Quality Improvement

Improving Systems of Care

"Every system is perfectly designed to achieve exactly the results that it achieves."

"Quality of care is the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge."

(Institute of Medicine, 1990)

"All health care organizations, professional groups, and private and public purchasers should pursue six major aims; specifically, health care should be safe, effective, patient-centered, timely, efficient, and equitable."

(Institute of Medicine, 2001)

"Health care interventions that are known to work and save lives are not being implemented for every patient every time."

(Salzburg Seminar Statement, 2013)

Quality improvement (QI) is an important strategy to improve systems and reduce variation in delivery of care and services so that patients receive the right care every time they visit clinic, increasing the likelihood of their achieving the expected benefits and outcomes of care. As we move forward to end AIDS in the United States and meet the goals of the National HIV/AIDS Strategy, QI becomes an even more important methodology to implement in local systems through evidence-based interventions that can improve care, linkage, and retention.

Quality improvement has become a fundamental component of the HIV service delivery system whether care is provided in dedicated or integrated delivery models. Clinical quality management is a legislative requirement for Ryan White-funded programs. Many clinicians have learned the basics of quality management, which are reinforced through Maintenance of Certification programs directed through medical and specialty boards. Many clinicians not only are participating actively in QI activities, but also are leading improvement efforts in their clinics. Moving beyond the basics, however, remains a challenge for clinicians who have limited time to participate in activities not related to direct patient care. Yet, focusing on quality can reveal important phenomena in the operational processes and delivery systems of the clinic of which the leadership is unaware and may reveal factors that explain why intended outcomes are not always being realized. Additionally, the participation of clinicians in clinic-wide QI improvement activities is often a critical ingredient for their success.

Increasingly, QI work in the HIV field is directed toward achieving important health outcomes such as HIV viral load suppression, retention in care, and reductions in readmissions and emergency department utilization. Simple subanalyses of basic performance data also may reveal disparities in how care is being provided to different patient groups in the clinic, for example, according to age, gender, or race/ethnicity. Careful assessment of the social determinants of health also may show which patients need to be targeted in improvement activities. At the same time, advances in health information technology have made it easier to generate data for performance measurement and to produce simple reports that can be used for improvement activities.

This chapter will review the basics of QI; an appendix at the end of the chapter illustrates concepts with examples of more advanced improvement work. The Health Resources and Services Administration HIV/AIDS Bureau Performance Measures chapter in this manual presents a national quality initiative developed by the U.S. Health Resources and Services Administration (HRSA) HIV/AIDS Bureau (HAB) for Ryan White HIV/AIDS Program-funded clinics; HRSA's Performance Measures can be incorporated into the quality improvement programs of local clinics.

The fundamental concepts of QI have evolved over the past century to include the following:

  • QI provides an opportunity to solve problems that are part of the system and do not depend on one individual.
  • Reducing variation in performance will allow consistent delivery of the best possible care.
  • Improving processes within the health care delivery system will lead to improvements in outcomes.
  • Data are the key to identifying problems and measuring change.
  • Focusing on performance measurement and improvement usually stimulates employees to maximize their performance.
  • Team-based problem-solving techniques lead to better care and promote a positive working environment.
  • Testing changes will identify solutions that work and eliminate putting ineffective solutions into practice.
  • Consumers play a pivotal role in providing the "end-user" perception of the quality of the services delivered; their active participation in the quality management program strengthens improvement work and leads to better results.

In addition, documentation of QI activities helps to demonstrate institution-wide compliance with accreditation responsibilities and funding requirements. Data generated from the clinic's QI program showing improvements over time demonstrate to constituents that the program is successful and help to justify its funding. These data also build the evidence base for determining which interventions are successful and can be disseminated to achieve large scale change.

Finally, quality management systems that are dependent on single individuals will not last when these key players leave the clinic or are absent for long periods, whereas a fully functioning QI program that involves staff working in teams with a clearly defined infrastructure will keep going when even the most dynamic individuals depart.

This chapter will articulate the core principles of QI and describe activities that can be easily adapted into the HIV ambulatory care setting to implement a sustainable quality management program.

