Primary care teams: Past, present and future

Evidence is mixed on the effect of value-based payment models on access, quality, and care. One reason may be that while a great deal of attention has been paid to redesigning care delivery and payment models, less focus has centered on redesigning the workforce to deliver team-based care in new models of care. Bodenheimer suggests that the survival of primary care hinges on creating teams that share the care with well-trained and empowered health professionals who can take on functions that do not require a physician. Such structural changes to primary care require retraining physicians and other providers to more effectively function in teams, remapping workflows, and redesigning care to allow for more collaboration between physicians and other health care professionals. Despite the growing body of research on the evolving roles of medical assistants, nurses (RNs), social workers, pharmacists, nurse practitioners (NPs), and physician assistants (PAs), we lack a good understanding of different team configurations in primary care practices

The value of workforce data in shaping nursing workforce policy: A case study from North Carolina

Background In 2015, the Institute of Medicine's Committee for Assessing Progress on Implementing the Future of Nursing recommendations noted that little progress has been made in building the data infrastructure needed to support nursing workforce policy. Purpose This article outlines a case study from North Carolina to demonstrate the value of collecting, analyzing, and disseminating state-level workforce data. Methods Data were derived from licensure renewal information gathered by the North Carolina Board of Nursing and housed at the North Carolina Health Professions Data System at the University of North Carolina at Chapel Hill. Discussion State-level licensure data can be used to inform discussions about access to care, evaluate progress on increasing the number of baccalaureate nurses, monitor how well the ethnic and racial diversity in the nursing workforce match the population, and investigate the educational and career trajectories of licensed practical nurses and registered nurses. Conclusion At the core of the IOM's recommendations is an assumption that we will be able to measure progress toward a “Future of Nursing” in which 80% of the nursing workforce has a BSN or higher, the racial and ethnic diversity of the workforce matches that of the population, and nurses currently employed in the workforce are increasing their education levels through lifelong learning. Without data, we will not know how fast we are reaching these goals or even when we have attained them. This article provides concrete examples of how a state can use licensure data to inform nursing workforce policy

Building better oncology data systems and workforce models in a rapidly changing health care system

This issue of Journal of Oncology Practice includes numerous articles that address the critical, but difficult to answer, question of whether the oncology workforce supply will be adequate to meet the population demand for cancer care in the years to come. The articles in this issue underscore the limitations of existing data sources, methodologies, and models in answering fundamental questions like how many practitioners currently provide oncology care and how many oncologists will be needed in 10 years. Reading between the lines of these articles, the reader is left with the sense that although there are many known factors shaping the workforce, including increasing feminization and the growing demand for better work-life balance among younger generations of physicians, there are far more unknowns about how the rapid pace of health system transformation and the changing demographic and practice characteristics of providers will affect the workforce

Building a Value-Based Workforce in North Carolina

Health care in the United States is likely to change more in the next 10 years than in any previous decade. However, changes in the workforce needed to support new care delivery and payment models will likely be slower and less dramatic. In this issue of the NCMJ, experts from education, practice, and policy reflect on the "state of the state" and what the future holds for multiple health professional groups. They write from a broad range of perspectives and disciplines, but all point toward the need for change-change in the way we educate, deploy, and recruit health professionals. The rapid pace of health system change in North Carolina means that the road map is being redrawn as we drive, but some general routes are evident. In this issue brief we suggest that, to make the workforce more effective, we need to broaden our definition of who is in the health workforce; focus on retooling and retraining the existing workforce; shift from training workers in acute settings to training them in community-based settings; and increase accountability in the system so that public funds spent on the health professions produce the workforce needed to meet the state's health care needs. North Carolina has arguably the best health workforce data system in the country; it has historically provided the data needed to inform policy change, but adequate and ongoing financial support for that system needs to be assured

Community Use of Physical and Occupational Therapy After Stroke and Risk of Hospital Readmission

Objectives To determine whether receipt of therapy and number and timing of therapy visits decreased hospital readmission risk in stroke survivors discharged home. Design Retrospective cohort analysis of Medicare claims (2010–2013). Setting Acute care hospital and community. Participants Patients hospitalized for stroke who were discharged home and survived the first 30 days (N=23,413; mean age ± SD, 77.6±7.5y). Interventions Physical and occupational therapist use in the home and/or outpatient setting in the first 30 days after discharge (any use, number of visits, and days to first visit). Main Outcome Measures Hospital readmission 30 to 60 days after discharge. Covariates included demographic characteristics, proxy variables for functional status, hospitalization characteristics, comorbidities, and prior health care use. Multivariate logistic regression analyses were conducted to examine the relation between therapist use and readmission. Results During the first 30 days after discharge, 31% of patients saw a therapist in the home, 11% saw a therapist in an outpatient setting, and 59% did not see a therapist. Relative to patients who had no therapist contact, those who saw an outpatient therapist were less likely to be readmitted to the hospital (odds ratio, 0.73; 95% confidence interval, 0.59–0.90). Although the point estimates did not reach statistical significance, there was some suggestion that the greater the number of therapist visits in the home and the sooner the visits started, the lower the risk of hospital readmission. Conclusions After controlling for observable demographic-, clinical-, and health-related differences, we found that individuals who received outpatient therapy in the first 30 days after discharge home after stroke were less likely to be readmitted to the hospital in the subsequent 30 days, relative to those who received no therapy

