Citations

AbstractRationale, aims and objectivesAlthough the condition of low haemoglobin (Hb) levels has been established as a risk factor in the development of coronary artery disease (CAD), it is still a debate particularly in patients with angiographically documented disease. In the present study, we sought to identify the relationship between Hb levels and the presence of CAD.MethodsThe study consisted of 356 consecutive patients referred for elective coronary angiography (CAG). Exclusion criteria included a history of prior MI within last 3 months, presence of neoplastic disorders or any inflammatory diseases or overt diabetes mellitus. Blood samples for haematologic and biochemical measurements were collected on admission following at least 12 hours of overnight fasting. Patients were divided into four groups based on the quartiles of Hb (quartile I < 13.50 g/dL, quartile II 13.50–14.70 g/dL, quartile III 14.71–15.74 g/dL, quartile IV > 15.74 g/dL). Additionally, patients filled out a questionnaire of asking their brief medical histories and baseline characteristics.ResultsLower Hb quartiles were independently related to the presence of CAD in subjects who were referred to elective CAG. The patients with older age [P = 0.008, odds ratio (OR) = 1.042], male gender (P = 0.007, OR = 3.408), in quartile I (P = 0.003, OR = 5.697), in quartile II (P < 0.001, OR = 8.767), in quartile III (P = 0.011, P = 3.076), higher white blood cells count (P = 0.037, OR = 1.208), lower platelet count (P = 0.049, OR = 0.995), condition of current smoker (P = 0.030, OR = 2.548), higher value of fasting glucose (P = 0.014, OR = 1.038), estimated glomerular filtration rate < 60 (mL/min/1.73 m2; P = 0.004, OR = 3.269) were more likely associated with the risk of the presence of CAD.ConclusionsThe present study revealed that lower quartiles of Hb levels were independently related to the presence of CAD in subjects who were referred to elective CAG. Hb levels, which can be measured easily in almost all medical centres, may be considered as a potential predictor for the presence of CAD in patients at high risk for CAD.

Introduction: Collaborative care management (CCM) for the treatment of depression has been shown to be an effective therapy. CCM can be seen as a resource intensive treatment. Early identification of patients who would not be effectively treated with CCM could allow for alteration of therapy or change in modality. Methods: A retrospective case-controlled study used 132 patients with prolonged enrollment (>1 year) in CCM (cases) and 396 randomized CCM patients who achieved remission within 6 months (controls). The hypothesis was that by studying the epidemiology of patients in prolonged care management (PCM), characteristics could be determined to help define this group. Results: With regression modeling, the odds of a patient having PCM at 1 year was highly significant for those unmarried patients (odds ratio [OR] = 1.736, confidence interval [CI] = 1.115-2.703, P = .015) with dysthymia (OR = 2.362, CI = 1.104-5.052, P = .027) and severe depression (OR = 2.856, CI = 1.551-5.260, P = .001). The adjusted baseline Patient Health Questionnaire–9 (PHQ-9) score showed a difference of 16.0 for the cases versus 14.8 for the controls ( P < .001). By 10 weeks, the difference is much larger at (10.7 vs 4.9, P < .001). At 26 weeks, the control group had an adjusted average PHQ-9 score of 2.0, whereas the case group was still elevated at 10.2 ( P < .001). Conclusions: Case-controlled analysis of PCM patients demonstrated independent predictors (such as unmarried status, diagnosis of dysthymia or severe depression), however, no baseline data was of sufficient clarity to suggest changes in clinical practice. The trend of the patient’s PHQ-9 over time was strongly suggestive of allowing differentiation between the groups.

As retail clinics provide a less costly alternative for health care, it would be reasonable to expect an increase in multiple (repeat) retail visits by those patients who may have expenses for receiving primary care. If costs were not a significant factor, then repeat visits should not be significantly different between these patients and those with coverage for primary care visits. The hypothesis for this study was that patients with the potential for out-of-pocket expenses would have a higher frequency of repeat retail clinic visits within 180 days compared to those with primary care coverage. A retrospective chart review was conducted of 5703 patients utilizing a retail clinic in Rochester, Minnesota from January 1, 2009 through June 30, 2009. The first visit to the retail clinic was considered the index visit and the chart was reviewed for repeat retail clinic visits within the next 180 days. Using a multiple logistic regression model, the odds of a pediatric patient ( N =2344) having a repeat retail visit within 180 days of the index visit were not significantly impacted by insurance coverage ( P =0.4209). Of the 3359 adult patients, those with unknown coverage had a 25.6% higher odds ratio of repeat retail clinic visits than those with insurance coverage (odds ratio 1.2557, confidence interval 1.0421–1.5131). This study suggested that when cost is an issue, the adult patient may favor retail clinics for episodic, low-acuity health care. In contrast, the pediatric population did not, suggesting that other factors, such as convenience, may play more of a role in the choice of episodic health care for this age group. ( Population Health Management 2012;15:358–361)

