Article
Implementation of a CKD Checklist for Primary Care Providers Mallika L. Mendu,* Louise I. Schneider,† Ayal A. Aizer,‡ Karandeep Singh,* David E. Leaf,* Thomas H. Lee,†§ and Sushrut S. Waikar*
Abstract Background and objectives CKD is associated with significant morbidity, mortality, and financial burden. Practice guidelines outlining CKD management exist, but there is limited application of these guidelines. Interventions to improve CKD guideline adherence have been limited. This study evaluated a new CKD checklist (a tool outlining management guidelines for CKD) to determine whether implementation in an academic primary care clinic improved adherence to guidelines. Design, setting, participants, & measurements During a 1-year period (August 2012–August 2013), a prospective study was conducted among 13 primary care providers (PCPs), four of whom were assigned to use a CKD checklist incorporated into the electronic medical record during visits with patients with CKD stages 1–4. All providers received education regarding CKD guidelines. The intervention and control groups consisted of 105 and 263 patients, respectively. Adherence to CKD management guidelines was measured. Results A random-effects logistic regression analysis was performed to account for intra-group correlation by PCP assignment and adjusted for age and CKD stage. CKD care improved among patients whose PCPs were assigned to the checklist intervention compared with controls. Patients in the CKD checklist group were more likely than controls to have appropriate annual laboratory testing for albuminuria (odds ratio [OR], 7.9; 95% confidence interval [95% CI], 3.6 to 17.2), phosphate (OR, 3.5; 95% CI, 1.5 to 8.3), and parathyroid hormone (OR, 8.1; 95% CI, 4.8 to 13.7) (P,0.001 in all cases). Patients in the CKD checklist group had higher rates of achieving a hemoglobin A1c target,7% (OR, 2.7; 95% CI, 1.4 to 5.1), use of an angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker (OR, 2.1; 95% CI, 1.0 to 4.2), documentation of avoidance of nonsteroidal anti-inflammatory drugs (OR, 41.7; 95% CI, 17.8 to 100.0), and vaccination for annual influenza (OR, 2.1; 95% CI, 1.1 to 4.0) and pneumococcus (OR, 4.7; 95% CI, 2.6 to 8.6) (P,0.001 in all cases).
*Division of Renal Medicine and † Division of General Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; ‡ Harvard Radiation Oncology Program, Boston, Massachusetts; and §Press Ganey Associates, Inc., Boston, Massachusetts Correspondence: Dr. Mallika L. Mendu, Division of Renal Medicine, Brigham and Women’s Hospital, 75 Francis Street, MRB-4, Boston, MA 02115. Email: [email protected]
Conclusions Implementation of a CKD checklist significantly improved adherence to CKD management guidelines and delivery of CKD care. Clin J Am Soc Nephrol 9: 1526–1535, 2014. doi: 10.2215/CJN.01660214
Introduction CKD affects approximately 13% of adults in the United States and is associated with significant morbidity, mortality, and financial burden (1–3). Optimal CKD care involves diagnosis, slowing progression, treating complications, and renal replacement preparation (4). The Kidney Disease Improving Global Outcomes program established practice guidelines that address the multifaceted nature of CKD care (5). These guidelines include recommendations related to screening, modification of risk factors (such as hypertension, diabetes, and proteinuria), and management of complications (such as cardiovascular disease, anemia, and bone disease). Since CKD practice guidelines were published, investigators have called for guideline utilization to “improve patient outcomes through recognition of CKD, vigilant monitoring, and appropriate interventions.” (6) However, studies have shown that primary care providers (PCPs) have limited knowledge of 1526
Copyright © 2014 by the American Society of Nephrology
these guidelines (7–10). There have been few interventions to improve adherence to CKD guidelines. One potential innovation to improve CKD care is a CKD checklist, a tool designed to promote adherence to established guidelines (11). The implementation of surgical checklists significantly reduced surgical complications and death (12). Checklists have been used in other areas of medicine, such as critical care related to ventilator care and catheter use, resulting in improved outcomes (13,14). Checklists eliminate some barriers associated with guideline implementation, such as a lack of knowledge, and provide a simplified format. We developed and piloted a CKD checklist in a primary care clinic to test its effect on the delivery of optimal CKD care.
Materials and Methods Study Design We conducted a prospective, nonrandomized study involving the implementation of a CKD checklist for www.cjasn.org Vol 9 September, 2014
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patients with CKD stages 1–4 in a primary care clinic. The intervention group included patients with CKD receiving care from one of four PCPs; these providers were selected by the clinic’s medical director because they were not involved in similar ongoing quality improvement projects. The control group included patients with CKD receiving care from the remaining nine PCPs. The nonrandomized study design was formulated on the basis of feasibility considerations, specifically to avoid assigning PCPs already engaged in quality improvement projects with another ongoing project. The CKD checklist was designed primarily on the basis of national (Kidney Disease Outcomes Quality Initiative [KDOQI]) (2) and international (Kidney Disease Improving Global Outcomes and National Institute for Health and Care
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Excellence) (5,15) guidelines supported by level 1–2 evidence, as well as guidelines for smoking cessation, nephrotoxin avoidance, lipid management, and immunizations for which there exists strong, compelling evidence (see Figure 1). The final version was formulated according to feedback from PCPs within the practice regarding ease of use. Education materials regarding CKD management and the checklist were provided to all 13 PCPs in a 30-minute lecture. We entered the CKD checklist into the electronic medical record before each patient’s clinic visit (see Figure 2). The CKD checklist was populated electronically with relevant information (testing already completed that year along with the results) by a study investigator or nursing staff. We sent providers an email reminder regarding
Figure 1. | CKD checklist for primary care providers. ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; CBC, complete blood count; HbA1c, hemoglobin A1c; NSAID, nonsteroidal anti-inflammatory drug.
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Figure 2. | CKD checklist for primary care providers: screenshot of implementation using the electronic medical record. DM, Diabetes Mellitus.
patients with CKD checklists to complete the week of scheduled visits. The CKD checklist was reviewed, notated by the PCP, and maintained as a separate document from the clinic visit note within the medical record. We conducted this study at the Gretchen and Edward Fish Center for Women’s Health, a primary care practice affiliated with Brigham and Women’s Hospital in Boston, Massachusetts. The institutional review board approved the study and waived the need for informed patient consent. Patient Population and Data Sources We analyzed 368 patients (105 in the intervention group and 263 in the control group) during a 1-year time period from August 2012 to August 2013. Inclusion criteria included the presence of CKD stages 1–4, defined as two consecutive eGFRs between 15 and 60 ml/min per 1.73 m 2 or two
consecutive urine tests showing significant proteinuria ($11 on dipstick or urine microalbumin-to-creatinine ratio.30 mg/g) separated by $90 days (2). Exclusion criteria included eGFR,15 ml/min per 1.73 m2 or RRT. We used the Brigham and Women’s Hospital Research Patient Data Registry and electronic medical record to determine adherence to CKD guidelines in both groups. Measured Variables and Outcomes We examined adherence to both process and quality measures by recording BP, medications (including angiotensinconverting enzyme inhibitors [ACE-Is] and angiotensinreceptor blockers [ARBs]), laboratory results, documentation of discussion about avoiding nonsteroidal anti-inflammatory drugs (NSAIDs), and vaccination for influenza and pneumococcus. Additional variables collected include demographic
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characteristics and comorbid conditions. To isolate the effects of the checklist intervention on differences in the delivery of CKD care as opposed to differences across providers unrelated to the intervention, we performed two sensitivity analyses. First, we collected data from the year before (August 1, 2011— July 31, 2012) the checklist intervention to compare guideline adherence pre- and post-intervention. Second, we measured adherence to guidelines distinct from CKD care, including appropriate use of mammography, colonoscopy, abdominal ultrasonography, Papanicolaou smear, and tetanus vaccination (16–20). Statistical Analyses We used a Fisher exact test to compare categorical variables between groups and the Wilcoxon rank-sum test or t test for continuous variables. We compared guideline adherence before and after the intervention using the McNemar test for matched pairs. To adjust for correlation among patients of a given PCP, we used a random-effects logistic regression model with provider used as a random intercept and adjusted for age and CKD stage. We also examined whether sex, race, and an adapted Charlson comorbidity index incorporating hypertension (assigning a score of 1 to hypertension) (21,22) were confounders. A two-sided P value ,0.05 was considered to represent a statistically significant difference. Statistical analyses were performed using SAS software, version 9.3 (SAS Institute, Cary, NC).
