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AMBULATORY QUALITY AND SAFETY

Lawrence Ward and Rhea E. Powell

The healthcare landscape in the United States is dynamic—continuously evolving as the transition from volume to value takes hold under pressure from increasing healthcare costs and a need to deliver better care. This

foundational change in the way care is financed has greatly influenced the way care delivery is measured. Although the most acutely ill patients are managed in an acute (inpatient hospital) setting, the vast majority of patients are man- aged in ambulatory (outpatient) offices. The ambulatory setting is where most people, both those in good health and those with acute or chronic illnesses, have frequent contact with the healthcare system; likewise, it is where healthcare providers have the best opportunity to influence healthy behaviors and to prevent future illness. Providers, insurers, and regulatory agencies expect—and are increasingly demanding—to know more about the quality of care delivered in the ambulatory setting, raising the urgency of the need to develop appropri- ate methods and metrics. This chapter specifically examines the ambulatory- based quality and safety landscape, details important trends in this area, and provides an overview of the directions expected in the future.

The Ambulatory Care Setting

Ambulatory care refers to medical services performed on an outpatient basis, without admission to a hospital or other facility. Although the definition is evolving as a result of advances in technology, traditional sites of ambulatory care include primary care and specialty offices, as well as ambulatory surgery centers, urgent care centers, retail clinics, freestanding emergency departments, and work-based clinics (Medicare Payment Advisory Commission 2017). For the purposes of this chapter, we will focus on ambulatory-based providers in both primary care and subspecialist offices.

For many years, inpatient settings—such as acute care hospitals, surgi- cal facilities, emergency departments, and other facilities with more acutely ill patients—have been subject to regulation, standards, and inspection by groups such as The Joint Commission, and metrics for performance in such settings have been clearly developed and defined. In addition, payers—notably, the Centers for Medicare & Medicare Services (CMS)—have linked financial

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C o p y r i g h t 2 0 1 9 . H e a l t h A d m i n i s t r a t i o n P r e s s .

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EBSCO Publishing : eBook Collection (EBSCOhost) - printed on 9/14/2021 3:22 PM via NORTHCENTRAL UNIVERSITY AN: 2144507 ; David Nash.; The Healthcare Quality Book: Vision, Strategy, and Tools, Fourth Edition Account: s1229530.main.eds

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payments and penalties to providers’ performance on the metrics, and these financial incentives have provided motivation for a number of highly developed performance improvement infrastructures, often employing tools from Lean, Six Sigma, and other formal strategies.

Historically, ambulatory settings have not been subject to the same level of scrutiny and regulation that inpatient settings have seen, and they have not had the same incentives for improvement. However, given the large volume of patients seen in ambulatory settings and the significant potential for harm that exists, ambulatory settings need to develop a similar infrastructure to spur improvement.

Ambulatory settings present unique challenges related to the complexity of practice settings and issues with communication and flow of information. Furthermore, they often have difficulty obtaining critical quality data for such areas as medication errors, adverse drug events, missed/incorrect/delayed diagnoses, and delay of proper treatment or preventive services. Additional challenges involve the ambulatory setting’s focus on population-based man- agement—a key difference between ambulatory and inpatient care.

Hospitalized patients are tracked for the duration of their admission—and perhaps for some time afterward to reduce the likelihood of readmission—but they are not actively managed for long beyond a single episode of care. There- fore, inpatient quality and safety metrics are often one-time measures—for instance, a measure of whether patients develop a catheter-associated urinary tract infection over the course of a hospital stay. In the ambulatory setting, however, most measures focus on a population of patients seen over a certain period of time. For instance, an ambulatory practice might be responsible for ensuring appropriate colon cancer screening for every patient seen within the previous two years. An individual patient might have been seen only once, 15 months earlier, but if the data suggest that a gap in screening care has occurred, the practice is responsible for arranging for the proper screening to occur (or for correcting the data, if the screening has in fact occurred). Thus, an ambulatory practice needs to be able to identify gaps in care when patients arrive in the office, educate patients about the need for care, and arrange for appropriate follow-up. In cases where a patient chooses not to receive the recommended care, the practice needs to implement an efficient mechanism for identification, monitoring, and outreach.

Ambulatory Quality Improvement

Historical Development Donabedian’s (1966) seminal paper “Evaluating the Quality of Medical Care” created a framework that is still used to measure healthcare quality today. It divides measures into three categories: structure, processes, and outcomes.

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This framework was instrumental in the establishment in 1970 of the Insti- tute of Medicine (IOM), which has since launched numerous efforts focused on evaluating, informing, and improving the quality of healthcare delivered (National Academies of Sciences, Engineering, and Medicine 2018). Most influential among these IOM efforts were the reports To Err Is Human (Kohn, Corrigan, and Donaldson 2000) and Crossing the Quality Chasm (IOM 2001).

The organization currently known as the Agency for Healthcare Research and Quality (AHRQ) was founded in 1989, in response to data that revealed wide geographic variations in practice patterns without supporting clinical evidence (Steinwachs and Hughes 2008). Tasked with supporting a research program focused on clinical effectiveness, treatment outcomes, and practice guidelines, AHRQ has been instrumental in driving the quality agenda, espe- cially in the form of researching and defining best practices (Hospital Consumer Assessment of Healthcare Providers and Systems 2017).

