Ann Scheck McAlearney, ScD

The COVID-19 pandemic has highlighted the need for, and barriers to, a comprehensive plan to implement advance care planning (ACP) in the United States. The overwhelming of health care infrastructure, coupled with pandemic restrictions at many health care facilities, curtailed interactions that give clinicians the ability to elicit patient preferences and the capacity to interact with families. Although the pandemic facilitated many policy changes related to care delivery, even allowing telehealth ACP, more transformative innovation must accompany these adjustments to both counteract pandemic-driven obstacles and address existing barriers to ACP moving forward. To address these and future needs, we suggest a shared public health–primary care ACP partnership (Public-Primary ACP) for adult patients. Although such an approach presents steep implementation barriers, similar partnerships, such as newborn screening (NBS) programs, have succeeded by dreaming big at the outset and evolving over decades. Leveraging experience from this program, we present a Public-Primary ACP implementation road map following a 5-step process paralleling NBS programs that includes prework, screening, follow-up, assessment and management, and program evaluation. The ongoing pandemic has demonstrated the need to think beyond a traditional brick-and-mortar approach to medical care and highlights the importance of adapting to meet patients and families in the community. Public-Primary ACP proposes processes that will require significant contextual modifications throughout implementation but are worth considering now in response to ongoing ACP health care system failures. If successful, Public-Primary ACP may promote patient preference–aligned care in a postpandemic health care system, albeit at a significant cost.

Am J Accountable Care. 2022;10(1):31-37. 

SARS-CoV-2 and the ensuing global pandemic of COVID-19 represent one of the most significant public health emergencies of the last century.

 Although COVID-19 vaccines provide hope for pandemic mitigation, the slow uptake of vaccines, coupled with the emergence of highly contagious SARS-CoV-2 variants such as Delta and Omicron, forebode a prolonged pandemic recovery.

 Pandemic-driven morbidity and mortality rates have underscored the need for advance care planning (ACP), especially for older adults and patients living with chronic disease.

 These pandemic disruptions provide an opportunity to drastically reenvision how ACP can be successfully delivered. Ideally, ACP promotes preference-aligned medical care during serious illness through an anticipatory process that helps patients and their surrogates identify and communicate health care preferences.

 However, despite a quarter-century of investigation and intervention, translation of ACP to clinical practice has yielded uneven results.

Inadequacies in ACP predate the COVID-19 pandemic. At least one-third of dying hospitalized patients receive medical care that is not aligned with personal preference.

 Those least likely to receive ACP are at highest risk for COVID-19 infection and complications: older adults with complex chronic disease, underrepresented racial and ethnic groups, individuals living in poverty, and those with lower educational attainment.

 Pandemic-related clinician shortages and limitations to usual patient care

 risk further exacerbation of ACP inadequacies and disparities. Systematic delivery of high-quality ACP, during and beyond the COVID-19 pandemic, requires serious consideration of paradigm shifts from existing models.

The restructuring of health care delivery processes as part of the COVID-19 response provides opportunities to envision foundational ACP transformation. At the peak of the pandemic in the United States, up to 2 million patients daily were receiving COVID-19 testing,

 delivered by a combination of public health, clinical, and commercial entities. Although primary care providers are a critical component of COVID-19 testing workflows, direct provider-patient visits occur only in a small proportion of these interactions, often driven by illness acuity or other patient needs.

 Local public health departments provision COVID-19 testing and follow-up for case investigation and contact tracing, markedly increasing the frequency of health care interactions with community members.

 These shifts in health care delivery present new prospects for coordination between frontline public health and primary care entities for ACP. The pandemic has not only highlighted a need for reforming ACP but also provides new approaches to drive transformation. We present a public health–primary care ACP model (Public-Primary ACP) as one compelling mechanism for transformation. Such partnerships are successfully used elsewhere, such as for newborn screening (NBS).

 This new ACP delivery model can help address specific challenges presented by the COVID-19 pandemic while filling long-standing gaps in ACP for a more patient- and family-centered health care future.


NBS programs epitomize primary care–public health partnership in clinical care coordination, handoffs, and delivery. These programs have formally existed for more than 60 years and currently provide ubiquitous screening to newborns for genetic, endocrine, and metabolic disorders 24 hours after birth.

