Brooks, J. M., and Fang, G. (2009). “Interpreting treatment-effect estimates with heterogeneity and choice: Simulation model results.” (AHRQ grant HS016094). Clinical Therapeutics 31(4), pp. 902-919.
Health services researchers and clinicians are realizing that the effect of a certain treatment cannot be assumed to be the same for comparable patients receiving it, but that the treatment's effects more often are different across patients with similar diagnoses. The various treatment-effect estimators in use may essentially be identifying different concepts of treatment effect. Based on their results using simulation models, the authors suggest that health services researchers carefully define the model of treatment choice being used before they estimate treatment effect and interpret those estimates using observational data. According to the authors, this study's simulation results support published theories using models of treatment choice with heterogeneous treatment effects. Such models supply the foundation for establishing and interpreting boundaries for results, the reason for the source of instrumental variables, and the theoretical basis for the source of confounding.
Clancy, C. M. (2009, July). “Finding your way: Talking about end-of-life treatment decisions.” (2009, July). AARP Bulletin Today (bulletin.aarp.org). Reprints (AHRQ Publication No. 09-R078) are available from the AHRQ Publications Clearinghouse.
The author discusses how important it is for individuals to create advance directives for health care, legal documents that allow you to convey your decisions about end-of-life care well before they are needed. Fewer than half of severely or terminally ill patients have advance directives in their medical records, according to research sponsored by the Agency for Healthcare Research and Quality. Further, there is greater need for doctors and patients to discuss these topics-as many as three-quarters of physicians whose patients had advance directives did not know that these documents existed, and relatively few patients with advance directives had received input from their doctors in preparing the documents. The form of an advance directive will depend on the State of patient's residence, but may include a living will, a durable power of attorney (or health care proxy), and a do-not-resuscitate order, the author notes.
Clancy, C. M. (2009). “Reengineering hospital discharge: A protocol to improve patient safety, reduce costs, and boost patient satisfaction.” American Journal of Medical Quality 24, pp. 334-346. Reprints (AHRQ Publication No. 09-R082) are available from the AHRQ Publications Clearinghouse.
In this commentary, the author notes that hospital discharge has been a nonstandard process in most hospitals, resulting in substantial costs from unnecessary rehospitalizations (defined as readmission within 30 days of a discharge) and visits to the emergency department (ED). One in five hospitalizations is complicated by an adverse event after discharge, and a similar proportion of Medicare beneficiaries is readmitted within 30 days without having seen a physician for followup care. To address these problems, a program called Project RED (for Reengineered Discharge) was developed by a research team at Boston Medical Center to educate patients about their care needs after discharge from the hospital. The redesigned discharge process uses specially trained registered nurses, called discharge advocates, to help patients arrange followup appointments, confirm medication routines, and understand their diagnoses. A pharmacist calls patients 2 to 4 days after discharge to reinforce the medical plan and to answer their questions. In one study, the 370 patients who participated in Project RED were one-third less likely to be readmitted to the hospital or visit the ED than the 368 patients who did not. The Project RED patients almost all left the hospital with followup appointments. Project RED also saved substantial amounts of money compared with the control group, an average lower cost of $412 per person.
Devine, E. B. (2009, March). “The art of obtaining grants.” (AHRQ grant HS14739). American Journal of Health-System Pharmacy 66(6), pp. 580-587.
The author discusses strategies for researchers to improve their chances at success in obtaining grants, while keeping the effort put into writing the grant proposal to a minimum. The focus is on pharmacy research, although the strategies are applicable to most biomedical research. Specific examples of nongovernmental funding sources are aimed at pharmacy researchers, however. Besides sources of funding, the author discusses whether it is better to start as a coinvestigator on a grant obtained by a more experienced researcher, or to pursue a small grant as a sole principal investigator. Other sections of the article describe writing and submitting grant proposals, what to expect in the grant review process, and how to manage a grant once it has been awarded.
Effken, J. A. and Abbott, P. (2009). “Health IT-enabled care for underserved rural populations: The role of nursing.” (AHRQ Contract No. 290-04-0016). Journal of the American Medical Informatics Association 16(4), pp. 439-445.
