Era baru administrasi layanan kesehatan, Rekam medik elektronik
Era baru sistem administrasi kesehatan. Perkembangan IT/TI telah merasuki seluruh sendi kehidupan dan secara masife merubah cara hidup manusia termasuk pada cara bagaimana meningkatkan derajat kesehatan masyarakat. Salah satu bagian dari proses perubahan dalam layanan administrasi oleh adanya TI adalah layanan administrasi kesehatan. Laporan berikut menunjukkan adanya arus besar menuju perubahan yang mendasar pada sistem administrasi layanan kesehatan.
Special Article
Electronic Health Records and Quality of Diabetes Care
Randall D. Cebul, M.D., Thomas E. Love, Ph.D., Anil K. Jain, M.D., and Christopher J. Hebert, M.D.
Incentives to increase adoption and meaningful use of electronic health records (EHRs) anticipate a quality-related financial return.1,2 However, empirical data showing either quality improvement or cost savings from EHR adoption are scarce. Available studies have shown few quality-related advantages of current EHR systems over traditional paper-based medical-record systems.1-5 Projected cost savings are mostly based on models with largely unsupported assumptions about adherence to and the effect of fully functional EHR systems.6,7 Data are particularly scarce on EHR adoption by “priority primary care providers” — health care professionals practicing in small groups and those serving vulnerable populations, as such providers are defined in the Health Information Technology for Economic and Clinical Health (HITECH) Act.8 EHR adoption by such providers is supported by the national network of Health Information Technology Regional Extension Centers.
Innovations in care delivery as specified in the Affordable Care Act, such as accountable care organizations and patient-centered medical homes (PCMHs), also provide incentives for using information most easily obtained through EHR systems.9,10 Data regarding the benefits of PCMHs have come largely from reports by EHR-based organizations,11-13 and these data support the posited links among EHR use, quality improvement, and cost savings. However, these reports did not compare EHR and paper-based systems.
Regional quality-improvement initiatives, such as those supported by the Robert Wood Johnson Foundation’s Aligning Forces for Quality (AF4Q) program,14 by Medicare and state Medicaid initiatives,15,16 and by multistakeholder collaboratives,17 provide an opportunity to evaluate the effectiveness of EHRs and refinements in national payment policy.15,18 In greater Cleveland, one of 16 AF4Q sites nationwide, diverse EHR-based and paper-based ambulatory practices publicly report on the quality and outcomes of care for patients with chronic medical conditions. Regional achievement of diabetes-related standards has been reported six times to date. The reported data come from practices with high concentrations of priority primary care providers and allow a comparison of quality standards for EHRs and paper records, after adjustment for important patient-level attributes. We examined the independent association of EHR use with achievement of quality standards for the care of patients with diabetes.
Methods
Study Design
We analyzed data from a retrospective cohort of primary care practices of seven diverse health care organizations that publicly reported achievement of quality standards for adults with diabetes between July 2007 and June 2010. Data reported here include the most recent yearlong cross section (July 2009 through June 2010) as well as practice-level trends across three years of reports.
Setting and Subjects
The primary care practice partners of Better Health Greater Cleveland (hereafter referred to as Better Health) are responsible for the majority of medical care for people with chronic disease in Cuyahoga County, an urban area in northeastern Ohio with 1.3 million residents; the county includes Cleveland, one of the nation’s poorest large cities, and its affluent suburbs. Participating practices include 21 sites of large not-for-profit health care organizations, 1 of which serves many vulnerable (“safety net”) patients; 12 sites of a large safety-net public hospital system; 1 safety-net practice of a university hospital; and the safety-net practices of all 3 of the county’s federally qualified health centers. Since the program’s inception in 2007, reporting primary care providers have included physicians in general internal medicine, family practice, and medicine–pediatrics. In July 2009, nurse practitioners and other health care professionals with prescription-writing privileges were added to the list of reporting providers. Patients include all adults (18 to 75 years of age) with diabetes who made at least two visits to the same primary care practice during each yearlong measurement interval.
Care and Outcome Standards
Better Health’s Clinical Advisory Committee approved nine quality standards for diabetes, including four standards of care and five standards of intermediate outcomes. Care standards are reported by standard and as an all-or-none composite19; outcome standards are reported by standard and as a composite indicating achievement of at least four of the five standards. Care standards include receipt of a glycated hemoglobin value, testing for urinary microalbumin or prescription of an angiotensin-converting–enzyme inhibitor or an angiotensin-receptor blocker, an eye examination to screen for diabetic retinopathy, and administration of a pneumococcal vaccination. Intermediate-outcome standards include a glycated hemoglobin value below 8%, a blood pressure below 140/80 mm Hg, a low-density lipoprotein (LDL) cholesterol value below 100 mg per deciliter or documented prescription for a statin medication, a body-mass index (the weight in kilograms divided by the square of the height in meters) below 30, and nonsmoking status. All care and outcome standards pertain to the most recent result documented in the measurement interval, except pneumococcal vaccination (administration at any time is sufficient for meeting this standard).
Covariates
Patient information was collected regarding several sociodemographic variables, including insurance type (Medicare, commercial, Medicaid, or uninsured), race or ethnic group (white, black, Hispanic, or other), age, sex, estimated household income, and educational level, all prespecified for our analyses. Insurance type is the primary insurance reported during the most recent doctor’s visit. Data on race or ethnic group were primarily obtained through self-report. Household income and educational level were estimated by linking each patient’s home address to Census 2000 summaries.
Data Collection and Study Oversight
Clinical practices or health care organizations submitted a unique study code for each patient and health care provider to Better Health’s Data Management Center. EHR-based organizations provided data on all eligible patients. Data from paper-based organizations were gathered by centrally trained chart abstractors for a random sample of patients selected by the Data Management Center. More than 95% of patients in the sample had charts available for review. Each site reviewed summary results for accuracy before publicly reporting data. The MetroHealth System’s Human Privacy Board approved data collection and submission protocols.
Quality-Improvement Assistance
The collaborative supports three types of quality-improvement assistance. First, partner sites receive comparisons with other practices in their organization and regionwide for case mix, achievement of Better Health’s standards, and quality improvement. Practice directors can identify data regarding specific providers. Public reports highlight the top 10% of practice sites with respect to achievement of standards or improvement, by insurance category and overall. Second, Better Health sponsors semiannual daylong summits featuring national speakers and sharing of best practices in quality improvement and management of reported chronic conditions. Third, since mid-2009, all practices have had the opportunity to receive program-sponsored practice coaching. Coaching has principally focused on culture change, workflow redesign, and quality-improvement projects related to specific metrics.