedure Codes for Identifying Total Colectomy 12 Table 12: ICD-9 Diagnosis Codes for Identifying Colorectal Cancer 13 Table 13: HCPCS Codes for Identifying Colorectal Cancer 13 Table 14: CPT Procedure Codes for Identifying CT Colonographies 14 Measure Logic and Flow Chart 15 16 Data Collection and Submission Preparations and Considerations 17 Section A: Identifying the Patient Population (Denominator) 19 Section B: Data Collection 24 Data Elements and Field Specifications 26 Section C: Data File Creation 35 Section D: Exclusions File and Data File Submission 36 Section E: Data Validation 42 Appendices 44 Appendix A: Description of the Measure 45 Appendix B: MNCM Data Portal Registration 46 Appendix C: Resources to Help You Get Started 47 Appendix D: Sampling Methods 48 Appendix E: About 50 Appendix F: About MN Community Measurement and Measure Development 52 2
Overview of the Process and Timeline Process Step Registration Medical group registers clinics and providers on the MNCM Data Portal and electronically signs the Site Terms of Use Agreement and Business Associate Agreement. Resources: Download Clinic & Provider Registration Instructions from the RESOURCES Tab on the MNCM Data Portal or MNCM.org. NOTE: If you have already registered for 2015, you do not need to register again. If you have already registered but have had changes in your clinics (e.g., one of the clinics closed), contact MNCM to discuss appropriate changes. If you have not registered, you must do so before you can submit data. Pre-Submission Data Certification (formerly Denominator Certification) Medical groups submit a pre-submission data certification form outlining the method for identifying the initial patient population on the MNCM Data Portal. MNCM reviews and approves the method. MNCM must approve the presubmission data certification form prior to data collection. Resources: Download Colorectal Cancer Screening 2015 Pre-Submission Data Certification Form from the RESOURCES Tab on the MNCM Data Portal. Data Collection and Submission Data collection begins after the billing cycle is completed for the measurement period. Medical group prepares CSV file to submit via the MNCM Data Portal. Resources: Download Colorectal Cancer Screening 2015 Data Collection Guide and Colorectal Cancer Screening 2015 Data Collection Spreadsheet Template from the RESOURCES Tab on the MNCM Data Portal. Preliminary Results Review and Quality Checks Medical group reviews the preliminary results available on the MNCM Data Portal to verify the rates are as expected; provides information on rate or population changes. MNCM then reviews the preliminary results and comments. Resources: HOME tab, Data Submission (scroll to Data Comparison Tool). Data Validation MNCM auditor conducts an audit to validate the submitted data matches the source data in the patient medical record. Resources: MNCM will e-mail instructions and post a list of randomly-selected patients for audit on the MNCM Data Portal. Two-Week Medical Group Review and Comment Period Medical groups review preliminary results of all medical groups along with statewide results. This is the final opportunity to verify results before public reporting on MNHealthScores.org. Resources: MNCM will e-mail information and directions to all appropriate medical group contacts registered on the MNCM Data Portal. Data Results After the successful submission and validation of the clinical data, MNCM will post the results on MNHealthScores.org. Helpful Information and Dates to Remember Registration occurs annually during December/January Contact MNCM if your clinic did not register at support @mncm.org Registration must be completed before data submission can occur Submit denominator document in June 2015 MNCM Data Portal opens for data submission July 13, 2015 MNCM Data Portal closes August 14, 2015 Completed by medical groups after data submission (prior to validation audit) A MNCM auditor will contact the medical group to schedule the validation audit after the data file is submitted. October 2015 Late 2015 3
(07/01/2014 to 06/30/2015 Dates of Service) Measure Specifications 4
Measure Specifications Summary of Changes Clarification of Eligible Providers All Advanced Practice Registered Nurses are eligible providers. This includes, but is not limited to, Certified Nurse Practitioner, Certified Nurse Specialist, and Certified Nurse Midwife. Description Methodology Rationale A measure of the percentage of patients who are up-to-date with appropriate colorectal cancer screening exams. Population identification is accomplished via a query of a practice management system or Electronic Medical Record (EMR) to identify the population of eligible patients (denominator). Data elements are either extracted from an EMR system or abstracted through medical record review. Full population is required for clinics that had an EMR in place by 07/01/2013. Cancer of the colon and rectum is one of the most prevalent forms of cancer, representing 8.6% of all new cancer cases in the U.S. and the second leading cause of cancer-related deaths for both men and women. The burden of colorectal cancer rests primarily in older adults. Over 70% of all deaths due to colorectal cancer occur in adults over the age of 65. At an aggregated level, about 4.8% of all Americans will be diagnosed with colorectal cancer at some point in their lives, but specific populations will be effected at different rates with men more likely to acquire than women, rural populations having higher incidence rates than urban and American Indian populations seeing incidence rates far greater than other race/ethnicity groups. The colorectal cancer screening measure currently reported by MN Community Measurement comes from the NCQA s HEDIS colorectal cancer screening rate measure. The measure reports the percentage of patients within a medical group who have received colorectal cancer screening during a 12 month period by capturing the entire population age 51 to 75 years with screening tests either within the reporting period or in the medical history as dictated by the test type. Populations not represented by the current HEDIS rate include patients who have Medicaid insurance and Medicare Fee For Service patients. Unlike many cancers, colorectal cancer develops in a largely predictable progressive pattern where a small tissue growth in the large intestine can turn cancerous over a period of several months to several years. Screening for colorectal cancer to identify and remove these growths is believed to account for the biggest potential reduction in mortality rates. Preventing the incidence and mortality for colorectal cancer has been a key focus of several state and nationwide initiatives, including Healthy People 2010, the Minnesota Cancer Alliance, and the American Cancer Society. This measure has the following benefits: a) Can capture screening rates at a clinic site level; b) Can more appropriately capture the entire patient population in a clinic s case mix by including Medicare Fee For Service and Medicaid patients; and c) Will potentially allow for a real impact on the burden and mortality of colorectal cancer due to early detection and prevention associated with increased screening. 5
Measure Specifications Measurement Period Measurement period will be a fixed 12-month period: 07/01/2014 to 06/30/2015. Denominator Patients who meet each of the following criteria are included in the population: Patient was age 51 to 75 years at the end of the measurement period (date of birth was on or between 07/01/1939 to 06/30/1964). Patient was seen by an eligible provider in an eligible specialty face-to-face visit at least two times during the last two measurement periods (07/01/2013 to 06/30/2015). Use this date of service range when querying the practice management or EMR system to allow a count of the visits. Patient was seen by an eligible provider in an eligible specialty face-to-face visit at least one time during the measurement period (07/01/2014 to 06/30/2015). Eligible specialties: Family Medicine, General Practice, Internal Medicine, Geriatric Medicine, Obstetrics/Gynecology Allowable Exclusions Eligible providers: Medical Doctor (MD), Doctor of Osteopathy (DO), Physician Assistant (PA), Advanced Practice Registered Nurses (APRN) The following are allowable exclusions: Patient was in hospice at any time during the measurement period. Patient died prior to the end of the measurement period. Patient with history of any of the following diagnoses: o Total colectomy (CPT procedure codes 44150 to 44153, 44155 to 44158, 44210 to 44212 and/or ICD-9 procedure codes 45.81 to 45.83; See Tables 10 and 11). o Colorectal cancer (ICD-9 diagnosis codes 153.0 to 153.9, 154.0, 154.1, 197.5, V10.05 and/or HCPCS codes G0213 to G0215, G0231; See Tables 12 and 13). Patient had a CT Colonography (CPT procedure codes 74261to 74263, 0066T, 0067T; See Table 14) screening examination performed in the measurement period or four years prior to the measurement period (07/01/2010 to 06/30/2015). Numerator The number of patients who were up-to-date with appropriate colorectal cancer screening exams. Appropriate exams include colonoscopy, sigmoidoscopy, or fecal blood tests as outlined below. Note: Date of referral-only not accepted, providers must be able to produce documentation that the colonoscopy was completed (e.g. consult letter, procedure note, or patient self-report). COLONOSCOPY within the measurement period or prior nine years (Valid dates = 07/01/2005 to 06/30/2015). Using claims codes: Provide the service date associated with the codes for a colonoscopy. See Tables 1 to 3. o Accepted colonoscopy CPT procedure codes: 44388 to 44394, 44397, 45355, 45378 to 45387, 45391, 45392. 6
Measure Specifications o Accepted colonoscopy ICD-9 procedure codes: 45.22, 45.23, 45.25, 45.42, 45.43. o Accepted colonoscopy HCPCS codes: G0105, G0121. OR Using an electronic medical record: Provide the date field associated with the date of the colonoscopy procedure. SIGMOIDOSCOPY within the measurement period or prior four years (Valid dates = 07/01/2010 to 06/30/2015). See Tables 4 to 6. Using claims codes: Provide the service date and code associated with the sigmoidoscopy procedure. o Accepted sigmoidoscopy CPT procedure codes: 45330 to 45335, 45337 to 45342, 45345. o Accepted sigmoidoscopy ICD-9 procedure codes: 45.24. o Accepted sigmoidoscopy HCPCS codes: G0104. OR Using an electronic medical record: Provide the date field associated with the date of the sigmoidoscopy procedure. STOOL BLOOD TESTS within the measurement period (07/01/2014 to 06/30/2015). Acceptable stool tests: guaiac FOBT (gfobt) and fecal immunochemical test (FIT). Must be done within the measurement period (valid dates = 07/01/2014 to 06/30/2015). Using claims codes: Provide service date and code associated with the stool test. See Tables 7 to 9. o Accepted CPT procedure codes: 82270, 82274. o Accepted HCPCS codes: G0328. o Accepted LOINC codes: 2335-8, 12503-9, 12504-7, 14563-1, 14564-9, 14565-6, 27396-1, 27401-9, 27925-7, 27926-5, 29771-3, 56490-6, 56491-4, 57905-2, 58453-2. OR Using an electronic medical record: Provide the name of the test used and date field associated with the date of the order of the stool test. 7
