[Skip to Navigation]
Sign In
Figure 1. 
Persistence with antihypertensive medication in the first 6 months among 13 205 incident patients newly starting treatment.

Persistence with antihypertensive medication in the first 6 months among 13 205 incident patients newly starting treatment.

Figure 2. 
Reduction in relative risk of nonpersistence in the first 6 months by medical management (clinical decision-making) and communication (data collection: history and physical examination skills) ability. Standardized examination scores were converted from a standard mean of 500 to the raw score mean of 66.8% overall for all examination administrations and the mean standard deviation of 5.73. Adjusted odds ratios (Table 4) were used to plot the change in relative risk of nonpersistence for each 1-SD change in examination score within the score range observed in the study population, from the lowest score category (−3 SDs) to the highest (+3 SDs).

Reduction in relative risk of nonpersistence in the first 6 months by medical management (clinical decision-making) and communication (data collection: history and physical examination skills) ability. Standardized examination scores were converted from a standard mean of 500 to the raw score mean of 66.8% overall for all examination administrations and the mean standard deviation of 5.73. Adjusted odds ratios (Table 4) were used to plot the change in relative risk of nonpersistence for each 1-SD change in examination score within the score range observed in the study population, from the lowest score category (−3 SDs) to the highest (+3 SDs).

Table 1. 
Characteristics of the 645 Physicians in the Study Population
Characteristics of the 645 Physicians in the Study Population
Table 2. 
Characteristics of the 13 205 Patients Who Started Antihypertensive Treatment
Characteristics of the 13 205 Patients Who Started Antihypertensive Treatment
Table 3. 
Association Between Patient Characteristics and Nonpersistence With Antihypertensive Treatment in First 6 Months After Starting Therapy
Association Between Patient Characteristics and Nonpersistence With Antihypertensive Treatment in First 6 Months After Starting Therapy
Table 4. 
Association Between Physician Abilities and Nonpersistence With Antihypertensive Treatment in First 6 Months of Treatment
Association Between Physician Abilities and Nonpersistence With Antihypertensive Treatment in First 6 Months of Treatment
Table 5. 
Association Between Physician-Mediated Antihypertensive Treatment Characteristics and Nonpersistence With Antihypertensive Treatment in First 6 Months of Treatment
Association Between Physician-Mediated Antihypertensive Treatment Characteristics and Nonpersistence With Antihypertensive Treatment in First 6 Months of Treatment
1.
Daar  ASSinger  PAPersad  DL  et al.  Grand challenges in chronic non-communicable diseases.  Nature 2007;450 (7169) 494- 496PubMedGoogle Scholar
2.
Heron  MHoyert  DXu  JScott  C Deaths: preliminary data for 2006.  Natl Vital Stat Rep 2008;56 (12) 1- 52Google Scholar
3.
Ford  ESAjani  UACroft  JB  et al.  Explaining the decrease in U.S. deaths from coronary disease, 1980-2000.  N Engl J Med 2007;356 (23) 2388- 2398PubMedGoogle Scholar
4.
Morris  ABLi  JKroenke  KBruner-England  TEYoung  JMMurray  MD Factors associated with drug adherence and blood pressure control in patients with hypertension.  Pharmacotherapy 2006;26 (4) 483- 492PubMedGoogle Scholar
5.
Perreault  SLamarre  DBlais  L  et al.  Persistence with treatment in newly treated middle-aged patients with essential hypertension.  Ann Pharmacother 2005;39 (9) 1401- 1408PubMedGoogle Scholar
6.
Bourgault  CSenecal  MBrisson  MMarentette  MAGregoire  JP Persistence and discontinuation patterns of antihypertensive therapy among newly treated patients: a population-based study.  J Hum Hypertens 2005;19 (8) 607- 613PubMedGoogle Scholar
7.
Chou  CCLee  MSKe  CHChuang  MH Factors influencing the switch in the use of antihypertensive medications.  Int J Clin Pract 2005;59 (1) 85- 91PubMedGoogle Scholar
8.
Mazzaglia  GMantovani  LGSturkenboom  MC  et al.  Patterns of persistence with antihypertensive medications in newly diagnosed hypertensive patients in Italy: a retrospective cohort study in primary care.  J Hypertens 2005;23 (11) 2093- 2100PubMedGoogle Scholar
9.
Rasmussen  JNChong  AAlter  DA Relationship between adherence to evidence-based pharmacotherapy and long-term mortality after acute myocardial infarction.  JAMA 2007;297 (2) 177- 186PubMedGoogle Scholar
10.
Grégoire  JPMoisan  JGuibert  R  et al.  Determinants of discontinuation of new courses of antihypertensive medications.  J Clin Epidemiol 2002;55 (7) 728- 735PubMedGoogle Scholar
11.
Caro  JJSpeckman  JLSalas  MRaggio  GJackson  JD Effect of initial drug choice on persistence with antihypertensive therapy: the importance of actual practice data.  CMAJ 1999;160 (1) 41- 46PubMedGoogle Scholar
12.
Heisler  MHogan  MMHofer  TPSchmittdiel  JAPladevall  MKerr  EA When more is not better: treatment intensification among hypertensive patients with poor medication adherence.  Circulation 2008;117 (22) 2884- 2892PubMedGoogle Scholar
13.
Banning  M Older people and adherence with medication: a review of the literature.  Int J Nurs Stud 2008;45 (10) 1550- 1561PubMedGoogle Scholar
14.
DiMatteo  MR Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research.  Med Care 2004;42 (3) 200- 209PubMedGoogle Scholar
15.
Schroeder  KFahey  TEbrahim  S Interventions for improving adherence to treatment in patients with high blood pressure in ambulatory settings.  Cochrane Database Syst Rev 2004; (2) CD004804PubMed10.1002/14651858.CD004804Google Scholar
16.
Ambrosioni  ELeonetti  GPessina  ACRappelli  ATrimarco  BZanchetti  AScientific Committee of the Italian Pharmacoepidemiological Survey on Antihypertensive Therapy, Patterns of hypertension management in Italy: results of a pharmacoepidemiological survey on antihypertensive therapy.  J Hypertens 2000;18 (11) 1691- 1699PubMedGoogle Scholar
17.
Wright  JMMusini  VM First-line drugs for hypertension.  Cochrane Database Syst Rev 2009; (3) CD001841PubMed10.1002/14651858.CD001841.pub2Google Scholar
18.
Bokhour  BGBerlowitz  DRLong  JAKressin  NR How do providers assess antihypertensive medication adherence in medical encounters?  J Gen Intern Med 2006;21 (6) 577- 583PubMedGoogle Scholar
19.
Tarn  DMHeritage  JPaterniti  DAHays  RDKravitz  RLWenger  NS Physician communication when prescribing new medications.  Arch Intern Med 2006;166 (17) 1855- 1862PubMedGoogle Scholar
20.
Martin  RMKerry  SMHilton  SR Initial treatment choices, second-line therapy, and reasons for stopping medication in the treatment of hypertension by general practitioners in England, Scotland and Wales: 1990-1995.  Pharmacoepidemiol Drug Saf 1997;6 (4) 253- 261PubMedGoogle Scholar
21.
Gandhi  TKWeingart  SNBorus  J  et al.  Adverse drug events in ambulatory care.  N Engl J Med 2003;348 (16) 1556- 1564PubMedGoogle Scholar
