CHCHiiR-R-AZHQAZHQ

Center for Health Information & Center for Health Information & ResearchResearch

Fall 2013 Stakeholder Fall 2013 Stakeholder MeetingMeeting

agenda

• Welcome/Introductions• Status of CHiR – Bill Riley & Tameka Sama

– existing program– what’s new & improved

• Project Updates/Results - Bill Johnson– trauma registry– physician, use, exchange & evaluation of EMRs

• Q & A• Remarks

welcome & introductions

• Name

• Position

• Organization

• Brief statement of affiliation with CHiR

• Interests going forward

status of

what hasn’t changed

• AZ Board of Regents research center

• Multidisciplinary

• Neutral source of information

• Community resource & tool

• HIPAA compliant environment

• Voluntary participation • Business Associate Agreements• Covered entities retain

ownership of data• Flexible data submission formats• Covered entities authorize data

uses/disclosures• Patients never identified in

research output without individual consent

data sharing partnership principles

data sources

Administrative claims data (ED, inpatient, outpatient, office visits)

Administrative claims data (ED, inpatient, trauma, outpatient/office visits)

Hospital discharge data (ED & inpatient)State Vital Records (birth/death certificate info)

Licensing & Survey data

• AZ Medical Board / AZ Board of Osteopathic Examiners

• AZ State Board of Nursing

• AZ State Board of Pharmacy

Sonora Quest Labs

Banner Health SystemDignity Health: ArizonaJohn C. Lincoln Health NetworkMaricopa Integrated Health SystemMountain Park Health CenterPhoenix Children’s HospitalScottsdale Healthcare

HEALTH CARE WORKFORCE

• Individual level health encounter data on millions of Arizona residents

• Geographically-based

• Sub-repositories

• Data sharing partnerships

• Tracks patients across health care systems and over time

Health Care Workforce

• Licensing data– demographics, education,

certifications

• Survey data– Questions differ across

licensing cycles– Current physician questions:

HIT– Current nursing/pharmacy

questions: Employment status/setting/role

– Physician surveys optional with licensing applications; Nursing & pharmacy surveys required

data repositories

what’s new, improved & under development?

Vision

• To provide comprehensive health care information for Arizona.

Goals

• Develop new business strategy

• Expand data architecture– Incorporate clinical data

(EMR/EHR)

• Increase available services– CHNA, etc.

• Advance data sharing partnerships

vision & objectives

health professional workforce

• Practicing Physicians (in state only)– MD -13,508– DO – 1,700

• Active Nurses– RN = 74,637– LPN = 10,525– NP = 4,336

• Pharmacy– Pharmacists – 6,179– Technicians – 15,984

15,208

89,498

22,163

Total126,869

Source: http://www.azmd.gov/MediaCenter/MediaFactSheet.aspx http://www.azdo.gov/MediaCenter/FactSheet.aspx; Daily Arizona Nursing Statistics, http://www.azbn.gov/; Arizona State Board of Pharmacy 2011-2012 Annual Report, http://www.azpharmacy.gov/pdfs/2012%20annual%20report.pdf.

licensed health care organizations

Total2,903

130 Hospitals (short/long term, critical access, psych, federal, children’s)

154 Ambulatory surgical centers

1,212 Outpatient treatment centers

101 FQHCs

21 Rural health clinics

1,249 Pharmacies

14 Individual health insurers

22 Employer group health plans

service opportunities

services we provide

community health needs assessments

• Useful for strategic planning, community benefit planning, grant proposals, and federal reporting (IRS).

• Uses data at the city and/or county level for specified zip codes

• Streamlined Basic Information Report – community demographics– community health care facilities & resources– community health needs (ED/IP use, insurance coverage, injuries,

deaths)– primary and chronic disease needs (asthma, heart disease,

diabetes, stroke, cancer incidence)– other health issues (behavioral health, risk factors, births)

• Data Sources: state hospital discharge data and birth/death records, publicly available data

data requests

• Various requests for data from: – university researchers & students– community researchers– providers– insurers– others

• Customizable from simple counts of a particular condition to more complex data sets for analysis with multiple variables from multiple sources.

• All HIPAA rules and business associate rules apply

• Standardized processing fees

health outcomes studies

• Most studied area• Defined as “research that seeks to

understand the end result of health care delivery.”

• Our goal: assist the health sector in reviewing the impact of health care services and improving the quality of care provided to consumers.– multi business associate collaborations

health workforce

• Longitudinal data systems to track the physician, physician assistant, nursing and pharmacy workforce in AZ.

