Optimizing patient and financial outcomes by reducing unwarranted clinical variation

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ABSTRACTAs the healthcare industry continues to shift toward value-based care models, and with the increased focus on

population health management, the delivery of high-quality, cost-effective care is a greater priority for providers

than ever before. Unwarranted care variation (which includes over- and underutilization of care and services)

that results from a lack of evidence-based care standards can lead to increased healthcare costs and less-than-

optimal patient outcomes. This represents a major impediment to achieving superior care with great outcomes

for patients.

The objectives of this white paper are as follows:

1. Address the benefits of evidence-based clinical interventions.

2. Identify reasons for care variation and how variations in the implementation of evidence- based care

interventions impact clinical and financial outcomes.

3. Provide recommendations for taking corrective action to reduce unintended clinical variation and

prevent gaps in care.

4. Explore the important role that actionable, real-time (or near-real-time) data and technology reporting

and management solutions play in reducing care variation.

5. Discuss the use of technology to effectively measure clinical quality and outcomes.

6. Consider the value in empowering clinicians with education and other resources that guide the most

impactful clinical actions to ensure that appropriate standardized care is provided.

Value-based care models reward healthcare providers for providing high-quality care and doing so in as cost-

effective manner as possible. This motivates health systems to provide care with more positive patient outcomes

and the ability to provide more efficient management of a patient population’s health. Evidence-based care

protocols can help organizations achieve those goals across multiple settings.

The vast majority of hospitals (96 percent) have implemented computerized provider order entry (CPOE) systems that include

clinical decision support tools based on evidenced-based protocols,

according to a 2016 American Society of Health-System Pharmacists

(ASHP) survey and summarized by Pedersen et al (2016).

Organizations increasingly recognize that tools such as CPOE and other

decision support platforms support the delivery of standardized care.

When that care is based on the latest evidence, it drives higher-quality

patient outcomes and increases overall patient safety. Data-driven

technology that analyzes physician practice variations can provide

insight into both costs and outcomes.

Graham et al (2018) noted that “decision support tools can provide

patient-specific assessments that support clinical decisions, improve

prescribing practices, reduce medication errors, improve the delivery

of primary as well as secondary prevention, and improve adherence to

standards of care.”

“Decision support tools can provide patient-specific assessments that support clinical decisions, improve prescribing practices, reduce medication errors, improve the delivery of primary as well as secondary prevention, and improve adherence to standards of care.”

TARGETING UNWARRANTED VARIATIONEliminating practice variation is key to improving clinical systems, according to Cook et al (2018). In a 2011

executive summary, the American Hospital Association (AHA) reached a similar conclusion. The AHA found

that variations in care exist at all levels within the healthcare system, across all settings, and among all patient

populations.

Variation can lead to the underuse of effective care, the

overuse of nonbeneficial services, and an emphasis on

physician opinions versus patient preferences. Cook et al

(2018) noted that “unwarranted variation has been linked

to suboptimal outcomes and to increased cost for the same

outcome (ie, inefficient care).” The authors also noted that

standardized, evidence-based care has a multitude of

benefits, including reductions in unnecessary readmissions,

lower rates of hospital-acquired infections, greater patient

safety, and improved patient outcomes and satisfaction.

In a report for The Advisory Board, Evans and Clark (2019)

stated that unnecessary variations in care cost millions to

hospitals every year and that health system chief financial

officers view clinical standardization as the biggest

opportunity to boost productivity and/or cut costs.

Sutcliffe, K. M. (2015). Managing the unexpected(K. E. Weick, Ed.). San Francisco, CA: Jossey-Bass.

doi:10.1002/9781119175834

Table 1 | Characteristics of High Reliability

Characteristic and Description

Preoccupation With Failure: The first high-reliability organization principle, it captures the need for continuous attention to irregularities that may be symptomatic of larger system problems.

Reluctance to Simplify: The principle that mindful organizing is produced by a reluctance to simplify because simplifying obscures unexplainable, unwanted, and unanticipated details which, in doing so, increases the potential for unreliable performance.

Sensitivity to Operations: This principle is associated with paying close attention to current happenings. Definitions of the situation matter; sensitivity to these definitions also matter.

Deference to Expertise: Characterized by a pattern of respectful yielding, domain-specific knowledge, compressed and generalizable experience, and negative expertise.

