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Leveraging SPNS Initiatives to Leveraging SPNS Initiatives to Transform Client Level Data CollectionTransform Client Level Data CollectionTransform Client Level Data Collection Transform Client Level Data Collection
into Service and Quality Toolsinto Service and Quality Tools
Facilitated by:Facilitated by:Washington, DCWashington, DC Facilitated by:Facilitated by:
Catherine CorreaCatherine CorreaJesse Jesse ThomasThomas
August 23, August 23, 20102010
JesseJesse o aso as
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Today’s AgendaToday’s Agenda
• Problem Statement• Client Level Data CollectionClient Level Data Collection• Client Level Data Reporting
• Use of Client Level Data• Use of Client Level Data• Stakeholders and Technology
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Where Are We From?
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Who Are You?
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RSR!
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The Challenge and the Opportunity
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COMPAS ( 2) Vi l /eCOMPAS (e2) Visual / Clickabkle RSRClickabkle RSR
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RSR Aggregate DataRSR Aggregate Data• Preview of Client Level Data before submission to HRSA
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• eCOMPAS provides drilldown capability• Click on any number to see the client y
records that comprise that aggregate number.
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• …which allows you to go to any client’s record, and update their data accordinglytheir data accordingly.
• Changes are reflected immediately in the RSR, for the correct reporting time period.
• This is the eCOMPAS Time Machine feature and allows you• This is the eCOMPAS Time Machine feature, and allows you to correct past data historically, without creating problems in current data.
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• eCOMPAS also offers Data CleanupeCOMPAS also offers Data Cleanup Tools, which will check for inconsistent or invalid data alert you to them and allowinvalid data, alert you to them, and allow you to correct them.
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Y d t lti l li t t• You can even update multiple clients at the same time.
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• And uploading the data to the HRSA EHB is real-time and easyis real time and easy.
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eCOMPAS RSReCOMPAS RSR
The RSR process was transformed from aThe RSR process was transformed from a mandated challenge into a user-friendly, data quality improvement opportunitydata quality improvement opportunity
and still serves today as a quality improvement tool used by Case Managers.
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Cross-Part Collaborative Data
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eCOMPAS Supporting ImprovementImprovement
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Benchmark Data Feature AddedBenchmark Data Feature Added
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Cross Part Collaborative OutcomesCross Part Collaborative OutcomesAll Provid
120%
CCR Rel
100%
120%
60%
80%
ator
%
40%
60%
Indi
ca
CD4
VL
Med Visit
0%
20%
Med Visit
Syphilis
CCR Release
0%11/14/07 2/22/08 6/1/08 9/9/08 12/18
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Cross Part Collaborative OutcomesCross Part Collaborative OutcomesAll Providers - By Indicator
120%
CCR Release
100%
120%
60%
80%
ator
%
40%
60%
Indi
ca
CD4
VL
M d Vi it
0%
20%
Med Visit
Syphilis
CCR Release
0%11/14/07 2/22/08 6/1/08 9/9/08 12/18/08 3/28/09 7/6/09 10/14/09 1/22/10 5/2/10 8/10/10
Date
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Cross Part CollaborativeClinical Outcomes @ a GlanceClinical Outcomes @ a Glance
Bergen-Passaic Cycle 1-8 CPC Data120
89
79 80
91
82
77
93
8482
81
94
84 84
77
96
83 84
7780
100
120
51
5654
7262
53
42
66
78 76
54
54
73
79 80
67
56
78 76
62
77
61
63
77 77
40
60
80
Perc
ent
30
3642
20
40
0CD4s HAART Visits Prophylaxis Syphilis