Results Clinical Characteristics The two provider groups did not significantly differ with respect to number of clinic sessions, patient volume, physician age, years in practice, and percentage of time dedicated to clinical practice. The providers were all women, had similar training in internal medicine, practiced in the same location, and had access to the same nephrologists. Patients whose PCPs were assigned to the CKD checklist intervention (checklist group) had clinical characteristics similar to those whose PCPs were not (control group) (Table 1). Patients were predominantly women, given that the clinic is a center for women’s health. The checklist group was older, more likely to have a history of malignancy and coronary artery disease, and had a higher serum creatinine concentration and systolic BP than the control group. Patients in the control group were seen more frequently during the study period than was the intervention group (median, 3 visits [interquartile range, 1–4] compared with two visits (interquartile range, 2–4; P=0.01). Patients in the two groups were managed in a similar manner before the study period (i.e., prior to implementation in the checklist group or observation in the control group), with respect to comanagement by nephrology (defined as ongoing care by a nephrologist), CKD listed in the problem list, ACE-I or ARB use, and most laboratory testing (data not shown). Patients in the control group were more likely to have had a complete blood count (CBC; 42.6% versus 29.5%; P=0.02) and calcium (44.9% versus 28.6%; P,0.01) obtained before the study period. Adherence to CKD Management guidelines Table 2 depicts the effect of the CKD checklist on CKDrelated care. Compared with the control group, patients in
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the checklist group had higher rates of adherence to many guidelines, including annual testing of albuminuria, CBC, iron studies, phosphate, parathyroid hormone (PTH), more frequent use of an ACE-I or ARB, higher rates of achievement of hemoglobin A1c#7%, higher rates of vaccination for influenza and pneumococcus, and higher rates of documentation of NSAID avoidance. We found no significant difference in achievement of BP control, LDL cholesterol level#100 mg/dl, or annual calcium testing. New recognition of CKD and referral to nephrology were significantly higher in the checklist group; all patients referred to nephrology met at least one of the criteria noted in the checklist. We conducted a random-effects logistic regression analysis to account for intragroup correlation by PCP assignment and adjusted for age and CKD stage; we found no significant change in our results other than a lack of significance for annual CBC testing (Figure 3). We also found that clinically relevant variables such as sex, race, and Charlson comorbidity index incorporating hypertension were not confounders when added to the univariate model. Additional analysis for effect modification showed that for the outcomes of annual urine microalbumin and annual phosphate testing, patients with later-stage CKD (stages 3–4) derived more benefit from the checklist intervention than patients with early-stage (stages 1–2) CKD. Finally, we examined guideline adherence by PCP to examine whether there were outlier providers within either group, and we found that the providers were homogenous within each group (data not shown). Of the patients in the CKD checklist group, 21 patients did not receive the checklist intervention (the patient met criteria for CKD, a checklist was entered in the medical record, but the PCP did not use the checklist). The most common reasons for not using the CKD checklist were PCP perception that the checklist would not be appropriate because of patient age (n=6) or patient care goals (n=10); a clear reason was not provided for five patients. We performed an as-treated analysis to compare patients who actually received the checklist (n=84) with those who did not receive a checklist (n=284). Patients who received a CKD checklist had higher rates of guideline adherence across all metrics, except for BP target of #140/90 mmHg during the study period. In the as-treated analysis, 26.2% of patients had an ACE-I or ARB started or adjusted during the study period compared with 4.2% of patients who did not receive a CKD checklist (P,0.001); furthermore, 90% of those in the as-treated intervention group with a definitive indication (diabetes and/or proteinuria) for ACE-I/ARB therapy received treatment, compared with 32.1% in the control group (P=0.003). No adverse drug events (hyperkalemia, AKI, allergic reactions) occurred among patients with ACE-I/ARB therapy initiated or adjusted. Sensitivity Analyses Table 2 also shows the results of adherence to healthcare maintenance guidelines not specifically related to CKD care in the checklist and control groups. We determined the number of patients for whom a particular guideline was indicated on the basis of age and clinical history and the number of patients who had the appropriate test or immunization performed. We found no difference between the intervention and control groups in guideline adherence to colonoscopy, mammography, Papanicolaou smear, or abdominal ultrasonography. The only difference
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Table 1. Demographic and clinical characteristics
Characteristics Demographic Women Age (yr) Married College education or above White Comorbid conditions History of malignancy Diabetes Hyperlipidemia Congestive heart failure Coronary artery disease Hypertension CKD stagesa 1–2 CKD stage 3 CKD stage 4 CKD-related management before enrollment Comanaged by nephrology CKD listed in problem list ACE-I or ARB use SBP first visit (mmHg) DBP first visit (mmHg) Hemoglobin A1c checked Hemoglobin A1c,7% Urine MALB/creatinine ratio checked LDL cholesterol checked LDL cholesterol,100 mg/dl CBC checked Iron checked Calcium checked Phosphate checked PTH checked Laboratory values at enrollment Creatinine (mg/dl) Hemoglobin A1c (%) Urine MALB/creatinine ratio (mg/g) LDL cholesterol (mg/dl) Hemoglobin (g/dl) Calcium (mg/dl) Phosphate (mg/dl) PTH (pg/ml)
Control Group (n=263)
Checklist Group (n=105)
P Value
238 (90.5) 66614.0 116 (44.1) 167 (63.5) 181 (68.8)
93 (88.6) 69611.7 57 (54.3) 70 (66.7) 81 (77.0)
0.57 0.05 0.08 0.63 0.13
38 (14.4) 77 (29.2) 122 (46.3) 14 (5.3) 34(12.9) 198 (75.3) 40(15.2) 210 (79.9) 13 (4.9)
25 (23.8) 28 (26.6) 46 (43.8) 10 (9.5) 25 (23.8) 86 (81.9) 11 (10.5) 91 (86.7) 3 (2.9)
0.05 0.70 0.73 0.16 0.01 0.22 0.54 0.54 0.54
45 (17.1) 79 (30.0) 115 (43.7) 130 (120.0–138.0) 70 (63.0–78.0) 58 (22.1) 42 (15.9) 32 (12.2) 42 (16.0) 30 (11.4) 112 (42.6) 22 (8.5) 118 (44.9) 41(15.6) 25 (9.5) 1.10 (1.00–1.26) 6.5 (5.6–6.5) 31.20 (0–111.5) 99.6637.2 12.9 (11.9–13.9) 9.5 (9.20–9.8) 3.4 (3.10–3.7) 49.9 (33.6–70.1)
12 (11.4) 42 (40.0) 45 (42.9) 134 (120.0–148.0) 70 (62.0–78.0) 20 (19.0) 14 (13.3) 14 (13.3) 23 (21.9) 11(10.5) 31 (29.5) 7 (6.7) 30 (28.6) 16 (15.2) 11 (10.5) 1.13 (1.02–1.29) 5.9 (5.5–6.7) 13.1 (0–83.3) 95.8632.0 12.7(11.7–13.6) 9.5 (9.20–9.90) 3.5 (3.20–3.80) 50.2 (38.7–72.95)
0.20 0.09 0.90 0.01 0.68 0.78 0.63 0.73 0.18 0.86 0.02 0.67 ,0.01 .0.99 0.85 0.05 0.77 0.12 0.68 0.16 0.06 0.11 0.89
Values are expressed as number (percentage) of patients, mean6SD, or median (interquartile range). ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blockers; SBP, systolic BP; DBP, diastolic BP; urine MALB/creatinine, urine microalbumin-to-creatinine ratio; CBC, complete blood count; PTH, parathyroid hormone. a Based on most recent eGFR before study enrollment period.
between groups was in the administration of the tetanus vaccine, which was performed more frequently in the control group (48.6% versus 69.2%; P,0.001). Among the 105 patients included in the checklist intervention, 80 were seen by the same PCP in the year before inclusion in the study. We found significantly higher rates of adherence to most guidelines after the checklist intervention compared with the year before, except for achievement of BP target of #140/90 mmHg and nephrology referral (Table 3). This analysis reflects the changes over the study period within the intervention group. Additional adjustment for baseline adherence to guidelines was performed within the random-effects logistic
regression model and made no substantial difference to the findings presented in Figure 3.
Discussion In this intervention trial of a CKD checklist in a primary care practice, we found improvements in the delivery of care to patients managed with a checklist. Implementation of a CKD checklist resulted in improved adherence to various CKD management guidelines that persisted after adjustment for age and CKD stage and after accounting for within-group correlation based on PCP assignment. We conducted sensitivity analysis illustrating that the observed
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Table 2. Adherence to CKD guidelines
Guideline Adherence CKD guidelines, n (%) BP#140/90 mmHg during study period HbA1c#7% during study period Annual urine MALB/creatinine ratio obtained Receiving ACE-I or ARB during study period NSAID avoidance discussed during study period LDL cholesterol#100 mg/dl during study period Annual influenza vaccine given 5-yr pneumococcal vaccine given Annual CBC obtained Annual iron studies obtained Annual calcium obtained Annual phosphate obtained Annual PTH obtained CKD newly recognizeda Patient referred to nephrologyb Non–CKD-related guidelines, n/n (%)c Colonoscopy Mammography Papanicolaou smear Abdominal ultrasonography Tetanus
Control Group (n=263)
Checklist Group (n=105)
P Value
209 (79.5)
84 (80.0)
.0.99
141 (53.6)
81 (77.1)
,0.001
73 (27.8)
77 (73.3)
,0.001
128 (48.7)
71 (67.6)
0.001
17(6.5)
75 (71.4)
,0.001
134 (51.0)
58 (55.2)
0.49
127 (48.3) 73 (27.8) 219 (83.3) 50 (19.0) 242 (92.0) 93 (35.4) 43 (16.4) 2 (0.8) 0(0)
71 (67.6) 69 (65.7) 98 (93.3) 38 (36.2) 102 (97.1) 69 (65.7) 64 (61.0) 43 (41.0) 10 (9.5)
,0.001 ,0.001 0.01 ,0.001 0.10 ,0.001 ,0.001 ,0.001 ,0.001
168/232 (72.4) 167/212 (78.8) 91/111 (82.0) 9/18 (50.0) 182/263 (69.2)
67/102 (65.7) 64/91 (70.3) 26/39 (66.7) 1/6 (16.7) 51/105 (48.6)
0.24 0.14 0.07 0.34 ,0.001
HbA1c, hemoglobin A1c NSAID, nonsteroidal anti-inflammatory drug. a CKD listed in the problem list for the first time over the course of the study period. b Patient newly referred to nephrology during the study period. c Denominator for each test represents population for which testing is indicated.
improvements were probably not due to differences in physician practice patterns but rather were attributable to the intervention. The CKD checklist was designed primarily on the basis of guidelines for which there was strong evidence- and consensus-based support. Anemia and bone disease recommendations have been debated (23,24). Certain recommendations have received more widespread acceptance given the strength of existing evidence, particularly the control of BP, proteinuria, hemoglobin A1c, and the use ACE-Is and ARBs (15). BP reduction has been convincingly shown to stem the progression of CKD (25–27). Increasing evidence suggests that a BP#140/90 mmHg may be an appropriate target (28). There is also strong evidence that proteinuria reduction reduces the risk of CKD progression (29,30). ACE-Is and ARBs reduce proteinuria independently of BP (31,32). Large studies have shown that achieving a hemoglobin A1c level#7% reduces proteinuria and the risk of CKD (33,34). Limited evidence exists for smoking cessation (35), lipid control (36), and the avoidance of nephrotoxic agents (37). However, lipid control and smoking cessation seem prudent in light of the high incidence of cardiovascular mortality. Finally, early immunization in the spectrum of CKD care has been associated with improved outcomes (38).