Measure Specifications Codes to Identify Patients who underwent Colorectal Cancer Screening Tests Table 1: CPT Procedure Codes for Identifying Colonoscopies CPT Procedure Code CPT Procedure Code Description 44388 Colonoscopy through stoma; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure) 44389 Colonoscopy through stoma; with biopsy or multiple 44390 Colonoscopy through stoma; with removal of foreign body 44391 Colonoscopy through stoma; with control of bleeding (e.g., injection, bipolar cautery, unipolar cautery, laser, heater probe, stapler, plasma coagulator) 44392 Colonoscopy through stoma; with removal of tumor(s), polyp(s), or other lesion(s) by hot biopsy forceps or bipolar cautery 44393 Colonoscopy through stoma; with ablation of tumor(s), polyp(s), or other lesion(s), not amenable to removal by hot biopsy forceps, bipolar cautery or snare technique 44394 Colonoscopy through stoma; with removal of tumor(s), polyp(s), or other lesion(s) by snare technique 44397 Colonoscopy through stoma; with transendoscopic stent placement (includes predilation) 45355 Colonoscopy, rigid or flexible, transabdominal via colotomy, single or multiple 45378 Colonoscopy, flexible, proximal to splenic flexure; diagnostic, with or without collection of specimen(s) by brush or washing, with or without colon decompression 45379 Colonoscopy, flexible, proximal to splenic flexure; with removal of foreign body 45380 Colonoscopy, flexible, proximal to splenic flexure; with biopsy, single or multiple 45381 Colonoscopy, flexible, proximal to splenic flexure; with directed submucosal injection(s), any substance 45382 Colonoscopy, flexible, proximal to splenic flexure; with control of bleeding (e.g., injection, bipolar cautery, unipolar cautery, laser, heater probe, stapler, plasma coagulator) 45383 Colonoscopy, flexible, proximal to splenic flexure; with ablation of tumor(s), polyp(s), or other lesion(s) not amenable to removal by hot biopsy forceps, bipolar cautery or snare technique 45384 Colonoscopy, flexible, proximal to splenic flexure; with removal of tumor(s), polyp(s), or other lesion(s) by hot biopsy forceps or bipolar cautery 45385 Colonoscopy, flexible, proximal to splenic flexure; with removal of tumor(s), polyp(s), or other lesion(s) by snare technique 45386 Colonoscopy, flexible, proximal to splenic flexure; with dilation by balloon, 1 or more 8
Measure Specifications CPT Procedure Code CPT Procedure Code Description strictures 45387 Colonoscopy, flexible, proximal to splenic flexure; with transendoscopic stent placement (includes predilation) 45391 Colonoscopy, flexible, proximal to splenic flexure; with endoscopic ultrasound examination 45392 Colonoscopy, flexible, proximal to splenic flexure; with transendoscopic ultrasound guided intramural or transmural fine needle aspiration/biopsy(s) Table 2: ICD-9 Procedure Codes for Identifying Colonoscopies ICD-9 Procedure Code ICD-9 Procedure Code Description 45.22 Endoscopy of large intestine through artificial stoma 45.23 Colonoscopy 45.25 Closed [endoscopic] biopsy of large intestine 45.42 Endoscopic polypectomy of large intestine 45.43 Endoscopic destruction of other lesion or tissue of large intestine Table 3: HCPCS Codes for Identifying Colonoscopies HCPCS Code HCPCS Code Description G0105 G0121 Colorectal cancer screening; colonoscopy on individual at high risk Screening colonoscopy, patients at average risk Table 4: CPT Procedure Codes for Identifying Sigmoidoscopies CPT Procedure Code CPT Procedure Code Description 45330 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure) 45331 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with biopsy, single or multiple 45332 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with removal of foreign body 45333 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with removal of tumor(s), polyp(s), or other lesion(s) by hot biopsy forceps or bipolar cautery 9
Measure Specifications CPT Procedure Code CPT Procedure Code Description 45334 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with control of bleeding (e.g. Injection, bipolar cautery, unipolar cautery, laser, heater probe, stapler, plasma coagulator) 45335 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with directed submucosal injection(s), any substance 45337 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with decompression of volvulus, any method 45338 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with removal of tumor(s), polyp(s), or other lesion(s) by snare technique 45339 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with ablation of tumor(s), polyp(s), or other lesion(s) not amenable to removal by hot biopsy forceps, bipolar cautery or snare techniques 45340 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with dilation by balloon, 1 or more strictures 45341 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with endoscopic ultrasound examination 45342 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with transendoscopic ultrasounds guided intramural or transmural fine needle aspiration/biopsy(s) 45345 Sigmoidoscopy, flexible; diagnostic, with or without collection of specimen(s) by brushing or washing (separate procedure); with transendoscopic stent placement (includes predilation) Table 5: ICD-9 Procedure Codes for Identifying Sigmoidoscopies ICD-9 Procedure Code ICD-9 Procedure Code Description 45.24 Flexible sigmoidoscopy Table 6: HCPCS Codes for Identifying Sigmoidoscopies HCPCS Code HCPCS Code Description G0104 Colorectal cancer screening; flexible sigmoidoscopy 10
Table 7: CPT Procedure Codes for Identifying Stool Tests CPT Procedure Code Colorectal Cancer Screening 2015 Measure Specifications CPT Procedure Code Description 82270 Blood, occult, by peroxidase activity (e.g. guaiac), qualitative, feces, consecutive collected specimens with single determination, for colorectal neoplasm screening (i.e. patient was provided 3 cards or single triple card for consecutive collection) 82274 Blood, occult, by peroxidase activity (e.g. guaiac), qualitative, feces, 1-3 simultaneous determinations, performed for other than colorectal neoplasm screening Table 8: HCPCS Codes for Identifying Stool Tests HCPCS Code HCPCS Code Description G0328 Colorectal cancer screening; fecal occult blood test, immunoassay, 1-3 simultaneous Table 9: LOINC Codes for identifying stool tests LOINC Code LOINC Code Description 2335-8 Hemoglobin.gastrointestinal 12503-9 Hemoglobin.gastrointestinal^4th specimen 12504-7 Hemoglobin.gastrointestinal^5th specimen 14563-1 Hemoglobin.gastrointestinal^1st specimen 14564-9 Hemoglobin.gastrointestinal^2nd specimen 14565-6 Hemoglobin.gastrointestinal^3rd specimen 27396-1 Hemoglobin.gastrointestinal 27401-9 Hemoglobin.gastrointestinal^6th specimen 27925-7 Hemoglobin.gastrointestinal^7th specimen 27926-5 Hemoglobin.gastrointestinal^8th specimen 29771-3 Hemoglobin.gastrointestinal 56490-6 Hemoglobin.gastrointestinal^2nd specimen 56491-4 Hemoglobin.gastrointestinal^3rd specimen 57905-2 Hemoglobin.gastrointestinal^1st specimen 58453-2 Hemoglobin.gastrointestinal 11
Measure Specifications Codes Used to Identify Patients who Meet Exclusion Criteria Table 10: CPT Procedure Codes for Identifying Total Colectomy CPT Procedure Code CPT Procedure Code Description 44150 Colectomy, total, abdominal, without proctectomy; with ileostomy or ileoproctostomy 44151 Colectomy, total, abdominal, without proctectomy; with continent ileostomy 44152 Colectomy, total, abdominal, with proctectomy; with ileoanal anastomosis, includes loop ileostomy, and rectal mucosectomy, when performed 44153 Colectomy, total, abdominal, with proctectomy; with ileoanal anastomosis, creation of ileal reservoir [S or J], includes loop ileostomy, and rectal mucosectomy, when performed 44155 Colectomy, total, abdominal, with proctectomy; with ileostomy 44156 Colectomy, total, abdominal, with proctectomy; with continent ileostomy 44157 Colectomy, total, abdominal, with proctectomy; with ileoanal anastomosis, includes loop ileostomy, and rectal mucosectomy, when performed 44158 Colectomy, total, abdominal, with proctectomy; with ileoanal anastomosis, creation of ileal reservoir (S or J), includes loop ileostomy, and rectal mucosectomy, when performed 44210 Laparoscopy, surgical; colectomy, total, abdominal, without proctectomy, with ileostomy or ileoproctostomy 44211 Laparoscopy, surgical; colectomy, total, abdominal, with proctectomy, with ileoanal anastamosis, creation of ileal reservoir (S or J), with loop ileostomy, includes rectal mucosectomy, when performed 44212 Laparoscopy, surgical; colectomy, total, abdominal, with proctectomy, with ileostomy Table 11: ICD-9 Procedure Codes for Identifying Total Colectomy ICD-9 Procedure Code ICD-9 Procedure Code Description 45.81 Total intra-abdominal colectomy 45.82 Open total intra-abdominal colectomy 45.83 Other and unspecified total intra-abdominal colectomy 12
Measure Specifications Table 12: ICD-9 Diagnosis Codes for Identifying Colorectal Cancer ICD-9 Diagnosis Code ICD-9 Diagnosis Code Description 153.0 Malignant neoplasm of the colon, hepatic flexure 153.1 Malignant neoplasm of the colon, transverse flexure 153.2 Malignant neoplasm of the colon, descending colon 153.3 Malignant neoplasm of the colon, sigmoid colon 153.4 Malignant neoplasm of the colon, cecum 153.5 Malignant neoplasm of the colon, appendix 153.6 Malignant neoplasm of the colon, ascending colon 153.7 Malignant neoplasm of the colon, splenic flexure 153.8 Malignant neoplasm of the colon, other specified site of large intestine 153.9 Malignant neoplasm of the colon, unspecified 154.0 Malignant neoplasm of rectum, rectosigmoid junction, and anus; Rectosigmoid junction 154.1 Malignant neoplasm of rectum, rectosigmoid junction, and anus; Rectum 197.5 Secondary malignant neoplasm of respiratory and digestive systems; Large intestine and rectum V10.05 Personal history of malignant neoplasm; Gastrointestinal tract; Large intestine Table 13: HCPCS Codes for Identifying Colorectal Cancer HCPCS Code HCPCS Code Description G0213 G0214 Pet imaging whole body; diagnosis; colorectal Pet imaging whole body; initial staging; colorectal G0215 Pet imaging whole body; restaging; colorectal cancer (replaces g0163) G0231 Pet, whole body, for recurrence of colorectal or colorectal metastatic cancer; gamma cameras only 13
