Implementing a palm pilot intervention for primary care providers: Lessons learned

Abstract

The Personal Digital Assistance for Guideline Adherence (GLAD Heart) study was designed to test a strategy to improve quality of care through increased adherence to ATPIII cholesterol guidelines. This paper describes the overall study design including the multi-faceted intervention and outcome measures. Sixty-one primary care practices in NC were recruited and randomized to either a personal digital assistant-based cholesterol management intervention or an intervention similar in intensity and frequency of contact but focused on a hypertension clinical practice guideline. Installation and implementation of the technology intervention was challenging. Over the course of the study, there were 74 technical issues requiring assistance for the palm pilot from 23 participating practices. The GLAD Heart project was completed successfully with some impact on cholesterol management. Technology has the potential to improve the quality of care provided in the healthcare setting. However, potentially expensive interventions such as that conducted in GLAD Heart should undergo rigorous testing to assure their efficacy before widespread adoption.

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

“…Eleven trials (17%) were published prior to 2000 [77-89], 16 (25%) trials [58,60-76] between 2000 and 2004 and 38 (58%) trials [16-57,59] after 2004. Most studies (n = 41, 63%) [16-21,23,24,26,28,31-33,38,40,42-44,47,48,55-57,60,61,63,66-68,70,72-80,82-88] reported public funding; nine (14%) [29,34,35,45,46,49,50,52,53,59,71] reported private funding; six (9%) [22,36,37,41,54,64,65,69] reported public and private funding, and 9 (14%) [25,27,30,39,51,58,62,81,89] did not disclose a funding source (see Additional file 3, Table S3). We were able to determine whether improvement occurred with a CCDSS for process of care outcomes in 59 studies [16-24,26-38,40-70,72-76,80-83,85-87,89]; 29 studies reported patient outcomes [19,25,26,29,33,38,39,43,45,48,49,51-53,…”

“…As presented in Additional file 2, Table S2, the majority of CCDSS systems in our sample were integrated with an EMR (n = 38/61, 62%) [17,18,20,23-26,28,31,32,34,40,42,44-47,49,55,56,58-66,68-70,73,74,77-85,87,89], delivered feedback via a computer display (n = 44/62, 71%) [17,18,20,23-26,28,30-36,38-40,42,44,46-49,51,55-58,60-66,68-71,73-76,80,82-84] at the time of care (n = 53/64, 83%) [16-21,23-26,28,30-35,38,40,42,44,46-51,53,55-58,60-70,72-85,87-89]. A minority of authors reported testing a CCDSS with a graphical user interface (n = 22/25, 88%) [16-18,20,21,23-25,28,30,31,34,38,40,45,46,55,56,58-60,…”

“…A minority of authors reported testing a CCDSS with a graphical user interface (n = 22/25, 88%) [16-18,20,21,23-25,28,30,31,34,38,40,45,46,55,56,58-60,63,65,70,73,75,83], pilot-testing the system before the trial (n = 25/45, 56%) [17-19,24,28,29,31-33,35,38,39,43-45,47,48,55,59,63,66,70-72,74,75,77-79,84], or training users on system use (n = 29/52, 56%) [16,19,21,26,28,29,31,32,34,35,38,43-47,53,56-60,62,64-66,69,75-79,83-85]. Data required by the CCDSS to produce recommendations were most commonly entered via EMR link (n = 32/61, 52%) [17,18,20,24,26,28,31,32,34,40,44-47,49,51,55,56,58-60,62-66,68-…”

“…No significant difference was found between Rx-only (23/33) [18,22,23,26,30,32,33,35-38,41,43,48,50,54,58,62,65,68,73,81,87,89] and multi-faceted (14/26) [16,19,21,27,29,31,40,45,52,53,57,59,63,70,74,75,80] CCDSSs for process of care improvement.…”

Non-Adherence Codes in the New ICD-10: Need for Prospective Trials

“…Providers were able to obtain second opinions on complicated cases and advice from specialists not stationed at their base. Digital technology including electronic patient health portals, apps and social media will be a key player in shaping adherence behavior, by making more data available for a more insightful understanding of patient adherence and decision-making [13]. The digitalization of health records alone will facilitate data sharing across providers and provide detailed information about patient adherence, along with demographic data, medical history and current precipitating factors.…”