 Initial adoption of newborn screening, however, was a gradual process. The discovery in the 1960s of a blood test for the detection of phenylketonuria (PKU) in newborns demonstrated the scientific and public health potential of NBS. Much of the medical community met NBS with great skepticism, initially rejecting efforts to systematically implement this test, arguing that PKU was too rare to warrant such attention.

Momentum for the systematic adoption of PKU infant screening grew as advocates, including parents of children with metabolic disease, drove changes in governmental policy and medical practice after advances in laboratory technology opened the door for eventual clinical feasibility of screening.

 These advocacy efforts prompted the American Academy of Pediatrics (AAP) to endorse PKU screening for newborns in 1965.

 State health departments subsequently began implementing formal screening programs through testing protocol development, funding mechanism identification, and laboratory infrastructure establishment.

 As additional tests were developed, state NBS panels expanded, increasing the early detection of congenital disease to reduce disease-related morbidity and mortality.

 Despite the initial skepticism and implausibility facing NBS, the program experienced successes unimaginable to its initial advocates.

As of 2018, all states provide universal screening for at least 35 conditions, including neonatal hypothyroidism, PKU, and cystic fibrosis.

 NBS programs now screen greater than 99.9% of the 4 million infants born each year, detecting congenital metabolic or genetic conditions in an estimated 12,500 infants annually.

 NBS programs integrate laboratory testing with parent/provider education, follow-up, diagnosis, treatment, and evaluation.

 In 2006, the AAP outlined a framework highlighting key components of newborn screening: (1) prework, (2) screening, (3) follow-up, (4) assessment and management, and (5) program evaluation (

 Each step requires complex care coordination between primary care pediatricians and local health departments.

 NBS program evaluation has continually improved screening breadth and uptake. Moreover, the universality of NBS has normalized neonatal serious illness evaluation. This model of successful coordination between primary care and public health entities provides an important road map that can inform the restructuring of ACP delivery in response to COVID-19–driven health care transformation.

Application of the NBS Framework to ACP: A Public Health–Primary Care Approach

By aligning itself with the NBS framework, the Public-Primary ACP strategy will promote universal ACP as a part of comprehensive clinical care while remaining feasible for real-world implementation.

 Importantly, the long-term success of an ACP approach motivated by the NBS framework will require adaptability to local circumstances and environmental considerations. Public-Primary ACP strategies that align with COVID-19 health care transformations and mirror NBS processes include (1) preparing patients for program participation at the point of scheduling COVID-19 testing to give patients the opportunity to engage in the program or decline participation (prework); (2) serious illness risk screening during COVID-19 testing encounters (screening); (3) handoff to a primary care provider for ACP delivery and documentation (follow-up); (4) promoting preference-aligned care through centralized, accessible ACP documentation, and when possible, ACP-informed shared decision-making (assessment and management); and (5) collaborative process measure evaluation by public health and primary care partners for continuous program improvement (program evaluation). The Figure

 describes these proposed Public-Primary ACP interventions corresponding to each of the 5 AAP NBS framework components. Gradual, piecemeal, and modified adaptation of these proposed components can yield realistic but steady uptake of the Public-Primary ACP concept while advancing a culture shift that can grow over time, similar to the progression seen with NBS programs.

 Although the unpredictability of the COVID-19 pandemic has created waxing and waning demand for COVID-19 testing and contact tracing, using these pandemic opportunities to introduce and normalize the concept of ACP as a public health service may gradually increase ACP access to individuals and reduce ACP health disparities.

Another opportunity resulting from the tailored implementation of the Public-Primary ACP framework, aligned with NBS, involves the development of notification infrastructure that allows comprehensive ACP information sharing across public health and fragmented health system entities. These capabilities would provide a marked improvement over ACP modules contained within electronic health records (EHRs) that often lack the capacity for sharing across health settings (eg, primary care, subspecialty, inpatient) and health systems, thus advancing patient-centered, preference-aligned high-value care.

 The proposed systems build on recent innovations promoting ACP information sharing between public health and health care systems, such as statewide patient registries housing Advance Directives and Portable Medical Orders (POLST).

 The transfer of information about patient preferences, proxy decision makers, and goals of care within and across health systems offers significant potential to improve end-of-life care.