Introduction to Quality Improvement

QI includes regular measurement of processes and outcomes to analyze the performance of the system of care with the ultimate goal of reducing variation in care delivery. It involves the implementation of solutions to improve care and the monitoring of their effectiveness in achieving optimal health outcomes for patients. Ongoing cycles of change and remeasurement are implemented to test and try different ideas to determine which practices result in improved care. QI activities in clinics can range from a single team focusing on improving one aspect of care to a comprehensive QI program with many teams working on a wide variety of improvement projects, with a well-established plan and an oversight committee.

The methods of QI are based on core principles that are readily translated into a practical approach and integrated into the clinical care delivery system (see Table 1). Successful implementation of QI involves actions at two levels: the QI activities and the HIV program processes that provide the structural backbone for them.

Table 1. Core Principles of Quality Improvement

  • Emphasis on systems of care: improve processes that link to desired outcomes
  • Focus on the customer: understanding patients' experience in the clinic will identify areas that are important for improving care
  • Measurement: collect and use data to improve care
  • Involvement of participants: encourage direct participation in teams by those individuals who implement the processes being evaluated

Measurement and Management Are Not Sufficient

Although it is the bedrock for improving care, measurement alone is not sufficient to improve quality. A common pitfall in implementing QI programs is to rely solely upon performance data, the medical or program director's interpretation of it, and one person's decisions about how to make changes. Successful improvements occur most often when staff members from the systems being assessed work together in teams. When they are engaged in the process, staff members are more likely to generate ideas for improvement and to accept changes. Staff review of improvement charts (e.g., see Figure 1, below) generates pride and a sense of accomplishment based on members' participation in the QI work. These charts may be posted on bulletin boards in common areas of clinics so that everyone can view them.

QI Personnel

The size of the clinic will determine who participates in quality-of-care activities. In small HIV clinics with a primary care provider, case manager, nurse, and support staff, most of the staff members are involved in all aspects of QI work. Larger institutions usually establish an HIV Quality Committee that includes senior management of the HIV clinic, designated QI staff members if there are any, and other key players who work in the clinic. A member of this committee represents the group in the agency-wide QI committee. The Quality Committee identifies the priorities for improvement or agrees to pursue the priorities identified by staff members or patients in the clinic. The Quality Committee also charters improvement teams and identifies potential members who are key stakeholders in the process under investigation. In a small clinic that has only a handful of staff members, all clinic personnel may participate in the quality management program and in QI activities, although perhaps in a less formal way than in larger clinics.

Team Membership and Responsibilities

Teams are formed to address the specific care processes or systems that are targeted for improvement. Team members should be selected to represent the different functions involved in these processes or to represent the components of the system under focus. The size of a team varies according to the size of the clinic and the process under study. In small clinics, the few dedicated HIV program staff members may constitute the project teams, with added representation from different departments as needed (such as from the laboratory, or from other medical disciplines). In larger clinics, teams often include 6-10 members. Membership should include representatives from the different groups in the clinic who are involved in the care process. In addition to the clinical and case management staff, scheduling clerks and medical records personnel are often important participants, especially when follow-up appointments and documentation are components of the care process or have been identified as areas that need to be improved.

Teams sometimes struggle with engaging physicians in their QI activities. Increasingly, physicians have overcome their reluctance to join process improvement teams, especially since more sophisticated data systems and comparative reports have become available to focus interest on improving care that does not meet standards or falls below mean performance rates. Moreover, physicians are now required to directly engage in practice-based learning and improvement to satisfy requirements for maintenance of professional certification. Studies of physician performance have demonstrated that participation in QI activities enhances job satisfaction and reduces work-life stress.

Involving consumers in QI project teams enhances the work of the team. Consumers who are involved in the clinic's community advisory board often are natural leaders and have a good grasp of clinic processes. Their feedback on the experience of care delivery can reveal areas that need improvement. They know the bottlenecks and can inform the staff how long a clinic visit lasts, whether assessments truly occurred, and whether behavioral interventions are effective. Their ideas about what improves care often diverge significantly from those generated by providers and may not even be recognized unless consumers participate directly in discussions about the system.

