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Updated PCCI Vulnerability Index Highlights Progress, but Ongoing At-Risk Communities

By Thomas Roderick, PCCI’s Executive in Resident
& George “Holt” Oliver, MD, PhD, Vice President, Clinical Informatics

Why this post

More than a year ago, the data scientists at Parkland Center for Clinical Innovation (PCCI) committed to take the fight to COVID-19 by assisting North Texas residents, community leaders and public health officials through delivering actionable pandemic intelligence.

Many of us at PCCI and in the community have suffered the loss of family members, colleagues, coworkers, neighbors and friends. So with great relief we have witnessed tremendous scientific achievements in the development, approval and distribution of COVID-19 vaccines within a year. We have also seen the community evolve and adapt to life with COVID-19 and the actions expand from initial testing strategies to vaccine deployment, herd immunity projections and tracking, to now overcoming vaccination hesitancy and surveillance tracking of emerging variants, re-infections and individual/community immunity.

As our community and pandemic efforts evolve, so does the intelligence it needs. To meet that need, PCCI is evolving its technology and is pleased to announce the next phase of the Vulnerability Index.

What is the Vulnerability Index?

The Vulnerability Index is a measure of risk a community faces due to COVID-19. Higher risk means that people may be more likely to be infected with COVID-19, and if they do, they are more likely to experience symptoms and potentially face hospitalization and even death.

When the Vulnerability Index was first built, it covered factors correlated with COVID-19, including attributes in the community that don’t change quickly (like proportion of elderly population, people living with chronic conditions that are associated with COVID-19, and Non Medical Drivers of Health) as well as dynamic factors that increase immediate risk, like active COVID-19 cases and the mobility of the people living in the community.

How has the Vulnerability Index changed?

The North Texas community has evolved in two very important ways, and so the Vulnerability Index is changing as well.

    • First, as with the rest of the world it has adopted mask-wearing, social distancing, hand washing, and other hygiene and behavioral recommendations from public health authorities to limit the spread of COVID-19. Combined with the full opening of the economy, this means that a mobility factor has less relevance in identifying risk, because people change their behavior when they are out shopping at the grocery store, working, visiting parks, and otherwise engaging in the community. Without these behavior adjustments, mobility would continue to be important to monitor and understand, but not a critical factor in predicting neighborhood vulnerability.
    • Second, the introduction and uptake of the vaccine has started the process of lifting communities to herd immunity (HI), which is where the virus has a hard time finding people to infect because enough people have antibodies. As more people get vaccinated, there are fewer people in the community to become infected, and the community is less vulnerable.

An important caveat is that COVID-19 variants can continue to arise. PCCI is conducting ongoing surveillance on reinfections across Dallas County to assess the emergence of new variants, transmission and potential drop off of previously developed immunity. If this happens it means the mediating effect of the vaccination against COVID-19 risk may be decreased – so more people face infection risk. This is also captured in the updated Vulnerability Index.

How is the Vulnerability Index used?

The Vulnerability Index is used to inform how the communities and municipalities across Dallas County coordinate efforts to improve access to testing, vaccinations and create a path towards herd immunity. Below is a balloon plot, which shows cases on the horizontal axis and vaccinations on the vertical axis. It highlights HI progress in early April for ZIP codes across Dallas County. Each circle represents the current progress; each tail shows the improvement over two weeks. Upward “balloon” trajectory is favorable as it indicates that improvement was a result of vaccinations, not infections.

Source: The Parkland Center for Clinical Innovation

One thing that immediately jumps out is that ZIP codes with higher static vulnerability (or long-term risks in a community that do not change quickly such as age, medical comorbidities and social/economic factors) were slower at vaccine uptake. A potential reason for this is Non Medical Drivers of Health (NMDOH) – people who live in these zip codes may be in jobs that are not conducive to have the ability to take time off from work and to travel to vaccine sites to be vaccinated. This information is used by community organizers, public health officials, and health care providers to coordinate efforts and target each community in a way that removes barriers to vaccinations and target information and education via convenient and trusted sources.

Excelsior!

Ongoing vigilance against the virus remains key, and this includes getting vaccinated at your first available opportunity. As we enter the second summer in the pandemic, we at PCCI are committed to monitoring for COVID-19’s continued impact on the community, whether through improving the view into impacted communities, the impact of variants, reinfection risk, and more.

For more information about how PCCI has taken the fight to COVID-19, go to: https://pcci1.wpengine.com/taking-the-fight-to-covid-19/

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World Asthma Day: How PCCI’s predictive model helped improve care low-income children with asthma in Dallas

As part of May’s Asthma Awareness Month and World Asthma Day (May 4), PCCI is presenting its work, partnering with Parkland and the Parkland Community Health Plan, where its platform supporting pediatric asthma has helped thousands of children, dramatically reduced hospital visits and resulted in millions of dollars in cost savings. Following is an overview of the pediatric asthma programs that PCCI has played a key role in developing.

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How PCCI’s predictive model helped improve care low-income children with asthma in Dallas

By Yolande Pengetnze, MD, MS, FAAP,
Senior Medical Director, Parkland Center for Clinical Innovation

Bringing together advanced data science and clinical expertise to help at-risk populations is a primary mission at PCCI and the results derived from our program to help improve care and outcomes for children with asthma, demonstrate the effectiveness of this approach.

Working closely with leaders from Parkland Community Health Plan’s (PCHP) team, PCCI developed a predictive model to help reduce the incidence and cost of asthma-related emergency department (ED) visits and hospitalizations among Medicaid-insured low-income Dallas children.

