To measure the cost-effectiveness and direct budget impact of a pharmacist follow-up program in high-risk patients versus usual care.

Cost-effectiveness analysis of a quality improvement initiative comparing a postdischarge pharmacist program versus usual care.

 Pharmacists at Cedars-Sinai Medical Center, a large, community-&shy;based, academic medical center, contacted patients within 72 hours of discharge. Patient and prescriber drug-related problems (DRPs) were identified and resolved. Eligible patients met 1 or more of the following criteria: (1) receiving more than 10 medications, (2) having a diagnosis of pneumonia or congestive heart failure, and (3) receiving anticoagulants. The study measured annualized incremental direct hospital cost per 30-day readmission prevented.

Of 185 patients identified, 90% were contacted within 72 hours of discharge; of this group, 86.4% had 1 or more DRPs. The 30-day intention-to-treat readmission rates for the program versus usual care were 16.2% and 21.6%, respectively, and the average costs per patient were $3433 and $4015, respectively (difference, $582; Monte Carlo 95% CI, $528-$635). In multivariable sensitivity analysis across 1000 hypothetical hospitals of varying size and staffing, the intervention remained cost-saving in 98.3% of head-to-head trials.

The previously documented efficacy of pharmacist postdischarge care remains effective in a real-world application. The program is cost-saving to hospitals operating in a population health model or capitated model.

The American Journal of Accountable Care. 2018;6(2):e1-e8

There are more than 3 million hospital readmissions per year in the United States, costing over $41 billion in direct healthcare expenditures.

 One in 5 acute hospitalizations results from complications of treatment itself, of which half are medication related; it is possible that many of these hospitalizations can be prevented.

 The rising incidence of medication-related hospitalizations is a consequence of polypharmacy among patients with multiple comorbidities, poor health literacy, and decreased medication adherence.

 Further, patients with chronic conditions often receive uncoordinated care from disconnected physicians, leading to complex regimens and difficulty in ensuring that medication lists are accurate during vulnerable care transitions.

Up to 86% of patients have errors in their medication list upon admission, with an average of 3.3 errors per patient overall

 Nearly 40% of these drug-related problems (DRPs) have the potential to cause harm.

 Half of DRPs occur from unintentional prescribing errors because of incomplete or inaccurate information about what is prescribed.

 Furthermore, medication errors occur in up to 75% of patients during hospitalization, with many of these mistakes propagated after discharge

; between 14% and 80% of patients have at least 1 medication list discrepancy upon leaving the hospital. Postdischarge adverse drug events occur in up to 19% of patients, and one-third of these events are preventable.

In short, DRPs are pervasive and expensive before, during, and after acute hospitalization.

Findings of previous efficacy trials reveal that when pharmacists perform intensive medication reconciliation and patient education during and after discharge, there are fewer adverse drug events, emergency department visits, and readmissions, particularly in patients at high risk for DRPs.

 However, despite clear evidence that integrated pharmacist postdischarge programs are highly efficacious, it is unclear whether they are cost-effective when subjected to everyday care within a population health model. Given the large expense of hospital readmissions, we hypothesized that cost savings from a pharmacist-led postdischarge program would offset the costs of establishing and maintaining the program.

In this study, we measured the real-world budget impact of instituting a pharmacist follow-up program. We then performed sensitivity analysis to create a return on investment (ROI) lookup table for hospitals of varying size and staffing costs that are considering implementation of a similar pharmacist postdischarge follow-up program.

We conducted this study at Cedars-Sinai Medical Center (CSMC), a large, urban, academic hospital in Los Angeles, California. We instituted a quality improvement project in which postgraduate residency-trained pharmacists conducted telephone postdischarge follow-up for high-risk patients. We compared 30-day readmission rates between consecutive patients managed in the pilot program and a control population that did not receive the pharmacist intervention. We then calculated the incremental cost per readmission avoided and the budget impact of the pharmacist program on direct hospital outlays. Finally, we performed sensitivity analyses to estimate the program’s health economic performance in other healthcare systems, recognizing that our local results may not generalize to other settings. In the sections below, we describe the health economic analyses, competing management strategies, cost accounting, clinical probability estimates, and sensitivity analyses. 

We used decision analysis software (TreeAge Pro, version 2014; TreeAge Software, Inc; Williamstown, Massachusetts) to compare directly measured costs of 2 patient cohorts hospitalized at CSMC. The 

displays the truncated decision model. We populated the model with data obtained from a quality improvement project at CSMC comparing a standardized pharmacist postdischarge follow-up program versus usual care, described below. We then followed the cohort over the course of a 30-day time horizon and compared 30-day readmissions between strategies. 

Pharmacist postdischarge follow-up program. 

Between December 2014 and June 2015, we conducted a quality improvement project in partnership with our medical hospitalist services to screen high-risk patients at risk of readmission. Upon admission, high-risk patients were identified as meeting 1 or more of the following 3 criteria: (1) receiving 10 or more chronic medications, (2) having a diagnosis of pneumonia or congestive heart failure, and (3) receiving anticoagulants, as well as having low scores on an organizational medication literacy and adherence algorithm. These criteria were selected based on their association with hospital readmissions and expert opinion from our medical staff. Pharmacy staff were trained to use the algorithm when performing admission medication reconciliation.

Predischarge medication reconciliation was performed as part of usual care, primarily by physicians and allied health professionals, for an average of 90% of patients during the study period.

High-risk patients were selected for postdischarge follow-up by a transition of care (TOC) pharmacist. The TOC pharmacist compared the prior-to-admission medication list of each eligible patient with the after-visit summary discharge medication list. The TOC pharmacist contacted the discharging physician prior to and/or after patient contact to discuss and resolve any DRPs identified and to ensure that the physician’s intent was carried out during the telephone follow-up call. 

The objectives of each call were to ensure the patient had an accurate medication list, had obtained new medications initiated during hospitalization, understood how to take new and existing medications, and was taking them correctly. The TOC pharmacist conducted phone calls within 72 hours of discharge using a standardized procedure called “G.O. P.A.T.I.E.N.T.” to ensure that these objectives were met (

]). Pharmacists were trained on the standardized procedure, which included how to manage barriers to adherence, such as access to medications, literacy, and cultural beliefs. DRPs attributable to the patient and physician were captured during the call. Patient DRPs included nonadherence, misunderstanding medication directions for use, and taking extraneous medications. Prescriber DRPs included incorrect medications, doses, frequencies, or duration; doses not adjusted for organ dysfunction, drug—drug or drug–disease interactions; extraneous, duplicate, or omitted medications; and/or incomplete or inconsistent medications prescribed versus intent of medication use based on the information documented in the electronic health record. The TOC pharmacist contacted the treating physician after the patient interview to resolve DRPs and recontacted the patient as needed. The hospital discharge medication list was updated to ensure that errors were not propagated in future patient encounters and hospitalizations. Two call attempts were made, and if the TOC pharmacist was unable to contact the patient or the patient refused to return the call, then the patient was considered lost to follow-up.   

