1
00:00:00,640 --> 00:00:03,199
Philips is a health tech leader focused on

2
00:00:03,199 --> 00:00:06,000
innovation that improves the health and well-being of

3
00:00:06,000 --> 00:00:09,460
people. Our health care technology and informatics solutions

4
00:00:09,599 --> 00:00:12,559
help care teams diagnose, treat, and manage more

5
00:00:12,559 --> 00:00:16,244
patients with greater precision, speed, and confidence across

6
00:00:16,244 --> 00:00:19,225
the care journey. With Philips, clinicians are empowered

7
00:00:19,285 --> 00:00:21,765
with streamlined insights in the moments that matter

8
00:00:21,765 --> 00:00:24,904
for every patient. Better care for more people.

9
00:00:25,204 --> 00:00:25,704
Philips.

10
00:00:29,070 --> 00:00:31,309
This is Gracelyn Keller with the Becker's Healthcare

11
00:00:31,309 --> 00:00:33,229
Podcast, and we are recording live at the

12
00:00:33,229 --> 00:00:36,289
9th Annual Health IT Digital Health and RCM

13
00:00:36,509 --> 00:00:37,009
Conference.

14
00:00:37,549 --> 00:00:39,869
I am joined by doctor Jim Blum this

15
00:00:39,869 --> 00:00:42,344
morning who is the chief health information officer

16
00:00:42,425 --> 00:00:45,304
at University of Iowa Hospitals and Clinics. So,

17
00:00:45,304 --> 00:00:47,304
doctor Blum, thanks so much for joining me.

18
00:00:47,304 --> 00:00:48,984
Would love to have you start off by

19
00:00:48,984 --> 00:00:51,145
introducing yourself a little bit further. Well, thank

20
00:00:51,145 --> 00:00:52,825
you. Thank you for having me this morning.

21
00:00:52,825 --> 00:00:54,125
It's a pleasure to be here.

22
00:00:54,880 --> 00:00:56,880
So I'm the chief health information officer at

23
00:00:56,880 --> 00:00:57,940
the University of Iowa

24
00:00:58,479 --> 00:00:58,979
and,

25
00:00:59,600 --> 00:01:02,560
predominantly, I'm charged with making sure that we

26
00:01:02,560 --> 00:01:05,040
acquire the best technologies possible for the care

27
00:01:05,040 --> 00:01:07,219
delivery in our in our system.

28
00:01:07,865 --> 00:01:09,865
And that may be everything for making us

29
00:01:09,865 --> 00:01:11,725
more efficient to improving our quality,

30
00:01:12,185 --> 00:01:14,585
to help making our providers' lives better. So

31
00:01:14,585 --> 00:01:16,204
it really spans the gamut

32
00:01:16,745 --> 00:01:17,145
of,

33
00:01:17,625 --> 00:01:18,745
the typical chief,

34
00:01:19,145 --> 00:01:21,005
chief health information officer role.

35
00:01:21,400 --> 00:01:23,239
Wonderful. Well, Iowa is my alma mater, so

36
00:01:23,239 --> 00:01:25,399
go Hawks. Glad to have you on this

37
00:01:25,399 --> 00:01:26,840
morning. We'll see we'll see how the football

38
00:01:26,840 --> 00:01:28,759
season goes. I don't know. I don't know.

39
00:01:28,759 --> 00:01:29,793
I don't know. I don't know. I don't

40
00:01:29,793 --> 00:01:31,560
know my I don't I'm not not holding

41
00:01:31,560 --> 00:01:32,780
my breath this year, unfortunately.

42
00:01:33,079 --> 00:01:34,599
No. Me either, but we can hope for

43
00:01:34,599 --> 00:01:35,500
the best. Yes.

44
00:01:36,005 --> 00:01:38,645
Alright. Well, let's start our conversation with AI

45
00:01:38,645 --> 00:01:40,885
adoption. It's exploding right now in health care.

