Quality Improvement in Health Care

Abstract

This article addresses the topic of quality improvement in health care. We begin by looking at the issue of trust and uncertainty in medical practice and then look at the development of outcomes research as the first step in identifying effectiveness in medical care, designing methodologies and measures of health outcome data, and developing quality indicators. A brief review of quality improvement management techniques and their application in health care is presented. The article concludes with an overview of future directions in quality improvement; in particular, the development of medical scorecards and assessment ratings.

Overview

In the beginning, there was only trust—the trust a patient had in his or her physician to professionally and competently diagnose and treat illness (Millenson, 2001). The trust was based on the physician's reputation, word-of-mouth recommendations, and the experience of repeated patient encounters. There was little hard data that patients could rely on to compare physician services. Patients did not have access to the same information that physicians had and therefore did not know what available treatment options there might be, if the option the physician chose was the most appropriate or the most cost effective. In economic terms, this state of imbalance between provider knowledge and patient knowledge is called information asymmetry. The effect of information asymmetry in health care is that the balance of power in the health care market was skewed to providers, i.e. hospitals and physicians, as sellers of health services. One economic outcome of this imbalance is rising costs. Buyers had to pay the price demanded by sellers because buyers lacked information on the best treatment options at what price. Sellers of health care services had a monopoly on information. Another feature of the health care market that contributed to imbalance is that providers based their prices on services provided regardless of the outcome of the service. In other words, if you had a cold and went to see your doctor, you paid the doctor for the visit whether your cold was cured or not.

This era of trust began eroding with the passage of Medicare and Medicaid in 1965. Almost immediately health care costs began to rise. The costs of hospital care climbed seven percent between 1963 and 1966 and jumped 13 percent between 1966 and 1969. Hospital net income increased 76 percent between 1965 and 1969. In this same time period physician fees doubled (Millenson, 2001). One explanation for this meteoric rise was that Medicare and Medicaid reimbursed physicians on the basis of fees deemed "usual, customary, and reasonable." Reimbursement was paid for services rendered, not for treatment outcome. Amendments to the Social Security Act of 1972 gave the federal government the right to disallow costs deemed unnecessary to the "efficient" provision of care (Millenson, 2001). This was the first curb put on Medicare spending. Private commercial health insurers followed suit by adopting similar reimbursement policies. The problem with this policy, however, was in determining what was "efficient." At this point in time, there were no measures in place to define what was efficient. Further, there were no measures or data to determine the outcomes of care—let alone efficiency.

As health care costs continued to rise throughout the 1970s, the pressure to show efficacy and appropriateness of treatment in relation to reimbursement increased. With the advent of managed care payment plans, there was now pressure for hospitals and physician practice groups to show that selected treatments were not just necessary but appropriate and cost effective.

The Road to Quality Improvement

Utilization Review. One implication of the widespread use of third-party payors for health care, be it Medicare/Medicaid or employer-paid commercial health insurance is the problem of 'moral hazard.' Moral hazard refers to the behavior of the insured as a result of having access to insurance. In the case of health care, the moral hazard is the overuse of health care services because consumers have little concept of how much their health care costs. Third-party payers, i.e. insurance companies and the government, pay the majority of health care costs.

One solution to the overuse of health care services was the implementation of utilization review. The process of utilization review involves monitoring medical treatments before their execution (pre-authorization) or determination of what procedures will be reimbursed after treatment is delivered. The Health Care Finance Adminsitration (the predecessor to the Centers for Medicare and Medicaid) created a system of Peer Review Organizations that performed regular medical chart audits in hospitals to determine utilization rates and efficacy. Commercial health insurance followed suit; frequently hiring physicians to perform chart reviews for out-patient as well as in-patient treatment. By 1988, a policy of utilization review was adopted by 95 percent of large corporation health plans (Millenson, 2001).

Development of Outcomes Research. Beginning in the early 1980s, research studies examining variation in individual physician practice behavior revealed that variation in practice patterns could be attributed more to geography than individual behavior (AHRQ, 2007). Studies conducted by John Wennberg (1984) found that there were large variations in the frequency of hysterectomies, mastectomies, hemorrhoidectomies, and other common surgical procedures. These findings spawned a new era of research in health care services with an emphasis on treatment outcomes rather than descriptive treatment procedures. Government support for this new direction in research was significant. The Medical Treatment Effectiveness Program (MEDTEP) initiated by the federal Agency for Health Care Policy and Research (now known as the Agency for Healthcare Research and Quality) was launched with an initial appropriation of $6 million in 1989. By 1991, the MEDTEP appropriation grew to $63 million.