During the study period, we monitored a control group of high-risk patients who received usual care and therefore did not receive pharmacist postdischarge follow-up.

Our base-case model incorporated a range of probability estimates governing the relative effectiveness of the intervention versus usual care (

). First, because the pharmacist intervention can only be effective in patients who are successfully contacted, we accounted for the probability of reaching patients by telephone within the 72-hour postdischarge period. Next, among the subgroup of patients successfully contacted, we assessed the relative effectiveness of the intervention versus control, as measured by 30-day readmissions. Because the base-case data were derived from our local experience, we conducted sensitivity analyses to simulate alternative results and environments, as described in the Sensitivity Analyses section below. Finally, because the relative budget impact of the pharmacist program will depend on the number of high-risk patients eligible to benefit from the intervention, we modeled varying numbers of high-risk patients across a range of hospital sizes.

We performed direct cost accounting to compare the pharmacist postdischarge program versus usual care. Because the pharmacist intervention is principally designed to drive value of care—meaning to improve outcomes while reducing costs&mdash;we employed a population health—based managed care perspective in which the health system is financially responsible for the index hospitalization as well as any readmissions. Specifically, we measured the direct outlay by the hospital for the total care of the patient. We included up-front costs of the program pharmacists, comprising salary and benefits for 1 pharmacist, 1 pharmacy resident, and 3 technicians hired by the hospital for the pilot program. To project cost-effectiveness in hospitals of different size and patient burden, we also modeled a broad range of team sizes, salaries, and benefit plans. Finally, we included downstream readmission costs based on direct cost accounting for resources consumed in the care of the readmitted patient, including staff time and supplies. All estimates used 2015 US$. Because our study cohort was followed within a 1-year period, discounting was not performed.

Because our base-case cost and probabilities will not apply to all hospitals, we conducted 1-way sensitivity analyses for all estimates. We also conducted a Monte Carlo simulation, assuming that all variables followed a triangular distribution, which is widely accepted and standard practice,

 with base-case, minimum, and maximum values listed in Table 1 and the Figure. We also used results from the Monte Carlo simulation to generate a cost-effectiveness scatterplot and tested willingness-to-pay thresholds. One thousand trials were simulated and a 95% confidence ellipse was graphed around all trials in the scatterplot. We present both the confidence ellipse and 95% CIs around the base-case result. Finally, we created an ROI lookup table that accounts for the size of the hospital and staffing resources to implement the program.

The Cedars-Sinai Institutional Review Board approved this study (IRB Pro00038038).

lists the characteristics of the study participants in the pharmacist program (n = 185) and usual care (n = 51). The usual care group represented patients who had no pharmacist postdischarge follow-up due to limited resources; they served as a control group. There were no significant differences in patients enrolled between the 2 groups. The average age across groups was 70.4 years, 58% were male, and participants used 13.2 medications on average. Of the 185 patients in the pharmacist quality improvement program, 90% could be successfully contacted within 72 hours of discharge; of this group, 86.4% were found to have 1 or more medication discrepancies. The mean and median numbers of discrepancies were 2.8 and 2.0, respectively, which includes both physician-related (ie, errors of medication reconciliation) and patient-related (ie, due to patient misunderstanding) DRPs. The most commonly found DRPs were patient-related nonadherence (39.0%), prescriber-related omission of order (15.3%), wrong dose or frequency (12.5%), and duplicate therapy (10.9%). The overall 30-day readmission rates for the program and usual care were 16.2% and 21.6%, respectively (relative risk reduction, 0.248; 95% CI, —39.4 to 59.5).

The average costs per patient for the program and for usual care were $3433 and $4015, respectively (difference, $582 per patient; Monte Carlo 95% CI, $528-$635). In multivariable sensitivity analysis across 1000 hypothetical hospitals of varying size and staffing, and assuming a willingness-to-pay threshold of only $10,000 per readmission prevented, the intervention remained cost-saving in 98.3% of head-to-head trials. In a projected 1-year analysis, and assuming the pharmacy team could successfully contact and manage 150 high-risk patients per month, the net annual savings to the hospital was $1,047,600.

Because the base-case assumptions of the model may not be reproducible across hospitals, we performed sensitivity analysis to test the model using other probability and cost estimates. One-way sensitivity analysis revealed that the pharmacy program would remain cost-saving so long as the following are true: (1) at least 34 patients are contacted by a pharmacist per month, (2) at least 21% of patients can be contacted by the pharmacist and/or do not refuse to speak, (3) the average direct hospital cost of a readmission is at least $3660, and (4) the intervention reduces readmissions by at least 9%

The model was highly sensitive to the number of patients served by the pharmacy team and the size and cost of the team (

For example, if 200 patients are served per month at an annual staffing cost of $300,000 in salary and benefits, then the cost savings to the hospital is $1,696,800; if 300 are served at a team cost of $250,000, then $2,242,800 is saved. Table 3 provides an ROI lookup table to assist hospitals of different sizes and staffing levels in projecting the potential cost savings of implementing the pharmacist program. 

This quality improvement study focused on high-risk patients being followed by hospitalist services. Approximately 50% of these patients were determined to be high risk based on our study criteria. During the study period, although predischarge medication reconciliation was documented as part of usual care in an average of 90% of patients, prescriber-related DRPs were identified during the postdischarge calls. The findings of prescriber-related DRPs post discharge are consistent with published observations that documentation of discharge medication reconciliation does not necessarily mean that the process was performed completely and accurately.

 Comprehensive predischarge medication reconciliation would ensure timely resolution of DRPs and prevent potentially harmful errors from occurring post discharge.

Extensive research indicates that when pharmacists perform postdischarge medication reconciliation and education, there are fewer readmissions and better outcomes.

 In addition to these benefits, we also evaluated whether pharmacists could save costs in a real-world application. Using data directly obtained from a quality improvement initiative in a large community-based academic medical center, we found that the pharmacist postdischarge follow-up program was cost-saving, using a population health model in which the organization is responsible for hospitalization and readmissions. Depending on how many people are eligible for the program and the reach of the pharmacy team, hospitals can expect to save between hundreds of thousands to millions of dollars in direct costs per year, according to our ROI lookup table (Table 3). Furthermore, because high-risk patients in the study were older than 65 years and some had conditions for admission that are included in the CMS readmission penalty program (ie, congestive heart failure and pneumonia), this model could help organizations reduce readmission penalties.

The pharmacist program appears cost-effective under a wide range of scenarios; it was not highly sensitive to the precise estimates in the model or to our local base-case results. As long at least 34 patients are served per month, and assuming the pharmacists can contact at least 21% of eligible patients (90% were contacted in our experience), the program is likely to pay for itself. These are low thresholds that should be exceeded in most implementations; we found that 98.3% of hospitals will realize cost savings if the program is equally effective as achieved in our pilot program. The program does not need to be overwhelmingly effective to pay for itself; it must only reduce readmissions by a relative

9%. In pilot testing at CSMC, the program reduced readmissions by 25% relative to usual care (21.5% vs 16.2% absolute readmission rates). Previous research in other hospitals has shown similar results, with effect sizes ranging from a relative 14.2% to 56.2% in published studies.