Despite the publication of CKD practice guidelines, adoption among PCPs and nephrologists has been limited (7–10). A survey involving 301 physicians who were presented a hypothetical with CKD showed that only 47% of nephrologists and 33% of internists could identify five of six laboratory tests indicated by guidelines (7). A study of 11,774 patients with stages 3–4 CKD in a primary care setting found low rates of adherence to many CKD practice guidelines, including annual urine protein (30%), target LDL cholesterol,100 mg/dl (44%), annual PTH (13%), and inappropriate drugs prescribed (26%) (9). Few studies have examined adherence to nephrology referral recommendations have illustrated discrepancies among providers, resulting in late or inappropriate referral (39– 41). In summary, studies have demonstrated that although guidelines have been established, opportunities to improve CKD care remain. Interventions to improve adherence to CKD practice guidelines have been studied in a few settings. Southern California Kaiser Permanente developed an initiative to identify patients with CKD on the basis of KDOQI guidelines and alert PCPs, and found that nephrology visits increased modestly from 20% to 24% (42). The Upstate New York Practice-Based Research Network study examined computer decision-making support based on guidelines
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Figure 3. | Forest plot depicting adjusted effect of CKD checklist on adherence to CKD management guidelines. The random effects logistic regression model accounts for within-group correlation by primary care provider assignment and is adjusted for age and CKD stage (1–4). Odds ratio (OR).1 (to right of solid vertical line) reflects increased adherence in patients assigned to the CKD checklist. Results for avoidance of nonsteroidal anti-inflammatory drugs avoidance cannot be seen in the figure because the OR is 41.7 (95% confidence limit [95% CL], 17.8 to 100), which is beyond the scale of the figure. LCL, lower confidence limit PTH; parathyroid hormone; UCL, upper confidence limit; urine MALB/creat, urine microalbumin-to-creatinine ratio. ORs presented are based on 263 patients in the control group and 105 patients in the checklist group.
in primary care clinics and found that the recognition of CKD and diagnosis of anemia improved substantially (43). These two studies focused on improving recognition of CKD as opposed to addressing comprehensive CKD guidelines. Algorithms have been developed to promote adherence to CKD guidelines (44,45). However, none have been validated, and most are cumbersome to follow. The CKD checklist meets several requirements: (1) incorporation of guidelines for which there is evidence-based support, (2) design targeted toward the appropriate specialty (i.e., the primary care–specific checklist includes nephrology referral guidelines), and (3) a format accessible to clinicians (46). Several points warrant additional discussion. First, it is important to address why the CKD checklist did not affect hypertension control. The most likely reason is that this intervention was not comprehensive enough to address all factors associated with lack of BP control, particularly adherence to antihypertensive agents and dietary factors (47). Although the CKD checklist may improve clinician inertia, the most effective hypertension interventions include education and BP monitoring (48). Second, the lack of significant improvement in annual calcium measurement in the intention-to-treat analysis is probably due to the high rate of adherence before implementation of the checklist (likely reflecting inclusion of serum calcium in
the routine basic metabolic panel). Third, LDL control was not significantly improved in the intention-to-treat analysis, although it was in the as-treated analysis. As with BP, factors such as diet and medication adherence are not addressed with a checklist. Finally, it is important to emphasize that the success of a CKD checklist depends on consideration of provider workflow and strategic implementation. Although we adopted a checklist model, other features, such as automatic entry into the electronic medical record, autopopulation, and weekly reminders, constitute a form of clinical decision support. Before implementation of this study, PCPs were asked about practice patterns and preferences regarding incorporation of the checklist into their workflow, and this was critical to the success of the intervention. There may be providers who are “early adopters” and take the initiative to incorporate the CKD checklist into their workflow; most providers will require system support to facilitate use. This could come in the form of an electronic medical record that identifies patients meeting criteria for CKD and automatically populates a progress note with a CKD checklist, or a medical assistant who helps the provider complete the checklist during an annual visit. Regardless of the approach, it is clear from this study that strategic implementation can lead to the success of a CKD checklist in improving guideline adherence.
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Table 3. Adherence to CKD management guidelines in the intervention group, before and after implementation
Guideline Adherence
Before Intervention n=80
After Intervention n=80
P Value
BP#140/90 mmHg during study period HbA1c#7% during study period Annual urine MALB/creatinine ratio obtained Receiving ACE-I or ARB during study period NSAID avoidance discussed during study period LDL cholesterol#100 mg/dl during study period Annual influenza vaccine given 5-yr pneumococcal vaccine given Annual CBC obtained Annual iron studies obtained Annual calcium obtained Annual phosphate obtained Annual PTH obtained CKD newly recognizeda Patient referred to nephrologyb
53 (66.3)
62 (77.5)
0.05
30 (37.5) 20 (25.0)
62 (77.5) 60 (75.0)
,0.001 ,0.001
45 (56.3)
57(71.3)
,0.001
8 (10.0)
58 (72.5)
,0.001
32 (40.0)
43 (53.8)
,0.001
42 (52.5) 23 (28.8) 62 (77.5) 16 (20.0) 74 (92.5) 16 (20.0) 13 (16.3) 2 (2.3) 4 (0.1)
54 (67.5) 52 (65.0) 76 (95. 0) 31 (38.8) 78 (97.5) 52 (65.0) 49 (61.3) 34 (42.3) 9 (11.3)
,0.001 ,0.001 ,0.001 ,0.001 0.005 ,0.001 ,0.001 ,0.001 0.25
Values are expressed as number (percentage). a CKD listed in the problem list for the first time over the course of the study period. b Patients newly referred to nephrology during the study period.
Potential limitations warrant mention. The major limitation of this study was the potential bias introduced based on PCP agreement to use the CKD checklist (i.e., those who participated may be more motivated to provide appropriate care independent of checklist use). We sought to address this by educating all providers in the practice regarding project goals and evidence regarding CKD management. We also performed sensitivity analyses that showed no differences in rates of adherence to non– CKD-related guidelines and improvements within the intervention group before and after the intervention. One limitation related to NSAID avoidance is the possibility that the observed improvement reflected documentation only, rather than an improvement in care. Another limitation involves the possibility of the Hawthorne effect, in which knowledge of study participation leads to behavior changes affecting the outcome of interest (49,50). Both provider groups were aware of the study, which may mitigate potential bias. Because involvement with other qualityimprovement projects was a selection criterion for control group providers, it is possible that the observed differences resulted from the control group’s focus on other initiatives rather than an effect of the checklist. Finally, although we examined some outcome measures ( such as BP control, LDL control, immunization administration, and NSAID avoidance), other important outcomes (such as control of proteinuria and progression of CKD) require longer-term follow-up, which was beyond the scope of this study. We recognize the importance of pursuing further steps, such as conducting a randomized controlled trial of multiple clinics over the course of several years and measuring outcomes (e.g., proteinuria control, CKD progression, and mortality).