• Combines survey questions with license applications.

• Analyzes and forecasts the supply and demand for these health professionals

• Analyzes the impact of health information technology.

• Model developed to assist in policy decisions that address workforce needs assessments and relate these to the available training programs in AZ.

current projects& results

AHCCCS/ASETAHCCCS/ASETHIE Cooperative Agreement HIE Cooperative Agreement

ProgramProgramSeptember 2013September 2013

Physician Adoption & Physician Adoption & Ranking of Electronic Medical Ranking of Electronic Medical

RecordsRecords2007-20132007-2013HighlightsHighlights

William G. Johnson, PhDWilliam G. Johnson, PhDProfessor of Biomedical InformaticsProfessor of Biomedical InformaticsFounder, CHiRFounder, CHiR

Gevork HarootunianGevork HarootunianSenior Statistical Programmer, CHiRSenior Statistical Programmer, CHiR

Center for Health Information & Research

Acknowledgements

I would like to gratefully acknowledge the contributions of Tom Betlach, the Director of AHCCCS; Lorie Mayer, HIT Director, AHCCCS; Jenna Jones, the Executive Director of Arizona Board of Osteopathic Examiners in Medicine and Surgery and Lisa Wynn, the Executive Director of the Arizona Medical Board.

The results to be presented today would not have been possible without their dedicated cooperation.

Data Collection Methods

• Data collection on physicians began in 1991. (Extended to nurses and pharmacists in 2007.)

• Survey data are merged with licensing applications.

• Scope of the survey limited by reliance on paper forms until adoption of electronic survey in March, 2012.

• Data are collected for in-state and out-of-state physicians. The current report is restricted to in-state physicians.

• Physicians with active licenses who are retired, semi-retired or on leave are excluded from the study.

Data Collection March 2012 – April 2013

Source: Arizona Medical Board (AMB), Arizona Board of Osteopathic Examiners (ABOE) Survey and Administrative Data, 2012-2013.Note: Physicians who responded to the survey as retired or semi-retired/on leave were excluded.

Utilization of Electronic Medical

Records

Center for Health Information & Research

Electronic Medical Records

• In 2012-2013, approximately 61% of Arizona physicians who responded to the survey used some type of electronic medical record (EMR)

• In 2009-2011, approximately 52% of physicians used EMRs

• In the 2007-2009 approximately 45% of physicians used EMRs

Methods of Storing Medical Records 2012-2013 vs. 2007-2009 & 2009-2011

Source: AMB, ABOE Survey Data, 2007-2009; 2009-2011; 2012-2013. Note: 2007-2009, Respondents who did not identify a method of storing medical records (missing): 390 for 2007-2009 and 2,567 for 2012-2013.*Data on “EMR alone or in combination” is not mutually exclusive from other categories.

The Persistence of Paper

• Paper records alone declined from 46% to 12%

» BUT

• Paper & scanned images combined with EMR tripled– Problem of gradual conversion of files– Problem of lack of HIEs so practices with

EMRs sharing data on paper/scanned images

EMR Rates by Type of Practice, 2012-2013 (N = 5,323)

Source: AMB, ABOE Survey Data, 2012-2013.Note: Rates = % of physicians within each practice type. 1,196 respondents were missing type of practice.

Type of Practice Rates Rank Government Health (VA, Indian Health Service, etc.)

95.80% 1

Hospital or Medical School Physician Group Practice

91.70% 2

Medical School/University/Research Center

91.60% 2

Community or Rural Health Center 91.30% 3Private Hospital System 87.40% 4State or County Hospital System 85.90% 5Physician Owned Group Practice 78.60% 6Non-Hospital Private Outpatient Facility 76.50% 7Other 69.20% 8Physician Owned Solo Practice 53.90% 9

Trends in the Target Population of Physicians without EMRs by County, 2012-2013 vs. 2007-2009

LocationNon- Users of EMRs as a Percent of Physicians

2012-2013 2007-2009Apache 31.3% 47.1%Cochise 17.2% 56.6%Coconino 17.6% 56.8%Gila 12.5% 67.7%Graham 12.5% 57.9%Greenlee 0% 57.9%La Paz 60.0% 66.7%Maricopa 19.6% 57.2%Mohave 20.0% 64.1%Navajo 31.0% 52.9%Pima 16.5% 56.0%Pinal 14.0% 52.1%Santa Cruz 0% 77.8%Yavapai 10.3% 62.6%Yuma 15.6% 73.3%Total 17.8% 57.6%Source: AMB, ABOE Survey Data, 2012–2013.