The base-case estimates used in the model were based on our local experience implementing the pharmacy program at CSMC in a quality improvement project focused on high-risk patients who were followed by hospitalist physicians. Other hospitals may bear different costs and realize different benefits. To address this, we tested a wide range of values for both cost and effectiveness in 1-way sensitivity and Monte Carlo analyses. We found that the cost-effectiveness ranking was robust to sensitivity analyses and that the intervention is likely to be cost-saving in just about every hospital that can successfully implement the program, even if it is only modestly effective.

This quality improvement project did not demonstrate a statistically significant reduction in readmissions, likely due to the small size of the usual care group that did not receive postdischarge follow up by a pharmacist due to staffing limitations. However, extensive literature already indicates that these programs result in statistically significant reductions in 7-, 14-, and 30-day readmission rates

Here, we focused on direct real-world costs and benefits in an applied implementation of existing science. The assumption is that the hospital is responsible for the cost in this model, which is based on capitated reimbursements. Nonetheless, by conducting a Monte Carlo analysis over 1000 simulated trials using our base-case results as the base-case estimate, we found that the resulting 95% CIs did not cross unity; this is consistent with the existing literature.

In addition, our findings may not be generalizable to all high-risk patients. We studied inpatients receiving more than 10 chronic medications, having a diagnosis of pneumonia or congestive heart failure, and/or receiving anticoagulants. We cannot be sure whether these results are repeatable in other populations, although this cohort includes a prevalent and high-risk group reflective of many inpatient medical services. By using common conditions in the base-case model, we attempted to generate results that are relevant to most settings in which the program might be implemented, with particular focus on the highest-risk individuals.

This analysis revealed that a pharmacist postdischarge program is likely cost-saving to hospitals in a population health model. Hospitals may use these thresholds and lookup tables to project cost savings and help determine whether to fund and implement similar programs.

The authors would like to thank and acknowledge Lydia Noh, PharmD, for her support and contributions to this project.

Department of Medicine, Division of Health Services Research (BS), and Department of Pharmacy Services (RS, DDL, KP), Cedars-Sinai Health System, Los Angeles, CA; Department of Health Policy and Management, UCLA Fielding School of Public Health (BS), Los Angeles, CA; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE) (BS), Los Angeles, CA.

 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 (RS, KP, DDL); acquisition of data (RS, KP, DDL); analysis and interpretation of data (RS, KP, DDL); drafting of the manuscript (BS, RS, KP, DDL); critical revision of the manuscript for important intellectual content (BS, RS); administrative, technical, or logistic support (RS, KP, DDL); and supervision (BS, RS, KP, DDL).

Brennan Spiegel, MD, MSHS, Cedars-Sinai Health System, Cedars-Sinai Health System Pacific Theaters Building, 116 North Robertson Blvd, 4th Fl, Los Angeles, CA 90048. Email: Brennan.Spiegel@cshs.org.

Articles

The American Journal of Accountable Care

A multivariable sensitivity analysis conducted on a pharmacy follow-up program of high-risk patients demonstrated cost savings to hospitals in 98.3% of head-to-head trials across 1000 hypothetical hospitals.

Cost-Effectiveness of Pharmacist Postdischarge Follow-Up to Prevent Medication-Related Admissions

The American Journal of Accountable Care. 2018;6(2):36-37

The United States healthcare system is undergoing a shift to value-based care that has been uneven across sectors and parts of the country, but there are plenty of organizations pushing forward, explained speakers at the forefront of the movement during 

’s Accountable Care Delivery Congress, held May 11, 2018, in San Diego, California.

During her keynote speech, Suzanne Delbanco, PhD, MPH, executive director of Catalyst for Payment Reform, explained that employers may sometimes be intimidated by the idea of purchasing healthcare, but they are in a position to transform the market.

Although employers are interested in new models tying payment to value, Delbanco’s group believes that each of the myriad of payment types in healthcare has a place, including fee-for-service.

“We don’t believe that we’re necessarily moving from traditional fee-for-service all the way to global payment and [will] reach Nirvana and then we’re done,” she said.

Employers are also making efforts to control costs without impacting quality through new benefit designs, provider network arrangements, and providing services like onsite or near-site clinics or telehealth as alternative settings of less expensive care.

The first panel of the meeting focused on new ways of delivering care to address social determinants of health. Rachel Gold, PhD, MPH, of the Kaiser Permanente Center for Health Research and OCHIN, explained that the biggest challenge to addressing social determinants of health that she is trying to overcome is how community health centers can start to collect social determinant data and document them so providers can actually be aware of them.

Developing care plans for patients is a futile effort if providers don’t know a patient’s social needs. For instance, if a patient is homeless, a provider shouldn’t prescribe a medication that needs to be refrigerated, she explained.

“Sounds obvious, but if the provider doesn’t know the patient’s homeless, because it’s not in the record, and they didn’t think to ask, then they’re going to create a serious barrier to the patient acting on their care recommendations,” Gold said.

She added that her research has also shown that sometimes there are reasons to not screen for social needs, as the providers don’t always have a way to address the patient’s needs. In the Portland area, there is a housing crisis, so if a provider finds out that a patient is homeless, the provider might not actually be able to do anything about it.

Karin VanZant, of CareSource, pushed back by emphasizing that identification of social needs has to happen. There are always resources available, even if certain geographic areas may have supply&shy;-and-demand issues. The trick is to knit together the social fabric and safety net within the geography.

Carter Wilson, MCOM, of the Camden Coalition of Healthcare Providers, added that providers need to tailor screening questions to the available resources within a community. Still, he finds that primary care physicians are hesitant to ask questions about social needs because they “don’t want to open that can of worms.” He’s trying to train them to be comfortable bringing up these issues.

“It’s only a can of worms for the provider—not for the patient,” Wilson said. “The patient is living this life. They’re not traumatized by their own life or talking about their own life. So, it’s a provider anxiety about what they’re going to do to their patients, and it’s incorrect.”

To make sustainable changes in care delivery, the payment mechanisms need to be there. During the second panel, David Muhlestein, PhD, JD, of Leavitt Partners; Michael Funk, FACHE, CMPE, of Humana; John McConnell, PhD, of Oregon Health & Science University; and Tim Gronniger, MPP, MHSA, of Caravan Health, noted that with so much of the health system still in fee-for-service models, there is no business case for organizations to move fully to value-based care.

The panelists agreed that the federal government has to be involved to drive the shift. Muhlestein noted that HHS Secretary Alex Azar has changed gears from his predecessor, Tom Price, MD, and is more in line with how former President Barack Obama’s HHS secretary, Sylvia Mathews Burwell, viewed Medicare and Medicaid as policy levers.

