Local knowing and the use of electronic patient records: categories and continuity of health care

2012 ◽  
Vol 2 (3) ◽  
pp. 185-196 ◽  
Author(s):  
Thomas Winman ◽  
Roger Säljö ◽  
Hans Rystedt
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Feifei Bu ◽  
Daisy Fancourt

Abstract Background There is increasing awareness of the importance of patient activation (knowledge, skills, and confidence for managing one’s health and health care) among clinicians and policy makers, with emerging evidence showing higher levels of patient activation are associated with better health outcomes and experiences of health care. This study aimed to examine the association between patient activation and a wide range of specific types of healthcare service utilisation in England, including GP and non-GP primary care, elective and emergency hospital admissions, outpatient visits, and attendances at the Accident and Emergency department. Methods Data were derived from linked electronic patient records collected by primary and secondary healthcare providers in North West London between January 2016 and November 2019. Our analyses focused on adults (18+) with a valid Patient Activation Measure (PAM). After excluding patients with missing data, we had an analytical sample of 15,877 patients. Data were analysed using negative binomial regression and logistic regression models depending on the outcome variable. Results Patients had a mean activation score of 55.1 and a standard deviation (SD) of 17.7 (range: 0–100). They had an average of 5.4 GP visits (SD = 8.0), 26.8 non-GP visits (SD = 23.4) and 6.0 outpatient attendances (SD = 7.9) within a one-year follow-up. About 24.7% patients had at least one elective admission, 24.2% had one or more emergency admissions, and 42.3% had one or more A&E attendance within the follow-up. After accounting for a number of demographic and health factors, we found a linear (or proximately linear) association between patient activation and the number of GP visits, emergency admissions and A&E attendance, but a non-linear relationship between patient activation and the number of non-GP visits, the number of outpatient attendance and elective inpatient admission. Conclusions This study has provided strong empirical evidence from England linking patient activation with healthcare service utilisation. It suggests the value of supporting patient activation as a potential pathway to ease the burden of healthcare system.


1999 ◽  
Vol 38 (04/05) ◽  
pp. 345-349
Author(s):  
R. Draper ◽  
I. Hamilton ◽  
M. Rigby

AbstractThe application of computing to health care, and particularly to electronic patient records, offers major benefits but raises issues of confidentiality and of potential misuse. Sound access control mechanisms are therefore important, but most models focus upon informed consent by the data subject. This raises challenges in mental health care, and for other vulnerable patients including those comatose, and the severely ill and temporarily distressed. Published algorithms which are used to control record access within a controlled environment therefore have value, as a means of ensuring an open and informed, yet ethically sound, solution. The paper describes the background and issues, and gives an example of such an algorithm.


1999 ◽  
Vol 38 (04/05) ◽  
pp. 253-259 ◽  
Author(s):  
E.-H. W. Kluge

AbstractAn electronic patient record consists of electronically stored data about a specific patient. It therefore constitutes a data-space. The data may be combined into a patient profile which is relative to a particular speciality as well as phenomenologically unique to the specific professional who constructs the profile. Further, a diagnosis may be interpreted as a path taken by a health care professional with a certain specialty through the data-space relative to the patient profile constructed by that professional. This way of looking at electronic patient records entails certain ethical implications about privacy and accessibility. However, it also permits the construction of artificial intelligence and competence algorithms for health care professionals relative to their specialties.


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