Despite the potential limitations, our study indicates that the implementation of a CKD checklist can significantly improve adherence to various CKD management guidelines and improve the delivery of CKD care. Disclosures None. References 1. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, Van Lente F, Levey AS: Prevalence of chronic kidney disease in the United States. JAMA 298: 2038–2047, 2007 2. National Kidney Foundation: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39[Suppl 1]: S1–S266, 2002 3. United States Renal Data System: USRDS 2010 Annual Data Report. Bethesda, MD, National Institutes of Health, National Institutes of Diabetes and Digestive and Kidney Disease, 2010. Available at: http://www.usrds.org/2010/pdf/v1_00a_intros.PDF. Accessed December 1, 2013 4. Pereira BJ: Optimization of pre-ESRD care: The key to improved dialysis outcomes. Kidney Int 57: 351–365, 2000 5. Stevens PE, Levin A; Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members: Evaluation and management of chronic kidney disease: synopsis of the kidney disease: Improving global outcomes 2012 clinical practice guideline. Ann Intern Med 158: 825–830, 2013 6. Eknoyan G: Meeting the challenges of the new K/DOQI guidelines. Am J Kidney Dis 41[Suppl]: 3–10, 2003 7. Charles RF, Powe NR, Jaar BG, Troll MU, Parekh RS, Boulware LE: Clinical testing patterns and cost implications of variation in the evaluation of CKD among US physicians. Am J Kidney Dis 54: 227–237, 2009 8. Morrow BD, Stewart IJ, Barnes EW, Cotant CL: Chronic kidney disease management in an academic internal medicine clinic. Clin Exp Nephrol 14: 137–143, 2010
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9. Allen AS, Forman JP, Orav EJ, Bates DW, Denker BM, Sequist TD: Primary care management of chronic kidney disease. J Gen Intern Med 26: 386–392, 2011 10. Philipneri MD, Rocca Rey LA, Schnitzler MA, Abbott KC, Brennan DC, Takemoto SK, Buchanan PM, Burroughs TE, Willoughby LM, Lentine KL: Delivery patterns of recommended chronic kidney disease care in clinical practice: Administrative claims-based analysis and systematic literature review. Clin Exp Nephrol 12: 41–52, 2008 11. Gawande A: The checklist: If something so simple can transform intensive care, what else can it do? New Yorker : 86–101, 2007 12. Haynes AB, Weiser TG, Berry WR, Lipsitz SR, Breizat AH, Dellinger EP, Herbosa T, Joseph S, Kibatala PL, Lapitan MC, Merry AF, Moorthy K, Reznick RK, Taylor B, Gawande AA; Safe Surgery Saves Lives Study Group: A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med 360: 491–499, 2009 13. Weiss CH, Persell SD, Wunderink RG, Baker DW: Empiric antibiotic, mechanical ventilation, and central venous catheter duration as potential factors mediating the effect of a checklist prompting intervention on mortality: An exploratory analysis. BMC Health Serv Res 12: 198, 2012 14. Teixeira PG, Inaba K, Dubose J, Melo N, Bass M, Belzberg H, Demetriades D: Measurable outcomes of quality improvement using a daily quality rounds checklist: two-year prospective analysis of sustainability in a surgical intensive care unit. J Trauma Acute Care Surg 75: 717–721, 2013 15. Saweirs WW, Goddard J: What are the best treatments for early chronic kidney disease? A background paper prepared for the UK Consensus Conference on early chronic kidney disease. Nephrol Dial Transplant 22[Suppl 9]: ix31–ix38, 2007 16. Vesco KK, Whitlock EP, Eder M, Lin J, Burda BU, Senger CA, Holmes RS, Fu R, Zuber S. Screening for Cervical Cancer: A Systematic Evidence Review for the U.S. Preventive Services Task Force Agency for Healthcare Research and Quality (US); 2011 May. Report No.: 11-05156-EF-1. 17. Humphrey LL, Helfand M, Chan BK, Woolf SH: Breast cancer screening: A summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med 137: 347–360, 2002 18. Advisory Committee on Immunization Practices: Recommended adult immunization schedule: United States, 2013. Ann Intern Med 158: 191–199, 2013 19. Fleming C, Whitlock EP, Beil TL, Lederle FA: Screening for abdominal aortic aneurysm: A best-evidence systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 142: 203–211, 2005 20. Holden DJ, Jonas DE, Porterfield DS, Reuland D, Harris R: Systematic review: Enhancing the use and quality of colorectal cancer screening. Ann Intern Med 152: 668–676, 2010 21. Jung SY, Rosenzweig M, Linkov F, Brufsky A, Weissfeld JL, Sereika SM: Comorbidity as a mediator of survival disparity between younger and older women diagnosed with metastatic breast cancer. Hypertension 59: 205–211, 2012 22. Charlson ME, Charlson RE, Peterson JC, Marinopoulos SS, Briggs WM, Hollenberg JP: The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients. J Clin Epidemiol 61: 1234–1240, 2008 23. Ingelfinger JR: Through the looking glass: anemia guidelines, vested interests, and distortions. Clin J Am Soc Nephrol 2: 415– 417, 2007 24. Kovesdy CP, Mehrotra R, Kalantar-Zadeh K: Battleground: Chronic kidney disorders mineral and bone disease—calcium obsession, vitamin D, and binder confusion. Clin J Am Soc Nephrol 3: 168–173, 2008 25. Maki DD, Ma JZ, Louis TA, Kasiske BL: Long-term effects of antihypertensive agents on proteinuria and renal function. Arch Intern Med 155: 1073–1080, 1995 26. Peterson JC, Adler S, Burkart JM, Greene T, Hebert LA, Hunsicker LG, King AJ, Klahr S, Massry SG, Seifter JL: Blood pressure control, proteinuria, and the progression of renal disease. The Modification of Diet in Renal Disease Study. Ann Intern Med 123: 754–762, 1995 27. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National
28.
29.
30.
31.
32.
33.
34.
35. 36.
37. 38. 39.
40.
41. 42.
Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee: The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 289: 2560–2572, 2003 Peralta CA, Norris KC, Li S, Chang TI, Tamura MK, Jolly SE, Bakris G, McCullough PA, Shlipak M; KEEP Investigators: Blood pressure components and end-stage renal disease in persons with chronic kidney disease: The Kidney Early Evaluation Program (KEEP). Arch Intern Med 172: 41–47, 2012 de Zeeuw D, Remuzzi G, Parving HH, Keane WF, Zhang Z, Shahinfar S, Snapinn S, Cooper ME, Mitch WE, Brenner BM: Proteinuria, a target for renoprotection in patients with type 2 diabetic nephropathy: Lessons from RENAAL. Kidney Int 65: 2309–2320, 2004 Lea J, Greene T, Hebert L, Lipkowitz M, Massry S, Middleton J, Rostand SG, Miller E, Smith W, Bakris GL: The relationship between magnitude of proteinuria reduction and risk of end-stage renal disease: Results of the African American study of kidney disease and hypertension. Arch Intern Med 165: 947–953, 2005 MacKinnon M, Shurraw S, Akbari A, Knoll GA, Jaffey J, Clark HD: Combination therapy with an angiotensin receptor blocker and an ACE inhibitor in proteinuric renal disease: a systematic review of the efficacy and safety data. Am J Kidney Dis 48: 8–20, 2006 Jafar TH, Schmid CH, Landa M, Giatras I, Toto R, Remuzzi G, Maschio G, Brenner BM, Kamper A, Zucchelli P, Becker G, Himmelmann A, Bannister K, Landais P, Shahinfar S, de Jong PE, de Zeeuw D, Lau J, Levey AS: Angiotensin-converting enzyme inhibitors and progression of nondiabetic renal disease. A metaanalysis of patient-level data. Ann Intern Med 135: 73–87, 2001 UK Prospective Diabetes Study (UKPDS) Group: Intensive bloodglucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 352: 837–853, 1998 Ohkubo Y, Kishikawa H, Araki E, Miyata T, Isami S, Motoyoshi S, Kojima Y, Furuyoshi N, Shichiri M: Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulin-dependent diabetes mellitus: a randomized prospective 6-year study. Diabetes Res Clin Pract 28: 103–117, 1995 Stengel B, Tarver-Carr ME, Powe NR, Eberhardt MS, Brancati FL: Lifestyle factors, obesity and the risk of chronic kidney disease. Epidemiology 14: 479–487, 2003 Baigent C, Landray MJ, Reith C, Emberson J, Wheeler DC, Tomson C, Wanner C, Krane V, Cass A, Craig J, Neal B, Jiang L, Hooi LS, Levin A, Agodoa L, Gaziano M, Kasiske B, Walker R, Massy ZA, Feldt-Rasmussen B, Krairittichai U, Ophascharoensuk V, Fellstro¨m B, Holdaas H, Tesar V, Wiecek A, Grobbee D, de Zeeuw D, Gro¨nhagen-Riska C, Dasgupta T, Lewis D, Herrington W, Mafham M, Majoni W, Wallendszus K, Grimm R, Pedersen T, Tobert J, Armitage J, Baxter A, Bray C, Chen Y, Chen Z, Hill M, Knott C, Parish S, Simpson D, Sleight P, Young A, Collins R; SHARP Investigators: The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): A randomised placebo-controlled trial. Lancet 377: 2181–2192, 2011 Gooch K, Culleton BF, Manns BJ, Zhang J, Alfonso H, Tonelli M, Frank C, Klarenbach S, Hemmelgarn BR: NSAID use and progression of chronic kidney disease. Am J Med 120: e1–e7, 2007 Kausz A, Pahari D: The value of vaccination in chronic kidney disease. Semin Dial 17: 9–11, 2004 Navaneethan SD, Kandula P, Jeevanantham V, Nally JV Jr, Liebman SE: Referral patterns of primary care physicians for chronic kidney disease in general population and geriatric patients. Clin Nephrol 73: 260–267, 2010 Greer RC, Powe NR, Jaar BG, Troll MU, Boulware LE: Effect of primary care physicians’ use of estimated glomerular filtration rate on the timing of their subspecialty referral decisions. BMC Nephrol 12: 1, 2011 Boulware LE, Troll MU, Jaar BG, Myers DI, Powe NR: Identification and referral of patients with progressive CKD: A national study. Am J Kidney Dis 48: 192–204, 2006 Rutkowski M, Mann W, Derose S, Selevan D, Pascual N, Diesto J, Crooks P: Implementing KDOQI CKD definition and staging
Clin J Am Soc Nephrol 9: 1526–1535, September, 2014
43.
44.
45.
46.
47.
guidelines in Southern California Kaiser Permanente. Am J Kidney Dis 53[Suppl 3]: S86–S99, 2009 Fox CH, Swanson A, Kahn LS, Glaser K, Murray BM: Improving chronic kidney disease care in primary care practices: An upstate New York practice-based research network (UNYNET) study. J Am Board Fam Med 21: 522–530, 2008 U.S. Department of Veterans Affairs: VA clinical practice guideline for management of chronic kidney disease in primary care. 2008. Accessed at: http://www.healthquality.va.gov/ guidelines/CD/ckd/ckd_v478.pdf. Date Accessed December 1, 2013 Manley HJ: Disease progression and the application of evidencebased treatment guidelines diagnose it early: A case for screening and appropriate management. J Manag Care Pharm 13 [Suppl D]: S6–S12, 2007 Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, Rubin HR: Why don’t physicians follow clinical practice guidelines? A framework for improvement. JAMA 282: 1458– 1465, 1999 Oliveras A, Schmieder RE: Clinical situations associated with difficult-to-control hypertension. J Hypertens 31[Suppl 1]: S3– S8, 2013
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48. Gallagher H, de Lusignan S, Harris K, Cates C: Qualityimprovement strategies for the management of hypertension in chronic kidney disease in primary care: a systematic review. Br J Gen Pract 60: e258–e265, 2010 49. McCambridge J, Witton J, Elbourne DR: Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects. J Clin Epidemiol Nov: 22, 2013 50. Garrouste-Orgeas M, Soufir L, Tabah A, Schwebel C, Vesin A, Adrie C, Thuong M, Timsit JF; Outcomerea Study Group: A multifaceted program for improving quality of care in intensive care units: IATROREF study. Crit Care Med 40: 468– 476, 2012 Received: February 12, 2014 Accepted: June 5, 2014 Published online ahead of print. Publication date available at www. cjasn.org. See related editorial, “Checklists as Computer Decision Support at the Point of Care: A Step Forward in the Recognition and Treatment of CKD by Primary Care Physicians,” on pages 1505–1506.