Outcomes and effectiveness research focuses on the end results of medical treatment. The end results measured go beyond the descriptive clinical results of treatment. The end results also include patient satisfaction with care provided, impact of insurance coverage and reimbursement policy, and the functional status of the patient following the treatment, i.e. quality of life. As noted in a report by the Foundation for Health Services Research (1994):

An important distinction exists between outcomes research and clinical research trials in identifying treatment effectiveness. Clinical research trials such as those conducted by the National Institutes of Health are conducted in controlled laboratory settings, typically using a homogeneous population and rigorously controlling for all possible variables. Any observed effect in the research subjects, i.e. patients, can then be attributed to treatment effects, given stated statistical confidence. Outcomes research, on the other hand, is conducted using large statistical databases provided by health plans, managed care organizations and Medicare/Medicaid. Medical outcomes are observed in a real-world setting as opposed to a controlled laboratory setting. In addition to database analysis, outcomes research studies may also include patient questionnaires and meta-analysis; an analytical summary of multiple research findings.

According to a report issued by the Foundation for Health Services Research (1994), outcome studies typically report on four areas of analysis.

• The first is identifying variation in care. For example one study found that residents in New Haven are twice as likely as residents in Boston to undergo coronary bypass surgery.
• The second area of analysis compares the effectiveness of various treatments and procedures. Variables examined in this analysis include the training of the provider, the type of provider, e.g. primary care physician, specialist, nurse practitioner, etc., the socioeconomic status of the patient, the treatment setting, communication among the care-giving team, and the financial incentives of both patient and provider, e.g. health insurance coverage and reimbursement policy.
• The third area is development of appropriateness of care criteria. For example, identifying conditions when a particular treatment may not be appropriate even if it has been proven medically effective. Outcomes research has been particularly useful in identifying over-use and under-use of medical resources.
• The fourth area is development of health status and consumer preference measures. One of the most important contributions of the field of outcomes research is the development of measures with empirical reliability and validity, especially those related to patient satisfaction, functional status, and quality of life. Previously, physicians relied on biomedical or physiological indicators to measure the effects of their prescribed treatments. Examples of these measures include blood pressure, laboratory tests, x-rays, etc. However, these measures do not address issues of functional status or feelings of well-being. One type of question, for example, is 'do treatment effects and outcomes interfere with activities of daily living, social interactions, work or family roles and responsibilities?'

Putting Outcomes & Effectiveness Research into Practice. Results from outcomes and effectiveness research have provided a strong foundation for the implementation of quality improvement at multiple levels of health care delivery. For physicians and other health care providers, outcomes research has been instrumental in the development of clinical practice guidelines. For hospitals and other healthcare institutions, the use of outcomes research data has been incorporated into accreditation criteria. The Joint Commission on Accreditation of Healthcare Organizations (JACHO) is using outcome data to redefine its standards of accreditation, placing a greater emphasis on performance data rather than structural and operational data. Third-party payors, traditional insurance companies, managed care plans, and government payers are using outcomes data to guide their reimbursement policies (Foundation for Health Services Research, 1994).

From Outcomes & Effectiveness to Quality Improvement. At the system level, outcomes and effectiveness research is providing the foundation for implementing quality improvement systems for hospitals, health plans, and other healthcare organizations and institutions. In 2001, the Committee on Health Care Quality in America and the Institute of Medicine (IOM) issued a landmark report Crossing the Quality Chasm: A New Health System for the 21st Century. This report was a follow-up to an earlier publication To Err Is Human, which documented medical errors, in particular those that contributed to patient deaths, in the U.S. health care system. Together, these reports have galvanized health care organizations to improve their quality of health care delivery. In "Crossing the Quality Chasm," the IOM Committee proposed an agenda to improve quality by addressing six key dimensions of health care systems:

• Safety: Avoiding injuries to patients from the care that is intended to help them.
• Effectiveness: Providing services based on scientific knowledge and avoiding under use and overuse of medical resources.
• Patient-centered: Providing care that is respectful of and responsive to individual patient preferences, needs, and values and ensuring that patient values guide all clinical decisions.
• Timely: Reducing waits and sometimes harmful delays for both those receive and those who give care.
• Efficient: Avoiding waster, including waste of equipment, supplies, ideas, and energy.
• Equitable: Providing care that does not vary in quality because of personal characteristics such as gender, ethnicity, geographic location, and socioeconomic status.

