Quality Advisory Committee. March 10, 2016

Transcription

1 Quality Advisory Committee March 10, 2016 GREG AUGUSTINE, COO, AZARA HEALTHCARE CHRIS WELLS, DATA ANALYST, NYSDOH AIDS INSTITUTE

2 Agenda Introduction to Azara Healthcare CHCANYS and the CPCI HIV Reporting and HIVQual: The CHCANYS / AIDS Institute / Azara Partnership ehivqual What was it Who participated Outcomes and Learnings

3 3 Azara Healthcare Our History Large investment via formal partnership with Mass League Specialty in large scale data reporting & analytics for Community Health Customers and Patients Data on 15 million+ patients Nearly 150 CHC s live Key Relationships 8 PCA s 8 Networks 15 States NACHC, CDC Focus on Community Health Set up specifically to deliver DRVS to the Community Health marketplace using a Software as a Service (SaaS) model Largest provider of aggregated reporting and analytics for PCA s and CHCs nationwide

4 NY State Center for Primary Care CHCANYS has developed the New York State Center for Primary Care Informatics (CPCI) A priority goal in the CHCANYS Strategic Plan To support improvements in quality, patient and population health outcomes To help control costs To Support growth & success in a changing environment As a central CPCI strategy, CHCANYS has implemented a statewide reporting and analytics solution for NY s FQHCs The Azara DRVS product, rebranded as CPCI, is the analytic engine Collects and normalizes data from multiple sources to create an integrated database for enhanced analysis & reporting Provide actionable data and valuable reporting at individual health centers CPCI includes a program of technical assistance from CHCANYS Clinical QI & Health IT Programs

5 CHCANYS and CPCI April Community Healthcare Network (ecw) 2. Greater Hudson Valley Family Health Center (GE Centricity) 3. Institute for Family Health (EPIC) October Anthony Jordan Health Center (ecw) 5. Open Door Family Medical Center (ecw) 6. CHC of the North Country (ecw) 7. Schenectady Family Health Services (ecw) 8. Hudson River HealthCare (ecw) 9. Whitney M Young Jr. CHC (ecw) 10. Oak Orchard CHC (ecw) Feburary Ezras Choilim Community Health Center (Allscripts) 12. Morris Heights Health Center (GE Centricity) 13. Lutheran Family Health Centers (ecw) 14. Access Community Health Center (NextGen) 15. Regional Primary Care Network (ecw) December Betances (ecw) 17. Settlement (GE Centricity) 18. CHC Richmond (ecw) 19. Brownsville (NextGen) 20. Damian Family Care Center (ecw) 21. William F. Ryan Health Center (ecw) 22. Housingworks (ecw) 23. NOCHSI (Vitera) 24. Bedford-Stuyvesant (ecw) 25. Project Renewal (ecw) 26. HealthCare Choices ICL (ecw) 27. Finger Lakes (ecw) 28. Acacia (NextGen) 29. HHHN (Athena) 30. Refuah (ecw) 31. CHC of Buffalo (ecw) 32. The Chautauqua Center (Allscripts) 33. HELP-PSI (ecw) 34. Urban Health Plan (ecw) 35. Beacon Christian (SuccessEHS) 36. Boriken (ecw) 37. Universal Primary Care/ Southern Tier (ecw) 38. Family Health Network (GE) 39. No. Country Family HC (GE) 40. Ezra Medical (NextGen) 41. Harlem United (ecw) 42. Brooklyn Plaza (ecw) 43. APICHA (ecw) 44. Neighborhood HC (Allscripts) 45. Callen Lorde (NextGen) 46. Syracuse CHC (NextGen) In progress: 47. Metro CHC (ecw) 48. Jericho Road (Medent) 49. East Hill (Allscripts)

6 CPCI Architectural Overview Data from disparate EHR and EPM systems refreshed daily Extensive data quality analysis (QD=QC) and data validation Data unified in EHR-agnostic Data Warehouse for apples to apples comparison Simple, web-based reporting interface accessible from any major browser User role differentiation and data blinding Graphical and text based depictions of datasets Bi-Directional links to External Data systems

7 How Data Gets Into the CPCI Hlth Ctr #x EHR / EPM Extract X Hlth Ctr #x EHR / EPM Extract X Load Staging Transformations & Aggregations CPCI Reporting & Analytics A Hlth Ctr #x EHR / EPM Extract X Health Center Specific Connector B Azara CPCI Nightly Processing Rpt A C Rpt Z

