Factors Associated With Preventive Pharmacological Therapy Adherence Among Patients With Kidney Stones

Factors Associated With Preventive Pharmacological Therapy Adherence Among Patients With Kidney Stones

Accepted Manuscript Title: Factors Associated with Preventive Pharmacological Therapy Adherence among Patients with Kidney Stones Author: Casey A. Dau...

687KB Sizes 1 Downloads 16 Views

Accepted Manuscript Title: Factors Associated with Preventive Pharmacological Therapy Adherence among Patients with Kidney Stones Author: Casey A. Dauw, Yooni Yi, Maggie J. Bierlein, Phyllis Yan, Abdulrahman F. Alruwaily, Khurshid R. Ghani, J. Stuart Wolf, Brent K. Hollenbeck, John M. Hollingsworth PII: DOI: Reference:

S0090-4295(16)30011-5 http://dx.doi.org/doi: 10.1016/j.urology.2016.03.030 URL 19709

To appear in:


Received date: Accepted date:

18-12-2015 17-3-2016

Please cite this article as: Casey A. Dauw, Yooni Yi, Maggie J. Bierlein, Phyllis Yan, Abdulrahman F. Alruwaily, Khurshid R. Ghani, J. Stuart Wolf, Brent K. Hollenbeck, John M. Hollingsworth, Factors Associated with Preventive Pharmacological Therapy Adherence among Patients with Kidney Stones, Urology (2016), http://dx.doi.org/doi: 10.1016/j.urology.2016.03.030. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


Casey A. Dauw, MD; Yooni Yi, MD; Maggie J. Bierlein, MS; Phyllis Yan, MS; Abdulrahman F. Alruwaily, MD; Khurshid R. Ghani, MD; J. Stuart Wolf Jr., MD; Brent K. Hollenbeck, MD, MS; and John M. Hollingsworth, MD, MS

From the Divisions of Endourology and Health Services Research, Department of Urology, University of Michigan Medical School

Keywords: kidney stones, preventive pharmacological therapy, adherence, secondary prevention Acknowledgements: This work is supported by a grant from the AHRQ and the Urology Care Foundation, 1K08HS020927-01A1 Corresponding Author: John M. Hollingsworth 2800 Plymouth Road Building 16, 1st Floor, Room 112W Ann Arbor, MI 48109 Email: [email protected] Phone: 734-763-2797 Fax: 734-232-2400 ABSTRACT Objective: To determine adherence patterns for thiazide diuretics, alkali citrate therapy, and allopurinol, collectively referred to as preventive pharmacological therapy (PPT), amongst patients with kidney stones. Materials and Methods: Using medical claims data, we identified adults diagnosed with kidney stones between 2002 and 2006. Through National Drug Codes, we determined


Page 1 of 15

those with one or more prescription fills for a PPT agent. We measured adherence to PPT [as determined by the proportion-of-days-covered (PDC) formula] within the first 6 months of starting therapy and performed multivariate analysis to evaluate patient factors associated with PPT adherence. Results: Among 7,980 adults with kidney stones who were prescribed PPT, less than one third (30.2%) were adherent to their regimen (indicated by PDC≥80%). Among those on monotherapy, rates of adherence differed by the type of PPT agent prescribed: 42.5% for thiazides, 40.0% for allopurinol, and 13.4% for citrate therapy. Factors that were independently associated with lower odds of PPT adherence included combination therapy receipt, female gender, less generous health insurance, and residence in the South or Northeast. In contrast, older patients and those with salaried employment had a higher probability of PPT adherence. Conclusions: Adherence to PPT is low. These findings help providers identify patients where PPT adherence will be problematic. Moreover, they suggest possible targets for quality improvement efforts in the secondary prevention of kidney stones.


Kidney stones are a chronic medical condition, for which secondary prevention can play an important management role. In recognition of this, the American Urological Association and the American College of Physicians recently released clinical guidelines, outlining a rational approach to reduce kidney stone recurrence in adults.1,2 Recommendations include a trial of a thiazide diuretic, citrate, or allopurinol— collectively referred to as preventive pharmacological therapy (PPT)—in the patient with


Page 2 of 15

active kidney stone disease that fails to respond to dietary modification alone. However, while multiple randomized, controlled trials have shown PPT to be efficacious, getting patients to accept a prescribed regimen and adhere to it may be difficult since the benefits of treatment are not obviously apparent when patients are between symptomatic stone events.3-7 Indeed, the literature on other chronic medical conditions like diabetes and hypertension suggests that medication adherence rates are about 50% at best.8 Because nonadherence may mitigate treatment benefit or even cause harm, understanding baseline adherence rates among patients on preventive pharmacological therapy is important.9,10 In this context, we used medical claims data to identify adult patients with a diagnosis of kidney stones. Among those with a prescription fill for a PPT agent, we assessed their adherence using a validated metric. We then evaluated for changes in rates of adherence over time. Finally, we determined patient-level factors that were associated with higher adherence. Findings from our study serve to inform future interventions designed to increase the uptake of PPT among patients with kidney stone disease. METHODS

Data source and study population For our study, we used Truven Health Analytics MarketScan® Commercial Claims and Encounters Database (2002 to 2006). This longitudinal database contains medical and drug claims from a population of working-age adults with employersponsored insurance and their dependents.


