The Impact of Psychiatric Practice Guidelines on Medication Costs and Youth Aggression in a Juvenile Justice Residential Treatment Program

Abstract Background PTB is an infectious disease, which not only seriously affects people’s health, but also causes a heavier disease economic burden on patients. At present, reform of the medical insurance payment can be an effective method to control medical expenses. Therefore, our study is to explore the compensation mechanism for pulmonary tuberculosis (PTB) patients with a full period of treatment, to alleviate the financial burden of PTB patients and provide a reference and basis for the reform of PTB payment methods in other regions and countries. Methods The quantitative data of PTB patients was collected from the first half of 2015 to the first half of 2018 in Dehui Tuberculosis Hospital in Jilin Province, and medical records of PTB patients registered in the first half of 2018 (n = 100) from the hospital was randomly selected. Descriptive analysis of these quantitative data summarized the number, cost, medication and compliance. Semi-structured in depth interviews with policymakers and physicians were conducted to understand the impact of interventions and its causes. Results After implementation of the compensation mechanism, the number of PTB patient visits in 2018 was increased by 14.2%, average medical costs for outpatients and inpatients were significantly reduced by 31.8% and 47.0%, respectively, and the auxiliary medication costs was reduced by 36.5%. Moreover, the hospital carried out standardized management of tuberculosis, and the patient compliance was very high, reaching almost 90%. Conclusions The capitation compensation mechanism with a full period of treatment was a suitable payment method for PTB, and it is worthy of promotion and experimentation. In addition, the model improved patient compliance and reduced the possibility of drug-resistant PTB. However, due to the short implementation time of the model in the pilot areas, the effect remains to be further observed and demonstrated.

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The impact of COVID-19 on opioid treatment program (OTP) services: Where do we go from here?

Journal of Substance Abuse Treatment ◽

10.1016/j.jsat.2021.108394 ◽

2021 ◽

pp. 108394

Author(s):

Kathlene Tracy ◽

Leah Wachtel ◽

Teri Friedman

Keyword(s):

Treatment Program ◽

Opioid Treatment ◽

The Impact

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What matters most? Comparing the impact of individual, job, and organizational factors on job stress and job satisfaction among juvenile justice personnel

Criminal Justice Studies A Critical Journal of Crime Law and Society ◽

10.1080/1478601x.2021.1929207 ◽

2021 ◽

pp. 1-20

Author(s):

Kristin Mack ◽

Gayle Rhineberger-Dunn

Keyword(s):

Job Satisfaction ◽

Juvenile Justice ◽

Job Stress ◽

Organizational Factors ◽

The Impact ◽

What Matters

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A field study of the impact of psychotropic medication on delinquency and juvenile justice system involvement among a high risk sample of children and adolescents

Journal of Offender Rehabilitation ◽

10.1080/10509674.2020.1767258 ◽

2020 ◽

Vol 59 (6) ◽

pp. 334-353

Author(s):

Natalie Armstrong-Hoskowitz ◽

Adam T. Schmidt ◽

Craig E. Henderson ◽

David V. Nelson ◽

Brian J. Allen

Keyword(s):

High Risk ◽

Juvenile Justice ◽

Children And Adolescents ◽

Field Study ◽

Psychotropic Medication ◽

Justice System ◽

Juvenile Justice System ◽

System Involvement ◽

The Impact

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Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

Digital Health ◽

10.1177/2055207620968355 ◽

2020 ◽

Vol 6 ◽

pp. 205520762096835

Author(s):

C Blease ◽

C Locher ◽

M Leon-Carlyle ◽

M Doraiswamy

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Medical Profession ◽

Descriptive Analysis ◽

Psychiatric Practice ◽

Limited Attention ◽

Written Responses ◽

Future Technology ◽

Qualitative Descriptive ◽

The Impact

Background The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. Objective This study aimed to explore psychiatrists’ opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice Methods In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses (“comments”) to three open-ended questions in the survey. Results Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that ‘man and machine’ would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention. Conclusions This study presents timely information on psychiatrists’ views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

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