Shinyi Wu

Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care

Key Summary Points Health information technology has been shown to improve quality by increasing adherence to guidelines, enhancing disease surveillance, and decreasing medication errors. Much of the evidence on quality improvement relates to primary and secondary preventive care. The major efficiency benefit has been decreased utilization of care. Effect on time utilization is mixed. Empirically measured cost data are limited and inconclusive. Most of the high-quality literature regarding multifunctional health information technology systems comes from 4 benchmark research institutions. Little evidence is available on the effect of multifunctional commercially developed systems. Little evidence is available on interoperability and consumer health information technology. A major limitation of the literature is its generalizability. Health care experts, policymakers, payers, and consumers consider health information technologies, such as electronic health records and computerized provider order entry, to be critical to transforming the health care industry (1-7). Information management is fundamental to health care delivery (8). Given the fragmented nature of health care, the large volume of transactions in the system, the need to integrate new scientific evidence into practice, and other complex information management activities, the limitations of paper-based information management are intuitively apparent. While the benefits of health information technology are clear in theory, adapting new information systems to health care has proven difficult and rates of use have been limited (9-11). Most information technology applications have centered on administrative and financial transactions rather than on delivering clinical care (12). The Agency for Healthcare Research and Quality asked us to systematically review evidence on the costs and benefits associated with use of health information technology and to identify gaps in the literature in order to provide organizations, policymakers, clinicians, and consumers an understanding of the effect of health information technology on clinical care (see evidence report at www.ahrq.gov). From among the many possible benefits and costs of implementing health information technology, we focus here on 3 important domains: the effects of health information technology on quality, efficiency, and costs. Methods Analytic Frameworks We used expert opinion and literature review to develop analytic frameworks (Table) that describe the components involved with implementing health information technology, types of health information technology systems, and the functional capabilities of a comprehensive health information technology system (13). We modified a framework for clinical benefits from the Institute of Medicines 6 aims for care (2) and developed a framework for costs using expert consensus that included measures such as initial costs, ongoing operational and maintenance costs, fraction of health information technology penetration, and productivity gains. Financial benefits were divided into monetized benefits (that is, benefits expressed in dollar terms) and nonmonetized benefits (that is, benefits that could not be directly expressed in dollar terms but could be assigned dollar values). Table. Health Information Technology Frameworks Data Sources and Search Strategy We performed 2 searches (in November 2003 and January 2004) of the English-language literature indexed in MEDLINE (1995 to January 2004) using a broad set of terms to maximize sensitivity. (See the full list of search terms and sequence of queries in the full evidence report at www.ahrq.gov.) We also searched the Cochrane Central Register of Controlled Trials, the Cochrane Database of Abstracts of Reviews of Effects, and the Periodical Abstracts Database; hand-searched personal libraries kept by content experts and project staff; and mined bibliographies of articles and systematic reviews for citations. We asked content experts to identify unpublished literature. Finally, we asked content experts and peer reviewers to identify newly published articles up to April 2005. Study Selection and Classification Two reviewers independently selected for detailed review the following types of articles that addressed the workings or implementation of a health technology system: systematic reviews, including meta-analyses; descriptive qualitative reports that focused on exploration of barriers; and quantitative reports. We classified quantitative reports as hypothesis-testing if the investigators compared data between groups or across time periods and used statistical tests to assess differences. We further categorized hypothesis-testing studies (for example, randomized and nonrandomized, controlled trials, controlled before-and-after studies) according to whether a concurrent comparison group was used. Hypothesis-testing studies without a concurrent comparison