Summary 2007-2013

• Sources of growth– Incentives/penalties designed to induce

increases in use of EMRs– As older physicians retire they are replaced by

cohorts trained in use of EMRs (see med school rates)

– Decrease in percentage of physicians in solo practice

Utilization of EMR Functions

Center for Health Information & Research

Summary Utilization of EMR Functions

The Exchange Problem

• Most but not all physicians use the functions included in their EMRs but relatively few who use the functions also exchange the information with others. – Patient care summary is used by approximately 91%

of physicians but only 33% of the physicians exchange the information.

– The comparable percentages for prescriptions are 89% using the function and 48% exchanging the information.

– Public health information: 76% utilization and 31% exchange.

HIE: the next frontier in HIT

• EMR use is not universal but the upward trend is well established

• Problem: most of the benefits of EMRs require exchanges among organizations

• Lack of HIEs and failure of many attempts show need for solutions

• HINAZ continues to expand

EMR Software Use and Physician Rankings by

Brand

Center for Health Information & Research

EMR Use by Vendor ≥ 70 Users

Source: AMB, ABOE Survey Data, 2012–2013.Note: The “Other” vendor includes all vendors contracted with government hospitals/clinics. 2,820 physicians did not respond to the survey question on vendor name.

EMR Use by Vendor < 70 Users

Source: AMB, ABOE Survey Data, 2012–2013.Note: 2,820 physicians did not respond to the survey question on vendor name.

EMR Users Rankings of All Vendors: (1=awful: 5=outstanding)

CriterionWeighted

MeanNumber of Physicians

Ease of Use 3.3 4,640

Effect on Physician Productivity

3.0 4,619

Effect on Staff Productivity

3.1 4,597

Reliability 3.5 4,604

Performance vs. Promise

3.1 4,517

Mean of the Weighted Means

3.3 --

Source: AMB, ABOE Survey Data, 2012–2013.Note: Physicians practicing in government settings have been excluded from these results.

Summary of Rankings

• Despite widespread complaints about EMRs, average ratings are either neutral (3.0) or slightly positive (3.3)

• Rankings by vendor generally cluster around the overall means with some notable exceptions

Summary Ranking of Weighted Means by Vendor (N = 4,599)

Name of EMR/EHR- InState

Total Weight

ed Average Rank

Ease of Use

Doc Producti

vity

Productivity

Reliability

Performance vs

Promise

Total Responde

nts

Allscripts 2.9 3.0 2.7 2.8 3.3 2.8 541Amazing Charts

3.6 3.8 3.3 3.5 3.8 3.8 59

Aprima 3.1 3.3 2.9 3.2 3.4 3.0 46Athena Health

3.4 3.6 3.0 3.3 3.9 3.3 122

Cerner 3.0 3.0 2.8 2.8 3.4 2.8 732CHARTCARE

1.8 2.0 1.0 2.0 2.0 2.0 1

ClaimTrak 2.6 2.8 2.6 2.6 2.5 2.3 22eClinicalWorks

3.8 4.0 3.6 3.8 4.0 3.8 266

eMDs 3.6 3.7 3.4 3.5 3.8 3.4 80Epic 3.2 3.3 3.0 3.0 3.6 3.1 323GE Centricity

3.6 3.7 3.4 3.6 3.8 3.5 122

gloStream 3.8 4.0 3.9 4.0 3.8 3.4 9GMed 3.7 4.0 3.5 3.8 3.9 3.4 21

Summary Ranking of Weighted Means by Vendor (N = 4,599) (cont.)

Name of EMR/EHR- InState

Total Weight

ed Average Rank

Ease of Use

Doc Producti

vity

Productivity

Reliability

Performance vs

Promise

Total Responde

nts

Greenway Medical 3.4 3.5 3.1 3.4 3.8 3.2 56

HealthPort 4.0 4.0 4.0 4.0 4.0 4.0 1McKesson 3.0 3.0 2.8 2.9 3.3 2.8 208Meditech 2.9 2.8 2.7 2.7 3.2 2.8 67NextGen 2.9 2.9 2.7 2.8 3.2 2.8 374Noteworthy 3.3 3.3 3.4 3.3 3.6 3.1 29Office Practicum 3.7 3.8 3.5 3.7 4.0 3.8 26

Practice Fusion

3.7 4.0 3.2 3.3 3.9 3.9 82

Sage 3.3 3.4 3.1 3.4 3.5 3.1 127SOAPware 3.8 4.0 3.6 3.7 4.0 3.6 22Sunrise 3.4 3.3 3.4 3.4 3.7 3.2 16Other 3.4 3.5 3.2 3.2 3.6 3.2 862Don't Know 3.1 3.2 3.1 3.1 3.3 3.0 385Average 3.3 3.4 3.1 3.3 3.5 3.2 --

Source: AMB, ABOE Survey Data, 2012–2013.Note: Physicians practicing in government settings have been excluded from these results.