Implementation of a CKD Checklist for Primary Care Providers Mallika L. Mendu,* Louise I. Schneider,† Ayal A. Aizer,‡ Karandeep Singh,* David E. Leaf,* Thomas H. Lee,†§ and Sushrut S. Waikar*
Abstract Background and objectives CKD is associated with significant morbidity, mortality, and financial burden. Practice guidelines outlining CKD management exist, but there is limited application of these guidelines. Interventions to improve CKD guideline adherence have been limited. This study evaluated a new CKD checklist (a tool outlining management guidelines for CKD) to determine whether implementation in an academic primary care clinic improved adherence to guidelines. Design, setting, participants, & measurements During a 1-year period (August 2012–August 2013), a prospective study was conducted among 13 primary care providers (PCPs), four of whom were assigned to use a CKD checklist incorporated into the electronic medical record during visits with patients with CKD stages 1–4. All providers received education regarding CKD guidelines. The intervention and control groups consisted of 105 and 263 patients, respectively. Adherence to CKD management guidelines was measured. Results A random-effects logistic regression analysis was performed to account for intra-group correlation by PCP assignment and adjusted for age and CKD stage. CKD care improved among patients whose PCPs were assigned to the checklist intervention compared with controls. Patients in the CKD checklist group were more likely than controls to have appropriate annual laboratory testing for albuminuria (odds ratio [OR], 7.9; 95% confidence interval [95% CI], 3.6 to 17.2), phosphate (OR, 3.5; 95% CI, 1.5 to 8.3), and parathyroid hormone (OR, 8.1; 95% CI, 4.8 to 13.7) (P,0.001 in all cases). Patients in the CKD checklist group had higher rates of achieving a hemoglobin A1c target,7% (OR, 2.7; 95% CI, 1.4 to 5.1), use of an angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker (OR, 2.1; 95% CI, 1.0 to 4.2), documentation of avoidance of nonsteroidal anti-inflammatory drugs (OR, 41.7; 95% CI, 17.8 to 100.0), and vaccination for annual influenza (OR, 2.1; 95% CI, 1.1 to 4.0) and pneumococcus (OR, 4.7; 95% CI, 2.6 to 8.6) (P,0.001 in all cases).
*Division of Renal Medicine and † Division of General Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; ‡ Harvard Radiation Oncology Program, Boston, Massachusetts; and §Press Ganey Associates, Inc., Boston, Massachusetts Correspondence: Dr. Mallika L. Mendu, Division of Renal Medicine, Brigham and Women’s Hospital, 75 Francis Street, MRB-4, Boston, MA 02115. Email: [email protected]
Conclusions Implementation of a CKD checklist significantly improved adherence to CKD management guidelines and delivery of CKD care. Clin J Am Soc Nephrol 9: 1526–1535, 2014. doi: 10.2215/CJN.01660214
Introduction CKD affects approximately 13% of adults in the United States and is associated with significant morbidity, mortality, and financial burden (1–3). Optimal CKD care involves diagnosis, slowing progression, treating complications, and renal replacement preparation (4). The Kidney Disease Improving Global Outcomes program established practice guidelines that address the multifaceted nature of CKD care (5). These guidelines include recommendations related to screening, modification of risk factors (such as hypertension, diabetes, and proteinuria), and management of complications (such as cardiovascular disease, anemia, and bone disease). Since CKD practice guidelines were published, investigators have called for guideline utilization to “improve patient outcomes through recognition of CKD, vigilant monitoring, and appropriate interventions.” (6) However, studies have shown that primary care providers (PCPs) have limited knowledge of 1526
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these guidelines (7–10). There have been few interventions to improve adherence to CKD guidelines. One potential innovation to improve CKD care is a CKD checklist, a tool designed to promote adherence to established guidelines (11). The implementation of surgical checklists significantly reduced surgical complications and death (12). Checklists have been used in other areas of medicine, such as critical care related to ventilator care and catheter use, resulting in improved outcomes (13,14). Checklists eliminate some barriers associated with guideline implementation, such as a lack of knowledge, and provide a simplified format. We developed and piloted a CKD checklist in a primary care clinic to test its effect on the delivery of optimal CKD care.
Materials and Methods Study Design We conducted a prospective, nonrandomized study involving the implementation of a CKD checklist for www.cjasn.org Vol 9 September, 2014
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patients with CKD stages 1–4 in a primary care clinic. The intervention group included patients with CKD receiving care from one of four PCPs; these providers were selected by the clinic’s medical director because they were not involved in similar ongoing quality improvement projects. The control group included patients with CKD receiving care from the remaining nine PCPs. The nonrandomized study design was formulated on the basis of feasibility considerations, specifically to avoid assigning PCPs already engaged in quality improvement projects with another ongoing project. The CKD checklist was designed primarily on the basis of national (Kidney Disease Outcomes Quality Initiative [KDOQI]) (2) and international (Kidney Disease Improving Global Outcomes and National Institute for Health and Care
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Excellence) (5,15) guidelines supported by level 1–2 evidence, as well as guidelines for smoking cessation, nephrotoxin avoidance, lipid management, and immunizations for which there exists strong, compelling evidence (see Figure 1). The final version was formulated according to feedback from PCPs within the practice regarding ease of use. Education materials regarding CKD management and the checklist were provided to all 13 PCPs in a 30-minute lecture. We entered the CKD checklist into the electronic medical record before each patient’s clinic visit (see Figure 2). The CKD checklist was populated electronically with relevant information (testing already completed that year along with the results) by a study investigator or nursing staff. We sent providers an email reminder regarding
Figure 1. | CKD checklist for primary care providers. ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; CBC, complete blood count; HbA1c, hemoglobin A1c; NSAID, nonsteroidal anti-inflammatory drug.
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Figure 2. | CKD checklist for primary care providers: screenshot of implementation using the electronic medical record. DM, Diabetes Mellitus.
patients with CKD checklists to complete the week of scheduled visits. The CKD checklist was reviewed, notated by the PCP, and maintained as a separate document from the clinic visit note within the medical record. We conducted this study at the Gretchen and Edward Fish Center for Women’s Health, a primary care practice affiliated with Brigham and Women’s Hospital in Boston, Massachusetts. The institutional review board approved the study and waived the need for informed patient consent. Patient Population and Data Sources We analyzed 368 patients (105 in the intervention group and 263 in the control group) during a 1-year time period from August 2012 to August 2013. Inclusion criteria included the presence of CKD stages 1–4, defined as two consecutive eGFRs between 15 and 60 ml/min per 1.73 m 2 or two
consecutive urine tests showing significant proteinuria ($11 on dipstick or urine microalbumin-to-creatinine ratio.30 mg/g) separated by $90 days (2). Exclusion criteria included eGFR,15 ml/min per 1.73 m2 or RRT. We used the Brigham and Women’s Hospital Research Patient Data Registry and electronic medical record to determine adherence to CKD guidelines in both groups. Measured Variables and Outcomes We examined adherence to both process and quality measures by recording BP, medications (including angiotensinconverting enzyme inhibitors [ACE-Is] and angiotensinreceptor blockers [ARBs]), laboratory results, documentation of discussion about avoiding nonsteroidal anti-inflammatory drugs (NSAIDs), and vaccination for influenza and pneumococcus. Additional variables collected include demographic
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characteristics and comorbid conditions. To isolate the effects of the checklist intervention on differences in the delivery of CKD care as opposed to differences across providers unrelated to the intervention, we performed two sensitivity analyses. First, we collected data from the year before (August 1, 2011— July 31, 2012) the checklist intervention to compare guideline adherence pre- and post-intervention. Second, we measured adherence to guidelines distinct from CKD care, including appropriate use of mammography, colonoscopy, abdominal ultrasonography, Papanicolaou smear, and tetanus vaccination (16–20). Statistical Analyses We used a Fisher exact test to compare categorical variables between groups and the Wilcoxon rank-sum test or t test for continuous variables. We compared guideline adherence before and after the intervention using the McNemar test for matched pairs. To adjust for correlation among patients of a given PCP, we used a random-effects logistic regression model with provider used as a random intercept and adjusted for age and CKD stage. We also examined whether sex, race, and an adapted Charlson comorbidity index incorporating hypertension (assigning a score of 1 to hypertension) (21,22) were confounders. A two-sided P value ,0.05 was considered to represent a statistically significant difference. Statistical analyses were performed using SAS software, version 9.3 (SAS Institute, Cary, NC).