An international call to arms to improve allied health workforce planning

Although the funding and organization of the health care systems in the United States and England are quite different, there are striking similarities in the allied health workforce planning challenges facing the two countries. This paper identifies some common issues facing workforce policy-makers in both countries and suggests key next steps to enhance workforce research and planning in both countries, including the creation of a national minimum data set for allied health professions

Counting physicians in specialties: By what they do or how they train?

The number of actively practicing physicians in the United States is not precisely known, nor do we know the total number of physicians required to meet population needs. The possible gap between these two numbers is a controversial issue, especially for primary care physicians. Primary care physicians can be counted in more than one way, either by their "area of practice" (in other words, what they do) or by the specialty in which they train. Regulatory agencies and other health organizations see the area of practice as more relevant to understanding physician supply. In North Carolina, the counts of primary care physicians were historically based on specialty of training. In 2010, the way physicians were counted was changed from definition by specialty of training to definition by area of practice, which resulted in an apparent drop in the number of primary care physicians by more than 16% in a single year. When terms such as "hospitalist," "urgent care," "student health," and "integrative medicine" were added to describe additional practice areas of physicians, most of the loss was accounted for. Researchers, regulators and policy makers need to be aware of the effects of a shift in how physicians are counted and assigned to specialties to understand the extent of pending shortages

A shortage of health information management professionals: How would we know?

The introduction of computers, the expansion of health insurance coverage through employers and government programs, and the increased use of personal health information have created a demand for a new breed of qualified medical record and health information personnel. The health information management workforce, which is entrusted with accurately coding, maintaining, storing, managing, analyzing, and disseminating all personal health information created from health care encounters, is reportedly in short supply. Given the complexity in defining and enumerating the profession, it is challenging to determine if such a shortage exists. There is a lack of uniformity across scope of practice, job titles, educational paths, and credentials. We report selected findings from a study of the health information management profession in North Carolina illustrating the methodologic problems encountered when measuring the supply and demand of this workforce. A case is made that greater standardization across these multiple facets of the profession would be beneficial to the workforce, and we offer recommendations on how this could be accomplished

Specialty distribution of physician assistants and nurse practitioners in North Carolina

Physician workforce projections often include scenarios that forecast physician shortages under different assumptions about the deployment of physician assistants (PAs) and nurse practitioners (NPs). These scenarios generally assume that PAs and NPs are an interchangeable resource and that their specialty distributions do not change over time. This study investigated changes in PA and NP specialty distribution in North Carolina between 1997 and 2013. The data show that over the study period, PAs and NPs practiced in a wide range of specialties, but each profession had a specifi c pattern. The proportion of PAs-but not NPs-reporting practice in primary care dropped signifi cantly. PAs were more likely than NPs to report practice in urgent care, emergency medicine, and surgical subspecialties. Physician workforce models need to account for the different and changing specialization trends of NPs and PAs

Physical and Occupational Therapy From the Acute to Community Setting After Stroke: Predictors of Use, Continuity of Care, and Timeliness of Care

Objective: To identify predictors of therapist use (any use, continuity of care, timing of care) in the acute care hospital and community (home or outpatient) for patients discharged home after stroke. Design: Retrospective cohort analysis of Medicare claims (2010–2013) linked to hospital-level and county-level data. Setting: Acute care hospital and community. Participants: Patients (N=23,413) who survived the first 30 days at home after being discharged from an acute care hospital after stroke. Interventions: Not applicable. Main Outcome Measures: Physical and occupational therapist use in acute care and community settings; continuity of care across the inpatient and home or the inpatient and outpatient settings; and early therapist use in the home or outpatient setting. Multivariate logistic and multinomial logistic regression analyses were conducted to identify hospital-level, county-level, and sociodemographic characteristics associated with therapist use, continuity, and timing, controlling for clinical characteristics. Results: Seventy-eight percent of patients received therapy in the acute care hospital, but only 40.8% received care in the first 30 days after discharge. Hospital nurse staffing was positively associated with inpatient and outpatient therapist use and continuity of care across settings. Primary care provider supply was associated with inpatient and outpatient therapist use, continuity of care, and early therapist care in the home and outpatient setting. Therapist supply was associated with continuity of care and early therapist use in the community. There was consistent evidence of sociodemographic disparities in therapist use. Conclusions: Therapist use after stroke varies in the community and for specific sociodemographic subgroups and may be underused. Inpatient nurse staffing levels and primary care provider supply were the most consistent predictors of therapist use, continuity of care, and early therapist use