McConnell and Funk have been encouraged by what they’ve seen so far. Although McConnell said the coordinated care organizations in Oregon, which are similar to accountable care organizations, are “here to stay,” Funk believed that current models and payment structures probably won’t be around at the end of the transformation.

The final panel of the day highlighted technology innovations in healthcare, with 3 panelists discussing how their organizations are leading the field. Taylor Justice, of Unite Us, explained that his company uses software to address social determinants of health by connecting patients to appropriate resources. The software creates a single record for each patient that follows him or her regardless of the care setting. Each new care organization is given access to the parts of the record that it needs.

Arien Malec of Change Healthcare, highlighted the fast-changing technology landscape in healthcare, with artificial intelligence and machine learning starting to be used to relieve administrative burdens.

“What we’re doing is not the holy grail of replacing the physician and having the computer do everything for you,” Malec explained. “We’re trying to automate a lot of the routine activities of healthcare,” she said, to have people work at the top of their licenses.

Aledade is working with 22 accountable care organizations across the country, helping providers who want to make the shift to value-based care but need help with things like regulatory issues, technology, and data analytics that must be addressed during the transformation. Edwin Miller, of Aledade, explained that providers are having trouble getting access to the information that health systems and hospitals have.

“The data blocking is real,” he said. “We have trouble getting information. We struggle to get those connections.”

At the Accountable Care Delivery Congress, speakers discussed ways to address social determinants of health, use payment mechanisms as levers, and forge connections through technology.

Utilizing Community Resources, New Payment Models, Technology to Deliver Accountable Care

As value-based reimbursement prepares to enter the outpatient setting, little is known about medical offices’ preparedness to face this challenge. Although workplace climate is a strong predictor of organizational performance and patient outcomes, there is a critical lack of evidence regarding a climate for value in frontline medical offices. Our goal was to assess medical office staff member perceptions of a workplace climate for value.

The Medical Office Value and Efficiency Survey, developed by the Agency for Healthcare Research and Quality, was pilot-tested among 2315 workers in 96 medical offices. Of these, 840 completed surveys, 57% of whom were clinical staff members. Most respondents worked full time (86%), had been at their current place of employment for at least 1 year (83%), and worked in larger practices with 11 or more clinical staff (70%).

 Percentage of positive survey responses was used for comparisons by occupational role and organizational context.

Medical office staff positively responded to 44.6% of the 25 climate survey statements. Clinical staff were more positive, but few had used data to assess the results of performance improvement activities (8.8%), shadowed patients to improve their care experience (12.4%), or served on a committee to make a work process more efficient (15.7%). Among nonclinical staff, those working in smaller medical offices had more positive perceptions than those in larger offices.

Findings highlight the need for management strategies that emphasize staff training and engagement and the use of performance data and that stress value principles across all organizational activities, including workforce development, performance management, and recruitment.

The American Journal of Accountable Care. 2018;6(2):11-19

With the ongoing implementation of the Medicare Access and CHIP Reauthorization Act of 2015, new physician reimbursement methods continue the trend in payment reform policies attempting to shift the emphasis from volume to value. While the efficacy of such policies is currently being evaluated under many pilot studies,

 researchers have identified the need to better understand the intrinsic motivators contributing to organizational behavior change.

 Organizational climate is the meaning that employees attach to the policies, practices, and procedures they experience in the workplace.

 In healthcare organizations, climate has been empirically associated with staff and patient outcomes.

 Workplace climates characterized by high levels of positivity, staff involvement in decision making, and interprofessional collaboration create an appropriate context for the delivery of compassionate, coordinated, and patient-centered services to meet the needs of complex patients.

 Conversely, negative climates have been attributed to poor patient safety outcomes and failed implementation of new interventions and technologies.

 Yet, as medical offices prepare for value-based reimbursement, there is a critical lack of evidence regarding staff perceptions of office policies and procedures that facilitate a climate for value in the workplace.

To address this gap, the Agency for Healthcare Research and Quality (AHRQ) sponsored the development and pilot-testing of the Medical Office Value and Efficiency Survey (MOVES). Modeled after the agency’s influential patient safety culture program, MOVES was developed to assist managers in assessing the extent to which medical offices emphasize and adopt processes to promote efficiency, waste reduction, patient-centeredness, care quality, and cost reduction.

 Because value-based reimbursement introduces greater financial risk to frontline medical offices, it is essential to assess their readiness to perform in this new environment. Soliciting staff perceptions regarding internal processes and policies has proved fruitful in understanding complex organizational issues, such as patient safety, in hospitals.

 Similarly, insights from staff with considerable exposure to everyday workplace policies and care delivery practices in frontline providers may offer a unique and highly relevant contribution to this topic.

Although little is known about the current climate for value-based care in medical offices, it will be the centerpiece of outpatient reimbursement by 2019 when Medicare’s Merit-based Incentive Payment System and alternative payment models (eg, accountable care organizations [ACOs]) will be implemented together as the world’s largest pay-for-performance program. Similar efforts are underway in the private sector. The Health Care Transformation Task Force, a new coalition of private insurers and provider organizations, is aiming to move 75% of its contracts into value-based payment models by 2020. As of 2016, about 41% of their contracts were value-based, up from 30% in 2014.

 By putting providers at financial risk to implement value-based care, there is hope that the United States can begin to reduce the annual $750 billion (30%) in excess costs spent on low-value care and overuse.

 At the same time, there is strong interest in keeping small physician-owned medical offices on the front line of value-based care, as recent research shows that they have lower costs and fewer ambulatory care—sensitive admissions.

 Similarly, the smaller ACOs were found to have performed better in the 2015 Medicare Shared Savings Program.

To keep medical offices on the leading edge of value-based care, there is a need to assess their climate for dealing with value-based performance, efficiency, and waste and overuse concepts. Little is known about clinicians’ perceptions of value-based care. The evidence regarding patient perceptions is growing, albeit mixed. A recent AHRQ survey of marketplace consumers found little trust in value-based healthcare, viewing it as an unnecessary external intrusion into their patient—physician relationship.

 Another study, using the AHRQ Consumer Assessment of Healthcare Providers and Systems (CAHPS), found that efforts to improve efficiency and reduce waste in primary care clinics, such as with Lean programs, improved patient satisfaction with access to care but lowered satisfaction concerning interactions with clinicians.

Whether clinicians have perceptions similar to those of patients in these value and efficiency domains is an open question. Recent provider climate surveys have been limited. Since 2004, AHRQ has maintained a family of 5 surveys to assess the climate and culture of organizations with respect to patient safety, collectively called the Surveys on Patient Safety Culture (SOPS).

 However, the SOPS have not emphasized climates of value and efficiency. To address this weakness, MOVES was designed by AHRQ to specifically fit into its current suite of surveys: the 5 SOPS and the 10 CAHPS surveys.