Teams are expected to analyze clinical processes, identify areas of change, implement tests of the changes, review data assessing the change, and ultimately make recommendations about which improvements should be adopted in the clinic.

Data Collection

Selecting Measures

Evaluating measurable aspects of care can help in determining the extent to which a facility provides a certain element of care. Quality measures should be based on standards or guidelines, meet the primary goals of QI, and reflect priorities specific to the community and the clinic. In addition, they should represent processes where changes are feasible. For example, in HIV clinics where the population consists of a large number of women, indicators may include rates of routine cervical cancer screening, rates of preconception counseling, or other aspects of care specific to women. In clinics that care for a high volume of patients who have been treated with antiretroviral therapy (ART) for a long time, measures may focus on rates of virologic suppression, screening for adverse effects of antiretroviral medications, and resistance testing. As we focus on our strategies to maximize community viral suppression, measures of linkage to care, engagement, and retention in care become priorities.

Some measures should be selected by soliciting input from patients who attend the clinic (see Table 2). Staff members also often know what aspects of care would benefit from being measured and improved, and they should be consulted to determine priorities. If routine data collection systems already exist in the clinic, data should be reviewed to determine which components of care would be prime candidates for improvement.

Table 2. Methods for Obtaining Input from Patients

  • Suggestion box
  • Surveys
  • Exit interviews
  • Focus groups
  • Consumer advisory board
  • Participation on QI teams
  • Membership on the QI Committee

On a national level, the HRSA HIV/AIDS Bureau (HAB) has developed HIV/AIDS Performance Measures for monitoring the quality of care provided in Ryan White HIV/AIDS Program-funded clinics. These measures emphasize important areas of HIV care that are linked to the goals of the National HIV/AIDS Strategy and that are also endorsed by the National Quality Forum, which confers eligibility for inclusion in Meaningful Use criteria and other provisions of the Accountable Care Act that are important for both measuring care and are linked to enhanced reimbursement programs. They form a core package of priority indicators that can be enhanced by those that are identified through analysis of local data, or identified by local stakeholders. See chapter Health Resources and Services Administration HIV/AIDS Bureau Performance Measures for these.

Ideally, a balanced set of measures should be selected. Different ways to categorize measures might include the following:

  • Structure/process/outcome
  • Treatment/care (non-ART)/prevention/nonclinical service
  • Provider/consumer/funder driven
  • Aspects representing overutilization, underutilization, or misutilization of services

Developing and Quantifying Quality Measures

Three major activities constitute the process of developing performance measures:

  • Defining the measurement population
  • Defining the measures
  • Developing the data collection plan

The measurement population is defined by determining factors such as the location of care being studied, whether both men and women are eligible, the applicability of the measure to various age groups, whether any clinical conditions are necessary to determine the applicability of the measure, the number of clinic visits by the patient, and amount of time the patient has been in care.

After the population is defined, the measure needs to be defined. The measure should be objective and should address specific aspects of quality care. It also should have a straightforward, dichotomous answer. For each measure, specific criteria must be developed to define the "yes" response and the "no" response (see Table 3). This often involves deciding the time period during which an activity has been performed. For example, a measure that evaluates viral load monitoring must include the frequency with which that test should be performed. One simple way to construct this measure would be to ask, "Was viral load measured within the past 6 months?"

Table 3. Examples of Specific Measures with Definitions of Responses
Measure Definition of Measure Yes/No Response
HIV Viral Load Monitoring Was HIV viral load measured in the past 6 months? Yes: Viral load testing was performed

No: Viral load testing was not performed (or the test was done but results were not documented)

HIV Viral Load Suppression Was the HIV viral load <200 copies/mL at the most recent test during the past year? Yes: Viral load was <200 copies/mL

No: Viral load was >200 copies/mL

Several elements of care should be measured simultaneously, whether abstracted from medical records or analyzed through administrative databases. Measures reflecting aspects of patient management should be selected, as should those involving different populations. Measures also should be selected to evaluate various components of the health care system, such as the components of the chronic disease model. Clinical measures should include those that affect a large proportion of the patient population, such as whether comprehensive mental health screening has been performed.

