Measuring and Managing Population Health Texas Medicine February 2018

Information and Communication Tools

Texas Medicine Logo(1)

Symposium on Population Health — February 2018 

By William M. Tierney, MD; Justin F. Rousseau, MD, MMSc; and Anjum Khurshid, MBBS, PhD

William M. Tierney, MD, is professor and chair of the Department of Population Health at The University of Texas at Austin Dell Medical School. Justin F. Rousseau, MD, MMSc, is assistance professor of neurology and population health and Dell Medical School. Anjum Khurshid, MBBS, PhD, is assistant professor of population health at Dell Medical School.

Health care delivery and health promotion require timely, accurate, and useful information. Nowhere are useful data more needed than population health management. Although mountains of health-related data exist, useful information is often diffuse, poorly organized, and often inaccurate and incomplete, and doesn't serve those providing health care to individual patients, managing care for groups of patients, or promoting health for communities. 

Information and communication technologies are rapidly evolving to enhance population health management. These tools include electronic health records, health information exchanges, patient portals and personal health records, telemedicine and virtual health tools, the internet and social media, mobile devices, and wearable sensors. We describe each of these emerging health technologies and their future opportunities for enhancing population health.  

Introduction

The field of public health originated in 1915 with the Welch-Rose Report, which resulted in establishing the first U.S. schools of public health.1,2 This report argued for professionally trained public health workers as parallel entities to medical doctors, separating health promotion and disease prevention from curative medicine. Population health, however, is a newer concept: From 1960 through 1990, the term "population health" occurred in the title or abstract of only 86 articles in Medline (Figure). Twenty such articles were published in 1990, 118 in 2000, 378 in 2010, and 997 in 2016. Population health improvement has been termed the "third curve of academic medicine," reflecting an evolution of the academic mission of medical schools beyond treatment of individual patients.3

However, the term "population health" has multiple meanings depending on one's perspective. As shown in Table 1, populations can be patient cohorts defined by who provides their health care, where health care is delivered, or who pays for it. Populations can also be defined geographically and include many people who are not patients at all. The foci of population health include treating existing conditions; providing primary, secondary, and tertiary prevention; and overcoming social, economic, and structural barriers to health and well-being.4

Health care is an information-intensive business: Its efficiency, effectiveness, quality, and costs depend on the right information, on the right people being in the right place in the right format at the right time — the "five rights" of health informatics.5,6 One cannot improve any aspect of health or overcome any barrier to health, without being able to rigorously define and measure it. Yet health care delivery systems determine only 20% of health outcomes compared with 40% for social and economic factors, 30% for health behaviors, and 10% for people's physical environment.7,8 Additionally, a majority of clinical research is performed at academic medical centers where fewer than 1 person in 1,000 is hospitalized annually.9 Therefore, comprehensive (i.e., geographic) population health improvement requires comprehensive, detailed, timely, and actionable data from both within and outside of health care delivery systems. 

Population Health Informatics

We are in the Information Age and are witnessing remarkable, and remarkably rapid, developments in information and communication technologies. In the rest of this article (summarized in Table 2A, 2B, 2C), we discuss the currently available population health information management tools, project future tool development, and suggest forward pathways. 

Electronic Health Records (EHRs)

The Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the American Recovery and Reinvestment Act of 2009,10 provided more than $30 billion to place EHRs in U.S. hospitals11 and physician offices.12 It was successful: To date, more than 95% of acute care hospitals and 87% of physician offices use EHRs.13 For many health care providers (especially physicians), however, EHRs are difficult and time-consuming to use and sometimes impede health care delivery.14-17 Yet, because of the high adoption of EHRs, health systems and their providers now have usable, mostly standardized data to manage individual and groups of patients to enhance health care quality and outcomes, control costs (hopefully), and increase patient safety by reducing errors. Patients with problems accessing health care and adhering to treatments can be identified and helped. 

Yet to date, EHRs are not being widely used for population health management. Current EHR systems make it difficult for health care team members to enter relevant data, often requiring redundant data entry from all team members, leading to widespread workarounds such as copy-and-pasting prior notes,18 errors in data entry, or omission of potentially useful data that render EHRs inaccurate and difficult to read and navigate. Entering required data within visit notes to justify patient billing often leaves little time for documenting information needed to manage patients' care. Variability in the quality of data entered into EHRs has broad implications for the secondary use of these data for quality reporting and research.19

Even with efforts toward using structured reporting, free-text notes and reports will always be required to tell the patient's story and describe procedures. Thus, we need increasingly sophisticated natural language processing (NLP) tools to extract useful and reliable data from free text20,21 or radically redesigned and less cumbersome methods of data entry. 