22.
Wilson  IBSchoen  CNeuman  P  et al.  Physician-patient communication about prescription medication nonadherence: a 50-state study of America's seniors.  J Gen Intern Med 2007;22 (1) 6- 12PubMedGoogle Scholar
23.
Heisler  MCole  IWeir  DKerr  EAHayward  RA Does physician communication influence older patients' diabetes self-management and glycemic control? results from the Health and Retirement Study (HRS).  J Gerontol A Biol Sci Med Sci 2007;62 (12) 1435- 1442PubMedGoogle Scholar
24.
Golin  CDiMatteo  RDuan  NLeake  BGelberg  L Impoverished diabetic patients whose doctors facilitate their participation in medical decision making are more satisfied with their care.  J Gen Intern Med 2002;17 (11) 857- 866PubMedGoogle Scholar
25.
Piette  JDHeisler  MKrein  SKerr  EA The role of patient-physician trust in moderating medication nonadherence due to cost pressures.  Arch Intern Med 2005;165 (15) 1749- 1755PubMedGoogle Scholar
26.
Schillinger  DPiette  JGrumbach  K  et al.  Closing the loop: physician communication with diabetic patients who have low health literacy.  Arch Intern Med 2003;163 (1) 83- 90PubMedGoogle Scholar
27.
Hulka  BSCassel  JCKupper  LLBurdette  JA Communication, compliance, and concordance between physicians and patients with prescribed medications.  Am J Public Health 1976;66 (9) 847- 853PubMedGoogle Scholar
28.
DiMatteo  MR Patient adherence to pharmacotherapy: the importance of effective communication.  Formulary 1995;30 (10) 596- 598, 601-602, 605PubMedGoogle Scholar
29.
Haq  CSteele  DJMarchand  LSeibert  CBrody  D Integrating the art and science of medical practice: innovations in teaching medical communication skills.  Fam Med 2004;36 ((suppl)) S43- S50PubMedGoogle Scholar
30.
Garg  AXAdhikari  NKMcDonald  H  et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.  JAMA 2005;293 (10) 1223- 1238PubMedGoogle Scholar
31.
Reznick  RKBlackmore  DDauphinee  WDRothman  AISmee  S Large-scale high-stakes testing with an OSCE: report from the Medical Council of Canada.  Acad Med 1996;71 (1) ((suppl)) S19- S21PubMedGoogle Scholar
32.
Wenghofer  EKlass  DAbrahamowicz  M  et al.  Doctor scores on national qualifying examinations predict quality of care in future practice.  Med Educ 2009;43 (12) 1166- 1173PubMedGoogle Scholar
33.
Tamblyn  RAbrahamowicz  MDauphinee  D  et al.  Physician scores on a national clinical skills examination as predictors of complaints to medical regulatory authorities.  JAMA 2007;298 (9) 993- 1001PubMedGoogle Scholar
34.
Tamblyn  RAbrahamowicz  MDauphinee  WD  et al.  Association between licensure examination scores and practice in primary care.  JAMA 2002;288 (23) 3019- 3026PubMedGoogle Scholar
35.
Regie de l’assurance-maladie du Quebec, Statistiques Annuelles.  Quebec, QC Regie de l’assurance-maladie du Quebec2000;Report ISBN 2-550-30856-5
36.
Sikka  RXia  FAubert  RE Estimating medication persistency using administrative claims data.  Am J Manag Care 2005;11 (7) 449- 457PubMedGoogle Scholar
37.
Steiner  JFProchazka  AV The assessment of refill compliance using pharmacy records: methods, validity, and applications.  J Clin Epidemiol 1997;50 (1) 105- 116PubMedGoogle Scholar
38.
Choo  PWRand  CSInui  TS  et al.  Validation of patient reports, automated pharmacy records, and pill counts with electronic monitoring of adherence to antihypertensive therapy.  Med Care 1999;37 (9) 846- 857PubMedGoogle Scholar
39.
Medical Council of Canada, Clinical stations.  Medical Council of Canada Web site. 2009 http://www.mcc.ca/en/exams/qe2/clinical_stations.shtml. Accessed June 2005Google Scholar
40.
Mandin  HDauphinee  WD Conceptual guidelines for developing and maintaining curriculum and examination objectives: the experience of the Medical Council of Canada.  Acad Med 2000;75 (10) 1031- 1037PubMedGoogle Scholar
41.
Page  GBordage  GAllen  T Developing key-feature problems and examinations to assess clinical decision-making skills.  Acad Med 1995;70 (3) 194- 201PubMedGoogle Scholar
42.
Tamblyn  RLavoie  GPetrella  LMonette  J The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Quebec.  J Clin Epidemiol 1995;48 (8) 999- 1009PubMedGoogle Scholar
43.
Tamblyn  RLaprise  RHanley  JA  et al.  Adverse events associated with prescription drug cost-sharing among poor and elderly persons.  JAMA 2001;285 (4) 421- 429PubMedGoogle Scholar
44.
Charlson  MEPompei  PAles  KLMacKenzie  CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis 1987;40 (5) 373- 383PubMedGoogle Scholar
45.
Zeger  SLLiang  KYAlbert  PS Models for longitudinal data: a generalized estimating equation approach.  Biometrics 1988;44 (4) 1049- 1060PubMedGoogle Scholar
46.
Miettinen  OS Proportion of disease caused or prevented by a given exposure, trait or intervention.  Am J Epidemiol 1974;99 (5) 325- 332PubMedGoogle Scholar
47.
Wilchesky  MTamblyn  RMHuang  A Validation of diagnostic codes within medical services claims.  J Clin Epidemiol 2004;57 (2) 131- 141PubMedGoogle Scholar
48.
Rudd  PMiller  NHKaufman  J  et al.  Nurse management for hypertension: a systems approach.  Am J Hypertens 2004;17 (10) 921- 927PubMedGoogle Scholar
49.
Goff  SLMazor  KMMeterko  VDodd  KSabin  J Patients' beliefs and preferences regarding doctors' medication recommendations.  J Gen Intern Med 2008;23 (3) 236- 241PubMedGoogle Scholar
50.
Hauber  ABMohamed  AFJohnson  FRFalvey  H Treatment preferences and medication adherence of people with type 2 diabetes using oral glucose-lowering agents.  Diabet Med 2009;26 (4) 416- 424PubMedGoogle Scholar
51.
Chessare  JB Teaching clinical decision-making to pediatric residents in an era of managed care.  Pediatrics 1998;101 (4, pt 2) 762- 767PubMedGoogle Scholar
52.
Ogur  BHirsh  DKrupat  EBor  D The Harvard Medical School-Cambridge integrated clerkship: an innovative model of clinical education.  Acad Med 2007;82 (4) 397- 404PubMedGoogle Scholar
53.
Reidel  KTamblyn  RPatel  VHuang  A Pilot study of an interactive voice response system to improve medication refill compliance.  BMC Med Inform Decis Mak 2008;8 (1) 46PubMedGoogle Scholar
54.
Green  BBRalston  JDFishman  PA  et al.  Electronic communications and home blood pressure monitoring (e-BP) study: design, delivery, and evaluation framework.  Contemp Clin Trials 2008;29 (3) 376- 395PubMedGoogle Scholar
55.
Fursse  JClarke  MJones  RKhemka  SFindlay  G Early experience in using telemonitoring for the management of chronic disease in primary care.  J Telemed Telecare 2008;14 (3) 122- 124PubMedGoogle Scholar
56.
Piette  JDWeinberger  MKraemer  FBMcPhee  SJ Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs Health Care System: a randomized controlled trial.  Diabetes Care 2001;24 (2) 202- 208PubMedGoogle Scholar
57.
Oake  NJennings  Avan Walraven  CForster  AJ Interactive voice response systems for improving delivery of ambulatory care.  Am J Manag Care 2009;15 (6) 383- 391PubMedGoogle Scholar
Original Investigation
June 28, 2010