Page 3 of 15

Through an established International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9) code-based algorithm,11 we identified adults between the ages 18 and 64 years old with a diagnosis of urinary stone disease. To be eligible for inclusion, a beneficiary had to have continuous health insurance coverage for 180 days prior to the index stone claim and 180 days after his/her prescription fill for a PPT agent. Since our analytic focus was on PPT, we then used appropriate National Drug Codes to abstract the subset of beneficiaries with a new prescription fill for a thiazide diuretic, alkali citrate therapy, and/or allopurinol during the six months after their index stone claim. Understanding that medications such as thiazide diuretics and allopurinol are not necessarily specific for metabolic stone management, we conducted a secondary analysis in which we excluded patients with a concomitant diagnosis of hypertension (ICD-9 codes 401.1, 401.9) or gout (274.0, 242.01, 242.02, 242.03, 274.89, 274.9) A complete list of the medications considered to be PPT is available upon request.

Measuring medication adherence To estimate medication adherence, we used the proportion of days covered (PDC) formula. While there are multiple ways of measuring and assessing medication adherence using secondary data, the PDC offers several important advantages. First, it provides a more conservative estimate of adherence (compared to other popular methods) when multiple medications are intended to be used concomitantly. Second, the PDC avoids double-counting of days of medication coverage because a day is only counted if all medications are available on that day.12 Third, it is the only measure recommended by the Pharmacy Quality Alliance.13


Page 4 of 15

With values ranging from 0 to 1, the PDC is calculated as the number of days available or “covered” by a certain medication divided by the total number of days in the follow-up period.14 For our study, we used a 180-day follow-up period after a beneficiary’s first prescription fill for a PPT agent. In the event that a beneficiary was prescribed multiple agents from different classes (e.g., a thiazide diuretic and potassium citrate), we estimated adherence by calculating the average of class-specific PDC values. We then multiplied the PDC by 100 to express it as a percent. Consistent with prior studies, we defined a beneficiary as being adherent if this percent was at or above 80%.15

Statistical analysis For our initial analytic step, we assessed overall adherence to PPT by study year. To assess for changes over time in adherence, we used the Cochran-Armitage Trend test. Next, we examined for differences in adherence based on the class of agent prescribed. We then made comparisons between adherent and nonadherent beneficiaries over a variety of sociodemographic factors. Specifically, we examined for differences related to their age at the time of the index stone claim, gender, employment classification (salaried versus hourly) and status (full- versus part-time), generosity of health insurance, urban/rural status, geographic region of residence, and baseline health status. To determine the generosity of health insurance, we calculated the percentage covered by insurance for each prescription fill during the 180-day follow-up period and took the mean for each beneficiary. We then ranked beneficiaries by this mean, splitting into tertiles of low, medium, and high generosity. To assess baseline health status, we used a


Page 5 of 15

modification of the Charlson comorbidity index score. For all bivariate comparisons, we used t-tests and chi-square tests where appropriate. Finally, we used multivariate regression to understand the determinants of adherence. For our binary outcome, we fit log binomial regression models where our independent variable of interest was receipt of combination therapy. Our a priori hypothesis was that this would be associated with lower probability of adherence. We adjusted our models for the other patient-level factors described above. We completed all analyses using the SAS statistical software package, Version 9.3 (SAS Institute Inc., Cary, NC). We performed two-sided significance with alpha set to 0.05. Our Institutional Review Board deemed that this study (based on de-identified data) was exempt from oversight.

