Partnering for Maternal Data Quality Improvement Elliott Main, MD: CMQCC Medical Director Anne Castles, MPH, MA: CMDC Project Manager Barbara Murphy, RN, MS: CMQCC Administrative Director Supported with grants from: Centers for Disease Control California Health Care Foundation

Presenter Disclosure(s): Objectives: Describe the initiatives in California to improve BC data quality Describe the national multi-organization effort to standardize maternity terminology Describe the importance of sharing data in order to improve the data quality Presenter Disclosure(s): None

CMQCC and CPQCC Mission: Improving care for moms and newborns California Maternal Quality Care Collaborative (CMQCC) Expertise in maternal data analysis Developer of QI toolkits Host of collaborative learning sessions California Perinatal Quality Care Collaborative (CPQCC) Expertise in data capture from hospitals Established secure data center Data use agreements in place with 130 hospitals with NICUs Model of working with state agencies to provide data of value Both are Multi-Stakeholder Public/Private Quality Collaboratives With DPH playing a leading role

The California Maternal Data Center (CMDC) Project Vision Build a statewide data center to collect and report timely maternity metrics—in way that is low cost, low burden and high value for hospitals Produce metrics that will support QI and L&D service line management Improve quality of administrative data Facilitate reporting to national performance organizations Over time, publicly report select set of robust measures to inform decisions of childbearing women Low Cost: The Maternal Data Center is being financed in its beginning stages by both the CDC and the California HealthCare Foundation. Because of this funding, it is anticipated that, for at least the next 2 years, there will be no hospital participation fees. Data Quality: There’s no reason to duplicate data reporting efforts when most of the required data is already being captured via administrative data sets such as OSHPD PDD and the birth certificate data. We know admin data is not perfect, but our philosophy is to work with hospitals to improve the accuracy and completeness of those data sets, rather than setting up a whole new, duplicative data reporting effort. As part of this initiative, want to provide tools to assist with data quality improvement, as well as clinical quality improvement. Over time, as hospital have chance to work on both clinical and data quality, work towards publicly reporting a select set of measures, much as CMS is already doing with the Medicare-related perform metrics. The goal is to provide childbearing women with high quality information with which to base their health care decisions.

PDD--Discharge Diagnosis File Birth Certificate File CMQCC Maternal Data Center: Data Flow PDD--Discharge Diagnosis File (ICD9 codes) Birth Certificate File (Clinical Data) Many IRBs! Uploads electronic files Links Birth Data to OSHPD file Runs exclusions 3. Identifies CS and Inductions 4. Prints list of charts for review CMQCC Data Center Web-based Client-Server Application (secure) Local encryption of protected health information (PHI) This approach is very similar to that taken by NSQIP (National Surgical Quality Improvement Program) Hospital uploads data to CMDC and then can see their own data with PHI This allows them to add data on individual patients The CMQCC server and staff do not have access to un-encrypted PHI such as name, medical record number (MRN) <39wk Elective Delivery CHART REVIEW Labor?/SROM? (~6% of cases for brief review) Limited manual data entry for this measure REPORTS Benchmarks against other hospitals Sub-measure reports Calculates all the Measures Mantra: “If you use it, they will improve it”

Why Improve Maternity Data? HISTORICALLY: Maternity data in PDD and BC used by researchers and public health professionals to track trends and practices NOW: An additional focus on evaluating and improving the quality of maternity services CMS Inpatient Quality Reporting Program: reporting of ED<39 weeks to start in 2013 Medi-Cal: Developing quality dashboard; likely to include perinatal metrics TJC to require reporting of perinatal set for hospitals that perform more than 1100 deliveries annually: to start 2014 QI Collaboratives: Patient Safety First and HENs :

How Many Horses Are At Your Data Trough?

Key Principle: The more users for the data, the greater the effort for improving data quality.