Results Clinical Characteristics The two provider groups did not significantly differ with respect to number of clinic sessions, patient volume, physician age, years in practice, and percentage of time dedicated to clinical practice. The providers were all women, had similar training in internal medicine, practiced in the same location, and had access to the same nephrologists. Patients whose PCPs were assigned to the CKD checklist intervention (checklist group) had clinical characteristics similar to those whose PCPs were not (control group) (Table 1). Patients were predominantly women, given that the clinic is a center for women’s health. The checklist group was older, more likely to have a history of malignancy and coronary artery disease, and had a higher serum creatinine concentration and systolic BP than the control group. Patients in the control group were seen more frequently during the study period than was the intervention group (median, 3 visits [interquartile range, 1–4] compared with two visits (interquartile range, 2–4; P=0.01). Patients in the two groups were managed in a similar manner before the study period (i.e., prior to implementation in the checklist group or observation in the control group), with respect to comanagement by nephrology (defined as ongoing care by a nephrologist), CKD listed in the problem list, ACE-I or ARB use, and most laboratory testing (data not shown). Patients in the control group were more likely to have had a complete blood count (CBC; 42.6% versus 29.5%; P=0.02) and calcium (44.9% versus 28.6%; P,0.01) obtained before the study period. Adherence to CKD Management guidelines Table 2 depicts the effect of the CKD checklist on CKDrelated care. Compared with the control group, patients in
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the checklist group had higher rates of adherence to many guidelines, including annual testing of albuminuria, CBC, iron studies, phosphate, parathyroid hormone (PTH), more frequent use of an ACE-I or ARB, higher rates of achievement of hemoglobin A1c#7%, higher rates of vaccination for influenza and pneumococcus, and higher rates of documentation of NSAID avoidance. We found no significant difference in achievement of BP control, LDL cholesterol level#100 mg/dl, or annual calcium testing. New recognition of CKD and referral to nephrology were significantly higher in the checklist group; all patients referred to nephrology met at least one of the criteria noted in the checklist. We conducted a random-effects logistic regression analysis to account for intragroup correlation by PCP assignment and adjusted for age and CKD stage; we found no significant change in our results other than a lack of significance for annual CBC testing (Figure 3). We also found that clinically relevant variables such as sex, race, and Charlson comorbidity index incorporating hypertension were not confounders when added to the univariate model. Additional analysis for effect modification showed that for the outcomes of annual urine microalbumin and annual phosphate testing, patients with later-stage CKD (stages 3–4) derived more benefit from the checklist intervention than patients with early-stage (stages 1–2) CKD. Finally, we examined guideline adherence by PCP to examine whether there were outlier providers within either group, and we found that the providers were homogenous within each group (data not shown). Of the patients in the CKD checklist group, 21 patients did not receive the checklist intervention (the patient met criteria for CKD, a checklist was entered in the medical record, but the PCP did not use the checklist). The most common reasons for not using the CKD checklist were PCP perception that the checklist would not be appropriate because of patient age (n=6) or patient care goals (n=10); a clear reason was not provided for five patients. We performed an as-treated analysis to compare patients who actually received the checklist (n=84) with those who did not receive a checklist (n=284). Patients who received a CKD checklist had higher rates of guideline adherence across all metrics, except for BP target of #140/90 mmHg during the study period. In the as-treated analysis, 26.2% of patients had an ACE-I or ARB started or adjusted during the study period compared with 4.2% of patients who did not receive a CKD checklist (P,0.001); furthermore, 90% of those in the as-treated intervention group with a definitive indication (diabetes and/or proteinuria) for ACE-I/ARB therapy received treatment, compared with 32.1% in the control group (P=0.003). No adverse drug events (hyperkalemia, AKI, allergic reactions) occurred among patients with ACE-I/ARB therapy initiated or adjusted. Sensitivity Analyses Table 2 also shows the results of adherence to healthcare maintenance guidelines not specifically related to CKD care in the checklist and control groups. We determined the number of patients for whom a particular guideline was indicated on the basis of age and clinical history and the number of patients who had the appropriate test or immunization performed. We found no difference between the intervention and control groups in guideline adherence to colonoscopy, mammography, Papanicolaou smear, or abdominal ultrasonography. The only difference
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Table 1. Demographic and clinical characteristics
Characteristics Demographic Women Age (yr) Married College education or above White Comorbid conditions History of malignancy Diabetes Hyperlipidemia Congestive heart failure Coronary artery disease Hypertension CKD stagesa 1–2 CKD stage 3 CKD stage 4 CKD-related management before enrollment Comanaged by nephrology CKD listed in problem list ACE-I or ARB use SBP first visit (mmHg) DBP first visit (mmHg) Hemoglobin A1c checked Hemoglobin A1c,7% Urine MALB/creatinine ratio checked LDL cholesterol checked LDL cholesterol,100 mg/dl CBC checked Iron checked Calcium checked Phosphate checked PTH checked Laboratory values at enrollment Creatinine (mg/dl) Hemoglobin A1c (%) Urine MALB/creatinine ratio (mg/g) LDL cholesterol (mg/dl) Hemoglobin (g/dl) Calcium (mg/dl) Phosphate (mg/dl) PTH (pg/ml)
Control Group (n=263)
Checklist Group (n=105)
P Value
238 (90.5) 66614.0 116 (44.1) 167 (63.5) 181 (68.8)
93 (88.6) 69611.7 57 (54.3) 70 (66.7) 81 (77.0)
0.57 0.05 0.08 0.63 0.13
38 (14.4) 77 (29.2) 122 (46.3) 14 (5.3) 34(12.9) 198 (75.3) 40(15.2) 210 (79.9) 13 (4.9)
25 (23.8) 28 (26.6) 46 (43.8) 10 (9.5) 25 (23.8) 86 (81.9) 11 (10.5) 91 (86.7) 3 (2.9)
0.05 0.70 0.73 0.16 0.01 0.22 0.54 0.54 0.54
45 (17.1) 79 (30.0) 115 (43.7) 130 (120.0–138.0) 70 (63.0–78.0) 58 (22.1) 42 (15.9) 32 (12.2) 42 (16.0) 30 (11.4) 112 (42.6) 22 (8.5) 118 (44.9) 41(15.6) 25 (9.5) 1.10 (1.00–1.26) 6.5 (5.6–6.5) 31.20 (0–111.5) 99.6637.2 12.9 (11.9–13.9) 9.5 (9.20–9.8) 3.4 (3.10–3.7) 49.9 (33.6–70.1)
12 (11.4) 42 (40.0) 45 (42.9) 134 (120.0–148.0) 70 (62.0–78.0) 20 (19.0) 14 (13.3) 14 (13.3) 23 (21.9) 11(10.5) 31 (29.5) 7 (6.7) 30 (28.6) 16 (15.2) 11 (10.5) 1.13 (1.02–1.29) 5.9 (5.5–6.7) 13.1 (0–83.3) 95.8632.0 12.7(11.7–13.6) 9.5 (9.20–9.90) 3.5 (3.20–3.80) 50.2 (38.7–72.95)
0.20 0.09 0.90 0.01 0.68 0.78 0.63 0.73 0.18 0.86 0.02 0.67 ,0.01 .0.99 0.85 0.05 0.77 0.12 0.68 0.16 0.06 0.11 0.89
Values are expressed as number (percentage) of patients, mean6SD, or median (interquartile range). ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blockers; SBP, systolic BP; DBP, diastolic BP; urine MALB/creatinine, urine microalbumin-to-creatinine ratio; CBC, complete blood count; PTH, parathyroid hormone. a Based on most recent eGFR before study enrollment period.
between groups was in the administration of the tetanus vaccine, which was performed more frequently in the control group (48.6% versus 69.2%; P,0.001). Among the 105 patients included in the checklist intervention, 80 were seen by the same PCP in the year before inclusion in the study. We found significantly higher rates of adherence to most guidelines after the checklist intervention compared with the year before, except for achievement of BP target of #140/90 mmHg and nephrology referral (Table 3). This analysis reflects the changes over the study period within the intervention group. Additional adjustment for baseline adherence to guidelines was performed within the random-effects logistic
regression model and made no substantial difference to the findings presented in Figure 3.
Discussion In this intervention trial of a CKD checklist in a primary care practice, we found improvements in the delivery of care to patients managed with a checklist. Implementation of a CKD checklist resulted in improved adherence to various CKD management guidelines that persisted after adjustment for age and CKD stage and after accounting for within-group correlation based on PCP assignment. We conducted sensitivity analysis illustrating that the observed
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Table 2. Adherence to CKD guidelines
Guideline Adherence CKD guidelines, n (%) BP#140/90 mmHg during study period HbA1c#7% during study period Annual urine MALB/creatinine ratio obtained Receiving ACE-I or ARB during study period NSAID avoidance discussed during study period LDL cholesterol#100 mg/dl during study period Annual influenza vaccine given 5-yr pneumococcal vaccine given Annual CBC obtained Annual iron studies obtained Annual calcium obtained Annual phosphate obtained Annual PTH obtained CKD newly recognizeda Patient referred to nephrologyb Non–CKD-related guidelines, n/n (%)c Colonoscopy Mammography Papanicolaou smear Abdominal ultrasonography Tetanus
Control Group (n=263)
Checklist Group (n=105)
P Value
209 (79.5)
84 (80.0)
.0.99
141 (53.6)
81 (77.1)
,0.001
73 (27.8)
77 (73.3)
,0.001
128 (48.7)
71 (67.6)
0.001
17(6.5)
75 (71.4)
,0.001
134 (51.0)
58 (55.2)
0.49
127 (48.3) 73 (27.8) 219 (83.3) 50 (19.0) 242 (92.0) 93 (35.4) 43 (16.4) 2 (0.8) 0(0)
71 (67.6) 69 (65.7) 98 (93.3) 38 (36.2) 102 (97.1) 69 (65.7) 64 (61.0) 43 (41.0) 10 (9.5)
,0.001 ,0.001 0.01 ,0.001 0.10 ,0.001 ,0.001 ,0.001 ,0.001
168/232 (72.4) 167/212 (78.8) 91/111 (82.0) 9/18 (50.0) 182/263 (69.2)
67/102 (65.7) 64/91 (70.3) 26/39 (66.7) 1/6 (16.7) 51/105 (48.6)
0.24 0.14 0.07 0.34 ,0.001
HbA1c, hemoglobin A1c NSAID, nonsteroidal anti-inflammatory drug. a CKD listed in the problem list for the first time over the course of the study period. b Patient newly referred to nephrology during the study period. c Denominator for each test represents population for which testing is indicated.
improvements were probably not due to differences in physician practice patterns but rather were attributable to the intervention. The CKD checklist was designed primarily on the basis of guidelines for which there was strong evidence- and consensus-based support. Anemia and bone disease recommendations have been debated (23,24). Certain recommendations have received more widespread acceptance given the strength of existing evidence, particularly the control of BP, proteinuria, hemoglobin A1c, and the use ACE-Is and ARBs (15). BP reduction has been convincingly shown to stem the progression of CKD (25–27). Increasing evidence suggests that a BP#140/90 mmHg may be an appropriate target (28). There is also strong evidence that proteinuria reduction reduces the risk of CKD progression (29,30). ACE-Is and ARBs reduce proteinuria independently of BP (31,32). Large studies have shown that achieving a hemoglobin A1c level#7% reduces proteinuria and the risk of CKD (33,34). Limited evidence exists for smoking cessation (35), lipid control (36), and the avoidance of nephrotoxic agents (37). However, lipid control and smoking cessation seem prudent in light of the high incidence of cardiovascular mortality. Finally, early immunization in the spectrum of CKD care has been associated with improved outcomes (38).
