The Lagging U.S. Health Care Information Technology Infrastructure: Parallel Challenges for Plastic Surgery
Bibliographic record
Abstract
A recent USA Today article reported that the United States trails other nations in high-speed Internet access, and warned that catching up to the rest of the world may not happen unless governmental policy implements change.1 According to this article, the median download speed in the United States is 1.97 megabits per second, far behind that of many other countries (Table 1). The Federal Communications Commission has designated that download speeds of 200 kb per second or faster are “high speed,” but this speed would not be recognized as “broadband” in many countries. That the country with the largest economy in the world has one of the slowest Internet speeds is alarming.Table 1: Download Speeds by Country or StateEqually alarming are the findings of a study commissioned by The Commonwealth Fund. The 2006 Commonwealth Fund International Health Policy Survey of Primary Care Physicians reported wide gaps between the leading and lagging countries in clinical information systems and payment incentives.2 The study shows that U.S. primary care physicians are among the least likely to have extensive clinical information systems or incentives targeted on quality and the most likely to report that their patients have difficulty paying for care. In a similar fashion to the USA Today article, this study concludes that sweeping policy changes in the U.S. health-care system may be necessary to overcome the documented performance gaps. DETAILS OF THE REPORT The report focuses on primary care physicians in seven countries: Australia, Canada, Germany, The Netherlands, New Zealand, the United Kingdom, and the United States. It begins by reporting that many countries are instituting public health policies that hold primary care practices accountable for managing chronic conditions and meeting clinical standards. Financial incentives are being designed and implemented for practice redesign, emphasizing the following items: Improved information technology systems Improved team approaches to patient care Patient safety, as achieved through better use of technology Increased sharing of patient data and coordination among health-care providers Patient-centered medical care and record keeping Efficiency through improved speed and diminished redundancy Diversity in the way insurance pays for patient care is noted. The United Kingdom pays for care on a capitation basis, in which the patient pays little or no fee for primary health care. The Netherlands has a mixed system, based on capitation and fee for service. Canada covers doctor visits entirely, but the patient is responsible for his or her medication costs to varying degrees. Australia, Germany, and New Zealand have mixed systems. Of concern, in the United States alone, a high percentage of the population has no insurance; when patients do have insurance, they often bear high deductible fees and other costs for health care. INFORMATION TECHNOLOGY, SHARING, AND PATIENT RECORD COORDINATION Primary care practices’ use of information technology and information-sharing systems showed major discrepancies among the seven countries studied. The most widespread use of information technology and data sharing was found in Australia, The Netherlands, New Zealand, and the United Kingdom. Germany ranked in the middle, with Canada and the United States far behind. Fully 98 percent of primary care practices in The Netherlands utilize an electronic medical records system, whereas only 28 percent do in the United States. These systems: Automatically alert doctors to potential drug dosage interactions; Automatically prompt doctors to provide test results to patients; and Automatically send patient follow-up and appointment reminders. In the four leading countries, between 50 and 90 percent of primary care physicians have electronic medical records systems implemented to provide the above data; by contrast, fewer than 25 percent of U.S. and Canadian practices have systems in place to provide these functions. More than 60 percent of U.S. and Canadian practices have no system (manual or otherwise) to provide these functions for their patients. In parallel with the findings about electronic medical records systems and information technology implementation, U.S. and Canadian doctors reported the highest incidence of not hearing the results of referrals to other doctors. Also, U.S. and Canadian doctors reported the greatest incidence of medical records sometimes or often not being available at the time of the patient’s appointment. CHRONIC ILLNESSES, ACCESS TO PRIMARY CARE, PRESCRIPTIONS, AND QUALITY INCENTIVES The United States and Canada were the least prepared among the seven countries to provide optimal care for chronically ill patients with multiple illnesses, with only 68 percent of U.S. practices indicating the ability to do so. Providing written self-care instructions to patients with multiple illnesses was conducted most effectively by German practices (63 percent) but much less frequently among the other six countries studied. After-hours coverage arrangements again showed the Canadian and U.S. practices lagging behind. Half of Canadian practices and three