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During early implementation for Indiana's initial care management program, the State held a series of four quality improvement collaboratives in which provider practices were invited to participate. The collaboratives focused on diabetes, congestive heart failure, and care for children with asthma. The participating practices set quality improvement goals and reported their performance once a month.

Ideas were shared during monthly conference calls and via an E-mail listserv.


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The nurse care managers and telephone center leads also attended the collaborative learning sessions. Providers also should be involved during the evaluation stage to provide feedback on preliminary results, offer suggestions on areas for program refinement, and comment on new initiatives within the care management program. Finally, providers can advocate for the care management program to State legislators and their staff and agency leadership.

Kansas' care management program was nearly cancelled because of budget restrictions and a new administration. However, local physicians' support of the program created enough pressure to reverse the decision to cancel the program. States involve providers during the implementation and evaluation stages through their standing advisory committees or targeted outreach to physician and provider organizations and societies, as discussed above.

A significant component of a care management program focuses directly on understanding the patient and his or her needs and subsequently providing appropriate interventions. By securing the patient and patient advocacy community's support, States have received useful input on program design and significant support for program sustainability. Stakeholder lobbying also can influence the legislature and Medicaid agency.

A strong lobby might exist for a particular disease e. Communicating routinely with lobbyists regarding program successes, failures, and new initiatives will help manage expectations and build support for the program. A key ally can be won if program staff identify ways to support advocacy group initiatives through the care management program. By involving consumers during the planning and designing stages, program staff will be better able to gauge the possible impact of certain interventions and will be able to design a better, more effective program overall.

Attaining support from the patient and advocacy community provides insight into the patients' needs and fosters support for program sustainability. Pennsylvania's vendor assembled Regional Advisory Committees RAC in which beneficiaries and physicians met regularly to provide feedback on disease management activities and input on the evaluation and selection of potential vendors in the early planning stages.

The RACs provide ongoing feedback to the vendor and State. By establishing infrastructure such as standing committees or focus groups, program staff can plan the care management program and identify areas for program improvement. Engaging patients during the implementation and evaluation stages of a care management program can also help program staff understand the program's effects on patient behavior and identify areas for program improvement.

In addition, engaged patients are more likely to follow providers or care managers' recommendations. Finally, patients can advocate for the care management program to State legislators and senior agency leadership. Involving the patient community through committees and focus groups can represent an effective strategy to build support, increase awareness of the program, and improve program outcomes. Similar to senior leadership, the State legislature retains the ability to influence the care management program significantly.

Legislators are unique in their capacity to influence program design and budget allocation through the legislative cycle. Program staff should work with State legislators and their staff during all stages of a care management program to understand their goals for the program and ensure support. Since legislators might lack the necessary information to realize the impact of certain design features, program staff should coordinate and communicate regularly regarding the care management program.


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  • Specifically, program staff should understand the State legislature's expectations of the program, program design requirements, and whether a mandatory savings requirement exists. In addition, since State legislators and their staff will not necessarily approach program staff for input, program staff should remain proactive and set up meetings to exchange ideas. Program staff should become the key contact for questions surrounding the care management program for legislators. Once the program is implemented, program staff should involve the legislators on an ongoing basis; periodic briefings can help build support and manage expectations in case the program progresses more slowly or has different outcomes than anticipated.

    State legislatures often require savings guarantees from care management programs. However, because cost savings might be an unrealistic expectation for the program's first few years, communication with the legislators and senior leadership can help establish realistic expectations for care management programs. Indiana State legislators, the Medicaid Director, and the Health Commissioner attended a National Governors Association Policy Academy on Chronic Disease while the State was in the planning stage of its former disease management program.

    Throughout the implementation stage, the Medicaid agency worked with this group and others in the legislature to inform them of key developments, set realistic goals, and share progress. With their comprehensive understanding of program goals and status, the legislators became natural advocates for the program. Demonstrated results, such as improved health outcomes, lower program costs, or higher beneficiary satisfaction, can and should be communicated to the legislature and other stakeholders whenever possible. Placing these results within the context of the program and not "overselling" the results is important.