RESULTS Among the 7,980 beneficiaries who met our study’s inclusion criteria, the majority were on thiazide (40.5%) or citrate (30.1%) monotherapy. Combination therapy was infrequently prescribed (Table 1). Among those on monotherapy, adherence rates were highest for thiazides (42.5%), followed by allopurinol (40.0%) and citrates (13.4%). Regardless of the agent prescribed, adherence to monotherapy was higher than combination therapy (31.4% versus 23.3%, P<0.001 for the comparison). Our findings were robust even after excluding patients with pre-existing diagnoses of hypertension or gout. As shown in Table 2, adherent and not adherent beneficiaries differed in measurable ways. For instance, adherent beneficiaries tended to be older men from the


Page 6 of 15

Midwest region with lower levels of comorbidity. In addition, they were more likely to have salaried employment and enjoy more generous health insurance benefits. After controlling for these differences, we found that patients on combination therapy had nearly 30% lower probability (relative risk, 0.71; 95% confidence interval, 0.63 to 0.79) of medication adherence compared to those on monotherapy. Other factors associated with lower probability of adherence included female gender, less generous health insurance, and residence in the Northeast or South (Table 3). On the other hand, increasing age, salaried employment, and residence in the Midwest were protective (Table 3).


The present study explored PPT adherence rates among working-age adults with kidney stones. In a cohort of 7,980 patients, less than 1 in 3 patients were adherent to prescribed therapy. Increasing age, salaried employees, those with greater generosity of insurance, and residence in the Midwest were associated with a higher probability of medication adherence. However, receipt of combination therapy was associated with a lower probability of PPT adherence. Although prescription of PPT is recommended by several professional societies1,2,16 for the secondary prevention of kidney stones, there are few data regarding adherence to these medications. Despite limited information on this topic in patients with kidney stones, our results are consistent with reported adherence rates to medication therapy in other chronic medical conditions, where adherence has been well studied. In a cohort of more than 34,000 patients with hyperlipidemia, Benner et al found that


Page 7 of 15

adherence to statin therapy at 3 and 6 months following initiation was 60% and 43%, respectively.17 Similarly, Cramer et al conducted a systematic review and meta-analysis in diabetic patients in which adherence to anti-hyperglycemic medication was noted to be 30% to 90% depending on the medication prescribed.18 Not only are rates of medication adherence low in patients with chronic medical conditions, but poor adherence has a significant impact on disease specific health outcomes. The renowned physician C. Everett Coop was correct when he plainly stated, “Drugs don’t work in patients who don’t take them.”19 In one of the only studies published in the urologic literature regarding the impact that medication adherence has on disease specific health outcomes for patients with kidney stones, Dauw and colleagues found that greater adherence to PPT was associated with decreased odds of emergency department visit, hospitalization, and surgical intervention.20 These findings are consistent with studies from other medical fields. Ho et al examined a cohort of patients with diabetes and ischemic heart disease and found 50% lower odds of mortality amongst patients who where adherent to at least one cardioprotective medication.15 Similarly, Wei et al found that in a cohort of patients with incident myocardial infarction, rates of subsequent acute coronary syndrome and death were diminished in patients who adhered to statin therapy.21 It should be noted that prescription of monotherapy was far more common than combination therapy in our study (Table 1). This is interesting in that thiazide diuretics, for example, can cause hypokalemia and lead to hypocitraturia due to intracellular acidosis. To address this, physicians often supplement potassium, either in the form of potassium chloride or potassium citrate. The low observed use of combination therapy


Page 8 of 15

could stem from the fact that guidelines on medical management of kidney stones were not available over the study interval (those from the European Association of Urology and the American Urological Association were only recently released). This fact could also explain the relatively high frequency with which allopurinol monotherapy was prescribed (13.5%). Indeed, recent guidelines offer very specific and limited indications for allopurinol (i.e.,patients with recurrent calcareous nephrolithiasis with hyperuricosuria and normal urine calcium) While several patient factors were related to adherence, our finding that higher socioeconomic status was associated with higher odds of medication adherence bears mentioning. Similar findings have been noted elsewhere in the chronic disease literature. Namely, a recent systematic review and meta-analysis revealed that higher socioeconomic status was associated with improved medication adherence among patients with hypertension.22 Taken together, before a physician prescribes PPT for a patient with kidney stones, he/she should consider whether the patient has the means to pay for it. Understanding that patients with kidney stones have low rates of PPT adherence raises the question of what can we as clinicians do? A recent Cochrane review found that decreasing medication dosing complexity and motivational strategies led to modest improvements in medication adherence in patients with hypertension.23 Interestingly, patient counseling did not seem to impact adherence rates in this study. A more contemporary study by DeKoekkoek et al evaluated the use of text messaging to improve medication adherence. They reported a 15% to 17% increase in medication adherence in


