Network Of Physicians Research Articles

Preference based scheduling in a healthcare provider network

Healthcare services are often provided by a large network of physicians and clinic facilities to patients with various levels of health conditions and preferences. Appointment scheduling is used to manage access to these services by matching patient demand with physician availability. This raises tremendous challenges for providers due to the heterogeneity in patient preference and physician availability. We propose a preference-based “nested” network model that consists of most practical operational constraints. Our model considers patients with varied priorities who can visit any clinic location and provider of their preference, and request the day and time of the appointment of their choice. The common challenges of patient no-show, cancellation, and uncertainty of physician availability are taken into account. We formulate this model as a Markov decision process and propose an approximate dynamic programming approach to provide robust scheduling policies. We also analyze the joint appointment scheduling and physician capacity planning problem as a mixed-integer nonlinear program. The proposed scheduling policies maximize revenue and minimize physician overtime and idle time while satisfying patient preferences. These policies are shown to perform within a close bound to the best achievable policy. They are also robust under patient demand uncertainties. We highlight the importance of considering patient heterogeneity and preference as well as systematic uncertainties to provide an optimal set of appointments.

Global Influenza Surveillance and Response System: 70 years of responding to the expected and preparing for the unexpected

When a cluster of respiratory viral infections occurs, early recognition by clinicians linked to a global network is essential for rapid identification of the causal pathogen and subsequent risk assessment and public health response. Crucial to this process are sentinel physician and hospital networks where samples are collected from patients with febrile respiratory infections; trained laboratory staff to identify the causative pathogen; and epidemiologists and public health staff to collect data and evaluate pathogen spread and disease severity in susceptible populations.

Optimal Physician Shared-Patient Networks and the Diffusion of Medical Technologies.

Social network analysis has created a productive framework for the analysis of the histories of patient-physician interactions and physician collaboration. Notable is the construction of networks based on the data of "referral paths" - sequences of patient-specific temporally linked physician visits - in this case, culled from a large set of Medicare claims data in the United States. Network constructions depend on a range of choices regarding the underlying data. In this paper we introduce the use of a five-factor experiment that produces 80 distinct projections of the bipartite patient-physician mixing matrix to a unipartite physician network derived from the referral path data, which is further analyzed at the level of the 2,219 hospitals in the final analytic sample. We summarize the networks of physicians within a given hospital using a range of directed and undirected network features (quantities that summarize structural properties of the network such as its size, density, and reciprocity). The different projections and their underlying factors are evaluated in terms of the heterogeneity of the network features across the hospitals. We also evaluate the projections relative to their ability to improve the predictive accuracy of a model estimating a hospital's adoption of implantable cardiac defibrillators, a novel cardiac intervention. Because it optimizes the knowledge learned about the overall and interactive effects of the factors, we anticipate that the factorial design setting for network analysis may be useful more generally as a methodological advance in network analysis.

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan.

The aging world population requires a sustainable and high-quality healthcare system. To examine the efficiency of medical cooperation, medical provider and physician networks were constructed using patient claims data. Previous studies have shown that these networks contain information on medical cooperation. However, the usage patterns of multiple medical providers in a series of medical services have not been considered. In addition, these studies used only general network features to represent medical cooperation, but their expressive ability was low. To overcome these limitations, we analyzed the medical provider network to examine its overall contribution to the quality of healthcare provided by cooperation between medical providers in a series of medical services. This study focused on: i) the method of feature extraction from the network, ii) incorporation of the usage pattern of medical providers, and iii) expressive ability of the statistical model. Femoral neck fractures were selected as the target disease. To build the medical provider networks, we analyzed the patient claims data from a single prefecture in Japan between January 1, 2014 and December 31, 2019. We considered four types of models. Models 1 and 2 use node strength and linear regression, with Model 2 also incorporating patient age as an input. Models 3 and 4 use feature representation by node2vec with linear regression and regression tree ensemble, a machine learning method. The results showed that medical providers with higher levels of cooperation reduce the duration of hospital stay. The overall contribution of the medical cooperation to the duration of hospital stay extracted from the medical provider network using node2vec is approximately 20%, which is approximately 20 times higher than the model using strength.

