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Longitudinal survey of clinician behavior change in CKD management

Shaw-Gallagher, Marlene, PA-C; Boyle, Rebecca, PA-C; Zuber, Kim, PA-C


A table that was not part of the article was published on page 42 in the April 2019 issue.

The publisher regrets this error.

Journal of the American Academy of PAs. 32(5):1, May 2019.

Journal of the American Academy of PAs: April 2019 - Volume 32 - Issue 4 - p 39–43
doi: 10.1097/01.JAA.0000554226.79123.75
Original Research

Objective: To assess longitudinal improvement for a simple intervention to teach physician assistants (PAs) and NPs management of patients with diabetes and chronic kidney disease (CKD).

Methods: The original cohort from the Kidneys in a Box quality improvement project was revisited at the 3-year mark and asked about patient statin use, A1C measurement, urine albumin-creatinine ratio (UACR), CKD staging, distribution of over-the-counter (OTC) medication caution lists, and documentation of smoking history.

Results: A statistically significant increase in quality metrics was seen at 3 months postintervention for the original cohort. At the 3-year mark, these improvements were sustained. For UACR and smoking quality metrics, performance increased beyond the gains initially seen at 3 months.

Conclusions: This study demonstrates that a single-intervention quality improvement program can affect sustained improvements in clinical care of patients with diabetes and CKD. The results provide evidence that one-time quality improvement interventions have the power to promote longitudinal practice changes associated with reduced rates of CKD progression and potentially reduced healthcare costs.

Marlene Shaw-Gallagher is an assistant professor in the PA program at the University of Detroit-Mercy in Detroit, Mich., and practices in the Department of Nephrology at the University of Michigan Health System in Ann Arbor, Mich. Rebecca Boyle practices at Stanford (Calif.) Hypertension Center. Kim Zuber is executive director of the American Academy of Nephrology PAs in Oceanside, Calif. The authors disclose that this research was supported by an unrestricted educational grant from the National Kidney Foundation. The authors have disclosed no other potential conflicts of interest, financial or otherwise.

Kidney disease is a worldwide epidemic, affecting more than 850 million people.1 In the United States, more than 30 million patients, or 15% of the population, have chronic kidney disease (CKD).2 Although the cost to patients and their families is significant, the monetary cost to society is even greater, accounting for more than 20% of the entire Medicare budget in 2016.3 Diabetes and hypertension are the two main causes associated with the development of CKD, which is more common in women and adults over age 60 years but can be slowed (not reversed) with proper treatment.3 One in seven US residents will develop stage 3 to 5 CKD during their lifespan and one in three patients with diabetes will develop kidney disease.4,5 Patients often are referred to nephrology after kidney disease is advanced. However, early identification and appropriate management can slow CKD progression and prevent patients from progressing to kidney failure that requires dialysis or transplant.

The American Academy of Nephrology PAs (AANPA), in conjunction with the National Institutes of Health's (NIH's) National Kidney Disease Education Project (NKDEP), developed Kidneys in a Box (KIB), a kidney-specific outreach educational project for PAs and NPs who manage patients with diabetes. Using six parameters identified by NKDEP that have been shown to slow progression of kidney disease in patients with diabetes, PAs and NPs developed practice-specific interventions to address each of the six modifiable parameters:6,7

  • statin use
  • A1C measured within the last 6 months
  • urine albumin-creatinine ratio (UACR) measured within the last year
  • CKD stage documented in chart
  • an over-the-counter (OTC) medication caution list of drugs that patients should avoid to reduce their risk for iatrogenic kidney injury
  • smoking cessation (documentation of smoking history).

The KIB quality improvement project directs PAs and NPs to compare aspects of their practice with national benchmarks, performance guidelines, or other established evidence-based metric or standards and ascertain how well they are doing. Using the tools from KIB, the participants developed an intervention and evaluated their practices against the original benchmarks 3 months after introducing the intervention. Initial evaluations of the interventions from KIB showed statistically significant increases in management for five of the six parameters.7 The sixth parameter, smoking history documentation, showed nonstatistically significant improvement. The improvements were seen across the spectrum of participants for both PAs and NPs and for specialty and primary care practices.

One of the theoretical limitations of quality improvement projects is the potential for loss of initially observed performance improvement as the effects of the initial intervention dissipate over time. Because the long-term goal of KIB was to introduce permanent changes in practice, we returned at 3 years postintervention to determine if the original improvement seen in 2014 was sustained.8

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Institutional review board exemption for this study was obtained from the University of Detroit-Mercy. Full methodology of the original KIB program is detailed in the original publication.7 The 204 PAs and NPs who made up the original 2014-2016 participant cohort were contacted 3 years postintervention via US Postal Service (USPS). Three attempts were made from August 2017 through January 2018 with an envelope containing instructions and a self-addressed stamped envelope for return of data. Email contact, when available, was reserved for reaching participants who had submitted USPS mail responses that contained missing or incomplete chart abstraction.

