515363
editorial2013
JPCXXX10.1177/2150131913515363Journal of Primary Care & Community HealthRohrer
Editorial
What Is Quality Improvement?
Journal of Primary Care & Community Health 2014, Vol 5(1) 2–3 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/2150131913515363 jpc.sagepub.com
James E. Rohrer1
Quality improvement (QI) in medical care and health services has a long history. Practitioners and scholars have debated whether we should focus on whether the services delivered meet professional standards (process measures) or on end results. Ultimately, a valid measure of the quality of the process will be related to good outcomes. And a valid patient outcome measure will be related to guideline adherence. After all, if providers cannot improve a particular outcome then they should not be held accountable for it. In primary care and community health, quality indicators can be classified as biomarkers, health behaviors, or measures of service use. Commonly examined biomarkers include the following: blood glucose, HbA1c, blood pressures, cholesterol levels, body mass index, depression, anxiety, and similar measures relating to common medical conditions. Examples of health behaviors that, in theory, should be influenced by medical and health programs include tobacco use, physical activity, diet, alcohol consumption, and use of illicit drugs. Use of health services also can relate to the quality of services. Service use measures can include screenings, hospital admissions for sentinel events, hospital readmissions, emergency department visits, return visits to ambulatory care providers, referrals to specialists, polypharmacy, and adherence to protocols. Patient satisfaction with care and provider perceptions of quality are relevant but are not direct measures of the quality of care. The above list covers a lot of ground and raises questions about whether the field needs any more quality indicators. Don’t we have enough to work with already? However, health services evolve as new medical technology emerges, so established indicators may need to be tested for their responsiveness to variations in the care process and sometimes new quality indicators may be necessary. Also, our persistent concern with the cost of collecting data pushes us toward measures that can be obtained from medical records, hopefully via automated extraction. If we must survey patients, we try to do so with brief scales, so as to reduce the burden on both patients and analysts and also boost response rates. So, these new, less expensively obtained indicators must be validated.
measures of the care process to clinical outcomes without overtly describing themselves as QI studies, yet such studies attest to the validity of both the process indicators and the outcome indicators. Clearly such studies are vital to the field. When a study correlates a process measure (eg, guideline adherence) to an outcome (eg, improvement in blood pressures), then it has validated adherence to that particular guideline. If the study also shows that adherence to the guideline varies among sites or types of care settings, then it also qualifies as a type C QI study.
Type B Quality Improvement Study A second type of QI study is one that assesses the prevalence of a quality problem. Another way to express this is to say the investigators measure the baseline level of a quality indicator. This is quality assessment, even if the term is not used by the authors. Quality prevalence studies may address biomarkers, patient health behaviors, or service use. Studies of this type can and should identify risk factors associated with the indicator. Risk factors could be patient characteristics or structural factors (eg, being in a patient-centered medical home or receiving care management). Risk factor epidemiology is a standard design for this type of study. Including care settings of different types as independent variables allows for assessing their independent impact on outcomes. When this is done, the prevalence study morphs into what might be described as impact evaluation, which is type C.
Type C Quality Improvement Study A third type of QI study intends to measure variations in quality levels achieved in different care settings. These might be simply observational and could be published in our Original Research section if they have enough cases and appropriate covariates are included. Cross-sectional, retrospective cohort, and case-control designs might be employed. Longitudinal studies are, of course, most convincing. 1
Mayo Clinic, Rochester, MN, USA
Type A Quality Improvement Study Validation of quality indicators is an important type of QI study. Interestingly, many papers are written linking
Corresponding Author: James E. Rohrer, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. Email: [email protected]
Downloaded from jpc.sagepub.com by guest on March 30, 2015
3
Rohrer
Type D Quality Improvement Study The most widely recognized QI study describes the results of a QI intervention. Investigators who are self-consciously attempting to improve patient care may implement a program of improvement that might include baseline assessment, an intervention, and monitoring. Mixed-methods designs might be expected, in which the report includes quantitative patient outcome measures, guideline adherence, patient satisfaction, and staff reactions. We might publish this type of study as a Case Study.
The foregoing discussion enlarges the definition of QI. My intention is to prompt authors to reconceptualize their projects as QI, to use quality improvement as a keyword, and to include recommendations applying their findings for the improvement of medical care and health services. Readers are encouraged to code the articles in this issue of the journal as type A, B, C, and/or D. Perhaps we can, collectively, break down the boundaries now surrounding QI so that a richer set of studies are accepted into the field.