Measure Specifications Table 14: CPT Procedure Codes for Identifying CT Colonographies CPT Procedure Code CPT Procedure Code Description 74261 Computed tomographic (CT) colonography, diagnostic, including image post processing; without contrast material 74262 Computed tomographic (CT) colonography, diagnostic, including image post processing; with contrast material(s) including non-contrast images, if performed 74263 Computed tomographic (CT) colonography, screening, including image post processing 0066T 0067T Computed tomographic colonography (i.e., virtual colonoscopy); screening Computed tomographic colonography (i.e., virtual colonoscopy); diagnostic 14
Measure Specifications Measure Logic and Flow Chart Is the patient s DOB between 07/01/1939 and 06/30/1964? No PATIENT NOT INCLUDED IN MEASURE Yes Has the patient had two office visits between 07/01/2013 to 06/30/2015 with at least one office visit between 07/01/2014 to 06/30/2015? No 2015 Colorectal Cancer Screening Measure Flow Chart Please see the Data Elements and Field Specifications Tables for more detailed information about each component. Yes PATIENT INCLUDED IN DENOMINATOR Did the patient have a colonoscopy between the dates of 07/10/2005 to 06/30/2015? Yes PATIENT NUMERATOR COMPLIANT No Yes Did the patient have a sigmoidosocopy between the dates of 07/01/2010 to 06/30/2015? Yes No Yes No Did the patient have a stool blood test between the dates of 07/01/2014 to 06/30/2015? Yes Is the stool blood test a FIT? Yes Did the patient have one or more stool tests returned? No PATIENT NOT NUMERATOR COMPLIANT No Is the stool blood test a gfobt? No Yes Did the patient have three or more stool tests returned? No 15
(07/01/2014 to 06/30/2015 Dates of Service) 16
Data Collection and Submission Preparations and Considerations Before collecting and submitting data to MNCM, please review: Data submission preparations: Your medical group and clinics MUST BE REGISTERED in the MNCM Data Portal. See Appendix B for more information. Save the MNCM websites in your Favorites internet folder for future reference. o o o MNCM Data Portal: https://data.mncm.org/login MNCM Corporate website: MNCM.org MNCM Consumer-facing website: MNHealthScores.org Create a folder in your network drive dedicated to all data submission documents. o Save all spreadsheets, forms and data submission materials in the dedicated folder. Name versions of documents clearly so you are using the most recent files. Log in to the MNCM Data Portal at https://data.mncm.org/login. See Appendix C for more resources to help you get started. In the RESOURCES tab of the MNCM Data Portal, you are able to access and download the following items: o o o o o Patient Attribution: Colorectal Cancer Screening 2015 Data Collection Guide Colorectal Cancer Screening 2015 Pre-Submission Data Certification Form Colorectal Cancer Screening 2015 Data Collection Form Colorectal Cancer Screening 2015 Data Collection Spreadsheet Template Colorectal Cancer Screening 2015 Exclusions Template A patient is attributed to one clinic and one provider within the medical group that are considered responsible for managing the patient s care. This method was developed in order to capture and attribute all eligible patients. Use the following attribution methods in order: 1. First, attribute the patient to the clinic and provider within your medical group that are assigned to the patient OR are responsible for the patient s care. If the patient does not have an assigned clinic or provider within your medical group, then 2. Attribute the patient to the clinic and provider within your medical group that saw the patient most often in the measurement period. If more than one provider saw the patient equally, then 3. Attribute the patient to the clinic and provider within your medical group that saw the patient most recently in the measurement period. If a provider within your medical group has left the clinic, you either attribute the patient to the provider within your medical group who has left or to a new provider within your medical group now managing the patient s care. Note: the patient must remain in the data file if they meet eligibility criteria even if their provider no longer works at the clinic. 17
Total vs. Sample Population During the pre-submission data certification process, medical groups must indicate whether total population or sample population data will be submitted. Clinics with EMRs in place during the entire prior measurement period (dates of service 07/01/2013 to 06/30/2014) are required to submit total population data. Clinics without EMRs in place during the entire prior measurement period are permitted to submit sample population data utilizing a random sampling methodology. See Appendix D for instructions on identifying a random sample of patients. Sample size restrictions do apply and require a minimum of 60 records to be included in sample population data submissions. Clinics with 60 or less patients in the total population must submit total population data. MNCM encourages medical groups to submit total population whenever possible. Benefits include: More reliable performance scores. Performance measurement scores based on total population data more reliably reflect the quality of care delivered by a clinic and medical group. Reliability depends on the degree of random measurement error and the size of the population or sample. As the population size in a data submission increases, the margin of error for reporting differences in performance narrows. Performance scores calculated from sample population data will have a larger margin of error and the reporting clinic s results may not be able to be statistically differentiated from the statewide average, resulting in a greater likelihood of receiving an Average HealthScore on MNHealthScores.org. This is especially important for clinics participating in Minnesota Bridges to Excellence and health plan pay-for-performance programs that rate clinics based on performance measurement scores. Improved risk adjustment. Risk adjustment is based on the distribution of characteristics within a clinic s submitted patient population and its comparison to the statewide distribution. Potential variables for risk adjustment include health plan product, patient demographic information and health status factors. Total population data produces a more reliable representation of a clinic s patient population and increases the number of variables available for risk adjustment. Using multiple data collectors Use of one data collector or data collection process is preferred as it ensures consistent methods for data collection and results in improved reliability. However, if more than one person must collect data, steps to maximize inter-rater reliability (IRR) are strongly recommended, including but not limited to training for all persons involved in data collection regarding the process and methods to be applied. Training could include a review of this guide and all related data collection forms, as well as instructions for locating information in the medical record. MNCM also recommends referring to data collection errors made in previous submissions, making plans to improve the data collection process, and performing quality checks on the data. This ensures that measurement specifications are interpreted consistently and data is collected uniformly across multiple data collectors. 18
Section A: Identifying the Patient Population (Denominator) The first stage of the process includes identifying the total number of patients who are eligible for the measure using a standard set of criteria. Review the Denominator section noted in the Measure Specifications for the detailed criteria. All eligible patients who meet denominator criteria must be identified. Step 1: Pre-Submission Data Certification (formerly Denominator Certification) This must be done prior to identifying the patient population and collecting data. To aid medical groups in identification of the correct patient population, MNCM will review each medical group s source code and/or methodology for producing the patient population upfront. This process is intended to identify potential issues prior to data submission, thus avoiding rework for medical groups. However, the responsibility to submit an accurate patient population rests with the medical group. Please contact support@mncm.org with any questions. NOTE: MNCM s pre-submission data certification process may include a comprehensive review of the steps used by the medical group to identify the patient population, including a final listing of the identified patients. MNCM recommends saving all original queries, spreadsheets and other documentation of the process used to identify the patient population for potential review. Patient Population Identification Methodology Details The following elements are included on the Colorectal Cancer Screening 2015 Pre-Submission Data Certification Form. Medical groups will need to indicate on the form how they will identify each element: Date of birth range. ICD-9-CM, CPT, HCPCS and LOINC codes included in query. o When querying, use the appropriate sets of code ranges. Do NOT use one single code range to query as this will include more patients in the population that do not apply to this measure. Visit date range and visit count details. Description of how patients will be attributed (assigned) to one provider and one clinic. Board certified specialties of providers included in the search. Whether exclusions will be taken and how they will be handled. o Medical groups with EMRs can list which accepted exclusions will be filtered through the query process. o Medical groups that will manually abstract data can describe that exclusions will be identified and documented during record review. Whether total population or a sample of the patient population will be submitted. If a sample is submitted, the process for generating a sample will need to be described. Inactive patients: Patients designated as inactive in a practice management system, billing system or EMR must be included in the patient population if they meet the criteria. 19
