A randomized controlled trial of an online health tool about Down syndrome.

PURPOSE: We sought to determine if a novel online health tool, called Down Syndrome Clinic to You (DSC2U), could improve adherence to national Down syndrome (DS) guidelines. We also sought to determine if primary care providers (PCPs) and caregivers are satisfied with this personalized online health tool. METHODS: In a national, randomized controlled trial of 230 caregivers who had children or dependents with DS without access to a DS specialist, 117 were randomized to receive DSC2U and 113 to receive usual care. The primary outcome was adherence to five health evaluations indicated by national guidelines for DS. DSC2U is completed electronically, in all mobile settings, by caregivers at home. The outputs-personalized checklists-are used during annual wellness visits with the patient's PCP. RESULTS: A total of 213 participants completed a 7-month follow-up evaluation. In the intention-to-treat analysis, the intervention group had a 1.6-fold increase in the number of indicated evaluations that were recommended by the primary care provider or completed compared with controls. Both caregivers and PCPs reported high levels of satisfaction with DSC2U. CONCLUSIONS: DSC2U improved adherence to the national DS health-care guidelines with a novel modality that was highly valued by both caregivers and PCPs.

Assessment of Stakeholder Engagement in a Down Syndrome Research Study.

There is growing recognition of the importance of engaging patients early in the design of research studies. For studies involving patients with intellectual and cognitive disabilities, researchers may consider engaging with family caregivers, health professionals, community advocates, and/or subject matter experts to provide a more multifaceted, surrogate perspective. Evaluating the engagement of these stakeholder groups in research is nascent, and tools are limited. Research studies involving these individuals provide the opportunity to test new methods of measurement of stakeholder engagement in research. We conducted a 3-year research study implementing and evaluating Down Syndrome Clinic to You, an online platform for caregivers of individuals with Down syndrome who do not have access to Down syndrome specialists. We established 3 key stakeholder groups - family caregivers, primary care physicians, and medical/scientific experts in the field - who were involved from grant-writing through preparation of the final report. To assess stakeholder engagement, we utilized the Patient Engagement in Research Scale, a validated instrument originally developed to evaluate patient engagement in arthritis research. Overall, results were suggestive of strong engagement levels by the key stakeholder groups. This study contributes to the limited available literature evaluating measures of stakeholder engagement in research.

Lessons from implementing a combined workflow-informatics system for diabetes management.

Shortcomings surrounding the care of patients with diabetes have been attributed largely to a fragmented, disorganized, and duplicative health care system that focuses more on acute conditions and complications than on managing chronic disease. To address these shortcomings, we developed a diabetes registry population management application to change the way our staff manages patients with diabetes. Use of this new application has helped us coordinate the responsibilities for intervening and monitoring patients in the registry among different users. Our experiences using this combined workflow-informatics intervention system suggest that integrating a chronic disease registry into clinical workflow for the treatment of chronic conditions creates a useful and efficient tool for managing disease.

A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP).

OBJECTIVE: Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We created diabetic patient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181). RESULTS: Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites. CONCLUSIONS: Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required.

A rheumatology-specific informatics-based application with a disease activity calculator.

OBJECTIVE: To design a rheumatology-specific tool with a disease activity calculator integrated into the electronic medical records (EMRs) at our institution and assess physicians' attitudes toward the use of this tool. METHODS: The Rheumatology OnCall (ROC) application culls rheumatology-pertinent data from our institution's laboratory, microbiology, pathology, radiology, and pharmacy information systems. Attending rheumatologists and rheumatology fellows accessed the ROC and disease activity calculator during outpatient visits at the time of the clinical encounter. RESULTS: During the 12-week study period, 15 physicians used the ROC application and the disease activity calculator during 474 and 429 outpatient clinic visits, respectively. In weekly survey responses, physicians reported that use of the ROC interface improved patient care in 140 (78%) of 179 visits, and that the Disease Activity Score in 28 joints (DAS28) results at the time of the visit would not have changed patient management in 157 (88%) of these, although seeing a trend in DAS28 was useful in 149 (96%) of 156 visits. At the study's conclusion, most physicians reported that the ROC application was useful (11 of 12 physicians) and that seeing a trend in DAS28 improved daily patient care (12 of 13 physicians). CONCLUSION: The ROC application is useful in daily rheumatologic care, and the disease activity calculator facilitates management of patients with rheumatoid arthritis. However, widespread acceptance and use of such tools depend upon the general acceptance of and access to EMRs in the clinical setting. The utility of the disease activity calculator may be limited by the lack of available acute-phase reactant results at the time of the clinical encounter.

Physician ability to assess rheumatoid arthritis disease activity using an electronic medical record-based disease activity calculator.

OBJECTIVE: To assess physicians' concordance with Disease Activity Score in 28 joints (DAS28) categories calculated by an electronic medical record (EMR)-embedded disease activity calculator, as well as attitudes toward this application. METHODS: Fifteen rheumatologists used the EMR-embedded disease activity calculator to predict a rheumatoid arthritis (RA) DAS28 disease activity category at the time of each clinical encounter. RESULTS: Physician-predicted DAS28 disease activity categories ranged from high (>5.1, 15% of cohort, 66 of 429 patient visits) to moderate (>3.2-5.1, 21% of cohort, 90 of 429 patient visits) to low (2.6-3.2, 29% of cohort, 123 of 429 patient visits) to remission (<2.6, 35% of cohort, 150 of 429 patient visits). Overall concordance between calculated DAS28 results and physician-predicted RA disease activity was 64%. Using either the physician-predicted or the calculated DAS28 category as the gold standard, accuracy was greatest for patients in remission (75% and 88% accuracy, respectively) and those with high disease activity (68% and 79% accuracy, respectively), and less for patients with moderate (48% and 62% accuracy, respectively) or low disease activity (62% and 31% accuracy, respectively). CONCLUSION: Accurate physician prediction of DAS28 remission and high disease activity categories, even without immediate availability of the erythrocyte sedimentation rate or the C-reactive protein level at the time of the visit, may be used to guide quantitatively driven outpatient RA management.

Cost of an informatics-based diabetes management program.

OBJECTIVES: The relatively high cost of information technology systems may be a barrier to hospitals thinking of adopting this technology. The experiences of early adopters may facilitate decision making for hospitals less able to risk their limited resources. This study identifies the costs to design, develop, implement, and operate an innovative informatics-based registry and disease management system (POPMAN) to manage type 2 diabetes in a primary care setting. METHODS: The various cost components of POPMAN were systematically identified and collected. RESULTS: POPMAN cost 450,000 dollars to develop and operate over 3.5 years (1999-2003). Approximately 250,000 dollars of these costs are one-time expenditures or sunk costs. Annual operating costs are expected to range from 90,000 dollars to 110,000 dollars translating to approximately 90 dollars per patient for a 1,200 patient registry. CONCLUSIONS: The cost of POPMAN is comparable to the costs of other quality-improving interventions for patients with diabetes. Modifications to POPMAN for adaptation to other chronic diseases or to interface with new electronic medical record systems will require additional investment but should not be as high as initial development costs. POPMAN provides a means of tracking progress against negotiated quality targets, allowing hospitals to negotiate pay for performance incentives with insurers that may exceed the annual operating cost of POPMAN. As a result, the quality of care of patients with diabetes through use of POPMAN could be improved at a minimal net cost to hospitals.