Maternal Data QI in California: 5 Components Standardize Definitions Education (providers and staff) Redesign / System Changes Improving Data as QI Project Create Value for Maternal Data QI for hospitals

Maternal Data QI in California: 5 Components Standardize Definitions reVITALize Project GA Toolkit (work with ACOG and Hospitals)

Obstetric Data Definitions Initiative National Conference August 2-3, 2012 Arlington, Virginia

Campaign Initiatives To nationally standardize obstetric clinical data definitions. To educate and advocate for national implementation of the standardized obstetric data elements and definitions in electronic medical records, birth certificates, and data registries To increase and improve performance measurement and implementation of the national obstetric data standards and encourage data aggregation.

In addition to primary funding from ACOG, we had the financial support of the March of Dimes, SMFM, and United Health Foundation. As well as the volunteer hours, expertise, dedication of individuals from a variety of organizations including federal agency partners. Over 80 national leaders in women’s health care with the common goal of standardizing clinical obstetric data definitions for use in registries, EMRs, and vital statistics

It’s the Language… The World of Clinical Obstetrics The World of Public and Admin Health Communications “Britain and America are two nations divided by a common language.” --George Bernard Shaw

It’s the Language… Different regions of the country may use terms differently … Even within an OB department, not everyone uses the same terms for the same condition… Different notes on the same patient, can have different terms used (induced vs augmented) Birth clerks and coders have to read the notes and then….guess? And then translate into their categorical systems

Pre-Conference Preparation Timeline 1 Pre-Conference Preparation Identified data elements from various sources, including: 2003 Birth Certificate ACOG/National Committee for Quality Assurance/Physician Consortium for Performance Improvement – Maternity Care Set Agency for Healthcare Research and Quality – Birth Trauma Injury Rate California Maternity Quality Care Collaborative – Healthy Term Newborn The Joint Commission – Perinatal Care Core Set Two rounds of surveys were completed by conference stakeholders to determine necessity of revision and priority Provided existing definitions from ACOG, ICD-09, Williams Obstetrics, the National Center for Health Statistics, and others to serve as a basis for revision discussion

Conference Proceedings 2 Conference Proceedings Over 80 national leaders in women’s health care with the common goal of standardizing clinical obstetric data definitions for use in registries, EMRs, and vital statistics 69 individual data elements up for consideration Attendees were divided into five workgroups to facilitate discussion and formulate revised definitions 53 revised data element definitions were developed and voted on by conference attendees 44 revised data element definitions received > 85% ‘Support’ votes 9 failed to reach 85% ‘Support’ and required additional revision Five workgroups = Labor, Delivery, Gestational Age & Term, Maternal Indicators Historic, Maternal Indicators Current Describe the hours of deliberation and voting

Post-Conference Follow-Up 3 Post-Conference Follow-Up The data element definitions not reaching 85% of attendee support were brought back into workgroup conference calls for additional discussion and revision 50 refined data element definitions were sent forward for Public Comment Public Comment was open NOV 2012 to JAN 2013 625 individuals, representing over 450 organizations participated Nearly 11,000 responses were received in support of the revised definitions Public Comment Review and Finalization (In Progress) Public Comment Process

Implementation (In Progress) 4 Implementation (In Progress) Publications Data Dictionary Articles Education Incorporation into Integrating the Healthcare Enterprise (IHE) profiles for EMR certification and Meaningful Use Clinical decision support EMR Patient Management Triggers Data quality auditing logic models Incorporation into coding and nomenclature What is next?