Pre-Submission Data Certification Form Colorectal Cancer Screening 2015 A template is provided to ensure all medical groups are using the required set of criteria to identify the patient population. Updated forms must be submitted on an annual basis. The form requires source code or screen shots, which are helpful for the pre-submission data certification process. Medical groups need to complete this form and submit it through the MNCM Data Portal. To download the form and submit it for certification: 1. Login to the MNCM Data Portal (https://data.mncm.org) 2. Under RESOURCES, select Cycle C Colorectal Cancer Screening from the drop-down menu. Download the Colorectal Cancer Screening 2015 Pre-Submission Data Certification Form. 3. Complete the form and save it in a dedicated file location on the computer or network. 4. Login to the MNCM Data Portal and click on Denominator Certification under the Colorectal Cancer Screening Data Submission 2015 Report (07/01/2014 06/30/2015 DOS) section. Follow the instructions to upload the form to the MNCM Data Portal. 5. MNCM will review the information and respond within three business days. MNCM will either (1) contact the medical group if more clarification is needed, in which case the medical group will need to make the necessary revisions and re-upload the form, or (2) certify the methodology. An automatic e- mail will notify the medical group that the method is certified. Step 2: Patient Population Identification After completing Step 1, medical groups will be able to query their systems to determine the patient population for this measure. This step must be completed regardless of whether the group plans to submit total population or a sample of patients. If a medical group opened or acquired a new clinic in the last year, the new clinic must register and submit data with the medical group. Contact support@mncm.org to discuss submitting this data. For medical groups that implemented a new practice management system or EMR in the last two years, the patient population list will need to be generated using both systems. Two queries or patient lists will be necessary. The lists should then be combined and a common identifier(s) selected to de-duplicate the list. Contact support@mncm.org with any questions. 20
System Query: Helpful data elements that can be included in the system query Refer to the data elements and field specifications to determine how to format the data elements that must be submitted to MNCM: Clinic or facility Patient ID number Patient date of birth (DOB) Provider NPI, type and specialty code Insurance payer and insurance member ID Date of last visit in the measurement period Gender Zip Code Race/Hispanic ethnicity, country of origin and preferred language Allowable Exclusions Keep a Crosswalk : It is very important to keep a crosswalk between the unique identifier and the patient s name and DOB, so that records can be located by clinic staff at the time of validation by MNCM. In general, allowable exclusions are kept to a minimum and are supported by evidence. The evidence must show frequency of occurrence in which the results would be distorted without the exclusion or is clinically appropriate. See the Allowable Exclusions noted in the Measure Specifications for a complete list. See Tables 10 to 14 for a complete list of codes used to identify patients who meet exclusion criteria. If a patient meets the established patient criteria for the population and none of the allowable exclusions apply, the patient must be included. Using allowable exclusions is optional. If exclusions are used, you must track patients who meet exclusion criteria and the exclusion reason for each patient must be clear. If you are using the allowable exclusions, submit the exclusions template to MNCM using the instructions below. If you will not be using allowable exclusions, please skip to the next section. For validation purposes, track the excluded patients found during data collection: Exclusions Template: A template is available on the MNCM Data Portal to use. This document will need to be uploaded to the MNCM Data Portal when the clinical data file is submitted. MNCM will review this list and validate a selection of records during the validation audit. Read more about the Colorectal Cancer Screening 2015 Exclusions Template upload in Section D. If a sample of patients will be submitted and a patient in the sample meets one of the exclusion reasons above, document this reason on the original patient list or data collection form, and enter this patient in the Colorectal Cancer Screening 2015 Exclusions Template. Then replace the patient with another patient from your oversample. See Appendix D for instructions on how to replace excluded patients in your sample. If the total population will be submitted using an EMR extraction of data, it is acceptable to upload a different Excel file of excluded patients that are removed from the population. Using the Colorectal Cancer Screening 2015 Exclusions Template is not necessary, although the exclusion reason for each patient must be clear. 21
Do NOT enter a patient on the Colorectal Cancer Screening 2015 Exclusions Template if the patient did not meet the initial denominator criteria (e.g., the patient is younger than age 50 at the end of the measurement period). Only include patients that meet denominator criteria and one of the allowable exclusions. Helpful information for identifying the patient population For the purposes of determining if a patient is established to a practice, medical groups will count the number of face-to-face visits using the criteria described in the Measure Specifications. Medical groups may have different ways of defining or classifying visit types within a practice, but the intent is to count visits where there is face-toface evaluation of the patient by an MD, DO, PA or NP. Face-to-face visits include: office visits, physical exams, annual visits, and pre-op visits. If the clinic offers after-hours primary care, these patients must be included. Do not include hospital visits, urgent care visits, clinic lab-only visits or nurse blood pressure checks. Evaluation and Management (E & M) Current Procedural Terminology (CPT) Codes The following list of codes may be helpful in determining what types of visits to include when identifying the patient population (denominator). E & M codes do NOT need to be used when querying a practice management system to determine visit counts; however, they have been included here to help further define what is meant by a face-to-face visit with a provider. Refer to a CPT coding manual for more details. Description E & M Codes Preventive Codes Office Consultation Individual Counseling Group Counseling Other Preventive Medicine Services Unlisted E & M Codes CPT Codes 99201 99205, 99211 99215 99386 99387, 99396 99397 99241 99245 99401 99404 99411 99412 99420, 99429 99499 Finalizing the patient population list: 1. Sort the list by the clinic site (where the patient is attributed). 2. De-duplicate the list and include only one record for each patient. If a patient is listed more than once within a clinic or the entire medical group, determine which provider or clinic the patient will be attributed to and delete the other patient medical record/row. See page 17 for more information about patient attribution. 3. Review the number of patients in the population. Is the total number of patients in the population similar to last year? If the totals are significantly different, does the difference make sense? Did a clinic open or close, or did a clinic s overall patient population increase or decrease this year? Does a correction in the methodology or query need to be made? 22
Patient Registries: A patient registry is an important tool to help clinics track patient progress and use for quality improvement purposes. However, MNCM cautions the use of a patient registry for identifying patients in the population or for the collection of clinical data. Many registries give a snapshot of patients at a given time and would therefore not include all patients according to established patient criteria or may not reflect the most recent clinical data (e.g., most recent screening exam). Registries that are programmed to update the patient population and clinical results on a continual basis could possibly be used; however, please discuss this with MNCM before proceeding. During the validation audit, the MNCM auditor will compare the patient s medical record, not the patient registry. If a clinic uses data from a patient registry, the auditor may find a more recent date/value in the patient s medical record and this would be counted as a validation error. 23
Section B: Data Collection Colorectal Cancer Screening 2015 The second stage in the process to calculate performance scores is to collect the required data elements. Specific information can be found in the Data Elements and Field Specifications Table. If medical groups are submitting total population data, data will need to be collected for all patients identified in the patient population. If medical groups are submitting sample population data, data will need to be collected for the patients in the sample. Review Appendix D for more information about how to identify a sample population. Medical groups can collect clinical data from medical records by either 1) extracting the data from an EMR through a data query; or 2) abstracting the data from the medical record (paper record or EMR). Data collection occurs after: 1. The clinic s billing and medical record updates are complete for the measurement period; 2. The patient population identification method is certified by MNCM; and 3. The total patient population is pulled. If applicable, a sample is selected according to the measure specifications and sampling instructions. Step 1: Collect the Data Data must be submitted using the provided Excel template. It contains all of the necessary fields and the correct column formatting to submit data according to the measure specifications. Download the Colorectal Cancer Screening 2015 Data Collection Spreadsheet Template from the MNCM Data Portal, under RESOURCES by selecting Cycle C Colorectal Cancer Screening from the drop-down menu. Locating Data Elements in the Patient Medical Record The primary source of data is the clinic s documentation in the medical record (e.g., flow sheets, progress notes, lab reports, etc.). Data collectors may also choose to review the outside correspondence in the clinic s medical record that documents more recent data within the measurement period, but this is optional. If data is used from outside correspondence, it must be documented in the patient s medical record for validation audit purposes. If the most recent data from the primary clinic s medical record is used, the MNCM auditor will NOT do a more extensive review of outside correspondence during the validation audit. Colonoscopy within the measurement period or prior nine years EMR documentation of the date of procedure was performed from the progress note. Documentation from an outside provider. Copy of colonoscopy report as scanned into the EMR or paper medical chart. See Tables 1 to 3 for a more detailed list: o Accepted colonoscopy CPT codes: 44388 44394, 44397, 45355, 45378 45387, 45391, 45392 o Accepted colonoscopy ICD-9 procedure codes: 45.22, 45.23, 45.25, 45.42, 45.43 o Accepted colonoscopy HCPCS codes: G0105, G0121 Data Collection Tips: When manually collecting data using an EMR, highlight the row, column or cell that contains the data needed. This reduces the chance of looking at the wrong row, column or cell. Watch for typos when entering data (number transpositions, etc.). 24