The authors of this white paper propose a fundamental transformation in rural health care through the application of information technology (IT). They state that since nurses provide much of the health care in rural communities, the nursing profession should assume leadership roles in using IT to transform rural care. With training, rural nurses can make use of various IT instruments as appropriate (e.g., electronic health records, telehealth and tele-home care, social networking, distributed e-learning, and personal health records) and play a critical role on IT-enabled care management teams for patients in rural communities. Changes are needed in nursing policy, education, practice, and funding if this new model of rural health care is to be achieved. Toward this end, the authors call for development of a partnership of providers, rural nurses, nursing informatics specialists, professional organizations, the health IT industry, and funding bodies.
Ford, D., Zapka, J. G., Gebregziabher, M., and others. (2009). “Investigating critically ill patients' and families' perceptions of likelihood of survival.” (AHRQ grant HS10871). Journal of Palliative Medicine 12(1), pp. 45-52.
The authors surveyed 100 patients treated in an academic medical intensive care unit (MICU) for longer than 3 days, or their surrogates, to study the perception of the chance of survival among these critically ill patients (23 respondents) or their family members (77 respondents). Patient or surrogate perceptions were compared with actual survival and scores on a tool that provides clinical estimates of disease severity (Acute Physiology and Chronic Health Evaluation II). The respondents were more optimistic about the chance of survival than was supported by either actual survival or medical estimates of illness severity. In particular, blacks and those reporting that faith influenced their health decisionmaking were more optimistic when other factors were accounted for, the authors note. Only patients who had been transferred to the MICU after prior hospitalization were less optimistic than indicated by actual survival or illness severity. Clinicians should pay more attention to discussing prognosis and treatment preferences with MICU patients and their families, the authors conclude.
Frisse, M. E. (2009, March). “Health information technology: One step at a time.” (AHRQ Contract No. 290-05-0006). Health Affairs-Web Exclusive, pp. 379-384.
The author of this commentary discusses the potential role of the American Recovery and Reinvestment Act of 2009 in developing health information technology (health IT). He cautions that simply spending more on existing types of systems without improving the focus and operation of existing initiatives may not guarantee improved benefits to society or health outcomes. Despite this, the law provides potential for incremental change, a shift in incentive strategies, and funding for States to migrate toward a common technology architecture, he says. The author cautions that the health IT policy committee and other advisory groups established by this law should strongly consider a policy of restrained incrementalism.
Glance, L. G., Osler, T. M., Mukamel, D. B., and others. (2009, June). “TMPM-ICD9: A trauma mortality prediction model based on ICD-9-CM codes.” (AHRQ grant HS16737). Annals of Surgery 249(6), pp. 1032-1038.
This paper presents an improved approach to predicting deaths from injuries by using a regression model of injury severities. For the past 20 years, the American College of Surgeons has established and maintained the National Trauma Databank (NTDB), which now includes data from 1.5 million patients from 70 percent of the Level I trauma centers in the United States. Mortality estimates have been based on expert consensus-based Abbreviated Injury Scale (AIS) coding of injury severity. To improve the quality and clinical value of the NTDB, a 2008 data standard now mandates use of ICD-9-CM codes to characterize injury diagnoses, replacing AIS for coding anatomic injuries. The authors propose the new model, the Trauma Mortality Prediction Model (TMPM)-ICD9, and compare it with two previous mortality prediction models. The TMPM-ICD9 provided better discrimination and calibration than the older ICD9-based models. Thus, the authors suggest that it should be used in risk-adjusting trauma outcomes when injuries are recorded using ICD-9-CM codes.
Holtrup, J. S., Stommel, M., Corser, W., and Holmes-Rovner, M. (2009, March). “Predictors of smoking cessation and relapse after hospitalization for acute coronary syndrome.” (AHRQ grant HS10531). Journal of Hospital Medicine 4(3), pp. E3-E9.
