Behavioral health providers' beliefs about health information exchange: a statewide survey

Objective

To assess behavioral health providers'' beliefs about the benefits and barriers of health information exchange (HIE).

Methods

Survey of a total of 2010 behavioral health providers in a Midwestern state (33% response rate), with questions based on previously reported open-ended beliefs elicitation interviews.

Results

Factor analysis resulted in four groupings: beliefs that HIE would improve care and communication, add cost and time burdens, present access and vulnerability concerns, and impact workflow and control (positively and negatively). A regression model including all four factors parsimoniously predicted attitudes toward HIE. Providers clustered into two groups based on their beliefs: a majority (67%) were positive about the impact of HIE, and the remainder (33%) were negative. There were some professional/demographic differences between the two clusters of providers.

Discussion

Most behavioral health providers are supportive of HIE; however, their adoption and use of it may continue to lag behind that of medical providers due to perceived cost and time burdens and concerns about access to and vulnerability of information.     

Patient-controlled sharing of medical imaging data across unaffiliated healthcare organizations

Background

Current image sharing is carried out by manual transportation of CDs by patients or organization-coordinated sharing networks. The former places a significant burden on patients and providers. The latter faces challenges to patient privacy.

Objective

To allow healthcare providers efficient access to medical imaging data acquired at other unaffiliated healthcare facilities while ensuring strong protection of patient privacy and minimizing burden on patients, providers, and the information technology infrastructure.

Methods

An image sharing framework is described that involves patients as an integral part of, and with full control of, the image sharing process. Central to this framework is the Patient Controlled Access-key REgistry (PCARE) which manages the access keys issued by image source facilities. When digitally signed by patients, the access keys are used by any requesting facility to retrieve the associated imaging data from the source facility. A centralized patient portal, called a PCARE patient control portal, allows patients to manage all the access keys in PCARE.

Results

A prototype of the PCARE framework has been developed by extending open-source technology. The results for feasibility, performance, and user assessments are encouraging and demonstrate the benefits of patient-controlled image sharing.

Discussion

The PCARE framework is effective in many important clinical cases of image sharing and can be used to integrate organization-coordinated sharing networks. The same framework can also be used to realize a longitudinal virtual electronic health record.

Conclusion

The PCARE framework allows prior imaging data to be shared among unaffiliated healthcare facilities while protecting patient privacy with minimal burden on patients, providers, and infrastructure. A prototype has been implemented to demonstrate the feasibility and benefits of this approach.     

Improving personal health records for patient-centered care

Objective

To assess the patient-centeredness of personal health records (PHR) and offer recommendations for best practice guidelines.

Design

Semi-structured interviews were conducted in seven large early PHR adopter organizations in 2007. Organizations were purposively selected to represent a variety of US settings, including medium and large hospitals, ambulatory care facilities, insurers and health plans, government departments, and commercial sectors.

Measurements

Patient-centeredness was assessed against a framework of care that includes: (1) respect for patient values, preferences, and expressed needs; (2) information and education; (3) access to care; (4) emotional support to relieve fear and anxiety; (5) involvement of family and friends; (6) continuity and secure transition between healthcare providers; (7) physical comfort; (8) coordination of care. Within this framework we used evidence for patient preferences (where it exists) to compare existing PHR policies, and propose a best practice model.

Results

Most organizations enable many patient-centered functions such as data access for proxies and minors. No organization allows patient views of clinical progress notes, and turnaround times for PHR reporting of normal laboratory results can be up to 7 days.

Conclusion

Findings suggest patient-centeredness for personal health records can be improved, and recommendations are made for best practice guidelines.     

Professional and geographical network effects on healthcare information exchange growth: does proximity really matter?

Background and objective

We postulate that professional proximity due to common patients and geographical proximity among practice locations are significant factors influencing the adoption of health information exchange (HIE) services by healthcare providers. The objective of this study is to investigate the direct and indirect network effects of these drivers on HIE diffusion.

Design

Multi-dimensional scaling and clustering are first used to create different clusters of physicians based on their professional and geographical proximities. Extending the Bass diffusion model to capture direct and indirect network effects among groups, the growth of HIE among these clusters is modeled and studied. The network effects among the clusters are investigated using adoption data over a 3-year period for an HIE based in Western New York.

Measurement

HIE adoption parameters—external sources of influence as well as direct and indirect network coefficients—are estimated by the extended version of the Bass diffusion model.

Results

Direct network effects caused by common patients among physicians are much more influential on HIE adoption as compared with previously investigated social contagion and external factors. Professional proximity due to common patients does influence adoption decisions; geographical proximity is also influential, but its effect is more on rural than urban physicians.

Conclusions

Flow of patients among different groups of physicians is a powerful factor in HIE adoption. Rather than merely following the market trend, physicians appear to be influenced by other physicians with whom they interact with and have common patients.     