AHRQ and other quality-oriented entities were established in part because healthcare organizations were seeing a rise in costs and looking for practical methods to reduce waste and disseminate best practices. Promoting ambulatory quality by providing financial incentives for high-quality care was seen as one mechanism for accomplishing these goals (American College of Physicians 2009). Traditionally, insurance companies have paid ambulatory- based physicians according to a fee-for-service model, in which the primary financial incentive for the physicians has been to see a higher volume of patients and to perform more procedures—essentially, the more they did, the more they were paid. However, as insurance companies began recognizing the need to control rising healthcare costs, they implemented methods to diversify the incentives for physicians, especially those practicing primary care.

The movement to change financial incentives for physicians began in earnest during the late 1980s and into the 1990s, through the broad devel- opment of health maintenance organizations (HMOs). Having originated in the 1940s with Kaiser Permanente, HMOs became much more widespread during this period (Markovich 2003). HMOs were among the first large-scale examples of a nongovernmental (private) insurance company asking physi- cians to recognize that they were responsible for the care of a population of patients. Under the HMO structure, physicians were assigned a set of patients who chose the HMO as their primary care provider. The insurance company then paid each physician a set amount each month to care for this group of patients. The physician would receive this “capitated” payment whether the patient received care at the office or not; however, the physician would also be responsible for care provided to the patient by other physicians. If a patient saw subspecialty physicians or went to the emergency department too often, the primary care physician would be held ultimately responsible and could face a financial penalty from the insurance company (Markovich 2003).

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Despite its many limitations, the HMO model successfully introduced primary care physicians to the concept of population health, which was central to an HMO’s success. Beginning in the mid-1990s, insurance companies began to relax the restrictions of the HMO model. While continuing the practice of capitated payments, they modestly eased the rules on referral management and the penalties toward primary care physicians for high costs of care (Marquis, Rogowski, and Escarce 2004). However, the insurance companies needed some mechanism to incentivize physicians to provide care, so they turned toward paying providers for successfully meeting goals on quality-of-care measures. In this era, before widespread use of electronic health records (EHRs), the most easily agreed-upon and trackable measures focused on such elements as suc- cessful cancer screening, care for patients with diabetes, and the prescription of generic medications. These measures were generally accepted by everyone involved as evidence-based elements of good care (Rosenthal et al. 2004).

Expansion of Quality Improvement Through Pay for Performance The National Committee for Quality Assurance (NCQA) was established in 1990, and it is tasked with managing accreditation programs for individual physicians, health plans, and medical groups, with the objective of improving healthcare quality (Sennett 1998). The organization measures accreditation performance through the administration and submission of the Healthcare Effec- tiveness Data and Information Set (HEDIS) and the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey (Marjoua and Bozic 2012).

Today, NCQA (2018) continues to have a significant influence on the selection and development of quality measures through their industry-leading recognition programs, including those for patient-centered medical homes (PCMHs) and patient-centered specialty practices (PCSPs). The PCMH, ini- tially created for pediatrics in 1967 but now widespread among all primary care specialties, is a model of care that has, more than any other before it, influenced the transition of ambulatory medicine to a patient-centered, population-based construct that places an emphasis on quality improvement (Robert Graham Center 2007).

As policymakers, purchasers, and payers looked for ways to create efficien- cies, a strong primary care system was identified as a vital aspect of managing cost and quality (Future of Family Medicine Project Leadership Committee 2004). The NCQA PCMH program asked primary care offices to commit to performance measurement and accept accountability for continuous quality improvement, and it required recognition on a continuous basis. In doing so, the program succeeded in providing financial incentives to implement permanent quality improvement elements that had rarely been seen before in ambulatory settings. Although early studies were mixed on the effectiveness of the PCMH model, more recent data have demonstrated a variety of benefits,

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including reduced hospitalizations and readmissions, better management of chronic illnesses, and improved patient satisfaction (Jackson et al. 2013; Fried- berg et al. 2014; Friedberg, Rosenthal, and Werner 2015; NCQA 2017).

The drive toward increased emphasis on ambulatory quality continued with the establishment of the National Quality Forum (NQF) in 1999 (NQF 2017a). The NQF defined national goals and priorities for healthcare quality improvement, and it built a national consensus around standardized perfor- mance metrics for quantifying and reporting on national healthcare quality efforts. NQF endorsement has thus become the “gold standard” for healthcare performance measures, relied upon by healthcare purchasers such as CMS and, by extension, private insurers as well (Marjoua and Bozic 2012).

Influenced by the NQF’s work, CMS implemented a new Physician Qual- ity Reporting System (PQRS) in 2006 (CMS 2017e). Established under the Tax Relief and Health Care Act, PQRS was noteworthy as the first nationwide “pay-for-reporting” program, and it focused on the physician as the target of feedback and incentives. It provided a bonus on the total allowed Medicare Part B fee-for-service charges to incentivize successful reporting on a series of ambulatory quality measures (CMS 2017e). Initially voluntary in nature, reporting soon became mandatory. Financial incentives were removed, and penalties for practices that failed to achieve the desired results were instituted in their place (CMS 2015).

The Affordable Care Act The movement toward ambulatory quality improvement was further supported by the passage of the Patient Protection and Affordable Care Act (ACA) of 2010, which included multiple provisions aiming to improve quality while low- ering costs and expanding access. The ACA included requirements for quality measurement, coupled with cost controls, to stimulate more efficient models of care that sought to prevent the overuse, underuse, and inappropriate use of healthcare—a focus regarded as essential for both improving quality and lowering cost (Blumenthal, Abrams, and Nuzum 2015).