Development of indicators to assess quality and patient pathways in interdisciplinary care for patients with 14 ambulatory-care-sensitive conditions in Germany

BackgroundIn settings like the ambulatory care sector in Germany, where data on the outcomes of interdisciplinary health services provided by multiple office-based physicians are not always readily available, our study aims to develop a set of indicators of health care quality and utilization for 14 groups of ambulatory-care-sensitive conditions based on routine data. These may improve the provision of health care by informing discussions in quality circles and other meetings of networks of physicians who share the same patients.MethodsOur set of indicators was developed as part of the larger Accountable Care in Deutschland (ACD) project using a pragmatic consensus approach. The six stages of the approach drew upon a review of the literature; the expertise of physicians, health services researchers, and representatives of physician associations and statutory health insurers; and the results of a pilot study with six informal network meetings of office-based physicians who share the same patients.ResultsThe process resulted in a set of 248 general and disease specific indicators for 14 disease groups. The set provides information on the quality of care provided and on patient pathways, covering patient characteristics, physician visits, ambulatory care processes, pharmaceutical prescriptions and outcome indicators. The disease groups with the most indicators were ischemic heart diseases, diabetes and heart failure.ConclusionOur set of indicators provides useful information on patients’ health care use, health care processes and health outcomes for 14 commonly treated groups of ambulatory-care-sensitive conditions. This information can inform discussions in interdisciplinary quality circles in the ambulatory sector and foster patient-centered care.

Routine data-based quality indicators for the treatment of gonarthrosis and coxarthrosis patients in the ambulatory care sector – A study protocol for a cluster-randomised pilot trial to evaluate the MobilE-ARTH study

BackgroundIn 2019, Germany had the highest rate of hip replacement surgery and the fourth highest rate of knee replacement surgery among more than 30 OECD countries. The age-standardised rates were estimated at 174 hip joint and 137 knee joint replacements per 100,000 population. Against this background, the contrast between financial incentives for surgery and missing incentives for non-surgical treatment options is repeatedly discussed. Quality indicators (QIs) can serve to measure and transparently present the quality of evidence-based care. Comparing results in the form of audit and feedback has been shown to improve e.g. guideline-compliant ambulatory care. Existing QIs targeting the care of gon- and coxarthrosis mainly focus on discharge management after joint replacement surgery and/or require additional data collection. Therefore, as part of the MobilE-ARTH project, a set of QIs for ambulatory care prior to joint replacement surgery calculable based on routine data is being developed. The present study’s aim is to evaluate the impact of this QI set in terms of providing feedback on the quality of care.MethodsThe MobilE-ARTH project comprises (Phase 1) developing a QI set following the RAND/UCLA Appropriateness Method, (Phase 2) implementing the QIs in established physician networks of a German statutory health insurance (SHI) within a prospective, non-blinded, cluster-randomised pilot study, and (Phase 3) evaluating the QI set’s effectiveness. The physicians in the intervention networks will (a) receive feedback reports providing information about the routine data-based QIs of their gon- and/or coxarthrosis patients and aggregated results for their network, and (b) be invited to two voluntary, facilitated network meetings. In these network meetings, the physicians can use the information provided on the feedback reports to discuss multiprofessional care pathways for patients with gon- and/or coxarthrosis. Selected indicators of the QI set will serve as primary and secondary outcome measures. Routine data will be analysed within multi-level models using an intention-to-treat approach.DiscussionFeedback reports help maintaining clinical standards and closing the gap between evidence and medical practice, thus enabling an overall improvement in health care. Providing physicians with QI-based information on quality of care promotes identifying strengths and weaknesses in medical treatments.Trial registrationGerman Clinical Trials Register, number DRKS00027516, Registered 25th January 2022 – Prospectively registered.

The influence of strong and weak ties in physician peer networks on new drug adoption.

