Karen Sakala, RN BSN, PCMH-CCE Diabetes Advisory Council June 20, 2014

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1 Karen Sakala, RN BSN, PCMH-CCE Diabetes Advisory Council June 20, 2014

2 ! Focused on Community Health Centers (FQHCs) in NM! Goal: To improve the ABCs of diabetes! FY : Assessment questionnaire! FY : Work with one CHC with a high % of patients with diabetes and an EHR! FY : Add another CHC with a different EHR vendor! FY : Continue to work with the two CHCs. Spread learnings to other CHCs with the same EHRs (11 total)

3 ! Federally Qualified Health Center! Non-profit private or public entities! Have a community board of directors, 51% are patients! Serve medically underserved areas or populations! Serve all people, regardless of their insurance status or ability to pay! Receive a Federal 330 Grant to help compensate for the loss of revenue

4 ! Communicate with Providers! Standards of Practice / Clinical Guidelines! Show them the data & compare it to the standards

5 Data! Communicating About Data! Data Recovery! Data Reporting

6 ! Patient Demographics! Scheduling! Billing Information! Chart Documentation! Referrals! Orders Practice Management EHR

7 Learning a whole new language!"#$%&'("% )"*+"#$%,-."-%

8 !"#$ %&'$ ()*"$+,-)$.)*/0"*$ 12",0*$ $ $$9:;<3=$ 38#> $ $$?%?$ 4@$ 3885@8$ 6 753A56838$ 3B8576$ > C56B56838$$$9)-D:0D;$ 7#7 45>856838$ $$<3=$ C#> 385>856838$$$9)-D:0D;$ 33#8 33@5A@$ B $ $$9:;<3=$ 8#8C3 B $ $$<3=$ 7#> 756>56838$ 3856B56838$ 3856B56838$ $$?%?$ 333$ 3665C8$

9 !"#$ %&'$ ()*"$+,-)$.)*/0"*$ 12",0*$ $ $$9:;<3=$ 38#> $ $$?%?$ 4@$ 3885@8$ 6 753A56838$ 3B8576$ > C56B56838$$$9)-D:0D;$ 7#7 45>856838$ $$<3=$ C#> 385>856838$$$9)-D:0D;$ 33#8 33@5A@$ B $ $$9:;<3=$ 8#8C3 B $ $$<3=$ 7#> 756>56838$ 3856B56838$ 3856B56838$ $$?%?$ 333$ 3665C8$

10 !"#$ %&'$ ()*"$+,-)$.)*/0"*$ 12",0*$ $ $$9:;<3=$ 38#> $ $$?%?$ 4@$ 3885@8$ 6 753A56838$ 3B8576$ > C56B56838$$$9)-D:0D;$ 7#7 45>856838$ $$<3=$ C#> 385>856838$$$9)-D:0D;$ 33#8 33@5A@$ B $ $$9:;<3=$ 8#8C3 B $ $$<3=$ 7#> 756>56838$ 3856B56838$ 3856B56838$ $$?%?$ 333$ 3665C8$

11 pop Diagnosis Gender Time Frame Test Results pop Age pop

12 Test Results Age/Gender Diagnosis Time Frame

13 ! EHR data for self-pay patients in Oct ( through )! Found only 61% of the number of patients from the previous year s UDS Report (billing data)! Only 6% had A1c, BP, LDL-C done during that time! LDL-C Only 7% had a test done

14 ! Where are all the patients with DM?! Why did only 6% of patients have all 3 tests?! Why did only 7% of patients have an LDL-C?! Was this a documentation issue or an issue of sub-standard care?

15 ! Data queries were reconfigured found the missing patients.! Did spot checks on individual charts to see if ABC tests had been done they were.! Documentation issues were:! A1c tests done by standing order, but no order in the chart! LDL-C tests sent to a reference lab, reports weren t consistently closed out by providers

16 ! Figured out data layering parameters and were consistent in data collection! Re-trained HC staff/providers on appropriate areas to document information! Had IT run reports (monthly) to see if documentation had changed

17 ! Added another Health Center with a different EHR vendor! Also an early adopter of EHR! Had high percentage of patients with DM

18 The EHR as a Black Hole

19 ! Why were blood pressure results missing?! What caused lab tests (that were done) to be missed in a data query?