46
00:01:40,885 --> 00:01:42,725
So I'd love to hear what the most

47
00:01:42,725 --> 00:01:44,424
significant or promising application

48
00:01:44,885 --> 00:01:46,725
of this technology is right now in your

49
00:01:46,725 --> 00:01:49,319
view. And how is this informing your organization's

50
00:01:49,380 --> 00:01:50,359
innovation strategy?

51
00:01:50,740 --> 00:01:53,620
Yeah. So we've really invested very heavily in

52
00:01:53,620 --> 00:01:56,180
AI in the last 12 months. Last year,

53
00:01:56,180 --> 00:01:57,540
I think I had the privilege of joining

54
00:01:57,540 --> 00:01:58,980
you folks and said this was gonna be

55
00:01:58,980 --> 00:02:00,734
the year, and it it is the year.

56
00:02:00,814 --> 00:02:03,295
There is no doubt. So in this year,

57
00:02:03,295 --> 00:02:04,194
we've unleashed,

58
00:02:04,575 --> 00:02:07,395
a torrent of AI technologies across our enterprise.

59
00:02:07,935 --> 00:02:11,074
Everything from predictive analytics that we've both purchased

60
00:02:11,215 --> 00:02:13,314
and acquired to look at patient deterioration,

61
00:02:14,280 --> 00:02:16,439
identify patients that we could potentially intervene on

62
00:02:16,439 --> 00:02:17,739
and improve their care,

63
00:02:18,039 --> 00:02:20,759
all the way through addressing provider burnout with

64
00:02:20,759 --> 00:02:23,639
ambient technologies and chart binding technologies to help

65
00:02:23,639 --> 00:02:25,659
make it much easier to assess the patient.

66
00:02:26,314 --> 00:02:28,555
I think the early investment where we're really

67
00:02:28,555 --> 00:02:29,294
gonna see

68
00:02:30,555 --> 00:02:32,715
the most significant impact in health care right

69
00:02:32,715 --> 00:02:35,354
now is on that later end. We've got

70
00:02:35,354 --> 00:02:37,775
really good data coming out of Iowa demonstrating

71
00:02:38,250 --> 00:02:41,449
just how much these technologies reduce provider burnout

72
00:02:41,449 --> 00:02:43,229
in a very short period of time.

73
00:02:43,849 --> 00:02:45,530
And I think that's a very welcome change

74
00:02:45,530 --> 00:02:47,770
in health care after the past 4 very

75
00:02:47,770 --> 00:02:48,909
turbulent years.

76
00:02:50,169 --> 00:02:52,814
Absolutely. And switching tracks just a little bit

77
00:02:53,055 --> 00:02:53,794
toward data.

78
00:02:54,415 --> 00:02:57,215
Currently, healthcare leaders are managing greater volumes of

79
00:02:57,215 --> 00:02:59,375
data and more devices across a growing number

80
00:02:59,375 --> 00:03:00,354
of care settings.

81
00:03:00,814 --> 00:03:02,655
So this is a complex environment, and I'd

82
00:03:02,655 --> 00:03:04,830
love to hear what clinical integration tools or

83
00:03:04,909 --> 00:03:07,870
practices you're seeing drive improvements in patient outcomes.

84
00:03:07,870 --> 00:03:09,790
And I'd love to hear specific examples of

85
00:03:09,790 --> 00:03:12,590
that. Yeah. So we have really taken a

86
00:03:12,590 --> 00:03:16,430
focus on centering our patient data around our

87
00:03:16,430 --> 00:03:16,930
EHR.

88
00:03:17,775 --> 00:03:20,014
So our approach right now is to really

89
00:03:20,014 --> 00:03:22,335
bring we're at Epic shop, is to bring

90
00:03:22,335 --> 00:03:24,974
everything we can into that Epic environment and

91
00:03:24,974 --> 00:03:27,615
use it wherever we can to analyze and

92
00:03:27,615 --> 00:03:28,754
present that data.

93
00:03:29,615 --> 00:03:31,855
We are making a shift in sort of

94
00:03:31,855 --> 00:03:33,074
our advanced analytics.

