Page 104 - Harvard Business Review (November-December, 2017)

FEATURE THE IT TRANSFORMATION HEALTH CARE NEEDS

operational barriers, and fix workflow issues. Then of hospital-acquired infection in different parts of the
the information was used to develop systems for au- hospital, patients’ length of stay, and so on), and they
tomatically collecting process-quality metrics (such could then determine whether and how to change
as the time between a patient’s registering at the their own workflows.
emergency department’s front desk and being put Beyond encouraging the development of the
in a bed and seen by a clinician) and automatically necessary data infrastructure, senior leaders must
reporting that information to government agencies also help establish a vision for how the collected
and regulatory bodies. (See “How RFID Technology data will be used to improve productivity. In many
Improves Hospital Care,” at hbr.org.) cases, pursuing the vision may involve supporting
Similarly, Rush University Medical Center in the creation of entirely new measures of perfor-
Chicago built a new outpatient practice with RTLS mance. Sabermetrics, the mathematical analysis of
sensors for each room, clinician, patient, and piece baseball data, offers an example of how new mea-
of equipment. The system alerts staff when a patient sures—and technologies to collect and analyze the
leaves his or her exam room, eliminating the need information related to them—can revolutionize an
for a practice manager to inform cleaning staff that a industry. Developed by statisticians (the most prom-
room needs to be serviced and preventing awkward inent of whom is Bill James), sabermetrics involves
interruptions of patients who are still dressing after an measuring aspects of the performance of individual
appointment. The time saved per patient is relatively players and calculating their contributions to team
small—perhaps just one minute. But over the course outcomes. Initially, gathering the data was tedious.
of a day, the total savings allow clinicians to see more As sabermetrics pioneers found homes in big-league
patients, thereby improving productivity. clubs, however, data warehouses were developed
Over time, as passive-data-collection technologies to ease collection and analysis. Since 2015, high-
become less costly and as clinicians and patients be- resolution cameras and Doppler radar have been
come more comfortable with them, the benefits will installed in all stadiums to glean previously hard-to-
increase. This will help organizations justify the up- track information, such as speed and acceleration, to
front cost and make it easier to overcome hurdles such quantify a player’s defensive prowess. This in turn
as employee concerns about being monitored. has led to the creation of entirely new metrics such
as “wins above replacement,” which has become the
standard, all- inclusive measure of an individual’s
TURNING DATA INTO ACTIONABLE INFORMATION value to a team.
Persuading clinicians to engage with a new IT sys- Compared to other industries, health care is in a
tem—and making it less burdensome for them to do relatively early stage of applying analytics. But the
so—is only half the battle. Turning the data collected promise is great. For example, a small but growing
into actionable information is also vital and requires number of health care organizations have built sophis-
senior leadership’s support. One of the most critical ticated systems that facilitate a deep understanding
tasks for a leader is to set expectations for how the of costs and quick illustration of how innovations in
system will be structured. We’re talking not about the providing care can improve both outcomes and costs.
technical specifications but about organizational or Intermountain was a pioneer in this realm, but others
cultural guidelines for using the data to support daily are following suit. Recently, University of Utah Health
care-related activities. created a system with a 200 million–row database that
A key step is establishing a core data warehouse for yields information on key operational metrics such as
the organization and getting clinicians to understand cost per minute in the emergency room. According to
its importance. In making the case to the staff of NYU a New York Times article, the organization has used
Langone, Grossman emphasized the value of having this information to change operational workflows, re-
a single source of truth across inpatient facilities, out- ducing costs by 0.5% a year over the past few years,
patient centers, and the medical school. In the process whereas other academic medical centers in its market
of developing the data warehouse, various parties at area averaged annual increases of 2.9%.
NYU Langone that were previously protective of their Another important use of analytics is identify-
turf and information were forced to work together. ing unnecessary variation in treatment. A good ex-
Disputes over which of several data sources were ac- ample is New York–based Crystal Run Healthcare, a
curate ended, and Grossman persuaded department physician-owned multispecialty medical group that
chairs to start using tools such as data dashboards wanted to standardize treatment for 15 diagnoses that
to assess what was (and was not) working across de- were common among its patients. As reported in a
partments. Over time, as the benefits of the result- Health Affairs blog post, the organization first calcu-
ing transparency became apparent, clinical leaders’ lated the total annual cost per patient—segmented
initial skepticism about the IT system subsided. by professional, laboratory, radiology, and proce-
Departments would receive data on quality metrics dure charges—and then examined the cost of care
for peer departments within NYU Langone (the rates across physicians so that each could see how he or

134 HARVARD BUSINESS REVIEW NOVEMBER–DECEMBER 2017