Problem list completeness in electronic health records: A multi-site study and assessment of success factors.

OBJECTIVE: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. METHODS: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation>=7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. RESULTS: Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. DISCUSSION: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. CONCLUSION: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

Telemedicine-based digital retinal imaging vs standard ophthalmologic evaluation for the assessment of diabetic retinopathy.

OBJECTIVE: To study the cost benefit analysis of using a telemedicine-based digital retinal imaging evaluation compared to conventional ophthalmologic fundus examination of diabetic patients for diabetic retinopathy. METHODS: In this study, diabetic patients from Community Health Center, Inc. (CHCI), a large multi-site Federally Qualified Health Center) were evaluated by teleophthalmology using the Canon CR-1 nonmydriatic fundus camera. Digital images were acquired in the CHCI offices and saved on the EyePACS server network. The images were later evaluated by retinal specialists at the Yale Eye Center, Yale University Department of Ophthalmology and Visual Science. The costs for the standard of care ophthalmic examinations were calculated based on 2009 Medicaid reimbursement rates. The process of telemedicine-based diagnosis was based on a take-store-forward-visualize system. The cost of telemedicine-based digital retinal imaging examination included cost for devices, training, annual costs and a transportation fee. Current Medicaid reimbursement, transportation, and staff labor costs were used to calculate the conventional retinal examination cost as a comparison. RESULTS: Among the 611 patients digital retinal images screened in the first year of this program and for whom data are available, 166 (27.2%) cases of diabetic retinopathy were identified. Seventy-five (12.3%) patients screened positive with clinically significant disease and were referred for further ophthalmological evaluation and treatment. The primary direct cost of the telemedicine was $3.80, $15.00, $17.60, $1.50, and $2.50 per patient for medical assistant, ophthalmologist, capital cost (Equipment + Training), equipment maintenance, and transportation fee, respectively. The total cost in the telemedicine-based digital retinal imaging and evaluation was $40.40. The cost of conventional retinal examination was $8.70, $65.30, and $3.80 per patients for round-trip transportation, 2009 national Medicaid Physician Fee Schedule allowable for bilateral eye examination, and medical assistant personnel, respectively. The total costs of conventional fundus examination were $77.80. An additional conventional ophthalmologic retinal examination was required for 75 (12.3%) patients with clinically significant disease on telemedicine evaluation, which involves an averaged additional cost of $ 9.55 per patient for all the patients in the study. If the cost of subsequent examination was added, the total cost of telemedicine-based digital fundus imaging was $49.95 per patient in our group of 611 patients evaluated. CONCLUSIONS: Our cost analysis indicates that telemedicine-based diabetic retinopathy screening cost less ($49.95 vs $77.80) than conventional retinal examination and the telemedicine-based digital retinal imaging examination has the potential to provide an alternative method with greater convenience and access for the remote and indigent populations. Diabetes mellitus and diabetic retinopathy are growing problems in the United States and worldwide. Large scale adoption of telemedicine should be encouraged as a means toward providing improved access, increasing compliance with annual evaluation, at a low cost for patients with diabetes with direct access to an eye care specialist.