Cycle
1 2 3 4 5 6 7 8
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Bergen-Passaic Indicators Improvement
95%90%
100%
Cross Part Collaborative (cycle 2-9)
48%66%
60%
70%
80%
33% 34%
20%
30%
40%
50%
0%
10%
20%
CD4 Screening HAART Visits Prophylaxis Syphilis Screening
Bergen Passaic
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ProactiveProactive
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eCOMPAS Alerts
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Agency Alerts
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Agency Alerts
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Client Header – On all screens
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Client Alerts Tab
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Email Alerts• Proactive, regular, push notification• Clicking sends to secure siteg• Same summary as the agency report in
eCOMPASeCOMPAS
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Email Alerts - Subscription• Everyone subscribed originally• Option to opt outp p
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Alerts Module Usage vs. OutcomesAlerts Usage vs. Number of Alerts
2400
2450
ts 450
500
s
CD4 Past DueVL Past DueAlerts Usage
2300
2350
ber O
f Clie
ntic
ated
)
300
350
400
ber O
f Tim
eed
Alerts Usage
2200
2250
lativ
e N
umb
(not
und
upli
150
200
250
ulat
ive
Num
bA
cces
s
2150
2200
Cum
ul
50
100
150
Cum
u
210011/3/09 11/23/09 12/13/09 1/2/10 1/22/10 2/11/10 3/3/10 3/23/10 4/12/10 5/2/10
Date
0
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Viral Load
70%
80%
50%
60%
ge Detectable
30%
40%
Perc
enta
g
Undetectable
10%
20%
0%2006 2007 2008 2009
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Medication Adherence
80.0%
90.0%
60.0%
70.0% 0/4 Taken
1/4 Taken
2/4 Taken
40.0%
50.0%
Perc
enta
ge 3/4 Taken
4/4 Taken
20.0%
30.0%
0.0%
10.0%
2007 2008 2009
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Leveraging SPNS Initiatives to Transform Client Level Data Leveraging SPNS Initiatives to Transform Client Level Data Collection into Service and Quality ToolsCollection into Service and Quality ToolsCollection into Service and Quality ToolsCollection into Service and Quality Tools
F ilit t d bF ilit t d bFacilitated by:Facilitated by:
Peter Whiticar, Peter Whiticar, Hawaii Dept. of HealthHawaii Dept. of HealthCharles LydenCharles Lyden AIDS Community Care TeamAIDS Community Care Team
August 23, 2010August 23, 2010
Charles Lyden, Charles Lyden, AIDS Community Care TeamAIDS Community Care TeamDon Kyles, Don Kyles, Life FoundationLife FoundationBryan Talisayan, Bryan Talisayan, Waikiki Health CenterWaikiki Health CenterJesse Thomas,Jesse Thomas, RDE SystemsRDE SystemsJesse Thomas, Jesse Thomas, RDE Systems RDE Systems
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Where Are We From?
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IntroductionToday’s AgendaToday’s Agenda
IntroductionProblem Statement and Vision
MethodologyMethodologyOvercoming ChallengesOutcomes and BenefitsOutcomes and Benefits
Lessons LearnedConclusionConclusion
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Panel and Our Roles in Project
•• Peter Whiticar, Peter Whiticar, Hawaii Dept. of HealthHawaii Dept. of Health•• Charles Lyden, Charles Lyden, AIDS Community Care TeamAIDS Community Care Team•• Don Kyles, Don Kyles, Life FoundationLife Foundationy ,y ,•• Bryan Talisayan, Bryan Talisayan, Waikiki Health CenterWaikiki Health Center•• Jesse ThomasJesse Thomas RDE SystemsRDE Systems•• Jesse Thomas, Jesse Thomas, RDE SystemsRDE Systems
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Population 1,288,198
HIV/AIDS C b RGeneral PopulationWhite
African-American
HIV/AIDS Cases by RaceWhite
Asian
American Indian Alaska Native
Asian
Native Hawaiian
Hawaiian
African American
America Indian/Native Native HawaiianAlaskan
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Problem Statement
1. New HRSA and State data collection requirementsrequirements.
2. Aging, unsupported data system (Reggie)2. Aging, unsupported data system (Reggie) described as not user friendly and not meeting users’ needs.