Influence of Physicians' Management and Communication Ability on Patients' Persistence With Antihypertensive Medication

Author Affiliations

Author Affiliations: Departments of Epidemiology and Biostatistics (Drs Tamblyn, Abrahamowicz, Eguale, Winslade, Buckeridge, and Hanley and Ms Girard) and Medicine (Drs Tamblyn and Dauphinee), McGill University, Montreal, Quebec, Canada; School of Rural and Northern Health, Laurentian University and Northern Ontario School of Medicine, Sudbury, Ontario, Canada (Dr Wenghofer); Professional Development, College of Physicians and Surgeons of Ontario, Toronto (Dr Klass); Professional Development, Quebec College of Physicians, Montreal (Dr Jacques); and Medical Council of Canada, Ottawa, Ontario (Dr Smee and Ms Bartman).

Arch Intern Med. 2010;170(12):1064-1072. doi:10.1001/archinternmed.2010.167
Abstract

Background  Less than 75% of people prescribed antihypertensive medication are still using treatment after 6 months. Physicians determine treatment, educate patients, manage side effects, and influence patient knowledge and motivation. Although physician communication ability likely influences persistence, little is known about the importance of medical management skills, even though these abilities can be enhanced through educational and practice interventions. The purpose of this study was to determine whether a physician's medical management and communication ability influence persistence with antihypertensive treatment.

Methods  This was a population-based study of 13 205 hypertensive patients who started antihypertensive medication prescribed by a cohort of 645 physicians entering practice in Quebec, Canada, between 1993 and 2007. Medical Council of Canada licensing examination scores were used to assess medical management and communication ability. Population-based prescription and medical services databases were used to assess starting therapy, treatment changes, comorbidity, and persistence with antihypertensive treatment in the first 6 months.

Results  Within 6 months after starting treatment, 2926 patients (22.2%) had discontinued all antihypertensive medication. The risk of nonpersistence was reduced for patients who were treated by physicians with better medical management (odds ratio per 2-SD increase in score, 0.74; 95% confidence interval, 0.63-0.87) and communication (0.88; 0.78-1.00) ability and with early therapy changes (odds ratio, 0.45; 95% confidence interval, 0.37-0.54), more follow-up visits, and nondiuretics as the initial choice of therapy. Medical management ability was responsible for preventing 15.8% (95% confidence interval, 7.5%-23.3%) of nonpersistence.

Conclusion  Better clinical decision-making and data collection skills and early modifications in therapy improve persistence with antihypertensive therapy.

Effective management of chronic disease is a major challenge in health care.1 Among chronic conditions, cardiovascular disease is a leading cause of morbidity and mortality.2 Drug treatment can substantially reduce morbidity,3 but long-term therapy adherence is required to realize these benefits.4 Population-based studies of treatment persistence consistently show disappointing results, particularly for hypertension treatment.5-9 Less than 75% of people prescribed drugs for hypertension are still using them after 6 months, and nonpersistence is associated with an increased risk of hospitalization for cardiovascular problems.5,6,8-12

Few potentially modifiable determinants of persistence have emerged despite decades of research.4,6,10,13,14 Consequently, efforts to improve persistence target a variety of potentially important factors, each with a small contribution, such as patient understanding, motivation, forgetting, reinforcement, and cost.15 Results have been mixed, and these multifaceted complex programs are difficult to implement and sustain in regular practice.15

What is often overlooked is the role that physicians play in influencing adherence. Physicians determine treatment, educate patients, manage side effects, and influence patient knowledge and motivation.12 The physician's ability to manage these aspects of treatment may be particularly relevant for hypertension, in which discontinuation of treatment and poor adherence occur early in the course of therapy.6,8,10,16 The physician's choice of antihypertensive therapy appears to be one important determinant of treatment adherence. Although diuretics are recommended as first-line treatment,17 they have lower persistence rates than angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors, possibly because of differences in adverse effects.5,6,8,10 Physicians vary in the extent to which they discuss the rationale and expected effects of new medications,16,18,19 especially possible adverse effects.16,18 Because 22% to 62% of patients experience adverse effects from antihypertensive drugs in the initial period of use,10,16,20 effective physician-patient communication and therapeutic management of these problems is critical. Approximately 15% to 25% of patients will not spontaneously report adverse effects to their physicians, and, among those who do, physicians act in only 63% of cases.16,21,22

Although cross-sectional studies have provided compelling evidence about the importance of physician communication in improving adherence,14,22-28 until recently there has been no mechanism for systematically evaluating these skills in the training or licensure process. Moreover, medical management skills may also be important, particularly in treatment initiation and effective monitoring of treatment effects. These skill sets are amenable to improvement with structured education and practice support29,30 but have not been investigated.