Physicians interact and exchange information through various social networks. Understanding peer effects through different networks can help accelerate new medical technology and innovative treatment adoption. In this research, we measure the influence of strong-tie and weak-tie connections on new drug adoption and study the overlap between advice-discussion and patient-sharing network. We construct two physician networks with strong and weak ties from peer nomination surveys and commercial medical claims data. We design a dynamic system to define peer adoption status and build patient-level hierarchical logistic models to measure the peer influence on new product adoption for treating new-to-therapy patients. Our results show that A strong-tie early adoption peer has six times more influence on new drug adoption than a weak-tie peer. Weak tie peers collectively exert as much or higher influence than strong-tie peers because of the larger network size. In the case of inaccessibility to strong-tie data, researchers can still reliably use the influence of the weak tie data only even though they will lose the effect of the omitted strong ties.

Does knowing the influenza epidemic threshold has been reached influence the performance of influenza case definitions?

BackgroundDisease surveillance using adequate case definitions is very important. The objective of the study was to compare the performance of influenza case definitions and influenza symptoms in the first two epidemic weeks with respect to other epidemic weeks.MethodsWe analysed cases of acute respiratory infection detected by the network of sentinel primary care physicians of Catalonia for 10 seasons. We calculated the diagnostic odds ratio (DOR) and 95% confidence intervals (CI) for the first two epidemic weeks and for other epidemic weeks.ResultsA total of 4,338 samples were collected in the epidemic weeks, of which 2,446 (56.4%) were positive for influenza. The most predictive case definition for laboratory-confirmed influenza was the WHO case definition for influenza-like illness (ILI) in the first two epidemic weeks (DOR 2.10; 95% CI 1.57–2.81) and in other epidemic weeks (DOR 2.31; 95% CI 1.96–2.72). The most predictive symptom was fever. After knowing that epidemic threshold had been reached, the DOR of the ILI WHO case definition in children aged <5 years and cough and fever in this group increased (190%, 170% and 213%, respectively).ConclusionsDuring influenza epidemics, differences in the performance of the case definition and the discriminative ability of symptoms were found according to whether it was known that the epidemic threshold had been reached or not. This suggests that sentinel physicians are stricter in selecting samples to send to the laboratory from patients who present symptoms more specific to influenza after rather than before an influenza epidemic has been declared.

Modeling physician’s preference in treatment plan approval of stereotactic body radiation therapy of prostate cancer

Objective. Treatment planning of radiation therapy is a time-consuming task. It is desirable to develop automatic planning approaches to generate plans favorable to physicians. The purpose of this study is to develop a deep learning based virtual physician network (VPN) that models physician’s preference on plan approval for prostate cancer stereotactic body radiation therapy (SBRT). Approach. VPN takes one planning target volume (PTV) and eight organs at risk structure images, as well as a dose distribution of a plan seeking approval as input. It outputs a probability of approving the plan, and a dose distribution indicating improvements to the input dose. Due to the lack of unapproved plans in our database, VPN is trained using an adversarial framework. 68 prostate cancer patients who received 45 in 5-fraction SBRT were selected in this study, with 60 patients for training and cross validation, and 8 patients for independent testing. Main results. The trained VPN was able to differentiate approved and unapproved plans with Area under the curve 0.97 for testing data. For unapproved plans, after applying VPN’s suggested dose improvement, the improved dose agreed with ground truth with relative differences for PTV for PTV for penile bulb for rectum and for bladder Significance. VPN was developed to accurately model a physician’s preference on plan approval and to provide suggestions on how to improve the dose distribution.

Experiences with Innovation Fund healthcare models in primary care: aqualitative study amongst German general practitioners.