8 HIV Reporting and HIVQual at FQHCs A partnership was formed between the AI, CHCANYS and Azara Healthcare in early 2015 NYSDOH AIDS Institute CHCANYS Azara Healthcare

9 HIV Reporting and HIVQual CHCANYS and Azara partnered with the NYSDOH AIDS Institute Quality of Care Program to enhance CPCI in the area of HIV Reporting and for HIVQUAL submissions. There are currently more than 18 HIV specific measures and three (3) HIV registries available in CPCI These were funded with support from the NYU Lutheran Family Health Centers and AI NYSDOH/AI also funded the development of an extract process that fulfills ehivqual reporting requirements A subsequent initiative is now underway to supply annual HIV Case Load data to the Institute via automated extract out of CPCI as well Planning is underway to further fund and develop HIV quality of care capabilities within CPCI

10 HIV Reporting Measures in CPCI The set of measures included in CPCI include: New Patient Visit Frequency Visit Frequency (12 Month) Visit Frequency (24 Month) Viral Load Monitoring Viral Load Suppressed < 200 Viral Load Suppressed < 50 CD4 Monitoring PCP Prophylaxis Baseline Resistance Test Genital Chlamydia Testing Anal Chlamydia Testing Chlamydia Treatment Genital Gonorrhea Testing Anal Gonorrhea Testing Pharyngeal Gonorrhea Testing Gonorrhea Treatment

11 ehivqual The ehivqual submission included five (5) components: An extract of HIV patients and demographics including Exposure Risk An extract of patient visits (including date, provider and EHR location) An extract of Viral Load and CD4 lab (including date and results) An extract of ARV medications (active during the CY 2014) The patient level detail behind the STI, Baseline Resistance Test and Tobacco Screening measures

12 ehivqual Participating Centers 1. APICHA Community Health Center 2. Betances Health Center 3. Brightpoint Health 4. Brownsville Community Health Center 5. Callen-Lorde Community Health Center 6. Greater Hudson Valley Family Health Center 7. Harlem United Health Center 8. Housing Works East New York Community Health Center 9. Hudson River Healthcare 10. Lutheran Family Health Centers 11. Open Door Family Medical Center 12. Whitney M. Young Health 13. William F. Ryan Community Health Network

13 Where We Are in the Process Step AIDS Institute review of initial test data and feedback to Azara Conference calls with centers, Azara and AI Azara-guided EMR updates by centers AIDS Institute review of second extract and feedback to Azara Azara refinement of queries Import of data into ehivqual test site Analysis of preliminary results and reasons for variation Final Azara extract Assignment of patients to primary site of care in ehivqual Migration of data to ehivqual live website Center review and submission of data AIDS Institute review and approval of submissions Status Complete Complete Complete Complete Complete Complete In Progress If Needed Pending Pending Pending Process TBD

14 Outcomes and Learnings On the whole, the project has been very successful The number of patients being included in the electronic submission is over 8,000 Fewer than 2,000 were included in the prior submission More than 11,000 were included in the extract for evaluation for inclusion Centers took the opportunity to revisit data quality and more effectively document characteristics within their EHRs (e.g., Exposure Risk) Centers are seeing an opportunity to form a tighter community and bond that will afford sharing of best practices and processes ultimately leading to: More effective, common ways of recording structured data More actionable application of data; Changes to processes or approach based on data and quantifiable outcomes The use of CPCI has led to a more uniform application of the specification and aggregations for the measures (e.g., STI, Baseline and Tobacco)

15 Data Filtering during Import into ehivqual Data Element Azara ehivqual Percent Imported Reasons for Exclusion Patients 11,272 8,042 71% No applicable visit Clinical Visits 255, ,525 50% Not related to primary care (e.g., dentistry, podiatry); missing data Labs (VL & CD4) 53,073 51,947 98% Missing data ARV Medications 134, ,525 96% Missing or contradictory data Patients receive a variety of medical services at FQHCs. Approximately half of the visits were removed as not relevant to the current review, and then patients with no applicable visits were excluded entirely. Only a small percentage of labs and medications were excluded.