95
00:03:34,039 --> 00:03:35,180
We are moving,

96
00:03:35,639 --> 00:03:38,299
we we were a Tableau shop for advanced

97
00:03:38,519 --> 00:03:39,019
visualizations.

98
00:03:39,319 --> 00:03:41,400
We're moving more to Power BI, which I

99
00:03:41,400 --> 00:03:44,039
think is a welcome change for better integration

100
00:03:44,039 --> 00:03:45,900
with the Microsoft suite of tools.

101
00:03:46,425 --> 00:03:48,364
We also have found a way to leverage

102
00:03:48,664 --> 00:03:49,724
our internal

103
00:03:50,584 --> 00:03:53,625
super high performance computing capabilities at the University

104
00:03:53,625 --> 00:03:55,465
of Iowa to really do a lot of

105
00:03:55,465 --> 00:03:56,284
model development.

106
00:03:56,905 --> 00:03:57,645
That is,

107
00:03:58,264 --> 00:04:00,824
I think gonna play very nicely with the

108
00:04:00,824 --> 00:04:02,599
soon to be released Togito

109
00:04:03,379 --> 00:04:05,139
cloud from EPIC that will enable us to

110
00:04:05,139 --> 00:04:06,439
really integrate that data,

111
00:04:06,740 --> 00:04:09,379
use SQL for more real time type works

112
00:04:09,379 --> 00:04:10,840
as opposed to the traditional

113
00:04:11,460 --> 00:04:13,460
modalities that are required for EPIC to do

114
00:04:13,460 --> 00:04:14,520
real time analytics.

115
00:04:15,544 --> 00:04:18,345
And as we discuss adoption of AI and

116
00:04:18,345 --> 00:04:20,204
growing data and new technologies,

117
00:04:20,665 --> 00:04:24,024
our IT teams become critical. So how can

118
00:04:24,024 --> 00:04:26,665
health care organizations better support both their IT

119
00:04:26,665 --> 00:04:29,165
and clinical teams as they carry out innovation

120
00:04:29,225 --> 00:04:31,779
efforts? And what are the common pitfalls that

121
00:04:31,779 --> 00:04:33,720
you've seen? Yeah. I I think

122
00:04:34,100 --> 00:04:36,339
I think it's the key thing you said

123
00:04:36,339 --> 00:04:38,419
there is integration. Right? The

124
00:04:39,699 --> 00:04:41,860
my observation is that in health care, we've

125
00:04:41,860 --> 00:04:43,814
done a even though there are people like

126
00:04:43,814 --> 00:04:45,814
me sitting there trying to straddle the fence

127
00:04:45,814 --> 00:04:46,314
of,

128
00:04:46,854 --> 00:04:47,754
of being

129
00:04:48,214 --> 00:04:50,634
a tech person and being a clinician,

130
00:04:51,175 --> 00:04:52,394
there's a lot of

131
00:04:52,774 --> 00:04:53,274
misunderstanding

132
00:04:53,814 --> 00:04:55,974
as to from the clinician side as to

133
00:04:55,974 --> 00:04:57,274
what's actually possible

134
00:04:57,839 --> 00:05:00,000
and a lot of misunderstanding on the IT

135
00:05:00,000 --> 00:05:02,259
side as to what's actually useful.

136
00:05:02,800 --> 00:05:05,199
And so really when you get those teams

137
00:05:05,199 --> 00:05:06,720
together, and I think when you put the

138
00:05:06,720 --> 00:05:09,360
user and the pay whoever that user is,

139
00:05:09,360 --> 00:05:11,084
whether it's the clinician,

140
00:05:11,464 --> 00:05:13,884
it's the patient, it's one of the ancillary

141
00:05:13,944 --> 00:05:15,884
services that's that's,

142
00:05:16,345 --> 00:05:18,845
being that's interfacing with the IT system.