Maximizing the usefulness and use of EHRs for patient and population health management will require the Centers for Medicare & Medicaid Services (CMS) and other payers to stop relying on the physician's data entry for payment, e.g., through new global or bundled payment models.22 Finally, most population health management tools in EHRs rely on problem lists and billing diagnoses that lack diagnostic accuracy.23 Because there is little if any consensus on how to define diseases, conditions, and outcomes of treatments using diverse types and sources of clinical data, the entire field of database epidemiology needs to grow and rapidly evolve with a focus on data quality.24 This will require substantial funding by the National Institutes of Health, the Agency for Healthcare Research and Quality, and the Centers for Disease Control and Prevention as a core "basic science" of population health. 

Health Information Exchanges (HIEs)

Most patients receive health care from multiple providers in multiple health systems. Therefore, avoiding errors and duplications while effectively and efficiently managing patients' care requires data from multiple sources, e.g., EHRs, laboratories, and pharmacies. Currently, tools don't exist for real-time, Google-like collation of data into "virtual EHRs" for individual patients. There are emerging tools for requesting data from other EHRs for managing individual patients,25-27 but they are not useful for managing care for patient populations. Until an application programming interface (API) is available to collate data on the fly from multiple EHRs, the so-called "universal API,"28 comprehensive population health management will require HIEs ― platforms that allow collection and reconciliation of data from different EHRs to create a single health record for each individual. Under the HITECH Act, the federal government invested more than $550 million to help create HIEs in all states;29 some states (like Texas) have multiple regional HIEs. An even larger number of private and enterprise level HIEs provide interoperability of disparate EHR systems that do not talk to each other. However, combining data from multiple EHRs into HIEs requires patient identity matching, which takes considerable expertise30 and still generates occasional errors (e.g., patients with multiple HIE identities or a single HIE identity representing multiple patients). The best solution would be a national patient identifier, which has been an unpopular notion in the United States.31,32

Once established, HIEs can support not only managing individual patients but also reporting notifiable conditions to health authorities in real-time, facilitating active biosurveillance for common conditions, such as influenza outbreaks, and uncommon ones, such as clusters of food-borne illnesses33,34 or sexually transmitted diseases.35 HIEs provide opportunities for managing population health where members of the population interact with multiple providers. They also save on duplicative and unnecessary laboratory and imaging costs.36

Unfortunately, most HIEs have not been financially sustainable.37,38 We need new business models that effectively leverage the information stored for disease prevention and management, government subsidies, or both — at least until a universal API is widely adopted and large HIEs are no longer needed. 

Moreover, all existing HIEs are, in reality, large, multisystem EHRs that don't include important nonclinical health-related data such as demographics from the Census Bureau, environmental data from the National Oceanic and Atmospheric Administration and the Environmental Protection Agency, data on population migration from the U.S. Postal Service, and high-accident locales from transportation and emergency medical services data. Prior efforts by public health or academic institutions to compile social vulnerability indicators from multiple sources39-41 have not been linked to EHRs or HIEs. An HIE that includes both clinical and nonclinical health-related data could facilitate collaboration of health systems and community organizations in supporting the health of populations, focusing together on difficult issues such as homelessness, poor nutrition, violence, and environmental exposures42 and help deliver integrated and coordinated health and social services with better outcomes. 

Patient Portals and Personal Health Records (PHRs)

Portals are websites that are becoming increasingly available to patients for communicating with their health care providers.43,44 Yet many portals are difficult to use, and patients often see multiple providers with different portals. As a result, patient portal use in most health systems is low.45 Most portals do not allow patients to enter data into their EHRs,46 and commercial attempts to create PHR systems that capture patient-entered data have failed.28,47 A better approach might be to allow patients direct access to their EHRs and HIEs. This would require significant programming to provide patients (often with limited health literacy and numeracy48-50) with easy access to understandable information and easy-to-use tools for recording categorical data (by clicking on relevant symptoms and conditions) or entering free text from which NLP could extract reliable data. Having easy-to-use patient interfaces and minimizing the burden of patient data entry are key to success. Additionally, wearable monitors will allow patients to provide streams of data or data summaries to their EHRs. 

Success will require widespread health literacy and computer training across the lifespan from kindergarten to nursing home. Enhancing health literacy and numeracy should become a standard goal of lifelong learning and will be required to maximize the value of portals and PHRs for capturing critical patient-reported symptoms, conditions, and outcomes, and for providing a vehicle for patients to actively participate in their care. 

Email, Telemedicine, and Virtual Health

Electronic patient-provider and provider-provider communication and health care management by asynchronous email, real-time text, and telemedicine tools is rapidly increasing. These tools will likely become the predominant means for delivering health care in the 21st century, relegating face-to-face patient encounters to situations requiring physical examinations, tests, or procedures. 