    Program staff should carefully explain the changes that have occurred and why they matter. When discussing outcomes with elected officials, telling the story succinctly and avoiding jargon is especially important. Moreover, making accomplishments seem "real," perhaps by illustrating successes with examples of enrollees affected by the program, is critical. Medicaid care management program staff and agency leadership should develop relationships with the media as a potential tool for building program support. Agency leaders can position themselves as contact persons for the media in cases of potential negative media coverage.

    If desired, the media can publicize the care management program during the planning stage, help make stakeholders aware of the program, and highlight program successes. Encouraging program champions to write opinion articles in the State newspaper, publish case studies, and provide access to "real people" affected by the program has proven a successful State strategy.

    In addition to State approval, the design of the care management program might require CMS formal approval in the form of a State plan amendment or a waiver. Although many States have implemented care management programs, considerable variability exists in program design and Federal authority. Therefore, approval procedures are individualized, usually depending on the program model. As a result, during the planning stage, program staff should work with CMS staff, both at the regional and national levels, even when they are simply soliciting feedback to understand the type of authority that must be used to implement certain care management program components versus others.

    Program staff also should maintain contact with CMS after the program is implemented, because CMS can help guide waiver evaluation reports and programmatic changes. A key challenge for Medicaid staff is communicating the value of care management to a variety of stakeholders—all of whom have potentially different interests. Program staff should identify each of their program stakeholders and their interests and construct messages accordingly. State staff should also determine the appropriate opportunities for publicizing their successes. In some States, program staff have found that operating their program "under the radar" is helpful to allow the program an opportunity to generate success.

    Medicaid leadership and program staff should identify stakeholders, including legislators, senior leadership, providers, and members. Medicaid leadership and program staff should determine what their interests and goals are for the program and provide information accordingly. After Medicaid leadership and program staff determine their stakeholders' interests, they should construct messages accordingly, as shown in Exhibit 2.

    Medicaid leadership and program staff should design a message to reflect why a stakeholder should care about the care management program. A message should provide:. Exhibit 2. Governor's office. State legislature. Set realistic expectations. Discuss slowing growth rate versus decreasing costs. Emphasize improvements in health outcomes.

    Draw from experiences in other States. Health Outcomes and Improved Quality Agency leadership. Other State Agencies. Focus on three to five key measures. Select sound benchmarks. Incorporate within context of overall State chronic disease environment. Provider Satisfaction Agency leadership.

    Frame care management as a supplemental service for providers. Encourage provider champions to contact their State legislators and Governor's office. Quality of Life and Patient Satisfaction Agency leadership. Communicate anecdotes. Communicating Your Message Although Medicaid leadership and senior program staff can use many strategies to communicate their message, they should keep in mind that key stakeholders are unable to devote much time to learning about the care management program.

    PHR data were mainly used to provide added functionalities to patients. The provider search results [ 20 , 22 , 47 , 49 , 64 ], for example, helped patients locate health care providers and health-related services. Similar functionalities enabled patients to obtain health advice from support groups. Other functionalities assisted patients with preparing for medical encounters through visit preparation questionnaires [ 24 , 46 , 66 , 70 - 72 ].

    Functionalities such as incentive programs [ 43 , 56 , 66 , 73 , 74 ] empowered patients through self-health monitoring. Finally, a unique PHR data category discovered in our review, environmental information [ 36 , 50 , 56 , 67 ], captured community health concerns and environmental domains, which can be linked to functionalities such as assessment of environment-related risk factors and recommendations for preventive care.

    Description of the data extracted revealed which functionalities were available to the patient through the PHR and indicated an interesting evolution of PHR functionalities Figure 4. Patient health record functionality evolution over time, showing the most common sources, data types, and functionalities found in the review. EHR: electronic health record. The evolution of PHR data elements over time Figure 4 illustrates the general inclination in the early stages toward providing the patient with access to health information regarding their medical encounter.