Although quality programs in the ACA primarily focused on hospi- tals, subsequent legislation and regulatory actions expanded quality and value programs to additional venues (Landers et al. 2016). The ACA also provided significant indirect support for the PCMH model, and it created new entities, such as the Patient-Centered Outcomes Research Institute (PCORI), the Hospital Value-Based Purchasing (VBP) Program, and the CMS Innovation Center, that expanded the use of incentives and penalties in connection with inpatient (primarily focused on reducing readmissions) and ambulatory quality measures (CMS 2017a, 2018b; PCORI 2017).

The Hospital VBP Program uses a broad set of performance-based payment strategies to link financial incentives to provider performance on a

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set of defined measures. It aims to financially reward care providers for deliver- ing appropriate, high-quality care at a lower cost, in an effort to drive quality improvement and to slow the growth in healthcare spending (CMS 2018b). Reports suggest that the Hospital VBP Program has had mixed effectiveness in the care of patients with certain chronic conditions, such as diabetes and hypertension (Chee et al. 2016), and some people have voiced concern that the program might have the unwanted effect of disincentivizing care for these complex patients if it has negative financial repercussions (Ryan and Blustein 2012). Some are also concerned that practices and healthcare organizations might focus their attention on the diseases that are measured, to the exclusion of other important aspects of healthcare. Nonetheless, despite its possible flaws, the Hospital VBP Program’s emphasis on providing top quality at a lower price has had a meaningful influence across all care settings, and it is widely viewed as critical to the financial future of healthcare (Keehan et al. 2011).

Accountable Care Organizations While the Hospital VBP Program brought attention to hospital-based quality and cost, analogous efforts in outpatient sites prompted a move toward account- able care organizations (ACOs). CMS (2018a) defines ACOs as “groups of doc- tors, hospitals, and other healthcare providers, who come together voluntarily to give coordinated high-quality care to their Medicare patients.” The ACO model aims to improve quality and lower costs by guiding healthcare providers and hospitals toward better-coordinated, higher-quality, and patient-centered care for Medicare patients and to replace the often fragmented care received under the traditional fee-for-service system (Marjoua and Bozic 2012).

The ACO model includes an embedded incentive payment in the form of revenue sharing, which represents part of the savings that can be achieved. ACOs require providers to share in the financial risk of the plan, rather than place the financial risk on insurers, as is done under a traditional managed care model. However, savings must also be accompanied by satisfactory performance on quality benchmarks that span various process and outcome measures over multiple domains, including patient experience of care, care coordination, patient safety, preventive health, and health of at-risk populations (Marjoua and Bozic 2012). A list of measures used in ACO performance standards is shown in exhibit 14.1.

Because ambulatory quality is integral to achieving financial savings in an ACO, practices were propelled to become PCMH-recognized, to refine workflows, to integrate EHRs, and to begin viewing their patients as a popula- tion that should be proactively managed (Davis, Abrams, and Stremikis 2011). Private insurers took note as well, and they began implementing programs to

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Measure Method of

Measurement

Risk-Standardized, All-Condition Readmission Claims

Skilled Nursing Facility 30-Day All-Cause Readmission Measures

Claims

All-Cause Unplanned Admissions for Patients with Diabetes Claims

All-Cause Unplanned Admissions for Patients with Heart Failure

Claims

All-Cause Unplanned Admissions for Patients with Multiple Chronic Conditions

Claims

Acute Composite (AHRQ Prevention Quality Indicator [PQI] #91) Claims

Medication Reconciliation Post-Discharge Web interface

Falls: Screening for Future Fall Risk Web interface

Use of Imaging Studies for Low Back Pain Claims

Preventive Care and Screening: Influenza Immunization Web interface

Pneumonia Vaccination Status for Older Adults Web interface

Preventive Care and Screening: Body Mass Index Screening and Follow-Up

Web interface

Preventive Care and Screening: Tobacco Use: Screening and Cessation Intervention

Web interface

Preventive Care and Screening: Screening for Clinical Depres- sion and Follow-Up Plan

Web interface

Colorectal Cancer Screening Web interface

Breast Cancer Screening Web interface

Statin Therapy for the Prevention and Treatment of Cardiovas- cular Disease

Web interface

Depression Remission at 12 Months Web interface

Diabetes: Hemoglobin A1c Poor Control Web interface

Diabetes: Eye Exam Web interface

Controlling High Blood Pressure Web interface

Ischemic Vascular Disease: Use of Aspirin or Another Antithrombotic

Web interface

Note: The measures listed are in addition to survey measures and EHR certification.

Source: Data from CMS (2017b).

EXHIBIT 14.1 Measures for Use in Establishing Quality Performance Standards That ACOs Must Meet for Shared Savings (2017)

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link quality and payment to create more efficient systems of care. These “pay- for-performance” programs would reward providers who met certain quality thresholds, often chosen according to what Medicare was reimbursing for high performance in its Advantage plans (Rosenthal and Dudley 2007). Medicare Advantage plans, which may involve versions of HMOs in the place of tradi- tional fee-for-service Medicare, now serve a third of all Medicare beneficiaries (L&M Policy Research 2016).

Medicare Advantage measures quality and performance using a five- star rating scale. Since 2012, plans that achieve four stars or more have been eligible for additional funds from CMS, and these funds can be invested in additional patient benefits to attract more members and to differentiate the plans from lower-quality plans (L&M Policy Research 2016). Many private insurance plans have copied these strategies and introduced their own ambula- tory quality programs, usually focused on payment for reporting results, as well as meeting specific criteria for measures such as patient medication adherence and cost effectiveness.