The data collection plan includes determining the source of information (e.g., whether medical records or an electronic database will be used), how the data will be recorded, who will record the data, and how a data sample will be selected. A representative sample will allow inferences to be made about the overall clinic population based on observations of the smaller sample. Some form of random sampling should be used, either by using a random numbers table or by selecting every nth record from the list of eligible patients.

If electronic health records (EHRs) are used, sampling will not be necessary. Careful planning is required, however, to ensure that the measures are included in the electronic system, and that the EHR database is constructed to contain the elements required in the reports generated by the quality evaluation queries.

A common pitfall at this point is to think of the measurement sample as a research project. For the purposes of QI, a sample needs only to be current, representative, and readily obtained (i.e., sample size calculations and the achievement of statistically significant results are not necessary).

Analyzing and Displaying Data

Figure 1. Percentage of Patients with HIV Viral Load Suppression, by Month

Percentage of Patients with HIV Viral Load Suppression, by Month

Adapted from Measuring Clinical Performance: A Guide for HIV Health Care Providers. New York: New York State Department of Health AIDS Institute. April 2002.

Figure 1. Percentage of Patients with HIV Viral Load Suppression, by Month

Sample Fishbone Diagram

Adapted from Measuring Clinical Performance: A Guide for HIV Health Care Providers. New York: New York State Department of Health AIDS Institute. April 2002.

Data should be reviewed and distributed to all members of the team and others involved in the care process under evaluation. When possible, data should be displayed in graphic format. After data from multiple time periods have been collected (e.g., percentage of patients with HIV suppression), a simple line graph (run chart) can be constructed with each point representing a performance rate (percentage) for a given period of time. This usually is the simplest and most effective way to show performance data (see Figure 1).

Identifying Targets and Implementing Improvements

Figure 2. Sample Fishbone Diagram

Sample Fishbone Diagram

Figure 2. Sample Fishbone Diagram

Sample Fishbone Diagram

After the project team has reviewed the data, it must decide where opportunities for improvement exist. The first step in this process is to investigate the care process in greater detail. Several techniques are used to accomplish this goal. The simplest is brainstorming, in which key stakeholders offer their suggestions as to which processes are the best candidates for change. Another easy method is flowcharting, in which the group breaks down the process into its components to identify how it is coordinated and how its parts fit together. A fishbone diagram, or cause-and-effect diagram, may aid in exploring and displaying the causes of a particular problem (Figures 2 and 3). It often helps for staff members to consider factors potentially influencing a process that are not obvious, and to help sort out those factors that are external to the clinic and those that are internal. A driver diagram is a visual tool to help understand and prioritize factors that drive desired outcomes, which are called the "primary outcome." Primary drivers are the factors that drive the primary outcome. Secondary drivers are subsets of factors that influence the primary drivers.

Figure 3. Fishbone Diagram: Low Collection Rates of Race and Ethnicity Patient Data

Fishbone Diagram: Low Collection Rates of Race and Ethnicity Patient Data

Used with permission from Kathleen A. Clanon, MD; Low-Income Health Program of Alameda County.

Figure 3. Fishbone Diagram: Low Collection Rates of Race and Ethnicity Patient Data

Fishbone Diagram: Low Collection Rates of Race and Ethnicity Patient Data

Used with permission from Kathleen A. Clanon, MD; Low-Income Health Program of Alameda County.

The driver diagram, which can be generated through discussion with stakeholders, is a particularly effective strategy to identify processes that may be key areas to target for improvement goals that will affect the ultimate outcome. For example, if retention in care is the desired outcome, housing status may be a primary driver that, in turn, is affected by access to factors such as entitlements, mental illness, substance use, or health literacy, which then are secondary drivers that, when addressed through QI activities, will affect the primary driver and ultimate outcome. Framing this larger picture of the system that is being improved may be extremely useful for participants at different levels who may be involved in only one aspect of the QI initiative, as well as for those only involved at the macro level who do not recognize the role of the processes being prioritized for ground-level work. An example of a driver diagram focusing on viral load suppression is shown in Figure 4.