How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use

Background

Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.

Objective

To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.

Methods

Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.

Results

Data were analyzed for 112 physicians and nurse practitioners, consisting of 430 803 encounters with 99 649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.

Conclusions

Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.     

Research and applications: Effects of health information exchange adoption on ambulatory testing rates

Objective

To determine the effects of the adoption of ambulatory electronic health information exchange (HIE) on rates of laboratory and radiology testing and allowable charges.

Design

Claims data from the dominant health plan in Mesa County, Colorado, from 1 April 2005 to 31 December 2010 were matched to HIE adoption data on the provider level. Using mixed effects regression models with the quarter as the unit of analysis, the effect of HIE adoption on testing rates and associated charges was assessed.

Results

Claims submitted by 306 providers in 69 practices for 34 818 patients were analyzed. The rate of testing per provider was expressed as tests per 1000 patients per quarter. For primary care providers, the rate of laboratory testing increased over the time span (baseline 1041 tests/1000 patients/quarter, increasing by 13.9 each quarter) and shifted downward with HIE adoption (downward shift of 83, p<0.01). A similar effect was found for specialist providers (baseline 718 tests/1000 patients/quarter, increasing by 19.1 each quarter, with HIE adoption associated with a downward shift of 119, p<0.01). Even so, imputed charges for laboratory tests did not shift downward significantly in either provider group, possibly due to the skewed nature of these data. For radiology testing, HIE adoption was not associated with significant changes in rates or imputed charges in either provider group.

Conclusions

Ambulatory HIE adoption is unlikely to produce significant direct savings through reductions in rates of testing. The economic benefits of HIE may reside instead in other downstream outcomes of better informed, higher quality care.     

Factors motivating and affecting health information exchange usage

Objective

Health information exchange (HIE) is the process of electronically sharing patient-level information between providers. However, where implemented, reports indicate HIE system usage is low. The aim of this study was to determine the factors associated with different types of HIE usage.

Design

Cross-sectional analysis of clinical data from emergency room encounters included in an operational HIE effort linked to system user logs using crossed random-intercept logistic regression.

Measurements

Independent variables included factors indicative of information needs. System usage was measured as none, basic usage, or a novel pattern of usage.

Results

The system was accessed for 2.3% of all encounters (6142 out of 271 305). Novel usage patterns were more likely for more complex patients. The odds of HIE usage were lower in the face of time constraints. In contrast to expectations, system usage was lower when the patient was unfamiliar to the facility.

Limitations

Because of differences between HIE efforts and the fact that not all types of HIE usage (ie, public health) could be included in the analysis, results are limited in terms of generalizablity.

Conclusions

This study of actual HIE system usage identifies patients and circumstances in which HIE is more likely to be used and factors that are likely to discourage usage. The paper explores the implications of the findings for system redesign, information integration across exchange partners, and for meaningful usage criteria emerging from provisions of the Health Information Technology for Economic & Clinical Health Act.     

Automated identification of drug and food allergies entered using non-standard terminology

Objective

An accurate computable representation of food and drug allergy is essential for safe healthcare. Our goal was to develop a high-performance, easily maintained algorithm to identify medication and food allergies and sensitivities from unstructured allergy entries in electronic health record (EHR) systems.

Materials and methods

An algorithm was developed in Transact-SQL to identify ingredients to which patients had allergies in a perioperative information management system. The algorithm used RxNorm and natural language processing techniques developed on a training set of 24 599 entries from 9445 records. Accuracy, specificity, precision, recall, and F-measure were determined for the training dataset and repeated for the testing dataset (24 857 entries from 9430 records).

Results

Accuracy, precision, recall, and F-measure for medication allergy matches were all above 98% in the training dataset and above 97% in the testing dataset for all allergy entries. Corresponding values for food allergy matches were above 97% and above 93%, respectively. Specificities of the algorithm were 90.3% and 85.0% for drug matches and 100% and 88.9% for food matches in the training and testing datasets, respectively.

Discussion

The algorithm had high performance for identification of medication and food allergies. Maintenance is practical, as updates are managed through upload of new RxNorm versions and additions to companion database tables. However, direct entry of codified allergy information by providers (through autocompleters or drop lists) is still preferred to post-hoc encoding of the data. Data tables used in the algorithm are available for download.

Conclusions

A high performing, easily maintained algorithm can successfully identify medication and food allergies from free text entries in EHR systems.     

Use of the internet and an online personal health record system by US veterans: comparison of Veterans Affairs mental health service users and other veterans nationally

Objective

The Department of Veterans Affairs (VA) operates one of the largest nationwide healthcare systems and is increasing use of internet technology, including development of an online personal health record system called My HealtheVet. This study examined internet use among veterans in general and particularly use of online health information among VA patients and specifically mental health service users.