Thank You, Workgroup Leaders! Jennifer Bailit, MD, MPH, FACOG Kimberly Gregory, MD, MPH, FACOG Cleveland, OH West Hollywood, CA Debra Bingham, DrPh, RN Washington, DC Tina Groat, MD, MBA, FACOG Canton, MI Gerald Carrino, PhD, MPH White Plains, NY Isabelle Horon, DrPH Baltimore, MD Suneet Chauhan, MD, FACOG Norfolk, VA David LaGrew, MD, FACOG Fountain Valley, CA Rebekah Gee, MD, MPH, FACOG Baton Rouge, LA David Lakey, MD Austin, TX Pause on this slide. Summarize main objectives Why data standardization is important Multistakeholder, multidisciplinary collaborative process with 60 day Public Comment of reVITALize Thanks to those who: participated in Public Comment, attendees who came to reVITALize, operational and clinical leaders who helped shepherd us through the process everyone in the audience, who will help disseminate, implement and incorporate them into practice documentation William Sappenfield, MD, MPH Tallahassee, FL

Maternal Data QI in California: 5 Components Standardize Definitions Education: Incent complete and accurate documentation among Providers Coders Birth Clerks Birth Data Quality Training Sessions (Vital Records) GA Toolkit (CMQCC, ACOG and Hospitals)

Findings for Key Fields: NTSV* CS Data Element Average Missing1 Average Missing or Inconsistent2 Birthweight 0.0% -- Delivery Method 0.7% OB-GA 0.2% LMP 2.2% Presentation 4.6% 10.1% Parity 0.3% *Nuliparous, Term, Singleton, Vertex; aka Low-risk, First Birth CS (HP 2020, Joint Commission, CMS measure) 1CA BC data from Jan--Sep 2012 statewide all births 2CA PDD vs. BC from Jan–Dec 2011 statewide all births

Conclusions for Key Fields Definite Area for Improvement Fetal Presentation Even though clerks score in medium range for ease of finding and frequency of contradictory information, large percentage of actual missing /contradictory suggest a problem When asked to code less common clinical terminology (e.g. Occiput Anterior), BC clerks picked right answer only 14-31% of time. (Report p. 6)

Conclusions for Key Fields Fetal Presentation Terminology Vertex = Occiput = Cephalic OA, OT, OP Deep transverse arrest Face or compound Presentation may be missing for CS deliveries

Birth Data Quality Improvement Project 2012

Tool Kit & Tip Sheets Agenda & Letter from CMQCC & SCCPHD AVSS Data (January-June 2012) Tip sheets Worksheet CD of all files and tip sheets Contact information

Maternal Data QI in California: 5 Components Standardize Definitions Education Redesign / System Changes: Improve clinical documentation systems across hospital providers to facilitate complete and accurate data capture Standard Locations for Key Data Work with EMR vendors to generate worksheet Develop and disseminate coding best practices GA Toolkit (CMQCC, ACOG and Hospitals)

The California Birth Clerk Survey Goals Assess current data collection practices and challenges for key data elements Identify potential strategies for facilitating accurate data capture by birth clerks

Data Issues for Gestational Age No EDD or GA in Doctor’s note(s) Multiple EDD / GA’s in L&D chart (which is best?) Multiple EDD’s in Prenatal chart (which is best?) Transcription errors when copying from prenatal Delivery occurring many days after the admission GA Revision of EDD / GA after admission Lack of a standard approach for using US to confirm/establish best EDD. Low Cost: The Maternal Data Center is being financed in its beginning stages by both the CDC and the California HealthCare Foundation. Because of this funding, it is anticipated that, for at least the next 2 years, there will be no hospital participation fees. Data Quality: There’s no reason to duplicate data reporting efforts when most of the required data is already being captured via administrative data sets such as OSHPD PDD and the birth certificate data. We know admin data is not perfect, but our philosophy is to work with hospitals to improve the accuracy and completeness of those data sets, rather than setting up a whole new, duplicative data reporting effort. As part of this initiative, want to provide tools to assist with data quality improvement, as well as clinical quality improvement. Over time, as hospital have chance to work on both clinical and data quality, work towards publicly reporting a select set of measures, much as CMS is already doing with the Medicare-related perform metrics. The goal is to provide childbearing women with high quality information with which to base their health care decisions. No wonder a Birth Certificate clerk may have difficulties!