Figure 4. Driver Diagram: Viral Load Suppression

Driver Diagram: Viral Load Suppression

Figure 4. Driver Diagram: Viral Load Suppression

Driver Diagram: Viral Load Suppression

Then, the areas that would be most likely to benefit from improvement are selected for change (see Figure 5) and tested in the Plan-Do-Study-Act (PDSA) cycle (see Figure 6). See "Appendix," below, for examples of QI projects conducted in HIV clinics.

Figure 5. Sample Flow Chart

Sample Flow Chart

Source: U.S. Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau. A Guide to Primary Care of People with HIV/AIDS. Bartlett JG, Cheever LW, Johnson MP, Paauw DS, eds. Rockville, MD: U.S. Department of Health and Human Services; 2004:145.

Figure 5. Sample Flow Chart

Sample Flow Chart

Source: U.S. Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau. A Guide to Primary Care of People with HIV/AIDS. Bartlett JG, Cheever LW, Johnson MP, Paauw DS, eds. Rockville, MD: U.S. Department of Health and Human Services; 2004:145.

Figure 6. Plan-Do-Study-Act Cycle

Plan-Do-Study-Act Cycle

Source: U.S. Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau. A Guide to Primary Care of People with HIV/AIDS. Bartlett JG, Cheever LW, Johnson MP, Paauw DS, eds. Rockville, MD: U.S. Department of Health and Human Services; 2004:145.

Figure 6. Plan-Do-Study-Act Cycle

Plan-Do-Study-Act Cycle

Source: U.S. Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau. A Guide to Primary Care of People with HIV/AIDS. Bartlett JG, Cheever LW, Johnson MP, Paauw DS, eds. Rockville, MD: U.S. Department of Health and Human Services; 2004:145.

Even if evidence-based criteria on how to improve desired outcomes exist, how they are implemented varies according to the local context. Thinking through the "hows" of an intervention - who will do it, when during the care process it will be done, where it will be done - are important questions to ask as the test of the intervention is planned. After a change has been selected, a test of the change can be quickly implemented and evaluated. A limited implementation of the proposed change can be tested - perhaps with just a few subsequent patients, or those attending on the following day, or those seen by a particular clinician. If the small change does not work, another change can be selected and implemented quickly. If the change is feasible and improvement is noted, it can be adopted more widely, before formal remeasurement occurs, and a regular period of remeasurement can be adopted. If the change was not successful, then another one can be chosen and tested. Occasionally, multiple changes may be tested simultaneously or on different days of the week.

Many different approaches to QI exist and can be implemented successfully. However, sometimes just stepping back to refocus on the three basic questions of the model for improvement presented by Langley et al. (see "Suggested Resources," below) can effectively guide QI activities. These are as follows:

  • What do we want to accomplish?
  • How do we know that a change will result in an improvement - in other words what measure will we use to demonstrate whether our improvements worked?
  • What kinds of changes can we test that will result in an improvement?

Establishing Systems to Support QI

The key to sustaining QI in the clinic is development of an infrastructure that supports ongoing QI activities. The central components of this infrastructure include the following:

  • A QI plan with goals and a process to prioritize these goals
  • A work plan that clearly defines steps, sets timeframes for completion, and identifies responsible parties
  • An organizational framework that displays clear lines of accountability for QI in the organization
  • Commitment of senior management staff to support the program, allocate resources, and celebrate its successes
  • Creation of a culture that supports quality in the program and that values the activities of QI as part of the regular work of the clinic (see Table 4)
  • Patient participation, to share experiential knowledge and inform QI program development
  • Establishment of a formal QI committee to oversee quality activities, monitor the quality plan, and evaluate its effectiveness

The regular, ongoing work of the QI committee, supported by the clinic leadership, constitutes the backbone of the infrastructure that supports ongoing QI activities. The committee oversees the dynamic process of planning, implementation, and evaluation that involves the following:

  • Analysis of data from the QI projects
  • Solicitation of feedback from participating staff members and from patients
  • Decision-making based on the information from its analysis

Table 4. Tips for Promoting a Culture of Quality Improvement: Integration of Quality into the Regular Work of the Clinic

  • Educate staff members about QI and provide them with the skills to participate in QI activities.
  • Consistently articulate the values of QI in staff meetings.
  • Display QI data and storyboards (simple statements and visual representations that describe a problem, the evaluation process, the proposed changes, and their implementation, and display the results).
  • Celebrate successes.
  • Provide opportunities for all staff members to participate in QI teams.
  • Reward staff members through performance evaluation for their contributions to the QI program.
  • Participate in activities with peers to discuss QI activities, share data and learn about successful strategies to improve care.