Finally, process evaluation plans, collaboratively established by program partners, can inform further implementation and continuous quality improvement. To optimize their partnerships, primary care and public health entities can tailor responsibility and resource delegation in response to local workflows, expertise, and infrastructure. For example, current applications of the Public-Primary ACP framework may consider prioritizing patients who receive ACP outreach based on factors known to increase risk of adverse COVID-19 outcomes,

 whereas future applications of this framework may include prioritizing equitable ACP delivery based upon factors such as age, life expectancy, and social determinants of health.

 Public-Primary ACP can potentially address long-standing barriers to effective ACP that have impeded the delivery of preference-aligned care by adding innovative care delivery structures, systems, and resources to existing ACP processes that involve patients and health systems.

If implemented, Public-Primary ACP will likely parallel the slow and fragmented uptake of NBS in the United States. Similar to PKU technology that catalyzed NBS in the 1960s,

 we collectively have several facilitators that would promote the launch and feasibility of Public-Primary ACP. The COVID-19 pandemic has fueled unprecedented public health investments. These investments will provide capacity to solidify public health–primary care collaboration forged during the pandemic. Second, patients have become accustomed to public health and primary care jointly delivering COVID-19–related services (eg, public health for test sample collection and contact tracing; primary care for diagnosis and disease management). This precedent can make shared management in Public-Primary ACP more acceptable to patients. Third, recent EHR and registry ACP advances have created an infrastructure for proposed information sharing of ACP documentation across public health and health system entities. For example, the partnership between the West Virginia Health Information Network and the West Virginia Center for End-of-Life Care, which has yielded a statewide registry to house advance directives and POLST for patients across the state, demonstrates that ACP information sharing between public health and health care entities is feasible with current technologies.

 Although the nature of this bidirectional communication must be individualized to account for local public health information systems and EHR platforms, progress in policies and technologies promoting health information sharing across systems will continue to facilitate Public-Primary ACP information sharing. Finally, many advances in national health policy concerning ACP reimbursement enhance feasibility and enthusiasm for creating systems-level ACP strategies. The inclusion of ACP as a quality measure for value-based payments by CMS has stimulated institutional engagement toward ACP innovation.

 Simultaneously, provider reimbursement for ACP delivery allows individual clinicians to dedicate clinical time to ACP with patients.

 These circumstances create a primed environment for Public-Primary ACP, especially at local levels. Such local implementation can motivate Public-Primary ACP advocacy and dissemination, similar to the historical development of NBS. Our proposed innovation and its integration of public health infrastructure build on such existing models as POLST by moving beyond the patient locus, allowing for a more holistic ACP workflow.

Several additional structural and policy supports must accompany the proposed framework to ensure its success. Expanding applications of existing infrastructure to reimburse for Public-Primary ACP services can provide critical initial resource investments to local health departments that want to implement framework components. In the short term, one strategy can include creating reimbursement pathways for Public-Primary ACP through the Provider Relief Fund, an HHS fee-for-service claims reimbursement system for COVID-19–related treatment coverage among uninsured patients.

 Small adjustments in existing ACP billing requirements, such as allowing health departments to submit billing codes and deeming public health workers to be qualified professionals able to deliver team-based services, can provide more long-term program resourcing. These immediate strategies may also promote the adult health care access needed for Public-Primary ACP success.

 In areas facing regional shortages in primary care and public health infrastructure, dedicated investments from CMS Innovation Center funds, which have piloted and expanded successful programs such as Comprehensive Primary Care Plus through payer alignment and regional strategy,

 can support the resource investments needed to implement program components. Additionally, a CMS Innovation Center model may also facilitate gradual adoption and ongoing evaluation of Public-Primary ACP activities among patients with chronic disease at the state level. Furthermore, Public-Primary ACP successes using these mechanisms will increase ACP delivery to patients, enhancing quality-driven institutional reimbursement through programs that integrate ACP as a quality measure, such as the CMS Bundled Payments for Care Improvement Advanced Model.

 These successes could inspire further institutional buy-in and new partnerships for Public-Primary ACP expansion.

 Additional policy changes to sustain Public-Primary ACP in future phases of expansion can be informed by the initial experiences. However, the road map described here provides the initial impetus needed to pilot the framework. This reenvisioning of ACP by harnessing recent COVID-19–driven health care transformation may help eventually overcome the ongoing stagnation of ACP delivery to patients.