Despite the publication of CKD practice guidelines, adoption among PCPs and nephrologists has been limited (7–10). A survey involving 301 physicians who were presented a hypothetical with CKD showed that only 47% of nephrologists and 33% of internists could identify five of six laboratory tests indicated by guidelines (7). A study of 11,774 patients with stages 3–4 CKD in a primary care setting found low rates of adherence to many CKD practice guidelines, including annual urine protein (30%), target LDL cholesterol,100 mg/dl (44%), annual PTH (13%), and inappropriate drugs prescribed (26%) (9). Few studies have examined adherence to nephrology referral recommendations have illustrated discrepancies among providers, resulting in late or inappropriate referral (39– 41). In summary, studies have demonstrated that although guidelines have been established, opportunities to improve CKD care remain. Interventions to improve adherence to CKD practice guidelines have been studied in a few settings. Southern California Kaiser Permanente developed an initiative to identify patients with CKD on the basis of KDOQI guidelines and alert PCPs, and found that nephrology visits increased modestly from 20% to 24% (42). The Upstate New York Practice-Based Research Network study examined computer decision-making support based on guidelines
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Figure 3. | Forest plot depicting adjusted effect of CKD checklist on adherence to CKD management guidelines. The random effects logistic regression model accounts for within-group correlation by primary care provider assignment and is adjusted for age and CKD stage (1–4). Odds ratio (OR).1 (to right of solid vertical line) reflects increased adherence in patients assigned to the CKD checklist. Results for avoidance of nonsteroidal anti-inflammatory drugs avoidance cannot be seen in the figure because the OR is 41.7 (95% confidence limit [95% CL], 17.8 to 100), which is beyond the scale of the figure. LCL, lower confidence limit PTH; parathyroid hormone; UCL, upper confidence limit; urine MALB/creat, urine microalbumin-to-creatinine ratio. ORs presented are based on 263 patients in the control group and 105 patients in the checklist group.
in primary care clinics and found that the recognition of CKD and diagnosis of anemia improved substantially (43). These two studies focused on improving recognition of CKD as opposed to addressing comprehensive CKD guidelines. Algorithms have been developed to promote adherence to CKD guidelines (44,45). However, none have been validated, and most are cumbersome to follow. The CKD checklist meets several requirements: (1) incorporation of guidelines for which there is evidence-based support, (2) design targeted toward the appropriate specialty (i.e., the primary care–specific checklist includes nephrology referral guidelines), and (3) a format accessible to clinicians (46). Several points warrant additional discussion. First, it is important to address why the CKD checklist did not affect hypertension control. The most likely reason is that this intervention was not comprehensive enough to address all factors associated with lack of BP control, particularly adherence to antihypertensive agents and dietary factors (47). Although the CKD checklist may improve clinician inertia, the most effective hypertension interventions include education and BP monitoring (48). Second, the lack of significant improvement in annual calcium measurement in the intention-to-treat analysis is probably due to the high rate of adherence before implementation of the checklist (likely reflecting inclusion of serum calcium in
the routine basic metabolic panel). Third, LDL control was not significantly improved in the intention-to-treat analysis, although it was in the as-treated analysis. As with BP, factors such as diet and medication adherence are not addressed with a checklist. Finally, it is important to emphasize that the success of a CKD checklist depends on consideration of provider workflow and strategic implementation. Although we adopted a checklist model, other features, such as automatic entry into the electronic medical record, autopopulation, and weekly reminders, constitute a form of clinical decision support. Before implementation of this study, PCPs were asked about practice patterns and preferences regarding incorporation of the checklist into their workflow, and this was critical to the success of the intervention. There may be providers who are “early adopters” and take the initiative to incorporate the CKD checklist into their workflow; most providers will require system support to facilitate use. This could come in the form of an electronic medical record that identifies patients meeting criteria for CKD and automatically populates a progress note with a CKD checklist, or a medical assistant who helps the provider complete the checklist during an annual visit. Regardless of the approach, it is clear from this study that strategic implementation can lead to the success of a CKD checklist in improving guideline adherence.
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Table 3. Adherence to CKD management guidelines in the intervention group, before and after implementation
Guideline Adherence
Before Intervention n=80
After Intervention n=80
P Value
BP#140/90 mmHg during study period HbA1c#7% during study period Annual urine MALB/creatinine ratio obtained Receiving ACE-I or ARB during study period NSAID avoidance discussed during study period LDL cholesterol#100 mg/dl during study period Annual influenza vaccine given 5-yr pneumococcal vaccine given Annual CBC obtained Annual iron studies obtained Annual calcium obtained Annual phosphate obtained Annual PTH obtained CKD newly recognizeda Patient referred to nephrologyb
53 (66.3)
62 (77.5)
0.05
30 (37.5) 20 (25.0)
62 (77.5) 60 (75.0)
,0.001 ,0.001
45 (56.3)
57(71.3)
,0.001
8 (10.0)
58 (72.5)
,0.001
32 (40.0)
43 (53.8)
,0.001
42 (52.5) 23 (28.8) 62 (77.5) 16 (20.0) 74 (92.5) 16 (20.0) 13 (16.3) 2 (2.3) 4 (0.1)
54 (67.5) 52 (65.0) 76 (95. 0) 31 (38.8) 78 (97.5) 52 (65.0) 49 (61.3) 34 (42.3) 9 (11.3)
,0.001 ,0.001 ,0.001 ,0.001 0.005 ,0.001 ,0.001 ,0.001 0.25
Values are expressed as number (percentage). a CKD listed in the problem list for the first time over the course of the study period. b Patients newly referred to nephrology during the study period.
Potential limitations warrant mention. The major limitation of this study was the potential bias introduced based on PCP agreement to use the CKD checklist (i.e., those who participated may be more motivated to provide appropriate care independent of checklist use). We sought to address this by educating all providers in the practice regarding project goals and evidence regarding CKD management. We also performed sensitivity analyses that showed no differences in rates of adherence to non– CKD-related guidelines and improvements within the intervention group before and after the intervention. One limitation related to NSAID avoidance is the possibility that the observed improvement reflected documentation only, rather than an improvement in care. Another limitation involves the possibility of the Hawthorne effect, in which knowledge of study participation leads to behavior changes affecting the outcome of interest (49,50). Both provider groups were aware of the study, which may mitigate potential bias. Because involvement with other qualityimprovement projects was a selection criterion for control group providers, it is possible that the observed differences resulted from the control group’s focus on other initiatives rather than an effect of the checklist. Finally, although we examined some outcome measures ( such as BP control, LDL control, immunization administration, and NSAID avoidance), other important outcomes (such as control of proteinuria and progression of CKD) require longer-term follow-up, which was beyond the scope of this study. We recognize the importance of pursuing further steps, such as conducting a randomized controlled trial of multiple clinics over the course of several years and measuring outcomes (e.g., proteinuria control, CKD progression, and mortality).