PCHP and PCCI launched the Pediatric Asthma Quality Improvement Program in April 2015. The program was driven by the large number of PCHP members with asthma. Asthma is the most common chronic disease of childhood affecting over 6 million children in the US and resulting in over 140,000 hospitalizations every year.

Asthma disproportionately impacts low-income, urban, Medicaid-insured children compared with privately insured children. Asthma, however, also is an ambulatory-care sensitive condition, meaning that appropriate outpatient care and self-care can prevent unnecessary ED visits and hospitalizations, with subsequent substantial direct and indirect costs savings. The opportunity was ripe to really help disadvantaged children with asthma.

How the predictive model works
Beginning in 2014, PCCI developed a logistic regression model to predict asthma emergency department (ED) visits or hospitalizations within the following three months for children with asthma, using clinical, health services utilization and socio-demographic variables from Medicaid claims data. The risk prediction model classifies every patient as Very-High-, High-, Medium-, or Low-risk for asthma ED visits or hospitalizations and the prediction is updated every month, based on new data input.

Compared to published predictive models, PCCI’s model has a very good predictive accuracy (C-statistic 0.84), is derived from a relatively large and diverse population [3] and is well-evaluated [4]. The PCCI asthma model is continuously evaluated and updated every year, to improve its accuracy and enhance actionable insights that guide clinical and community-based interventions. Deep learning methods have been and additional Non Medical Drivers of Health (NMDOH) data have been evaluated to enhance model accuracy. Communitywide data sources have been incorporated to improve and fully assess model impact. Using this model, we were able to predict high risk asthma patients. We have integrated the risk-score into the electronic health record (EPIC) at Parkland as a Best Practice Alert (BPA), to drive timely and streamlined point-of-care interventions. We also generate monthly reports sent to frontline providers and Case Management teams and other non-traditional stakeholders. The monthly reports contained just the right amount of information on patients’ risk profile to drive seamless clinical and cross-organizational workflow integrations and tailored population-level interventions.

The interventions are adaptable: the reports are used, at the providers’ discretion, to either augment or streamline existing interventions or initiate targeted interventions, depending on clinical/community settings, resources, and priorities. The ultimate goals are to reduce unnecessary hospital utilization and cost, increase patient adherence to medication and preventive office visits, and improve overall health care experience. Moreover, we use the risk prediction model to directly engage higher risk patients into a text messaging program for patient education and medication reminders.

Finally, we used patient’s risk-stratification to identify providers caring for the highest risk patients and community sources of high-risk children for enhanced support for program participation and community-based interventions.

Dallas County Community Health Needs Assessment (CHNA) Quality Improvement (QI) Initiative
In 2019, Dallas County performed a Community Health Needs Assessment (CHNA) through which pediatric asthma was identified as a driver of high morbidity among children in the county. In 2020, a communitywide quality improvement (QI) program was launched aiming to improve asthma outcomes for all Dallas County children through data-driven interventions and cross-systems care coordination, following the PCCI Asthma Program model. To support this community-wide initiative, we enhanced our asthma risk prediction model with the addition of electronic health records data, which, together with claims and Non Medical Drivers of Health (NMDOH) data, predict asthma risk among Dallas County children with asthma.

The new model retains a good prediction ability and provides additional clinical insights not previously available using claims data only. With the addition of electronic health records data, our new asthma model can be used for all children irrespective of insurance status, thus expanding the benefits of our program to more vulnerable children with asthma. The asthma text messaging program also has been expanded to impact all children with asthma, irrespective of insurance status.

Moreover, community-based services providers in the social and Public Health sectors have been engaged to use PCCI asthma risk reports for community-based interventions beyond the traditional health care system. Community-based organizations and the Dallas County Health and Human Services department now use PCCI risk reports to drive community-based interventions such as home visits and outreach in community gatherings. The Dallas independent school district is also being engaged to use the risk reports for school-based interventions.

PCCI’s asthma risk model and reports are driving cross-organizational workflows and communitywide care coordination across North Texas, to improve health, educational, and quality of life outcomes for children with asthma and their families.

Insightful Community Risk Mapping
Over the past two years, we have added data insights capability to the program using local and regional maps to identify geographical areas with high risk patients and support targeted community outreach. Overlaying asthma risk maps with NMDOH maps (down to the block group level, see above) has uncovered discrete neighborhoods with asthma-risk and high social needs that might contribute to poor asthma outcomes, including transportation and childcare needs. These opportunity maps are driving community engagement to improve health, education, and wellbeing of children with asthma and their families.
Results

Since inception, PCCI’s pediatric asthma population health framework has not only reduced unnecessary hospital visits and costs, it has improved the healthcare experience for thousands of pediatric patients and their parents. The updated five-year impact report includes:

• Program expanded to support the communitywide Dallas County CHNA Asthma Quality Improvement initiative
• ~93,000 unique children with asthma risk-stratified to-date across both initiatives (PCHP and CHNA Asthma QI)
• Over 22,000 children with asthma risk-stratified every month and ~45,000 every year, with a rapidly increasing impact
• Over ~1800 high-risk children with asthma impacted by the text messaging program
• 21 large and medium community healthcare provider practices actively engaged, including two large Federally Qualified Health Centers (FQHC) and Parkland’s large network of community-oriented primary care clinics (COPC)
• Non-traditional community services providers engaged, including community-based organizations, Dallas County Health and Human Services community health workers, and Dallas ISD, using risk reports for community-, home-, and school-based interventions
• Dallas Fort Worth Hospital Council Foundation engaged as a source of comprehensive communitywide data to support data-driven interventions
• 30 – 40 percent reduction in asthma-related ED visits
• 50 percent reduction in asthma-related inpatient admissions

• 50 percent drop in annual total asthma cost to PCHP
• Approx. $30 million saved as a result of the risk-driven, multi-stakeholder pediatric asthma framework
• Moreover, the text messaging program has yielded an additional 6-fold drop in asthma-related ED visits among participants vs. non-participants
• Over 85% of participants remain in the text messaging program for more than 12 months and >90% feel empowered to care for asthma as a result of the program

Ongoing Program Enhancements
As we continue this program, we are evaluating the role of emerging deep learning models to improve our risk prediction model performance and explanation. Our original logistic regression model served as the baseline benchmark against which deep learning model results would be compared. We, also, are looking into adding block-level Non Medical Drivers of Health to provide additional actionable insights into patients’ asthma risk profile.

