To investigate the relation between physician and patient behaviour, we electronically accessed complete vaccination and screening records for primary care physicians who worked and were patients in Clalit Health Services (CHS), the largest health maintenance organization in Israel, which covers more than 50% of Israel’s population. We also accessed data for all of these physicians’ adult patients (n
= 1 886 791). We examined 8 prevention-related health quality indicators monitored by CHS as part of a national quality indicator program.7
As part of this program, all primary care physicians are evaluated routinely for their patients’ outcomes. Patients insured by CHS are randomly assigned to a primary care physician at the clinic nearest to their home. Essentially all physicians who work in CHS also have a CHS primary care physician. Patients see only the primary care physician to whom they are assigned, unless their physician is on vacation, the patient is out of town, or in an emergent situation during which their assigned physician is not working. Each primary care physician is evaluated using the quality indicator measures of all of his or her patients. All physicians in CHS are independent practitioners, and the primary care clinics are very small (physicians per practice: median 2, mode 1, range 1–10).
We obtained data from a comprehensive central database in which computerized data for all CHS patients are stored (demographic data, risk factors, disease registry data, pharmacy data, quality indicators and other clinical and administrative data). Data were identified by use of patients’ identification numbers and the primary care physician to whom they were assigned. For each primary care physician, we determined the total number of patients and the percentage of men, patients older than 65 years and patients of low socioeconomic status. We included CHS physicians who had worked for at least 1 year in the same practice, who were insured by CHS and whose practice included at least 500 patients. For each quality indicator, we included primary care physicians who had at least 5 patients eligible for that indicator, providing a cross-sectional measure of concordance between physicians’ and patients’ preventive experiences. This study was approved by the CHS ethics committee.
We included the following 8 prevention-related quality indicators: mammography in women 50–74 years of age; colorectal cancer screening (colonoscopy or fecal occult blood testing) among patents aged 50–74 years; low-density lipoprotein (LDL) measurement every 5 years for patients aged 35–54 and yearly among patients aged 55–74 years; blood pressure measurement every 5 years for patients aged < 40 years, every 2 years for patients 41–54 years, and yearly for patients ≥ 55 years; pneumococcal vaccination among patients with a chronic illness and those aged ≥ 65 years; and annual influenza vaccine among patients with a chronic illness and those aged ≥ 65 years.
For each quality indicator, we identified physicians who had at least 5 patients who met the above criteria, and we compared the percentage of patients who received the preventive intervention for physicians who had or had not received the intervention themselves (compliant v. noncompliant). We used χ2 tests for comparisons between groups. We considered p values less than 0.05 to be significant. We performed multivariable linear regression analyses for clustered data using generalized estimating equations to estimate the association between physician practice characteristics (total no. of patients within the physician’s practice, percentage of male patients, patients > 65 yr, patients of low socioeconomic status). The physician was the unit of analysis, and the practice was the cluster unit. A homogenous correlations matrix was used, because all physicians in each clinic were assumed to be equally correlated on their population properties and compliance with quality indicators. We performed a sensitivity analysis to evaluate the effect of 3 factors in the regression models (no. of patients in the practice, percentage of low socioeconomic status, percentage of patients > 65 yr).