MACRA and the Shift from Measuring Process to Measuring Outcomes Historically, the majority of quality measures developed for the ambulatory setting have focused on the completion of processes to care for patients with chronic illnesses, such as diabetes and coronary disease, and to help prevent and detect diseases such as breast cancer and colon cancer. These measures were easy to track and quantify even before the use of well-functioning EHRs, which now can be designed to improve office workflows and drive clinicians and staff to click the appropriate box and order the necessary test, vaccine, or study.

However, although these processes are important, the ultimate goal is to define and measure the health outcomes that are affected by these processes. Health outcomes are complicated by nature, and few true measures of health outcomes have yet to be adopted. Some examples may include measuring glycosylated hemoglobin levels in patients with diabetes and gauging the effec- tiveness of blood pressure control. However, even these examples are not true measures of a disease outcome. To truly measure the end effect of care would require measurement for the prevention of renal disease, a reduction in the rate of cardiac events, or a decrease in the incidence of malignancy. Although such measurement may be possible on a population level, it is extremely dif- ficult at the level of the individual medical office, much less at the level of the individual provider.

The rising costs of healthcare—and the urgent need to control them— have driven a shift away from measures of process and toward more measure- ments of true disease outcomes, utilization outcomes, and total cost of care. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) went into effect in 2017, significantly altering the way physicians are paid

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by Medicare. MACRA created the Quality Payment Program (QPP), which included two pathways for physician reimbursement: the new Merit-Based Incentive Payment System (MIPS) and Advanced Payment Models (APMs) (CMS 2018c, 2018d). For physicians in MIPS, payment is determined using four domains: cost, clinical practice improvement, advancing care information, and quality (McWilliams 2017). Although the inclusion of quality is laudable, that domain focuses primarily on the achievement of process measures, and the proportion it contributes to the overall MIPS score is set to decrease over the years. In addition, because these programs are built on historical volume- based architecture, they only offer healthcare providers a chance to earn money for quality retroactively through, most commonly, shared savings. As a result, even under the new QPP architecture, US healthcare is still not pursuing truly population-based payment, and thus progress toward true payment for quality is hindered (Landers et al. 2016).

The true value may be that MIPS establishes almost 300 quality mea- sures that will be fine-tuned over time, and that it requires subspecialists to participate in formal clinical practice improvement and submit quality results. Although the most visits occur in primary care, the highest costs arise from specialty (nonprimary care) visits and referrals (McWilliams 2017). Histori- cally, specialty practices have not often been included in ambulatory quality improvement or pay-for-performance efforts to a significant extent, and they continue to derive most of their income from patient visits, procedures, and studies. Therefore, increasing the involvement of specialist providers in quality improvement is a welcome development, with the potential to have a significant impact on quality and cost.

Ambulatory Safety

Evolution of the Patient Safety Movement In addition to spearheading the drive for quality improvement, the landmark IOM report To Err Is Human also brought patient safety to the forefront of healthcare issues, setting a national agenda for reducing medical errors (Kohn, Corrigan, and Donaldson 2000). Shortly after the report’s release, the federal government passed the Healthcare Quality and Safety Act, reauthorizing AHRQ and charging it with the responsibility to develop programs to identify causes of medical errors, to evaluate strategies for reducing errors in healthcare delivery, and to disseminate effective strategies throughout the industry (Congress.gov 2017). The years since that landmark IOM report have seen great strides in improving the safety of the American healthcare system.

Hospitals across the United States have designed and implemented programs to identify and address causes of patient safety problems. They have

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adopted specific approaches such as checklist interventions, antibiotic stew- ardship programs, and medication reconciliation programs, as well as broader approaches, such as programs to improve patient–provider communication and team-based care. At the same time, policy changes related to reimbursement for hospital-acquired conditions have shifted incentives, increasingly holding hospitals accountable for certain adverse safety events. The implementation of these programs and policies nationally has resulted in significant reductions in common hospital-acquired conditions such as central line–associated blood- stream infections, surgical site infections, hospital-onset Clostridium difficile infections, and hospital-onset Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia (Centers for Disease Control and Prevention 2016). The benefits that patients experience through improved safety are coupled with benefits to the healthcare system, with billions of dollars in healthcare costs believed to have been saved (AHRQ 2014).

Challenges to Delivery of Safe Care in the Ambulatory Setting Although much progress has been made in the inpatient hospital setting, system- atic programs to improve safety in the ambulatory setting have only been devel- oped more recently. Addressing the safety of healthcare delivery in the ambulatory setting presents myriad challenges. Ambulatory care is often fragmented, with patients receiving care from multiple providers and health systems. Patients may experience long waiting periods, with a number of transitions between healthcare settings. Patient engagement is also a challenge, as patients in the ambulatory setting are held responsible for making decisions about when and where to seek care, managing medications, and performing daily health-related tasks, often without immediate assistance from members of the healthcare team. Furthermore, although numerous evidence-based measures have been developed for the safety of hospital-based care, fewer measures are available to evaluate ambulatory safety. Similarly, fewer evidence-based programs are available for providers and health systems to adopt to improve patient safety in the ambulatory setting.