Despite the potential limitations, our study indicates that the implementation of a CKD checklist can significantly improve adherence to various CKD management guidelines and improve the delivery of CKD care. Disclosures None. References 1. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, Van Lente F, Levey AS: Prevalence of chronic kidney disease in the United States. JAMA 298: 2038–2047, 2007 2. National Kidney Foundation: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39[Suppl 1]: S1–S266, 2002 3. United States Renal Data System: USRDS 2010 Annual Data Report. Bethesda, MD, National Institutes of Health, National Institutes of Diabetes and Digestive and Kidney Disease, 2010. Available at: http://www.usrds.org/2010/pdf/v1_00a_intros.PDF. Accessed December 1, 2013 4. Pereira BJ: Optimization of pre-ESRD care: The key to improved dialysis outcomes. Kidney Int 57: 351–365, 2000 5. Stevens PE, Levin A; Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members: Evaluation and management of chronic kidney disease: synopsis of the kidney disease: Improving global outcomes 2012 clinical practice guideline. Ann Intern Med 158: 825–830, 2013 6. Eknoyan G: Meeting the challenges of the new K/DOQI guidelines. Am J Kidney Dis 41[Suppl]: 3–10, 2003 7. Charles RF, Powe NR, Jaar BG, Troll MU, Parekh RS, Boulware LE: Clinical testing patterns and cost implications of variation in the evaluation of CKD among US physicians. Am J Kidney Dis 54: 227–237, 2009 8. Morrow BD, Stewart IJ, Barnes EW, Cotant CL: Chronic kidney disease management in an academic internal medicine clinic. Clin Exp Nephrol 14: 137–143, 2010
1534
Clinical Journal of the American Society of Nephrology
9. Allen AS, Forman JP, Orav EJ, Bates DW, Denker BM, Sequist TD: Primary care management of chronic kidney disease. J Gen Intern Med 26: 386–392, 2011 10. Philipneri MD, Rocca Rey LA, Schnitzler MA, Abbott KC, Brennan DC, Takemoto SK, Buchanan PM, Burroughs TE, Willoughby LM, Lentine KL: Delivery patterns of recommended chronic kidney disease care in clinical practice: Administrative claims-based analysis and systematic literature review. Clin Exp Nephrol 12: 41–52, 2008 11. Gawande A: The checklist: If something so simple can transform intensive care, what else can it do? New Yorker : 86–101, 2007 12. Haynes AB, Weiser TG, Berry WR, Lipsitz SR, Breizat AH, Dellinger EP, Herbosa T, Joseph S, Kibatala PL, Lapitan MC, Merry AF, Moorthy K, Reznick RK, Taylor B, Gawande AA; Safe Surgery Saves Lives Study Group: A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med 360: 491–499, 2009 13. Weiss CH, Persell SD, Wunderink RG, Baker DW: Empiric antibiotic, mechanical ventilation, and central venous catheter duration as potential factors mediating the effect of a checklist prompting intervention on mortality: An exploratory analysis. BMC Health Serv Res 12: 198, 2012 14. Teixeira PG, Inaba K, Dubose J, Melo N, Bass M, Belzberg H, Demetriades D: Measurable outcomes of quality improvement using a daily quality rounds checklist: two-year prospective analysis of sustainability in a surgical intensive care unit. J Trauma Acute Care Surg 75: 717–721, 2013 15. Saweirs WW, Goddard J: What are the best treatments for early chronic kidney disease? A background paper prepared for the UK Consensus Conference on early chronic kidney disease. Nephrol Dial Transplant 22[Suppl 9]: ix31–ix38, 2007 16. Vesco KK, Whitlock EP, Eder M, Lin J, Burda BU, Senger CA, Holmes RS, Fu R, Zuber S. Screening for Cervical Cancer: A Systematic Evidence Review for the U.S. Preventive Services Task Force Agency for Healthcare Research and Quality (US); 2011 May. Report No.: 11-05156-EF-1. 17. Humphrey LL, Helfand M, Chan BK, Woolf SH: Breast cancer screening: A summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med 137: 347–360, 2002 18. Advisory Committee on Immunization Practices: Recommended adult immunization schedule: United States, 2013. Ann Intern Med 158: 191–199, 2013 19. Fleming C, Whitlock EP, Beil TL, Lederle FA: Screening for abdominal aortic aneurysm: A best-evidence systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 142: 203–211, 2005 20. Holden DJ, Jonas DE, Porterfield DS, Reuland D, Harris R: Systematic review: Enhancing the use and quality of colorectal cancer screening. Ann Intern Med 152: 668–676, 2010 21. Jung SY, Rosenzweig M, Linkov F, Brufsky A, Weissfeld JL, Sereika SM: Comorbidity as a mediator of survival disparity between younger and older women diagnosed with metastatic breast cancer. Hypertension 59: 205–211, 2012 22. Charlson ME, Charlson RE, Peterson JC, Marinopoulos SS, Briggs WM, Hollenberg JP: The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients. J Clin Epidemiol 61: 1234–1240, 2008 23. Ingelfinger JR: Through the looking glass: anemia guidelines, vested interests, and distortions. Clin J Am Soc Nephrol 2: 415– 417, 2007 24. Kovesdy CP, Mehrotra R, Kalantar-Zadeh K: Battleground: Chronic kidney disorders mineral and bone disease—calcium obsession, vitamin D, and binder confusion. Clin J Am Soc Nephrol 3: 168–173, 2008 25. Maki DD, Ma JZ, Louis TA, Kasiske BL: Long-term effects of antihypertensive agents on proteinuria and renal function. Arch Intern Med 155: 1073–1080, 1995 26. Peterson JC, Adler S, Burkart JM, Greene T, Hebert LA, Hunsicker LG, King AJ, Klahr S, Massry SG, Seifter JL: Blood pressure control, proteinuria, and the progression of renal disease. The Modification of Diet in Renal Disease Study. Ann Intern Med 123: 754–762, 1995 27. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National
28.
29.
30.
31.
32.
33.
34.
35. 36.
37. 38. 39.
40.
41. 42.
Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee: The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 289: 2560–2572, 2003 Peralta CA, Norris KC, Li S, Chang TI, Tamura MK, Jolly SE, Bakris G, McCullough PA, Shlipak M; KEEP Investigators: Blood pressure components and end-stage renal disease in persons with chronic kidney disease: The Kidney Early Evaluation Program (KEEP). Arch Intern Med 172: 41–47, 2012 de Zeeuw D, Remuzzi G, Parving HH, Keane WF, Zhang Z, Shahinfar S, Snapinn S, Cooper ME, Mitch WE, Brenner BM: Proteinuria, a target for renoprotection in patients with type 2 diabetic nephropathy: Lessons from RENAAL. Kidney Int 65: 2309–2320, 2004 Lea J, Greene T, Hebert L, Lipkowitz M, Massry S, Middleton J, Rostand SG, Miller E, Smith W, Bakris GL: The relationship between magnitude of proteinuria reduction and risk of end-stage renal disease: Results of the African American study of kidney disease and hypertension. Arch Intern Med 165: 947–953, 2005 MacKinnon M, Shurraw S, Akbari A, Knoll GA, Jaffey J, Clark HD: Combination therapy with an angiotensin receptor blocker and an ACE inhibitor in proteinuric renal disease: a systematic review of the efficacy and safety data. Am J Kidney Dis 48: 8–20, 2006 Jafar TH, Schmid CH, Landa M, Giatras I, Toto R, Remuzzi G, Maschio G, Brenner BM, Kamper A, Zucchelli P, Becker G, Himmelmann A, Bannister K, Landais P, Shahinfar S, de Jong PE, de Zeeuw D, Lau J, Levey AS: Angiotensin-converting enzyme inhibitors and progression of nondiabetic renal disease. A metaanalysis of patient-level data. Ann Intern Med 135: 73–87, 2001 UK Prospective Diabetes Study (UKPDS) Group: Intensive bloodglucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 352: 837–853, 1998 Ohkubo Y, Kishikawa H, Araki E, Miyata T, Isami S, Motoyoshi S, Kojima Y, Furuyoshi N, Shichiri M: Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulin-dependent diabetes mellitus: a randomized prospective 6-year study. Diabetes Res Clin Pract 28: 103–117, 1995 Stengel B, Tarver-Carr ME, Powe NR, Eberhardt MS, Brancati FL: Lifestyle factors, obesity and the risk of chronic kidney disease. Epidemiology 14: 479–487, 2003 Baigent C, Landray MJ, Reith C, Emberson J, Wheeler DC, Tomson C, Wanner C, Krane V, Cass A, Craig J, Neal B, Jiang L, Hooi LS, Levin A, Agodoa L, Gaziano M, Kasiske B, Walker R, Massy ZA, Feldt-Rasmussen B, Krairittichai U, Ophascharoensuk V, Fellstro¨m B, Holdaas H, Tesar V, Wiecek A, Grobbee D, de Zeeuw D, Gro¨nhagen-Riska C, Dasgupta T, Lewis D, Herrington W, Mafham M, Majoni W, Wallendszus K, Grimm R, Pedersen T, Tobert J, Armitage J, Baxter A, Bray C, Chen Y, Chen Z, Hill M, Knott C, Parish S, Simpson D, Sleight P, Young A, Collins R; SHARP Investigators: The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): A randomised placebo-controlled trial. Lancet 377: 2181–2192, 2011 Gooch K, Culleton BF, Manns BJ, Zhang J, Alfonso H, Tonelli M, Frank C, Klarenbach S, Hemmelgarn BR: NSAID use and progression of chronic kidney disease. Am J Med 120: e1–e7, 2007 Kausz A, Pahari D: The value of vaccination in chronic kidney disease. Semin Dial 17: 9–11, 2004 Navaneethan SD, Kandula P, Jeevanantham V, Nally JV Jr, Liebman SE: Referral patterns of primary care physicians for chronic kidney disease in general population and geriatric patients. Clin Nephrol 73: 260–267, 2010 Greer RC, Powe NR, Jaar BG, Troll MU, Boulware LE: Effect of primary care physicians’ use of estimated glomerular filtration rate on the timing of their subspecialty referral decisions. BMC Nephrol 12: 1, 2011 Boulware LE, Troll MU, Jaar BG, Myers DI, Powe NR: Identification and referral of patients with progressive CKD: A national study. Am J Kidney Dis 48: 192–204, 2006 Rutkowski M, Mann W, Derose S, Selevan D, Pascual N, Diesto J, Crooks P: Implementing KDOQI CKD definition and staging
Clin J Am Soc Nephrol 9: 1526–1535, September, 2014
43.
44.
45.
46.
47.
guidelines in Southern California Kaiser Permanente. Am J Kidney Dis 53[Suppl 3]: S86–S99, 2009 Fox CH, Swanson A, Kahn LS, Glaser K, Murray BM: Improving chronic kidney disease care in primary care practices: An upstate New York practice-based research network (UNYNET) study. J Am Board Fam Med 21: 522–530, 2008 U.S. Department of Veterans Affairs: VA clinical practice guideline for management of chronic kidney disease in primary care. 2008. Accessed at: http://www.healthquality.va.gov/ guidelines/CD/ckd/ckd_v478.pdf. Date Accessed December 1, 2013 Manley HJ: Disease progression and the application of evidencebased treatment guidelines diagnose it early: A case for screening and appropriate management. J Manag Care Pharm 13 [Suppl D]: S6–S12, 2007 Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, Rubin HR: Why don’t physicians follow clinical practice guidelines? A framework for improvement. JAMA 282: 1458– 1465, 1999 Oliveras A, Schmieder RE: Clinical situations associated with difficult-to-control hypertension. J Hypertens 31[Suppl 1]: S3– S8, 2013
CKD Checklist for Primary Care, Mendu et al.
1535
48. Gallagher H, de Lusignan S, Harris K, Cates C: Qualityimprovement strategies for the management of hypertension in chronic kidney disease in primary care: a systematic review. Br J Gen Pract 60: e258–e265, 2010 49. McCambridge J, Witton J, Elbourne DR: Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects. J Clin Epidemiol Nov: 22, 2013 50. Garrouste-Orgeas M, Soufir L, Tabah A, Schwebel C, Vesin A, Adrie C, Thuong M, Timsit JF; Outcomerea Study Group: A multifaceted program for improving quality of care in intensive care units: IATROREF study. Crit Care Med 40: 468– 476, 2012 Received: February 12, 2014 Accepted: June 5, 2014 Published online ahead of print. Publication date available at www. cjasn.org. See related editorial, “Checklists as Computer Decision Support at the Point of Care: A Step Forward in the Recognition and Treatment of CKD by Primary Care Physicians,” on pages 1505–1506.