The usefulness of email, text, and telemedicine for population health management is unclear. Providers can use email lists to send group messages to their patients with common conditions (e.g., encouraging patients with diabetes to inspect their feet) or to target those with common concerns (e.g., failure to refill important prescriptions). Telehealth platforms could be particularly helpful for patients with transportation, child care, or other impediments to accessing health care. Such tools could also facilitate communication among health care providers and community support organizations and patients' family members or caregivers needing social support. These new modes of communication also offer the promise of expanding the impact of specialty care into primary care and community settings to allow more comprehensive care to populations where geography is a barrier to access.52

Successfully implementing and using telehealth tools will require payment models that compensate health promotion and disease management without in-person visits. Existing tools need further development to be user-friendly, and standalone telemedicine companies will need efficient means for communicating with other providers (and their EHRs) to assist in patient and population management. The same considerations for enhancing the quality of data collected through EHRs and HIEs must apply to these new virtual health innovations for population health management. And evaluations of virtual health tools should include their use in population health management and research. While technology for virtual health has been improving considerably, the policies that will enable these tools to be integrated in usual practice are lagging far behind. The regulatory environment to address liability, scope of practice, and reimbursement vary from state to state53 and prevent providers from fully utilizing these technologies.54

Internet and Social Media

The internet has become a primary source of health information. For example, more than half of residents surveyed in Austin  turn to the internet for health information.55 However, not all websites provide up-to-date, accurate, evidence-based advice.56,57 A high percentage of social media posts concern health and health care,58 and increasingly online communities are emerging that provide information and support to patients with shared conditions and their families.59 Such activities should be encouraged, but missing are mechanisms to assess the value of online health-related information. In fact, some of what is presented as health information and evidence may actually be harmful to individual's health.60-61

Social media can also be a source of information for population health management. For example, Facebook and Twitter posts are more timely and accurate for identifying influenza outbreaks than biosurveillance.62-64 Social media also offers a new avenue for evaluating the quality of health systems65 while health systems are recognizing the importance of engaging patients through different modes, including social media. Population health informatics expertise is needed for the socially responsible use of such information. Similarly, health communication theory and research must inform the uses and limitations of social media in personal and population health strategies.66

Mobile Devices and Wearable Sensors (Consumer Health Technologies)

Millions of activity monitors used today have had little impact on health care and unclear impact on health.67 For many, however, such devices are the primary source of health information.68 Thousands of mobile device apps are available for capturing data on activities, diet, sleep, moods, and practically anything else. Much of this information might be very useful in early identification of conditions needing intervention, e.g., depression with suicidal ideation or adherence to treatment recommendations. Yet, most wearable and home monitors and mobile apps are being used by people in isolation from providers of health care and population health. Providers lack the time and expertise to deal with data from these devices and may question data validity. Data proven useful for patient or population health management should be included in patients' EHRs and HIEs in standardized formats. However, mechanisms for integrating consumer health data into EHRs/HIEs is lacking.46 While such patient-generated health data can guide person-centered care, there are also increasing concerns about health information of patients being collected and used by companies not covered by the legal protections to privacy and confidentiality of clinical.69 Much research and development is needed to better understand what infrastructure and processes are needed to use these sources of information without overloading people and their health care providers and caregivers. 

Privacy and Security

Widely reported breaches of information from health care and non-health care settings have people rightly concerned about their privacy and the security of data in EHRs, HIEs, and consumer health applications.70-72 Given the enormous number of organizations holding health-relevant data,73 the number of breaches is surprisingly low. Moreover, most health care data are not sensitive (e.g., negative tests, normal vital signs, inconsequential diagnoses). Privacy and security standards and tools are good and improving, yet people need assurance that their data are safe. One way to assure them would be giving them control over who can see specific data in their EHRs and HIEs.74-77 This is currently technically difficult78 but will become easier and more widespread with improvements in data standards and NLP tools. Conversations between health care providers and patients must guide which data are patient-controlled (without overwhelming them with too many choices), who gets EHR access and under what conditions, and when those preferences can be overridden by health care providers. This must include discussions of when consent is and is not needed for research, quality improvement, patient safety, and population health management. HIPAA regulations79 and the recent revision of the Common Rule are helpful, but involving patients in these discussions will be necessary to engender trust.80  

Conclusions

Health care is rapidly evolving from primarily focusing on individual provider-patient encounters to managing cohorts of patients and people in communities. The roles of health systems, providers, and civic organizations are also evolving, as are professional expectations and competencies. Information availability and management is key to success of both individual patient care and population health management, and new tools and approaches are rapidly evolving. We have outlined the current state-of-the-art of population health informatics, future opportunities, and barriers and facilitators to realizing them. Collaboration among health systems, health care providers, patients and their families, community and civic organizations, community residents, and researchers will be key to making significant progress to meet The Triple Aim of better care, better population health, and controlled costs.81

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February 2018 Texas Medicine Contents
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Last Updated On

February 01, 2018

Originally Published On

January 17, 2018