The relative lack of measures and evidence-based programs for addressing ambulatory patient safety should not be interpreted to mean that ambulatory settings have fewer patient safety problems. To the contrary, a variety of studies have underscored the frequency of medical errors that occur in the ambulatory setting (Sarkar 2016; Panesar et al. 2015).

In 2015, AHRQ sought to address this problem by establishing a task force to provide a comprehensive look at patient safety in the ambulatory setting (Shekelle et al. 2016). The resulting report focused on identifying problems relevant to ambulatory-based care and developing strategies to improve safety. The report identified five concrete patient safety areas that would need to be systematically targeted to meet ambulatory safety goals: (1) medication safety, (2) transitions of care, (3) test tracking, (4) referral tracking, and (5) diagnosis.

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Medication safety concerns are analogous to many safety issues in the hospital setting, including errors in prescribing, dispensing, and monitor- ing medications, as well as failure to note medication interactions. Other medication safety problems are more relevant to the ambulatory setting—for instance, failure to discontinue medications or to identify and address medica- tion nonadherence.

Transitions of care—for instance, during discharge from the hospital or after an emergency department visit—carry a high risk for adverse patient safety events (Forster et al. 2004, 2007; Moore et al. 2003). The risk of adverse drug events is especially high during these transitions, especially for older adults (Kanaan et al. 2013). Changes in medication are common during hos- pitalizations, including discontinuation of prior medications, initiation of new medications, and dose adjustments. Poor communication between inpatient and outpatient providers is common during transitions, and it has significant implications for safety (Kripalani et al. 2007).

Tracking tests that have been ordered and following up on patient referrals to specialists are essential for reducing errors in healthcare delivery. The tracking of pending test results is especially important during transitions of care. Research suggests that more than 40 percent of patients have pending test results at the time of hospital discharge (Roy et al. 2005). Errors at any step during the testing, reporting, interpretation, and communication processes can lead to errors in the ambulatory setting (Hickner et al. 2008). Ensuring that patients are aware of meaningful test results, both normal and abnormal, is important for the safe provision of care, as is the tracking of test results across the system—including tests that have been ordered but not completed.

Referrals throughout the ambulatory care system also must be tracked. Studies of patient referrals from primary care providers to specialists have revealed poor integration, breakdowns in communication, and process inef- ficiencies (Mehrotra, Forrest, and Lin 2011). Specialty providers are not always aware of the reasons for the referral, primary care providers are not always aware of specialists’ treatment recommendations, and patients are often burdened with transferring information between providers. Shared EHRs can help improve this communication, but they need to be coupled with systematic approaches to referral tracking and communication strategies among providers on a care team.

Finally, diagnostic error has garnered much attention as an area of focus for patient safety efforts. In a 2015 report titled Improving Diagnosis in Health Care, the National Academy of Medicine defined diagnostic error as either the “failure to (a) establish an accurate and timely explanation of the patient’s health problem(s) or (b) communicate that explanation to the patient” (National Academies of Sciences, Engineering, and Medicine 2015, 4). Although diag- nostic error rates are difficult to measure, such errors are common. They are believed to affect at least 5 percent of US adults in the outpatient setting, or

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12 million adults annually (Singh, Meyer, and Thomas 2014). The figures are even higher in the inpatient setting (Graber 2013). Accurate and timely communication of diagnosis is central to the provision of safe care across all healthcare settings.

Strategies for Safe Care Although patient safety in the ambulatory setting has challenges distinct from those in the inpatient setting (Wachter 2006), many strategies to improve safety are common to both. Key strategies include establishing and maintaining channels of communication, effectively using health information technology (IT), providing team-based care, fostering patient and family engagement, and developing organizational approaches and a culture of safety (Shekelle et al. 2016). These strategies are essential for organizing and delivering safe, high- quality care in the ambulatory setting.

Patient-centered medical homes and other patient-centered popula- tion health models of care can facilitate improved patient safety by leveraging teamwork, information management, population measurement, and patient empowerment (Singh and Graber 2010). These strategies must not be lim- ited to primary care providers; they should engage specialists as well. Patient- centered specialty practices and medical neighborhood models can facilitate the establishment of referral agreements between primary care providers and specialists (Ward et al. 2017). Coupled with effective health IT utilization, such agreements can improve referral tracking and communication between specialists and primary care physicians (Akbari et al. 2008). Health IT measures are also essential for maximizing the safety of test tracking—although, even with advanced EHRs, systems are still needed to ensure that critical results are addressed in a timely manner (Singh et al. 2009).

Future Challenges and Keys to Success

The Role of Primary Care and Subspecialty Providers Primary care is considered by many to be the foundation for any successful population health strategy, because primary care physicians—including family physicians, general internists, and pediatricians—are the medical providers who most commonly oversee all aspects of their patients’ care. They are the main providers for patients with such chronic diseases as coronary artery disease, diabetes, and emphysema, and they are usually the healthcare professionals held responsible for ordering the majority of preventive cancer screenings. They are also the providers most often called upon to manage the numerous ambulatory quality metrics. Primary care physicians have long been central to programs such as PCMHs and the Comprehensive Primary Care Plus (CPC+) model (White 2015). Demand for primary care physicians is likely to increase

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in the coming years as populations age and grow in size (Health Resources and Services Administration 2013).