16 Rules for Filtering Visit Data Algorithm was developed with the intention of finding a sustainable, extensible process for including applicable clinical visits. Uses information from Location, Provider Type and Provider Specialty fields Rule Description 1 If Location Name cannot be mapped to current or newly defined ehivqual clinic, visit should be excluded 2 If visit occurred prior to the year of diagnosis or after review period, visit should be excluded 3 If Provider Type is not "Medical Doctor", "Doctor of Osteopathy", "Nurse Practitioner", "Needs Update" or "Physician Assistant", visit should be excluded 4 If Provider Specialty is not "Internal Medicine", "Family Medicine", "General Practice", "Obstetrics/Gynecology", "Pediatric Medicine", "Nurse Practitioner", "Physician Assistant", "Pediatrics", "Obstetrics & Gynecology", "Cardiology" or "Infectious Disease", visit should be excluded

17 Most Common Reasons for Excluding Visit Data Reason Excluded Visits % of Excluded Visits Mental/Behavioral Health Care 46, % Missing Data 34, % Dentistry 14, % Typo in the Data 8,753 7 % Other Specialty Care 2,994 2 % Podiatry 2,934 2 % Midwifery 362 < 1 % Physical Therapy 236 < 1 %

18 More Outcomes and Learnings On the whole, the project has been very successful NYSDOH/AI has greater insight to the challenges centers face in recording the requisite information in a structured, efficient manner in their EMRs Some information is still be recorded in free text notes as opposed to structured fields Lab results are not stored consistently across different centers (e.g., copies/ml vs log copies) Lab results for STI tests are not structured with a simple positive or negative being returned EHRs are challenged in terms of the capability of storing transgender and SOGI information Centers have the ability to store multiple responses for Exposure Risk The full dataset provided will perhaps show different results, but it will also afford the Institute a more complete picture of the population We have the ability to extract and provide 2015 data sooner hopefully in the 2nd half of 2016

19 Missing Data FQHC Total Pts. No CD4 No VL Med. Before Dx. Other Validation Report Flags A B C D E F G H I J K L M Percentage of patients with missing information is low at most centers, but considerable variation exists between centers Missing CD4 data may reflect uncertain prior ARV history, but some patients truly do not have CD4s and/or VLs. Diagnosis date not always known, but opportunity to correct/update where clearly wrong Many of the validation flags refer to tobacco screens that appear not to have been repeated in 2014; should be able to remove these.

20 Indicators Where Data Are Consistent with Other Recent Results Mean clinic score for the 2014 Azara-derived reviews is within 10 percentage points of the mean clinic score for the same clinics in 2013 and/or the mean score for the approved non-azara 2014 submissions Visit Frequency (12-month) Visit Frequency (24-month) New-patient Visit Frequency Always Suppressed within Review Period Suppressed on Final Viral Load of Review Period Genital Gonorrhea Testing Rectal Gonorrhea Testing among MSM and MtF Patients Pharyngeal Gonorrhea Testing among MSM and MtF Patients Genital Chlamydia Testing Rectal Chlamydia Testing among MSM and MtF Patients

21 Indicators Where Data Are Not (Yet) Consistent with Other Recent Results Mean clinic score for the 2014 Azara-derived reviews differs by more than 10 percentage points from the mean clinic score for the same clinics in 2013 and the mean score for the approved non-azara 2014 submissions ARV Therapy Baseline Resistance Test Genital Gonorrhea Treatment Rectal Gonorrhea Treatment Pharyngeal Gonorrhea Treatment Genital Chlamydia Treatment Rectal Chlamydia Treatment Tobacco Use Screening Tobacco Cessation Counseling

22 Other Areas for Improvement With all our success, there is room for improvement on future submissions Historically Azara has limited experience in reporting HIV measures We are not experts on the standards of care for STIs and HIV but we are getting there! The definition of ARV naive is more complicated than it sounds Patients not on ARV meds on January 1st but who were on meds recently (e.g., the prior November or December) are not necessarily ARV naive Medications change relatively frequently and we need to find a manner by which we can collectively update the medications used in the measures Azara has developed a means to use Medication names and RxNorm codes as opposed to relying on NDC codes Greater collaboration between the centers, the Institute and Azara Especially true with regards to expected outcomes for the measures, the population, etc. Greater communication to and understanding by the centers Expectations on data quality

23 We should add here the steps we are taking at AI to validate facility specific based on our meetings this week We should also include a mention of Toan s survey

24 Open Discussions / Questions