Methods

A nationally representative sample of 7215 veterans from the 2010 National Survey of Veterans was used. Logistic regression was employed to examine background characteristics associated with internet use and My HealtheVet.

Results

71% of veterans reported using the internet and about a fifth reported using My HealtheVet. Veterans who were younger, more educated, white, married, and had higher incomes were more likely to use the internet. There was no association between background characteristics and use of My HealtheVet. Mental health service users were no less likely to use the internet or My HealtheVet than other veterans.

Discussion

Most veterans are willing to access VA information online, although many VA service users do not use My HealtheVet, suggesting more education and research is needed to reduce barriers to its use.

Conclusion

Although adoption of My HealtheVet has been slow, the majority of veterans, including mental health service users, use the internet and indicate a willingness to receive and interact with health information online.     

Emergency Physicians’ Perceptions of Health Information Exchange

Background

Health information exchange (HIE) is a potentially powerful technology that can improve the quality of care delivered in emergency departments, but little is known about emergency physicians’ current perceptions of HIE.

Objectives

This study sought to assess emergency physicians’ perceived needs and knowledge of HIE.

Methods

A questionnaire was developed based on heuristics from the literature and implemented in a Web-based tool. The survey was sent as a hyperlink via e-mail to 371 attending emergency physicians at 12 hospitals in New York City.

Results

The response rate was 58% (n = 216). Although 63% said more than one quarter of their patients would benefit from external health information, the barriers to obtain it without HIE are too high—85% said it was difficult or very difficult to obtain external data, taking an average of 66 minutes, 72% said that their attempts fail half of the time, and 56% currently attempt to obtain external data less than 10% of the time. When asked to create a rank-order list, electrocardiograms (ECGs) were ranked the highest, followed by discharge summaries. Respondents also chose images over written reports for ECGs and X-rays, but preferred written reports for advanced imaging and cardiac studies.

Conclusion

There is a strong perceived need for HIE, most respondents were not aware of HIE prior to this study, and there are certain types of data and presentations of data that are preferred by emergency physicians in the New York City region.     

A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions

Background

Data-driven risk stratification models built using data from a single hospital often have a paucity of training data. However, leveraging data from other hospitals can be challenging owing to institutional differences with patients and with data coding and capture.

Objective

To investigate three approaches to learning hospital-specific predictions about the risk of hospital-associated infection with Clostridium difficile, and perform a comparative analysis of the value of different ways of using external data to enhance hospital-specific predictions.

Materials and methods

We evaluated each approach on 132 853 admissions from three hospitals, varying in size and location. The first approach was a single-task approach, in which only training data from the target hospital (ie, the hospital for which the model was intended) were used. The second used only data from the other two hospitals. The third approach jointly incorporated data from all hospitals while seeking a solution in the target space.

Results

The relative performance of the three different approaches was found to be sensitive to the hospital selected as the target. However, incorporating data from all hospitals consistently had the highest performance.

Discussion

The results characterize the challenges and opportunities that come with (1) using data or models from collections of hospitals without adapting them to the site at which the model will be used, and (2) using only local data to build models for small institutions or rare events.

Conclusions

We show how external data from other hospitals can be successfully and efficiently incorporated into hospital-specific models.     

Information seeking and social support in online health communities: impact on patients' perceived empathy

Objective

Many healthcare organizations (HCOs) including Kaiser Permanente, Johns Hopkins, Cleveland Medical Center, and MD Anderson Cancer Center, provide access to online health communities as part of their overall patient support services. The key objective in establishing and running these online health communities is to offer empathic support to patients. Patients'' perceived empathy is considered to be critical in patient recovery, specifically, by enhancing patient''s compliance with treatment protocols and the pace of healing. Most online health communities are characterized by two main functions: informational support and social support. This study examines the relative impact of these two distinct functions—that is, as an information seeking forum and as a social support forum—on patients'' perceived empathy in online health communities.

Design

This study tests the impact of two variables that reflect the above functions of online health communities—information seeking effectiveness and perceived social support—on perceived empathy. The model also incorporates the potential moderating effect of homophily on these relationships.

Measurements

A web-based survey was used to collect data from members of the online health communities provided by three major healthcare centers. A regression technique was used to analyze the data to test the hypotheses.

Results

The study finds that it is the information seeking effectiveness rather than the social support which affects patient''s perceived empathy in online health communities run by HCOs. The results indicate that HCOs that provide online health communities for their patients need to focus more on developing tools that will make information seeking more effective and efficient.     

A Framework for evaluating the costs, effort, and value of nationwide health information exchange

Objective

The nationwide health information network (NHIN) has been proposed to securely link community and state health information exchange (HIE) entities to create a national, interoperable network for sharing healthcare data in the USA. This paper describes a framework for evaluating the costs, effort, and value of nationwide data exchange as the NHIN moves toward a production state. The paper further presents the results of an initial assessment of the framework by those engaged in HIE activities.