Being hospitalized for a major heart condition prompts many, but not all, smokers to quit. This paper looked at the factors that predicted whether patients hospitalized with acute coronary syndrome (ACS) quit smoking and were able to remain nonsmokers during followup. The subjects, 136 patients hospitalized with ACS who smoked at the time of admission, were interviewed at baseline (1-4 weeks after hospital discharge) and at 3 and 8 months posthospitalization. The authors found that 33 percent of patients continued to smoke at baseline and at subsequent interviews. Nearly half of the patients (48 percent) had quit smoking at baseline and remained nonsmokers for at least 3 months. Nineteen percent of the patients reported quitting smoking at baseline, but had resumed smoking by the 3- or 8-month interview. Using regression modeling, the authors found that the significant predictors of successful quitting were higher income, no other smokers in the household, and being a lighter smoker. Patients with a history of depression and heavier smokers had higher rates of relapsing. Successful interventions for smoking cessation in ACS patients should include other family members and use specialized methods for heavy smokers, the authors conclude.
Hughes, R. G. and Clancy, C. M. (2009, July-September). “Complexity, bullying, and stress. Analyzing and mitigating a challenging work environment for nurses.” Journal of Nursing Care Quality 24(3), pp. 180-183. Reprints (AHRQ Publication No. 09-R081) are available from the AHRQ Publications Clearinghouse.
Every workplace has its pressures, but these are magnified in the health care environment, which is fast-paced and in which errors can lead to serious harm. Nurses are central to the successful provision of health care, even under conditions that may be chaotic, loud, and confusing, the authors note in this commentary. Specific sources of stress for nurses (and other members of the health care team) include the complexity of care, the presence of bullying, the structure of the workplace, the gap between education and reality, and the impact of the demands of the job on the nurse's personal life. Complexity is inherent in health care processes and technologies, patient needs, and in the health care organizations themselves. The hierarchical nature of many hospital units providing health care can lead to bullying by physicians or administrators, the authors note. Nurses' drive for professional autonomy at work can clash with many physicians' views of themselves as the team leader in providing care, and physician-focused decisionmaking can undercut the empowerment of nurses and other care team members. Nurses often find large discrepancies between their education (especially at the graduate level) and what is expected of them on the clinical unit. This problem and conflicts with the nurses' home life prompt many to leave patient care.
Kern, L. M., Dhopeshwarkar, R., Barron, Y., and others. (2009, July) “Measuring the effects of health information technology on quality of care: A novel set of proposed metrics for electronic quality reporting.” (AHRQ grant HS17067). The Joint Commission Journal on Quality and Patient Safety 35(7), pp. 359-369 [online only].
This paper describes an effort to develop a set of measures for the effects of health information technology, specifically electronic health records (EHR) with health information exchange, on the quality of patient care. No such set of metrics exists at present, so the researchers examined 17 sets of measures to identify a set of metrics that could be retrieved electronically. From more than 1,000 individual quality metrics, the authors and an expert panel narrowed the group down to 18 quality measures. This group of measures dealt with the quality of care for asthma, cardiovascular disease, congestive heart failure, diabetes, medication and allergy documentation, mental health, osteoporosis, and prevention. In addition, the authors and their expert panel developed 14 new measures to address test ordering, medication management, referrals, followup after discharge, and revisits. The novel set of 32 metrics is proposed as suitable for electronic reporting to capture the potential quality effect of EHRs with health information exchange. This metric set may have broad utility as health information technology becomes increasingly common with Federal stimulus and other funds, note the researchers.
Kieckhefer, G. M., Trahms, C. M., Churchill, S. S., and Simpson, J. N. (2009) “Measuring parent-child shared management of chronic illness.” (AHRQ grant HS13384). Pediatric Nursing 35(2) pp. 101-127.
To develop a tool nurses can use in developing family care management plans, the researchers asked 129 parents of children with one or more chronic conditions to fill out a 103-item self-report survey. Their analysis found that parent-child shared management at home of the child's chronic condition(s) progresses through stages as the child grows up. Management shifts from total parental responsibility for the very young child to parental continued involvement in supporting better physiologic control for the adolescent. Based on these results, researchers developed a tool that accurately gauges parents' desires for, knowledge of, and current actions in support of parent-child shared management-data nurses need to individualize care management plans. This tool can also be used to determine where to begin the discussion of parent-child shared management with a family.
