The International Journal of Medical Banking

Abstract

THE PURPOSE OF Performance Normalization is to analyze various approaches available to the public and the investment community in order to gauge hospital and other healthcare entity performance across the board. The approach takes a view towards normalizing available data along with the publicized findings of major grading organizations and recommended guidelines that could lead to the creation of a single index, basket group of indices or a common approach. This indicator would represent a synopsis of traditional quality measures, performance, satisfaction and outcome metrics, and financial ratio’s across the “for profit” and “not for profit” spectrum.

The focus of this paper is to introduce the concept of Performance Normalization. We propose a tool for unifying and analyzing the disparate factors people and organizations take into account when making decisions about health care. The audience is the general public, the investment community, hospitals and healthcare entities themselves, payers, raters and government entities. This paper provides an overview of some of the concepts and challenges—including the vast array of groups already measuring various indicators — and the possible benefits of Performance Normalization.

Background

Many parties have a desire to learn how healthcare entities compare to each other for various reasons. Current trends are redefining the concept of a hospital in the public mind. Integrated Delivery Networks and extended hospitals servicing their clients through technology and telecommunications are gaining in community awareness. In our context, we focus on traditional hospitals. However, even within this limited subset, discovery and comparison become complicated due to diverse information sources, none of which are unified in one place.

The Problem

There is a need to see a simple indicator that addresses the many traditional measurements of a hospital or other healthcare entity. There is public confusion. As the trend towards Consumerism advances the demand for transparency will grow. The issues are across the board. The process is clouded even further by the categorization of hospitals based on tax basis — for example, non-profit and for-profit, which includes those owned by both public and private entities and public hospitals supported by taxes, donations and insurance reimbursements. These analyses may show negative margins.

Which indicators should be used? Will it be possible to find entities that share all indicators chosen and have standard information available for evaluation purposes? How will information about the financial health of for-profit hospitals be garnered when corporate parents change ownership forms (as in the case for example of HCA, the largest private operator of health care facilities in the world)? How do we tell how the hospital itself is doing when the financial data is merged with the holdings of the company and goes across many regions? How do we break it out? Where do we look?

Quality

If Quality is a major factor that can influence a unifying index and helps drive understanding and decision making then it would seem one could look to common measurements of this factor as one path. However, the search for common quality indicators is not easy to find. In hospitals there may be upwards of 200 quality measures depending on the condition, co-morbidity, or even on the scenario by which a patient enters the hospital walls. Add to this the multitude of companies that offer guidelines on the 10 best or top 100 hospitals, or “The Best” from the view point of employers, insurance companies, various media groups and companies, groups focused on specific specialty mixes, bond raters, Joint Commission, and even standard government data from CMS and AHRQ (Agency for Health Research and Quality). The task for the consumer is daunting.

Other groups weighing in include AHIP (America’s Health Insurance Plans) for payers, CARF (Commission on Accreditation of Rehabilitation Facilities) for behavioral health, NQMC (National Quality Measures Clearinghouse) for providers and practices, NCQA (National Committee for Quality Assurance) for managed care organizations, CAQH (Council for Affordable Quality Healthcare) involved with credentialing, various organizations that measure satisfaction both of the patient and the provider and those that posit safety as a key determinant of good care, Healthgrades, Consumer Reports, Solucient and the Leapfrog Group and even a version of Zagat’s that addresses patient experiences based on their own reviews. And this is the short list. How can a hospital be good on one list and less good on another and why? It seems the customer has a right to know in terms they can understand and trust as they evaluate a product or service within the context of their own health and well being.

In “Crossing the Quality Chasm: A New Health System for the 21st Century,” a 2001 report by the Institute of Medicine, six aims are addressed for improvement in healthcare from a quality perspective:

• Safety – Avoid injuries to patients;
• Effectiveness – use outcomes and evidence to avoid the over or underuse of care;
• Patient-Centeredness – Respect for the patient socially, culturally, and by specific needs with a patient active role in the determination of their own care;
• Timeliness – Reduce waiting time for patient and caregiver;
• Efficiency – Reduce waste;
• Equity – Close racial and ethnic gaps regarding the availability of care.