    Even though the giving patients access to their own health data was initiated in the s, PHR systems were not widely used until the early s. Because of the infancy of PHR systems, research in this domain has focused on system adoption and how it relates to patient satisfaction. Only limited research is available on how to leverage PHR data to improve health outcomes. Starting in , data elements reported in the literature indicate a shift toward a more interactive view of the PHR system and the introduction of several new attributes and functionalities.

    Patient PHR settings, including security and privacy preferences, became more prevalent. The most significant development of this time period of PHR evolution was the interaction and engagement of the patient with the system. Functionalities such as patient-provider secure messaging and appointment scheduling were becoming more common.

    More recently, the PHR system has seen a greater inclusion of patient tracking and monitoring functionalities as daily reported data from patients and caregivers become more prevalent. Albeit rare, PHR systems also increasingly allow for cost measurement and management. Overall, the results indicate an increasing focus in the literature on newer types and sources of data, as well as on providing patients with access to their health data. Yet some of these may be progressing so rapidly that important related issues are somewhat neglected. Problems related to understanding of health data may lead to stress and anxiety [ 63 ], which could outweigh the potential benefits of data access.

    Hence, research is needed in the area of data visualization and representation models specifically targeted for patient use. Examples of such models available in the literature are the what-if analysis, [ 99 ] brief intervention [ ], and traffic-light feedback system [ 74 ]. These methods indicate the risks associated with specific health activities, along with related outcomes and recommended interventions.

    The traffic-light feedback system, for example, provides patients with an effective visualization tool to track their progress toward attainment of blood pressure goals. In addition, more research is needed to investigate and improve the quality of patient-entered data. Today, more than 35, mobile health apps are available for the iOS and Android operating systems, generating large amounts of data [ ].

    Data are also increasingly entered through patient forums and portals. While new platforms allow the generation and availability of large data volumes, the wide variety of levels of expertise could lead to reliability and validity issues. Patient-entered data have been shown to be reliable for simple measures such as demographics and symptoms, but less reliable when they pertain to reporting more complicated measures such as laboratory values [ 5 ].

    One method for improving accuracy could be to provide patients with standardized measures and guidelines for entering their own data, but even that needs to be part of a broader strategy to verify accuracy of data through triangulation from multiple sources. As the variety of PHR data sources increases, special care is needed for data curation [ ] and harmonization [ ]. Processes need to be established to produce usable patient-reported data that can be used for research [ ].

    Standards need to be developed to improve interoperability between different components of the new PHR systems [ ]. Data integration methods, such as entity stream mining [ ], might be required to cross-reference patient data generated by different tools and devices. In the coming years, PHR systems will create many data-related challenges, such as quality, heterogeneity, openness, security, scalability, and transparency. Abundant patient data might also trigger information overload. While potentially beneficial for improving health outcomes, streaming patient data can amount to very large volumes, creating new data quality, storage, and analysis issues.

    All of these challenges open doors for valuable research in health information systems. The large amounts of data generated by sensors and devices might also require storage and analysis on the cloud [ ], potentially increasing storage and analysis costs. Sharing patient data between networks may also create a risk of personal health information disclosure [ ], generating additional costs for preserving patient privacy and security.

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    Overall, PHR data evolution indicates a general trend toward greater patient engagement and health tracking. Moving forward, a continuation of these trends will lead to accumulation of vast amounts of rich data. If patients provide permission, research on PHR data can pave the way for patient-centered care.

    The design of patient-centered decision support systems that use a combination of comprehensive individual patient information and aggregate data collections of patient records to provide personalized patient recommendations will be a significant area of research. While past literature has listed patient-provider messaging as an important communication tool for patients and providers, secure message content may potentially provide a valuable patient data source for analysis.