The Innovation Fund was set up in 2015 with the aim of improving medical care in the German statutory health insurance system. Primary care needs to be involved in testing interventions and new forms of care for effectiveness and inclusion in standard care. There has so far been hardly any research on how far Innovation Fund models accommodate the primary care setting, or on the experience general practitioners have had with these models. Between September 2021 and January 2022, 36semi-standardized individual interviews were performed with general practitioners who had already participated in Innovation Fund projects. Eleven regional physician networks in Rhineland-Palatinate, Hesse, North Rhine-Westphalia, and Schleswig-Holstein were involved in the recruitment process. Most of the interviewees associated the Innovation Fund with potential and opportunity including intensification of application-oriented healthcare research, independent financing, and general healthcare involvement. Even so, many general practitioners were unsure as to how far primary care in particular would stand to benefit from the Innovation Fund in the long term. Amostly positive balance was drawn from participation in care models-benefit of intervention as well as cost-benefit ratio. However, some also reported hurdles and stress factors such as documentation requirements and disruption in everyday office routine. Innovation Fund projects will need to be suitable for general practitioners especially regarding medical decision-making leeway, limits to documentation requirements, preserving established office routine, greater involvement in research planning, and improvements to the primary care setting to encourage willingness to participate in Innovation Fund projects amongst general practitioners.

Abstract #1180544: A Novel Pharmacist-led Virtual Endocrinology Consult Program Reduces A1C in Collaboration with an ACO Primary Care Physician Network in Patients with Poorly Controlled Type 2 Diabetes

A1C is a standard CMS diabetes outcome quality metric for accountable care organizations (ACO) with financial implications. Our goal was to improve A1C in our healthcare system’s ACO using a novel program of pharmacist-led Virtual Endocrinology Consult Program (VECP) to provide expert, individualized interventions for management of type 2 diabetes (T2D) in collaboration with an ACO Primary Care Physician (PCP) network.

Association of County Race and Ethnicity Characteristics With Number of Insurance Carriers and Insurance Network Breadth

While the Affordable Care Act (ACA) set out to eliminate insurer discrimination based on preexisting conditions, the ACA health exchanges allow insurers to select what markets to enter and afford them great freedom on how they design their physician networks. Strategic market participation and physician network design based on population race, ethnicity, and health characteristics may give rise to a present-day form of redlining within health insurance markets-ie, a systematic underprovision of insurance plans and in-network practitioners within areas that are populated with higher proportions of non-Hispanic Black residents. To examine if markets with relatively higher non-Hispanic Black populations have systematically fewer insurers and lower network inclusion of physicians residing within these areas. This cohort study conducted a regression analysis of the US ACA health insurance exchange marketplace across 34 states with federal exchanges and physicians located within the 500 most populous US cities in 2014. County-level data were sourced from individual market and issuer enrollment databases and county health rankings; census tract data came from a national database of physician networks in 2014 marketplace plans, US Census Bureau data, and the Centers for Disease Control and Prevention's PLACES database. Adjustment was made for a rich set of county (or census tract) controls and state fixed effects to capture broad market and/or policy differences across states. Analyses were performed in June 2021. The raw count of insurers within a county and the mean percentage of insurance networks that physicians participate in within each census tract. A total of 2270 counties were examined within our first analyses. In the counties analyzed, a mean (SD) of 23.0% (3.2%) of the population was aged 18 years or younger, and a mean (SD) of 11.0% (15.8%) of the population had non-Hispanic Black race and ethnicity. For the second analysis, 16 006 to 25 096 census tracts were examined (depending on physician specialty). With adjustment for population size, age, and race and ethnicity, a 1-SD increase in the county non-Hispanic Black population was associated with a 14.1% reduction in the number of insurers (mean [SE] marginal effect size, -2.18 [0.13]; P < .001). Accounting for additional county-level risk selection controls and state fixed effects, a 1-SD increase in the non-Hispanic Black population was associated with a 2.3% reduction in available insurers (marginal effect size, -0.36 [0.17]; P = .04). For practitioners network breadth inclusion, a 1-SD increase in the non-Hispanic Black population was associated with a 15.8% (marginal effect size, -0.32 [0.01]; P < .001) to 24.7% (marginal effect size, -0.14 [0.02]; P < .001) reduction in the physicians' network participation depending on their specialty. Adjusting for additional state fixed effects yielded estimates of 6% (marginal effect size, -0.08 [0.01]; P < .001) to 13.5% (marginal effect size, -0.12 [0.02]; P < .001) reductions in practitioner network participation. These findings suggest that strategic decisions by insurers may contribute toward markets with higher racial or ethnic minority populations having systematically fewer participating insurers, as well as a higher prevalence of local physicians not included in coverage networks. These findings call for further examination of potential insurance redlining within the ACA marketplaces.

Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations

BackgroundCoordinating health care within and among sectors is crucial to improving quality of care and avoiding undesirable negative health outcomes, such as avoidable hospitalizations. Quality circles are one approach to strengthening collaboration among health care providers and improving the continuity of care. However, identifying and including the right health professionals in such meetings is challenging, especially in settings with no predefined patient pathways. Based on the Accountable Care in Germany (ACD) project, our study presents a framework for and investigates the feasibility of applying social network analysis (SNA) to routine data in order to identify networks of ambulatory physicians who can be considered responsible for the care of specific patients.MethodsThe ACD study objectives predefined the characteristics of the networks. SNA provides a methodology to identify physicians who have patients in common and ensure that they are involved in health care provision. An expert panel consisting of physicians, health services researchers, and data specialists examined the concept of network construction through informed decisions. The procedure was structured by five steps and was applied to routine data from three German states.ResultsIn total, 510 networks of ambulatory physicians met our predefined inclusion criteria. The networks had between 20 and 120 physicians, and 72% included at least ten different medical specialties. Overall, general practitioners accounted for the largest proportion of physicians in the networks (45%), followed by gynecologists (10%), orthopedists, and ophthalmologists (5%). The specialties were distributed similarly across the majority of networks. The number of patients this study allocated to the networks varied between 95 and 45,268 depending on the number and specialization of physicians per network.ConclusionsThe networks were constructed according to the predefined characteristics following the ACD study objectives, e.g., size of and specialization composition in the networks. This study shows that it is feasible to apply SNA to routine data in order to identify groups of ambulatory physicians who are involved in the treatment of a specific patient population. Whether these doctors are also mainly responsible for care and if their active collaboration can improve the quality of care still needs to be examined.

How do patients with secondary progressive multiple sclerosis enrolled in the EXPAND randomized controlled trial compare with those seen in German clinical practice in the NeuroTransData multiple sclerosis registry?

BackgroundIn EXPAND (NCT01665144), a phase 3 randomized clinical trial, siponimod reduced disability progression versus placebo in patients with secondary progressive multiple sclerosis (SPMS). AimTo understand how a real-world population with SPMS relates to that in EXPAND, we conducted a retrospective, observational cohort study using the German NeuroTransData (NTD) multiple sclerosis (MS) registry.MethodsThe NTD MS registry is run by a Germany-wide network of physicians. Two cross-sectional analyses were performed using the NTD MS registry. The first included patients with SPMS, as recorded in the registry, and compared their characteristics between 1 January 2018 and 31 December 2018 with patients in EXPAND. The second described the characteristics of patients in the registry at the time of diagnosis of SPMS between 1 January 2010 and 31 December 2018.ResultsThe first analysis included 773 patients: patients were older in the NTD MS registry than in EXPAND (mean age, 57.9 vs 48.0 years) and had a longer duration of SPMS (mean, 6.2 vs 3.8 years). In the NTD MS registry, median Expanded Disability Status Scale (EDSS) scores were comparable to EXPAND (6.0 versus 6.0), although fewer patients had relapses in the previous 24 months (16% vs 36% [siponimod] and 37% [placebo]). Data on gadolinium-enhancing lesions were only available for 5.8% of patients in the NTD MS registry. The second analysis included 916 patients: at the time of SPMS diagnosis, the mean age was 53.2 years and the median EDSS score was 5.0.ConclusionThe population in the NTD MS registry was older to that in EXPAND, but were similar in terms of disability. Differences likely reflect the inclusion criteria of EXPAND but also highlight that real-world populations encompass a wider range of patient characteristics.