Performance Normalization attempts to help define value. Becky Cherney, Chair and CEO of the Florida Health Care Coalition, speaks of value as influenced by price and quality. Her view is that Quality + Price = Value and this forms the basis of her “Quality First Initiative,” that has become well recognized in Florida. Some government or government-sanctioned organizations are beginning to see the need for this type of public information. In Florida, The Agency for Health Care Administration (AHCA), Florida Center for Health Information and Policy Analysis was awarded a contract from the Agency for Healthcare Research and Quality (AHRQ) for a pilot project to study new ways to approach hospital quality measures. The contract adds clinical laboratory data to hospital administrative data that AHCA already collects. The end goal of the project is to develop predictors of hospital quality indicators.

To answer the question of value we need to understand quality – a more illusive term than it at first seems. There is a subjective side to quality that must be addressed. It is dynamic and changing and difficult to measure unless continuously addressed. Is quality based only on objective measurements? Interesting corollaries support different viewpoints. For example, the German economy was recently studied to understand the state of the country. In analyzing many measurements such as unemployment, inflation, productivity and others, the results were right on target with where the government and generally accepted global measurements of success were supposed to be. Yet a poll of the German people revealed that over 50% said the economy was not good. Which is the right answer, the indicators or the views of those served? Which do we accept?

Some may remember studies of people rating doctors highly because of good bedside manners. Many valued feeling good around the doctor and the treatment they received by the support staff over performance indicators that, in some cases, showed a negative history based on outcomes for that doctor. In many cases, the patients knew and had the choice to switch but preferred to stay with the doctors where they felt treated better even in life threatening situations.

The subjective nature of quality is a key factor in determining an approach and must be factored in. A common indicator that addresses quality could address these issues in a dynamically-weighted process that takes into account the current health care environment and the needs and wants of the public in regard to the public good.

Justification for Performance Normalization

Groups working in the realm of Process Improvement are sensitive to the dynamics of measuring quality and performance. It is, many times, more about the process and the never ending tasks of observing, monitoring, and adjusting within a framework that embraces an almost paradoxical structured approach. Some outside observers might conclude that the approach implies static conditions and a laboratory-like setting but it doesn’t. The reality is that PI embraces a dynamic approach (a good example if CQI). A key strength of PI is that it tends to balance opposing forces to find workable solutions.

Approach

How can we make this process easier, consistent, and offer a methodology that results in an indicator that is perceived by the public as sanctioned by a trusted party or intermediary? Who should that intermediary be? Can we find a formula that everyone can understand?

To address these questions we may look to examples in niche areas. An example from the private sector is MorningStar, an organization that provides subscribers and the general public with information on funds and stocks in many companies. They use various ways to reach their conclusions and their targeted public audience views them as a standard source of information. They are accepted by the specific audience they serve. Another example exists in the media section of the financial industry. In the online business section of the New York Times, one can choose an interactive graph and in seconds, see major companies offering similar outputs and can tell at a glance who is bad, improving, good or declining over different timeframes. One can tell how big an entity is in terms of capitalization and what they do best, worst or what they offer. Using easy to follow graphics like a color bubble, one can deduce within each company itself, how each department ranks against others, how it ranks against departments of companies doing the same thing in the outside world of similar organizations, the cost and margin, and which department or specialty has the best people, the best equipment, which are good and which are not so good.

A similar tool would be useful in the healthcare field. Should our healthcare system be viewed and measured like a retail commodity outlet selling a product? We think not. There is a special relationship in our field regarding the people we serve. There is a limit to how far the private model works when it comes to life events concerning illness and well being. Do we need a “MorningStar of Healthcare”? Again, probably not. But perhaps one can walk away with some pointers of what works in the non-healthcare environment and consider them in light of community goods and services that return more than dollar profit yet in some limited ways are influenced by similar factors. We can learn from these and choose or choose not to apply them. It’s not all in the numbers we call money, it is in what the money represents, the concept of wealth, the link between health and wealth and how it can help us achieve our goals from a societal view. It is our way of measurement.