Lin, K. W., and Slawson, D. C. (2009, July). “Identifying and using good practice guidelines.” American Family Physician 80(1), pp. 67-69. Reprints (AHRQ Publication No. 09-R079) are available from the AHRQ Publications Clearinghouse.
A good, evidence-based practice guideline can be hard to find among the many guidelines issued by professional organizations, disease advocacy groups, government agencies, and insurance plans. Guidelines issued, even by professional associations, are too often based on expert opinion or consensus, rather than on conclusive evidence, note the authors of this commentary. They suggest that a good practice guideline should be based on a comprehensive and systematic search of the evidence; use a strength-of-recommendation grading system linked to the evidence; use recommendations based on patient-oriented (not disease-oriented) outcomes; be developed through a transparent process that reveals possible conflicts of interest, which could bias the recommendations; and acknowledge situations where clinical decisions are not clear-cut. Most importantly, the test of a good guideline is whether its adoption has been shown to improve patient-oriented outcomes in real-world settings. Finally, the authors encourage clinicians who find a good practice guideline to share it with their colleagues.
Lin, K. W. (2009, July). “[Tips from Other Journals] Simple charts compare health risks for adults.” American Family Physician 80(1), pp. 86-90. Reprints (AHRQ Publication No. 09-R080) are available from the AHRQ Publications Clearinghouse.
The author reprints (with permission) and explains charts, for men and women separately, that give the risk of death from major diseases by age per 1,000 individuals. The data are categorized as death from vascular disease (heart disease, stroke), cancer (lung, colon, prostate for men; lung, breast, colon, ovarian, cervical for women), infection (pneumonia, flu, AIDS), lung disease (chronic obstructive pulmonary disease), or accidents. For each 5-year age point, the risk is listed separately for current smokers and those who never smoked. Although the charts appear to indicate a “protective” effect for smokers from colon cancer (in men older than 65 years) and breast cancer (in women 55 to 70 years old), this is actually the result of smokers dying earlier from other causes of death, the author notes.
Mark, B., Harless, D. W., and Spetz, J. (2009, February). “California minimum-nurse-staffing legislation and nurses' wages.” (AHRQ grant HS10153). Health Affairs-Web Exclusive, pp. W326-W334.
This study used several databases to look at the impact of minimum-nurse-staffing legislation on pay for registered nurses (RNs) and licensed practical nurses, comparing pay before and after the 2004 implementation of the staffing requirements. The researchers found that the growth in real wages for RNs in metropolitan areas of California between 2000 and 2006 was up to 12 percent higher than in comparable areas in other States not implementing minimum nurse staffing. This confirmed the argument made before the legislation passed that the staffing legislation would increase the demand for nurses, and thus increase the wages of RNs. Because of the limitations of different databases (only the National Sample Survey of Registered Nurses, sponsored by the Bureau of Health Professions at the Health Resources and Services Administration, distinguished between nurses working in hospital inpatient and outpatient settings), it is hard to be sure about the true magnitude of the wage differential. In the end, policymakers will have to weigh the potential for wage increases from minimum-nurse-staffing legislation with the potential benefit to quality of care, the authors conclude.
Mayer, M., Beil, H. A., and Allmen, D. (2009). “Distance to care and relative supply among pediatric surgical subspecialties.” (AHRQ grant HS13309). Journal of Pediatric Surgery 44, pp. 483-495.
Little is known about geographic access to pediatric surgical care. The researchers conducted the first study ever to estimate distances to care and relative supply of pediatric surgical specialists in the United States. They used data from the American Medical Association's Physician Masterfile and the Claritas Pop-Facts Database to calculate distances. For five of the seven pediatric surgical specialties studied, approximately 25 percent of the population younger than 18 years of age lives more than a 1-hour drive from a provider. Across pediatric surgical specialties, average distances to the nearest provider ranged from 27.1 miles for pediatric surgery to 100.9 miles for pediatric cardiothoracic surgery. The findings suggest that pediatric surgical specialties may face many of the distributional challenges plaguing pediatric medical subspecialties.