Commitment to Resilience: The fifth principle, focused on limiting errors, devising workarounds that keep the system functioning, and absorbing change while persevering.

“High-reliability organizations work to create an environment in which potential

problems are anticipated, detected early, and virtually always responded

to early enough to prevent catastrophic consequences. This mindset is supported

by five characteristic ways of thinking: preoccupation with failure; reluctance

to simplify explanations for operations, successes, and failures; sensitivity

to operations (situation awareness); deference to frontline expertise; and

commitment to resilience.”

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TAKING PROACTIVE MEASURES Evidence-based medicine is one of the characteristics of high-

reliability organizations, according to the Agency for Healthcare

Research and Quality (AHRQ) Patient Safety Network. The

AHRQ states: “High-reliability organizations work to create an

environment in which potential problems are anticipated, detected

early, and virtually always responded to early enough to prevent

catastrophic consequences. This mindset is supported by five

characteristic ways of thinking: preoccupation with failure;

reluctance to simplify explanations for operations, successes, and

failures; sensitivity to operations (situation awareness); deference

to frontline expertise; and commitment to resilience.”

All of these characteristics can help reduce both clinical and

operational variations (see Table 1 - Characteristics of High

Reliability).

Over the last several years, industry groups and executive-level

healthcare leaders have increasingly focused on the value of

evidence-based care. In a 2017 Advisory Board executive research

briefing, Umanski (2017) notes that C-suite leaders identified

“minimizing unwarranted clinical variation” and “controlling

unavoidable utilization” as among their top priorities.

“It is critical for health systems to focus on the right application

of this data infrastructure in order to surface true sources of care

variation and determine how changes in practice and operations

will impact clinical and financial outcomes,” according to the brief.

The Institute of Medicine’s 2013 Roundtable on Value & Science-

Driven Health Care, which convened to help transform the way

evidence on clinical effectiveness is generated and used to

improve health and healthcare, has also prioritized reducing

care variation. The Roundtable set a goal that by the year 2020,

90 percent of clinical decisions will be supported by accurate,

timely, and up-to-date clinical information, and will reflect the best

available evidence.

Physicians and other clinical care workers are also on board.

A survey of 250 physicians, nurse practitioners, and physician

assistants reported in the Cook et al (2018) study found that most

clinicians agree that practice variation should be reduced and that

reducing clinical practice variation would benefit most patients.

• Identify trends around theutilization of evidence-basedinterventions across the entirepatient/provider encounter.

• Detect over- or underutilization ofevidence-based interventions.

• Ensure focus on interventionsthat have an impact on keyquality measures and outcomes,such as inpatient mortality,readmissions, and length-of-stay.

• Identify which providers are (andare not) utilizing interventionswith an evidence-based link tooutcomes and order sets.

• Track order set variability anddetermine how many differentorder sets providers are using.

• Track how utilization of vitalinterventions and order setschange after the implementationof educational campaigns andquality improvement initiatives.

• Monitor the charge capture of thecare provided.

• Determine whether or not ordersare placed, fulfilled, and chargedcorrectly.

• Improve patient charge accuracy.

• Promote accurate accounting ofchargeable items.

• Evaluate charge capture withindiagnoses groups to provideinsight into revenue leakage.

To optimize clinical and financial outcomes based on evidence-based practices, hospitals and health systems need solutions that:

CUTTING COSTS AND BOOSTING SATISFACTIONIdentifying unintended variation provides financial benefits to healthcare

organizations–and their patients–that go beyond government incentives and

risk-sharing contracts. By identifying variations from evidence-based protocols,

hospitals have the opportunity to improve billing accuracy and ensure correct

reimbursement.

The Evans and Clark (2019) report published by The Advisory Board confirmed

the correlation between care variation, care quality, and costs. The report

analyzed more than 20 million patient discharges from over 450 hospitals and

quantified the potential cost savings from reductions in care variation reduction. “Hospitals in the top quartile

for performance had less variation and lower costs than the national cohort for 726 out of 983 APR-DRGs,”

according to the report. “This means higher quality is associated with both lower costs and lower variation in

care.”

The Advisory Board report calculated that among the hospitals with more than 100 beds, the organizations

could realize combined savings in excess of $16 million by reducing unintentional variation for their top 30

conditions, which include septicemia and disseminated infections, percutaneous cardiovascular procedures

without acute myocardial infarction, and heart failure. The figure escalates to more than $29 million when

variation is reduced across all conditions.

