The Association between eHealth Capabilities and the Quality and Safety of Health Care in the Netherlands: Comparison of HIMSS Analytics EMRAM data with Elsevier's 'The Best Hospitals' data.

OBJECTIVE: To test the hypothesis that advanced electronic medical record (EMR) capabilities are associated with better quality and safety of hospital care. METHODS AND FINDINGS: We used data from the HIMSS Analytics EMR Adoption Model (EMRAM(SM)) to measure the adoption and use of information technology in Dutch hospitals. To measure the quality and safety of healthcare in Dutch Hospitals we used select data from the publicly available basic set and the safety set of the Health Care Inspectorate (IGZ) and the Dutch Health Care Transparency Program 'Zichtbare Zorg' (ZIZO) program. The quality and safety measures selected reflect the measures used to score Dutch hospitals as presented in Elsevier's annual 'The Best Hospitals' publication. The scores of this publication are based upon 542 of the 1516 available indicators from this basic set and safety set. Almost all indicators from the hospital-wide indicator sets are included in the selection, as are a large portion of indicators for acute care delivered by all hospitals. Of the 84 non-academic hospitals in the Netherlands, 67 (80 %) were included in this study. RESULTS: There is no statistically significant association found between a hospital's EMRAM score and their overall quality/safety performance in the Elsevier hospital scoring model. CONCLUSION: There is no evidence found to support the research hypothesis at this point in time. This outcome maybe the result of a multiplicity of factors to include the (limited) use of the methodologies used in this study, the fact that no fully digitalized hospital (EMRAM stage 7) is yet present in the NL, and/or the organizational competency of the NL hospitals in fully leveraging the EMR to facilitate patient care. Further research is needed to explore these findings.

Understanding EMRAM and how it can be used by policy-makers, hospital CIOs and their IT teams.

The Electronic Medical Record Adoption Model (EMRAM)SM developed by HIMSS Analytics has become a universally recognized maturation model of a hospital's electronic medical record (EMR) environment. Numerous health care organizations (HCOs) throughout the world spend significant time and resources to improve their EMRAM standing. Yet, to the health care information technology (HIT) outsider, the value of the EMRAM and the outcomes of the efforts tied to advancing EMR capabilities are virtually unknown. This is a significant concern when efforts around the EMR compete for scarce health care resources. This article purposes to establish the EMRAM as a valuable framework for policy-makers and hospital leaders. To accomplish this end, we begin with a necessarily brief description of the EMRAM process and stages. Our attention will then turn to examples of the model's use and presence throughout the world, before ending on the ERMAM's benefits for varied health care audiences.

Adoption of Health Information Technology Among US Nursing Facilities.

OBJECTIVES: Nursing facilities have lagged behind in the adoption of interoperable health information technology (ie technologies that allow the sharing and use of electronic patient information between different information systems). The objective of this study was to estimate the nationwide prevalence of electronic health record (EHR) adoption among nursing facilities and to identify the factors associated with adoption. DESIGN: Cross-sectional survey. SETTING & PARTICIPANTS: We surveyed members of the Society for Post-Acute & Long-Term Care Medicine (AMDA) about their organizations' health information technology usage and characteristics. MEASUREMENTS: Using questions adopted from existing instruments, the survey measured nursing home's EHR adoption, the ability to send, receive, search and integrate electronic information, as well as barriers to usage. Additionally, we linked survey responses to public use secondary data sources to construct measurements for 8 determinants known to be associated with organizational adoption: innovativeness, functional differentiation, role specialization, administrative intensity, professionalism, complexity, technical knowledge resources, and slack resources. A series of regression models estimated the association between potential determinants and technology adoption. RESULTS: 84% of nursing facilities reported using an EHR. After controlling for all other factors, respondents who characterized their organization as more innovative had more than 6 times the odds (adjusted odds ratio = 6.39, 95% confidence interval = 2.69, 15.21) of adopting an EHR. Organization innovativeness was also associated with an increased odds of being able to send, integrate, and search for electronic information. The most commonly identified barrier to sharing clinical information among nursing facilities with an EHR was a reported absence of interoperability (57%). CONCLUSIONS/IMPLICATIONS: An organizational culture that fosters innovation and awareness campaigns by professional societies may facilitate further adoption and effective use of technology. This will be increasingly important as policy makers continue to emphasize the use of EHRs and interoperability to improve the quality of care in nursing facilities.

Building consensus toward a national nursing home information technology maturity model.

OBJECTIVES: We describe the development of a nursing home information technology (IT) maturity model designed to capture stages of IT maturity. MATERIALS AND METHODS: This study had 2 phases. The purpose of phase I was to develop a preliminary nursing home IT maturity model. Phase II involved 3 rounds of questionnaires administered to a Delphi panel of expert nursing home administrators to evaluate the validity of the nursing home IT maturity model proposed in phase I. RESULTS: All participants (n = 31) completed Delphi rounds 1-3. Over the 3 Delphi rounds, the nursing home IT maturity staging model evolved from a preliminary, 5-stage model (stages 1-5) to a 7-stage model (stages 0-6). DISCUSSION: Using innovative IT to improve patient outcomes has become a broad goal across healthcare settings, including nursing homes. Understanding the relationship between IT sophistication and quality performance in nursing homes relies on recognizing the spectrum of nursing home IT maturity that exists and how IT matures over time. Currently, no universally accepted nursing home IT maturity model exists to trend IT adoption and determine the impact of increasing IT maturity on quality. CONCLUSIONS: A 7-stage nursing home IT maturity staging model was successfully developed with input from a nationally representative sample of U.S. based nursing home experts. The model incorporates 7-stages of IT maturity ranging from stage 0 (nonexistent IT solutions or electronic medical record) to stage 6 (use of data by resident or resident representative to generate clinical data and drive self-management).