Meyerhoefer, C. D. and Zuvekas, S. H. (2009). “New estimates of the demand for physical and mental health treatment.” Health Economics (Online at www.interscience.wiley.com). Reprints (AHRQ Publication No. 09-R056) are available from the AHRQ Publications Clearinghouse.
Consumer price responsiveness is central to health care reform proposals, but the best available estimates are more than 23 years old. The researchers, using data from the Medical Expenditures Panel Survey, estimated health care demands by calculating expected end-of-year prices and incorporating them into a zero-inflated ordered probit model applied to several overlapping panels of data from 1996 to 2001. Their findings indicate that the price responsiveness of ambulatory mental health treatment has decreased substantially and is now slightly lower than physical health treatment. In general, price responsiveness was greatest among the privately insured population, which represents 58 percent of the overall population. Most importantly, their estimates imply that the demand for outpatient mental health visits has become substantially less price elastic over the last 25 years. The researchers suggest that rapid advances in medical technology and the diffusion of managed care may account for some of this change.
Pitzer, V. E., Viboud, C., Simonse, L., and others. (2009, July). “Demographic variability, vaccination, and the spatiotemporal dynamics of rotavirus epidemics.” Science 325, pp. 290-294. Reprints (AHRQ Publication No. 09-R084) are available from the AHRQ Publications Clearinghouse.
Rotavirus as a leading cause of diarrhea among children in both developed and developing countries has captured the attention of policymakers and vaccine manufacturers in recent years. Rotavirus is transmitted by fecal-oral transmission but adults are typically asymptomatic. In the United States, annual rotavirus activity has started in the Southwest in late fall and ended in the Northeast 3 months later; however, this trend has diminished in recent years. Traveling waves of infections or local environmental drivers cannot account for these patterns. A transmission model calibrated against epidemiological data shows that spatiotemporal variation in birthrate can explain the timing of rotavirus epidemics. The recent large-scale introduction of rotavirus vaccination provides a natural experiment to further test the impact of susceptible recruitment on disease dynamics. The researchers' model predicts a pattern of reduced and lagged epidemics post vaccination, closely matching the observed dynamics.
Poon, E. G., Cusack, C. M., and McGowan, J. J. (2009) September/October). “Evaluating healthcare information technology outside of academia.” (AHRQ Contract No. 290-04-0016). Journal of the American Medical Informatics Association 16(5), pp. 631-636.
The Agency for Healthcare Research and Quality's (AHRQ's) National Resource Center for Health Information Technology (NRC) was formed in 2004 as part of the AHRQ health information technology (IT) portfolio to support the implementation and evaluation efforts of AHRQ health IT grantees. One of the core functions of the NRC was to assist grantees in their evaluation efforts of health IT. The authors discuss the activities of the NRC's Value and Evaluation group in assisting evaluation efforts by grantees and in gathering lessons learned from grantees. These activities included 1-hour tutorials delivered by teleconference; development of a written evaluation toolkit, workshop curricula, and case studies; and holding of “office hours” via teleconference to answer grantee questions. This process led to a structured and quantitative evaluation of evaluation plans submitted by 15 recipients of implementation grants. From this process, the NRC was able to highlight some common challenges experienced by health IT project teams at nonacademic institutions. These problems included inappropriately scoped and resourced evaluation efforts, inappropriate choice of metrics, inadequate planning for data collection and analysis, and lack of consideration of qualitative methodologies.
Rowe, V. T., Blanton, S., and Wolf, S. L. (2009, May-June). “Long-term follow-up after constraint-induced therapy: A case report of a chronic stroke survivor.” (HS37606). American Journal of Occupational Therapy 63, pp. 317-322.
