Predicting Use of Nurse Care Coordination by Older Adults With Chronic Conditions.

To be effective, nurse care coordination must be targeted at individuals who will use the service. The purpose of this study was to identify variables that predicted use of care coordination by primary care patients. Data on the potential predictor variables were obtained from patient interviews, the electronic health record, and an administrative database of 178 adults eligible for care coordination. Use of care coordination was obtained from an administrative database. A multivariable logistic regression model was developed using a bootstrap sampling approach. Variables predicting use of care coordination were dependence in both activities of daily living (ADL) and instrumental activities of daily living (IADL; odds ratio [OR] = 5.30, p = .002), independent for ADL but dependent for IADL (OR = 2.68, p = .01), and number of prescription medications (OR = 1.12, p = .002). Consideration of these variables may improve identification of patients to target for care coordination.

Improving hypertension control in diabetes: a multisite quality improvement project that applies a 3-step care bundle to a chronic disease care model for diabetes with hypertension.

Hypertension in diabetes patients leads to significant morbidity and mortality. Nonetheless blood pressure (BP) control in patients with diabetes remains disappointing. The authors applied a care bundle to decrease the proportion of patients with BP exceeding 130/80. Teams from 4 sites in 3 states (Minnesota, Florida, and Arizona) developed a bundle consisting of a standardized BP process, an order set, and a patient goal. Baseline data were collected in the first 12 weeks, followed by 6 weeks of implementing changes. The final 16 weeks represented the intervention. There was a statistically significant decrease in the proportion of patients with uncontrolled BP in 3 of 4 sites (P < .0001 in all 3 sites demonstrating improvement). There was a statistically significant improvement in the satisfaction survey (P = .0011). Implementing an evidence-based care bundle for hypertension in diabetes mellitus can improve BP outcomes.

Use of a clinical decision support system to increase osteoporosis screening.

BACKGROUND: In 2002, the US Preventive Services Task Force recommended routine osteoporosis screening for women aged 65 years or older. However, studies have indicated that osteoporosis remains underdiagnosed, and various methods such as the use of health information technology have been tried to increase screening rates. We investigated whether we could boost the low rates of bone mineral density testing with implementation of a point-of-care clinical decision support system in our primary care practice. METHODS: We retrospectively reviewed the medical records of female patients eligible for osteoporosis screening who had no prior bone mineral density test who were seen at our primary care practice sites in 2007 or 2008 (before and after implementation of a point-of-care clinical decision support system). RESULTS: Overall, screening rates were 80.1% in 2007 and 84.1% in 2008 (P < 0.001). Of patients who did not have osteoporosis screening before the visit, 5.87% completed the screening after the visit in 2007, compared with 9.79% in 2008 (when the clinical support system was implemented), a 66.7% improvement (P = 0.025). CONCLUSION: Clinical decision support for primary care doctors significantly improved osteoporosis screening rates among eligible women. Carefully designed clinical decision support systems can optimize care delivery, ensuring that important preventive services such as osteoporosis screening for patients at risk for fracture are performed while unnecessary testing is avoided.

Does pre-ordering tests enhance the value of the periodic examination? Study Design - Process implementation with retrospective chart review.

BACKGROUND: To evaluate the value of a pre-ordering process for the pro-active scheduling and completion of appropriate preventive and chronic disease monitoring tests prior to a periodic health examination (PHE). METHODS: A standardized template was developed and used by our nursing staff to identify and schedule appropriate tests prior to the patients PHE. Chart reviews were completed on all 602 PHE visits for a 3-month interval in a primary care setting. A patient satisfaction survey was administered to a convenience sample of the PHE patients. RESULTS: Of all the patients with tests pre-ordered, 87.8% completed the tests. All providers in the division used the process, but some evolved from one template to another over time. Most patients (61%) preferred to get their tests done prior to their PHE appointment. Many of our patients had abnormal test results. With this process, patients were able to benefit from face-to-face discussion of these results directly with their provider. CONCLUSIONS: A pre-order process was successfully implemented to improve the value of the PHE visit in an internal medicine primary care practice using a standardized approach that allowed for provider autonomy. The process was accepted by patients and providers and resulted in improved office efficiency through reduced message handling. Completion of routine tests before the PHE office visit can help facilitate face-to-face discussions about abnormal results and subsequent management that otherwise may only occur by telephone.

Clinical informatics to improve quality of care: a population-based system for patients with diabetes mellitus.

BACKGROUND: The prevalence of diabetes mellitus is increasing in the USA. However, control of intermediate outcome measures remains substandard. Recently, significant emphasis has been placed on the value of electronic medical records and informatics systems to improve the delivery of health care. OBJECTIVE: To determine whether a clinical informatics system improves care of patients with diabetes mellitus. METHODS: In this quality improvement pilot initiative, we identified 48 patients with diabetes mellitus who were due for their annual haemoglobin A1c (HbA1c), low-density lipoprotein (LDL) and microalbumin tests. Through our newly developed clinical informatics initiative, patients were reminded to schedule tests and a physician appointment. Seventy-five patients without reminders served as controls. RESULTS: A significant improvement in LDL control was achieved in the intervention group (35.4% vs 13.3%; P=0.004). The intervention group had a greater percentage of patients who underwent the three tests, and members of this group also showed greater control of haemoglobin A1c, but these differences were not statistically significant. CONCLUSIONS: A clinical informatics system, used to deliver proactive, co-ordinated care to a population of patients with diabetes mellitus, can improve process and also quality outcome measures. Larger studies are needed to confirm these early findings.