 In this study, we present the first results from a pilot test of MOVES among 840 staff members in 96 medical offices.

Medical Office Value and Efficiency Survey

MOVES was developed by AHRQ through its contractor, Health Research & Educational Trust (HRET), and its subcontractor, Westat. The stated goal of the project was to provide tools for managers to assess staff perceptions of 5 important domains for value: (1) staff empowerment, (2) focus on efficiency, (3) patient-centeredness, (4) leadership support for value, and (5) staff training and engagement in quality improvement. Definitions of key terms, such as waste, efficiency, and value, are presented in 

 and were used in the survey instrument. The domains and definitions were identified through a process that included an extensive review of the organizational climate literature concerning healthcare organizations and guidance from an oversight panel comprising both health system leaders and research experts.

Survey participants were asked to state their level of agreement with 25 statements as applying to their medical office. As the instrument’s purpose was to measure individual perceptions of workplace attributes, the statements were framed using a referent-shift consensus approach consistent in climate survey methodology. The instrument underwent thorough psychometric analysis by Westat, similar to all of Westat’s psychometric analyses of the AHRQ SOPS, and is available on AHRQ’s website.

 Reliability was strong, with Cronbach’s α coefficients of the composites ranging from 0.77 to 0.92, with an average of 0.87.

During the pilot test, HRET worked with the Medical Group Management Association and the American Medical Group Association to help recruit a range of medical office sizes and specialties. The MOVES survey was administered to 2315 workers in a stratified sample of 96 medical offices that varied by geographic location, practice size (ie, number of clinical staff), and type of practice (ie, primary care, multispecialty, and single-specialty/non—primary care). Completed surveys were received from 1081 medical office employees (47% response rate). Of these respondents, 241 participants self-identified as being an owner or partner in their office and were excluded from this analysis. The final sample consisted of 840 completed surveys. Office-level response rates varied from 20% to 100% across the 96 practices.

The extent to which respondents perceived their workplace environment as supporting a climate of value was measured as the percentage of positive responses (PPR) to survey statements. Bivariate analyses compared survey item responses by occupational role, organizational size, and type of practice. Random effects ordinary least squares (OLS) regression examined the relationship of individual and office characteristics with the PPR measure.

 presents a summary of survey respondents by occupational and organizational characteristics. A majority of respondents reported performing a clinical role in the practice (57.6%), including physicians (4.3%); nurses (12.1%); physician assistants, nurse practitioners, and other nonphysician providers (6.2%); and other clinical staff (35.0%). Nonclinical personnel made up 39.6% of survey respondents, with most reporting having an administrative, health information technology, or other clerical role. Overall, respondents were mostly full-time staff working at least 33 hours per week (86%) and reporting considerable workplace experience. Almost half of participants (46.1%) had worked between 1 and 6 years at their current medical office. More than one-third (37.6%) reported working at their office for 6 or more years. Finally, most participants worked in either a primary care or a multispecialty practice (53%) with 11 or more clinical staff (70%).

Staff Perceptions of Office Climate for Value and Efficiency

On average, medical office staff positively responded to 44.6% (SD = 23.1%) of the 25 climate statements as applying to their workplace (

). Almost three-quarters (74.2%) of respondents reported that their offices work to improve patient flow. Other items receiving a high level of staff agreement included the acknowledgment that office leaders place a high priority on working efficiently without compromising patient care (69.6%), that the office has taken steps to reduce patient wait times (65.2%), and that staff actively try to find ways to reduce waste in work processes (62.6%).

Less agreement was observed within the training and engagement domain, where respondents were presented with specific activities designed to improve efficiency and waste reduction. Few respondents reported having used data in the past year to assess the results of an activity to improve efficiency (8.8%), having shadowed patients to identify ways to improve their care experience (12.4%), or having served on a team or committee to make a work process more efficient (15.7%). Of the 8 items presented in the training and engagement domain, only having made a suggestion about improving an inefficient work process received a positive response from a majority of participants (55.0%).

Table 3 presents bivariate analyses of survey items and climate dimension scores by clinical and nonclinical staff. Overall, clinical office staff responded positively to 3.5% more statements, on average, compared with their nonclinical colleagues. Significant differences in mean climate dimension scores were observed for the patient-centeredness and training and engagement domains. Clinical staff were more likely than nonclinical colleagues to agree that their office focused on eliminating unnecessary tests and procedures, took steps to reduce patient wait time, and sought patient or family member input on improving efficiency. In addition, clinical staff reported a higher level of engagement in training and waste reduction activities than nonclinical participants. Participation was higher among clinical staff for certain activities: having followed patients to identify ways of improving patient care, made a suggestion to management to improve the patient care experience, and looked at visual displays or graphs of office performance. Clinical staff were more likely than nonclinical personnel to rate their office as “very good” to “excellent” for providing care based on scienti-

Staff Differences by Organizational Context

Differences in staff perceptions were observed across multiple climate dimensions by practice size and type (

). Staff members in primary care offices had, on average, 4.1% more positive responses overall compared with personnel in single-specialty and multispecialty offices, and they had significantly higher mean scores for 3 of 6 climate dimensions surveyed: patient-centeredness (+11%), focus on efficiency (+6%), and training and engagement (+4%).

Similarly, staff members in large medical offices were less positive than colleagues in small- and medium-sized practices. Mean PPR was 4.2% less, on average, for staff in large practices, with relative differences for staff empowerment (—8%), leadership support (–7%), and training and engagement (–4%).

 presents the results of random effects OLS regression analyses to test for associations of individual and office attributes with climate survey PPR measures. Clinical and nonclinical models were tested in addition to the full sample. Differences were observed based on occupational role, tenure, employment status, and practice size in the full model. Respondents who reported having a managerial role in the office had 16% higher PPR scores compared with the occupational category of other clinical staff (

 <.0001). Staff members with 3 or fewer years of tenure were 4% to 5% more positive than colleagues with more than 6 years of tenure, and part-time staff were 6% less positive compared with full-time workers (

 = .006). At the organizational level, clinical staffers in small offices were 9% more positive compared with workers in large practices (

 = .006). No differences were observed by practice type. Medical office attributes accounted for less than 1% of the variance in the full model.

The clinical and nonclinical models revealed differences by occupational role. Tenure differences were observed as the only significant factor associated with the PPR measure among clinical staff. Specifically, clinical staff with less than 6 years of tenure were between 5.7% and 10.2% more positive than clinical staff with longer tenure. No differences were observed in mean PPR scores among clinical staff based on clinical occupation, employment status, or organizational attributes. Medical office characteristics accounted for less than 1% of the variance in the clinical staff model. Conversely, differences in mean PPR scores for nonclinical staff were positively associated with identification as a manager (

 = .026). PPR scores were negatively associated with part-time employment status (

 = .020). Medical office attributes accounted for almost 16% of the variance in the nonclinical staff model.

