Latest / Becker’s Healthcare Digital Health + Health IT / Dr. Mark Townsend, Chief Clinical Digital Ventures Officer at Bon Secours Mercy Health

Transcript

Dr. Mark Townsend, Chief Clinical Digital Ventures Officer at Bon Secours Mercy Health · Becker’s Healthcare Digital Health + Health IT

• 0:00
  Hello, everyone. This is Jacob Emerson with the
• 0:02
  Becker's Digital Health and Health IT podcast. Thrilled
• 0:05
  today to be joined by doctor Mark Townsend,
• 0:07
  who is the chief clinical digital ventures officer
• 0:10
  at Bon Secours Mercy Health. Doctor Townshend, thank
• 0:13
  you so much for taking the time to
• 0:14
  sit down with me on the podcast today.
• 0:17
  Sure thing, Jacob. I think, thanks for having
• 0:19
  me. Yeah. Absolutely. And before we dive into
• 0:21
  everything we wanna talk with you about, can
• 0:23
  you tell us a little bit more about
• 0:24
  yourself, your background in health care, and what
• 0:27
  it is that you're doing today at Bon
• 0:28
  Secours?
• 0:30
  Yeah. Sure. So I'll break that into three,
• 0:33
  I guess. So beginning, with myself,
• 0:36
  serving
• 0:37
  as chief clinical digital ventures officer,
• 0:40
  is,
• 0:40
  the job of a lifetime. It's a super
• 0:43
  cool job, and I'll describe that in a
• 0:44
  little bit of detail.
• 0:47
  I I think it would make sense to
• 0:48
  begin with my background.
• 0:50
  And, so my background,
• 0:53
  began as a physician, obviously,
• 0:55
  intent on on practicing internal medicine pediatrics,
• 0:59
  which allowed me to go into adult congenital
• 1:01
  cardiology and pediatric cardiology. So,
• 1:04
  four boards later,
• 1:06
  I I had the honor and privilege of
• 1:08
  of being part of a specialty that was
• 1:10
  essentially up and coming adult congenital cardiology,
• 1:13
  which put me on the front end of
• 1:15
  program growth, and development and, actually, technology growth
• 1:19
  and development as well,
• 1:20
  which which really led to my current role.
• 1:23
  So,
• 1:24
  as you mentioned, I serve at Bon Secours
• 1:25
  Mercy Health, and, we are the fifth largest
• 1:28
  Catholic health care system in the country.
• 1:31
  50 facilities, 10 regional markets.
• 1:33
  And we have a company called Accrete, which
• 1:35
  is our digital ventures arm.
• 1:38
  And so,
• 1:39
  my job as an operator is representing essentially
• 1:43
  the the core of of BSMH and knowing
• 1:46
  the operators and the pain points
• 1:48
  of our boots on the ground people, if
• 1:50
  you will, in the health system.
• 1:52
  They then come forward,
• 1:53
  with technology,
• 1:55
  you know, requests specific to individual pain points
• 1:58
  or use cases.
• 1:59
  And then what we've been able to do
• 2:00
  through Recruit is put together acceleration funding. So
• 2:03
  an operator comes forward with a problem,
• 2:05
  and,
• 2:06
  and they will create, for example, an offset
• 2:08
  in their budget to support a pilot. What
• 2:10
  we then do
• 2:12
  is then provide majority
• 2:14
  funding in real time, if you will, so
• 2:16
  without having to wait for a budget cycle
• 2:17
  to go by.
• 2:19
  And then we can accelerate some of these
• 2:21
  these relationships and technologies, and we can scale
• 2:24
  them throughout our organization. So,
• 2:26
  again, I'm blessed to be in this role.
• 2:29
  Super cool space to be in, and,
• 2:31
  and and, definitely sets us up for for
• 2:34
  a good conversation today.
• 2:36
  Yeah. Absolutely. Well, I appreciate that overview, Mark.