The Investment Community

In our economy, many companies or entities are measured by financial indicators. Many of the indicators are geared toward profit realization. The capital markets are awash in indicators. Investors sometimes decide whether or not to put their money into a company by following its performance on an index. With publicly traded companies, this index serves as a road map of how the company has performed in the past and will perform in the future, based on large and diverse sources of information. With non-profit companies that are not obligated to report their profits and losses the field becomes murkier and different road maps exist.

Many believe bond ratings are determinants of good financial performance as well. This assumes that the ratings companies and the investing public are the best determinants of financial value in the market. It also assumes that our choice of financial quality indicators are the best determinants of social value. This is not true.

The data from financial organizations such as Moody’s Standard & Poors, Fitch, Ambest, and bond insurers Ambac and MBIA are also determinants. Banks are as well. Hospitals occasionally need to borrow money, and banks monitor them to determine risk and the potential for default. A bank’s credit view of a hospital could serve as an indicator. A company or city seeking to build a hospital may also issue bonds to fund construction or in some cases major capital projects. A knowledge of publicly traded bonds can be revealing. Bond price and yield movement in the secondary market (where capital – assets used to create other assets- is traded as opposed to the primary market where it is issued) can be influenced by speculation as well instead of on fundamental knowledge, or true value, and therefore may have no real connection to quality. Using market data alone would not be wise. In the capital markets — where long term funding is raised (versus the Money Markets which are short term focused) — investing boils down to trust and the objectives of the investor.

The Risk/Return Model is a concept that is good for understanding Healthcare dynamics and we may help learn new ways of observing our industry by understanding these concepts. In the financial industry risk is key. There are some that view risk as the chance of something going wrong. This is the common view. There are also schools that view risk as the chance of an unexpected event happening regardless of being labeled positive or negative. There is no judgment in this second approach. Directly related to risk is the expected return. In financial terms this is a measure in dollars and percentages. There are elaborate approaches to determining the risk/return ratio of a target investment or a portfolio (group) of investments which are populated based on understandings of the various risks of each underlying holding (co-efficient correlations) in the portfolio. Can an approach to the risk models in the financial world apply to healthcare? Can we merge our overlapping and unique characteristics and take advantage of the predictive nature of this approach? Can we possibly apply these disciplines to help us understand the good versus bad model in light of who is asking the question and the unique characteristics of the events in existence when that question is asked? Maybe the answer is not always the same. Maybe it is dependent on the needs of those asking at the time. There are possible approaches to address this. One is called Data Envelope Analysis, or DEA.

One Approach – DEA, an Example

If we can agree that some common set of representative indicators are possible to identify we may be able to get a picture. Once the indicators are determined, a method to evaluate and weigh the different indicators, or variables, must be determined. One such method that has been suggested is called Data Envelopment Analysis, which is used to measure efficiency between organizations with similar goals and objectives. There are other methods available beyond the scope of this paper.

Data Envelopment Analysis (DEA) is a relatively new data oriented approach for evaluating the performance of a set of peer entities. Decision Making Units, (DMUs) convert multiple inputs into multiple outputs. The definition of a DMU is generic and flexible. Recent years have seen a great variety of applications of DEA for use in evaluating the performances of many different kinds of entities engaged in many different activities in many different contexts in many different countries. These DEA applications have used DMUs of various forms to evaluate the performance of entities, such as hospitals, US Air Force wings, universities, cities, courts, business firms, and others, including the performance of countries, regions, etc. Because it requires very few assumptions, DEA has also opened up possibilities for use in cases which have been resistant to other approaches because of the complex (often unknown) nature of the relations between the multiple inputs and multiple outputs involved in DMUs.

