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Health care reform and leadership: switching from volume to value.

THE LANDSCAPE OF HEALTH CARE IS CHANGING rapidly, making it more difficult for health care leaders to navigate their way through unfamiliar terrain. Several variables are contributing to these changes, making the course uncertain, uneven and unpredictable.

Health care reform has shifted the paradigm from volume to value. Crucial to the sustainability of health care organizations in this era of reform will be their success in various Centers for Medicare & Medicaid Services (CMS) at-risk programs such as the Value-Based Purchasing (VBP) program.

Much of the "value" in such a program is driven by physician practices. One is following recommended processes of care (core measures) and the documentation to support them. The shift from physician autonomy to physician accountability will require physician engagement and leadership, not just at the bedside but in the boardroom.

Although there has been a slight increase of physicians being promoted to the C-suite, their leadership in quality initiatives remains marginal. Few would disagree with the importance of physician engagement in improving the quality of care for patients in the hospital setting. However, engaging physicians in quality improvement (QI) has become a common challenge for hospitals. (1)

The challenges associated with early adoption of QI programs in the past have been in defining and measuring the value of health care. A definition of value is quality (patient outcomes, safety and service) divided by cost over time, which works well for some clearly defined conditions but is more challenging for complex patients with multiple problems. (2)

Although quality patient care is the goal of physician practice, how care is defined as quality by CMS does not always align with physicians. This makes it difficult for health care leaders to gain physician buy-in and ownership for quality benchmarked outcomes. This issue is likened to the physician-as-artist metaphor; just as the artist has a unique style and interpretation when sculpting or painting, the physician has unique care delivery methods for his or her patients. (3)

Complicating matters is the fact that there are few physician role models, meaning that until physicians can see how a real program works operationally and can see an improvement in overall quality, resistance to clinical governance will continue. (4)

The concept of being measured by a form of clinical governance outside the medical discipline as with the VBP is difficult for many physicians to embrace. When measurements are used to evaluate performance, there will be those that fall below, meet or exceed the benchmarks.

In terms of thinking about clinical quality outcomes in relation to the bell curve, there are always going to be hospitals that perform below and above the middle, with the majority often performing in the middle. According to the nationally recognized general surgeon Atul Gawande, acknowledgement of the bell curve is distressing for most doctors in that it "... contradicts the belief nearly all of us have that we are doing our job as well as it can be done," and such information used to compare records of success and failures is difficult for physicians to share with peers. (5)

LEADERSHIP REFORM REQUIRED--Sooner rather than later, physicians must be at the quality table. According to Carolyn Clancy, "The pace of these developments represents an unprecedented opportunity for physician leadership" when it comes to understanding the specifics about measures, data collection and submission. (5)

Physicians are often the most effective messengers for delivering performance data to frontline staff and when they provide feedback to other physicians, "... it provides validation that the data came from colleagues with shared interests in promoting, as well as shared barriers to providing, optimal clinical care." (7)

As a means of developing an alignment approach with physicians, Thomas indicated that hospitals should take an inventory of their current physician relationships, listen to their key physician leaders, discuss and define their intentions, and communicate their initiatives. (8)

Vital to hospital executives across the country is the ability to identify physicians within their organizations who are quality improvement champions who in turn can increase the effectiveness of their group through modeling and/or disseminating behavior change to improve the overall quality of care outcomes. In 2013, the use of social network analysis (SNA) was discovered as a viable method and tool for hospital leaders to identify such physicians. (9)

SOCIAL NETWORK ANALYSIS--To identify a physician leader, one must first identify and understand a physician's social network. A social network refers to the set of actors and the ties among them. (10)

A social network is "a specific set of linkages among a defined set of persons, with the additional property that the characteristics of these linkages as a whole may be used to interpret the social behavior of the persons involved." (11) Social network analysis focuses on relationships among social entities and on the patterns and implications of these relationships.

A 2013 study applied SNA methods to observe physicians (actors) in a 265-bed acute care hospital to identify physician level of prominence (importance) within their network. Prominence was quantified mathematically by measuring centrality (level of involvement of an actor with other actors in the network.) (9)

Two levels of centrality studied that showed promise in understanding the network included degree (the higher the centrality degree, the more visible and active a physician is in the network), and closeness (defined as the distance of the reach to other physicians in the network measuring the speed at which quality information might be disseminated).

The study surveyed employed physicians identified in terms of their influence in quality that was representative of cardiology, family practice, internal medicine, hospitalists, physicians holding leadership roles, and physicians active in chairing or co-chairing quality committees. A 60 percent response rate was obtained in answering the following three questions:

1. How often do you communicate?

2. How often do you have discussions specific to quality issues within the organization?

3. How often do you seek input from this person before making key decisions?

The physician responses provided the data necessary to construct sociomatrices that were used for analysis and in developing sociograms (a two-dimensional diagram for displaying the relations among actors within the network as depicted in Figure 1).

In addition to the research questions, physician specialty, years of service, familiarity with CMS Core Measures and the Value-Based Purchasing Program also were addressed. Figure 1 displays the physician network studied representing a fairly equally connected network with identifiable central clustering and three individuals located on the periphery connected by only one or two other physicians.

FINDINGS--Degree centrality, simply put is "where the action is in the network." (10) There are two components to the measure: in-degree, which identifies the physician level of information sharing, and out-degree, that measures physician influence.