of five U.S. practices indicated they had no after-hours coverage arrangements, in contrast to fewer than 25 percent of practices in the other countries studied. Not surprisingly, use of local emergency rooms was highest among Canadian and U.S. patients for care that could have been provided had a regular doctor been available. The United States, the only country studied among the group of seven without universal health insurance and with increasingly high deductible payments for patients with insurance, stands out in regard to medication costs. More than half of the U.S. primary care physicians reported that their patients “often” had difficulty paying for medications. They also indicated that many of their patients experienced difficulty paying for care. Nonfinancial incentives to improve patient care and safety—in the form of physicians routinely receiving patient survey data and results of clinical outcomes trials—were mixed. A majority of doctors in the United Kingdom, Germany, and New Zealand indicated they did receive results of patient surveys as well as clinical outcomes results. The U.K. doctors led the group in this regard; nearly all doctors reported receiving such data, evidence of the national efforts to include patients’ experiences as outcome indicators. As a result, the United Kingdom has developed a battery of evidence-based clinical guidelines and patient surveys. As of yet, the United States and Canada do not have financial payment initiatives in place that focus on physicians and primary care. Instead, the United States has relied on private insurance, employer, and state initiatives to explore and implement payment incentives and payment methods. IMPLICATIONS FOR PLASTIC SURGERY It is important to emphasize that the Commonwealth study is limited in that it focuses on primary care physicians in a limited number of countries. Data from this study cannot be directly transferred to the plastic surgery community because it differs in fundamental ways from primary care physicians. The report does indicate, however, that U.S. medicine lags behind other countries in terms of overall information technology infrastructure, cohesiveness of patient data transfer, and an overall policy of improving physician performance and patient payment structures. These are important points to consider. Both the United States and Canada lag in information capacity; interestingly, both countries have relied primarily on market-driven, individual care systems or individual physician investment to build information technology capability. In the other countries studied, collective efforts to support primary care have provided increases in information technology capacity to a broad range of solo and small group practices. Of note, only the United States appears to lack a national plan to support expanded primary care information technology development. Of the countries studied, the United States outspends the rest in per capita health-care costs (Table 2). Despite this, primary care physicians in the United States are more limited than those in other leading countries in information capacity, shared performance reporting, and development of evidence-based quality metrics. Despite having among the best-trained and skilled doctors in the world, the United States lags behind in overall provision of primary health care. Additional evidence of this is that the United States is not a leader in clinical outcomes and often ranks low among industrialized countries for mortality rates in diseases that are amenable to medical care. In a 2005 survey, the United States often ranked last or tied for last on issues of patient safety, access, and care efficiency.3Table 2: Per Capita Health-Care SpendingFor the U.S. plastic surgeon, development of information technology infrastructure is critical for the advancement of our specialty. Surgical training and technique and innovations in medical technology in the United States are among the best in the world. However, as all of you are aware, the practice of medicine and plastic surgery is more than time in the operating room! Effective medical care and plastic surgery are situated in a larger medical infrastructure context, which is, sad to say, falling behind. Until (or unless) government-led initiatives change this landscape, it falls to the individual plastic surgery practices, institutions, and societies to invest in the hardware, software, training, and management skills necessary to implement effective change. Evidence-based patient outcomes instruments for evaluating physician performance will also assist in the improvement of patient safety and enhance effectiveness overall. Such metrics and instruments are already being developed. That is all the more reason for our major national society—the American Society of Plastic Surgeons—to provide a streamlined pathway for day-to-day patient outcome management and guidelines for optimizing electronic medical records systems that can be used by all practicing plastic surgeons. If we are to advance in our specialty of plastic surgery, we need the information technology infrastructure to do so in our offices, in our research, and in our country. The time to start is long overdue!
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".