A unique opportunity to address these issues arose in Canada when medical regulatory authorities requested the development of a national clinical skills examination to qualify for licensure. This examination assesses the physician's ability to communicate with patients, conduct a clinical assessment, and develop an appropriate management plan.31 Previous research has shown that lower scores on this examination predict complaints about poor communication and quality of care in the first decade of practice, as well as unsatisfactory peer review assessment.32-34 The possibility that physicians who possess greater proficiency in communication and/or medical management will achieve better medication adherence among their patients has not been examined. By linking physician examination results with information about newly treated hypertensive patients in the Quebec health care system, we were able to test the hypothesis that the newly treated hypertensive patients of physicians with superior communication and medical management abilities would achieve better adherence.

Methods
Context

The study was conducted in Canada, where universal health coverage is provided through provincial health insurance plans. Each province maintains a population-based registry of insured persons, discharge abstracts of all hospitalizations (diagnoses and procedures), claims for all physician visits remunerated on a fee-for-service basis, and prescriptions provided through the public drug insurance plan. Claims for physician visits include information on the diagnosis, procedure, date, location, and cost of service. Each prescription claim includes the drug, quantity, duration, and date of dispensing.35 All claims also record unique physician and patient identifiers that can be used to create longitudinal histories of utilization. In Quebec, 99% of residents have provincial health insurance, 85% to 95% of medical visits are remunerated on a fee-for-service basis, and 50% of persons (all elderly, welfare recipients, and persons not insured through their employer) have public drug insurance.35

Starting in 1992, to receive a license to practice in Canada, all physicians had to complete the Medical Council of Canada (MCC) national clinical skills examination (MCCQE2) in addition to the traditional written examination that assesses knowledge and clinical decision making (MCCQE1). The clinical skills examination assessed communication, history, and physical examination skills and clinical management by direct observation of performance by physician examiners in 18 to 20 standardized patient cases.31

Design and study population

A prospective cohort of Quebec physicians who completed the MCCQE2 between 1993 and 1996 was assembled. All hypertensive patients in Quebec who were started on an antihypertensive medication regimen by these physicians between 1993 and 2007 were followed up for the first 6 months after the initial prescription to assess persistence. Claims data were available for 100% of patients. Newly treated patients with hypertension were defined as having a dispensed prescription for an antihypertensive medication (diuretic, β-blocker, calcium channel blocker, angiotensin-converting enzyme inhibitor, angiotensin II receptor blocker, or α-receptor modifier), no previous prescription for an antihypertensive medication in the past year, and a diagnosis of hypertension (International Classification of Diseases, Ninth Revision, code 401) recorded in a physician visit in the past 12 months. Only patients whose treatment was initiated by physicians in the Quebec physician cohort were included. Patients who started treatment with more than 1 antihypertensive drug or who had insufficient follow-up because they died in the first 6 months after the start of treatment were excluded.

To protect confidentiality, the MCC and the Quebec medical regulatory authority assembled the physician cohort and replaced nominal physician data with a study number. The provincial health insurance agency (Régie de l’assurance maladie du Québec [RAMQ]) retrieved records for the 5.8 million patients who were seen by study physicians between 1993 and 2007, including all medical claims, prescriptions, and hospitalizations for these patients irrespective of the treating physician. The RAMQ encrypted all physician and patient identifiers, added the physician study number, and sent de-identified data for analysis. The MCC, Quebec privacy commission, RAMQ, and McGill University institutional review board provided ethics and legal approval.

Persistence with antihypertensive medication

Persistence with antihypertensive treatment was measured in the first 6 months because the greatest attrition in adherence to antihypertensive therapy occurs in the initial treatment period and is likely influenced by physician-related factors.5,6,8,10,11,20 Persistence was measured by means of records of prescription claims from all community-based pharmacies and was defined as having a continuous supply of at least 1 antihypertensive medication, with gaps no greater than 90 days, in the first 6 months of treatment. Prescription refills provide a good proxy measure of medication use because refill rates are strongly correlated with targeted clinical outcomes such as blood pressure.36-38 Nonpersistence with antihypertensive treatment was operationally defined as not refilling prescriptions for any antihypertensive treatment for at least 3 months and was assessed by checking 90 days after the end date of each prescription. If there were no further antihypertensive prescriptions dispensed, the end date on the last prescription was considered the start date of nonpersistence.

Physician-related determinants of persistence

Communication ability was assessed by means of standardized scores achieved in the communication, history, and physical examination components of the MCCQE2. Physician-patient communication skills are assessed in 3 or 4 cases, selected to represent challenging situations in which effective communication is required for management (eg, discuss refusal of treatment for a terminal illness, counsel an adolescent about birth control) by trained physician observers using case-specific checklists.31 Data collection skills by history and physical examination are assessed in a 5- or 10-minute interaction with 16 or 17 cases selected to represent common and important problems in practice (eg, conduct a focused history and physical examination for a patient presenting with abdominal pain).31,33,39 We also assessed overall scores achieved on the clinical skills examination, taken in the second postgraduate year, based on the mean of scores achieved in each standardized patient case.31

Medical management ability was assessed by means of the standardized medical knowledge and clinical decision-making scores on the MCCQE140 and clinical management scores on the MCCQE2.31 Medical knowledge is assessed by 450 multiple-choice questions that test medical knowledge in medicine, surgery, obstetrics-gynecology, psychiatry, pediatrics, and preventive medicine.40 Key feature problems are used to assess clinical decision making.41 Examinees are asked to respond to critical data collection, diagnosis, and/or management features of 36 to 40 clinical problems.41 Clinical management is assessed on the MCCQE2 by post–standardized patient encounter responses to short-answer questions about the case. We also assessed overall scores achieved on the MCCQE1, taken at the end of medical school, based on the weighted standardized score achieved on the multiple-choice questions and clinical decision-making components.40

Additional physician-related factors were examined as possible mediators between physician ability and persistence. Choice of initial therapeutic class for hypertension treatment has been shown to be associated with the risk of treatment discontinuation.6,8,10 Initial treatment was classified into 5 mutually exclusive categories: diuretics, β-blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers.