Claims data have strengths and insufficiencies worth highlighting. Claims data consist of billing codes that health care providers and facilities submit to payers. claims data follow a consistent format and use a standard set of pre-established codes that describe specific diagnosis, procedures, medications, as well as billed and paid amounts [5]. Additionally, claims data document nearly all interactions a patient has across all the health care systems. They capture broader information for patients and provide access to larger and more diverse patient cohort. Claims data, however, have a time lag of about 30 to 90 days due to the processing time before they are finally added to the database and become available for analysis. We have begun the process of bringing in additional and timely data sources to enhance or supplement claims data, including electronic health records data and communitywide health and social data, which are progressively improving the timeliness, accuracy, and insights of our asthma risk prediction models and risk reports.

Conclusion
In conclusion, patient education, preventive care, and appropriate use of asthma controller medications are the cornerstone of effective asthma care. Accurate risk prediction of asthma ED visits or hospitalizations, timely provider reports, patient education, and communitywide stakeholder engagement drive the prioritization of evidence-based interventions tailored to the highest risk patients, to efficiently reduce asthma-related ED visits/hospitalizations and associated costs, and improve care experience among children with asthma. By bringing together all the factors from PCCI’s predictive model and applying them to thoughtful and direct interventions, at-risk group of children and their families can experience better outcomes that are beneficial from the health, cost, societal, and consumer experience perspectives. Through our comprehensive approach to whole-person care, , the benefits of PCCI’s risk -driven asthma quality improvement initiatives, which started with one health plan, are now reaching deeper into the North Texas community, bringing quality, coordinated care to vulnerable children where they live, learn, and play.

About the author
Yolande Pengetnze, MD, MS, FAAP, Senior Medical Director, joined PCCI in December 2013 as a Physician Scientist while remaining a Clinical Faculty at the University of Texas South Western (UTSW) School of Medicine and a practicing pediatrician at Children’s Health in Dallas, Texas. Her interests include the use of advanced predictive analytics integrating traditional and novel data sources to improve health outcomes at the individual and population level. She currently leads multiple projects at PCCI, including two population health quality improvement projects in pediatric asthma and preterm birth risk prevention. She received her MD in 1998 from the University of Yaounde in Cameroon, completed a Pediatric Residency training in 2008 at Maimonides Medical Center in New York City, and a Master of Science in Clinical Science at UTSW.

[1] M. Xu, K. G. Tantisira, A. Wu, A. A. Litonjua, J.-h. Chu, B. E. Himes, A. Damask, and S. T. Weiss. Genome wide association study to predict severe asthma exacerbations in children using random forests classifiers. BMC medical genetics, 12(1):90, 2011.

[2] E. Forno, A. Fuhlbrigge, M. E. Soto-Quirós, L. Avila, B. A. Raby, J. Brehm, J. M. Sylvia, S. T. Weiss, and J. C. Celedón. Risk factors and predictive clinical scores for asthma exacerbations in childhood. Chest, 138(5):1156– 1165, 2010.

[3] M. Schatz, E. F. Cook, A. Joshua, and D. Petitti. Risk factors for asthma hospitalizations in a managed care organization: development of a clinical prediction rule. The American journal of managed care, 9(8):538–547, 2003.

[4] A. L. Andrews, A. N. Simpson, W. T. Basco Jr, R. J. Teufel, et al. Asthma medication ratio predicts emergency department visits and hospitalizations in children with asthma. Medicare & Medicaid research review, 3(4), 2013.

[5] W. J and B. A. The benefit of using both claims data and electronic medical record data in health care analysis. Technical report, Optum Insight, 2012.

National Asthma & Allergy Awareness Month: PCCI’s Pediatric Asthma Efforts Making A Difference With Dallas Children

To support  May being National Asthma & Allergy Awareness Month, please review the exciting programs and innovation PCCI has spearheaded to help children manage asthma:

27 MARCH 2020

IN THE NEWS: HCPLIVE – TEXT MESSAGE PLATFORM IMPROVES ASTHMA OUTCOMES

Yolande Pengetnze, MD, MS, senior medical director at PCCI spoke to HCPLive about a texting program designed to improve outcomes for patients with asthma and pregnant women, and how the technology can be used at other health systems and for other chronic conditions. Click the image below to read the full interview:

15 JANUARY 2020

PCCI POSTER PRESENTATION: PRETERM BIRTH & ASTHMA POSTER FROM IHI SCIENTIFIC SYMPOSIUM

PCCI’s text messaging program on asthma and preterm birth prevention was featured as a poster presentation at December’s Institute for Healthcare Improvement (IHI) Scientific Symposium. The poster program titled “A Novel Evidence-Based Approach to Digital Outreach Improves Patient Engagement and Health Outcomes in Two Distinct Cohorts of Medicaid Patients,” was presented by by PCCI’s Senior Read More »