Physicians A and C had the highest out-degree centrality and should be considered most influential in the network. Actors who have high out-degrees are actors who are able to exchange with many others or to make many others aware of their views and are often said to be influential actors. (12) In-degree examination showed physicians Y, C and A (in order of highest to next-highest value) having the highest in-degree centrality, which indicated that information sharing is most prominent among these three physicians.

Closeness centrality measures the distance of an actor to all other actors and can be broken down into receiving (in-closeness) and disseminating (out-closeness) information.

Physicians C and A had the highest degree of in-closeness while physicians A and J had the highest degree of out-closeness. This would imply that physician C is most likely to receive information in the network while physician A is likely to disseminate and receive.

Physician A stood out as the most prominent in the network with the greatest capability of influencing and disseminating information. Physician C followed physician A's prominence in having values in the top three for in-degree, out-degree and in-closeness implying that he/she was not only prominent in the network but was influential and was most likely to receive information.

The most prominent physicians within the network are listed in Table 1 providing identification of their specialty, years of service, and familiarity with CMS's core measures and the VBP program. Although statistical inferences could not be made in identifying relationships among the aforementioned variables, prominence and familiarity could prove to be extremely valuable information for the health care leader to improve the effectiveness of the network in modeling and or disseminating behavior change.

For example, even though physician A had the highest degree of prominence in the network, he/she was only familiar with the core measures and the VBP program, while physician C, in addition to being prominent, was very familiar with the programs and should be recognized as a likely champion for assisting the administrative team in educating other physicians in the network on these programs.

Physician attribution by prominence was applied to the same physician sociogram seen in Figure 1. It provides yet another two-dimensional visualization of the seven most prominent physicians in the network represented by size and shading of the nodes (see Figure 2).

The study demonstrates that the principles and methods of SNA can be used to identify the most influential physicians in a network by defining centrality in relation to quality information sharing and dissemination in the hospital setting.

The practical implications of such a study provide mathematical and visual relational information about the physician network that can assist health care leaders in identifying physician quality improvement champions as a means of increasing the effectiveness of their group in modeling and/or disseminating behavior change within the hospital setting. This in turn can position an organization for success in such programs as VBP and those yet to surface as a result of reform.

REFERENCES

(1.) Gosfield AG and Reinersten JL. Finding common cause in quality: Confronting the physician engagement challenge. The Physician Executive, 34(2), March/April 2008, 26-31.

(2.) Asplin BR. Value-based purchasing and hospital admissions: doing the right thing isn't easy. Annals of Emergency Medicine, 2010, 56(3), 258-260.

(3.) Goodroe JH. Using comparative data to improve health care value. Health care Financial Management, June 2010, 63-66.

(4.) Shekell PG. Why don't physicians enthusiastically support quality improvement programs? Quality & Safety in Health Care, 2002, 11, 6.

(5.) Gawande A. Better: A surgeon's notes on performance. New York, NY: Picador, 2007.

(6.) Clancy CM. Physician leadership for high-quality care. Chest, 2009, 136(6), 1396.

(7.) Randolph G, Esporas M, Provost L, Massie S, and Bundy DG. Model for improvement-part two: Measurement and feedback for quality improvement efforts. Pediatric Clinics of North America, 2009, 56, 779-798.

(8.) Thomas JR. Hospital-physician alignment: No decision is a decision. Health care Financial Management, December 2009, 76-80.

(9.) Wagner KM, Johnson J, Stephens J, and Tackett W. Exploring the use of social network analysis in identifying physician engagement in quality improvement in the hospital setting. 2013 (Doctoral dissertation). Retrieved from http://condor.cmich.edu/utils/getfile/collection/ p1610-01coll1/id/3698/filename/3699.pdf

(10.) Wasserman S, and Faust K. Social network analysis. Methods and applications. New York, NY: Cambridge University Press, 1994. 11 12

(11.) Tichy, NM, Tushman ML, and Fombrun C. (1979). Social network analysis for organizations. The Academy of Management Review, 4(4), 507-519.

(12.) Hanneman RA and Riddle M. Concepts and measures for basic network analysis. In Scott, J. & Carrington, P.J. (Eds.), The SAGE handbook of social network analysis. Los Angeles, CA: SAGE Publications, 2011.

Kay Wagner, DHA, MSN, RN

Kay Wagner, DHA, MSN, RN, is director of quality at MidMichigan Health in Midland, MI.

Kay.Wagner@midmichigan.org

TABLE 1

PHYSICIAN PROMINENCE IDENTIFIERS

Physician   Specialty      Years of   Core Measures   VBP Program
                           Service

A           Leader          26-30     Familiar        Familiar
C           Hospitalist/    11-15     Very familiar   Very familiar
              leader
B           Cardiology      16-20     Familiar        Not at all
                                                        familiar
Y           Leader          21-25     Familiar        Familiar
E           Cardiology      21-25     Familiar        Not at all
                                                        familiar
J           Family          26-30     Familiar        Not at all
              Practice                                  familiar
T           Family          26-30     Familiar        Not at all
              Practice                                  familiar
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Title Annotation:Quality
Author:Wagner, Kay
Publication:Physician Leadership Journal
Date:Sep 1, 2014
Words:1983
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