• 2:39
  And the first thing we wanted to talk
• 2:40
  with you about is something that we're hearing
• 2:42
  about from health systems all over the country
• 2:44
  all the time, and it's how they're increasingly
• 2:47
  using
• 2:47
  real world data. So,
• 2:50
  my my first question for you is what
• 2:51
  are some of the main challenges and opportunities
• 2:54
  for health systems in terms of integrating unstructured
• 2:57
  data into their clinical workflows and and ultimately
• 3:00
  improving care
• 3:01
  delivery at scale?
• 3:03
  Yeah. Sure. Great question.
• 3:05
  And you point out there the difference between
• 3:07
  structured and unstructured data, which is which is
• 3:10
  a key part of the conversation as well.
• 3:11
  So
• 3:12
  challenges and opportunities, quite frankly, can be synonymous
• 3:15
  here.
• 3:16
  Data acquisition is changing rapidly,
• 3:19
  changing as we speak, and we'll we can
• 3:21
  talk a little bit about that.
• 3:23
  And and so, you know, specific to our
• 3:26
  approach to data,
• 3:27
  the opportunity for us, and I like to
• 3:29
  say I'm standing on the shoulder of giants
• 3:31
  here who actually built this, but we built
• 3:33
  a an intentional
• 3:35
  approach to data aggregation,
• 3:37
  a data mart. And, and and so that
• 3:40
  data repository
• 3:41
  essentially empowers us then, for example,
• 3:44
  to then, formalize relationships,
• 3:47
  and with technologies that can can help us.
• 3:49
  And so one of the technologies I'd like
• 3:52
  to highlight today is Omni.
• 3:53
  And so OmniHealth,
• 3:56
  is an ecosystem
• 3:58
  and, again, that they partner through a group
• 3:59
  for for BSMA for Bontecore Mercy Health. So
• 4:02
  OmniHealth,
• 4:04
  you know, itself,
• 4:06
  pulls in 1,000,000,000 patient encounters,
• 4:09
  three and a half billion unstructured clinical notes,
• 4:12
  and and really is helping us with our
• 4:14
  approach to unstructured
• 4:16
  documentation. So the difference, of course, being structured
• 4:19
  documentation
• 4:20
  turns clinicians into data entry technicians. Right? And
• 4:24
  we have to enter data into specific,
• 4:26
  specific fields or discrete fields,
• 4:29
  unstructured data. And and and this is kind
• 4:31
  of an interesting time to be having that
• 4:33
  conversation because ambient documentation is growing.
• 4:36
  And and I think anecdotally,
• 4:40
  we're seeing that the length of the the
• 4:42
  clinical documents
• 4:43
  increasing.
• 4:45
  We're capturing more problems,
• 4:47
  and, arguably, we're capturing more unstructured data. And,
• 4:50
  you know, it's been
• 4:54
  a a a a hot topic in in
• 4:55
  health care to to really implement these technologies
• 4:58
  with ambient dictation.
• 5:00
  So so back to then, you know, the
• 5:02
  the making sense, if you will, of all
• 5:04
  of this data.
• 5:06
  You know, it it is important to have
• 5:08
  a data strategy as a health system. But
• 5:10
  then,
• 5:11
  the tools to essentially help us,
• 5:14
  parse that data, to read that data, to
• 5:16
  mine it, to look for a needle in
• 5:17
  a haystack essentially
• 5:19
  are,
• 5:20
  you know, really the the value propositions that
• 5:22
  empower relationships like the one we have with
• 5:24
  Omni.
• 5:26
  Certainly. And let's talk a little bit about
• 5:28
  your your most recent partnership with OmniHealth.
• 5:31
  You're you're partnered with them to unlock valuable
• 5:33
  insights from unstructured
• 5:35
  clinical notes. You just mentioned the rise of
• 5:37
  ambient listening all at health systems all over
• 5:40
  the country,
• 5:41
  Mark. So can you expand a little bit
• 5:43
  upon that in terms of what what you
• 5:46
  see as some of the biggest opportunities
• 5:48
  in leveraging this type of data for improving
• 5:50
  the care to your patients and then clinical
• 5:53
  decision making within the broader health system?
• 5:56
  Yeah. Sure.
• 5:57
  You know, we have talked for, I feel
• 5:59
  like, a decade or more about,
• 6:02
  you know, the growing interest in genomics and
• 6:04
  precision medicine, etcetera.
