A Markov chain model for analysis of physician workflow in primary care clinics.

This paper studies physician workflow management in primary care clinics using terminating Markov chain models. The physician workload is characterized by face-to-face encounters with patients and documentation of electronic health record (EHR) data. Three workflow management policies are considered: preemptive priority (stop ongoing documentation tasks if a new patient arrives); non-preemptive priority (finish ongoing documentation even if a new patient arrives); and batch documentation (start and finish documentation when the desired number of tasks is reached).

Classification of Opioid Usage Through Semi-Supervised Learning for Total Joint Replacement Patients.

Opioid misuse and overdose have become a public health hazard and caused drug addiction and death in the United States due to rapid increase in prescribed and non-prescribed opioid usage. The misuse and overdose are highly related to opioid over-prescription for chronic and acute pain treatment, where a one-size-fits-all prescription plan is often adopted but can lead to substantial leftovers for patients who only consume a few. To reduce over-prescription and opioid overdose, each patient's opioid usage pattern should be taken into account.

Protecting healing relationships in the age of electronic health records: report from an international conference.

We present findings of an international conference of diverse participants exploring the influence of electronic health records (EHRs) on the patient-practitioner relationship. Attendees united around a belief in the primacy of this relationship and the importance of undistracted attention. They explored administrative, regulatory, and financial requirements that have guided United States (US) EHR design and challenged patient-care documentation, usability, user satisfaction, interconnectivity, and data sharing.

An Analytical Framework for TJR Readmission Prediction and Cost-Effective Intervention.

This paper introduces an analytical framework for assessing the cost-effectiveness of intervention strategies to reduce total joint replacement (TJR) readmissions. In such a framework, a machine learning-based readmission risk prediction model is developed to predict an individual TJR patient's risk of hospital readmission within 90 days post-discharge. Specifically, through data sampling and boosting techniques, we overcome the class imbalance problem by iteratively building an ensemble of models.

Reducing COPD readmissions through predictive modeling and incentive-based interventions.

This paper introduces a case study at a community hospital to develop a predictive model to quantify readmission risks for patients with chronic obstructive pulmonary disease (COPD), and use it to support decision making for appropriate incentive-based interventions. Data collected from the community hospital's database are analyzed to identify risk factors and a logistic regression model is developed to predict the readmission risk within 30 days post-discharge of an individual COPD patient. By targeting on the high-risk patients, we investigate the implementability of the incentive policy which encourages patients to take interventions and helps them to overcome the compliance barrier.

The impact of e-visits on patient access to primary care.

To improve patient access to primary care, many healthcare organizations have introduced electronic visits (e-visits) to provide patient-physician communication through secure messages. However, it remains unclear how e-visit affects physicians' operations on a daily basis and whether it would increase physicians' panel size. In this study, we consider a primary care physician who has a steady patient panel and manages patients' office and e-visits, as well as other indirect care tasks.

A practice guide for continuous opioid therapy for refractory daily headache: patient selection, physician requirements, and treatment monitoring.

Objectives: To provide a guide to the use and limitations of continuous opioid therapy (COT, or daily scheduled opioids) for refractory daily headache, based on the best available evidence and expert clinical experience.

Background: There has been a dramatic increase in opioid administration over the past 25 years, with limited evidence of efficacy for either pain reduction or increased function, and increasing evidence of adverse effects, including headache chronification. To date, there has been no consensus on headache-specific guidelines for selecting patients for COT, physician requirements, and treatment monitoring.

Collaboration saves time.

Caring for patients today is very complicated and involves many clinical and administrative tasks. Clinicians are often asked to fill out a wide variety of forms, including forms that verify that the patient's clinical status is stable. Currently, these forms are filled out manually by the clinician or staff.

In-office discussions of migraine: results from the American Migraine Communication Study.

Background: Research indicates that successful migraine assessment and treatment depends on information obtained during patient and healthcare professional (HCP) discussions. However, no studies outline how migraine is actually discussed during clinical encounters.

Objective: Record naturally occurring HCP-migraineur interactions, analyzing frequency and impairment assessment, and preventive treatment discussions.