group included those using simple prepost, time-series, and historical control designs. Remaining hypothesis-testing studies were classified as cross-sectional designs and other. We classified quantitative reports as a predictive analysis if they used methods such as statistical modeling or expert panel estimates to predict what might happen with implementation of health information technology rather than what has happened. These studies typically used hybrid methodsfrequently mixing primary data collection with secondary data collection plus expert opinion and assumptionsto make quantitative estimates for data that had otherwise not been empirically measured. Cost-effectiveness and cost-benefit studies generally fell into this group. Data Extraction and Synthesis Two reviewers independently appraised and extracted details of selected articles using standardized abstraction forms and resolved discrepancies by consensus. We then used narrative synthesis methods to integrate findings into descriptive summaries. Each institution that accounted for more than 5% of the total sample of 257 papers was designated as a benchmark research leader. We grouped syntheses by institution and by whether the systems were commercially or internally developed. Role of the Funding Sources This work was produced under Agency for Healthcare Research and Quality contract no. 2002. In addition to the Agency for Healthcare Research and Quality, this work was also funded by the Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services, and the Office of Disease Prevention and Health Promotion, U.S. Department of Health and Human Services. The funding sources had no role in the design, analysis, or interpretation of the study or in the decision to submit the manuscript for publication. Data Synthesis Literature Selection Overview Of 867 articles, we rejected 141 during initial screening: 124 for not having health information technology as the subject, 4 for not reporting relevant outcomes, and 13 for miscellaneous reasons (categories not mutually exclusive). Of the remaining 726 articles, we excluded 469 descriptive reports that did not examine barriers (Figure). We recorded details of and summarized each of the 257 articles that we did include in an interactive database (healthit.ahrq.gov/tools/rand) that serves as the evidence table for our report (14). Twenty-four percent of all studies came from the following 4 benchmark institutions: 1) the Regenstrief Institute, 2) Brigham and Womens Hospital/Partners Health Care, 3) the Department of Veterans Affairs, and 4) LDS Hospital/Intermountain Health Care. Figure. Search flow for health information technology ( HIT ) literature. Pediatrics Types and Functions of Technology Systems The reports addressed the following types of primary systems: decision support aimed at providers (63%), electronic health records (37%), and computerized provider order entry (13%). Specific functional capabilities of systems that were described in reports included electronic documentation (31%), order entry (22%), results management (19%), and administrative capabilities (18%). Only 8% of the described systems had specific consumer health capabilities, and only 1% had capabilities that allowed systems from different facilities to connect with each other and share data interoperably. Most studies (n= 125) assessed the effect of the systems in the outpatient setting. Of the 213 hypothesis-testing studies, 84 contained some data on costs. Several studies assessed interventions with limited functionality, such as stand-alone decision support systems (15-17). Such studies provide limited information about issues that todays decision makers face when selecting and implementing health information technology. Thus, we preferentially highlight in the following paragraphs studies that were conducted in the United States, that had empirically measured data on multifunctional systems, and that included health information and data storage in the form of electronic documentation or order-entry capabilities. Predictive analyses were excluded. Seventy-six studies met these criteria: 54 from the 4 benchmark leaders and 22 from other institutions. Data from Benchmark Institutions The health information technology systems evaluated by the benchmark leaders shared many characteristics. All the systems were multifunctional and included decision support, all were internally developed by research experts at the respective academic institutions, and all had capabilities added incrementally over several years. Furthermore, most reported studies of these systems used research designs with high internal validity (for example, randomized, controlled trials). Appendix Table 1 (18-71) provides a structured summary of each study from the 4 benchmark institutions. This table also includes studies that met inclusion criteria not highlighted in this synthesis (26, 27, 30, 39, 40, 53, 62, 65, 70, 71). The data supported 5 primary themes (3 directly r