Therapy change, defined as a change in drug or dosage of initial treatment within the first 2 weeks, was assessed as an indicator of physician response to potential adverse effects or lack of therapeutic effect, identified by the patient or physician. We limited our assessment to the first 2 weeks after the first prescription was dispensed because most adverse effects for new antihypertensive treatment will occur in the first few weeks and to avoid reverse causality bias. Specifically, reverse causality bias can occur because therapy change necessitates the filling of a second prescription, which extends the period of use, and thus apparent persistence, unless there is sufficient follow-up after the expected end date of the prescription to accurately classify persistence. Because all prescriptions in Quebec are dispensed for 30 days or less,42 patients who had a new prescription for a drug or dosage change within the first 2 weeks after starting treatment, but stopped therapy after the second prescription, would still terminate their supply of medication before the end of the second month of follow-up. By the end of the 6-month follow-up period, such patients would have had no new prescriptions for more than 90 days and, thus, would be appropriately classified as nonpersistent.

Follow-up monitoring was defined in 2 ways: (1) as the number of visits to the prescribing physician in the 6 months after starting treatment and (2) as at least 1 early follow-up visit in the first 2 months when most adverse drug effects are expected. The first measure assessed the number of opportunities for the prescribing physician to reinforce the importance of therapy, whereas the latter measured the opportunity to assess initial treatment effects.

Physician sex, age, and specialty (family medicine/general practice, medical specialist, or surgical specialist) were retrieved from MCC and medical regulatory files. Physician practice experience was measured as a time-dependent variable that reflected the number of practice years since the completion of training when the physician prescribed hypertension treatment for a given patient. All physician-related variables were included in the analysis as potential confounders.

Patient determinants of persistence

Patient age, sex, and household income were measured by means of the RAMQ beneficiary database.43 Using hospitalization and medical services claims diagnostic codes for each patient in the year before the initiation of treatment, we assessed hypertension status (complicated or uncomplicated) and comorbidity. Complicated hypertension was defined as having a previous diagnosis of heart disease, diabetes, chronic kidney disease, atherosclerotic disease, cerebrovascular disease, peripheral arterial disease, asthma, chronic obstructive pulmonary disease, or benign prostatic hypertrophy. Comorbidity was measured by means of the Charlson Comorbidity Index,44 a weighted index of conditions that increase the risk of mortality. The setting in which the initial drug was prescribed, categorized as community, hospital, or emergency department, was also used as an indicator of patient acuity because patients whose antihypertensive treatment was initiated in acute care settings likely have more severe disease and would also have greater challenges in coordinating adequate community follow-up. Medication complexity was assessed by the number of different medications taken in the year before starting antihypertensive treatment.

Analysis

Nonpersistence during follow-up was descriptively summarized by life-table analysis. We tested the hypothesis that physician communication and management ability would be associated with persistence with hypertension treatment by means of the generalized estimating equation extension of multivariate logistic regression with an exchangeable covariance structure to account for clustering of patients within physicians (SAS, version 9.2; SAS Institute Inc, Cary, North Carolina).45 The patient was the unit of analysis, and nonpersistence at the end of the 6-month follow-up period was the binary outcome variable. We first fit the generalized estimating equation model with physician characteristics only and then adjusted their effects for patient characteristics and other physician-mediated determinants of persistence. We modeled each licensing examination score separately to avoid multicolinearity. We assessed nonlinearity by testing a quadratic term for examination score in each model. To determine whether the association between licensure examination scores and persistence with treatment was attenuated with increasing practice experience, we tested the statistical significance of interactions between ability scores and years of practice experience. In secondary analyses, we also assessed, in separate generalized estimating equation models with adjustment for physician and patient characteristics, the associations between licensure examination scores and the following intermediate physician-mediated outcomes of treatment: (1) antihypertensive drug choice (diuretics vs other classes), (2) therapy change in the first 2 weeks, and (3) at least 1 follow-up visit in the first 2 months. With a population of 13 205 patients, there was 88% statistical power to detect a relative increase of 10% per 1 SD in score, assuming a type 1 error of .05 and 20% nonpersistence.

To assess the clinical relevance of statistically significant relationships between physician communication and management ability and persistence, we calculated the prevented fraction by using the case-based approach.46 For this calculation, we used the reduction in risk of nonpersistence for patients of physicians in the 3 upper score quartiles relative to the bottom quartile because improving skills for the bottom 25% of physicians is a feasible goal for future intervention. The prevented fraction represents the proportion of expected cases of nonpersistence that were averted by better physician management and communication abilities and the potential reduction in nonpersistence that may be achieved by improving the skills of physicians in the bottom quartile.46

Results

A total of 645 of the 1161 physicians in the Quebec examination cohort who entered practice between 1993 and 2007 initiated hypertension treatment for at least 1 patient in their first 1 to 15 years of practice. The mean (SD) number of years of practice for these physicians was 5.6 (3.0) years; 54.3% were female, 57.8% were family physicians, and 32.9% were medical specialists (Table 1). The medical management and communication scores of study physicians were slightly above the mean score of 500 for all Canadian-trained physicians but diverged from the mean by up to 4 to 7 SDs.

Overall, physicians prescribed hypertensive treatment for 172 118 patients, of whom 13 205 (7.7%) met the inclusion criteria. Overall, 129 410 (75.2%) were excluded because of previous hypertensive therapy, 21 626 (12.6%) because there was no diagnosis of hypertension, 6794 (3.9%) because they started treatment with more than 1 drug, 263 (0.2%) because treatment duration was less than 5 days, and 820 (0.5%) because they died within the first 6 months of treatment. The mean age of newly treated hypertensive patients was 61.4 years, 57.7% were female, and the average household income was $46 010 (Table 2). Before starting antihypertensive treatment, 40.4% of patients were classified as having complicated hypertension, 43.1% were taking 2 to 5 other medications, and more than 30% had significant comorbidity on the Charlson index.

The most commonly used first-line treatments were angiotensin-converting enzyme inhibitors, diuretics, and calcium channel blockers (Table 2, eTable 1). Most antihypertensive treatment was started in a community-based setting, and the majority of patients had a follow-up visit with their prescribing physician in the first 2 months. The number of visits in the 6-month follow-up period was skewed (mean, 7.1; SD, 8.1) and therefore was reclassified as an ordinal variable in further analyses. After starting treatment, 8.0% of patients had a change in antihypertensive therapy in the first 2 weeks, the majority of which were drug changes.

Within the first 6 months, 2926 patients (22.2%) had discontinued all antihypertensive medication. More than half of nonpersistent patients (1717 [58.7%]) discontinued treatment in the first 60 days (Figure 1). Younger patients, males, and those who started treatment in hospital and emergency department settings were more likely to be nonpersistent, as were patients with lower income (Table 3).