    Based on their reported intended use, patient secure messages may contain information regarding health-related concerns such as new symptoms and adverse events. Among other possibilities, information retrieved from secure messages could, therefore, be used in research to identify treatment side effects and build patient risk models. However, it is important to keep in mind that terminology used by patients is likely to differ from terminology used by providers.

    Hence, natural language processing models traditionally used to extract patient information from provider notes may need to be adapted to fit the patient context. Recently developed and highly effective deep learning algorithms could also be used to extract, search, sort, and analyze information from the tremendous amounts of image, voice, and video data [ ] available in the PHR. Other new techniques might be needed to analyze relational data, such as from Google Maps and Google Calendars. Also, current methods used to store, extract, and analyze EHR data are not adequate for analysis of large volumes of time-series data.

    Nonrelational databases might be needed to store tracking information. Stream learning algorithms [ ] would also need to be applied to extract meaningful information from the terabytes of streaming data analyzed. As patient-centered decision support systems are being implemented, it is important to ensure the validity of the generated output. Misclassification errors can be dangerous in this domain. Patient systems, which are embedded in mobile devices, need to be evaluated and approved by medical experts.

    Data transmitted from different sources can potentially be leveraged by providers to improve patient and population health outcomes. However, accurate measures are still needed to assess and improve the performance of such systems. In addition, these metrics need to account for biases present in patient-generated data. Prior research indicated that PHR systems are mostly used by patients who are typically more sick. Those are patients with comorbidities, such as cancer survivors [ ]. Therefore, findings and models generated from analyzing these data might not be generalizable to other patient populations.

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    The new health care vision in the United States is characterized by automation and collaboration, creating the need for adaptation by all actors in the industry. Empowered patients today have the opportunity to leverage PHR systems data and functionalities.

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    This, however, requires some level of technical expertise for system access and interaction, and medical knowledge in order to understand and interpret the medical information presented. Similarly, medical providers now have to learn and adopt new technologies in order to report medical data and communicate with patients. As a major actor in the health care industry, insurance companies also need to adapt to the new industry environment. Insurance firms today need to assess the value of virtual medical encounters and automated care, and process new types of patient data such as secure messages.

    Adaptation methods by all health industry players are yet to be assessed and optimized. A limitation of this study is its focus on PHR data reported in the literature. The evolution of PHRs as described in this study might not necessarily reflect the state of the practice.

    More research is therefore needed to extract and evaluate PHR scope and the functionalities of the various PHR systems available in practice. Also, as mentioned above, this study focused on US studies, thereby limiting the scope of our analysis. Research comparing PHR systems in the United States with those used in other countries would help improve future data uses.

    Digital health platforms have changed drastically in recent years. The introduction of distributed PHR systems enabled a shift toward more personalized and increasingly automated health care. The multiuser nature of PHR systems also facilitated patient-to-provider and patient-to-patient information sharing. Yet these changes generated opportunities and challenges at the user, system, and industry levels. Our assessment here of the state of the patient digital infrastructure serves as a valuable foundation for future research.

    Research implications identified also offer ways to significantly advance health information systems research. Identifying available PHR data also facilitates the development of intelligent health systems. Although primarily aimed at health information systems researchers, implications listed in this study can be further extended to health practitioners, insurance providers, and policy makers.

    Conflicts of Interest: None declared. National Center for Biotechnology Information , U. J Med Internet Res. Published online Nov Author information Article notes Copyright and License information Disclaimer. Corresponding author. Corresponding Author: Lina Bouayad ude.

    This article has been cited by other articles in PMC. Abstract Background A new generation of user-centric information systems is emerging in health care as patient health record PHR systems. Objective The objective of our study was to assess PHR data types and functionalities through a review of the literature to inform the health care informatics community, and to provide recommendations for PHR design, research, and practice. Methods We conducted a review of the literature to assess PHR data types and functionalities.