Proposing change and implementing change to positively effect health systems and patient outcomes is a considerable challenge. The health care industry lags considerably behind other industries in the application of technology to improve efficiencies and operations and support quality improvement processes.

Approaches to Quality Improvement. An important outcome of the outcomes research programs of the AHRQ is the development of methodologies and data measurements that can be used in subsequent quality improvement initiatives. In this section, a brief overview of quality improvement methods is reviewed with examples of their applications in health care.

Continuous Quality Improvement (CQI). The principal behind CQI is that opportunity to improve quality exists at each phase and level of operation of an organization. In healthcare, CQI applies to the system of health delivery rather than the individual patient (Varkey, 2007). Total Quality Management (TQM) is one form of CQI. TQM is applied throughout the organization to ensure that the organization consistently meets or exceeds customer requirements and expectations. The focus of TQM is on process measurement and controls as a means of continuous improvement (Free Management Library, 2007).

Six Sigma. Introduced by the Motorola Corporation in the mid-1980s, six sigma employs a rigorous statistical approach to analyze cost, process variation, and eliminate defects. Sigma is a statistical term that refers to the number of standard deviations a given cost or process varies from perfection. Application of six sigma involves progression through a series of five steps: define, measure, analyze, improve, and control.

PDSA Cycle. PDSA is the shorthand for Plan, Do, Study, Act. It is a frequently used technique in health care for making rapid impacts on small operational changes and cyclical improvements (Varkey, 2007). In the plan phase, the operational objective or process to be changed is identified and a plan for change is developed. In phase 2—Do—the new process or procedure is implemented, data is collected on the effect of the change and preliminary data analysis is performed. In phase 3—Study—the results of the change are summarized and discussed. In phase 4—Act—the lessons learned from making the change are determined and further decisions are made as to whether further tests and changes are required.

Lean Methodology. Lean methodology is a quality initiative that focuses on elimination of non-value-added activities, i.e. waste. Developed at Toyota Motor Corporation, lean methodology is driven by customer requirements and needs. Examples of waste are supplies, energy, waiting time (for people or processes), money, and personnel.

Applications to Health Care. Varkey (2007) presents a number of examples of how each of these methodologies has been applied in different health care settings. Using six sigma methodology, the infection rate for colon and vascular surgery at the Charleston Area Medical Center, W.Va. decreased by 91 percent and realized a cost savings of just over one million dollars. Application of lean methodology at the Park Nicollet Medical Center in Minneapolis, MN resulted in the elimination of waiting rooms in a new ambulatory clinic, i.e. waiting time is wasted time. The procedure of scheduling patients and their providers ensures that no waiting time is needed. Varkey and colleagues applied the PDSA cycle to the process of medication reconciliation in an ambulatory clinic and decreased the number of physician-patient medication discrepancies by more than fifty percent.

Development of Quality Indicators. The common element in all of these quality improvement methodologies is the use of data. Data is critical to identifying the problem, measuring the impact of the problem, and measuring the impact of the change on the problem. Data collection may be small and focused such as used in a PDSA cycle or could involve large data sets such as used in outcomes and effectiveness studies. The push for quality improvement is driving the development of large databases that detail quality indicators within a healthcare organization from the individual patient-provider encounter to system wide performance and operation. Two examples of the development of quality indicators and resultant databases are HEDIS and QIOs.

HEDIS. The Healthcare Effectiveness Data and Information Set (HEDIS) is a data set constructed by the National Committee for Quality Assurance (NCQA). NCQA is a private not-for-profit organization created for the purpose of creating measurements that ensure comparability of health care plans and quality indicators in health improvement. HEDIS is one of the most widely used statistical data sets measuring clinical quality in healthcare. Originally designed for accreditation of managed care organizations and point-of-service plans, preferred provider organizations will now be required to be accredited by NCQA also. Each year, NCQA issues its State of Health Quality report to "monitor and report on performance trends over time, track variation in patterns of care and provide recommendations for future quality improvement" (NCQA, 2007). In addition to HEDIS, NCQA also produces the CAHPS(r) Survey. CAHPS(r), the Consumer Assessment of Healthcare Providers and Systems, is a group of surveys designed to obtain consumer comments and feedback from their health system experiences (NCQA, 2007).

