Public awareness of quality issues and rapidly increasing costs have placed increased focus on measuring the quality and cost of health care, using measures that are meaningful, simple, and actionable (i.e., they can be used to drive improvement over time). Toward these ends, private payers, federal and state agencies, consumer groups, and even health care providers themselves have proposed, tested, and implemented a variety of measures to evaluate the quality and cost of health care. Understanding and performing well against these standards is critical for an ACO to achieve savings, meet quality improvement targets, and differentiate itself. Such measurement will also enable ACO managers to identify the referral physicians, hospitals, or other providers that provide high-quality and cost-efficient care and the groups that offer opportunity for improvement.
For most organizations, the primary objective in assessing performance is to identify quality care at a reasonable cost and delivered with good service. Cost of care describes the relative resources used in delivering health care or managing a patient’s clinical condition. Quality is the assessment of clinical outcomes or the processes used in delivering patient care and their correspondence to evidence-based medicine and other treatment guidelines. Service can relate to patient satisfaction and access to care. Efficiency is the cost of care or resources required to deliver a given level of quality and service. This section focuses on the methods used to assess the quality and cost of care delivered by providers and organizations. Examples of how the results can be used to identify opportunities for improvement are provided. Methods to assess the quality of care are described first, followed by a discussion of cost measurement.
Measuring Quality of Care
There is a well-documented gap between current medical knowledge and actual health care practice – a number of studies have shown a correlation between compliance with care guidelines and proven treatments, and the outcome and/or cost of care.6,7,8,9,10 Across geographical regions, significant variation exists in the use of medical services without any evidence of improved outcomes, while health care costs continue to grow at a high rate nationwide.11 The increasing push to pay for quality translates into purchasers, consumers, and patients requiring increased transparency regarding the quality delivered by physicians and hospitals. Measuring and comparing the quality of care within an organization allows ACOs to:
•
Identify both high-performing providers and areas where improved compliance with prescribed care is recommended;•
Identify diagnostic tests or treatments that are unnecessary or potentially harmful, with the ability to determine the pervasiveness of these tests in their populations;•
Identify care management opportunities, including “gaps” in care for patients and populations;•
Identify patients with indications of poor disease control, such as poor adherence to prescribed medication regimens; and•
Reduce potentially harmful drug-to-drug or drug-to-disease interactions.A broad range of quality measures are currently available in the public domain, covering a range of measurement areas such as prevention, disease management, medication adherence, and patient safety. These measures support assessments of care for both chronic and acute patients and for a range of conditions covering the breadth of clinical medicine. As further investment is made
and as electronic clinical data become more widely available, quality measurement is likely to grow in a significant way. Below highlights some of the key issues and challenges involved with quality measurement.
Challenges and Progress in Measuring Quality of Care
Efforts to measure health care quality in the United States have historically faced considerable challenges. These challenges include limited agreement on the standards used to measure care, the need to identify valid and available data sources to support measurement, and the lack of tools that incorporate robust and adaptable sets of measurement criteria to assess compliance. More recently, progress has been made to address these challenges. Technology is better, metrics are improving, and national programs dedicated to the development of quality measures have grown.12 Quality standards and metrics are derived from published, peer-reviewed literature, as well as guidelines from medical specialty organizations and national quality organizations. Many physician specialty organizations are participating in
initiatives to develop quality measures. Endorsing organizations such as the National Quality Forum (NQF) are playing a significant role in setting the standards for measurement.
The information available to support measurement also has improved. Administrative or transaction data – including medical and pharmacy claims, and selected clinical data such as laboratory results – have increased in both availability and comprehensiveness, thus providing a rich and convenient information source from which organizations can evaluate health care. Significant investment is being made to standardize medical records and other electronic clinical data, thereby increasing access to this information – a key source for valid measurement. Equally important, tools and
technology exist that encode standards of care and provide an efficient and robust way to assess care compliance against these standards.
Process Measures and Outcome Measures
Most measures of health care quality can be categorized as either process measures or outcome measures. Process measures compare the care received by a patient with that indicated by research-based standards, with the idea that increased compliance with these standards will lead to better patient outcomes. For example, for patients with diabetes, process measures include13:
•
HbA1c Testing – an HbA1c test performed forthe patient during a 12-month measurement period (measurement year);
•
Eye Exam – an eye screening for diabetic retinaldisease by an eye care professional within the measurement year; and
•
LDL-C Screening – an LDL-C test performedduring the measurement year.
Outcome measures describe the clinical status of a patient or a clinical result, again reflecting published guidelines and standards of care. Increased patient functionality and quality of life can also be used as a measure of outcome. Examples of outcome measures for diabetes describing clinical status include:
•
Good HbA1c Control – the most recent resultfor an HbA1c test for the patient during the measurement year is < 7.0 percent;
•
LDL-C Control – the most recent resultfor an LDL-C test for the patient during the measurement year is < 100 mg/dL (threshold 1); and
•
BP Control – the most recent blood pressurereading for the patient during the measurement year is < 130/80 mm Hg.
