+

Improving the Care of Diabetic Patients in a Primary Care Practice via Affiliation with a Multi-Site Accountable Care Organization

Team: Mary Dallas, David Madison, Michael Peterson, Natalie Schwartz

+Consulting Project

Client: Best Health Medical Associates, 10 physician primary care group, Epic EMR, joined a local ACO

Location: Multiple clinics, Chicago area Affiliated Hospital: Columbia West, 700 beds, GE

Centricity EMR Ancillary Services: 3 different reference labs, 3 retail

pharmacies Goal: Diabetes Care Improvement Project to manage

diabetic patients in ACO

+Deliverables

Assessment of current technology platform and information gaps related to patient care

Recommend technology solutions to address information gaps with ROI estimation

Reports to identify ACO patients and monitor quality and cost of care

+ACO – The Shared Savings Model 3 year agreement for participating providers 2 options: one sided model, or two sided model 1st year participation consist primarily of reporting, and

quality and utilization baselines established 2nd and 3rd years will move to performance measures Shared Savings pool determined by both financial

performance as well as quality performance

+Shared Savings Model

(HHS, 2011)

+Diabetes ACO Quality MeasuresMeasure Method of

Submission

Year 1 Year 2 Year 3

HbA1c < 8%

GPRO Web Interface

Report Performance Performance

LDL <100 GPRO Web Interface

Report Performance Performance

BP <140/90

GPRO Web Interface

Report Performance Performance

Tobacco Non Use

GPRO Web Interface

Report Performance Performance

Aspirin Use GPRO Web Interface

Report Performance Performance

HbA1c >9%

GPRO Web Interface

Report Performance Performance

+Data Elements for Reports Patient identifiers (match patient across all data sources) Patient demographics (used in patient matching algorithms) Payer type (identify Medicare and other payer types) Diagnoses (multiple sources, identify diabetes and

comorbidities) Lab values (discrete data from lab systems) Blood Pressure values (documentation elements from EMRs) Medications (from med list in EMR and pharmacy PBM) Smoking use (documentation elements from EMRs) Claims data (multiple sources, to track utilization)

+Strategic Reports Age distribution- Young diabetics on dialysis or with other

disabilities are Medicare recipients Gender distribution- may influence co-morbid conditions, lifestyle,

compliance, choice of provider Co-morbid conditions/Severity of illness- Patient Risk adjustment

factor (RAF) score relative to the Per Member Per Month (PMPM) costs can identify gaps in care and opportunities for quality improvement

Socioeconomic status- income, education level, English proficiency impacts compliance with care/ technology ability

Patient residence- determines allocation of resources to different practice sites, likelihood of “network leakage”

Service Utilization- “network leakage”, ER utilization (appropriate and inappropriate) can identify gaps in access to care, physician referrals, and inappropriate practices

PRACTICE PCP # Members with Diagnosis of Diabetes Average Risk Score

Chicago 1 393 0.73Chicago 2 321 2.45Chicago 3 244 1.37Chicago 4 231 0.89TOTAL 1189 1.36

Evanston 5 230 2.11Evanston 5 289 1.76Evanston 7 150 1.9Evanston 8 178 0.83TOTAL 847 1.65

Cicero 9 283 1.89Cicero 10 181 1.67TOTAL 464 1.78

TOTAL ACO 2500 1.6

+Operational Reports (1)

PCP 1 PCP 2 PCP 3 PCP 4 PCP 5 PCP 6 PCP 7 PCP 8 PCP 9 PCP 100

20

40

60

80

100

120

Diabetic Quality Measurement Report for Each of the PCPs within BMHA Practice

(% patients meeting metric)

HbA1C<8%LDL<100BP<140/90Non-smokerASA useHbA1C>9%

% pts

+Operational Reports (2)