Page 9 of 15

patients that received the intervention.24 Such strategies may also have a role for improving medication adherence in patients with kidney stones. Our study must be considered in the context of several limitations. MarketScan data consist of medical and pharmacy claims from insured adults. Therefore, our findings may not be generalizable to the elderly or the uninsured. However, our study does capture the population of patients in whom urinary stone prevalence is highest. In addition, our measure of adherence to a medication is based on a beneficiary’s possession of it, and there is no guarantee that the medication was taken as prescribed. We must acknowledge the possibility of misclassification bias. Our measure of medication adherence—the PDC—relies on prescription refill records and does not account for communication between a patient and provider after therapy is initiated. For instance, if a physician recommended that a patient discontinue PPT due to intolerance of its side effects, the patient may be classified as non-adherent when, in fact, he/she was following his/her doctor’s advice. Nonetheless, the PDC is one of the most commonly used measures of medication adherence and is endorsed by the Pharmacy Quality Alliance. Despite these unknowns, drug claims provide an acceptable estimate of adherence with large patient populations.25,26


Limitations notwithstanding, our study is important in that it is the first to describe adherence to preventive pharmacologic therapy agents in patients with kidney stones. We observed that only 30.2% of patients were adherent to prescribed therapy.


Page 10 of 15

Although recent studies suggest favorable clinical implications related to adherence to PPT with regard to future stone events, the economic implications of these findings on patients with kidney stones are unclear. That said, our analysis will help providers identify patients for whom PPT adherence may be problematic. Moreover, it suggests possible targets for quality improvement efforts in the secondary prevention of kidney stones.



Pearle MS, Goldfarb DS, Assimos DG, et al. Medical management of kidney stones: AUA guideline. J Urol. 2014;192(2):316–324. doi:10.1016/j.juro.2014.05.006.


Qaseem A, Dallas P, Forciea MA, Starkey M, Denberg TD. Dietary and Pharmacologic Management to Prevent Recurrent Nephrolithiasis in Adults: A Clinical Practice Guideline From the American College of Physicians. Ann Intern Med. 2014;161(9):659–667. doi:10.7326/M13-2908.


Barcelo P, Wuhl O, Servitge E, Rousaud A, Pak CY. Randomized double-blind study of potassium citrate in idiopathic hypocitraturic calcium nephrolithiasis. J Urol. 1993;150(6):1761–1764.


Ettinger B, Pak CY, Citron JT, Thomas C, Adams-Huet B, Vangessel A. 11

Page 11 of 15

Potassium-magnesium citrate is an effective prophylaxis against recurrent calcium oxalate nephrolithiasis. J Urol. 1997;158(6):2069–2073. 5.

Ettinger B, Citron JT, Livermore B, Dolman LI. Chlorthalidone reduces calcium oxalate calculous recurrence but magnesium hydroxide does not. J Urol. 1988;139(4):679–684.


Laerum E, Larsen S. Thiazide prophylaxis of urolithiasis. A double-blind study in general practice. Acta Med Scand. 1984;215(4):383–389.


Ettinger B, Tang A, Citron JT, Livermore B, Williams T. Randomized trial of allopurinol in the prevention of calcium oxalate calculi. N Engl J Med. 1986;315(22):1386–1389. doi:10.1056/NEJM198611273152204.


World Health Organization. Adherence to Long-Term Therapy: Evidence for action. January 2003. http://www.who.int/chp/knowledge/pulications/adherence_full_report.pdf?ua=1.


Ho PM, Rumsfeld JS, Masoudi FA, et al. Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Arch Intern Med. 2006;166(17):1836–1841. doi:10.1001/archinte.166.17.1836.


Rasmussen JN, Chong A, Alter DA. Relationship between adherence to evidencebased pharmacotherapy and long-term mortality after acute myocardial infarction. JAMA. 2007;297(2):177–186. doi:10.1001/jama.297.2.177.


Semins MJ, Trock BJ, Matlaga BR. Validity of administrative coding in identifying patients with upper urinary tract calculi. J Urol. 2010;184(1):190–192. doi:10.1016/j.juro.2010.03.011.


Choudhry NK, Shrank WH, Levin RL, et al. Measuring concurrent adherence to multiple related medications. Am J Manag Care. 2009;15(7):457–464.


Pharmacy Quality Alliance: PQA Measure Development. http://www.pqaalliance.org/measures/default.asp. Accessed January 29, 2016.


Hess LM, Raebel MA, Conner DA, Malone DC. Measurement of adherence in pharmacy administrative databases: a proposal for standard definitions and preferred measures. Ann Pharmacother. 2006;40(7-8):1280–1288. doi:10.1345/aph.1H018.


Ho PM, Magid DJ, Masoudi FA, McClure DL, Rumsfeld JS. Adherence to cardioprotective medications and mortality among patients with diabetes and ischemic heart disease. BMC Cardiovasc Disord. 2006;6:48. doi:10.1186/14712261-6-48.