30 DECEMBER 2019

2019 YEAR IN REVIEW: PEDIATRIC ASTHMA

Among its accomplishments this year, PCCI reported how its predictive modeling helped reduce the harm caused by pediatric asthma. Please click on the image below to see how PCCI’s efforts were applied:

12 SEPTEMBER 2019

TEXAS MEDICINE MAGAZINE HIGHLIGHTS SUCCESS OF ONE CLINIC’S ALLERGY AND ASTHMA PILOT PROGRAM

The September issue of the Texas Medical Association’s magazine, Texas Medicine Magazine, featured the efforts of C. Turner Lewis, III, MD, Medical Director of Children’s Medical Clinics of East Texas, to mitigate the harmful effects of pediatric asthma and alergies. Dr. Lewis employed a pilot program that included elements of PCCI’s predictive modeling to help Read More »

29 JULY 2019

DEEP LEARNING MODEL TO PREDICT PEDIATRIC ASTHMA EMERGENCY DEPARTMENT VISITS

Pediatric asthma is the most prevalent chronic childhood illness, afflicting about 6.2 million children in the United States. However, asthma could be better managed by identifying and avoiding triggers, educating about medications and proper disease management strategies. Parkland Center for Clinical Innovation (PCCI) has been working with the Parkland Community Health Plan (PCHP) for the Read More »

17 JULY 2019

DALLAS MEDICAL JOURNAL: PEDIATRIC ASTHMA CONFRONT THE BARRIERS

PCCI’s mission is to support our community’s vulnerable populations, which includes helping children with chronic health issues, such as pediatric asthma. PCCI has been working for several years developing and testing predictive models to identify children at risk for asthma exacerbations. You can now see how this predictive modeling was used to help support pediatric asthma patients Read More »

Slowing vaccination rates push back PCCI’s herd immunity forecast for Dallas County

Update on Dallas County Reaching COVID Herd Immunity From PCCI CEO Steve Miff

In February, Parkland Center for Clinical Innovation (PCCI) forecast that Dallas County had an opportunity to reach COVID herd immunity by mid-June. However, due to slowing vaccination rate, we have updated our forecast of Dallas County reaching the COVID herd immunity threshold to late-June with the possibility of falling back even further into July.

PCCI’s herd immunity forecasts in February was based on 80 percent of the county’s residents either having recovered from COVID-19 or having received vaccinations.

Today, herd immunity for the county is at 64 percent. While is represents progress, vaccination rates have slowed which is having a negative effect on our herd immunity forecast. The key driver making vaccine rates to regress include vaccine hesitancy and uptake, particularly in the working population.

While we’ve made great progress and to date vaccinated over 35% of the Dallas County population, including more than 73 percent of residents over 65 years old, the vaccination rates have been dropping, despite ample supply of vaccines and no wait times. In recent weeks, we’ve been averaging 45,000 vaccines administer per week, down from the mid and upper 60,000s in March. Therefore, due to the reductions in vaccinations, the herd immunity projections have been pushed to late June and could slip even further into July.

The longer it takes us to contain and crush COVID, the more chances the virus has to create new mutations that could be more transmissible, more deadly and more elusive to previously developed antibodies.

We encourage everyone to receive their COVID vaccination sooner than later. The quicker we can reach herd immunity the sooner we can return to safely interacting with our friends and families, teachers return to classes without fear and reduce the strain on our first responders, hospitals and their staff. But most importantly, reaching herd immunity via vaccines will help spare families the hardships of loved ones becoming ill or even losing their lives.

Steve Miff, PhD.
President & CEO
Parkland Center for Clinical Innovation

Expert Perspective: PCCI CIO testifies at Texas House Committee in favor of a making it easier to enroll MCO members into electronic communication

Vikas Chowdhry, PCCI’s CIO testified at the Texas State Capitol in front of the TX House Human Services Committee (chaired by Rep. James Frank) in support of House Bill 4343 sponsored by Representative Toni Rose (District 110). This bill will require HHSC to gather member contact preferences and gain their informed consent on the application, and then pass that consent to the Managed Care Organization (MCO), thus making it easier for MCOs to contact their members via their preferred electronic modes of communications such as texting.

PCCI has observed health outcomes greatly improve for Parkland Health Plan’s members through our pediatric asthma and pre-term birth prevention text messaging programs and we fully support this bill that will allow MCOs to expand programs like this.

 

 

 

 

 

 

 

 

(Rep. Toni Rose (center) with Kay Ghahremani, CEO of Texas Association of Community Health Plans and Vikas Chowdhry, CIO at PCCI)

 

Full text of testimony is follows:

HOUSE BILL 4343 (ROSE)

TESTIMONY OF VIKAS CHOWDHRY

Mr. Chairman, members, good morning (afternoon), my name is Vikas Chowdhry.  I am the Chief Analytics and Information Officer for the Parkland Center for Clinical Innovation – PCCI – and I am testifying in support of House Bill 4343.

PCCI started as a department within Parkland Health and Hospital System and was spun out as an independent, not-for-profit organization in 2012 to not only serve the needs of Parkland, but to also pursue additional transformative initiatives that could have a broader impact. PCCI remains tightly connected to Parkland, the Parkland Foundation and the Parkland Community Health Plan. Our collaborative work focuses on the needs of vulnerable populations across North Texas and beyond. Our work focuses on cutting edge uses of AI, Non Medical Drivers of Health, and clinical expertise across clinical and community settings.