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24 Lab Test Report

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29 ! Test Name! A1c! a1c! Hgb A1c! Hemoglobin A1c! Loinc Codes! 10 different codes! Required for billing! If no Loinc Codes, not picked up on a report

30 ! Train, train, & re-train staff/providers on proper documentation! Give regular feedback on how they are doing! Set up proper security to avoid improper set up of the EHR

31 Getting a Clean Report

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34 ! Right care at the right time.! A1c: < 7.0 every 6 months! 7.0 every 3 months! BP: <130/80 - every visit (last BP reported) (< 140/90 was also assessed)! LDL-C: < 100 yearly! 100 or a change in meds every 6 mos

35 through A1c BP LDL /$:% 0% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 2;7/% 1;7/% 1'$"% 616% 1'$"% 616% 1'$"% 616% 1'$"% 4% 4#B 38#A <:= >% 33#4 3853> #4 65> CB 3C6 4A$ 3$ C#6 > B:A B:B C > > > > =% C# > > C% 33#B > CB $ C#4 >53C #A D:B 3B8 C CC <% A#C 3653A C> 35> $ C#B B #7 C :A 3> C 38$ 36#4 A #4 35A A56836 C6 A $ 38#6 653C56833 C#6 44:< 388 C C $ C# C#8 C#A C5> B:= B: B8 3>$ 7#B B8 7> A A#7 C53A C$ C53A A$ A#A C5C >> 7> 35> #3 >5> B $ 4#7 353C56833 C#C B56A #4 C D:B 3B6 C C B$ B56A56833 A> C B D% A C CB$ 453A56833

36 A1c BP LDL /$:%0% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 345%% 1'$"% 2;7/% 1;7/% 1'$"% 616% 1'$"% 616% 1'$"% 616% 1'$"% $ 4#B 38#A C#A >63$ > #4 65> CB 3C6 3853> A 65> >#3$ C#6 > #> #7 35> C > > > > > B$ C# > > $ > CB >4A$ C#4 >53C #A #7 3856B #8 653> B8 C CC 3856B C6A$ A#C 3653A C> 35> C#B B #7 C #> 653> > C 653> C8C$ 36#4 A A A56836 C6 A #6 653C56833 C# A #> C C A A7$ C# C#8 C#A C5> #A #3 656C B8 656C #B B8 7> A A# C C53A >4BA$ A#A C5C >> 7> 35> #3 >5> B A8C>$ 4#7 353C56833 C#C B56A #4 C #7 3653B B6 C C B B56A56833 A> C @5> B A737$ A C CB 453A56833

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38 %%345$$ 4#$%.'$'% >F.%.'$'% GHG% $$R$DS$!,T)F"*$U2"V$,"$0),*"$3$<3=$ DCI% CBR$ $$.)*/0"*W$ O7#8R ABR$ =AI% B>R$ 7#8$P$7#4R$ 4DI% 6>R$ C#8$P$4#8R$ 3>R$ 44I% 3>R$ Q$4#8R 4BI% 63R$ X%'$H),*/J)W$ Y$4#8R C>R$ <AI% 74R$

39 %%7/% 4#$%.'$'% >F.%.'$'% GHG% $$R$DS$!,T)F"*$U2"V$,"$0),*"$3$N!$ 44R$ 388R$ $$.)*/0"*W$ <%<$H),*/J)W$ O3>85C8$ ACR$ ==I% >8R$ X%'5HX$ H),*/J)W$ O3B8548$ C6R$ Z3B8548$ 3CR$ 4=I% >4R$

40 %%616;G%% 4#$%.'$'% >F.%.'$'% GHG% $$R$DS$!,T)F"*$U2"V$,"$0),*"$3$?%?$ 7BR$ <CI% $$.)*/0"*W$ C>I% A4R$ Z388 B8R$ A<I% B3R$

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42 ! Work on getting the correct PCP assigned to each patient! Give report card to providers with data comparisons at the end of the project year

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44 ! From time intensive reports and analysis! To push of a button results from Meaningful Use Dashboards

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46 ! Percentage of patients years old with diabetes (Type I or II) who had:! A1c > 9.0% (NQF0059 Diabetes Poor Control)! BP < 140/90 (NQF0061 Diabetes BP Management)! LDL-C < 100 mg/dl (NQF0064 Diabetes LDL Management)

47 ! The clinical measures are easily accessed! Can get numerators & denominators! Health Centers could practice reporting MU CQMs

48 ! One organization did not have 2 of the 3 measures! Clinic staff had to pull data from the A1c measure,! Requested that the Intermediary Organization send the reports for all three measures.! Got very different data for A1c reports

49 ! The other organization had all 3 measures, but also had almost twice as many patients with diabetes than the previous year.! We discovered the data are reported by provider and not by the patient s PCP. Provider Date of Service A1c Result Provider A (PCP) May Provider B August Provider A (PCP) November

50 ! DO NOT USE FOR CLINICAL QUALITY REPORTING

51 Project

52 Auto Mobile

53 ! Discovered flaw in MU clinical reporting & communicated it to others

54 ! When pulling data from an EHR! Use benchmarks to assess if the data is reasonable! If data is missing, do chart checks to asses if information was documented incorrectly or the task wasn t done! Look at workflows and documentation habits retrain staff as needed! Give regular feedback to staff on how they are performing! Involve staff in making the necessary changes to improve their performance

55 Contact information: Karen Sakala, RN BSN, PCMH CCE Clinical Quality Coordinator, NM Primary Care Assoc