This study is the first empirical examination of staff perceptions of a climate for value in medical offices. More than 800 medical office staff, both clinical and nonclinical, in 96 medical offices shared their perceptions of workplace practices, policies, and procedures across 6 dimensions: staff empowerment, focus on efficiency, patient-centeredness, leadership support for value, staff training and engagement, and office performance. In preparation for the expansion of value-based payment mechanisms to the outpatient setting, these findings address the crucial lack of evidence regarding the extent to which medical office staff perceive a climate for value in their workplace and the extent to which staff perceptions may differ by occupational role and organizational context.

Overall, medical office staff members responded positively to less than half (44.6%) of the 25 climate statements as applying to their workplaces. Only 8 statements received a positive response from a majority of participants. Regarding performance, almost 60% rated their office as “very good” or “excellent” for being responsive to individual patient preferences, needs, and values and for providing services based on scientific knowledge to all who can benefit. Less than half rated their office’s performance as high for minimizing waits and potentially harmful delays (42.5%) and for ensuring cost-effective care (41.7%). No differences were observed in office performance ratings by occupational role.

A majority of workers responded positively to all 3 of the statements in the efficiency dimension. Medical office staff agreed that their workplaces are active in finding ways to reduce waste in work processes (62.6%), working to improve patient flow (74.2%), and focusing on eliminating unnecessary tests and procedures (53.3%). Conversely, positive responses were generally low within the patient-centeredness dimension. Although 65.2% agreed that their offices took steps to reduce patient wait time, only one-third agreed that their office asked for patient and family member input on ways to make patient visits more efficient. Similarly, 30.9% agreed that patient and family member preferences have led to changes in office workflow. Medical offices that have adopted these patient-centered practices may be better prepared for reimbursement methodologies that reward based on patient experience.

A related finding was the generally low level of reported training and engagement in value-enhancing activities. Although clinical staff reported a higher level of engagement over the past year compared with nonclinical personnel (

 = .003), their mean number of reported activities was only 2.08 of 8 (SD = 1.82). Just 32.1% of respondents had received training in efficiency and waste reduction over the past year. Less than one-fourth reported helping to map a workflow process to identify wasted time, materials, or steps (20.1%), or looking at visual displays or graphs to see how well the office was performing (20.8%). Less than 10% reported using data to assess if improvement activities were in fact working. These findings highlight the need for management strategies that emphasize training and engagement in value-enhancing activities, for making performance data visual and available to staff to review, and for recognizing individuals and teams that strive to enhance value in the practice.

The study found differences in value climate perceptions by occupational role and organizational context, although specific factors influenced groups differently. Overall, clinical staff were more positive than nonclinical personnel across multiple climate dimensions. In the clinical staff analysis, no differences were observed by occupational role (eg, physician, nurse, nonphysician provider, clinical staff), employment status (full time vs part time), or by medical office size or type. Office tenure was found to be negatively associated with value climate perceptions among clinical staff. Among nonclinical staff, differences in value climate perceptions were observed by occupational role (manager vs nonmanager), employment status (full time vs part time), and practice size (small vs large). The organizational context accounted for considerably more variance in the nonclinical model, supporting the importance of emphasizing value climate principles not only in care delivery processes but across all organizational activities to include workforce and team development, performance management, and recruitment/selection programs.

There are several limitations to this study which should be considered when interpreting the results. First, the sample was made up of staff personnel employed by 96 medical offices participating in a pilot study of the survey instrument. Although the organizations were diverse across contextual aspects and geographic location, these medical offices may not be representative of the population of medical offices currently active in the United States. Second, participants were restricted to identifying themselves by only 1 of the occupational answer choices. It may be that some respondents serve in both a managerial and a clinical capacity at their workplace, but it was not possible to identify this category of staff in the survey data. Finally, the cross-sectional nature of the data restricts the analysis to a correlational design and subjects the findings to the potential for omitted variable bias.

This study assessed perceptions of 840 medical office staff regarding a climate for value in their workplace. Participants reported a generally low level of agreement for value climate items, but differences were noted by office role, tenure, and organizational size. Instituting deliberate policies and processes that incorporate patient input into workflow and that foster staff engagement in value-enhancing activities may be effective strategies for creating a workplace environment conducive to success under value-based reimbursement methodologies.

This study was funded by AHRQ. The views here do not necessarily reflect the views or policies of AHRQ or HHS. The authors would like to thank the Westat team, Joann Sorra, Theresa Famolaro, and Naomi Yount, as well as Kevin Kenward from HRET, for their work in pilot-testing the MOVES survey.

College of Health and Human Services, School of Health Sciences, Eastern Michigan University (RKM), Ypsilanti, MI; Center for Delivery, Organization and Markets, Agency for Healthcare Research and Quality (WEE), Rockville, MD.

Agency for Healthcare Research and Quality.

Concept and design (RKM, WEE); acquisition of data (WEE); analysis and interpretation of data (RKM); drafting of the manuscript (RKM); critical revision of the manuscript for important intellectual content (RKM, WEE); statistical analysis (RKM); and obtaining funding (WEE).

Rodney K. McCurdy, PhD, 313 Everett L. Marshall Bldg, Eastern Michigan University, Ypsilanti, MI 48197. Email: rmccurd3@emich.edu.

1. Oberlander J, Laugesen MJ. Leap of faith—Medicare’s new physician payment system. 

. 2015;373(13):1185-1187. doi: 10.1056/NEJMp1509154.

2. Berenson R, Rice T. Beyond measurement and reward: methods of motivating quality improvement and accountability. 

. 2015;50(suppl 2):2155-2186. doi: 10.1111/1475-6773.12413.

3. Schneider B, Barbera KM. Chapter 1: introduction: The Oxford Handbook of Organizational Climate and Culture. In: 

The Oxford Handbook of Organizational Climate and Culture

. Schneider B, Barbera KM, eds. New York, NY: Oxford University Press; 2014:3-20.

This study surveyed 840 clinical and nonclinical staff in 96 medical offices regarding workplace policies and procedures that facilitate a climate for value. 

Are Medical Offices Ready for Value-Based Reimbursement? Staff Perceptions of a Workplace Climate for Value and Efficiency

The Palm Beach Accountable Care Organization began a preventive care initiative aimed at scheduling visits for patients covered under commercial insurance who had not seen their primary care physicians in more than a year.&ensp;Reports of “dropped patients” who lost or were about to lose assignment to their doctors were produced and distributed to physician practices.&ensp;With the assistance of registered nurses and lay patient navigators, physician offices contacted and attempted to schedule the patients on the lists. In just 3 months, this effort retained 1242 patients to their physicians for their annual physicals and potentially saved an estimated $1,892,094.96 for the accountable care organization’s commercial insurance contracts.