 Consistent program evaluation and response can improve the reach of Public-Primary ACP, increasing overall ACP accessibility over time.


The Public-Primary ACP approach offers a promising potential model for improvements in ACP during and beyond the COVID-19 pandemic. Our framework for ACP, modeled after long-standing NBS programs, seeks to leverage opportunities and barriers created by the COVID-19 pandemic to reenvision ACP. This proposed public health–primary care collaborative ACP approach can expand beyond the duration of the pandemic through ongoing modification and transformation. Similar to the NBS program, gradual investments in payment, policy, and evaluation infrastructure will encourage continued program uptake and growth to address persistent ACP care gaps using a novel approach.

 Division of General Internal Medicine (SB-B, JC), Center for Health Outcomes in Medicine Scholarship and Service (HOMES) (SB-B, BPO, KOM, BJL, DH, JC, JFPB), and Division of Palliative Medicine (BJL), Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, OH; Division of Health Services Management and Policy, The Ohio State University College of Public Health (BPO, ASM), Columbus, OH; The Ohio State University College of Nursing (KOM), Columbus, OH; Department of Family and Community Medicine (ASM); Center for the Advancement of Team Science, Analytics, and Systems Thinking (CATALYST) (ASM, JFPB); Department of Biomedical Informatics (ASM, NC, JFPB); and Center for Bioethics and Medical Humanities (DH, JC), The Ohio State University College of Medicine, Columbus, OH.

 Dr Moss has received a College of Nursing seed grant for 2019-2021, a National Institute of Aging diversity supplement for 2019-2022, and a MAYFUND Scholars Award for 2021-2023. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design (SB-B, BPO, BJL, DH, JC, JFPB); analysis and interpretation of data (KOM, ASM, NC); drafting of the manuscript (SB-B, BPO, KOM, BJL, ASM, DH, JC, NC, JFPB); critical revision of the manuscript for important intellectual content (SB-B, BPO, KOM, BJL, ASM, DH, JC, NC, JFPB); administrative, technical, or logistic support (SB-B, BPO); and supervision (SB-B).

 Seuli Bose Brill, MD, Division of General Internal Medicine, Department of Internal Medicine, The Ohio State University College of Medicine, 895 Yard St, Columbus, OH 43212. Email: Seuli.Brill@osumc.edu.

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Articles

This article proposes a new model, Public-Primary ACP, that leverages coordination between primary care and public health workforces to improve delivery of advance care planning.

Integrating Primary Care and Public Health for Advance Care Planning

Patient portals are health information technology tools that offer patients access to their personal health information and a means to communicate with health care providers, but little is known about their impact on patient satisfaction. Identifying factors that increase patient satisfaction may improve patient care and can protect health care providers from financial penalties. Our study sought to investigate how patient portals are associated with patient satisfaction in both inpatient and outpatient settings.

Retrospective, pooled cross-sectional study.

 Data from the Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) and Hospital CAHPS (HCAHPS) patient satisfaction surveys were linked to inpatient and outpatient portal account status at a large academic medical center. Using fractional logistic regression, we investigated the relationship between patient satisfaction survey scores and patient portal activation.

 Patients with an activated outpatient portal account reported higher patient satisfaction across a subset of the CG-CAHPS dimensions, and patients with an activated inpatient portal account reported higher patient satisfaction across a subset of the HCAHPS dimensions, compared with patients without the respective portal accounts.

Our study suggests the potential for patient portals to enhance patient satisfaction, especially in areas such as care coordination and care transitions. In both inpatient and outpatient settings, portal use may improve the patient-centeredness of care. Our findings indicate important considerations for both health care organizations and their patients to promote patient portal use as a means of improving patient satisfaction, especially in the context of potential impacts on reimbursement and reputation.

This study sought to investigate how patient portals in both inpatient and outpatient settings are associated with patient satisfaction as measured by Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) and Hospital CAHPS (HCAHPS) surveys.

Patients with an activated outpatient portal account reported higher patient satisfaction in 2 dimensions of the CG-CAHPS survey (communication with their doctor and care coordination), and patients with an activated inpatient portal account reported higher patient satisfaction in 3 dimensions of the HCAHPS survey (communication with their nurse, care transition, and discharge), compared with patients without respective portal accounts.