Representative Rose, thank you for filing this bill.  Simply put, when a health plan is able to text its members, health outcomes improve.  They can do this now, but (as you heard) MCOs are required to first call a member and ask for their consent.  The problem is not having to seek the consent, which is entirely appropriate, but having to get the consent via a telephone call, because of course most people do not answer calls from numbers they don’t recognize.  In Representative Rose’s committee substitute, HHSC is tasked with gathering member contact preferences and sending those preferences to the MCO.  This should make it more likely that an MCO can contact a member via text.

Why is this beneficial?  At PCCI, we have documented the positive impacts of programs involving the texting of members.  In our Asthma program, we studied Parkland Community Health Plan members under the age of 18 who were enrolled in our text messaging program.  Those in the study received 3-5 educational or reminder text messages per week, including 2-item Asthma symptoms surveys once or twice a week.  We saw a 22.5% increase in asthma outpatient visits, and a six-fold drop in asthma-related visits to the emergency department.  84% of the respondents to our satisfaction survey said that the program has taught them to take better care of their child’s asthma

We performed similar research in our Preterm Birth Prevention Program.  Pregnant women enrolled in the program received four to five messages per week.This study produced positive results as well, with a 24 percent increase in prenatal visit attendance, and a 27 percent drop in preterm birth rates. More than two-thirds of the respondents to our satisfaction survey said that as a result of this program, they feel better prepared to take care of themselves and their baby.

The analysis that we have shared above is based on pre-COVID data. Through COVID period, we observed an overall reduced impact on outcomes across all these groups but even within that period, members enrolled in text messaging program still had better outcomes compared to those not enrolled. So, just through something as simple as a few text messages, we saw better health outcomes and less expensive care.  Texting works.

Mr. Chairman, Representative Rose, members, thank you for the opportunity to visit with you today.  I’m happy to answer any questions.

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Doing Our Part to Help Prevent Premature Births

In observation of Black Maternal Health Week, Parkland Community Health Plan (PCHP), in partnership with Parkland Center for Clinical Innovation (PCCI) want to highlight our efforts in Dallas to prevent preterm births, which is especially impactful on women in under-served communities.

To better serve pregnant women in our community, PCCI and PCHP developed and implemented an innovative maternal health program that uses a machine learning algorithm, healthcare data and Non Medical Drivers of Health to identify pregnant women who are at a higher risk of pre-term birth. The program engages these women through text messages designed to help them be proactive in seeking care during pregnancy.

Proactive care is critical because American women are more likely to die from pregnancy-related causes than women in other high-income nations and their own mothers a generation before. National severe maternal morbidity (SMM) rates have nearly doubled over the past decade, and the occurrence of SMM was 166% higher for African American women than white women from 2012 to 2015. More broadly, African American and Latino women, as well as socioeconomically disadvantaged populations, are disproportionately affected by poor health outcomes due to pregnancy related causes.

“One of the major risk factors for pregnant mothers and newborn babies is pre-term birth,” said John Wendling, chief executive officer of Parkland Community Health Plan. “Apart from adding to the risk during delivery itself, there are so many other long-term health and well-being risks for the mother and the child when a baby is born prematurely.”

The rate of preterm birth in Texas is highest for Black infants (14%) followed by American Indian/Alaska Natives (11%), and Hispanics (10.6%). In 2019, in Texas, 1 in 9 babies was born preterm. While there are many efforts to address poor maternal health outcomes in the US, most focus on preventing deaths during labor and delivery. Not enough attention is paid to the larger environmental context and non-traditional risk factors such as educational achievement, body mass index, socioeconomic status and mental and behavioral factors.

“As a local community health plan, we need to protect our at-risk pregnant women and the program we partnered with PCCI on is a very effective way to help,” said Wendling. “This program is a great example of a health plan utilizing sophisticated AI, Non Medical Drivers of Health and digital technology to improve patient engagement and experience. The long-term result is that we’ve positively affected the overall health and wellness of families in our community.”

The program has been running successfully for over three years in seven counties in North Texas and has risk stratified 40,000 unique pregnancies. We’ve seen preterm births reduced by 20% during this period. In a survey of the program participants, 73% of respondents agreed this program made them better prepared to take care of themselves and their babies.

“Not enough funding in healthcare innovation goes towards serving the vulnerable populations and that has exacerbated the digital divide,” Steve Miff PhD, president and chief executive officer of PCCI. “This pre-natal program with PCHP is a powerful application of advanced data science and technology at the point of care that focuses on the whole person to improve lives for the most vulnerable.”

PCCI’s Vikas Chowdhry, MBA (chief analytics and information officer) and Dr. Yolande Pengetnze (senior medical director) have helped oversee the success of the program in collaboration with key stakeholders at PCHP including Dr. Mark Clanton (chief medical officer) and Paula Turicchi (chief strategy officer). PCCI has filed for several patents related to this platform.

“In addition to PCCI’s technology created to use data analytics for maternal and pediatric health, this cutting-edge platform has been key to impacting innovation for COVID-19 related work, Parkland Health and Hospital System and Dallas County,” Miff said. “This unparalleled use of machine learning algorithm, healthcare data and Non Medical Drivers of Health to create practical, usable solutions will continue to impact of this investment in Dallas county and beyond.”

About the author

Vikas Chowdhry, MS, MBA, is PCCI’s Chief Analytics and Information Officer with 15+ years of healthcare experience. He works closely with data science and clinical teams at PCCI to develop machine learning driven technologies and products that can empower clinical and social services providers and individuals to create communities that are healthier and more productive.