Healthcare Utilization with Drug Acquisition and Expenses at the National Health Insurance Fund in Sudan.

Background: Understanding the pattern of care use can provide valuable information for reform interventions. This study investigates the pattern of healthcare utilization and its association with drug acquisition patterns and expenses in the National Health Insurance Fund (NHIF) of Al Jazira State in Sudan. Methods: A cross-sectional survey was conducted at NHIF primary healthcare centers of Al Jazirah state in Sudan. Results: A total of 768 beneficiaries were interviewed, of which 63.2% reported using out-of-network physician care, while 36.8% receive care from the NHIF physician network only. More than half (60.8%) of NHIF-interviewed clients reported a heavy burden of medication costs. The pattern of physician utilization was significantly associated with the number and source of regular drugs, the burden of out-of-pocket payment, and monthly out-of-pocket expenditures on medications, (p < 0.001). The regression analysis revealed that gender, marital status, number of chronic diseases, and number of regular drugs were the significant predictors of the pattern of physician care utilization; these factors explained nearly 36% of the variance in respondents’ pattern of physician care utilization. Conclusions: An impressive proportion of out-of-network care was found in Al Jazirah State in Sudan. The NHIF stakeholders should consider medication subsidy as a potential strategy for decreasing patient leakage to out-of-network services.

Perioperative magnetic resonance imaging in breast cancer care: Distinct adoption trajectories among physician patient-sharing networks.

BackgroundDespite no proven benefit in clinical outcomes, perioperative magnetic resonance imaging (MRI) was rapidly adopted into breast cancer care in the 2000’s, offering a prime opportunity for assessing factors influencing overutilization of unproven technology.ObjectivesTo examine variation among physician patient-sharing networks in their trajectory of adopting perioperative MRI for breast cancer surgery and compare the characteristics of patients, providers, and mastectomy use in physician networks that had different adoption trajectories.Methods and findingsUsing the Surveillance, Epidemiology, and End Results-Medicare database in 2004–2009, we identified 147 physician patient-sharing networks (caring for 26,886 patients with stage I-III breast cancer). After adjusting for patient clinical risk factors, we calculated risk-adjusted rate of perioperative MRI use for each physician network in 2004–2005, 2006–2007, and 2008–2009, respectively. Based on the risk-adjusted rate, we identified three distinct trajectories of adopting perioperative MRI among physician networks: 1) low adoption (risk-adjusted rate of perioperative MRI increased from 2.8% in 2004–2005 to 14.8% in 2008–2009), 2) medium adoption (8.8% to 45.1%), and 3) high adoption (33.0% to 71.7%). Physician networks in the higher adoption trajectory tended to have a larger proportion of cancer specialists, more patients with high income, and fewer patients who were Black. After adjusting for patients’ clinical risk factors, the proportion of patients undergoing mastectomy decreased from 41.1% in 2004–2005 to 38.5% in 2008–2009 among those in physician networks with low MRI adoption, but increased from 27.0% to 31.4% among those in physician networks with high MRI adoption (p = 0.03 for the interaction term between trajectory group and time).ConclusionsPhysician patient-sharing networks varied in their trajectory of adopting perioperative MRI. These distinct trajectories were associated with the composition of patients and providers in the networks, and had important implications for patterns of mastectomy use.

Employer Incentives and Distortions in Health Insurance Design: Implications for Welfare and Costs

This paper studies employer incentives in designing health insurance provider networks and whether observed offerings reflect preferences that are aligned with employees. I estimate a model of supply and demand where I endogenize employer health plan offerings with respect to hospital and physician networks. I find that employers “overprovide” broad networks by overweighting the preferences of certain employees, specifically older workers and those in regions with less provider competition, over the preferences of the average employee household. Shifting employers toward offering different provider networks in different geographic markets could yield substantial gains to surplus, with minimal distributional or selection effects. (JEL G22, G28, I13, J32, M52)