Implementing Measures of Quality and Applying Results
Quality measures are typically implemented using either commercial software that encodes the measure specifications or internally-
developed computer programs that capture these specifications. The data used to support quality measures include member enrollment data, administrative medical and pharmacy claims, encounter data, lab results, and information from medical records. The data is collected and integrated by the user and processed using the packaged software or program code. Outputs include the compliance results of each measure for each individual and information summarizing the details behind the measurement.
ACO managers can use the quality measurement results to support analysis at the organization, provider, or patient level. At the ACO level, reports can highlight the organization’s best opportunities for quality improvement by identifying the areas with the lowest guideline compliance. At the patient level, quality results can be used by providers and case managers to identify care opportunities and insights for patient education.
At the provider and provider group level, quality measurement can involve a number of steps. As a first step, patients and quality measures are attributed to those providers most responsible for patients’ care. Attribution is a key step in valid quality measurement and can be performed in different ways – the approach often depends on the providers being measured. For example, for primary care physicians, a wide range of measures can be attributed to the physician who is responsible for managing the patient’s care. For specialists, attribution may focus only on patients and measures where the specialist contributes significantly to the relevant care (e.g., an endocrinologist observed to provide the majority of diabetes care to a patient over some period of time.) For surgeons, the physician performing the procedure can be deemed responsible. Finally, the same quality measure
is often attributed to more than one provider,
recognizing the importance of care coordination and the fact that for many patients, multiple physicians contribute to their care.
Once attribution has been done, the provider’s results can be summarized at various levels, such as across measures for a particular condition or across all measures and patients. Results are often compared with internal and external benchmarks, such as a target level of compliance or the average results of the provider’s peers.
Examples of Quality Measurement Results
Table 4 provides an example of a report for an individual physician, summarizing the level of compliance with the treatment protocols prescribed for diabetes. A similar report could be created by the physician group or for all patients covered by the ACO. Eight measures are included in the example. The table lists a description for each of the measures and a clinical synopsis of the measure guideline.14 It shows the level of compliance for each of the measures for the patients attributed to “Dr. Smith.” As a comparison, the levels of compliance for the same measures for the other internists in the ACO are shown, along with the ratio of Dr. Smith’s performance relative to his peers. The last row of the table provides a composite result for Dr. Smith across all patients and measures.15 The value in this row for “% Peer Compliance” reflects the composite result for Dr. Smith’s peers if they had the same mix of opportunities across the eight measures as was observed for Dr. Smith.16
The results indicate that Dr. Smith’s level of compliance for these measures is somewhat less than his peers within the ACO, with the greatest discrepancies observed for HbA1c testing and screening for nephropathy and retinopathy. The ratio of Dr. Smith’s overall compliance rate (64 percent) to that of peers (74 percent) was 0.87, indicating compliance 13 percent below peers. A list of Dr. Smith’s patients for whom compliant care was not observed could accompany this report.
TABLE 4.
EXAMPLE OF PHY
SICIAN QUALITY REPOR
T, DIABETES QUALITY MEASURES
Dr
. John Smith, Inter
nal Medicine, Medical Gr
oup A Measur e Measur e Synopsis # of Opportunities Compliance Count % Compliance % Peers Compliance Compliance Relative to Peers
Patient(s) that had at least 2 HbA1c tests in last 12 r
eported
months.
HbA1c monitoring is r
ecommended for all
patients with DM. 200 90 45% 60% 0.75
Patient(s) that had an annual scr
eening test for diabetic
nephr
opathy
.
Annual scr
eening for diabetic nephr
opathy
is r
ecommended unless clinical exclusion
criteria have been met.
200
80
40%
55%
0.73
Patient(s) that had an annual scr
eening test for diabetic
retinopathy
.
Annual scr
eening for diabetic r
etinopathy is
recommended unless exclusion criteria have been met.
200
92
46%
62%
0.74
Adult(s) with a LDL cholester
ol
test in last 12 r
eported months.
Management of LDL cholester
ol goal is
recommended for adults with DM. This should be checked annually at minimum.
200
160
80%
85%
0.94
Adult(s) with most r
ecent LDL
result < 100mg/dL.
A LDL cholester
ol goal of < 100 mg/dl is
recommended for adults with DM. <70mg/ dL is a therapeutic option in some patients.
80
65
81%
90%
0.90
Patient(s) taking an ACE- inhibitor or angiotensin II receptor antagonist that had a serum potassium (K+) in last 12 reported months. Patients taking ACE-inhibitor or angiotensin II receptor antagonists should have, at a minimum, annual testing of specific serum parameters.
95
75
79%
91%
0.87
Patient(s) that had an office visit for diabetes car
e in last 6
reported months.
Patients with DM should have appr
opriate
access to car
e including, at a minimum,
assessment by a physician every 6 months. Patients with suboptimal diabetic contr
ol
can be identified for additional interventions.
200
190
95%
90%
1.06
Patient(s) with evidence of specific diabetic complications that had endocrinology consultation in last 6 r
eported
months.
Patients with evidence of specific diabetic complications would benefit fr
om
endocrinology consultation within 6 months.
30 22 73% 83% 0.88 All Measur es
Composite of all measur
es for Diabetes 1,205 774 64% 74% 0.87
Measuring Cost of Care
The cost of care is another important area of focus for ACOs in measuring performance. There are a number of steps involved in measuring costs. These steps are described generally in Table 5.