Participants were asked to abstract charts for their current performance for the same six practice parameters assessed in the original KIB program.7 If the participants were no longer in practice, they were asked to briefly describe their current role (for example, nonclinical employment, caregiving, retirement) without chart abstraction. Identical logistical data were collected from the cohort, as previously, with only a query added about further training in CKD prevention; this query was to confirm that the KIB training was the only intervention used by the cohort over the past 3 years. Data points were compared using single-pooled and double-pooled samples from both the original data (pretest), the 3-month intervention data (post-test), and the 3-year postintervention data (3-year post-test).

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Of the original cohort, 107 PAs and NPs responded, a 52.5% response rate, for 91 chart extractions; 16 PAs or NPs reported being retired or not practicing at this time. Data were subjected to a mixed-model analysis of variance and post-hoc comparisons of means to assess the strength of the relationship between the KIB intervention and changes in practice behavior. Bonferroni correction was performed to account for multiple comparisons on each of the six dependent quality measures (Figure 1). The six quality measures at specified pre-, post-, and 3-year post-test are summarized in Table 1.





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Statin use

Pretest results indicated a mean of 6.31 [CI 95: 5.83, 6.79] patients on a statin, with a 3-month post-test mean of 7.34 [CI 95: 6.90, 7.79], a statistically significant difference (P < .001). The 3-year post mean was 7.43 [CI 95: 6.96, 7.89] and although not statistically significant from the 3-month result, is statistically significant compared with the pretest mean (P = .001) (Figure 2).



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A1C testing

Pretest results indicated a mean of 8.40 [CI 95: 7.91, 8.89] patients with a recent A1C with a 3-month post-test mean of 8.99 [CI 95: 8.63, 9.35], which was statistically significant (P = .001). The 3-year post-test mean was 8.81 [CI 95: 8.39, 9.23], which was not significantly lower than the 3-month post-test but also was not significantly higher than the pretest mean. The post-test improvement over pretest was not maintained for A1C, but rather diminished over the course of 3 years (Figure 2).

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Pretest results indicated a mean of 4.86 [CI 95: 4.13, 5.6] patients with a UACR with a post-test mean of 6.86 [CI 95: 6.17, 7.55], which was a statistically significant difference (P < .001). The 3-year post mean was 6.98 [CI 95: 6.25, 7.7] and, although not statistically significant compared with the 3-month post-test, was statistically significantly higher than the pretest mean (P < .001) (Figure 2).

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CKD staging

Pretest results indicated a mean of 3.29 [CI 95: 2.63, 3.95] patients who had CKD stage documented with a post-test mean of 5.91 [CI 95: 5.26, 6.56], which was statistically significant (P < .001). The 3-year post mean was 6.33 [CI 95: 5.65, 7.02], which was not statistically significantly higher than the 3-month post-test but was statistically significantly higher than the pretest mean (P < .001) (Figure 2).

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OTC medication caution lists

Pretest results indicated a mean of 2.63 [CI 95: 1.83, 3.43] patients given an OTC medication caution list with a post-test mean of 6.72 [CI 95: 6.05, 7.40], a statistically significant difference (P < .001). The 3-year post mean was 5.29 [CI 95: 4.45, 6.13], which was not statistically significant when compared with the 3-month post-test (P = .01) but was statistically significantly higher than the pretest mean (P < .001) (Figure 2).

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Smoking history documentation

Pretest results indicated a mean of 5.33 [CI 95: 4.66, 6] patients with a documented smoking history in the chart, with a post-test mean of 5.64 [CI 95: 4.94, 6.33], which was not statistically significant in the original cohort. The 3-year post mean was 8.69 [CI 95: 8.23, 9.15] and was statistically significantly higher than both the pretest and 3-month post-test (P < .001)(Figure 2).

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KIB was developed to improve screening for kidney disease in patients with diabetes. The program encourages clinicians to use methods developed by the NKDEP to slow the progression of CKD. The original cohort who completed KIB showed statistically significant changes in evaluating and managing patients with diabetes and CKD.7 This 3-year follow-up study was designed to assess the potential to induce longitudinal practice changes in CKD care through a quality improvement project using the six parameters (described earlier) known to slow CKD progression.



At 3 years postintervention, clinicians reviewed their practice via chart survey to see if the initial changes were maintained. In four of the six interventions (statins, A1C, UACR, and CKD staging), the statistically significant post-test improvements were maintained at 3 years with no further interventions. For OTC medication caution lists, the results diminished somewhat over time but remained statistically significant when compared with pretest levels. Although the 3-year post-test did not increase further, improvements observed at 3-month post-test were sustained for 3 years after KIB. In other words, a simple, short intervention made in practices by PAs and NPs continued to show positive results 3 years later.