3. Emerging emphasis on quality management.
4. Desire by everyone to provide better service and reduce unnecessary paperworkreduce unnecessary paperwork.
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Vision
1. Fully comply with federal and State data requirementsrequirements.
2. User-friendly and intuitive web-based system.3. Save time and reduce stress.3. Save time and reduce stress.4. Improve data quality.5. Empower users to retrieve and use data for p
better service.6. Share data through information exchange.7. Establish a platform for the next level of quality
management and innovation.
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Data Collection Systems TimelineData Collection Systems Timeline
COMPIS era ReggieHAWAII decade
1990 20102000 2008 2009
SPNS Grant
AwardedLife Foundation
begins using ReggieHAWAIIwith rollout to
Hawaii receives first Ryan White
CARE Act funding.
other agencies within 2 years
g
State mandates use of COMPIS for data collection and
reportingreporting
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M th d lMethodology
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SPNS
• SPNS made it all possible
• Joint SPNS application developed by DOH pp p yand lead ASOs
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Initial Strategy
• After surveying systems, none met needs.
• Decided to build own system.y
• Until HRSA AGM 2008 when saw Paterson• Until HRSA AGM 2008, when saw Paterson TGA and eCOMPAS.
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Current Strategy
• eCOMPAS serve as platform to be adapted to local needs and new innovationsneeds and new innovations.
O t ithi “ t hi di ” i t d f• Operate within a “partnership paradigm” instead of a traditional “transactional paradigm” with our technology partner to achieve our large vision in atechnology partner to achieve our large vision in a short time frame.
• RDE Systems, makers of eCOMPAS, fit perfectly with this needed approach.pp
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Surveying and Interviewing to Id tif P t ti l B iIdentify Potential Barriers
and Challenges
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S Fi di f thSome Findings from the Initial Provider SurveyInitial Provider Survey
M l f l lik thiM l f l lik thiMany people feel like thisMany people feel like this
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e2Hawaii Challengese2Hawaii Challenges
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e2Hawaii Challengese2Hawaii Challenges*Time. Project time has been halved, which means less time for specs clarification, prototyping, feedback, development, testing, and launch preparation.
*Any new system with significant changes impacts work processes. Change is not easy nor always accepted.
*Data Conversion from one system to another.
*New Data Sharing model increases complexity of data management training etc*New Data Sharing model increases complexity of data management, training, etc.
*Lack of detailed specifications at outset make it difficult to plan and begin development.
*New concept of using the system to help support more standard work practices is valuable, but presents organizational challenges.
*Infrastructure. Ensuring a secure subnet, VPN, and access to vendor is a new area, and may present challenges.
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Top 10 eCOMPAS Guiding Principles
1. People are the most important component in success!
2. Success should be defined holistically by each stakeholder.
3. Everyone should be more empowered with better information.
4. Better action requires better system intelligence.
5. Visual is better.5 sua s bette
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Top 10 eCOMPAS Guiding Principles
6. Think outside the box!
7. Ease of use is critical for success.
8. Time is better spent with clients than on paperwork!
9. Simple and clean is more powerful than complex and messy.
10. No one has all of the answers. But a great process, open to everyone, produces great results.ope to e e yo e, p oduces g eat esu ts
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Data Collection Systems TimelineData Collection Systems Timeline
COMPIS era ReggieHAWAII decade
1990 20102000 2008 2009
RDE Systems selected.