Conclusion

• Percentage of physicians with EMRs is higher than national studies suggest, but much of the difference is due to difference in sample characteristics.

• Use of EMRs is generally limited to intra-office use with little electronic exchange of EMR data.

• Biggest obstacle is the absence of networks for the exchange of EMR data

• Variance among counties is very large with some rural counties having utilization rates higher than Maricopa and Pima.

• Many topics in the full report have been omitted from this presentation

Next Steps

• Current licensing renewal cycle ends in April 2014• Report on findings 2007-2014• Create new survey questions to be operational in

April 2014 (suggestions welcome)– Avoid asking same questions of same respondents

– Emphasize the effects of EMRs on practice

– Emphasize the nature of exchanging EMR information & barriers to exchange

– Create some separate decision trees for AHCCCS providers

Revising the Survey

• Organize a set of meetings to solicit suggestions for the issues to be addressed by the revised survey (October-November 2013)

• Draft the new survey and circulate among interested parties for comments (December 2013)

• January –March 2014 Software development & testing in cooperation with the licensing boards

• April 2014: implement the new survey

• YOU ARE ALL INVITED TO PARTICIPATE IN THE DEVELOPMENT PROCESS (sign up sheet is being circulated)

Trauma Registry

Sponsor: Arizona Biomedical Research Commission

2010-2014

Collaborative effort with the 8 Level 1 Trauma Centers and the Arizona Burn Center to:

Collect and merge trauma data into a repository to be used for reference and research as needed for:

• comparing processes and outcomes

• establishing benchmarks

• improving trauma care

• meeting the certification requirements of the American College of Surgeons.

database development and health outcomes study

Trauma 1 Registry: Falls Trauma 1 Registry: Falls

MortalityMortality

William G. Johnson, PhDWilliam G. Johnson, PhDProfessor of Biomedical InformaticsProfessor of Biomedical InformaticsFounder, CHiRFounder, CHiR

Gevork HarootunianGevork HarootunianSenior Statistical Programmer, CHiRSenior Statistical Programmer, CHiR

Center for Health Information & Research

Acknowledgements

I would like to gratefully acknowledge the contributions of the participating organizations: AZTRACC, ABRC, John C. Lincoln, St. Joesph’s, MIHS, and Scottsdale Trauma.

I would also like to specifically acknowledge the contributions of Tracey Sotelo, Executive Director of ABRC, Alicia Mangram, Medical Director of Trauma Services/Critical Care, JCL; James Dzandu, Trauma Research Manager, JCL; Michael Corneille, Trauma Medical Director of Research, JCL and Melissa Moyer, Trauma Registrar, JCL.

The Trauma 1 project would not have been possible without their dedicated cooperation.

Overview

• Data collected from JCL, Scottsdale, St. Joseph’s, and MIHS trauma centers from 2008-2011.

• Patients 60+ with ground level falls are identified and merged across to the ADHS Discharge and Vital Stats datasets.

• Trauma level data, demographic data, previous medical history, and death records will be utilized to examine factors associated with mortality after falls.

– Relationship of underlying cause of death with fall.

– Nature of the cause of fall: mechanical or medical.

– Predictive factors for mortality.

remarks

Center for Health Information & Research502 E Monroe St, Ste C320

Phoenix, AZ 85004-2430Web Site: http://chir.asu.edu

Email: chir@asu.eduMain: 602.496.2021 | Fax: 602.496.2020

William (Bill) Riley, PhDDirector & ProfessorSchool for the Science of Health Care Deliverywilliam.j.riley@asu.eduPh: 602.496.0878

William G. Johnson, PhDProfessor of Biomedical Informatics &Founder of CHiRwilliam.g.johnson@asu.eduPh: 602.516.4241

Gevork Harootunian, BSSenior Statistical Programmergevork.harootunian@asu.eduPh: 602.496.2008

Tameka Sama, MBASenior Coordinatortameka.sama@asu.eduPh: 602.496.2009

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