Mandated Reporting of Maternity Measures Organization Measure BC Data Elements NOT in PDD (ICD9 codes) CMS Early Elective Delivery Best OB GA The Joint Commission NTSV Cesarean Section Best OB GA, Parity Antenatal Steroid Neonatal Sepsis Birth Weight Exclusive Breast Milk Feeding Again…Best EDD  Best OB GA is the critical BC data element for QI

Consensus for Identifying Best EDD Spong CY. Defining “Term” pregnancy: Recommendations from the defining “term” pregnancy workgroup. JAMA 2013 May 3:1-2. [E-pub of print]

Most Important Single Data QI Project is: Best EDD Medical Policy Issues When to change Best EDD based on US Criteria for US (sac <7wks, CRL <14wk, BPD <20wk) How to reconcile multiple US reports Need to improve wording of US reports for EDD Implementation/Process Issues Prenatal Best EDD Black Box on every record To be completed by 20 weeks Tweak new AMA/PCPI OB quality measure to capture this On admission, this EDD is transferred to a similar Hospital Best EDD Black Box used by all (including BC clerks)

Maternal Data QI in California: 5 Components Standardize Definitions Education Redesign / System Changes Improving Data as QI Project: Apply QI principles to improving accuracy/completeness of data Hospital-BC Missing Data Reports Comparisons of BC to PDD for audit and feedback QI Run Charts for Data Quality

Data Quality Reports Identify discrepancies or missing data in Birth Certificate and Discharge data files Use to target data performance/quality improvement Screen shot from the California Maternal Data Center

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--Each individual hospital within Riverside County-- Hospital Alpha with high rate --Each individual hospital within Riverside County-- 36

A hospital with a system for transferring clinical data to the BC 38

Maternal Data QI in California: 5 Components Standardize Definitions Education Redesign / System Changes Improving Data as QI Project Create Value for Maternal Data QI for hospitals (“If you use it, they will improve it”) Use BC/PPD data for internal QI Use BC/PPD data for QI reporting (e.g. to TJC) Use BC/PPD data for Public Reporting

New Joint Commission Decision As of July 2013, hospitals have option to use Birth Certificate data for TJC Perinatal Set for: OB Estimate of GA Birthweight Parity Implication  Abstract one time (well!) and satisfy both Vital Records and TJC requirements Potential to make hospital data collection and reporting activities more efficient Improves quality of data for use by state policymakers

Data Quality Improvement Birth Clerk education (Tip Sheets, classes) Strategies for improving provider documentation Consensus on using US to confirm/establish Best EDD (ACOG, IHI) Require GA/Best EDD at Delivery note Standard black-bordered box for Best EDD on Prenatal and L&D admission forms Harness EMR system(s) in a structured manner (remember GIGO) Use Audit and Feedback to improve data Time-course run-charts Drill down to individual cases for careful analysis Comparison to others Accountability!! Low Cost: The Maternal Data Center is being financed in its beginning stages by both the CDC and the California HealthCare Foundation. Because of this funding, it is anticipated that, for at least the next 2 years, there will be no hospital participation fees. Data Quality: There’s no reason to duplicate data reporting efforts when most of the required data is already being captured via administrative data sets such as OSHPD PDD and the birth certificate data. We know admin data is not perfect, but our philosophy is to work with hospitals to improve the accuracy and completeness of those data sets, rather than setting up a whole new, duplicative data reporting effort. As part of this initiative, want to provide tools to assist with data quality improvement, as well as clinical quality improvement. Over time, as hospital have chance to work on both clinical and data quality, work towards publicly reporting a select set of measures, much as CMS is already doing with the Medicare-related perform metrics. The goal is to provide childbearing women with high quality information with which to base their health care decisions.

A boy and his Killer Whale… Timely sharing of Vital Record data with partners invested in improving data quality is a winner for everyone! FREE the DATA

Thank You!