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PCCI Names Healthcare Technology Expert, Russell “Rusty” Lewis, as Chief Digital Technology Officer

Dallas, Texas – Parkland Center for Clinical Innovation (PCCI), which improves healthcare for vulnerable populations using advanced data science and clinical experts, has named Russell “Rusty” Lewis as Chief Digital Technology Officer, where he will accelerate the advancement of PCCI’s digital technology platform and data applications.

“We are so pleased to welcome Rusty to our team of clinical and data science experts who are leading the industry in solving some of the most challenging issues facing vulnerable populations,” said Steve Miff, PCCI’s CEO and President. “Rusty is joining an existing dynamic team of top industry experts and his experience and vision will make PCCI’s groundbreaking AI/ML platform even more robust and impactful. Our partners and collaborators will find his humble, yet fun and outgoing personality a pleasure to work with.”

As a member of PCCI’s advisory team since 2017, Lewis is uniquely familiar with PCCI’s programs and leading-edge technology, enabling him to make a rapid impact. He will assume duties immediately, reporting to PCCI’s CEO in Dallas.

Lewis’ professional career spans a wide range of health care firms and technology roles, and most recently served as President of AppianRX, a manufacturer of healthcare-oriented artificial intelligence products. Previous to that, he was Group SVP of Data, Analytics, and Product Delivery for Vizient and Provista. Lewis also served as SVP and Chief Technology Officer for McKesson and later served as President of the Automation and Technology division of AmerisourceBergen.

Lewis has also served as a senior executive in a number of venture-backed health information technology (HIT) start-ups including Ameritech Health Connections, Bridge Medical Systems, and Skylight Healthcare Systems. Lewis began his career at Texas Instruments and holds more than 15 international and U.S. patents spanning handwriting recognition, virtual reality, clinical software and medication management systems. He is author of two books – “Impact of Information Technology on Patient Safety” and “Barcode and Auto-ID Implementation Guide” – both of which are published by the Healthcare Information and Management Systems Society (HIMSS).

Lewis holds degrees in computer science and applied mathematics from Southern Methodist University. He is a past board member of the National Alliance for Healthcare Information Technology (NAHIT) and Microsoft’s Healthcare User’s Group (MSHUG).

About Parkland Center for Clinical Innovation
Parkland Center for Clinical Innovation (PCCI) is an independent, not-for-profit, healthcare intelligence organization affiliated with Parkland Health & Hospital System. PCCI leverages clinical expertise, data science and Non Medical Drivers of Health to address the needs of vulnerable populations.

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PCCI’s Vulnerability Index Shows Lowest COVID-19 Infection Risk Level for Dallas County

DALLAS – Towards the end of March, Parkland Center for Clinical Innovation’s COVID-19 Vulnerability Index has recorded the lowest infection risk since the Vulnerability Index launched in June of last year.

“After the holidays, we had vulnerability index ratings at nearly 200, which meant the COVID-19 virus was running rampant through our community,” said George “Holt” Oliver, MD, Vice President of Clinical Informatics at PCCI. “It is a great relief to see that the highest vulnerability index rating now is only 16.91. This is a triumph for our county’s public health leaders, providers and residents who have made the sacrifices and efforts needed to bend the curve.”

One of the hardest hit ZIP Codes during the past year, 75211, which includes the areas around Cockrell Hill and Oak Cliff, saw its vulnerability risk hit the high of 196.9 in January. This was the highest level any ZIP code in Dallas County reached. By mid-March, its vulnerability rating was 8.74, a dramatic improvement for an area facing some of the most sever socioeconomic issues.

“This is very good news for the residents of the 75211 ZIP code; however, we advise caution going forward,” said Dr. Oliver. “I believe that our new normal will be continued vigilance. To keep COVID-19 from resurging, everyone who can be vaccinated should seek it, and adhere to local health official guidance that includes direction on social distancing and face covering.”

Launched in June 2020, PCCI’s Vulnerability Index identifies communities at risk by examining comorbidity rates, including chronic illnesses such as hypertension, cancer, diabetes and heart disease; areas with a high density of populations over the age of 65; and increased social deprivation such as lack of access to food, medicine, employment and transportation. These factors are combined with dynamic mobility rates and confirmed COVID-19 cases where a vulnerability index value is scaled relative to July 2020’s COVID-19 peak value. The PCCI COVID-19 Vulnerability Index can be found on its COVID-19 Hub for Dallas County at: https://covid-analytics-pccinnovation.hub.arcgis.com/.

Currently, the 75150 ZIP code, at the intersection of Interstate Highway 30 and 635 has the highest COVID-19 risk at 16.91, down from a high of 107.30 in January. The ZIP code 75204, in east downtown Dallas, has the second highest vulnerability level at 15.81, down from a high of 126.5 in January.

PCCI’s forecast of Dallas County reaching COVID-19 herd immunity is still on-track but reaching that threshold is highly dependent residents receiving their vaccinations.

“With vaccinations available to all adults, we need to get in line and get immunized,” said Dr. Steve Miff, PCCI President and CEO. “We don’t want another year to go by where grandparents can’t hug their grandchildren. We have seen how safe and effective the current vaccines are, so it is the responsible thing to do for our friends, families and co-workers to get immunized.”

While always concerning when adverse reactions emerge, the action by the FDA to pause the J&J vaccine is out of “abundance of caution” and it’s a strong signal of how responsive they are to any potential safety concerns. Cerebral venous sinus thrombosis (CVST) with J&J vaccine has been reported in 6 young women (ages 18-48) among 6.8 million doses in the US. To date, Dallas County has administered 61% Pfizer, 35% Moderna, and 4% J&J. The syndrome has been dubbed vaccine-induced immune thrombotic thrombocytopenia.(VITT), based on a similar syndrome after the commonly-used medication heparin abbreviated HITT. The reported rates are much lower than IV Heparin which is used frequently in the hospital. While the risk benefit ratio of continuing to use J& J vaccine in the US COVID-19 vaccination plan may still make sense given the observed case fatality rate of 1.8% of COVID-19, prudence to understand the situation given the FDA emergency use authorization for use is warranted..