Higher scores in medical management were protective against nonpersistence (Table 4). Clinical decision-making ability was the strongest predictor, for which the risk of nonpersistence was reduced by 23% (odds ratio [OR], 0.74; 95% confidence interval [CI], 0.63-0.87) per 2-SD increase in examination score and by 65% (0.35; 0.20-0.61) when comparing physicians who were 3 SDs above vs below the mean score (Figure 2). The relationship between clinical decision-making ability and persistence was not attenuated with longer practice experience, at least for the first 15 years of practice (score × years in practice interaction: P = .72). Better communication skills were also associated with a reduced risk of nonpersistence, specifically data collection skills, for which there was a 12% reduction in the risk of nonpersistence per 2-SD increase in score (OR, 0.88; 95% CI, 0.78-1.00) (Table 4, Figure 2). Higher overall scores in both the knowledge and clinical skills examinations were also associated with a lower risk of nonpersistence (Table 4).

Physician-mediated treatment characteristics were also associated with nonpersistence. Compared with patients taking diuretics, patients started on regimens of other classes of antihypertensive therapy were less likely to be nonpersistent (Table 5). Regardless of the class of antihypertensive treatment, early therapy change significantly reduced the risk of nonpersistence by 55% (OR, 0.45; 95% CI, 0.37-0.54). Both the number of follow-up visits and early follow-up were independently protective, the latter reducing the risk of nonpersistence by 14% (OR, 0.86; 95% CI, 0.75-0.98). Although there was no association between physician ability and choice of starting therapy, physicians with higher overall scores in knowledge and decision making were more likely to make therapy changes in the first 2 weeks (OR, 1.25; 95% CI, 1.01-1.53; per 2-SD increase in score), and physicians with higher scores in communication were more likely to have their patients come in for follow-up visits in the first 2 months (1.14; 1.01-1.29; per 2-SD increase in score) (eTable 2).

After adjusting for patient and treatment characteristics, 15.8% (95% CI, 7.5%-23.3%) of nonpersistence was prevented by physicians in the top 3 quartiles of clinical decision-making skills compared with physicians in the bottom quartile. For data collection, only physicians in the top quartile were significantly better than those in the bottom quartile, accounting for 4.8% (95% CI, 1.1%-7.9%) of nonpersistence.

Comment

We found that a substantial proportion of newly treated patients with hypertension discontinued all antihypertensive treatment within the first 6 months. Medical management ability, choice of therapy, and early changes in dosage and drug improved persistence. Physician-patient communication was also important, confirming results reported in previous cross-sectional studies,14,22-28 particularly more advanced skills in history taking and physical examination.

The strengths of this study are that we investigated novel approaches to assessing physician-related determinants of medication adherence using comprehensive population-based data on new users of antihypertensive treatment and national examination measures of physician ability. Limitations are that we used an indirect measure of medication persistence36-38 and we may have underestimated complications and comorbidity. Because administrative data have high specificity for diagnoses but only moderate sensitivity,47 these problems will produce random errors in measurement and attenuate associations. Similar to other studies, we found that diuretics were associated with higher risks of nonpersistence than other antihypertensive classes.6,8,10 The hypothesis that these differences are due to class-specific side effects is supported by our findings because the effect of therapeutic class was independent of patient and physician characteristics.

One of the most significant determinants of persistence was treatment change—specifically, the modification of the dosage or drug before the end of the first prescription. This is a new, but not unexpected, finding because 22% to 62% of new users of antihypertensive medications experience adverse effects that lead them to reduce or discontinue their use of prescription medication.10,16,20,48 We found that more knowledgeable physicians were more likely to make treatment changes, either because they followed up their patients more effectively or their patients were more motivated to report problems. Even after adjustment for therapy change, medical management ability, particularly clinical decision making, provided additional benefits, accounting for 15.8% of persistence in the first 6 months. Patients expect physicians to explain the rationale and benefits of hypertension treatment and adverse effects.49 More knowledgeable physicians may be more likely to provide relevant information to patients and to monitor and intervene for side effects. It is also possible that physicians with better clinical decision-making ability incorporate patient and family preferences into the treatment decision-making process—aspects of treatment decision making that have been shown to improve persistence.22,25,26,50 Indeed, during the past decade, many medical schools and specialty training programs have incorporated patient-centered case-based learning into the curriculum to enhance clinical decision-making abilities and the ability to involve patients in the decision-making process.51,52 This also may be one reason why physicians with better communication skills, particularly in history taking, had a lower risk of nonpersistence; they would be able to elicit patient preferences more effectively and incorporate this information into treatment decision making.

This study highlights several important avenues for future research. First, the hypothesis that physicians with better clinical decision-making and data collection skills are more likely to incorporate patient preferences into the treatment decision-making process needs to be tested. If true, training programs could improve the ability of physicians to manage chronic conditions by ensuring that these aspects of management are systematically incorporated into undergraduate and postgraduate medical training. For practicing physicians, continuing medical education interventions aimed at enhancing communication and clinical decision making should be evaluated to determine whether improving these skill sets will lead to better patient treatment adherence. However, the development and evaluation of tools to support clinical decision making and medication monitoring in the practice environment will likely be the most fruitful. In particular, new information technologies that can be integrated with the electronic medical record may have the greatest promise for enhancing drug- and patient-specific follow-up of adverse effects and treatment effectiveness. Technologies such as computerized decision support, community drug profiles from retail pharmacies, and follow-up monitoring tools such as interactive voice recording approaches have been shown to be effective in management of some chronic conditions,53-57 and their increased use in hypertension treatment should improve patient adherence and, ultimately, clinical outcome.

Correspondence: Robyn Tamblyn, PhD, Department of Medicine, McGill University, 1140 Pine Ave W, Montreal, QC, H3A 1A3 Canada (robyn.tamblyn@mcgill.ca).

Accepted for Publication: November 30, 2009.

Author Contributions:Study concept and design: Tamblyn, Abrahamowicz, Dauphinee, Jacques, Klass, Winslade, and Buckeridge. Acquisition of data: Tamblyn, Wenghofer, Jacques, Smee, Girard, and Buckeridge. Analysis and interpretation of data: Tamblyn, Abrahamowicz, Jacques, Eguale, Girard, Bartman, Buckeridge, and Hanley. Drafting of the manuscript: Tamblyn, Dauphinee, and Bartman. Critical revision of the manuscript for important intellectual content: Tamblyn, Abrahamowicz, Dauphinee, Wenghofer, Jacques, Klass, Smee, Eguale, Winslade, Girard, Buckeridge, and Hanley. Statistical analysis: Tamblyn, Abrahamowicz, Eguale, Girard, and Hanley. Obtained funding: Tamblyn and Dauphinee. Administrative, technical, and material support: Tamblyn, Wenghofer, Jacques, Klass, Smee, Winslade, Bartman, and Buckeridge. Study supervision: Tamblyn, Dauphinee, and Buckeridge.