Turk C, Knoll T, Petrik A. Guidelines on Urolithiasis, EAU Guidelines Urolithiasis 2014. wwwuroweborg. 12

Page 12 of 15

http://www.uroweb.org/gls/pdf/22%20Urolithiasis_LR.pdf. Accessed February 26, 2015. 17.

Benner JS, Glynn RJ, Mogun H, Neumann PJ, Weinstein MC, Avorn J. Long-term persistence in use of statin therapy in elderly patients. JAMA. 2002;288(4):455– 461.


Cramer JA. A systematic review of adherence with medications for diabetes. Diabetes Care. 2004;27(5):1218–1224.


Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005;353(5):487–497. doi:10.1056/NEJMra050100.


Dauw CA, Yi Y, Bierlein MJ, et al. Medication Nonadherence and the Effectiveness of Preventive Pharmacological Therapy for Kidney Stones. J Urol. October 2015. doi:10.1016/j.juro.2015.10.082.


Wei L, Wang J, Thompson P, Wong S, Struthers AD, MacDonald TM. Adherence to statin treatment and readmission of patients after myocardial infarction: a six year follow up study. Heart. 2002;88(3):229–233.


Alsabbagh MHDW, Lemstra M, Eurich D, et al. Socioeconomic status and nonadherence to antihypertensive drugs: a systematic review and meta-analysis. Value Health. 2014;17(2):288–296. doi:10.1016/j.jval.2013.11.011.


Schroeder K, Fahey T, Ebrahim S. Interventions for improving adherence to treatment in patients with high blood pressure in ambulatory settings. Cochrane Database Syst Rev. 2004;(2):CD004804. doi:10.1002/14651858.CD004804.


DeKoekkoek T, Given B, Given CW, Ridenour K, Schueller M, Spoelstra SL. mHealth SMS text messaging interventions and to promote medication adherence: an integrative review. J Clin Nurs. 2015;24(19-20):2722–2735. doi:10.1111/jocn.12918.


Steiner JF, Koepsell TD, Fihn SD, Inui TS. A general method of compliance assessment using centralized pharmacy records. Description and validation. Med Care. 1988;26(8):814–823.


Steiner JF, Prochazka AV. The assessment of refill compliance using pharmacy records: methods, validity, and applications. J Clin Epidemiol. 1997;50(1):105– 116.


Page 13 of 15

Table 1. PPT Use by Study Population Medication Class Frequency Thiazide Monotherapy 3,234 Citrate Monotherapy 2,484 Allopurinol Monotherapy 1,074 Thiazide and Allopurinol 225 Thiazide and Citrate 419 Citrate and Allopurinol 461 Thiazide, Citrate, and Allopurinol 83

Percent 40.5 31.1 13.5 2.8 5.3 5.8 1.0

Table 2. Bivariate Comparisons between Adherent and Nonadherent Patients Nonadherent Adherent PPatient Characteristic (n=5,567) (n=2,413) value Patient age, mean (standard 46.79 (10.74) 50.80 (9.21) <.0001 deviation) Salaried employee (%) 18.81 22.34 0.0003 Full-time employee (%) 60.97 59.01 0.1014 Charlson comorbidity score (%) <.0001 0 87.61 83.09 1 8.6 12.64 2 2.77 2.86 3+ 1.02 1.41 Plan type 0.0006 Comprehensive 10.66 13.97 Health maintenance 18.05 16.26 organization Other Noncapitated 58.31 56.92 Point-of-service 12.45 12.43 Preferred provider 0.52 0.42 organization Health insurance generosity <.0001 High 26.05 31 Medium 32.96 33.36 Low 40.99 35.64 Region <.0001 Northeast 8.93 8.33 South 47.51 41.53 West 17.82 17.94 Midwest 25.74 32.2 Male (%) 64 69.79 <.0001 Urban (%) 76.79 77.75 0.3519


Page 14 of 15

Table 3. Independent Predictors of Medication Adherence Patient Characteristic Female Age Combination therapy Urban Region (referent Midwest) Northeast South West Salaried Full-time Generosity of insurance plan (referent high) Low Medium Charlson comorbidity score (referent 3+) 0 1 2

Relative Risk 0.89 1.03 0.71 0.97

95% Confidence Interval 0.83-0.96 1.02-1.03 0.63-0.79 0.90-1.05

0.83 0.85 0.92 1.12 1.06

0.73-0.94 0.79-0.92 0.83-1.01 1.04-1.21 0.99-1.14

0.89 0.99

0.82-0.96 0.91-1.07

0.9 1.06 0.83

0.69-1.17 0.81-1.39 0.60-1.14


Page 15 of 15