The Role of Perceived Team Effectiveness in Improving Chronic Illness Care

Background/Objectives:The importance of teams for improving quality of care has received increased attention. We examine both the correlates of self-assessed or perceived team effectiveness and its consequences for actually making changes to improve care for people with chronic illness. Study Setting and Methods:Data were obtained from 40 teams participating in the national evaluation of the Improving Chronic Illness Care Program. Based on current theory and literature, measures were derived of organizational culture, a focus on patient satisfaction, presence of a team champion, team composition, perceived team effectiveness, and the actual number and depth of changes made to improve chronic illness care. Results:A focus on patient satisfaction, the presence of a team champion, and the involvement of the physicians on the team were each consistently and positively associated with greater perceived team effectiveness. Maintaining a balance among culture values of participation, achievement, openness to innovation, and adherence to rules and accountability also appeared to be important. Perceived team effectiveness, in turn, was consistently associated with both a greater number and depth of changes made to improve chronic illness care. The variables examined explain between 24 and 40% of the variance in different dimensions of perceived team effectiveness; between 13% and 26% in number of changes made; and between 20% and 42% in depth of changes made. Conclusions:The data suggest the importance of developing effective teams for improving the quality of care for patients with chronic illness.

Comparing the cost-effectiveness of HIV prevention interventions

Objective:Communities need to identify cost-effective interventions for HIV prevention to optimize limited resources. Methods:The authors developed a spreadsheet tool using Bernoulli and proportionate change models to estimate the relative cost-effectiveness for 26 HIV prevention interventions including biomedical interventions, structural interventions, and interventions designed to change risk behaviors of individuals. They also conducted sensitivity analyses to assess patterns of the cost-effectiveness across different populations using various assumptions. Results:The 2 factors most strongly determining the cost-effectiveness of the different interventions were the HIV prevalence of the population at risk and the cost per person reached. In low-prevalence populations (eg, heterosexuals) the most cost-effective interventions were structural interventions (eg, mass media, condom distribution), whereas in high-prevalence populations (eg, men who have sex with men) individually focused interventions to change risk behavior were also relatively cost-effective. Among the most cost-effective interventions overall were showing videos in STD clinics and raising alcohol taxes. School-based HIV prevention programs appeared to be the least cost-effective. Needle exchange and needle deregulation programs were relatively cost-effective only when injection drug users have a high HIV prevalence. Conclusions:Comparing estimates of the cost-effectiveness of HIV interventions provides insight that can help local communities maximize the impact of their HIV prevention resources.

Evaluation of a Quality Improvement Collaborative in Asthma Care: Does it Improve Processes and Outcomes of Care?

PURPOSE We wanted to examine whether a collaborative to improve asthma care influences process and outcomes of care in asthmatic adults. METHOD We undertook a preintervention-postintervention evaluation of 185 patients in 6 intervention clinics and 3 matched control sites that participated in the Institute for Healthcare Improvement Breakthrough Series (BTS) Collaborative for asthma care. The intervention consisted of 3, 2-day educational sessions for teams dispatched by participating sites, which were followed by 3 action periods during the course of a year. RESULTS Overall process of asthma care improved significantly in the intervention compared with the control group (change of 10% vs 1%, P = .003). Patients in the intervention group were more likely to attend educational sessions (20% vs 5%, P = .03). Having a written action plan, setting goals, monitoring peak flow rates, and using long-term asthma medications increased between 2% and 19% (not significant), but asthma-related knowledge was unchanged for the 2 groups. Patients in the BTS Collaborative were significantly more likely to be satisfied with clinician and lay educator communication (62% vs 39%, P = .02). Health-related quality of life, asthma-specific quality of life, number of bed days caused by asthma-related illness, and acute care service use were not significantly different between the 2 groups. CONCLUSIONS The intervention was associated with improved process-of-care measures that have been linked with better outcomes. Patients benefited through increased satisfaction with communication. Follow-up of patients who participated in the intervention may have been too brief to be able to detect significant improvement in health-related outcomes.

Motivation to change chronic illness care: results from a national evaluation of quality improvement collaboratives.

Abstract: This article examines the motivation of health care professionals to improve quality of chronic illness care using the Chronic Care Model and Plan-Do-Study-Act cycles. The findings suggest that organizational attempts to redesign care require support of activities initiated by practitioners and managers and an organizational commitment to quality improvement.

It takes a village to prevent falls: reconceptualizing fall prevention and management for older adults

Systematic evidence reviews support the efficacy of physical activity programs and multifactorial strategies for fall prevention. However, community settings in which fall prevention programs occur often differ substantially from the research settings in which efficacy was first demonstrated. Because of these differences, alternative approaches are needed to judge the adequacy of fall prevention activities occurring as part of standard medical care or community efforts. This paper uses the World Health Organization Innovative Care for Chronic Conditions (ICCC) framework to rethink how fall prevention programs might be implemented routinely in both medical and community settings. Examples of innovative programs and policies that provide fall prevention strategies consistent with the ICCC framework are highlighted, and evidence where available is provided on the effects of these strategies on processes and outcomes of care. Finally, a “no wrong door” approach to fall prevention and management is proposed, in which older adults who are found to be at risk of falls in either a medical or community setting are linked to a standard fall risk evaluation across three domains (physical activity, medical risks, and home safety).