The highest marginal gains in patient satisfaction scores for patients with an activated portal account were for care coordination for the outpatient portal and care transition for the inpatient portal.

Future work should evaluate the impact of patient portal functions and their use as mediating factors of the effect of patient portals on patient experience.

Patient satisfaction has become an important measure as the need for health care to be more patient centered has been increasingly emphasized. Identified as a key element of care quality by the Institute of Medicine,

 patient-centered care encourages providers to include patients as partners, engaging and empowering patients to actively participate in their health care.

 With the shift to this focus on patient-centered care, patient experience has become an important aspect of health care quality, in which patient satisfaction with their care is used as one measure of the patient experience.

To improve patient satisfaction, health care providers are increasingly focused on increasing the patient-centeredness of care, and patient-centered health information technologies such as patient portals are one such tool that may be beneficial. Patient portals are offered as websites or mobile applications and are tethered to a patient’s electronic health record (EHR) to provide patients with access to their personal health information and a means to manage their health care and communicate with their health care providers. Through these functions, patient portals satisfy CMS’ Promoting Interoperability Program (formerly the Meaningful Use program) requirements to improve quality of care by supporting health information exchange between health care providers and their patients.

Although they were first implemented in the outpatient setting, patient portals are now increasingly implemented in the inpatient setting, with functions tailored to support patients during hospitalization. Outpatient and inpatient portals together have the potential to benefit patients across care settings. Multiple benefits of patient portals have been reported in previous studies, including improved patient knowledge about their health conditions, increased patient engagement, and enhanced patient-provider communication,

 but the impact of patient portals on patient satisfaction is not well understood.

Our study aimed to address this gap in knowledge by exploring how outpatient and inpatient portals might be associated with patient satisfaction, as measured by Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) and Hospital CAHPS (HCAHPS) survey responses. The CG-CAHPS survey

 were developed by the Agency for Healthcare Research and Quality

 to collect standardized perspectives of patient satisfaction based on patients’ outpatient and inpatient experiences, respectively. These surveys assess patient satisfaction across several dimensions of the patient experience, such as communication with doctors, nurses, and staff; care coordination and care transitions; access to and responsiveness of care; and facility conditions.

Understanding the association between patient portal use and patient satisfaction, as measured by the CG-CAHPS and HCAHPS surveys, has important implications for the delivery of managed care. First, patient satisfaction measures are interpreted to reflect the quality of care received by the patient because they are based on patients’ perceived needs and expectations.

 In addition, public reporting of patient satisfaction scores by CMS provides comparable data among health care providers that can affect their reputation and influence patient recruitment and retention.

 Furthermore, patient satisfaction is included as a factor in performance assessments that affect reimbursement payments from CMS.

 Understanding whether and how patient portals are associated with patient satisfaction can help direct health care organizations to use these tools in ways that positively affect patient experience.

This study was conducted at The Ohio State University Wexner Medical Center, a large Midwestern academic medical center (AMC) that includes 6 hospitals and 53 ambulatory care locations. At this AMC, outpatients are offered electronic access to their health care information through an outpatient portal, MyChart (MC; Epic Systems). Inpatients at this AMC are offered Android tablets during their hospital stay; through these tablets, patients have access to an inpatient portal, MyChart Bedside (MCB; Epic Systems).

MC includes functions that allow patients to access their personal health information (eg, medical history, test results), view and schedule appointments, and message their providers. MCB includes functions that are tailored to the hospital setting; these functions allow patients to access their personal health information (eg, test results, vital signs), view an anticipated schedule for their medications and/or procedures, view educational materials, view names and pictures of their care team members, order meals, send requests, and message their care team (see 

Retrospective data were obtained for patient encounters from our AMC’s Information Warehouse (IW) in accordance with the Honest Broker protocol; this protocol is recognized by The Ohio State University’s Institutional Review Board (IRB) as a means to use deidentified data without requiring formal IRB approval. Data were obtained for patient encounters between January 2019 and January 2020 for patients aged between 18 and 110 years. Our study sample consisted of 50,314 outpatient encounters and 7783 inpatient encounters (ie, hospital stays). Our study sample was focused on encounters that have CG-CAHPS or HCAHPS responses from our AMC’s patient population.