% Pts with

HbA1C<8%

% Pts with

HbA1C>9%

% Pts with

out of n

etwork

visits

% Pts follo

wed by n

urse nav

igator

% Pts usin

g web

portal to

report

FS re

sults

% Pts in ac

tive weig

ht loss

program

% Pts in re

gular

exerc

ise pro

gram

0

10

20

30

40

50

60

70

80

90

Patient Characteristics by Practice Site

ChicagoEvanstonCicero

% pts

+ Provider Challenges Skepticism about realized incentives relative to disruption in

workflow and productivity and initial costs No real success stories for integrated delivery systems Need to change vital behaviors- workflow changes, evidence

based algorithms, mid level providers, more granular coding, improved medical documentation to support more complex patient visit levels

Need to identify physician champions and foster a culture of communication, transparency, and teamwork

Equitability of PCP attribution- the plurality of primary care services to diabetic patients can be provided by endocrinologists

Audit tracks of individual physician performance- patient outcomes, cost

+A symphony of interventions is required for ACO success

+Quality and outcomes not improved by technology alone

+“Doctors love information; they hate to be told what to do.” Clem McDonald

+Responsibilities extend well beyond the patient visit to office

+Leverage the HIE for Data

HIE Technical Overview (4/4/2011) from HIMSS.org

+HIE Advantages

Patient centric view of information across the community for monitoring and reporting quality elements

Can use translation tables to normalize data from different sources (such as HbA1c values from different labs with different normal ranges)

Can use HL7 to bring data from multiple sources into EMRs for better use of clinical decision support at the point of care

Offer a web based portal for non-EMR providers to enter and view healthcare data

Manage referrals across community providers Engage patients in collaborative care efforts

+Financial Review ROI 1. Funding and the business case for change. ACO-like improvements

require substantial investment in both time and money that may not be reimbursed directly, according to the study. While increased payments to ACOs and medical homes could create a business case for these activities, financial rewards from these investments may "not materialize for a long time, if ever.“

2. Resistance to change. Staff members are resistant to assuming new responsibilities or delegating work they use to perform. In some cases, the organizations faced challenges in recruiting and training employees with the appropriate skills for these roles.

3. Potential disruptions to productivity. According to the study, "many of the care-delivery and infrastructure improvements [such as EMR and patient registries] required changes in workflow that affected productivity of clinical and administrative staff.

4. Limited infrastructure to pursue change. Efforts to improve care coordination and delivery require a great deal of accurate data, which presents a fourth challenge to ACOs. Organizations in the study noted inaccurate data inhibits population management and financial incentives for health improvement. Organizations also mentioned concerns about sharing patient data under privacy regulations.

+Financial Effects (Primary)

+Financial Cost (Secondary)

+Estimated Cost for Project

+Estimated Cumulative ROI

+SUMMARY BMHA & ACO TECHNOLOGY PARTNERS

Patient

Active management of ACO participation:

Re-engineer practice workflowsImperative: HIE link to majority of providers in regionManage all diabetic patients with the same clinical rulesReal-time patient guidance to providersDashboard with practice level performance guidanceDashboard with provider level performance/comparison

+Summary of Recommendations

SHORT TERM CHANGES (0- 6 MONTHS)

+Short Term Changes (0-6 months) Create monthly reporting from EHR to monitor BHMA diabetes

based care quality: Number of patients with specific chronic disease conditions of

diabetes, ischemic vascular disease, hypertension, coronary artery disease, and heart failure by all payers, Medicare only, and non-Medicare

Number of patients with diabetes and have HbA1C not tested within past year, value <8%, value 8-9%, and value >9%, by all payers, Medicare and non-Medicare

Number of patients with diabetes and have BP <140/90, and =>140/90, by all payers, Medicare and non-Medicare

Number of patients with diabetes and have aspirin in their med list by all payers, Medicare and non-Medicare

Number of patients with diabetes and have LDL not tested within past year, <100 or =>100 by all payers, Medicare, and non-Medicare

Patients with a diagnosis of diabetes who have not had a visit within the previous 12 months, by all payers, Medicare and non-Medicare