Design

Using a literature review and knowledge gained from active NHIN technology and policy development, the authors constructed a framework for evaluating the costs, effort, and value of data exchange between an HIE entity and the NHIN.

Measurement

An online survey was used to assess the perceived usefulness of the metrics in the framework among HIE professionals and researchers.

Results

The framework is organized into five broad categories: implementation; technology; policy; data; and value. Each category enumerates a variety of measures and measure types. Survey respondents generally indicated the framework contained useful measures for current and future use in HIE and NHIN evaluation. Answers varied slightly based on a respondent''s participation in active development of NHIN components.

Conclusion

The proposed framework supports efforts to measure the costs, effort, and value associated with nationwide data exchange. Collecting longitudinal data along the NHIN''s path to production should help with the development of an evidence base that will drive adoption, create value, and stimulate further investment in nationwide data exchange.     

Electronic health records in small physician practices: availability,use, and perceived benefits

Objective

To examine variation in the adoption of electronic health record (EHR) functionalities and their use patterns, barriers to adoption, and perceived benefits by physician practice size.

Design

Mailed survey of a nationally representative random sample of practicing physicians identified from the Physician Masterfile of the American Medical Association.

Measurements

We measured, stratified by practice size: (1) availability of EHR functionalities, (2) functionality use, (3) barriers to the adoption and use of EHR, and (4) impact of the EHR on the practice and quality of patient care.

Results

With a response rate of 62%, we found that <2% of physicians in solo or two-physician (small) practices reported a fully functional EHR and 5% reported a basic EHR compared with 13% of physicians from 11+ group (largest group) practices with a fully functional system and 26% with a basic system. Between groups, a 21–46% difference in specific functionalities available was reported. Among adopters there were moderate to large differences in the use of the EHR systems. Financial barriers were more likely to be reported by smaller practices, along with concerns about future obsolescence. These differences were sizable (13–16%) and statistically significant (p<0.001). All adopters reported similar benefits.

Limitations

Although we have adjusted for response bias, influences may still exist.

Conclusion

Our study found that physicians in small practices have lower levels of EHR adoption and that these providers were less likely to use these systems. Ensuring that unique barriers are addressed will be critical to the widespread meaningful use of EHR systems among small practices.     

A personally controlled electronic health record for Australia

Objective

On July 1, 2012 Australia launched a personally controlled electronic health record (PCEHR) designed around the needs of consumers. Using a distributed model and leveraging key component national eHealth infrastructure, the PCEHR is designed to enable sharing of any health information about a patient with them and any other health practitioner involved in their care to whom the patient allows access. This paper discusses the consumer-facing part of the program.

Method

Design of the system was through stakeholder consultation and the development of detailed requirements, followed by clinical design assurance.

Results

Patients are able to access any posted information through a web-accessible ‘consumer portal.’ Within the portal they are able to assert access controls on all or part of their record. The portal includes areas for consumers to record their own personal information.

Discussion

The PCEHR has the potential to transform the ability of patients to actively engage in their own healthcare, and to enable the emerging partnership model of health and healthcare in medicine. The ability to access health information traditionally kept within the closed walls of institutions also raises challenges for the profession, both in the language clinicians choose and the ethical issues raised by the changed roles and responsibilities.

Conclusions

The PCEHR is aimed at connecting all participants and their interventions, and is intended to become a system-wide activity.     

Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors

Background

Electronic health records (EHR) have the potential to improve patient care through efficient access to complete patient health information. This potential may not be reached because many of the most important determinants of health outcome are rarely included. Successful health promotion and disease prevention requires patient-reported data reflecting health behaviors and psychosocial issues. Furthermore, there is a need to harmonize this information across different EHR systems.

Methods

To fill this gap a three-phased process was used to conceptualize, identify and recommend patient-reported data elements on health behaviors and psychosocial factors for the EHR. Expert panels (n=13) identified candidate measures (phase 1) that were reviewed and rated by a wide range of health professionals (n=93) using the grid-enabled measures wiki social media platform (phase 2). Recommendations were finalized through a town hall meeting with key stakeholders including patients, providers, researchers, policy makers, and representatives from healthcare settings (phase 3).

Results

Nine key elements from three areas emerged as the initial critical patient-reported elements to incorporate systematically into EHR—health behaviors (eg, exercise), psychosocial issues (eg, distress), and patient-centered factors (eg, demographics). Recommendations were also made regarding the frequency of collection ranging from a single assessment (eg, demographic characteristics), to annual assessment (eg, health behaviors), or more frequent (eg, patient goals).

Conclusions

There was strong stakeholder support for this initiative reflecting the perceived value of incorporating patient-reported elements into EHR. The next steps will include testing the feasibility of incorporating these elements into the EHR across diverse primary care settings.