Financial Disclosure: None reported.

Funding/Support: This study was supported by the Medical Council of Canada, Canadian Institutes for Health Research.

References
1.
Daar  ASSinger  PAPersad  DL  et al.  Grand challenges in chronic non-communicable diseases.  Nature 2007;450 (7169) 494- 496PubMedGoogle Scholar
2.
Heron  MHoyert  DXu  JScott  C Deaths: preliminary data for 2006.  Natl Vital Stat Rep 2008;56 (12) 1- 52Google Scholar
3.
Ford  ESAjani  UACroft  JB  et al.  Explaining the decrease in U.S. deaths from coronary disease, 1980-2000.  N Engl J Med 2007;356 (23) 2388- 2398PubMedGoogle Scholar
4.
Morris  ABLi  JKroenke  KBruner-England  TEYoung  JMMurray  MD Factors associated with drug adherence and blood pressure control in patients with hypertension.  Pharmacotherapy 2006;26 (4) 483- 492PubMedGoogle Scholar
5.
Perreault  SLamarre  DBlais  L  et al.  Persistence with treatment in newly treated middle-aged patients with essential hypertension.  Ann Pharmacother 2005;39 (9) 1401- 1408PubMedGoogle Scholar
6.
Bourgault  CSenecal  MBrisson  MMarentette  MAGregoire  JP Persistence and discontinuation patterns of antihypertensive therapy among newly treated patients: a population-based study.  J Hum Hypertens 2005;19 (8) 607- 613PubMedGoogle Scholar
7.
Chou  CCLee  MSKe  CHChuang  MH Factors influencing the switch in the use of antihypertensive medications.  Int J Clin Pract 2005;59 (1) 85- 91PubMedGoogle Scholar
8.
Mazzaglia  GMantovani  LGSturkenboom  MC  et al.  Patterns of persistence with antihypertensive medications in newly diagnosed hypertensive patients in Italy: a retrospective cohort study in primary care.  J Hypertens 2005;23 (11) 2093- 2100PubMedGoogle Scholar
9.
Rasmussen  JNChong  AAlter  DA Relationship between adherence to evidence-based pharmacotherapy and long-term mortality after acute myocardial infarction.  JAMA 2007;297 (2) 177- 186PubMedGoogle Scholar
10.
Grégoire  JPMoisan  JGuibert  R  et al.  Determinants of discontinuation of new courses of antihypertensive medications.  J Clin Epidemiol 2002;55 (7) 728- 735PubMedGoogle Scholar
11.
Caro  JJSpeckman  JLSalas  MRaggio  GJackson  JD Effect of initial drug choice on persistence with antihypertensive therapy: the importance of actual practice data.  CMAJ 1999;160 (1) 41- 46PubMedGoogle Scholar
12.
Heisler  MHogan  MMHofer  TPSchmittdiel  JAPladevall  MKerr  EA When more is not better: treatment intensification among hypertensive patients with poor medication adherence.  Circulation 2008;117 (22) 2884- 2892PubMedGoogle Scholar
13.
Banning  M Older people and adherence with medication: a review of the literature.  Int J Nurs Stud 2008;45 (10) 1550- 1561PubMedGoogle Scholar
14.
DiMatteo  MR Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research.  Med Care 2004;42 (3) 200- 209PubMedGoogle Scholar
15.
Schroeder  KFahey  TEbrahim  S Interventions for improving adherence to treatment in patients with high blood pressure in ambulatory settings.  Cochrane Database Syst Rev 2004; (2) CD004804PubMed10.1002/14651858.CD004804Google Scholar
16.
Ambrosioni  ELeonetti  GPessina  ACRappelli  ATrimarco  BZanchetti  AScientific Committee of the Italian Pharmacoepidemiological Survey on Antihypertensive Therapy, Patterns of hypertension management in Italy: results of a pharmacoepidemiological survey on antihypertensive therapy.  J Hypertens 2000;18 (11) 1691- 1699PubMedGoogle Scholar
17.
Wright  JMMusini  VM First-line drugs for hypertension.  Cochrane Database Syst Rev 2009; (3) CD001841PubMed10.1002/14651858.CD001841.pub2Google Scholar
18.
Bokhour  BGBerlowitz  DRLong  JAKressin  NR How do providers assess antihypertensive medication adherence in medical encounters?  J Gen Intern Med 2006;21 (6) 577- 583PubMedGoogle Scholar
19.
Tarn  DMHeritage  JPaterniti  DAHays  RDKravitz  RLWenger  NS Physician communication when prescribing new medications.  Arch Intern Med 2006;166 (17) 1855- 1862PubMedGoogle Scholar
20.
Martin  RMKerry  SMHilton  SR Initial treatment choices, second-line therapy, and reasons for stopping medication in the treatment of hypertension by general practitioners in England, Scotland and Wales: 1990-1995.  Pharmacoepidemiol Drug Saf 1997;6 (4) 253- 261PubMedGoogle Scholar
21.
Gandhi  TKWeingart  SNBorus  J  et al.  Adverse drug events in ambulatory care.  N Engl J Med 2003;348 (16) 1556- 1564PubMedGoogle Scholar
22.
Wilson  IBSchoen  CNeuman  P  et al.  Physician-patient communication about prescription medication nonadherence: a 50-state study of America's seniors.  J Gen Intern Med 2007;22 (1) 6- 12PubMedGoogle Scholar
23.
Heisler  MCole  IWeir  DKerr  EAHayward  RA Does physician communication influence older patients' diabetes self-management and glycemic control? results from the Health and Retirement Study (HRS).  J Gerontol A Biol Sci Med Sci 2007;62 (12) 1435- 1442PubMedGoogle Scholar
24.
Golin  CDiMatteo  RDuan  NLeake  BGelberg  L Impoverished diabetic patients whose doctors facilitate their participation in medical decision making are more satisfied with their care.  J Gen Intern Med 2002;17 (11) 857- 866PubMedGoogle Scholar
25.
Piette  JDHeisler  MKrein  SKerr  EA The role of patient-physician trust in moderating medication nonadherence due to cost pressures.  Arch Intern Med 2005;165 (15) 1749- 1755PubMedGoogle Scholar
26.
Schillinger  DPiette  JGrumbach  K  et al.  Closing the loop: physician communication with diabetic patients who have low health literacy.  Arch Intern Med 2003;163 (1) 83- 90PubMedGoogle Scholar
27.
Hulka  BSCassel  JCKupper  LLBurdette  JA Communication, compliance, and concordance between physicians and patients with prescribed medications.  Am J Public Health 1976;66 (9) 847- 853PubMedGoogle Scholar