The Value of Screening for Sexually Transmitted Diseases in an HIV Clinic

Because bacterial sexually transmitted diseases (STDs) facilitate HIV transmission, screening for and treatment of STDs among HIV-infected persons should prevent HIV spread to partners. Before screening programs for gonorrhea and Chlamydia infection should be widely established in HIV clinics, it is useful to know the prevalence of these infections. This study analyzed the results of a urine-based screening program for gonorrhea and Chlamydia in a New Orleans HIV clinic and compared the positivity rates to the prevalence in the local community. Among persons screened in the HIV clinic, 1.7% (46/2629) had gonorrhea and 2.1% (56/2629) had Chlamydia infection. Among persons aged 18-29 years, the test positivity for gonorrhea was similar in the HIV clinic to that of persons in sociodemographically similar community samples (3.1 versus 2.4%, adjusted odds ratio 1.6, P = 0.11) and the test positivity for Chlamydia infection was lower (5.4% versus 10.5%, adjusted odds ratio 0.6, P < 0.01). Based on a previously published mathematical model, it was estimated that treatment of all 46 gonorrhea and 56 Chlamydia infections in the HIV clinic may have averted 9 HIV infections among sex partners and saved far more in future medical costs than the cost of the screening. Routine screening for gonorrhea and Chlamydia infection should be considered in HIV clinics.

A cost-effectiveness analysis of a proposed national falls prevention program.

Falls are a major health concern for elderly people and cause substantial health care costs. The authors used meta-analytic findings on the effectiveness of fall prevention interventions to determine cost-effectiveness of a proposed Medicare fall prevention program for people who experience a recent fall. Using published clinical trial data, the authors constructed a population-based economic model and estimated that, in the base case, the program could prevent a half million people from falling again within a year. From the model, under most circumstances the cost-effectiveness ratio is less than

Technology-facilitated depression care management among predominantly Latino diabetes patients within a public safety net care system: Comparative effectiveness trial design

1500 per person prevented from experiencing a recurrent fall. Paying for a fall prevention program to increase the use of evidence-based interventions would be a cost-effective use of Medicare dollars.

Structural interventions to prevent HIV/sexually transmitted disease: are they cost-effective for women in the southern United States?

Health disparities in minority populations are well recognized. Hispanics and Latinos constitute the largest ethnic minority group in the United States; a significant proportion receives their care via a safety net. The prevalence of diabetes mellitus and comorbid depression is high among this group, but the uptake of evidence-based collaborative depression care management has been suboptimal. The study design and baseline characteristics of the enrolled sample in the Diabetes-Depression Care-management Adoption Trial (DCAT) establishes a quasi-experimental comparative effectiveness research clinical trial aimed at accelerating the adoption of collaborative depression care in safety net clinics. The study was conducted in collaboration with the Los Angeles County Department of Health Services at eight county-operated clinics. DCAT has enrolled 1406 low-income, predominantly Hispanic/Latino patients with diabetes to test a translational model of depression care management. This three-group study compares usual care with a collaborative care team support model and a technology-facilitated depression care model that provides automated telephonic depression screening and monitoring tailored to patient conditions and preferences. Call results are integrated into a diabetes disease management registry that delivers provider notifications, generates tasks, and issues critical alerts. All subjects receive comprehensive assessments at baseline, 6, 12, and 18 months by independent English-Spanish bilingual interviewers. Study outcomes include depression outcomes, treatment adherence, satisfaction, acceptance of assessment and monitoring technology, social and economic stress reduction, diabetes self-care management, health care utilization, and care management model cost and cost-effectiveness comparisons. DCATs goal is to optimize depression screening, treatment, follow-up, outcomes, and cost savings to reduce health disparities.