*Top-quartile performance is based on four quality measures: mortality, length of stay, readmissions, and complications. Cost

savings opportunity assumes full closure of unfavorable cost gaps between median costs of top-quartile performers and

studied hospitals. Actual opportunity must be downward adjusted to compensate for underlying demographic, clinical, and

operational disparities between organizations. All estimates are rounded to the nearest hundred-thousand. Adapted from

Evans and Clark (2019).

“The challenge,” Evans and Clark (2019) added, “is that, in order to unlock substantial savings, care variation

reduction has to be executed at scale. While you don’t need to focus on the top 30 conditions simultaneously,

you’ll want to build the capacity to tackle the majority of them within the near future.”

Table 2 | Average cost savings opportunity from matching top quartile performance*

Size of Hospital (Number of Patient Beds) - All Hospitals

All Conditions (in millions, rounded)

Top 30 Conditions (in millions, rounded)

Percentage of Total Opportunity Driven by

Top 30 Conditions

>100 $29.3 $16.1 54.9

100-200 $9.7 $6.3 65

201-400 $23.1 $13.4 58

>400 $79.4 $40.2 50.6

“In order to unlock substantial savings,

care variation reduction has to be executed at scale.”

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Many healthcare organizations are well-poised to report high-level quality

measures set by the Centers for Medicare & Medicaid Services. But

even when providers implement evidence-based practices, healthcare

organizations often lack visibility into how widely–or how narrowly–they are

adopted by their clinicians.

With the right tools, healthcare organizations can identify whether clinicians

are following guidelines and making the appropriate clinical decisions to

improve outcomes. With this detailed information, leaders can also evaluate

whether the appropriate clinical decisions result in the intended patient

outcomes. This helps inform clinicians on the effectiveness of the care they

provide and subsequently enact necessary changes to improve patient

care.

Clinicians also have increased opportunity to practice evidence-based care when they have better insight into

clinical quality and outcomes measurements and understand the impact of using the latest evidence-based

interventions. In the survey by Cook et al (2018), 94 percent of respondents agreed with the statement: “I

depend on practice guidelines to help me provide optimal care for my patients,” while 70 percent said “better

access to guidelines and synthesized evidence” would help standardize clinical practice.

The act of disseminating data can improve quality. According to an article published in the International Journal

for Quality in Health Care, Westert et al (2018) state that making data public “can be a useful start to a wide-

ranging conversation between clinicians, managers, and patient representative groups exploring why variation

exists in the local system and attempting to understand its causes and potential remedies.”

The ideal solution encompasses four unique aspects:

With the right tools, healthcare organizations can identify whether clinicians are following guidelines and making the appropriate clinical decisions to improve outcomes.

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Data can aid organizations in assessing variation of care by the setting it’s provided in, the department, or the

individual clinician. This provides transparency into what is happening in context–the real consequences and

results in real or near-real time–and creates pathways to intervene when improvement efforts are lacking.

Match the patient-specific orders

to the clinicians and to the vital interventions.

MATCH

Measure clinician adherence to

evidence-based practices over

time.

Send individualized messages that

educate clinicians and influence their

decisions with evidence-based

guidance.

Track impact to delivery of patient care to maximize

outcomes; maximize clinician engagement and

feedback.

MEASURE

MESSAGE MAXIMIZE

CONCLUSIONA strong analytics platform with reporting and

messaging capabilities can help organizations

reduce unwarranted variations in care and drive

improvements in quality of care, assessment of

financial impact, and more. The ideal solution will

help providers:

• Match: Match the patient-specific orders to the

clinicians and to the vital interventions.

• Measure: Measure clinician adherence to evidence-

based practices over time.

• Message: Send individualized messages that

educate clinicians and influence their decisions

with evidence-based guidance.

• Maximize: Track impact to delivery of patient

care to maximize outcomes; maximize clinician

engagement and feedback.

Once a hospital quantifies adherence to evidence-

based protocols, the organization can tailor its

messaging to support any necessary changes

in clinician behavior and workflows. Continuous

monitoring of operations helps leaders to gauge the

ongoing success of improvement campaigns. Gaining

insight into how physicians are using evidence-

based care guidelines can help organizations track

the impact of those efforts. By putting the protocols

and data into clinicians’ hands, physicians are better-

equipped to improve their day-to-day practices.