Sigmoidoscopy within the measurement period or prior four years EMR documentation of the date of procedure was performed from the progress note. Documentation from an outside provider. Copy of sigmoidoscopy report as scanned into the EMR or paper medical chart. Procedure documentation through the use of medical claims codes; See Tables 4 to 6 for a more detailed list: o Accepted sigmoidoscopy CPT codes: 45330 45335, 45337 45342, 45345 o Accepted sigmoidoscopy ICD-9 procedure codes: 45.24 o Accepted sigmoidoscopy HCPCS codes: G0104 Fecal blood tests within the measurement period Date that one of the following acceptable stool tests was ordered as noted in the EMR: guaiac FOBT (gfobt) and fecal immunochemical test (FIT). Procedure documentation through the use of medical claims codes; See Tables 7 to 9 for a more detailed list: o Accepted CPT codes: 82270, 82274 o Accepted HCPCS codes: G0328 o Accepted LOINC codes: 2335-8, 12503-9, 12504-7, 14563-1, 14564-9, 14565-6, 27396-1, 27401-9, 27925-7, 27926-5, 29771-3, 56490-6, 56491-4, 57905-2, 58453-2 Tracking Where Data is Located in the Patient Medical Record It is important to keep track of where data is located in the patient medical record. For example, if data is used from an outside specialist or provider note (that is within the primary clinic s record), document the source on the data collection form or Excel spreadsheet. If you are collecting data directly in the Excel spreadsheet, create a Notes column and enter the data source details in this column. After you have completed data collection, SAVE A COPY of the Excel file and remove the Notes column in the file that will be used for submitting to MNCM. 25
Data Elements and Field Specifications Colorectal Cancer Screening 2015 Column Field Name Notes Excel Format Example A Clinic ID Enter the MNCM Clinic ID of the clinic where the visit occurred for every patient submitted. MNCM assigns the clinic ID at the time of registration. Clinic IDs are listed in the MNCM Data Portal. Do not use the Medical Group ID. Blank values will create an ERROR upon submission. Quality Check: Verify Clinic ID in each cell matches the MNCM Clinic ID in the portal. B Patient ID Enter a unique patient ID that will identify each patient. Keep a crosswalk between the patient ID, the patient name and DOB to help clinic staff locate the record for the validation audit. Enter clinic-assigned ID (e.g., MRN, account number). Do NOT enter social security numbers. Blank values will create an ERROR upon submission. Quality Check: Verify patients were not duplicated. If patient is duplicated, determine which clinic you will attribute patient to. If submitting a sample population, you will need to replace the deleted record with the next sampled patient. Text 9999 Text 1 C Date of Birth Enter the patient s date of birth. Include patients aged 51 75 at the end of the measurement period (06/30/2015). The date of birth range for this measure is 07/01/1939 to 06/30/1964. Blank values or dates outside the range 07/01/1939 to 06/30/1964 will create an ERROR upon submission. Quality Check: Verify each date of birth is within the accepted range. Date (mm/dd/yyyy) 05/08/1950 26
Column Field Name Notes Excel Format Example D Gender Enter the patient s gender: Female = F; Male = M; Unknown = U E Zip Code, Primary Residence Blank values will create an ERROR upon submission. Quality Check: Verify each cell has one of the accepted codes. Enter the patient s five-digit zip code of primary residence at the most recent encounter on or prior to 06/30/2015. If EMR query extracts a nine-digit number, submit the nine-digit number (the portal will remove the last four digits automatically). Blank values will create an ERROR upon submission. Quality Check: Verify the zip code is five digits long and that each cell has data. Text Text 55111 F F G H I Race/Ethnicity1 Race/Ethnicity2 Race/Ethnicity3 Race/Ethnicity4 Please refer to a separate document entitled 2015 REL Data Field Specifications and Codes for the field specifications in Columns F N. This document can be found via the link above, under the RESOURCES Tab in the data portal under the Race/Ethnicity/Language Data (REL) section, or on MNCM.org under Submitting Data > Training & Guidance > Data Collection Guides. J K L M N Race/Ethnicity5 Country of Origin Code Country of Origin Other Description Preferred Language Code Preferred Language Other Description These are optional fields. For more information about collecting this data from patients, refer to the Handbook on the Collection of Race Ethnicity and Language Data available on MNCM.org under Submitting Data > Training & Guidance > Data Collection Guides. Quality Check: Verify each cell has one of the accepted codes. Blank cells are acceptable if there is no data is available. Number 1 Number 2 Text CountryA Number 1 Text LanguageB 27
Column Field Name Notes Excel Format Example O Provider NPI Enter the 10-digit NPI of the provider to which the patient is attributed based on the attribution methodology on p. 17. If the provider does not have an NPI, enter the provider ID as registered in the MNCM Data Portal. Health Care Homes Clinics: Enter the NPI of the patient s primary care provider. Blank values will create an ERROR upon submission. Quality Check: Verify each cell has data. Text 1234567891 P Provider Specialty Code Enter the board certified specialty of the provider (if multiple specialties, choose primary specialty): Number 5 1 = Family Medicine/General Practice 2 = Internal Medicine 5 = Geriatric Medicine 9 = Obstetrics/Gynecology If a provider from a specialty other than those listed above has patients they wish to submit data for, contact support@mncm.org. Blank values will create an ERROR upon submission. Quality check: Verify that each cell has an accepted code. Q R Insurance Coverage Code Insurance Coverage Other Description Please refer to a separate document entitled 2015 Insurance Coverage Data Field Specifications and Codes for these field specifications. This document can be found via the link above, under the RESOURCES Tab in the data portal under the Insurance Coverage Field Specs & Codes for DDS section, or on MNCM.org under Submitting Data > Training & Guidance > Data Collection Guides. This should be the patient s most recent insurance on or prior to 06/30/2015. Number 1 Text CIGNA S Insurance Plan Member ID Quality Check: Verify each cell has an accepted code and that all 99 codes have a name entered in Column R. Verify Social Security Numbers are NOT submitted. Text FBZXV123456 28
Column Field Name Notes Excel Format Example T Date of colonoscopy Target = Date of colonoscopy within the reporting period or previous nine years (07/01/2005 to 06/30/2015) Enter the date that corresponds to the patient s most recent colonoscopy. Leave BLANK if the patient does not have a colonoscopy documented. Do NOT enter any test date that occurred after 06/30/2015. The date the procedure was performed is required. The result or report is not required if the screening exam is a part of the medical history. Date of colonoscopy order alone does not count if the date of the exam is not part of the medical history the result or report must be produced on audit. Acceptable documentation to correspond with the date of the procedure can come from claims codes, colonoscopy report, or patient reported procedure date. If the exact date is not documented, use the first day of the month and year that is documented in the patient s record (e.g., if June 2007 is documented, enter 06/01/2007). If only a year is documented, use January 1 of the year documented (e.g., if 2007 is documented, enter 01/01/2007). Do NOT enter the date of a CT Colonography. This test does NOT count as a colonoscopy. Quality Check: Verify that there are no dates after 06/30/2015 if data is entered. Date (mm/dd/yyyy) 07/22/2010 29
Column Field Name Notes Excel Format Example U Date of sigmoidoscopy Target = Date of sigmoidoscopy within the reporting period or previous four years (07/01/2010 to 06/30/2015) Enter the date that corresponds to the patient s procedure date of the sigmoidoscopy. Leave BLANK if the patient does not have a sigmoidoscopy documented. Do NOT enter any test date that occurred after 06/30/2015. The date the procedure was performed is required. The result or report is not required if the screening exam is a part of the medical history. Date of sigmoidoscopy order alone does not count if the date of the exam is not part of the medical history the result or report must be produced on audit. Acceptable documentation to correspond with the date of the procedure can come from claims codes, sigmoidoscopy report, or patient reported procedure date. If the exact date is not documented, use the first day of the month and year that is documented in the patient s record (e.g., if October of 2011 is documented, enter 10/01/2011). If only a year is documented use January 1 of the year documented (e.g., if 2011 is documented, enter 01/01/2011). Quality Check: Verify that there are no dates after 06/30/2015 if data is entered. Date (mm/dd/yyyy) 07/22/2012 30