The Art and Science of Delegation: Staffing During COVID-19

Joseph: We did not furlough any direct-care nurses. Rebecca: During the first wave of COVID-19, we shut down our ambulatory and surgical services. In the beginning, we did not know how long the shutdown was going to last. As it became clear that it was not going to be a quick wave, we needed to figure out a way to open those services again, which took time. Knowing that it was far from ideal to furlough the staff, we brought staff members back as soon as we could but used them in different areas. Many came to work on the COVID-19 units as support, others worked on non–COVID-19 units.Joseph: We are talking about assigning additional duties to our patient care assistants so they can take some of the tasks away from the RNs.Rebecca: In our critical care unit, we use licensed practical nurses and RNs. We also have patient care technicians who are unlicensed assistive personnel. This staffing model was standard before COVID-19. During the first wave of COVID-19, we had help from areas that had shut down and furloughed staff. So nurses from other areas came to help. We also had medical students and residents who were able to help in different areas. These staff members did not change the workload at the bedside, though, unless they took an assignment or were part of a nursing team. During the second wave, we did not have access to staff from other areas because those areas were still open.Rebecca: Head on. We did not hide that it was hard or that people were feeling all sorts of ways. We made sure that everyone knew (and still knows) what resources our institution offers. For instance, we have an employee assistance program, a behavioral health partnership, and a well-being index. Our leadership team has an open door and checks in with staff. Our annual evaluations were postponed and modified to be more of a check-in than an evaluation.Joseph: We offered CareBridge EAP support to all staff, which is a 24/7, 365-day support for all employees and families. We also rolled out a partnership with Ginger, an on-demand mental health support for all Temple University Health System employees and family members 18 and older. We started Teladoc, so staff could have access to a large network of physicians virtually, which was convenient to our staff.

Work-Related Intervention Needs of Medical Assistants and How to Potentially Address Them according to Supervising General Practitioners: A Qualitative Study.

Work stress is common among health care professionals and this observation also holds true for general practitioners (GPs) and their medical assistance staff in Germany. Therefore, prior studies have examined the work-related intervention needs of medical assistants (MAs). We sought to explore potential interventions that may help to address these needs according to GPs’ views. Between December 2018 and April 2019 GPs were recruited via physician networks and through personal visits in general practices. Information on the nature and prevalence of 20 work-related intervention needs of MAs was presented to GPs. GPs then participated in a qualitative interview to reflect on the MAs’ needs. Qualitative content analysis according to Mayring was carried out using MAXQDA. A total of 21 GPs participated and perceived many of the needs as justified. The least understanding was expressed for requests of MA related to occupational aspects that were already known prior to hiring. The responsibility to address needs was often assigned to the German health policy. GPs expressed though that they considered addressing the need for better leadership style as their own responsibility as supervisors. Furthermore, professional training was discussed as one opportunity to raise the recognition and remuneration of MAs. Measures to address the work-related intervention needs of MAs and to thereby improve the working conditions of MAs were discussed with GPs.

Role of family physicians in providing primary healthcare during COVID-19 pandemic.

According to the World Health Organization, over 41 million cases of COVID-19 and 1 million deaths have been reported globally. More than 7 million cases of coronavirus have been reported in India alone. The growing number of cases of coronavirus worldwide poses numerous challenges to the country's current healthcare delivery system, especially in developing nations such as India. In such a situation, the task of maintaining continuity in the provision of comprehensive primary healthcare services in the community becomes a big challenge. This article discusses how family physicians can help to augment the healthcare system at the time of pandemic by providing easily accessible, holistic healthcare and by use of telemedicine. It also talks about the need to mainstream family medicine into the undergraduate and postgraduate medical curriculum and establish a robust network of family physicians trained in outbreak response and disease preparedness. For this study we looked for all papers with the terms 'Family physician', 'COVID-19', 'pandemic', and 'Primary health care'. Databases searched include PubMed, Google Scholar and DOAJ, using key words - family physician, family medicine, primary healthcare, COVID-19, and pandemic in different combinations.