These contribute to sustaining the QI program and its activities in the clinic.

Sustaining Improvements

Sustainability is probably the biggest challenge that clinics face in the field of QI. All too often, improvements do not last after initial projects are completed, because the structure and culture to support QI are not present or are not supported. The challenge of sustainability therefore is twofold: to maintain the successes of QI work and its clinical outcomes, and to maintain the systems of QI and keep the QI program vital. By asking questions about how care systems can be improved and how QI activities are progressing, clinicians play an important role in both catalyzing and supporting QI activities.

Appendix: Case Examples of Quality Management Initiatives

Using QI to Improve ART Management and Virologic Suppression

In one community health center, nearly 10% of patients on antiretroviral therapy (ART) were not virologically suppressed. The clinic had adopted a strategy of developing a specific ART management plan for each patient being treated. Review of the charts of the 45 patients not suppressed showed that only 40% had a plan in the chart. Only 20% had a plan that was executed. Improvement goals were set for each step, to increase from 40% to 90% for documentation of an ART management plan and from 20% to 75% for execution of the plan. Over the course of a 4-month period, clinicians and support staff were educated about the plan and decision-support tools were created, including an algorithm showing key decision points for plan development and execution with corresponding prompts in the clinic database. Visit forms were revised to incorporate data fields specific to the ART plans. Reminders also were created. All changes were implemented through small tests of change with formal remeasurement in 6 months; this showed that 100% of patients had a plan in their charts and that 71% of them had it executed. Continued monitoring showed a dip in performance 4 months later to 88% and 60%, respectively, but with gains restored 3 months subsequently to 100% and 65%, respectively. Vigilance and reaffirmation of the main steps have been keys to maintaining performance. The fields are now being added to the new clinic electronic medical record (EMR) system with automatic prompts based on changes in viral load values.

Another clinic focused QI efforts directly on improving rates of virologic suppression. Data on the HIV viral loads of each specific provider were generated to show comparative rates as a stimulus for improved performance on the part of individual providers. ART regimens were reviewed for their appropriateness, and renewed education about antiretroviral drug combinations and resistance monitoring was introduced. The clinicians reviewed their own patient lists each day. Patients who were not virologically controlled were contacted by phone by the clinician or a nurse. Nurses eventually were assigned directly to the primary care team to facilitate communication with patients and ensure that specific issues raised during phone conversations were addressed during clinic visits. Adherence problems were particularly common, and were addressed through these multiple contacts. Reasons for adherence lapses were identified, which allowed for more effective targeting of service interventions with specific patients, including substance use and mental health service referrals, regimen switching, and targeted adherence interventions. The individual providers improved their patients' rates of virologic suppression from 45% to 62%. Review of suppression rates also showed that a subset of patients remained controlled and did not require quarterly monitoring. A decrease in visit frequency was possible for this group, reducing overutilization of services and unnecessary costs.

Another federally qualified health center with multiple sites struggled with its rates of viral load suppression that ranged from 0% at one small clinic to 47% at another. The medical director was new to the clinic and undertook a thorough investigation of the problem with his team. First, they reviewed the results and matched them with their clinical data and knowledge of the patients. Based on that step, they sent specimens to another lab and found that there had been a major error in the processing of specimens. Once this special cause of their findings was corrected, their rates increased to a range of 50-67%. Then, the team undertook a more thorough investigation of their system and implemented a package of changes based on their analysis and discussions with their patients. Among the improvements the team introduced were the development of a group of adherence educators among their staff, case conferencing together with the patient to discuss the results and identify particular issues and concerns that could then be addressed (managed problem-solving), biweekly team case conferencing, home visits and phone calls as needed in between visits and preparing provider-specific data results to generate additional incentives for providers to intensify their efforts to work with their patients to decrease viral load. Rates have steadily improved up to the 70-80% range in the short run as the clinic team awaits ongoing measurement results to determine whether it can hold its gains and improve further.