Downloaded from jpc.sagepub.com by guest on March 30, 2015
editorial2013
JPCXXX10.1177/2150131913515363Journal of Primary Care & Community HealthRohrer
Editorial
What Is Quality Improvement?
Journal of Primary Care & Community Health 2014, Vol 5(1) 2–3 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/2150131913515363 jpc.sagepub.com
James E. Rohrer1
Quality improvement (QI) in medical care and health services has a long history. Practitioners and scholars have debated whether we should focus on whether the services delivered meet professional standards (process measures) or on end results. Ultimately, a valid measure of the quality of the process will be related to good outcomes. And a valid patient outcome measure will be related to guideline adherence. After all, if providers cannot improve a particular outcome then they should not be held accountable for it. In primary care and community health, quality indicators can be classified as biomarkers, health behaviors, or measures of service use. Commonly examined biomarkers include the following: blood glucose, HbA1c, blood pressures, cholesterol levels, body mass index, depression, anxiety, and similar measures relating to common medical conditions. Examples of health behaviors that, in theory, should be influenced by medical and health programs include tobacco use, physical activity, diet, alcohol consumption, and use of illicit drugs. Use of health services also can relate to the quality of services. Service use measures can include screenings, hospital admissions for sentinel events, hospital readmissions, emergency department visits, return visits to ambulatory care providers, referrals to specialists, polypharmacy, and adherence to protocols. Patient satisfaction with care and provider perceptions of quality are relevant but are not direct measures of the quality of care. The above list covers a lot of ground and raises questions about whether the field needs any more quality indicators. Don’t we have enough to work with already? However, health services evolve as new medical technology emerges, so established indicators may need to be tested for their responsiveness to variations in the care process and sometimes new quality indicators may be necessary. Also, our persistent concern with the cost of collecting data pushes us toward measures that can be obtained from medical records, hopefully via automated extraction. If we must survey patients, we try to do so with brief scales, so as to reduce the burden on both patients and analysts and also boost response rates. So, these new, less expensively obtained indicators must be validated.
measures of the care process to clinical outcomes without overtly describing themselves as QI studies, yet such studies attest to the validity of both the process indicators and the outcome indicators. Clearly such studies are vital to the field. When a study correlates a process measure (eg, guideline adherence) to an outcome (eg, improvement in blood pressures), then it has validated adherence to that particular guideline. If the study also shows that adherence to the guideline varies among sites or types of care settings, then it also qualifies as a type C QI study.
Type B Quality Improvement Study A second type of QI study is one that assesses the prevalence of a quality problem. Another way to express this is to say the investigators measure the baseline level of a quality indicator. This is quality assessment, even if the term is not used by the authors. Quality prevalence studies may address biomarkers, patient health behaviors, or service use. Studies of this type can and should identify risk factors associated with the indicator. Risk factors could be patient characteristics or structural factors (eg, being in a patient-centered medical home or receiving care management). Risk factor epidemiology is a standard design for this type of study. Including care settings of different types as independent variables allows for assessing their independent impact on outcomes. When this is done, the prevalence study morphs into what might be described as impact evaluation, which is type C.
Type C Quality Improvement Study A third type of QI study intends to measure variations in quality levels achieved in different care settings. These might be simply observational and could be published in our Original Research section if they have enough cases and appropriate covariates are included. Cross-sectional, retrospective cohort, and case-control designs might be employed. Longitudinal studies are, of course, most convincing. 1
Mayo Clinic, Rochester, MN, USA
Type A Quality Improvement Study Validation of quality indicators is an important type of QI study. Interestingly, many papers are written linking
Corresponding Author: James E. Rohrer, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. Email: [email protected]
Downloaded from jpc.sagepub.com by guest on March 30, 2015
3
Rohrer
Type D Quality Improvement Study The most widely recognized QI study describes the results of a QI intervention. Investigators who are self-consciously attempting to improve patient care may implement a program of improvement that might include baseline assessment, an intervention, and monitoring. Mixed-methods designs might be expected, in which the report includes quantitative patient outcome measures, guideline adherence, patient satisfaction, and staff reactions. We might publish this type of study as a Case Study.
The foregoing discussion enlarges the definition of QI. My intention is to prompt authors to reconceptualize their projects as QI, to use quality improvement as a keyword, and to include recommendations applying their findings for the improvement of medical care and health services. Readers are encouraged to code the articles in this issue of the journal as type A, B, C, and/or D. Perhaps we can, collectively, break down the boundaries now surrounding QI so that a richer set of studies are accepted into the field.
Downloaded from jpc.sagepub.com by guest on March 30, 2015