e2Hawaiie2Hawaii launched
e2 ver. 2 released
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Where are we?1. HRSA SPNS Award and User Advisory Group
Formed2 RDE Systems and eCOMPAS (e2) Identified2. RDE Systems and eCOMPAS (e2) Identified3. Stakeholder engagement throughout4 Many prototypes and pilots by RDE4. Many prototypes and pilots by RDE5. Regular user group feedback6 Beta Launch6. Beta Launch7. Security and Privacy Review8 Training Launch8. Training Launch9. Data Conversion by Life Foundation10.Data Conversion Launch 0 a a Co e s o au c11.Successful daily operation! We Are Here ☺
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Innovative Concepts
1. Cross-Agency Client Data Sharing for Care Coordination and Treatment
2. PHI Application – Standardizing HIPAA ComplianceCompliance
3. H-Programs (ADAP) Integrated with the g ( ) gState
4 Visual Interactive RSR for more than just4. Visual, Interactive RSR for more than just compliance
5. Health Information Exchange with Waikiki Health Center (Part C)
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Accomplishments and Outcomes1. One-day, smooth launch of very user
friendly system
2. RSR Compliant on Day 1
3. 3,795 clients and 409,000 units of services spanning over 18 years of data converted from legacy system 99 92%converted from legacy system. 99.92% data conversion success
4 Littl t t i i i d!4. Little-to-no training required!
5 High user satisfaction5. High user satisfaction
6. More engaged users
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Demo of HighlightsDemo of Highlights
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Client Intake – LoginClient Intake Login
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Client Intake – Access the IntakeClient Intake Access the Intake
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Client Intake – General InfoClient Intake General Info
• General Information Tab: Personal InfoGeneral Information Tab: Personal Info
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Service Delivery – Step 2Service Delivery Step 2
• Integrated Progress NotesIntegrated Progress Notes
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Scenario:Scenario:Referral from One Agency to
Another Agency
With Data Sharing!
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Authorization ConfirmationAuthorization Confirmation• Added document successfully• Easily editable• Client Shared between two agenciesClient Shared between two agencies
automatically
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Client Shows Up in Agency #2’s Client List
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Scenario:Scenario:Reporting
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Expenditures ReportExpenditures Report
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Service Performance ReportService Performance Report
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Roster Report - FilteringRoster Report Filtering
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Roster Report - OutputRoster Report Output
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SScenario:H-ProgramsH Programs
Problem Statement and Vision
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H-Programs – Step 1: SharingH Programs Step 1: Sharing
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H-Programs – Step 2: CertificationH Programs Step 2: Certification
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H-Programs – ValidationsH Programs Validations
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H-Programs – Step 3: ApplicationH Programs Step 3: Application
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H-Programs – Step 3: Application cont.H Programs Step 3: Application cont.
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State Department of Health’s View –P i A li tiProcessing Applications
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H-Programs – Processing ApplicationsH Programs Processing Applications
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Real-Time Updated Information Bet een Case Managers and StateBetween Case Managers and State
Department of Health
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H-Programs – Data ExtractH Programs Data Extract
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Summary of Highlighted FeaturesHighlighted Features
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FeaturesFeatures
• History audit trailsHistory audit trails
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FeaturesFeatures
• System AnnouncementsSystem Announcements
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FeaturesFeatures
• Visual AnalyticsVisual Analytics
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FeaturesFeatures
• One-Click RSROne Click RSR
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FeaturesFeatures
• Comprehensive Medical ModuleComprehensive Medical Module
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Part C SPNS Vignette:Part C SPNS Vignette:
U i Cli t L l D tUsing Client Level Data Requirements to Drive State-Wide q
Electronic Health Information ExchangeExchange
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The Old WayThe Old Way
ManualData Entry
ManualData Entry
ManualData Entry
Reggie
For:
P ti
For:
P t B
For:
P t CPractice Management
and EMR
Part BBilling andReporting
Part CRSR
Reporting
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Problems with the Old Wayy• Triple data entry!
• Data quality errors and time lost due to triple data entrydata entry.
• Keeping all sources of data in sync not feasibleKeeping all sources of data in sync not feasible – meaning data is not kept current in all systems.
• Data is not used fully for quality improvement.
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The New VisionThe New Vision
ManualData Entry
eCOMPASData Import
• Part B Billing• Part B Reporting
P t B RSRData ImportEngine
• Part B RSR• Part C RSR• Quality Management
and Quality Reportsand Quality Reports
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Project Challengesj g• EHR had incomplete and out-of-date Data Dictionary.