Column Field Name Notes Excel Format Example V Date of stool blood test order Target = Date of order of the stool blood test within the reporting period (07/01/2014 to 06/30/2015) Enter the date that corresponds to the order of the most recent stool test for the purpose of detecting colorectal cancer: Leave BLANK if the patient does not have an order for stool blood tests documented. Do NOT enter any test date that occurred after 06/30/2015. The date the result/samples were returned is acceptable if it occurs within the measurement period. The sample can be either a guaiac (gfobt) or fecal immunochemical test (FIT). Quality Check: Verify that there are no dates after 06/30/2015 if data is entered. Date (mm/dd/yyyy) 07/22/2013 W Stool test type ordered If the patient has a stool test ordered as noted in Column V, enter the name of the stool test ordered: gfobt (Guaiac Fecal Occult Blood Test) FIT (Fecal Immunochemical Test) Leave BLANK if there is no documentation of the type of stool blood test ordered for the patient. Quality Check: Verify that accepted codes are used. Verify this column is populated if Column V has a date entered. Text gfobt 31
Column Field Name Notes Excel Format Example X Number of stool tests returned If the patient has a stool test ordered as noted in the Column W, enter the number of tests returned in this column. Number 3 Target: Leave BLANK if there is no documentation of the number of stool tests returned. gfobt = 3 or more samples were returned Quality Check: Verify that number is as expected. FIT = 1 or more samples were returned 32
Step 2: Quality Check the Data Colorectal Cancer Screening 2015 MNCM recommends completing several internal quality checks of the data prior to submission. Quality checks improve data accuracy, reduce the likelihood of errors, and ensure that the data can be validated upon audit. Quality Check Option 1: Use Excel s AutoFilter feature to complete data quality checks of specific data elements in the Excel file. To set the filter and review specific data elements: 1. Click inside any data cell and activate the AutoFilter by : a. In Excel 2003, click the Data menu, point to Filter, and then click AutoFilter. b. In Excel 2007 and Excel 2010, click the Data tab and in the Sort & Filter area click Filter. 2. Click on the drop-down boxes of any column and scan for key entry errors, out-of-range or missing data and determine if the data needs to be corrected (e.g., if a date for a colonoscopy is entered as free text, About three years ago, the field will not be accepted by the MNCM Data Portal). 3. Click on the same drop-down box and select All to display all data again. 4. Remove the Filter option by : a. In Excel 2003, click Data, Filter, and AutoFilter again. b. In Excel 2007 and Excel 2010, click the Filter option again in the Sort & Filter area. Example Quality Check: Verify if there is stool blood test samples entered, there is also a stool blood test type completed. Filter for all rows that have numbers entered into Column X by deselecting the Blank box in the filter drop down menu. Then filter Column W by deselecting all options except Blank to see which record(s) had a missing value. Verify the data in the medical record and make changes in the Excel file if necessary. Quality Check Option 2: Complete an internal audit of clinical data by reviewing a random sample (8 to 10) of records or a full sample (30) to see if the data matches what was collected from the patient medical record. If errors are found, make the corrections in the Excel file; however, also consider if the errors were isolated cases or indicative of a larger data collection problem. (e.g., there are no patients with a colonoscopy date, and you are certain that colonoscopy dates are collected and should be in the data.). Quality Check Option 3: Complete the general quality checks outlined below: 1. Complete quality checks listed in the Notes section of each data element in the Data Elements and Field Specifications table. 2. Verify excluded records are removed and recorded on Colorectal Cancer Screening 2014 Exclusions Template. See Tables 10 to 14 for all applicable codes used to identify patients who meet exclusion criteria. 3. If the data field is supposed to be blank, do NOT enter hyphens or zero (leave blank). 4. Check that the Excel file does not have blank rows at the bottom of the spreadsheet as they can slow the data submission process. 33
a. To check for blank rows: Press Ctrl/End at the same time to go to the bottom-most cell in the spreadsheet. If there are several blank rows, remove them by highlighting the blank rows, rightclicking in the left margin, and selecting Delete. It is important to complete quality checks before submitting data to MNCM. This can help avoid delays in file submission and ensure submission of the most accurate data. All changes, additions or corrections must be made in the Excel file before submitting data to MNCM. 34
Section C: Data File Creation Colorectal Cancer Screening 2015 The third stage in the process to calculate performance scores is to create the data file for submission in the MNCM Data Portal. Before proceeding with the file submission, be sure to: Complete all data collection and data entry. Complete data quality checks. Combine all clinic files onto one spreadsheet. All clinics in a medical group must be uploaded in one, single file. The clinic identifier is the Clinic ID. Verify each column is formatted according to measure specifications (TEXT, NUMBER, or DATE formatting). Columns can remain at any width. Verify all original columns remain in the spreadsheet even if there is no data in a column. Do NOT delete any columns. Once these steps are completed, save the Excel template and then save the file as a CSV file, which will be uploaded to the MNCM Data Portal. If at any point in the process corrections to the data are needed, do NOT open the CSV file in Excel. Doing so destroys the formatting and alters the data. Instead, to view or make corrections to the data, open your original Excel file. Then save the changes as a new CSV file. If the CSV file is mistakenly opened in Excel, simply re-save a new CSV file from the original Excel file. Rename the old CSV file or delete it entirely. Create CSV File for Data Submission The steps for creating a CSV file using Excel 2003, 2007 or 2010 are below. If multiple tabs were created in the Excel spreadsheet, select the correct tab and proceed with the following steps. If only one tab was created, start with step 6. For Excel 2003 Users For Excel 2007 Users For Excel 2010 Users 1. Open the original Excel file (.xls). 2. Click Edit or right-click the tab of the spreadsheet you wish to save (near bottom of screen). 3. Select Move or Copy Sheet To book (new book) this is a dropdown selection. 4. Select Create Copy. 5. In this new book, click File, Save As. 2. Right-click the tab of the spreadsheet you wish to save (near bottom of screen). 3. Select Move or Copy Sheet To book (new book) this is a dropdown selection. 4. Select Create a Copy; click OK. 5. In this new book, click the Office Button (upper left-hand corner of screen); select Save As. 2. Right-click the tab of the spreadsheet you wish to save (near bottom of screen). 3. Select Move or Copy Sheet To book (new book) this is a dropdown selection. 4. Select Create a Copy; click OK. 5. In this new book, click the File tab (upper left-hand corner of screen); select Save As. 6. Select the folder and file name of your choice. 7. At the very bottom, you will see Save as type; choose from the drop-down menu, CSV (comma delimited). 8. Click Save. When you save the CSV file, the following warning will appear: may contain features that are not compatible with CSV. Do you want to keep the workbook in this format? Click Yes. 9. Now you can close the file; a message will appear: Do you want to save this file...? Click Yes or No. Your CSV file is now ready for upload to the MNCM Data Portal. Do NOT open the CSV file in Excel. If the file is mistakenly opened, simply resave a new CSV file. 35
Section D: Exclusions File and Data File Submission The fourth stage in the process to calculate performance scores is to submit the data file through the MNCM Data Portal. Go to the HOME tab on the MNCM Data Portal and scroll down to the Colorectal Cancer Screening Data Submission - 2015 Report (07/01/2014 06/30/2015 DOS) measure heading. Click on Data Submission and follow the steps below. Data File Transfer Beginning 2014, the Minnesota Department of Health (MDH) is requesting the receipt of patient level data for the uses described below. MDH has assured us that your organization is permitted to disclose this patient level data to MDH under applicable law (including Minnesota law and HIPAA) because it will be used by MDH only for public health activities, health oversight activities, or other activities required or authorized by state or federal law. Please indicate your selection on the MNCM Data Portal to indicate if you choose to have MNCM share patient-level data with MDH. A list of the data elements for each measure that will be shared with MDH is available in the MNCM Data Portal by going to the RESOURCES tab and selecting Minnesota Statewide Quality Reporting and Measurement System from the drop-down menu. MDH will use patient level data to: Validate quality measure results Publicly report clinic results Research risk adjustment methodologies Benchmark and evaluate Health Care Homes Design and evaluate public health interventions Research and analyze health disparities MDH will not use patient level data to pursue investigatory or regulatory activities. When you are ready to make this selection: 1. Click on the Data Files Transfer step on the HOME tab of the MNCM Data Portal under the Colorectal Cancer Screening measure heading. 2. Choose one of the two data sharing options: YES My organization agrees to have MNCM share our patient-level data with MDH for specified measures. NO My organization does not agree to have MNCM share our patient-level data with MDH. 3. Click Save. 36