Using Epic System’s EHR log files for MC and MCB, we identified variables that captured patient activation of their portal accounts. We defined patients with an activated MC or activated MCB account as those patients who registered their portal account online with an activation code provided by the medical center and successfully logged into the portal system at least once (see eAppendix A for additional details about MC and MCB activation). Among all patients during our study period, approximately 53% had activated MC accounts and 46% had activated MCB accounts.

Patient Satisfaction Surveys: CG-CAHPS and HCAHPS

The IW provided us with the CG-CAHPS and HCAHPS survey scores for the patient encounters of our study population with and without activated MC and MCB accounts during the study period. CG-CAHPS and HCAHPS scores were collected on a rolling basis at the AMC and were aggregated for our study time period. Of note, both the CG-CAHPS and HCAHPS surveys have inclusion and exclusion criteria that are described in great detail in the literature.

The CG-CAHPS and HCAHPS surveys contained questions that were aggregated into composite measures related to 4 and 9 dimensions of patient care, respectively. Each survey also collected 2 global measures that assessed the rating and recommendation of either the provider or the hospital (see 

 for a complete list of survey measures and dimensions). The measures for pain management in the hospital were excluded because scores for this measure were not available from the AMC during the study period because of an institutional decision to not collect this information. During our study period, CG-CAHPS and HCAHPS response rates at the AMC among all patients were approximately 14% and 19%, respectively.

We used top-box scores for each patient satisfaction dimension as the dependent variables for our study. The top-box score for each individual question was calculated as the fraction of respondents who selected the most positive response. Top-box scores within each dimension were aggregated by summing the top-box scores for all questions associated with that dimension and dividing by the total number of questions answered for that specific dimension. This resulted in the top-box proportion for each dimension, which was used as the dependent variable for the fractional logistic regression model. For example, a top-box proportion for Doctor Communication of 0.90 is constructed based on 2700 responses of “always” of a possible 3000 responses to any of the questions under this dimension.

To develop our analytic data set, we merged data from multiple data sources using a unique identifier variable for patient encounters. Using this identifier, we linked patient demographic/clinical information, patient satisfaction scores, and activated MC/MCB account status for patients by encounter. We subsequently split our analytic data into 2 separate sets, one for the MC and CG-CAHPS analysis and the other for the MCB and HCAHPS analysis. Our first data set contained 50,314 eligible patient encounters with CG-CAHPS scores for 1 or more dimensions. Of these encounters, we had 36,798 (73.1%) encounters with activated MC accounts. Our second data set contained 7783 eligible patient encounters with HCAHPS scores, with 3729 (47.9%) of those encounters with activated MCB accounts. For both of our analytical data sets, only CG-CAHPS and HCAHPS responses that were reported after portal activation were retained.

We used patient demographic and clinical characteristics as covariates to obtain adjusted estimates from our empirical models. These covariates, including race, age, patient self-reported health status, health insurance status, gender, and survey mode, were obtained from the CG-CAHPS or HCAHPS survey or the EHR (see 

 for additional details about the selection of covariates used in our empirical model). We also included a covariate that indicated multiple survey responses because respondents answering multiple surveys may have systematic differences in how they responded to the surveys compared with 1-time respondents.

Our study analysis included univariate and multivariate approaches. For the latter, we used fractional logistic regression model estimations on our separate data sets (see eAppendix C for more information about this analytic approach). Our analysis was at the patient encounter level and included patients with multiple encounters; hence, we estimated robust standard errors that clustered and accounted for the unique variance by patients. All statistical analyses, including our univariate tests (analysis of variance for continuous variables and χ

 for categorical and binary variables), were performed using Stata 15 software (StataCorp LLC). For our multivariate analysis, we corrected for multiplicity by performing Bonferroni corrections to maintain a family-wise error rate (FWER) of 0.05. We indicate results that have 

 values below the adjusted α levels for each analytical set.

 provide descriptive statistics about demographic and clinical characteristics for the patient encounters in our CG-CAHPS and HCAHPS data sets. Patients with activated MC and activated MCB accounts were most often White, 65 years or older, and female and had good self-reported health status and commercial insurance. Between patients with activated patient portal accounts (MC or MCB) and their counterparts with no activated patient portal accounts, there were significant differences by all the demographic and clinical characteristic variables used in our analysis. Notably, for both data sets, the groups without activated portal accounts had much older patients and more patients on Medicare than the respective groups with activated portal accounts. Survey mode and multiple survey response differed significantly across groups within each data set. We compared our analytical samples with the overall outpatient and inpatient encounters at our AMC by race, age, gender, and health insurance status. There were statistically significant differences based on these factors for both analytical samples, with the exception of gender in the inpatient sample. Both the inpatient and outpatient samples were more likely to have White, older, and Medicare-covered patient encounters; the outpatient sample was also likely to have more male patient encounters (results available on request).