Given the ever-increasing demands to deliver higher-quality care at a lower cost across all healthcare settings, a key issue involves incorporating the Institute for Healthcare Improvement’s Triple Aim—better experience of care, improved health of populations, and reduced costs (Berwick, Nolan, and Whit- tington 2008)—in subspecialty offices. MIPS and initiatives such as NCQA’s PCSP recognition program have initiated this transformation, but more work remains to be done. A greater emphasis will be placed on educating providers and implementing programs in offices that historically have not been heavily involved in formal ambulatory quality and safety programs (Ward et al. 2017).

Impact of Compensation and Aligning Incentives Regardless of the practice location, quality and safety metrics should align both with the best clinical care recommendations and with the incentives of medi- cal providers. Incentives for providers may be financial in nature, or they may involve the desire for the most efficient processes for completing the required care, or improved job satisfaction (Bodenheimer and Sinski 2014).

Well-aligned quality measures will promote optimal performance and boost clinicians’ motivation by rewarding them for managing patients appro- priately. Conversely, poorly aligned measures often add unnecessary work and can even have a negative impact on care by drawing attention away from more important duties (Cassell and Jain 2012; Young, Roberts, and Holden 2014). Furthermore, poor alignment can contribute to physician burnout and cause providers to lose confidence in the overall quality improvement effort (Greenhalgh, Howick, and Maskrey 2014). As healthcare shifts from volume- to value-driven payment approaches, the financial incentives for providers must include appropriate components that reward the delivery of high-quality care.

Number and Standardization of Measures As the measurement of quality in healthcare has grown and evolved, concerns have arisen about the measures’ complexity and the administrative burden they place on providers. For example, the NQF tracks 634 measures through its Quality Positioning System (NQF 2017b). The fact that so many metrics exist—and that a significant number of them must be reported on a regular basis—can be overwhelming. Reporting on such a large number of required measures risks impeding the ability of providers to focus on the metrics that have been proved to be the most important.

Researchers in 2012 estimated that quality measurements and analysis cost healthcare providers $190 billion annually, and that figure is likely to have increased (Meyer et al. 2012). The cost is especially high for organizations that participate in multiple quality initiatives (Blumenthal, Malphrus, and McGinnis 2015). At one such organization, an analysis documented the need to report

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more than 1,600 quality measures to 49 different sources, at a cost of more than $2 million (Murray et al. 2017).

Additional complexities may result from differences in the measures used from one insurance plan to another. For example, one insurer might choose to rate providers’ care of patients with diabetes based on their ability to bring the patients to a glycated hemoglobin (HbA1c) level of less than 9 percent; another might use a threshold of 8 percent. Still another might choose a com- posite score where HbA1c is only one of multiple metrics used, combined with diabetic eye and kidney care.

This lack of uniformity creates difficulty for provider organizations looking to gather accurate data and perform patient outreach to close gaps in care. It also risks turning providers against the quality improvement movement, if they feel the bar is being set impossibly high or the requirements are too complex for them to understand. To maximize the effectiveness and efficiency of quality improvement programs, all (or, at least, most) insurers must decide upon and utilize a standard set of baseline metrics.

Transparency of Data to Other Providers and the Public Today, many hospital quality and safety measures are publicly reported, and consumers often compare institutions with one another based on these mea- sures. Experts expect that similar reporting and comparisons with ambulatory measures will not be far behind (Lamb et al. 2013).

This development will require standardized data, but some health plans already have the ability to begin this process. We can easily envision, for instance, a health plan sharing information not only on the cost of care provided by one office compared to another but also on the offices’ safety or quality scores. CMS has already reported on PQRS participation, and it might publicly release future MIPS data in a fashion that supports comparisons between medical providers. Through these efforts, pay-for-performance programs become less important than the fact that patients will be able to decide whether to begin a relationship with a provider based on its performance on quality and safety scores.

Conclusion

The growing emphasis on ambulatory quality and safety has had a significant impact on practice operations, the daily workflows of medical providers, and the financial viability of healthcare organizations in the United States. Spurred by such initiatives as the PCMH program and the Value-Based Purchasing Program, ACOs, providers, and health systems are becoming accustomed to measuring quality and safety performance, reporting data, and being reimbursed for the quality of patient care.

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The momentum of national strategies to improve healthcare quality has been sustained by public and private funding and by the development of poli- cies that support measurement, public reporting, and accountability. Innova- tion and collaboration will continue to be a priority for quality improvement efforts, as new care-delivery and population-based models are explored to support integration across healthcare sectors. A key challenge will be to care- fully choose quality measures while also limiting redundancies and inefficiencies in the various measures employed across the healthcare landscape. Leaders in quality improvement will also need to continually evaluate the effectiveness of quality programs, incorporate new evidence from scientific research, and reach out to providers across all specialties and healthcare settings.

Case Study: A Private Practice in the Pennsylvania Chronic Care Initiative

Dr. Johnson had been a family medicine physician in Pennsylvania for ten years. He had one physician partner and an office staff of three people: his wife, who functioned as an office manager; a front desk clerk, who greeted visitors, checked patients in and out, and answered phones; and a medical assistant, who assisted with rooming patients, performing electrocardio- grams, and drawing blood. The office was under increasing pressure to see more patients and to have shorter appointment times, and Dr. Johnson was concerned about his ability to practice medicine the way he wanted.