28.
DiMatteo  MR Patient adherence to pharmacotherapy: the importance of effective communication.  Formulary 1995;30 (10) 596- 598, 601-602, 605PubMedGoogle Scholar
29.
Haq  CSteele  DJMarchand  LSeibert  CBrody  D Integrating the art and science of medical practice: innovations in teaching medical communication skills.  Fam Med 2004;36 ((suppl)) S43- S50PubMedGoogle Scholar
30.
Garg  AXAdhikari  NKMcDonald  H  et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.  JAMA 2005;293 (10) 1223- 1238PubMedGoogle Scholar
31.
Reznick  RKBlackmore  DDauphinee  WDRothman  AISmee  S Large-scale high-stakes testing with an OSCE: report from the Medical Council of Canada.  Acad Med 1996;71 (1) ((suppl)) S19- S21PubMedGoogle Scholar
32.
Wenghofer  EKlass  DAbrahamowicz  M  et al.  Doctor scores on national qualifying examinations predict quality of care in future practice.  Med Educ 2009;43 (12) 1166- 1173PubMedGoogle Scholar
33.
Tamblyn  RAbrahamowicz  MDauphinee  D  et al.  Physician scores on a national clinical skills examination as predictors of complaints to medical regulatory authorities.  JAMA 2007;298 (9) 993- 1001PubMedGoogle Scholar
34.
Tamblyn  RAbrahamowicz  MDauphinee  WD  et al.  Association between licensure examination scores and practice in primary care.  JAMA 2002;288 (23) 3019- 3026PubMedGoogle Scholar
35.
Regie de l’assurance-maladie du Quebec, Statistiques Annuelles.  Quebec, QC Regie de l’assurance-maladie du Quebec2000;Report ISBN 2-550-30856-5
36.
Sikka  RXia  FAubert  RE Estimating medication persistency using administrative claims data.  Am J Manag Care 2005;11 (7) 449- 457PubMedGoogle Scholar
37.
Steiner  JFProchazka  AV The assessment of refill compliance using pharmacy records: methods, validity, and applications.  J Clin Epidemiol 1997;50 (1) 105- 116PubMedGoogle Scholar
38.
Choo  PWRand  CSInui  TS  et al.  Validation of patient reports, automated pharmacy records, and pill counts with electronic monitoring of adherence to antihypertensive therapy.  Med Care 1999;37 (9) 846- 857PubMedGoogle Scholar
39.
Medical Council of Canada, Clinical stations.  Medical Council of Canada Web site. 2009 http://www.mcc.ca/en/exams/qe2/clinical_stations.shtml. Accessed June 2005Google Scholar
40.
Mandin  HDauphinee  WD Conceptual guidelines for developing and maintaining curriculum and examination objectives: the experience of the Medical Council of Canada.  Acad Med 2000;75 (10) 1031- 1037PubMedGoogle Scholar
41.
Page  GBordage  GAllen  T Developing key-feature problems and examinations to assess clinical decision-making skills.  Acad Med 1995;70 (3) 194- 201PubMedGoogle Scholar
42.
Tamblyn  RLavoie  GPetrella  LMonette  J The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Quebec.  J Clin Epidemiol 1995;48 (8) 999- 1009PubMedGoogle Scholar
43.
Tamblyn  RLaprise  RHanley  JA  et al.  Adverse events associated with prescription drug cost-sharing among poor and elderly persons.  JAMA 2001;285 (4) 421- 429PubMedGoogle Scholar
44.
Charlson  MEPompei  PAles  KLMacKenzie  CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis 1987;40 (5) 373- 383PubMedGoogle Scholar
45.
Zeger  SLLiang  KYAlbert  PS Models for longitudinal data: a generalized estimating equation approach.  Biometrics 1988;44 (4) 1049- 1060PubMedGoogle Scholar
46.
Miettinen  OS Proportion of disease caused or prevented by a given exposure, trait or intervention.  Am J Epidemiol 1974;99 (5) 325- 332PubMedGoogle Scholar
47.
Wilchesky  MTamblyn  RMHuang  A Validation of diagnostic codes within medical services claims.  J Clin Epidemiol 2004;57 (2) 131- 141PubMedGoogle Scholar
48.
Rudd  PMiller  NHKaufman  J  et al.  Nurse management for hypertension: a systems approach.  Am J Hypertens 2004;17 (10) 921- 927PubMedGoogle Scholar
49.
Goff  SLMazor  KMMeterko  VDodd  KSabin  J Patients' beliefs and preferences regarding doctors' medication recommendations.  J Gen Intern Med 2008;23 (3) 236- 241PubMedGoogle Scholar
50.
Hauber  ABMohamed  AFJohnson  FRFalvey  H Treatment preferences and medication adherence of people with type 2 diabetes using oral glucose-lowering agents.  Diabet Med 2009;26 (4) 416- 424PubMedGoogle Scholar
51.
Chessare  JB Teaching clinical decision-making to pediatric residents in an era of managed care.  Pediatrics 1998;101 (4, pt 2) 762- 767PubMedGoogle Scholar
52.
Ogur  BHirsh  DKrupat  EBor  D The Harvard Medical School-Cambridge integrated clerkship: an innovative model of clinical education.  Acad Med 2007;82 (4) 397- 404PubMedGoogle Scholar
53.
Reidel  KTamblyn  RPatel  VHuang  A Pilot study of an interactive voice response system to improve medication refill compliance.  BMC Med Inform Decis Mak 2008;8 (1) 46PubMedGoogle Scholar
54.
Green  BBRalston  JDFishman  PA  et al.  Electronic communications and home blood pressure monitoring (e-BP) study: design, delivery, and evaluation framework.  Contemp Clin Trials 2008;29 (3) 376- 395PubMedGoogle Scholar
55.
Fursse  JClarke  MJones  RKhemka  SFindlay  G Early experience in using telemonitoring for the management of chronic disease in primary care.  J Telemed Telecare 2008;14 (3) 122- 124PubMedGoogle Scholar
56.
Piette  JDWeinberger  MKraemer  FBMcPhee  SJ Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs Health Care System: a randomized controlled trial.  Diabetes Care 2001;24 (2) 202- 208PubMedGoogle Scholar
57.
Oake  NJennings  Avan Walraven  CForster  AJ Interactive voice response systems for improving delivery of ambulatory care.  Am J Manag Care 2009;15 (6) 383- 391PubMedGoogle Scholar
×