 reports the unadjusted and adjusted odds ratios for (1) the estimation of activated MC account status (reference: no MC account) on the 6 CG-CAHPS top-box dimensions and (2) the estimation of activated MCB account status (reference: no MCB account) on the 10 HCAHPS top-box dimensions. We also report the marginal effects for our adjusted models, which can be interpreted as the percentage change in the dependent variable (at the mean) associated with the switch from no patient portal to activated patient portal status.

With respect to the results in panel A, the odds of higher top-box proportions for doctor communication were 1.24-fold higher among patients with activated MC accounts compared with those without activated MC accounts. This was a 1.33% higher proportion of top-box scores for doctor communication associated with activated MC accounts. Similarly, the odds of higher top-box proportions for care coordination were 1.20-fold higher among patients with activated MC accounts compared with those without activated MC accounts. This was a 4.22% higher proportion of top-box scores for care coordination associated with activated MC accounts.

Panel B in Table 3 shows that patients with an activated MCB account had significantly higher odds of reporting higher top-box proportions for the HCAHPS dimensions, including nurse communication, care transition, and discharge. Notable relationships included care transition (7.24% higher). The other outcomes (ie, nurse communication and discharge) had higher proportions of top-box scores that ranged from 2.16% to 3.94%.

We reran our analysis for all the outcomes related to MC and MCB account status for encounters with only the most recent CG-CAHPS or HCAHPS scores (ie, without controlling for multiple responses). Our results were consistent for all but 1 outcome; the HCAHPS Discharge dimension was no longer significant at the FWER adjusted α. We discuss our findings based on our original models.

Our study found that patients with an active patient portal account had higher odds of reporting top-box scores on many dimensions of the CG-CAHPS or HCAHPS survey. Patients with an activated outpatient portal account had significantly higher odds of reporting top-box responses to dimensions of the CG-CAHPS survey regarding communication with their doctor and care coordination compared with patients without an activated outpatient portal account. Patients with an activated inpatient portal account had significantly higher odds of top-box responses to dimensions of the HCAHPS survey regarding nurse communication, care transitions, and discharge compared with patients without an activated inpatient portal account.

In many ways, functions of patient portals may be associated with different dimensions of the CG-CAHPS and HCAHPS surveys, as suggested by the findings of our study. For instance, patient portals support patient-provider communication through secure messaging in both inpatient and outpatient settings. In addition, patient portals can assist with the processes of care coordination, care transitions, and discharge from the hospital by providing access to personal health information and educational materials. Notably, the highest marginal gains in top-box scores in our study were for care coordination (4.22%) for the outpatient portal and care transition (7.24%) for the inpatient portal. By facilitating patient and provider communication regarding medications and test results, as well as providing patients tools to help them understand and manage their health conditions, patient portals may be able to support these dimensions of patient experience, as suggested by the association between these dimensions of patient satisfaction and patient portal use.

Interestingly, the dimensions of patient satisfaction that were not positively associated with activated patient portal status were those that were unlikely to be related to patient portal use. For example, activated outpatient patient portal status was not correlated with increased satisfaction with office staff, with whom the patients would not be expected to interact through the portal. Furthermore, portal status was not associated with increased satisfaction with access to care. Although the portal does offer a means to schedule appointments, the questions in this domain ask about phoning the provider’s office and the promptness of receiving appointments or care, which are extraneous to patient portal use. For activated inpatient portal accounts, there was no correlation with dimensions related to the hospital facility (ie, cleanliness and quietness of the hospital environment) or with responsiveness of care (eg, receiving help with the call button or getting to the restroom), neither of which were related to portal use.

Additional support for the role of patient portals comes from analyses showing that patient satisfaction was correlated with the provisioning of tablet computers in the hospital environment. As inpatient portals are commonly offered to patients through hospital-provided tablet computers, tablet access may influence patient satisfaction. However, prior work has shown that tablet access alone was not associated with higher scores on nurse communication or care transitions,

 suggesting that functions of the portal beyond tablet access may have contributed to the associations of these dimensions with patient satisfaction.