    Results We present several key findings related to the scope and functionalities in PHR systems. Conclusions Efforts are needed to improve 1 PHR data quality through patient-centered user interface design and standardized patient-generated data guidelines, 2 data integrity through consolidation of various types and sources, 3 PHR functionality through application of new data analytics methods, and 4 metrics to evaluate clinical outcomes associated with automated PHR system use, and costs associated with PHR data storage and analytics.

    Keywords: personal health record systems, health records, personal, electronic health records, data analytics, medical informatics, patient-centered care, review, health platforms, multiorganizational systems, ultralarge systems. Introduction The idea of patient health records PHRs emerged in the early s [ 1 , 2 ] with the goal of increasing patient engagement and empowerment, which in turn was intended to enable continuity of care, error reduction [ 3 ], treatment choice, and patient-provider partnership building [ 1 , 2 ]. Methods We conducted a review of US literature published from through to assess the scope and functionalities available through the PHR, along with associated data elements, formats, and sources.

    Eligibility Criteria In this review, we defined PHR as an electronic record designed for patients to self-manage care [ 6 ]. Open in a separate window. Figure 1. Data Categorization A list of all data elements extracted from the selected articles was further grouped by the reviewers into major data categories. Functional Taxonomy and Chronological Analysis Following PHR data extraction and categorization, we performed a cross-categorical analysis of the data by percentage, source, and format. Patient Health Record Systems Data—Scope The bar graph in Figure 2 displays the frequency of data elements described in the articles we reviewed.

    Figure 2. Patient health record PHR data category by citation percentage. Table 1 Patient health record data: common formats and sources. Figure 3. Patient health record PHR data elements by year of first mention. Figure 4. Discussion Implications and Future Directions—PHR Data Overall, the results indicate an increasing focus in the literature on newer types and sources of data, as well as on providing patients with access to their health data.

    Limitations A limitation of this study is its focus on PHR data reported in the literature. Conclusions Digital health platforms have changed drastically in recent years. Multimedia Appendix 1 Patient data elements reported in the literature.

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    Click here to view. Footnotes Conflicts of Interest: None declared. References 1. Sounding board. Giving the patient his medical record: a proposal to improve the system. N Engl J Med. Hinman E, Holloway J. The patient carried personal health record: a tool to increase patient participation in the treatment process. J Clin Comput. Jackson AN, Kogut S. Use of electronic personal health records to identify patients at risk for aspirin-induced gastrointestinal bleeding. Consult Pharm. J Am Med Inform Assoc. Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption.

    Personal health records: a scoping review. Alzheimers Dement. Qual Life Res. Segal J. The role of the Internet in doctor performance rating. Pain Physician. CHF has previously highlighted that there are a range of benefits that are likely to result from the implementation of an opt-out system, as opposed to an opt-in system, including:.

    An opt-out system for consumers will not deliver the same level of value if the system remains opt-in for health professionals. While consumers are likely to benefit from an opt-out system, rigorous governance, access and privacy protection measures are necessary and absolutely crucial to ensure ongoing consumer participation. Consumers want protection and confidence, comprehensive consumer information to ensure informed participation, and straightforward and easily accessible methods for opting-out should they not wish to participate. An opt-out model is acceptable for consumers only if the personally controlled aspect of the record remains intact.

    For consumers to have confidence in the system, and for participation to be informed in the context of an opt-out system, there will need to be:. CHF appreciates the challenges that would be presented by a change to an opt-out model at this stage. Subscribe to our newsletter 'Consumers Shaping Health' to keep up to date with what we're doing and how you can best make your voice heard. You can also elect to hear from us on upcoming opportunities and events. Search form Search this site. Follow CHF. Move to an independent governance arrangement that includes consumers.

    Specifically: the governance arrangements to be reviewed with a view to appointing an independent PCEHR System Operator; and the governance arrangements include an Independent Advisory Committee that includes strong consumer representation. CHF recommends the immediate resolution of current barriers that prevent the adoption of additional functionality in particular the incorporation of pathology results and diagnostic imaging results onto the PCEHR.