The FDA pause for the J&J vaccine will not significantly impact the PCCI initial estimate for Dallas County’s path to herd immunity by June. We were progressing towards herd immunity at a rate of approximately 3% per week, which was ahead of initial predictions. While the allocations for J&J were scheduled to increase and the latest developments will pause those vaccinations likely for days, up to several weeks, we forecast that Dallas county will continue to make progress at 2-2.5% per  week, which maintains the pace for mid-June.

A year in retrospective
With the COVID-19 pandemic ongoing for over a year, PCCI identified the zip codes with the highest average vulnerability from July 2020 through March 2021. These represent areas which have faced the highest risk during the COVID-19 pandemic to date.

Data Sources:
To build Vulnerability Index, PCCI relied on data from Parkland Health & Hospital System, Dallas County Health and Human Services Department, the Dallas-Fort Worth Hospital Council, U.S. Census, and SafeGraph.

About Parkland Center for Clinical Innovation
Parkland Center for Clinical Innovation (PCCI) is an independent, not-for-profit, healthcare intelligence organization affiliated with Parkland Health & Hospital System. PCCI leverages clinical expertise, data science and Non Medical Drivers of Health to address the needs of vulnerable populations. We believe that data, done right, has the power to galvanize communities, inform leaders, and empower people.

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Authors

Steve Miff, PhD., President & CEO of PCCI, George “Holt” Oliver, MD, Vice President of Clinical Informatics at PCCI and  Thomas Roderick, PhD, Senior Director of Data and Applied Sciences at PCCI.

“BUILDING CONNECTED COMMUNITIES OF CARE” BOOK EXCERPT Case Study – Engaging Patients—Location and Relationships Matter

Following is an excerpt from PCCI’s book, “Building Connected Communities of Care: The Playbook For Streamlining Effective Coordination Between Medical And Community-Based Organizations.” This is a practical how-to guide for clinical, community, and government, population health leaders interested in building connected clinical-community (CCC) services.

This section is from Chapter 6, “Clinical Providers Track.” The purpose of the Clinical Providers Track is to set out the stakeholders and processes required to integrate clinical entities, insights, programs, interventions, strategies, and measurement for the CCC.

PCCI and its partner Healthbox, offers readiness assessments as a service. If you and your organization are interested, go here for more information: https://pcci1.wpengine.com/connected-communities-of-care/.

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Case Study: Engaging Patients—Location and Relationships Matter

As part of our CCC history, PCCI has developed and tested a number of approaches to identifying individuals within the population of vulnerable and under-served Parkland patients who could benefit from screening for health related social determinants, engaging them in the completion of a brief risk assessment and subsequent linkage to available community resources. As with many of the elements of the CCC, this proved to be a learning experience in which initial, more conventional approaches gave way to new and more innovative approaches of engaging this population to optimize goal
attainment.

RECRUITMENT
Much of the initial work began with screening in the outpatient setting. Parkland has 12 Community-Oriented Primary Care (COPC) clinics located throughout Dallas County to serve local residents. Because the COPCs see a large number of patients on a daily basis, many of whom are considered vulnerable and underserved, these COPCs were determined to be a great
location to conduct the social determinant risk assessments. When a patient checked in for a visit, the office staff would provide the patient with a paper-based screening tool to self-administer. Trained community health workers were available in the waiting area to help, if required. Initially we felt like this approach made sense since the large number of COPC patients translated into large numbers of completed screening surveys. However, while there were a large number of initial screenings, the number was very low of patients that agreed to engage with a PCCI community health worker to connect with local community services. Many stated they were not interested or needed to leave the facility for another commitment. Other patients completed the needs assessment but left the COPC before staff members were able to connect with them. Of these, very few responded to follow-up phone outreach and the ones that did were hesitant about referral to community-based services. The team attributed this gap to the lack of personal engagement at the point of initial screening.

As a result of this initial experience, the team made some changes to the screening protocols. Three concurrent workflows focusing on different points of patient encounters were designed and tested. The three new points included: (1) engagement while the individual was in the ED, (2) engagement of individuals that had already left the ED, and (3) engagement of hospitalized patients on the medical/surgical floors of the hospital.

For the direct engagement while the individual was in the ED, licensed social workers conducted initial face-to-face screenings with patients awaiting care. The social workers were provided a list of eligible patients (those with multiple ED visits in the past year) and went room to room to conduct the screenings and determine if the patients were interested in connecting with community resources. Because many of these patient interactions took place while the individual was in the middle of an ED care visit, the PCCI team member was mindful of this and stepped aside, as needed, to ensure they didn’t interrupt the patient’s care. For those individuals that left the ED before screening, the PCCI team placed these individuals’ names and contact numbers on a sheet and later reached out to them by phone to explain the program and ask if they were interested in receiving information on community resources.

Finally, for those individuals undergoing an inpatient stay in the hospital, PCCI personnel obtained census data reports with information about eligible patients and then staff visited these patients in their rooms to conduct one-on-one conversations to implement the screening tool and to determine if the patients were interested in receiving more information about navigation services to community resources.


As shown in Table 6.1, a key learning from this undertaking was that the site matters in conducting the screenings and successfully connecting people to local programs for support. We learned that engaging patients during their inpatient stay was the optimal care setting in which to conduct screenings and then connect those patients to the appropriate community resources.