• EHR documentation incomplete and out-of-date No Data Extract capability.
• EHR training insufficient for report generation and data extracts.extracts.
• EHR doesn’t track all fields required by HRSA Ryan WhitWhite programs.
• The exported data must follow both HRSA requirementsThe exported data must follow both HRSA requirements and State-specific requirements.
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Methods Used to Overcome Challengesg
• A “Whatever it takes” paradigm – not a “That’s not my job” attitudejob attitude.
• Extra effort and flexible schedules between partners: late i ht d l i (ti diff )nights and early mornings (time difference).
• Great collaboration and “fun” working atmosphere toGreat collaboration and fun working atmosphere to offset additional work and challenges.
S t ti ll i d l d t d• Systematically reverse engineered poorly documented EHR database.
• Built a data extraction engine (eCOMPAS One Click Transfer).
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eCOMPAS DataImport EngineImport Engine
One-ClickTransfer
• Review Imported Data• Resolve Data Conflicts• Import Records
eCOMPASeCOMPASVisual RSR
• One Click Visual RSR
Upload toHRSA
• Quality Control Data• Generate Client Level
Data File
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Project Accomplishmentsj p• Extensive collaboration led to creative solutions for many
of the challenges and a foundation for future innovationof the challenges and a foundation for future innovation.
• Policies and data entry were modified to track additional fi ld i d b HRSA th t ’t i i ll t k dfields required by HRSA that weren’t originally tracked.
• Fully automated data import process and created rulesFully automated data import process and created rules for data conflicts so that the system prompts users only in cases when necessary and does so in a user-friendly wayway.
• Comprehensive security approach to ensure PHI is t t d d t dprotected end-to-end.
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Project Accomplishments cont’dj p• Estimated 80-90%+ data entry savings (some fields are
not tracked by EHR)not tracked by EHR)
• No further need to maintain multiple systems.
• Combined with innovative state-wide model of sharing data, this project will allow other agencies to see medicaldata, this project will allow other agencies to see medical data important to the treatment and service of clients.
L d P t C SPNS t t i t t l l• Leveraged Part C SPNS grant to integrate seamlessly with State-wide eCOMPAS system for sustainability.
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Lessons Learned
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Support and encourage staff so they’reSupport and encourage staff so they re not afraid to get their feet wet!
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Be Creative and Share your IdeasBe Creative and Share your IdeasThe small stuff counts too!
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One Team
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A Key Measure of Success
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Th S f L iThe Story of Lani
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Friday August 13, 2010
Hey you guys:
What a wonderful system to have at our beck and call!! The multi services screen is BEAUTIFUL!!! I love it. You all have exceeded yourselves in E2. I believe one can absolutely NOT make mistakes during the services input. The system allows one to 1) see your work, 2) make changes that are erroneous in just that ONE page instead of getting out of one2) make changes that are erroneous in just that ONE page instead of getting out of one
screen to access another to correct the error, 3) get finished in one-eighth of the time it originally took, 4) have plenty time to go on to other projects.
Gosh, you all are full of surprises. Myself did not know it would be so simple. Even a cave-man can do it!!
Thank you thank you thank youThank you, thank you, thank you…. Aloha, Lani
P.S. The client roster screen is very very informative. This is extremely beneficial to our case I k th th i t i h t t li h t W did tmanagers. I know they express their astonishment at your accomplishments. We did not
expect such detailed information.
Thank you again, Lani
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Some Ideas Moving ForwardSome Ideas Moving Forward
• Training for all levels learning how to useTraining for all levels, learning how to use data for many purposes
• Getting the data and into the system• Getting the data and into the system• Using data to focus effort to improve
di l tmedical outcomes• Lack on ongoing funding and DOH IT
resources• Use of e3Hawaii for HUD reporting like p g
NYC HOPWA
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Q&A
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How do we accomplish ambitious goals?
One bite at a time.
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