As AHRQ noted in its 2019 patient safety primer,

high-performing organizations are forward-thinking

and proactive. They address gaps and variations

in care immediately and in a comprehensive way.

By leveraging systems that measure the over- or

underutilization of evidence-based interventions,

hospitals can assess their impact, act as necessary,

and ultimately drive superior quality and financial

outcomes.

A strong analytics platform with reporting and messaging capabilities can help organizations reduce unwarranted variations in care and drive improvements in quality of care, assessment of financial impact, and more. The ideal solution will help providers:

Zynx Health, part of the Hearst Health network, provides healthcare professionals with vital information and processes that guide care decisions and reduce complexity across the entire patient journey in a way that leads to healthier lives for all.

Zynx is a pioneer and market leader in evidence- and experience-based clinical solutions that help health systems improve patient outcomes, financial outcomes, clinical engagement and technology performance. With Zynx Health, healthcare organizations exceed industry demands for delivering high-quality care at lower costs under value-based reimbursement models. To learn more, visit zynxhealth.com or call888.333.ZYNX (9969).

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REFERENCESAgency for Healthcare Research and Quality Patient Safety Network, Patient Safety Primer: High Reliability, January 2019. Retrieved from https://psnet.ahrq.gov/primers/primer/31/High-Reliability

Cook, D. A., Pencille, L. J., Dupras, D. M., Linderbaum, J. A., Pankratz, V. S., Wilkinson, J. M., Practice variation and practice guidelines: Attitudes of generalist and specialist physicians, nurse practitioners, and physician assistants, PLoS ONE, 31 January 2018. Retrieved from https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191943

Corallo, A. N., Croxford, R., Goodman, D. C., Bryan, E. L., Srivastava, D. Stukel, T. A.,A systematic review of medical practice variation in OECD countries, Health Policy,Volume 114, Issue 1, 2014, pp. 5-14. Retrieved from https://doi.org/10.1016/j.healthpol.2013.08.002

Evans, S., Clark, M., The 80/20 of Care Variation Reduction: In-depth profiles of organizations successfully reducing unwarranted care variation at scale, The Advisory Board, 9 January 2019. Retrieved from https://www.advisory.com/research/physician-executive-council/research-report/2019/the-80-20-of-care-variation-reduction

Graham, M. M., James, M. T., Spertus J. A., Decision Support Tools: Realizing the Potential to Improve Quality of Care; Canadian Journal of Cardiology, Volume 34, Issue 7, 3 March 2018, pp. 821–826. Retrieved from https://www.onlinecjc.ca/article/S0828-282X(18)30212-5/fulltext

Pedersen, C. A., Schneider, P. J., Scheckelhoff, D. J., ASHP national survey of pharmacy practice in hospital settings: Prescribing and transcribing—2016, American Journal of Health-System Pharmacy, Volume 74, Issue 17, 1 September 2017, pp. 1336–1352. Retrieved from https://doi.org/10.2146/ajhp170228

Report of the Task Force on Variation in Health Care Spending, American Hospital Association, 10 January 2011. Retrieved from https://www.scha.org/files/documents/Variation%20Report.pdf

Roundtable on Value & Science-Driven Health Care: Roundtable Charter, Institute of Medicine of the National Academies, December 2013. Retrieved from http://www.nationalacademies.org/hmd/~/media/Files/Activity%20Files/Quality/VSRT/Core%20Documents/CharterandVision.pdf

Sutcliffe, K. M. (2015). Managing the unexpected(K. E. Weick, Ed.). San Francisco, CA: Jossey-Bass. doi:10.1002/9781119175834

Umanski, B., The Clinical Leader’s Resource Guide: Executive Research Briefing, The Advisory Board, 14 June 2017. Retrieved from https://www.advisory.com/research/health-care-advisory-board/resources/2017/the-clinical-leader-resource-guide

Weick, K. E., & Sutcliffe, K. M. (Eds.). (2015). Managing the unexpected. San Francisco, CA: Jossey-Bass.

Westert, G. P., Groenewoud, S., Wennberg, J. E., Gerard, C., DaSilva, P., Atsma, F., Goodman, D. C., Medical practice variation: public reporting a first necessary step to spark change, International Journal for Quality in Health Care, Volume 30, Issue 9, 1 November 2018, pp. 731–735. Retrieved from https://doi.org/10.1093/intqhc/mzy092