One of the original parameters, smoking history documentation, had not changed significantly during the original study.7 In an unexpected result, smoking history documentation actually increased at 3 years postintervention and now showed statistically significant results (P < .001). One of the reasons that the original cohort did not show improvement in documenting smoking history may have been an issue with the wording of the question on the original evaluation form, “Does the patient have a smoking history?” For the 3-year post-test, the question was clarified and changed to, “Does the patient have a smoking history documented in the chart?” This may have led to a more accurate assessment of the intervention and the significant increase in reported documentation at the 3-year-post-test mark.

Four interventions maintained statistically significant improvements at both the 3-month post-test and 3-year post-test: statin use, UACR measured within the last year, CKD stage, and OTC medication caution list.

Documentation of CKD stage in patients with diabetes is key to early identification of disease progression. CKD progression can be slowed by monitoring A1C and UACR and educating patients about OTC medications they should use with caution or avoid.2

Short-term quality improvement interventions have been criticized as not powerful enough to effect long-term practice change. The results of this study demonstrate the potential for a single-intervention quality improvement program for PAs and NPs to cause sustained improvements in the clinical care of patients with diabetes and CKD. NKDEP has shown that incorporation of the six quality measures analyzed in our study has the power to slow CKD progression.2 Slowing disease progression not only translates into improved patient outcomes but also has the potential to dramatically reduce healthcare costs, because 20% of the Medicare budget supports patients with CKD and healthcare costs rise as patients' glomerular filtration rate falls.3

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In the absence of survey data from a control group of clinicians who did not participate in the KIB project, we cannot definitively exclude the possibility that the observed changes in practice were not attributable to influences outside the quality improvement intervention, such as self-initiated learning or other continuing medical education (CME) relating to managing patients with diabetes and CKD. To screen for any signal of non-KIB CME participation that may have influenced the sustained changes in practice observed in this study, we asked participants during the 3-year longitudinal follow-up whether they had engaged in CKD-related CME. Because only 7.3% indicated involvement in external CKD learning, the improvements in clinical practice seen at 3-month and 3-year follow-up were felt to be the result of KIB involvement. Excluding participants who did not submit chart abstraction at 3 years, longitudinal follow-up did not appear to significantly affect findings, as using a standard ANOVA to analyze all data available yielded the same pattern of findings. Given the novel introduction of practice improvement-specific CMEs for PAs and NPs at the time of the original KIB enrollment, it is possible that enrollment self-selected for providers highly motivated to make practice improvement. Most respondents were practicing PAs, so further studies within the larger population of CKD providers, including NPs, will help define the applicability of our findings to specific demographic subgroups and identify which practice behaviors are most responsive to quality improvement interventions. Data were diverse, with participation from primary care and specialty clinicians in 30 states. Future studies also might incorporate blinded chart abstraction to avoid participant bias in reporting positive results.

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The KIB intervention showed successful improvements from pretest measures at 3 years after the initial intervention for five of six interventions. This study shows that CKD education for PAs and NPs has the potential to significantly change clinician behavior and increase the use of interventions to slow kidney disease. Furthermore, the study shows that sustained behavioral changes are possible with a short-term quality improvement project.

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1. American Society of Nephrology/ERA-EDTA/International Society of Nephrology. The hidden epidemic: worldwide, over 850 million people suffer from kidney diseases. Accessed December 10, 2018.
2. Centers for Disease Control and Prevention. National chronic kidney disease fact sheet 2017. Accessed December 10, 2018.
3. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, US Renal Data System. 2017 USRDS annual data report: epidemiology of kidney disease in the United States. Bethesda, MD, 2017.
4. Grams ME, Chow EK, Segev DL, Coresh J. Lifetime incidence of CKD stages 3-5 in the United States. Am J Kidney Dis. 2013;62(2):245–252.
5. National Kidney Foundation. CKD facts. Accessed January 8, 2019.
6. National Kidney Foundation. KDOQI clinical practice guideline for diabetes and CKD: 2012 update. Am J Kidney Dis. 2012;60(5):850–886.
7. Thomsen K, Zuber K, Davis J, Thomas G. Improving treatment for patients with chronic kidney disease. JAAPA. 2016;29(11):46–53.
8. Silver SA, McQuillan R, Harel Z, et al How to sustain change and support continuous quality improvement. Clin J Am Soc Nephrol. 2016;11(5):916–924.

CKD; diabetes; longitudinal; intervention; quality improvement; kidney disease

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