Literature DB >> 10158370

Data rich, information poor (DRIP) syndrome: is there a treatment?

S Goodwin.   

Abstract

DRIP (data rich, information poor) syndrome is paralyzing the performance improvement efforts of many healthcare organizations. Symptoms of DRIP syndrome include the use of an abundance of indicators and the predominant use of a retrospective medical record review to collect data. Often, too many indicators are used because the organization is still subscribing to a traditional quality assurance methodology for performance improvement. In these cases, quality assurance programs monitor multiple areas of performance assuming that, except for occasional outliers, the results will be acceptable. Another cause of an unmanageable number of indicators may be a lack of understanding of JCAHO measurement requirements. The ¿prescription¿ includes changing to a continuous quality improvement culture, learning measurement requirements, inventorying current data collection to identify and eliminate useless data and aligning data collection with the goals and objectives of the organization. An organization should collect only data that is required to improve performance and meet accreditation and regulatory requirements. Data collection should be automated and built into work processes as much as possible. Ideally, a well-integrated computer system offers access to real-time information and permits timely or even proactive performance.

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Mesh:

Year:  1996        PMID: 10158370

Source DB:  PubMed          Journal:  Radiol Manage        ISSN: 0198-7097


  2 in total

1.  "Every Newborn-BIRTH" protocol: observational study validating indicators for coverage and quality of maternal and newborn health care in Bangladesh, Nepal and Tanzania.

Authors:  Louise T Day; Harriet Ruysen; Vladimir S Gordeev; Georgia R Gore-Langton; Dorothy Boggs; Simon Cousens; Sarah G Moxon; Hannah Blencowe; Angela Baschieri; Ahmed Ehsanur Rahman; Tazeen Tahsina; Sojib Bin Zaman; Tanvir Hossain; Qazi Sadeq-Ur Rahman; Shafiqul Ameen; Shams El Arifeen; Ashish Kc; Shree Krishna Shrestha; Naresh P Kc; Dela Singh; Anjani Kumar Jha; Bijay Jha; Nisha Rana; Omkar Basnet; Elisha Joshi; Asmita Paudel; Parashu Ram Shrestha; Deepak Jha; Ram Chandra Bastola; Jagat Jeevan Ghimire; Rajendra Paudel; Nahya Salim; Donat Shamb; Karim Manji; Josephine Shabani; Kizito Shirima; Namala Mkopi; Mwifadhi Mrisho; Fatuma Manzi; Jennie Jaribu; Edward Kija; Evelyne Assenga; Rodrick Kisenge; Andrea Pembe; Claudia Hanson; Godfrey Mbaruku; Honorati Masanja; Agbessi Amouzou; Tariq Azim; Debra Jackson; Theopista John Kabuteni; Matthews Mathai; Jean-Pierre Monet; Allisyn Moran; Pavani Ram; Barbara Rawlins; Johan Ivar Sæbø; Florina Serbanescu; Lara Vaz; Nabila Zaka; Joy E Lawn
Journal:  J Glob Health       Date:  2019-06       Impact factor: 7.664

2.  A Standardised Core Outcome Set for Measurement and Reporting Sedentary Behaviour Interventional Research: The CROSBI Consensus Study.

Authors:  Fiona Curran; Kieran P Dowd; Casey L Peiris; Hidde P van der Ploeg; Mark S Tremblay; Grainne O'Donoghue
Journal:  Int J Environ Res Public Health       Date:  2022-08-05       Impact factor: 4.614

  2 in total

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