QIOs. QIOs are Medicare Quality Improvement Organizations that work under contract to the Centers for Medicare and Medicaid to assist healthcare institutions with implementation of quality improvement practices, educate beneficiaries about quality of care ratings and assessments, and provide utilization review services. The American Health Quality Association provides a national network of quality improvement experts to support the work of QIOs, disseminate information on quality indicators and best practices, and coordinate the work of QIOs with the Centers for Medicare and Medicaid.

Conclusion

Like many subjective terms, "quality" is in the eye of the beholder. How quality gets defined depends on who the stakeholder is. In healthcare, there are multiple stakeholders each pressing for their own quality agenda. Providers, patients, payors, and employers each have a unique perspective on quality. No longer is it enough for providers to deliver health services and collect their fees. Payors, both government and employers with large corporate health plans, want to see a measurable outcome in health for the money they spend. Patients want to know what treatment options they have and what the outcomes will be in terms of not only their health status, but also their quality of life. Even providers are changing the way they practice, moving from clinical decision-making based on clinical judgment to evidence-based medicine.

One result of the demand for information is the development of rating systems and scorecards for physicians, hospitals, health care plans and other health care organizations. The internet, with its ability to disseminate information at an exponential rate, is a driving force behind the development of scorecards and rating systems. Consumers and other users of health care rating websites must exercise judgment in evaluating the quality of the information provided. The development of provider ratings and scorecards is still in a nascent stage. Critics of the scorecard approach to rating quality speak to problems of faulty methodology, erroneous assumptions, and bad data (Scalise, 2001). One way to evaluate these websites is to find out who developed the rating system and who endorses it. For example, the website healthgrades.com is endorsed by the Leapfrog Group, an organization of the nations' largest corporate employers.

Caveats aside, the availability of information on health care quality and outcomes is shifting the balance of information power in the healthcare market place. This shift will not only result in consumer driven health care but also with profound impacts on the economics of health care delivery.

Terms & Concepts

Continuous quality improvement: Management strategies that employ methods of measuring and analyzing organization performance and production to improve the quality of products and services.

HEDIS: Health Effectiveness Data and Information Set.

Information asymmetry: When the availability of information is skewed in the direction of either the buyer or seller in an economic market.

Outcomes research: Originally a program of the federal Agency for Healthcare Research and Quality to analyze payor and patient databases for the purpose of identifying the end results and effectiveness of medical interventions.

QIOs: Quality Improvement Organizations.

Utilization review: A forerunner of quality improvement practices in healthcare institutions that involves routine medical chart audits to identify over-use, under-use or misuse of medical resources.

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Suggested Reading

Feder, H. M. (2015). Quality improvement teams win special funding to address local health care delivery problems. Journal of Health Care Compliance, 17(6), 31-34. Retrieved March 21, 2018, from EBSCO online database Business Source Ultimate. http://search.ebscohost.com/login.aspx?direct=true&db=bsu&AN=110744251&site=ehost-live&scope=site

Keppel, K., Bilheimer, L., & Gurley, L. (2007). Improving population health and reducing health care disparities. Health Affairs, 26, 1281–1292. Retrieved October 16, 2007, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=26658227&site=bsi-live

Nadeem, E., Olin, S., Hill, L., Hoagwood, K., & Horwitz, S. (2013). Understanding the components of quality improvement collaboratives: A systematic literature review. Milbank Quarterly, 91, 354–394. Retrieved November 21, 2013, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=88156387

Robb, E., Mackie, S., & Elcock, K. (2007). Monitoring quality. Nursing Management – UK, 14, 22–26. Retrieved October 16, 2007, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=26503929&site=bsi-live

Selberg, J. D. (2007). The quest for quality. H&HN: Hospitals & Health Networks, 81, 70. Retrieved October 16, 2007, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=26324956&site=bsi-live