Establishing trust with patients early in the process was essential, both for completing the initial screening tool and for facilitating connection to community services. During our initial approach, we relied on self-administered screenings that provided little in the way of opportunity to establish a relationship with patients. Our modified workflow allowed our social workers and community health workers to verbally administer the screening tool and provide additional explanations as part of that exchange. This process also made the transition to navigation services virtually seamless and much more
effective. Feedback from patients has also been positive; most indicated that the information received was useful and many said they would share this information with other family members and close friends.

THE SCREENING PROCESS
The PCCI community engagement team consisted of six community health workers and two master’s-level, licensed social workers. Initially, the team consisted entirely of social workers, but our experience taught us that a blended staff model was more cost-effective. PCCI physician leaders coached all team members on how to be flexible and professional when working in the ED, where care moves at a rapid pace. The team needed to take cues from medical staff on where and when to step in to conduct the screenings. Similar trainings were delivered to those staff visiting patients in the hospital.

Over the course of the 6-month pilot, we were also able to identify a number of key elements that increased both the effectiveness and efficiency of the screening process. For example, we learned that it took on average 15 minutes to complete the assessment tool when it was facilitated by a team member but only 10 minutes when self-administered. While the self-administered survey took less time to complete, we found a much higher percentage of incomplete and inaccurate responses, making many of the screens useless. As would be expected, we also found that older patients—those 65 or older—took on average 20 minutes to complete the facilitated screening survey while younger individuals completed it in half the time. The difference was attributable to the amount of questions asked and attendant conversations, which were much more prevalent with older patients. Finally, once we began to work more closely with the patients and they developed a better sense of the purpose of the work, we encountered very few issues with obtaining consent from the patients to share their information with others.

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COVID-19 fatalities become the leading cause of death in Dallas County one year into the pandemic 

Dallas – With the anniversary of Dallas County’s first COVID-19 death having recently passed, mortalities due to the pandemic has become the leading cause of death among county residents, surpassing heart disease, cancer and strokes in the past year.

According to the Centers for Disease Control and Prevention (CDC), the first death in Dallas County was recorded on March 19, 2020. By March 21, 2021, deaths in Dallas County from COVID-19 stood at 3,763. This surpassed estimated deaths due to heart disease (3,668), cancer (3,356) and strokes (1,015) during that same period.

COVID-19 deaths in Dallas County saw their steepest increases starting in December. On Dec. 21, 2020, deaths due to COVID-19 stood at 1,841, but in the following three months deaths more than doubled, adding 1,922 more casualties.

“This is a sad milestone for Dallas County,” said Vikas Chowdhry, MBA, Chief Analytics and Information Officer at PCCI. “We can see that COVID-19 claimed the most lives following social gatherings and holiday travel beginning with Thanksgiving through Christmas and New Year’s. Starting in December we saw a startling spike of deaths due to COVID-19 that represented more than all of the deaths in the previous months we had experienced during the pandemic. This offers a valuable lesson going forward, that we must remain vigilant to protect ourselves, our families and friends.”

PCCI recently forecast that Dallas County may reach COVID-19 herd immunity by mid-June. However, in order to reach this threshold residents of Dallas County need to continue their efforts to protect themselves from infection. “We are remaining optimistic that we can reach herd immunity by the early summer, but the key is ongoing vigilance, including continued adhering to local health official guidance, social distancing, face covering, and registering for vaccinations as soon as possible,” said Chowdhry.

An animated graphic showing the evolution of the COVID-19 mortality rate in Dallas County can be viewed at https://covid-analytics-pccinnovation.hub.arcgis.com/, PCCI’s COVID-19 Hub for the region. This shows total COVID-19 deaths by day, based on data provided by the New York Times COVID-19 data tracking project. The mortality data includes both confirmed cases, based on laboratory testing and probable cases, based on specific criteria for symptom and exposure. This is per guidance form the Council of State and Territorial Epidemiologists.*

To help protect Dallas County residents, PCCI recently launched the MyPCI App, a web-based program to help inform the residents of Dallas County to their individual risks. The MyPCI App, free to register and use, is a secure, cloud-based tool that doesn’t require personal health information and doesn’t track an individual’s mobile phone data. Instead, it is a sophisticated machine learning algorithm, geomapping and hot-spotting technology that uses daily updated data from the Dallas County Health and Human Services (DCHHS) on confirmed positive COVID-19 cases and the population density in a given neighborhood. Based on density and distances to those nearby who are infected, the MyPCI App generates a dynamic personal risk score.

To use the MyPCI App, go to, https://pcci1.wpengine.com/mypci/, click on the link and register (Using code: GP-7xI6QT). Registration includes a request for individual location information that will be used only for generating a risk assessment, never shared. Once registered, simply login daily and a COVID-19 personal risk level score will be provided along with information to help individuals make informed decisions about how to manage their risk.

About Parkland Center for Clinical Innovation

Parkland Center for Clinical Innovation (PCCI) is an independent, not-for-profit, healthcare intelligence organization affiliated with Parkland Health & Hospital System. PCCI leverages clinical expertise, data science and Non Medical Drivers of Health to address the needs of vulnerable populations. We believe that data, done right, has the power to galvanize communities, inform leaders, and empower people.

 

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*The tallies reported here include probable and confirmed cases and deaths. Confirmed cases and deaths, which are widely considered to be an undercount of the true toll, are counts of individuals whose coronavirus infections were confirmed by a molecular laboratory test. Probable cases and deaths count individuals who meet criteria for other types of testing, symptoms and exposure, as developed by national and local governments.