An innovative technique called “constraint-induced therapy” has shown promise for stroke survivors with mild to moderate hemiparesis. This case report describes the long-term maintenance of improvements in impairments, function, and health-related quality of life associated with this therapy in a patient with a partially paralyzed right hand and arm. The constraint involved the wearing of a mitt on the patient's left hand for 90 percent of her waking hours for 14 consecutive days. Training with a rehabilitation specialist was done for an average of 5.5 hours each weekday. Pre- and post-training assessments were conducted around the time of the training, and then 4 and 5 years after the training. Improvements were maintained in reported use and ability of the arm and hand, time to complete functional tasks, and physical aspects of health-related quality of life. The improved upper-extremity function continued over a 5-year period after the therapy, although poststroke fatigue remained an important limiting factor.
Sarkar, U., Wachter, R. M., Schroeder, S. A., and Schillinger, D. (2009, July). “Refocusing the lens: Patient safety in ambulatory chronic disease care.” (AHRQ grants HS17594, and HS17261). The Joint Commission Journal on Quality and Patient Safety 35(7), pp. 377-383.
Ambulatory visits constitute the overwhelming majority of medical care encounters. The authors decided to extend the Chronic Care Model by using theoretical work in patient safety to develop a model for chronic disease safety. To describe the adaptation of this well-established model to ambulatory patient safety, they discuss the community and health system, the productive interactions between health systems and patients and providers, and the effects of patient and provider behavior on chronic disease safety. To elucidate elements of the model, they present a series of case vignettes focusing on health information decentralization, transitions, inadequate health literacy, patient-physician communication, caregiving and medication misuse, and symptom recognition. The authors conclude by making the following points: ambulatory health systems need more surveillance for patient safety problems; providers and policymakers must examine the safety consequences of chronic disease treatment intensifications; and all stakeholders must attend to chronic disease disparities to improve patient safety.
Vasilevskis, E. E., Kuzniewicz, M. W., Cason, B. A., and others. (2009). “Mortality probability model III and simplified acute physiology score II.” (AHRQ grant HS013919). Chest 136(1), pp. 89-101.
Even after adjusting for patient risk factors, intensive care unit (ICU) patients, the hospital's sickest, receive the highest level of resource-intensive care. Significant variation exists in these patients' ICU length of stay (LOS). If risk-adjusted ICU LOSs were to be calculated accurately, a better assessment of ICU performance would be facilitated. To identify the best available ICU LOS risk-adjustment model, researchers compared three mortality or LOS prediction models: (1) the recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; (2) the mortality probability model III at zero hours (MPM0 III); and (3) the simplified acute physiology score (SAPS) II mortality prediction model. They studied 11,295 ICU patients in 35 hospitals in the California Intensive Care Outcomes Project to compare the predictions of these 3 prediction models with actual patient outcomes. The researchers concluded that APACHE IV and MPM0 III were more accurate than SAPS II for prediction of LOS. However, if the cost burden of data collection required by APACHE IV or treatment effect bias is a consideration, the MPM0 III model may be a reasonable alternative.
Weidmer-Ocampo, B., Johansson, P., Dalpoas, D., and others. (2009, August). “Adapting CAHPS® for an American Indian population.”(AHRQ grants HS09204 and HS16980). Journal of Health Care for the Poor and Underserved 20(3), pp. 695-712.
This paper describes the development of a Consumer Assessment of Healthcare Providers and Systems (CAHPS®) American Indian Survey instrument as a true collaborative effort between the Choctaw Nation Health Services (CNHS) and the CAHPS® program. CNHS had asked the CAHPS® program to develop a survey instrument for evaluation of Choctaw patient experiences at the tribe's different Indian Health Service (IHS) clinics in Oklahoma. The IHS had also expressed interest in the CAHPS® program developing culturally appropriate, reliable, and valid survey instruments for use in assessing the different health care experiences of different American Indian tribes. The CAHPS® program is funded and administered by the Agency for Healthcare Research and Quality working with a consortium of public and private organizations. The authors note that this CNHS request was the first opportunity for CAHPS® partners to design and test a survey instrument specifically with and for a traditionally underserved ethnic or linguistic minority population. Results showed the CAHPS® American Indian Survey developed for the Choctaw Nation to be useful for assessing Choctaw patients' perceptions of the care they received in IHS clinics. The CAHPS® program can use this survey as the basis for developing other survey instruments for the IHS to measure quality of care across various health care programs serving different tribes in different parts of the country.
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