143
00:05:19,305 --> 00:05:21,865
When you get those people that are the

144
00:05:21,865 --> 00:05:23,224
users at this

145
00:05:23,625 --> 00:05:24,365
at the

146
00:05:24,769 --> 00:05:26,230
at the point of innovation,

147
00:05:26,610 --> 00:05:29,269
and you really design the systems around them,

148
00:05:30,209 --> 00:05:32,370
that's where you wind up with the maximal

149
00:05:32,370 --> 00:05:32,870
impact.

150
00:05:33,410 --> 00:05:34,769
The thing is you need to have those

151
00:05:34,769 --> 00:05:37,649
users cognizant of what is possible. Otherwise, you

152
00:05:37,649 --> 00:05:39,914
spend a bunch of time talking about how

153
00:05:39,914 --> 00:05:41,754
unicorns are gonna come and fairies are gonna

154
00:05:41,754 --> 00:05:43,834
make life wonderful and those types of things.

155
00:05:43,834 --> 00:05:45,995
And and someday, I'll have gold delivered from

156
00:05:45,995 --> 00:05:48,474
Fort Knox to my house. But until that

157
00:05:48,474 --> 00:05:48,974
day,

158
00:05:49,435 --> 00:05:51,995
we gotta understand what's actually possible before you

159
00:05:51,995 --> 00:05:53,854
can go ahead and design the solution.

160
00:05:54,750 --> 00:05:57,089
Absolutely. And as we wrap up the conversation

161
00:05:57,310 --> 00:05:59,310
today, I'd love to hear your top piece

162
00:05:59,310 --> 00:06:01,870
of advice for healthcare leaders as they prepare

163
00:06:01,870 --> 00:06:03,089
for these further advancements

164
00:06:03,629 --> 00:06:06,370
in technology and the greater demands for care.

165
00:06:06,589 --> 00:06:08,834
I think I think where health care leaders

166
00:06:08,834 --> 00:06:10,595
can really make a difference is making sure

167
00:06:10,595 --> 00:06:12,774
they have an educated clinician workforce

168
00:06:13,235 --> 00:06:16,535
that is able to sit and do that

169
00:06:17,154 --> 00:06:19,334
design with the IT teams.

170
00:06:20,129 --> 00:06:23,170
Also, I think we've had a historical approach

171
00:06:23,170 --> 00:06:24,949
to the way that we implement technologies

172
00:06:25,970 --> 00:06:28,770
that a lot of organizations wanna pilot things

173
00:06:28,770 --> 00:06:30,310
for long periods of time.

174
00:06:30,689 --> 00:06:31,650
And I think there's

175
00:06:31,995 --> 00:06:34,875
that's a very justifiable thing to do. But

176
00:06:34,875 --> 00:06:36,735
once you make the decision to invest,

177
00:06:38,394 --> 00:06:40,415
spending months rolling out a technology

178
00:06:41,514 --> 00:06:44,154
just is too long. Right? Months to years.

179
00:06:44,154 --> 00:06:47,269
And so finding ways to shorten that time

180
00:06:47,269 --> 00:06:48,089
to integration

181
00:06:48,629 --> 00:06:50,870
is really key. That's how you maximize that

182
00:06:50,870 --> 00:06:53,289
investment in your investment dollars.

183
00:06:54,069 --> 00:06:56,310
Spending, you know, 1,000,000 of dollars a year

184
00:06:56,310 --> 00:06:59,269
on contracts where you're only partially implemented doesn't

185
00:06:59,269 --> 00:07:00,490
do anyone a favor.

186
00:07:01,555 --> 00:07:03,475
Absolutely. Well, doctor Blum, thanks so much for

187
00:07:03,475 --> 00:07:05,634
joining me this morning on the Becker's healthcare

188
00:07:05,634 --> 00:07:06,134
podcast.

189
00:07:06,595 --> 00:07:08,435
Again, we're live at the 9th annual health

190
00:07:08,435 --> 00:07:11,475
IT digital health and RCM conference. Thanks so

191
00:07:11,475 --> 00:07:12,774
much. Thank you.