• 6:07
  And and,
• 6:09
  again, you know, with with that kind of
• 6:11
  needle in the haystack construct,
• 6:14
  you know, the the difficulty that we've all
• 6:16
  encountered, I think, as health systems is how
• 6:18
  do you wrap care around an individual,
• 6:21
  and and how do you customize care to
• 6:23
  an individual?
• 6:25
  It's difficult
• 6:26
  when, you know, an individual,
• 6:28
  data set specific to a a given patient
• 6:32
  is part of a very large ecosystem. Right?
• 6:34
  And so, you know, being able to parse
• 6:36
  down and find a specific patient,
• 6:39
  with a specific
• 6:40
  clinical presentation,
• 6:42
  or with a very specific,
• 6:45
  you know, component in their their problem,
• 6:47
  statement or their their past medical history, that's
• 6:50
  that's an example of that in a very
• 6:52
  granular sense. If you could then start there
• 6:54
  and say, okay. Well, what we're addressing then
• 6:56
  essentially are care gaps,
• 6:59
  then you start to, you know, think a
• 7:00
  little bit more broadly.
• 7:02
  And, in in addressing care gaps, for example,
• 7:06
  we are all,
• 7:08
  pulling in social and behavioral determinants of health,
• 7:11
  right, as part of our screening
• 7:13
  of of all of our our patients and
• 7:15
  our clinical populations.
• 7:16
  As we do that,
• 7:18
  for example,
• 7:19
  we are picking up on,
• 7:21
  gaps in care, not only just gaps in
• 7:24
  clinical care, but, for example, gaps in resources.
• 7:28
  And so we've really doubled down on addressing
• 7:30
  resource,
• 7:31
  constraints as well for our patients, again, wrapping
• 7:34
  care around them.
• 7:35
  So, you know, real world examples,
• 7:38
  housing insecurity,
• 7:40
  BSMH,
• 7:42
  as a Catholic health system, has a housing
• 7:44
  initiative. And, in some of our markets, we
• 7:46
  can actually help with that.
• 7:48
  Transportation limitations, for example, are very real world
• 7:51
  examples.
• 7:53
  And, capturing that in an
• 7:54
  unstructured
• 7:55
  format, you know, just in a conversation with
• 7:57
  a patient,
• 7:59
  allows us then to close those gaps. So
• 8:01
  we have partners,
• 8:02
  in that space as well that can really,
• 8:05
  service our patients and and close those those
• 8:08
  need gaps.
• 8:09
  And then taking all of,
• 8:11
  those individual
• 8:12
  resource constraints essentially
• 8:15
  and then pulling them into an after visit
• 8:17
  summary. You know, they're very real, use cases,
• 8:20
  and technologies that we're partnering with there as
• 8:23
  well.
• 8:24
  And so all of that now,
• 8:26
  you know, brings us full circle to the
• 8:28
  to the construct of, big data. Right? And
• 8:30
  so big data
• 8:32
  then allows us to look,
• 8:34
  at a population level for insights, and population
• 8:37
  based insights,
• 8:39
  you know, are really kind of exciting. And
• 8:41
  and,
• 8:42
  you know, whether or not we're talking about,
• 8:45
  you know, congestive heart failure
• 8:48
  as a KPI or, you know, whether or
• 8:50
  not, again,
• 8:51
  we're we're looking to match a specific patient,
• 8:55
  with a specific tumor
• 8:57
  with a clinical trial. Right? So all of
• 8:59
  those lend themselves to technology,
• 9:02
  again, empowered by data as an asset.
• 9:06
  Certainly. And just listening to you talk about
• 9:08
  this market, it seems like there's so much
• 9:09
  potential for this data. So I think the
• 9:12
  the natural follow-up question is, how do you
• 9:14
  foresee the role of health systems evolving in
• 9:18
  terms of using this type of data to
• 9:20
  drive innovation and to improve the outcomes for
• 9:23
  their patients?
• 9:25
  Yeah. Well, key term evolving.
• 9:29
  So it is evolving. It's evolving very quickly.