+Short Term Changes (0-6 months) Create reporting from EHR to segment potential ACO patients cared for

by BHMA Number of patients with primary care visits for the group by payer, reconcile

with CMS ACO reports quarterly Create reporting from EHR to evaluate cost of care with chronic disease states: For all patients with diabetes, those on insulin therapy with HbA1C values in

the categories defined in 1. For all patients with diabetes, medication cost estimate (using AWP for meds

in patient's med list) by all payers, medicare, non-medicare

Develop Clinical Decision Support within EPIC EHR: Alert for medications ordered but not filled within 2 weeks Alert for laboratory tests ordered but not completed within 1 month Alert for missed scheduled appointments for patients with diabetes

Employ a diabetes nurse navigator to review BHMA diabetes patient care reports monthly, and target resources to improve patient compliance

+Summary of Recommendations

MID TERM CHANGES (6-12 MONTHS)

+Mid Term Changes (6-12 months) Evaluate and select HIE vendor for functional capabilities with

regards to: Inventory of community physician participation with HIEs within the state

(which physicians are connected with which HIEs) HIE Vendor Single Sign On capability with EPIC EHR Capture of and normalization local lab values in patient context Capture of claims data for patient community CCD exchange with GE Centricity for Columbia West CCD exchange with EPIC EHR for BHMA CCD exchange with additional community EHRs Web Portal for direct HIE access and ability to update patient information Disease management registry capabilities Reporting capability for ACO patient population and BHMA patient

population Patient Portal functionality for messaging and maintaining a personal

health record with updates from provider EHRs

+Mid Term Changes (6-12 months) Invest in HIE participation with priority development of the

following: Automated data exchange with EPIC EHR to retrieve HIE information

upon patient visit registration and send information to HIE upon patient discharge

Bidirectional medication information exchange from HIE sources into EPIC EHR

Bidirectional lab and radiology results exchange from HIE sources into EPIC EHR

Bidirectional CCD exchange with HIE and EPIC EHR Bidirectional messaging integration with EPIC EHR and HIE messaging for

provider to provider messaging, and patient to provider messaging

Development of Clinical Decision Support tools at HIE level: Initiate development of disease based data warehouse in HIE, with the

ability to segment ACO patients as a group for reporting and alerting Alerts to ACO and PCP for ACO concerning beneficiary utilization – such

as any ED visit or hospitalization via automating messaging

+Mid Term Changes (6-12 months) Structure reports from HIE community information to

evaluate ACO beneficiary utilization estimates Define ACO patient beneficiaries within HIE patient population For all ACO patients with diabetes number of ED encounters

within past year sorted by all payers, Medicare and non-medicare

For all ACO patients with diabetes number of Ambulatory visits by specialty type sorted by all payers, Medicare and non-medicare

For all ACO patients with diabetes number of Hospital admissions sorted by all payers, Medicare and non-medicare

For all ACO patients with diabetes number of surgical procedures sorted by all payers, Medicare, and non-medicare

+Mid Term Changes (6-12 months) Structure reports from HIE community information to examine

ACO diabetes care quality Monthly list of ACO diabetes patients who have not had an HbA1C

value reported within the previous 6 months reported to ACO and PCP Monthly list of ACO diabetes patients who have not had an LDL value

reported within the previous 12 months reported to ACO and PCP Monthly list of ACO diabetes patients who have not had a Blood

Pressure reading within the previous 12 months reported to ACO and PCP

Monthly list of ACO diabetes patients who have not had a primary care visit within the previous 12 months reported to ACO and PCP

Monthly list of ACO diabetes patients who have a positive tobacco use history documented reported to ACO and PCP

Summary ACO beneficiary diabetes quality measure report quarterly

+Summary of Recommendations

LONG TERM CHANGES (12-24 MONTHS)

+Long Term Changes (12-24 months)

Revise model of diabetes care to utilize resources more effectively

Align ACO reporting to CMS to come directly from HIE, in lieu of individual group reporting on quality measures Disease registry for ACO beneficiaries created within HIE ACO participants send quality data to HIE via HL7 at the

end of each encounter ACO participants without EHRs can enter data directly into

HIE via web portal HIE reports quality data monthly to CMS

+The End!