Exclusions File Upload For medical groups choosing to submit patients who meet an allowable exclusion, they must be tracked on the Colorectal Cancer Screening 2015 Exclusions Template that can be downloaded from the MNCM Data Portal. See Tables 10 to 14 for all applicable codes used to identify patients who meet exclusion criteria. Enter each excluded patient (patient ID, clinic ID, DOB) found during manual data collection in the spreadsheet. Enter 1 in the cell of the accepted exclusion. Enter any notes for future reference. 1) Do NOT add columns that are not one of the accepted exclusions AND 2) Do NOT enter patients that did not meet the initial inclusion criteria (e.g., patient age not between 51 to 75 at the end of the measurement period, etc.) Keep the exclusions file in Excel format; do NOT convert the file to CSV format. This is different from the data file that needs to be converted to a CSV format. Before uploading the Colorectal Cancer Screening 2015 Exclusions Template to the MNCM Data Portal, do the following: 1. Sort the data by clinic site 2. Save the file for future reference When you are ready to submit Colorectal Cancer Screening 2015 Exclusions Template form: 1. Click on the Exclusions step on the HOME tab of the MNCM Data Portal under the Colorectal Cancer Screening Data Submission 2015 Report (07/01/2014 06/30/2015 DOS) measure heading. 2. Upload Data: Click Browse to search for the Excel file and click Save. Then click Submit. If more action is needed, click either Save as Draft to come back to this step or click Browse to upload the correct file 3. If no exclusions were taken, click No Exclusions. Data Submission Next click on the Data Submission step on the HOME tab of the MNCM Data Portal under the Colorectal Cancer Screening Data Submission 2015 Report (07/01/2014 06/30/2015 DOS) measure heading and use the following steps to submit data to MNCM. Step 1: Enter Denominator Medical groups may manually enter denominator counts and information, or upload a CSV file with the required information. Use either the manual instructions or the upload instructions below. Manual Instructions To manually enter denominator counts and information use the following steps: 1. Enter the following information for each clinic row. Once the information is entered, click on Save and Continue. 37
Method Used for Data Collection: Select one of the data collection methods from the dropdown box: o o o o o EMR: All data pulled via query EMR: Some data looked up manually EMR: All data looked up manually Manual: Paper records only Manual: EMR and paper record REL Data Collection: Indicate if you collect race, Hispanic ethnicity, preferred language and country of origin using best practice methods. Best practice methods include: o o Race and Hispanic Ethnicity: Allowing patient to self-report race AND not using a multiracial category AND system allows the collection and reporting of more than one race. Preferred Language and Country of Origin: Allowing patient to self-report these demographic data. Number of Patients That Meet Inclusion Criteria (Less Exclusions): Enter the number of patients who are eligible or met the inclusion criteria for the measure (based on diagnosis codes, age, visit criteria, etc.). o Do NOT include patients who met an accepted exclusion (e.g., deceased, etc.). Including excluded patients in this count will decrease the final rate, so remember to subtract these patients from the total population. Number of Patients Submitting: Enter the number of patients in the clinic that are being submitted. o For total population submission, enter the same number as what was entered in the Number of Patients That Meet Inclusion Criteria (Less Exclusions) category. o For a sample submission, enter the number of patients being submitted for the sample. o This count must match the count in your data CSV file. Not Reporting: Check this box if a clinic is not reporting for this cycle of data collection. o Be advised that MNCM s policy is that ALL clinic sites within a medical group submit their data through the DDS process if this method is chosen. o Provide a reason the clinic is not reporting. For example: The clinic has no patients meeting eligibility criteria. Upload Instructions To enter the denominator counts and information into an Excel sheet that will then be uploaded to the portal, use the following steps. 1. Click on Download the Denominator Worksheet. The clinic names will be displayed in Column A and the clinic IDs will be displayed in Column B of the downloaded worksheet. 2. Complete the worksheet by entering the following information for each clinic: Method Used for Data Collection (Column C): Enter the code for the method of data collection used in each clinic 1 = EMR: All data pulled via query 38
4 = EMR: Some data looked up manually 5 = EMR: All data looked up manually 2 = Manual: Paper records only 3 = Manual: EMR and paper record REL Data Collection (Columns D G): Indicate if you collect race, Hispanic ethnicity, preferred language and country of origin using best practice methods. Best practice methods include: o o Race and Hispanic Ethnicity: Allowing patient to self-report race AND not using a multiracial category AND system allows the collection and reporting of more than one race. Preferred Language and Country of Origin: Allowing patient to self-report these demographic data. For each clinic ID indicate if best practices are used by using the following codes and instructions: 1 = Yes, we follow the best practice 0 = No, we do not follow the best practice o Column D: Enter the appropriate code (1 or 0) to indicate if patients are allowed to selfreport race and Hispanic Ethnicity o Column E: Enter the appropriate code (1 or 0) to indicate if clinic is NOT using a multiracial category AND system allows the collection and reporting of more than one race o Column F: Enter the appropriate code (1 or 0) to indicate if patients are allowed to selfreport preferred language o Column G: Enter the appropriate code (1 or 0) to indicate if patients are allowed to selfreport race and Hispanic Ethnicity Number of Patients That Meet Inclusion Criteria (Less Exclusions) (Column H): Enter the number of patients who are eligible or met the inclusion criteria for the measure (based on diagnosis codes, age, visit criteria, etc.). o Do NOT include patients who met an accepted exclusion (e.g., deceased, etc.). Including excluded patients in this count will decrease the final rate, so remember to subtract these patients from the total population. Number of Patients Submitting (Column I): Enter the number of patients in the clinic that are being submitted. o For total population submission, enter the same number as what was entered in the Number of Patients That Meet Inclusion Criteria (Less Exclusions) category. o For a sample submission, enter the number of patients being submitted for the sample. o This count must match the count in your data CSV file. Not Reporting (Column J): Indicate if a clinic is not reporting for this cycle of data collection. 1 = No, this clinic is NOT reporting 0 = Yes, this clinic IS reporting o Be advised that MNCM s policy is that ALL clinic sites within a medical group submit their data through the DDS process if this method is chosen. 39
Reason not reporting (Column K): Provide a reason the clinic is not reporting. For example: The clinic has no patients meeting eligibility criteria. 3. Save the Excel file as a CSV file (See page 35 for more information about how to save a CSV file). Click Browse to search and find the CSV file and click Submit File. Step 2: Review & Save Verify the numbers entered by reviewing all of the clinic site s information for accuracy (no typos or duplicate patients). Click Save and Continue, or click Back to Step 1 to re-enter counts. Step 3: Upload Data Click Browse to search for the CSV file and click Upload CSV and Continue. The portal will now scan the CSV file to identify possible errors. The portal will then provide an Upload Status that will indicate if there are errors or warnings in the data file. Click on the Refresh link to view an updated upload status. To view errors and warnings, click View Errors & Warnings. If there are errors, the data file will need to be corrected and resubmitted to portal. Refer to the Data Elements and Field Specifications to review the required data for each column. 1. Errors: Corrections must be made and a corrected file uploaded (e.g., date of birth is out-of-range). Proceed to instructions below. 2. Warnings: Review possible errors and decide whether corrections are needed (e.g., colonoscopy date was more than 10 years ago). If corrections to the data file are necessary, proceed to instructions below. If corrections are not necessary, click Continue to Step 4. If corrections to the data file are necessary: Make corrections in the original Excel file and save the corrected file with a new name. Then save as a new CSV file to upload. Do NOT make corrections in the CSV file as this will destroy the format and alter the data. To start from Step 1: Click Clear & Start Over to re-enter population counts and upload the corrected file starting from Step 1: Enter Denominator. Note: All denominator count entries and a new file upload will be necessary if Clear & Start Over is clicked. To start from Step 3: If corrections are only needed to the data file click Re-Upload Data (csv) File. Begin with Step 3: Upload Data. Once the Data (CSV) File has been successfully uploaded to the portal, click Continue to Step 4. 40
Step 4: Review & Submit Colorectal Cancer Screening 2015 Review the quality checks for each item listed in the Data Elements and Field Specifications table as well as the preliminary rates and their comparison to the previous measure period s rates to determine if there are errors in the data. If your rate is 100%, verify you have submitted all eligible patients correctly. Do NOT submit only patients who are up-to-date with colorectal cancer screening. If you need to resubmit the data file only, click Re-Upload Data (CSV) File. If you need to resubmit the denominator counts and the data file, click Clear & Start Over at the bottom of the page. Again, make corrections in the original Excel file and save the corrected file with a new name. Then save as a new CSV file to upload. Do NOT make corrections in the CSV file as this will destroy the format and alter the data. Once the data has been successfully submitted, review and check each box of the Pre-Submission Quality Checklist. Click Continue. The page will be refreshed. Data Comparison Notes Review the current measurement period s preliminary rates for each clinic compared to the prior period s data submission and consider any changes between the current period and the prior period. Provide an explanation in the data comparison notes text box for any changes or indicate that the data comparison is what was expected. Providing thorough and insightful explanations of year to year changes in populations and/or rates will speed the quality check step of the data validation process and may reduce or eliminate the need for follow up contact from MNCM. When text entry is complete, click Save Notes. The page will again refresh. NOTE: If data has not been submitted for this measure in a previous period, the Data Comparison Notes text box will not display. Determine if the file is ready to submit to MNCM. You can click Save as Draft if you need to review the information in more detail prior to submitting the file to MNCM. To access your information again, you can click on Data Submission under the Colorectal Cancer Screening Data Submission 2015 Report (07/01/2014 06/30/2015 DOS) section on the HOME tab. When the data file is ready to submit to MNCM: Click Submit Data to MNCM and proceed to Step 5: Done. The Submit Data to MNCM button will not appear until the Pre-Submission Quality Checklist and Data Comparison Notes steps have been completed as stated above. Step 5: Done The data file has been successfully submitted. MNCM will send an e-mail that the data has been received. You can download the data by clicking Download Data near the top of the data comparison section to see which patients were numerator compliant (1) and which were not (0) by viewing the additional columns on the righthand side of the document. 41