As patient satisfaction measures are increasingly being incorporated in studies of patient portal use, few studies have utilized CG-CAHPS or HCAHPS surveys as a generalizable approach to measure the correlation between patient portals and patient satisfaction. Previous studies have primarily utilized a subset of CAHPS questions, and to our knowledge, their results have been both limited and variable.

 For example, in one study that used only CAHPS survey questions related to communication, higher self-reported outpatient portal use was correlated with high patient satisfaction and the belief that the portal improved communication.

 In another study, use of an outpatient portal in the inpatient environment was found to have minimal association with satisfaction when evaluated with partial responses to the HCAHPS survey questions regarding self-management, medications, and overall hospital rating.

Our study contributes to the existing literature by analyzing all CG-CAHPS and HCAHPS survey dimensions, which, as comprehensive measures, have consequences for health care organizations due to their impact on perceived quality of care, patient recruitment and retention, and reimbursement. Our analyses provide insight into how patient portals may positively affect patients’ experiences, both in ambulatory and hospital care settings. Future research should explore the causality of patient portal use on patient satisfaction scores, as well as identify the mediating factors of patient portals and their use on patient experience.

Our study has several limitations. First, our primary study predictors focused on activated patient portal accounts and did not measure overall portal use or use of specific portal functions. Future extensions of this work should incorporate use measures to enable evaluation of their correlation with dimensions of satisfaction. Second, our study was focused on patients of a single hospital system, which limits our ability to generalize across organizations. Third, the functions offered on the portals at our AMC may vary from those offered at other medical centers. Although portal platforms used by other hospital systems may also be different, the wide implementation of Epic Systems’ portal platforms across US hospitals, as well as the similarity of functions among different portal platforms, supports the generalizability of our results. Fourth, our samples of encounters with and without activated portal accounts differ by notable demographic characteristics. Although we control for these differences in our adjusted model and follow standard risk adjustment procedures for estimating patient satisfaction scores, we acknowledge that there may be unobserved factors that cannot be included in our models. Finally, the potential exists for a simultaneity effect, in which patients who decided to open a portal account are those who are highly satisfied with the provider or hospital, and this could result in an upward bias in our findings. Our study, however, took measures in study design and our analytical models to mitigate this potential effect, giving us confidence in the findings that we report.

Patient portals are a promising tool that can promote patient-centered care by enabling patients to participate in their health care. Our study provides preliminary evidence that patient portal use is correlated with patients’ positive perceptions of their care experiences. Given the importance of patient satisfaction scores in the context of reimbursement and reputation, our results encourage further research to understand how health care providers and institutions can consider the opportunity to promote patient portal use as a means of improving patient satisfaction.

The authors would like to thank Inal Elbeyli, senior systems consultant at their institution.

 The Center for the Advancement of Team Science, Analytics, and Systems Thinking (CATALYST) (NF, SRM, PJ, ASM), Department of Biomedical Informatics (NF, PJ), and Department of Family Medicine (ASM), College of Medicine, The Ohio State University, Columbus, OH; The Ohio State University Wexner Medical Center (SV), Columbus, OH.

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (NF, SRM, SV, ASM); acquisition of data (NF, ASM); analysis and interpretation of data (NF, SRM, SV, PJ, ASM); drafting of the manuscript (NF, SRM, SV, PJ, ASM); critical revision of the manuscript for important intellectual content (NF, SRM, SV, PJ, ASM); statistical analysis (NF, ASM); provision of patients or study materials (NF, ASM); obtaining funding (NF, ASM); administrative, technical, or logistic support (NF, ASM); and supervision (ASM).

 Naleef Fareed, PhD, CATALYST, College of Medicine, The Ohio State University, 460 Medical Center Dr, Ste 502, Columbus, OH 43210. Email: Naleef.Fareed@osumc.edu.

Crossing the Quality Chasm: A New Health System for the 21st Century

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Patients with activated patient portal accounts report higher patient satisfaction in respective dimensions of the Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) and Hospital CAHPS (HCAHPS) surveys compared with patients without portal accounts.

Ann Scheck McAlearney, ScD

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