In 2008, Dr. Johnson was contacted about a program called the Penn- sylvania Chronic Care Initiative (CCI), which was slated to begin the follow- ing year. The CCI was an NCQA-accredited program that partnered with his primary professional organization (the Pennsylvania Academy of Family Physicians) and was funded through the predominant local insurance com- panies, both private and public (Medicare and Medicaid). The CCI sought to create a collaborative network to assist practices in becoming true PCMHs, and it would pay practices monthly for the patients they were caring for on a per-member-per-month basis (Patient Centered Primary Care Collaborative 2015). Excited that this program might alleviate some of his financial burden while also helping him take better care of patients, Dr. Johnson decided to investigate. He learned that many other practices in the area were joining the program, so he decided to do so as well.

Dr. Johnson’s local insurers had recently begun offering financial incentives for meeting certain quality metrics, as well as for becoming rec- ognized as a PCMH. He had researched the PCMH concept and thought it

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sounded like a good idea. However, he was unable to meet the criteria for PCMH recognition without first having funds for additional staff to track his population of patients and to do the necessary outreach to them, along with other required components. He hoped that the CCI would quickly provide him the funds to help him meet the criteria and gain recognition.

Dr. Johnson was accepted into the CCI and quickly saw some ben- efits for his practice. First, he met with a practice facilitator who helped him develop workflows to meet PCMH criteria and to address the issues of patients who experienced gaps in some aspect of care (e.g., they were due for a mammogram). The facilitator also worked with him to better utilize the EHR system he had purchased a couple years earlier but had not used for anything beyond simple office documentation. Next, Dr. Johnson joined a regional learning collaborative with other practices similar to his own. The collaborative helped provide him and his staff with the education and tools necessary to further redesign his practice. Dr. Johnson was required to submit monthly reports on his performance, and he began to receive additional payments from the insurers.

Dr. Johnson quickly realized how much his office needed to improve to meet the demands of a modern medical practice. In addition to manag- ing the immediate medical needs of his patients, he also had to make sure that the numerous quality metrics (e.g., appropriate cancer screenings, diabetes care metrics) were met. His staff had to track the measures and identify patients who were missing a quality metric—even if those patients had not been seen in the office for up to two years. Significant time had to be devoted to accomplishing these tasks, in addition to writing letters and making phone calls.

Thankfully, Dr. Johnson’s performance after the first year of the pro- gram was very good, and his rate of meeting many quality metrics had improved significantly. For example, prior to joining the CCI, Dr. Johnson was not regularly tracking his rate of checking the HbA1c levels in patients with diabetes. The practice coaches calculated that he had been checking the levels in 68 percent of patients at some point in the previous year. By both identifying patients when they came to the office and performing outreach to those who did not, his office raised that rate to 90 percent.

Dr. Johnson saw similar improvements in most of the other metrics, with the exception of colon cancer screening. His rate of appropriate screen- ing had improved from 52 percent to 58 percent, but the national average was 70 percent; therefore, he was not satisfied. With the help of his staff and the regional collaborative’s suggestions, he sought to evaluate why his performance had not improved as much as he had hoped. Using the

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Plan-Do-Study-Act method, the office staff began making changes to their workflows, seeing what effect those changes had, and making the neces- sary adjustments to improve performance. Their primary discoveries were (1) that patients needed more information to convince them to undergo a colonoscopy and (2) that the gastroenterologist to whom the practice was referring patients was doing a poor job of contacting those patients who were referred for screening. Subsequently, Dr. Johnson improved his explanation to patients of why they needed a colonoscopy and provided supporting written materials. He also began referring patients to a different gastroenterologist who was better able to handle the volume of referrals from his office. After six months, his colon cancer screening rate rose to 74 percent, which qualified him for additional payments from several insurance companies at the end of the year.

Case Study: Comprehensive Primary Care Plus

In 2017, a suburban primary care practice consisting of four physicians and three nurse practitioners applied for and was accepted into a new CMS Innovation Center program called Comprehensive Primary Care Plus, or CPC+ (CMS 2017d). The program was intended as an expansion of the medical home model, which aimed to strengthen primary care through regionally based public/private payer payment reform and care delivery transformation.

The predecessor of CPC+, the CPC initiative, did not achieve financial savings or improvement on quality measures but did demonstrate ways that aligning financial incentives, quality improvement, and data feedback could support practice transformation (CMS 2017c; Dale et al. 2016; Anglin et al. 2017). Building on this knowledge, CPC+ was designed to provide significant funding to practices to make investments, improve quality of care, and reduce the number of unnecessary services their patients receive. As in the previ- ous CPC initiative (and like CCI in the previous case study), CMS provided member practices with a robust learning system, as well as actionable data feedback to guide their decision making. In addition, CPC+ is considered an “advanced” APM for MACRA, which allowed for bonus payments to providers in future years (CMS 2017d). Based on these potential benefits, the provid- ers in the primary care practice decided to join the program.

At the start of the CPC+ program, the practice was notified that it had 1,000 Medicare patients who were attributed (linked) to the practice for the purposes of the program. This attribution made the practice eligible

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to receive more than $300,000 that year, to be specifically used to hire additional personnel to support the program. After extensive discussion, the practice decided to hire a clinical social worker to assist with behav- ioral health; a nurse to provide care coordination to patients with complex medical needs; and two additional medical assistants to help close quality gaps and to contact patients soon after visits to hospitals and emergency departments.

The CPC+ program had significant administrative reporting require- ments, and satisfying the required quality metrics took substantial effort. At the end of the year, the practice had to submit to CMS the results of nine metrics that they had chosen at the start of the year. Because two of the metrics chosen had never been followed by the practice, and because the providers were unsure whether their EHR system would be able to record measures accurately, they chose to implement an additional two metrics just in case they had problems meeting all the requirements.