The American Journal of Accountable Care. 2018;6(2):26-29

The Palm Beach Accountable Care Organization (PBACO), founded in 2012, is the highest-earning accountable care organization in the nation, earning $31.5 million in shared savings alone in 2016. With almost 80,000 Medicare beneficiaries and more than 400 physicians spanning from Miami to Okeechobee, PBACO is rapidly growing its network of providers and patients. PBACO also effectively doubled its patient panel size after negotiating contracts with Cigna and Blue Cross Blue Shield (BCBS) in 2016 and with UnitedHealthcare (UHC) in 2017.

PBACO operates various population health projects to improve care quality and efficiency in south Florida. These include focusing on high-cost/high-risk patients, promoting transition care management for patients being discharged from the hospital, and keeping track of patients frequently admitted to the emergency department (ED). These projects are undertaken by nurses working for PBACO, as well as by lay patient navigators and assignment/provider representatives, who are employees tasked with coordination and data sharing and collecting among physician offices. Evidence shows that lay patient navigators can increase the efficiency of physician practices by reducing 25% of case managers’ nonclinical tasks, while also lowering ED visits and readmissions.

PBACO’s most recent initiative involves promoting preventive care for patients who have not seen their primary care physicians (PCPs) for more than 12 months and are thus “dropped” from their PCPs’ panels. According to the results of a study from the National Commission on Prevention Priorities, increasing preventive care utilization could save $3.7 billion in healthcare spending and 2 million lives annually.

 A possible obstacle to preventive care is a lack of regular visits by patients to their PCPs. However, the simple offer of free PCP visits has not been shown to increase patient retention. For instance, eligibility for free PCP visits did not increase the likelihood of visits for patients in Mississippi compared with patients in Georgia and Tennessee who were not eligible for a free visit.

 Therefore, additional efforts, like PBACO’s dropped-patient initiative, must be devoted to reaching out to relatively healthy patients who need to see their PCPs annually. With the medical landscape shifting from a fee-for-service model to value-based care,

 PBACO must dive deeper into the logistics of population health, especially regarding preventive care. Through the new dropped-patient initiative, PBACO has piloted a simple but innovative endeavor to support consistent patient access to care, maintenance of patient health, and prevention of wasteful procedures that stem from untreated and undiagnosed conditions.

First, comprehensive lists of patients who have not been seen in 1 year or more, organized by the PCP and insurer, were compiled based on quarterly reports from Cigna, BCBS, and UHC. From its PBACO nurses, assignment team member, or provider representative, each practice received the lists of dropped patients who had previously been assigned to them. The practice was encouraged to schedule the listed patients for annual physicals. Assignment team members, if permitted, could directly schedule dropped patients on behalf of the practices to which they were assigned. PBACO nurses, although initially not directly involved in scheduling, also began making appointments with the guidance of the assignment team. During scheduling, the dropped-patient reports were filled out to include the dates of the next scheduled physicals or the reasons for the inability to schedule an appointment. Patients who could not be called were sent postcards notifying them that they were due for an appointment. Filled-out reports were returned for data processing to assess the progress of scheduling. The process began in the first week of May 2017 and continued through the second quarter of 2017 (ending June 30), although some reports were returned late by the end of July.

Additional protocols were implemented in mid-June to target patients who had not been reached with an initial phone call. After sending a postcard, schedulers were encouraged to call 2 or 3 more times at different hours, using both the primary and secondary contact information provided by patients, over the span of a few weeks. Texting patients, if permitted by physician practices, was also encouraged. If patients still had not responded, a letter was sent to notify them about scheduling annual physicals.

Throughout the first period of sending out the dropped-patients report, the percentage of patients who were left phone messages (29.45% on June 9) was larger than that of the combined scheduled/already-seen percentage (26.45%). The new strategy to contact patients after June 9 helped lower the percentage of patients left messages to 25.50% while raising the scheduled percentage from 10.44% to 12.51% (

). By the end of July, the trend had reversed, with the 28.87% scheduled/already-seen rate surpassing the 25.50% left-message rate (

). PBACO’s assignment team and nurses, who organized report distribution and were the only ones using the new contacting protocols, demonstrated significant improvement in establishing patient contact through such special protocols/techniques. However, these PBACO employees were not granted full access to their assigned physicians’ patients—in some offices, they were relegated to purely a consultant role&mdash;and were only able to work with a smaller cohort of patients. The opposite was true for staff at physician offices, who worked with the majority of patients on the reports but generated slower progress, with a constant scheduling rate (categorized as “already seen”) of about 16% (

); the offices used no new methods of contacting patients. Therefore, the largest opportunity to retain patients through annual check-ups lies in improving office scheduling procedures by encouraging follow-up appointments to strengthen the PCP—patient relationship and preventing patients from being dropped in the first place. In the long run, offices can produce self-improvement and achieve enduring progress.

Many patients who were scheduled had not seen their PCP in more than a year simply because they hadn’t felt the need for a visit, and they only needed a phone call to remind them to make an appointment for an annual physical. Another predominant reason for dropping PCP assignment was change in the patient’s location, insurance, or choice of PCP, which accounted for 15.53% of the returned reports. Another 8.79% were patients who were either inactive or unavailable for scheduling or had no contact information and/or address in electronic health records (EHRs); 2.16% of patients could not be found in the EHR. Only 50 patients, 1.16% of the total returned, responded that they did not wish to return to their assigned PCP. It is highly possible that the remaining patients who were left a message, many of whom had been contacted by telephone at least 3 or 4 times to no avail and had been sent a postcard or letter, fell into this nonreturning category, although there is no definitive evidence to confirm so.

 Nevertheless, the second month’s gradual pace of distribution and scheduling of the dropped-patient reports indicated that most progress was achieved during the first month. Even with various changes in protocols, ranging from repeated phone calls and letters to allowing nurses to schedule appointments, the scheduling rate improved by only 2% over the second month. The postcards and letters yielded a minimal response rate, although some patients did reach out to their physicians for scheduling, and re-calling patients only reached about 10% of those who were left messages. Most likely, the patients who were more easily reached had already been contacted and scheduled within the first month, whereas patients who were initially harder to reach stayed harder to reach and comprised the population of the reports returned in the later weeks. The future methodology of processing dropped-&#8203;patient reports may have to adjust for this possibility, perhaps by exploring alternative strategies in attracting patients back or reforming practice scheduling methods.

Much of the methodology for processing the dropped-patient reports is also applicable to high-cost/high-risk reports, including data collection, categorization, and analysis and the patient scheduling process. Although these 2 projects cover opposite ends of the patient health—cost spectrum, they require similar procedures and reports. Due to the similarity in how the reports are completed, future distribution of dropped-patient and high-cost/high-risk reports to physician practices can be synchronized for more coordinated and efficient execution, as well as for the convenience of the scheduling staff.

The use of dropped-patient reports was projected to save $1,892,094.96 (

) for 2017. These savings were calculated using the latest available rosters and reports from all 3 payers. For each payer, the average per member per month (PMPM) cost of each payer’s population without the dropped patients and the average PMPM cost of the population with the dropped patients were calculated. The difference between the PMPM costs with and without the dropped patients was then multiplied by the panel size (with dropped patients included) and by 12 months. Each payer’s savings were then totaled.