Using QI to Eliminate Disparities

The quality committee in another clinic wanted to determine whether the clinic's performance was consistent across all patient groups and arranged to have the clinic's patient data sorted by race, ethnicity, and primary language spoken. This revealed that data about race, ethnicity, and language spoken were not recorded in a high proportion of patient records. The team invited patients from their community advisory board to attend a staff meeting where a fishbone diagram was developed to identify potential causes of the poor collection rates of these patient data. Potential reasons were identified in all categories: equipment, patients, procedures, and staff (see Figure 3). A flow chart was developed to identify the sequential steps of data collection. A training program for intake staff was developed, resulting in an improvement in collection of these data to 85%.

Subsequent analysis showed that only 54% of African-American patients and 68% of Latino patients had suppressed HIV RNA whereas white patients had a suppression rate of 75%. A focus group with Spanish-speaking patients revealed that these patients were not getting enough information about medication and its side effects. The QI team decided to aim for an improvement in virologic suppression rates to 75%. A number of changes were implemented and tested throughout the clinic including the addition of peer adherence counseling, using teach-back by nonphysician staff to facilitate adherence problem-solving, along with medication reconciliation. With these new interventions, virologic suppression rates improved to 71% for African-Americans, 80% for Latinos, and 81% for whites. With ongoing QI activities, suppression rates have subsequently increased for all groups and the gaps between groups has narrowed. Ongoing changes aim to narrow these gaps even further.

Finally, in another clinic, analysis showed that major differences in viral load suppression were noted among patients who were stably housed and those who were not. To tackle their low rates, this agency intensified its relationship with their local housing agency and began to investigate other resources in their community to provide transitional housing services.

Suggested Resources

  • Chassin and Loeb. The Ongoing Quality Improvement Journey: Next Stop, High Reliability. Heatlh Affairs. 2011 30, no. 4:559-568.
  • Langley GJ, Nolan KM, Norman CL, et al. The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. San Francisco: Jossey-Bass; 1996.
  • McGlynn EA, Asch SM. Developing a clinical performance measure. Am J Prev Med. 1998 Apr;14(3 Suppl):14-21.
  • New York State Department of Health AIDS Institute. HIVQUAL Group Learning Guide: Interactive Quality Improvement Exercises for HIV Healthcare Providers . May 2002, revised 2006.
  • Quinn M, et. al. The Relationship Between Perceived Practice Quality and Quality Improvement Activities and Physician Practice Dissatisfaction, Professional Isolation and Work-Life Stress. Med Care 2009;47: 924-928.
  • Scholtes PR, Joiner BL, Streibel BJ. The Team Handbook (3rd Edition). Madison, WI: Oriel; 2003.



General QI Websites


  • Institute for Healthcare Improvement. HIV/AIDS Bureau Collaborations: Improving Care for People Living with HIV/AIDS Disease. Boston: Institute for Healthcare Improvement; 2002.
  • Institute of Medicine. Medicare: A Strategy for Quality Assurance, Volume 1. Washington: National Academies Press; 1990.
  • Institute of Medicine. Crossing the Quality Chasm. Washington: National Academies Press; 2001.
  • Institute of Medicine. Measuring What Matters: Allocation, Planning, and Quality Assessment for the Ryan White CARE Act. Washington: National Academies Press; 2004.
  • New York State Department of Health AIDS Institute. HIVQUAL Group Learning Guide: Interactive Quality Improvement Exercises for HIV Healthcare Providers . May 2002, revised 2006. Accessed December 1, 2013.
  • New York State Department of Health AIDS Institute. HIVQUAL Workbook . September 2006. Accessed December 1, 2013.
  • U.S. Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau. Case Studies in QI in 9 Community Health Centers. Rockville, MD: U.S. Department of Health and Human Services; year of publication unknown.