• 9:32
  And and I think
• 9:34
  you know, the expectations of our patients and
• 9:36
  the populations that we serve are evolving as
• 9:38
  well. Right? So, you know, I referenced essentially
• 9:41
  how they receive care,
• 9:43
  you know, how we match,
• 9:45
  you know, specific constraints in care delivery to
• 9:48
  to specific needs.
• 9:50
  The evolution,
• 9:51
  of of essentially using data to to drive
• 9:55
  innovation.
• 9:57
  Again,
• 9:58
  you know, it's it's worth doubling down on,
• 10:00
  for example,
• 10:01
  specific disease processes. So
• 10:04
  so the email I wrote right before jumping
• 10:06
  on this this call with you, was specific
• 10:09
  to a new structural cardiologist
• 10:10
  in our Kentucky market,
• 10:13
  which is awesome. And,
• 10:15
  as he as he joins, you know, his
• 10:16
  first question is, alright. So I want to
• 10:19
  essentially parse datasets
• 10:21
  specific to the application
• 10:24
  of clinical guidelines,
• 10:26
  and and I want to find patients who
• 10:28
  have care gaps.
• 10:29
  And and so I was able to write
• 10:31
  back. I was like, well, sure. We can
• 10:33
  do that. So beginning with aortic stenosis, for
• 10:35
  example, I mean, we can take,
• 10:38
  guidelines, and guidelines, for example, used to live,
• 10:41
  for example, in the brains of my partners,
• 10:44
  my cells, and, you know, the the,
• 10:47
  the resources that we use to to get
• 10:49
  our patient care, you can take those guidelines
• 10:51
  now as an algorithm essentially, and you can
• 10:53
  use them to curate a list of patients
• 10:56
  who have a care gap,
• 10:58
  around a very specific disease state. State. Again,
• 11:01
  my background in cardiology. So using this example,
• 11:03
  aortic stenosis, you know, thickening of the aortic
• 11:05
  valve, give me a list of patients who
• 11:08
  meet the clinical criteria for intervention
• 11:11
  but who have not received appropriate care. Right?
• 11:13
  So we can do that, and then we
• 11:15
  can essentially then,
• 11:17
  turn that over to a navigator or a
• 11:18
  new structural cardiologist in Paducah, Kentucky and say,
• 11:21
  here you go. These are patients that would,
• 11:24
  very, very much appreciate a call from you
• 11:26
  all. And and so that that is it's
• 11:29
  it's, evolving very quickly, but it's exciting.
• 11:33
  And
• 11:34
  and quite frankly,
• 11:36
  you know, sometimes a little bit overwhelming. Right?
• 11:38
  You know, the the technology is coming at
• 11:40
  us pretty quickly. So,
• 11:42
  you know, I'd like to say that that
• 11:44
  we're keeping pace,
• 11:46
  as a health system, and,
• 11:48
  I don't think we're, like, bleeding edge, but
• 11:50
  but but we we aspire to absolutely be
• 11:53
  leading edge. Right? I mean, the early adopters.
• 11:56
  Absolutely. And that's a great example that you
• 11:58
  shared with us, so I really appreciate that,
• 12:00
  Mark. And to follow-up on on your last
• 12:02
  point there, exciting, but but certainly can be
• 12:04
  overwhelming. So, you know, what's your advice for
• 12:08
  the other health system leaders listening in right
• 12:11
  now in terms of how they can better
• 12:13
  build a data driven culture like Bon Secours
• 12:17
  within their organizations, particularly as they also work
• 12:20
  to integrate diverse data sources from from EHRs,
• 12:23
  from clinical notes,
• 12:25
  and from patient reported outcomes?
• 12:28
  Yeah. Great question and a challenging one as
• 12:31
  well. I think the challenge
• 12:32
  for us as,
• 12:34
  operators, health care administrators,
• 12:36
  physician leaders
• 12:37
  is is to be able to challenge our
• 12:39
  health systems to really view data as an
• 12:42
  asset. Right? And so,
• 12:45
  I've I've had a hand throughout my career
• 12:47
  in data aggregation and and fortunately, was, you
• 12:51
  know, known as a data geek. And, hence,
• 12:53
  the people would come and as they were
• 12:55
  building, you know, our our first enterprise data
• 12:57
  warehouse, for example, in a prior health system,
• 12:59
  they would come to me and say, so
• 13:01
  give us examples of use cases. That's where
• 13:03
  there's a disconnect.