Data Envelopment Analysis (DEA) is also a tool to address the efficiency of a number of producers. DEA can be applied to measure relative efficiency among organizations with the same goals and objectives.¹ DEA is a tool that can be used to measure the efficiency of transforming multiple inputs into multiple outputs, for example:

Inputs: Nonphysician FTEs; supplies costs; available bed-days

Outputs: Inpatient mortality rates; length of stay; patient satisfaction

As applied in this context, this approach might be applied here because of healthcare’s unique characteristics, i.e.:

• Health care is complex and expensive.
• Differences exist in case mix, patient demographics, insurers, academic affiliations, employed staff, and service heterogeneity.
• Benchmarking is often used for comparison purposes.
• Controlling for the variability among benchmarked institutions is very difficult.
• Readily available single factor comparisons (e.g. length of stay) are of limited use in comparing operational efficiencies.

Application of the DEA methodology can enable direct comparisons of production efficiency for organizations to identify the processes/flows that could be targeted for performance improvements. Determination of relative efficiency for each participant can then be weighed in a study against a hypothetical composite using linear programming. An exercise testing DEA in the context of Performance Normalization would be useful.

Other

It is also possible that another audience exists. Those who seek to donate their money philanthropically are also stakeholders and knowing the stability of a company reassures them that their charitable donation would be used properly. From a public perspective, this is also a dimension that consumers and investors wish to see.

For example, recently the 990 Coalition for Hospitals was established by four national organizations with experience in community benefit and hospital tax exemption. They are the American Health Lawyers Association, the Catholic Health Association, the Healthcare Financial Management Association and VHA, Inc. This coalition helps hospitals deal with the demands of the new version of IRS form 990 which is used for non profits and is of interest to many other parties. This new form and new Schedule H for hospitals will be used for not-for-profits to report on a variety of information from providers to assess the benefits they offer to the community as weighed against their tax-exempt status. The majority of hospitals are still not-for-profit. How can the public tell if their exemption is being used well? Is it living up to the activities of it’s peers and is it comparable against for-profits from the standpoint of providing a public good when no profit motive exists?

And then, especially given the current economic environment, how can we gauge hospitals that take differing break downs of the population in regard to the proportion of insured, under-insured, and uninsured and compare them financially on an equal footing? How can we tell who is providing the care to our community in the best way? What do we mean by “the best way?”

Summary

Performance Normalization allows anyone to view a single number or indicator that represents a synopsis of all major quality and financial information of any healthcare entity in support of any decision. It is obvious that the options are confusing and overwhelming. Which way is better than the other? Can we somehow find a way to use the best of all approaches? The need for the public to have an understanding of what is going on in health care goes beyond portfolio performance and checkbook balances.

Health care consumers are demanding increasing levels of convenience, service, quality, efficiency, and knowledge. Because the subjective nature of quality varies from person to person, and as patients increasingly view healthcare from a perspective of being responsible and educated for themselves and their own healthcare, Performance Normalization may become an area of interest.

Creating a uniform index ranking hospitals in all three financial categories—non-profit, profit and public would help unify diverse factors currently considered too widespread to analyze together. In addition, a way to view quality and performance indicators across the spectrum would be useful to the consumer when presented in easily understood and consistent terms. It could simplify the process of those in the investor community seeking knowledge upon how to gauge the environment so that they can make their investments regarding real return, as well as provide peace of mind to the public at large as they make decisions about their health care. Increased investment, in every sense of the word, leads to innovation, reduced cost, and better outputs as determined by citizens, the consumers of care.

By offering a consistent means of evaluating and comparing healthcare entities, people can then make informed decisions to choose the right hospital care or discover the true price and quality for services at competing organizations.

Note

¹Taken in part from Anderson Sweeny Willis, Quantitative Methods for Business, p. 384

Selected References

A. Charnes, W. Cooper, & E. Rhodes, “Measuring the efficiency of decision-making units”, 1978 (seminal work)

Staat et al, “Benchmarking the Health Sector in Germany – An Application of Data Envelope Analysis, October 2000

Huang and McLaughlin, “Relative Efficiency in Rural Primary Care: An Application of Data Envelopment Analysis”, June 1989

Salinas-Jimenez and Smith, “Data Envelopment Analysis Applied to Quality in Primary Health Care”, December 1996

Siddharthan, Ahern, Rosenman, “Data Envelopment Analysis to determine efficiencies of health maintenance organizations”, January 2000