A significant limitation to the results included the 1564 patient reports (26.66% of the total) that had not been returned. More than a quarter of the reports were not completed because some practices in particular counties scheduled the patients on the reports at a slower pace, a few practices had staffing or EHR complications, and other practices had not granted scheduling access to assignment team members. Data from all of the reports that had not been returned may have been rolled over to the next quarter’s results and would be recorded accordingly. Another limitation is that patients who had been scheduled may have canceled or not attended their appointment. Such patients could be tracked in the EHR every so often by assignment team members or nurses.

The savings calculations also had several limitations. The attribution dates for each payer’s latest roster differed and are all dated just prior to the distribution of the reports (May 2017). Therefore, the estimated costs from each roster may not reflect the most updated cost per patient at the time when offices started scheduling the dropped patients. Also, the PMPM costs for the Cigna roster were risk adjusted, unlike the PMPM costs of the dropped patients. Nevertheless, the estimated savings should provide a general idea of the dropped-patient reports’ effectiveness in improving healthcare access at a stable or lower cost over the span of a year.

Future dropped-patient reports should focus more on innovative and alternative techniques to reach patients. Letters and postcards may more easily reach older retired Medicare patients, whereas texting and emailing may be more viable strategies for contacting younger working patients who are covered under commercial plans. Calling at later hours near the end of the workday may also be effective. In the next rounds of future dropped-patient reports, more time and resources should be invested into testing different approaches.

The dropped-patient reports successfully retained at least 1 of every 5 patients who had lost or were about to lose assignment to their PCPs. Scheduling dropped patients is a crucial initial step in maintaining a stable panel size and improving quality of care. As these patients start attending appointments with their PCPs, the next step is to ensure they are also seen more frequently with follow-up appointments. PBACO hopes to encourage its member physicians to schedule follow-up appointments for every patient before they leave the office. By improving the quality of care and forming stronger bonds between PCPs and patients, dropped-patient reports have potentially generated pecuniary benefits. With the lessons learned from the initial report rollout, subsequent reports will be distributed and processed more efficiently, with more room to innovate and investigate the means of reaching out to patients.

Palm Beach Accountable Care Organization, Palm Springs, FL.

 The author reports 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; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content; and statistical analysis.

Nicholas Ma, Palm Beach Accountable Care Organization, 2326 South Congress Ave, Ste 2F, Palm Springs, Florida 33406. Email: nma@pbaco.org.

1. Insight driven health: patient navigation eases clinical workforce challenges—without clinical expertise. Accenture website. accenture.com/t20171213T020502Z__w__/us-en/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Dualpub_1/Accenture-Patient-Navigation-Eases-Clinical-Workforce-Challenges.pdf. Published 2014. Accessed July 10, 2017.

2. Maciosek MV, Coffield AB, Flottemesch TJ, Edwards NM, Solberg LI. Greater use of preventive services in U.S. health care could save lives at little or no cost. 

2010;29(9):1656-1660. doi: 10.1377/hlthaff.2008.0701.

3. Beech BM, Cordier T, Happe LE, et al. Does a free office visit affect primary care-seeking behavior? a study of new exchange health plan enrollees in Mississippi. 

4. Stowell C, Akerman C. Better value in health care requires focusing on outcomes. 

. September 17, 2015. hbr.org/2015/09/better-value-in-health-care-requires-focusing-on-outcomes. Accessed July 19, 2017.

Palm Beach Accountable Care Organization’s outreach to “dropped patients” demonstrates potential for strengthening physician–patient relationships and lowering the cost of care.

Case Study: Encouraging Patients to Schedule Annual Physicals

The objectives of this study were to: (1) assess the effects of an integrated medication therapy management (MTM) program for accountable care organization (ACO) patients on all-cause hospitalization rates, (2) evaluate the impact on 30-day hospital readmission rates for the ACO patients, and (3) assess the effect of an integrated MTM program on per capita Medicare parts A, B, and D costs for ACO patients.

A quasi-experimental nonequivalent design compared utilization and costs for ACO patients in an MTM program with those of patients in a Medicare Shared Savings Program (MSSP) but not an MTM program.

 The integrated medication management program linked a network of community pharmacies with ACO practitioners. Analyses included Medicare parts A and B claims data from January 1, 2013, through December 31, 2014, with a 9.5-month baseline period and a 14.5-month intervention period. The outcome variables were all-cause hospitalization rate (per 30 days), 30-day hospital readmission rate (per 100 discharges), and average monthly per capita costs for Medicare parts A and B. Longitudinal analyses (generalized estimating equations) were used to compare across groups and over time, controlling for age, gender, and race.

Data comparing 885 ACO patients with 642 MSSP patients showed significant decreases in hospitalization rates and Medicare costs over time, but no significant differences across the groups. No significant decreases were found in 30-day readmission rates.

An integrated medication management program was associated with lower hospitalization rates and costs of care over time, although these reductions were not significantly different from decreases found in a comparison MSSP group.

The American Journal of Accountable Care. 2018;6(2):20-25

Accountable care organizations (ACOs) have been stimulated by the Affordable Care Act, which prompted CMS to utilize ACOs to reform Medicare payments.

 Although ACO performance measures include quality and cost indicators, another important area that can affect the performance of an ACO is medication therapy, which is commonly used to manage chronic conditions. Whereas safe and effective medication therapy can keep patients out of the hospital and help control total healthcare costs,

 unsafe medication use, medication nonadherence, and drug-related problems can lead to adverse drug events and associated increased healthcare utilization, such as emergency department and other hospital use.

 Many of the ACO performance metrics used by CMS directly involve specific medication therapy or the control of conditions through the use of medications.

Some ACOs are employing pharmacists on care teams to address various medication-related issues, including reconciling medications at the time of hospital admission and discharge, helping to manage patients on high-risk medications, and serving on advanced care teams.

This article reports that an integrated medication management program in a Pioneer Accountable Care Organization was associated with decreases in all-cause hospitalization and Medicare costs.

June 2018

Cost-Effectiveness of Pharmacist Postdischarge Follow-Up to Prevent Medication-Related Admissions

Utilizing Community Resources, New Payment Models, Technology to Deliver Accountable Care

Are Medical Offices Ready for Value-Based Reimbursement? Staff Perceptions of a Workplace Climate for Value and Efficiency

Case Study: Encouraging Patients to Schedule Annual Physicals

Effects of an Integrated Medication Therapy Management Program in a Pioneer ACO

The Intersection of Health and Social Services: How to Leverage Community Partnerships to Deliver Whole-Person Care

Amazing Grace: A Free Clinic's Transformation to the Patient-Centered Medical Home Model

Lessons Learned in Implementing Behavioral Screening and Intervention