The United States Preventive Services Task Force and the National Osteoporosis Foundation recommend routine osteoporosis screening for women aged 65 years or older. Previous studies have shown that the use of a clinical decision-support tool significantly improves screening rates. In a recently published study, a statistically significant improvement was found in the screening rates for eligible women with use of the tool. To evaluate whether a clinical decision-support tool independently predicts completion of osteoporosis screening tests and to identify predictors of screening completion, we examined the records of 2462 female patients who were eligible for osteoporosis screening but had no prior baseline screening and who were seen in our primary care practices in 2007 and 2008. Patient and provider characteristics and clinic visit type were identified, and their association with screening test completion was statistically analyzed using both univariate and multivariate models. Screening completion rates increased significantly from 2007 to 2008. Factors associated with increased likelihood of screening completion included race, marital status, residence, presence of comorbidity (cancer, rheumatologic disease), and the year and type of visit. Screening was less likely for women aged 80 years or older. The use of a point-of-care decision-support tool not only improved osteoporosis screening rates significantly but appeared to be an independent predictor of screening completion. It potentially can facilitate the systematic and effective delivery of preventive health services to patients in the primary care setting. ( Population Health Management 2011;14:243–247)

The family history is used as a screening tool to identify persons who may be at risk for a heritable disorder. Primary care providers sometimes do not thoroughly gather and document the family history. This pilot study was undertaken to determine whether having a genetic counselor on site at our family medicine clinic 2 days a week for 3 months would improve the quality of the family history field in patient records. We compared 7 elements in the family history field for patients seen before and after the genetic counselor was on site. Documentation of 1 of the 7 elements (major disease) improved significantly after the intervention period ( P = .02). Changing provider behavior with regard to gathering and documenting family history of major disease may be facilitated by tools to help collect the family history and by using the increasing number of available genetic tests.

As medical providers seek new ways to control costs, online visits have begun to receive serious consideration. The purpose of this study was to compare the odds of being a cost outlier during a 6-month period after either an online visit or a standard drop-in visit in a conventional medical office setting. Medical records of primary care patients (both adults and children) seen in a large group practice in Minnesota in 2008 were analyzed for this study. Two groups of patients were studied: those who had an online visit ( N = 390) and a comparison group who had regular office care for same-day, acute visits ( N = 376). Case types were classified as either complex or common, with common being defined as treatment for pinkeye, sore throat, viral illness, bronchitis, or cough. Outliers were defined as patients for whom standard costs exceeded the 75 th percentile during a 6-month period after the index visit. Multiple logistic regression analysis was used to adjust for differences between groups. The percentage of online visitors who were cost outliers was 21.2 (versus 28.5 in the standard visit group). Median standard costs were $161 for online visits and $219 for same-day acute visits. The adjusted odds of being a cost outlier was lower for the online visit group than for the standard visit group (odds ratio [OR] 0.52, 95% confidence interval [95% CI] 0.35–0.77) after adjusting for number of visits in the previous 6 months, age, sex, and case type. Outpatient visits in the previous 6 months were positively related to outlier status (OR 1.23, 95% CI 1.17–1.29). Online visits appeared to reduce medical costs for patients during a 6-month period after the visit. ( Population Health Management 2010;13:59–63)

Open-access or advanced-access scheduling, which opens the clinic calendar to patients without requiring them to schedule far in advance of the visit, is being introduced in primary care for the purpose of improving access. None of the evaluations reported to date have measured differences in actual visits that might be associated with different scheduling systems. The purpose of this study was to compare utilization of visits to primary care providers for patients served by an open-access clinic with utilization patterns of patients served at clinics not using open-access scheduling. We hypothesized that the odds that a continuing patient received more than one primary care visit would be greater in the clinic where open-access scheduling was in use than in comparison clinics. Our study provides mixed support for the hypotheses. After adjustment for case mix, stable chronic patients treated in open-access clinics may sometimes have greater odds of receiving two or more preventive care visits. However, these effects do not occur in all clinics, suggesting that other clinic characteristics may overcome the effects of open-access scheduling.