Section E: Data Validation Colorectal Cancer Screening 2015 After data is submitted, MNCM completes key validation steps to identify potential errors. If errors are identified, the medical group must make corrections to the data file and resubmit before MNCM approves the data. MNCM completes data validation in three steps: (1) data quality checks, (2) the validation audit, and (3) the two-week medical group review. MNCM completes data quality checks of the demographic data, patient population and performance score. Validation audits verify that the submitted data matches source data in the medical record. Prior to approving final scores, medical groups are given an opportunity to review preliminary statewide results during what is called the two-week medical group review. Each step is critical to the validation process and ensures results are accurate and comparable. Preparing for the Validation Audit All medical groups are subject to a validation audit. Medical groups selected for audit are contacted by MNCM for scheduling and will be provided a list of records to be made available for audit. To prepare for the audit: The medical group or clinic site representative must be available to participate in the entire audit process. o For data that resides in an electronic record, the audit will be conducted via a HIPAA secure, online meeting service; the medical group or clinic representative will need to retrieve and display the selected records and screens necessary to complete the validation. o For data that resides in a paper record, the audit will take place onsite. Patient names or other personal information may be blinded. MNCM will verify the record is correct using the date of birth submitted. Clinics must have the following available at the time of the validation audit: o ALL requested patient records. o The crosswalk between the unique patient identifier and the patient s name and date of birth, as necessary. o Data collection forms and other notes describing where various data elements were located in the patient record. o List of patients that were excluded. Validation Audit Process MNCM utilizes the National Committee for Quality Assurance (NCQA) 8 and 30 process for validation audits. MNCM randomly selects 33 records from each applicable clinic site for validation. At most, 30 records for each clinic site will be reviewed. The additional three records are oversamples to ensure 30 records will be available on the day of the review. The MNCM auditor reviews records one through eight in the sample to verify whether the submitted data matches the source data in the medical record. If no errors are found in these eight records, the compliance rate is 100 percent, and the clinic site is determined to be in high compliance. The MNCM auditor may determine no further record review is necessary. The MNCM auditor communicates results to MNCM staff. 42
If the auditor identifies one or more records with errors, and will continue auditing records nine through 30 and a compliance rate is calculated (e.g., 27/30 records compliant, 90 percent). If the compliance rate is less than 90 percent, the auditor will communicate the results with MNCM who will contact the medical group to discuss a resubmission plan. Two-Week Medical Group Review The two-week medical group review is the official opportunity for data submitters to review and comment on the results prior to finalization. Each medical group is responsible for reviewing their own results, investigating any concerns, and submitting evidence to MNCM if a change in results is requested. MNCM staff will review all requests and determine an appropriate course of action. After Validation Once MNCM validation processes are complete, MNCM will approve the data in the MNCM Data Portal. An e- mail will be sent to the medical group s data contact notifying them that the data is approved. After all statewide results are approved, MNCM may publish clinic and medical group level results on MNHealthScores.org. Results can also be found on the MNCM Data Portal > Results tab. Medical groups should maintain data submission files and other documents related to data submission for two years. 43
(07/01/2014 to 06/30/2015 Dates of Service) Appendices 44
Appendices Appendix A: Description of the Measure The Colorectal Cancer Screening measure calculates a numerator rate equal to the: Percentage of all patients aged 51 75 at the end of the measurement period who (during dates of service 07/01/2014 to 06/30/2015) were up to date with appropriate colorectal cancer screening exams. Patients must have one of the following colorectal screening exams during the appropriate time range in order to be numerator compliant. Colorectal Screening Exams & Time Ranges Colonoscopy within the measurement period or prior nine years (Valid dates = 07/01/2005 to 06/30/2015). OR Sigmoidoscopy within the measurement period or prior four years (Valid dates = 07/01/2010 to 06/30/2015). OR Stool tests done within the measurement year (valid dates = 07/01/2014 to 06/30/2015) and with the appropriate number of tests returned. Acceptable stool tests include guaiac FOBT (gfobt) and fecal immunochemical tests (FIT). 45
Appendices Appendix B: MNCM Data Portal Registration Registration must be completed prior to data submission and is completed once a year. Registration instructions can be found under RESOURCES on the MNCM Data Portal https://data.mncm.org/login. Contact MNCM at support@mncm.org if you did not register. If your medical group opened or closed clinics after the 2015 Clinic and Provider Registration ended in February 2015, contact MNCM to update the registration and clinic information. If a medical group opened or acquired a new clinic in the last year, the new clinic must register and submit data with the medical group. Contact MNCM at support@mncm.org to discuss submitting this data. 46
Appendices Appendix C: Resources to Help You Get Started To identify your population, collect data, and get started in the data submission process, MNCM offers several resources and tools. To access the resources and tools for the Colorectal Cancer Screening measure, log in to the MNCM Data Portal using the following website: https://data.mncm.org and click on the RESOURCES tab. Select Cycle C - Colorectal Cancer Screening from the drop down menu. The Colorectal Cancer Screening Resources screen contains the Colorectal Cancer Screening Data Collection Guide, Colorectal Cancer Screening Resources and Frequently Asked Questions The documents you will need to download include: Colorectal Cancer Screening 2015 Data Collection Guide Colorectal Cancer Screening 2015 Data Collection Spreadsheet Excel Template Colorectal Cancer Screening 2015 Denominator Certification Form Optional: Colorectal Cancer Screening 2015 Data Collection Form (This is a patientlevel form that is optional and most useful for medical groups and clinics using paper records) 47
Appendix D: Sampling Methods Colorectal Cancer Screening 2015 Appendices If the clinic is submitting a sample population, use Method 1 or 2 in order to pull a random sample of patients. Prior to pulling a random sample of patients, you must first identify all patients who meet eligibility criteria. Refer to Section A for more detailed information about identifying all patients who meet eligibility criteria. The patients pulled into the random sample will be the patients who will be included in the data submission file. Method 1: Excel Random Number Generator 1. Insert a blank column on the leftmost side of the spreadsheet. 2. Label new column RAND. 3. Place cursor in the first blank cell (A2) and type =RAND(). 4. Press enter (a number like 0.793958 will appear). 5. Place the cursor back into this cell; resting over the corner to have the pointer change to a black cross, double click or drag the formula down to the last row/patient. 6. Highlight the whole column and click Edit, Copy, Paste Special = Values to freeze the random number (otherwise it will change with every click on the spreadsheet). 7. Sort entire patient population by this new random number. 8. Work down the list row by row, starting with the first row until the number of records in the sample is met for submission (at least 60 patients per clinic, plus at least 20 oversamples = 80 patients per clinic). 9. If a patient meets one of the accepted exclusions, note this on the exclusions spreadsheet and keep working down the list. Use oversamples that are after the number of records in the sample. For example, if 60 records will be submitted and two exclusions were found, include patient rows 61 and 62 to replace the excluded records. Method 2: Systematic (Nth Method) Sample Selection 1. Start with a list that has patients sorted by some unique patient related variable. a. Identifying number like a medical record number (MRN) or chart number is ideal. b. Sorting alphabetically is the least desirable in terms of randomness; however, this may be used when there is no other alternative. 2. Select every Nth patient for the number of patients that will be reported. N should equal the clinic site s total population divided by the number of patients that will be submitted (if needed, round down to the nearest whole number). Highlight or mark every Nth patient on the list. This is the sample. 48