The practice hired additional staff and went about implementing the many aspects required by the CPC+ program, including additional care management, tracking and contacting patients after hospital and emergency department visits, and arranging meetings in which patients and practice representatives discuss ways to improve the practice experience. The prac- tice also instituted weekly care team meetings in which physicians and other staff (clinical and nonclinical) would discuss complex patients and review data on hospital readmission rates and quality metrics. Some staff initially viewed these meetings as distractions that interfered with time that could be used to see patients. However, the practice soon realized that, through use of the Plan-Do-Study-Act methodology, results on several of their quality measures had begun to improve. Eventually, staff members came to view the meetings as invaluable opportunities to gather as a group to overcome barriers to improvement (IHI 2017).

Case Study: A New Pay-for-Performance Contract

An eight-member primary care medical practice signed a new contract with an insurance company. The previous contract had paid the practice an average of $90 for each office visit, and the practice had the opportunity to earn an extra $10 per patient, on average, if certain quality measures were met. Over the previous several years under that contract, they had been recognized as a level-3 PCMH, which had earned them an additional $3 per patient.

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The practice used the money to hire a nurse and to close quality care gaps. The members of the practice had met all of the quality measures and had successfully maximized their earnings.

Under the new contract, the members agreed to accept a lower aver- age payment of $80 per office visit but hoped to offset that drop by maxi- mizing the new quality payment program, which could earn them an extra $30 per patient. Unfortunately, the insurance company did not renew the extra payments for being a PCMH, stating that such status was now a basic expectation for all practices in the network. Nonetheless, the new contract gave the practice an opportunity to earn more money overall if it was suc- cessful in meeting its quality objectives. The members estimated that the practice would earn less money over the next year, because of the drop in payments per visit, but could earn more money when the quality results were tallied at the end of the year, if the practice performed well.

To maximize their chances of success, the practice worked with its EHR vendor to pull data reports from the system, helping to monitor the practice’s performance on quality metrics and to identify specific patients who had a gap in care (e.g., patients who needed to have a test completed). A specially trained medical assistant would then use the reports to call patients, briefly explain to them what was needed, and arrange for the test or study to be completed. A provider would write the order, and the medical assistant would make sure all necessary paperwork was completed.

The practice developed a workflow in the EHR that would flag patients with a gap in care so that the appropriate action could be initiated imme- diately by the front desk or medical assistant and quickly approved by the provider when the patients arrived for office visits. Under this approach, office staff were asked to work “at the top of their license” and felt that they were an integral part of the healthcare team. The approach also allowed providers to focus more on making the complex medical decisions they were trained to make.

A practice report card was developed to track performance and sup- port communication among the staff and providers. The report card was populated with data pulled from the EHR for each metric that was being tracked, and the data were directly linked to the goals stated in the insur- ance company contract. The report card was updated on a regular basis and shared at each monthly practice meeting, when everyone gathered to discuss current issues. Any metric that was not meeting the performance goal was discussed in detail, and action plans for improvement were developed. The staff then used Plan-Do-Study-Act cycles to fix any problems, with a follow-up report at the next monthly meeting.

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Study Questions

1. How has passage of the Affordable Care Act affected the emphasis on delivering high-quality care to patients?

2. Construct a possible future timeline for quality improvement activities and legislative initiatives. As healthcare funding moves increasingly to a focus on high-value care, how might measurement and reporting of quality and safety processes and outcomes change? How will these changes affect the way that care is financed by payers and delivered by providers?

Case Study: Referral Follow-Up and Ambulatory Safety

A 57-year-old man, Mr. Young, had experienced three months of burning chest pain after eating and intermittent diffuse abdominal discomfort. His primary care physician prescribed a proton-pump inhibitor for suspected gastroesophageal reflux and ordered a panel of lab tests, including a rou- tine screening for hepatitis C. The physician also noted that Mr. Young had never received a colon cancer screening, so she gave him a referral to a gastroenterologist. The physician included the referral with Mr. Young’s visit summary paperwork, but she forgot to explain the reason for the referral. He left the office without talking to any of the other staff members on the team.

Mr. Young took omeprazole as prescribed, and his symptoms improved significantly. Feeling much better, he decided to postpone getting the blood tests done. Mr. Young also misunderstood the reason for the gastroenter- ology referral, thinking he had been referred to address his now-resolved abdominal symptoms; thus, he felt no urgency to schedule the appointment.

Although this case is fictional, the scenario is typical of many inter- actions in the ambulatory setting. If the eventual tests revealed that Mr. Young was positive for hepatitis C or if he had abnormal findings on his colonoscopy, he would be at risk for delayed diagnosis. Thus, systematic strategies for test tracking and referral tracking should be implemented to alert the primary care physician if actions ordered for a patient have not been completed in a timely manner. Furthermore, team-based care strategies can be employed both at the time of the visit (e.g., having a medical assistant review the visit summary at check-out) and at a later date (e.g., having a team member use population health approaches to identify patients due for test completion or routine screening).

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3. Discuss the impact that federal quality and safety improvement initiatives will have on healthcare delivery in the state in which you reside. What federal legislative initiatives are controversial in your state or have a high degree of support? Why?

4. Discuss how the mandate to submit quality and safety data to insurance payers might affect a physician office. What would be the positive impact on the office and on the patients it serves? What would be the potential negative impact?

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