• 13:04
  And, again, you can pull together
• 13:06
  brilliant data teams, you know, who can aggregate
• 13:08
  data. There's infrastructure
• 13:10
  out there readily accessible,
• 13:13
  and and that has absolutely accelerated. But but
• 13:16
  it does need to be championed,
• 13:18
  you know, by by someone who who can
• 13:21
  actually understand the use cases. Right?
• 13:23
  So so finding out whether or not you
• 13:26
  have a data strategy, for example, whether or
• 13:28
  not you're aggregating your data, whether or not
• 13:30
  you've created a data mart, I think, you
• 13:32
  know, would be a good place to start
• 13:34
  and, you know, particularly
• 13:36
  smaller health systems, large health systems, of course,
• 13:38
  I think, you know, have invested in this
• 13:40
  strategy.
• 13:41
  But but then,
• 13:43
  coming forward with use cases
• 13:45
  and connecting with the clinicians who,
• 13:48
  again,
• 13:49
  you know, absolutely can tell you what they
• 13:52
  are seeing in terms of the technology.
• 13:54
  Younger physicians,
• 13:56
  older physicians are keeping pace. They they are
• 13:59
  constantly approached
• 14:01
  by our vendors in in the digital world,
• 14:03
  and, they can often point to, you know,
• 14:05
  very specific use cases.
• 14:07
  So I think then back to VSMH and
• 14:10
  our strategy, we recognized that we needed to
• 14:12
  be able to engage in real time
• 14:15
  And building that infrastructure that, you know, again,
• 14:18
  wasn't going to take a a a great
• 14:20
  idea and turn it into an eighteen month
• 14:22
  process
• 14:23
  was was really the challenge that we needed
• 14:25
  to address. And so being able to
• 14:27
  use a great acceleration,
• 14:29
  for example, and, you know, build a infrastructure
• 14:31
  that allows us to
• 14:33
  to, you know, to to finance and fund
• 14:35
  some of these programs in real time, that
• 14:38
  has been key for us. And, it really
• 14:40
  does engage your teams as well. So
• 14:43
  all lessons that we have learned are learning.
• 14:45
  We've got a lot to learn. We certainly
• 14:47
  haven't got it all figured out. I don't
• 14:50
  think anybody has. But,
• 14:52
  but it, again, takes, teams, and we're fortunate
• 14:55
  to to have teams that that really support
• 14:58
  this work.
• 14:59
  Fantastic. Well, Mark, what else are we missing?
• 15:02
  Any final thoughts you wanna offer our listeners
• 15:05
  today?
• 15:06
  You know, I often use this as the
• 15:08
  rallying cry, which is we're at the point
• 15:10
  where
• 15:11
  clinicians have reached the tipping point. Right? Cognitive
• 15:15
  assistance is required. The amount of information and
• 15:18
  data coming at us in health care
• 15:20
  is really beyond the human capacity, I think,
• 15:23
  to keep up. And so
• 15:25
  so,
• 15:26
  we we are thankfully
• 15:27
  living in an era where, you know, we
• 15:29
  we can empower,
• 15:31
  our teams,
• 15:33
  not only with data, but then with the
• 15:34
  tools, in many cases, AI driven tools that
• 15:37
  that allow us to to effectively overcome the
• 15:40
  the cognitive limitations. So this is my rallying
• 15:43
  cry. We've got to work smarter, not harder.
• 15:46
  And, I'll leave you with that, Jacob.
• 15:48
  Wonderful. Well, doctor Townsend, thank you so much
• 15:51
  for taking the time to sit down with
• 15:52
  us and for sharing your insights with our
• 15:54
  audience. We really appreciate it.
• 15:56
  My pleasure. Thanks for having me. Yeah. And
• 15:59
  if you'd like to listen to more podcasts
• 16:01
  from Becker's HealthCare, you can visit beckershospitalreview.com.