Using Tablet Computers to Collect Data in a Rural Clinic

1,422 views

Published on

Presented by Professor Graham Wright
Chair of Health Sciences Research, Walter Sisulu University

Published in: Health & Medicine, Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,422
On SlideShare
0
From Embeds
0
Number of Embeds
6
Actions
Shares
0
Downloads
1
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide

Using Tablet Computers to Collect Data in a Rural Clinic

  1. 1. Using tablet computers to collect data in a rural clinic by Professor Graham Wright Chair of Health Sciences Research
  2. 2. Me • Research Champion – Full professor – full time research – Increase Research Capacity • Chair of Health Sciences Research • New requirement for specialist to do Mmed – I supervise new supervisors and 130+ trainee in 29 specialties.
  3. 3. North Island New Zealand Eastern Cape South Africa 113,729 km2 168,966 km2 3,366,200 6,562,053
  4. 4. HIV Rates NZ ZA 2001 1,600 4,400,000 2006 2,100 5,200,000 2011 2,600 5,600,000 HIV+ now running at 29% of population in Eastern Cape
  5. 5. Eastern Cape Population groups • Black African 86.3% • Coloured 8.3% • White 4.7% • Indian or Asian 0.4% Languages (11 Official SA Languages) • Xhosa 78.8% • Afrikaans 10.6% • English5.6% • Sotho 2.5%
  6. 6. Each territory's size on the map is drawn according to its land area. Peter's map
  7. 7. Territory size shows the proportion of people worldwide who receive good basic health care that live there.
  8. 8. Each territory's size on the map is drawn according to its land area. Peter's map
  9. 9. Territory size shows the proportion of all people aged 15-49 with HIV (Human Immunodeficiency Virus) worldwide, living there.
  10. 10. Each territory's size on the map is drawn according to its land area. Peter's map
  11. 11. The longest life expectancy at birth is in Japan, at 81 years 6 months. The shortest life expectancy is in Zambia, at 32 years 8 months. The world average life expectancy is 67 years. Mthatha, South Africa is 47. I am 67 next birthday!!!!!!
  12. 12. Each territory's size on the map is drawn according to its land area. Peter's map
  13. 13. Territory size shows the proportion of all people with some electrical power in their homes living there.
  14. 14. 52 million population “More than half of South African households benefit from social assistance, and for 22% grants are the main source of income. By the end of next month, 16.1-million are expected to be grant beneficiaries.” Grants = approx 120 - 140 NZD per month Only 5 million are registered to pay tax and 2 million pay the majority
  15. 15. Percentage of population with HIV+
  16. 16. in Eastern Cape 714 are clinics and 42 Community Health Centers. Nurses do the job that in Europe and America would be undertaken by a GP Family Doctors in the Eastern Cape work in level 1 hospitals and occasionally go to clinics
  17. 17. HIV and TB are dangerous bed fellows: the co-infection rates exceed 70%, with TB being the most common opportunistic infection in HIV-positive patients. Read more: http://www.southafrica.info/about/health/health.htm#.Umkq2BarCYo#ixzz2ieI63pml
  18. 18. “Phone an ambulance? My dear, phoning an ambulance doesn’t even cross my mind. In my seven years at Pilani Clinic, I have never seen an ambulance at this clinic,” says Sister Sylvia Horner. Recently, there was no antiretroviral medicine for three months
  19. 19. Nurses undertake most of the primary care in the Eastern Cape They use a lot of paper for recording all sorts of information
  20. 20. Declaration of Alma-Ata International Conference on Primary Health Care, Alma-Ata, USSR, 6-12 September 1978 Target 9: Implement global and national health information and surveillance systems The development of key health status indicators for South Africa within a broad “Health for All” framework was discussed a decade ago and the issues of poor data quality recognised (HST 1998). The data collected in clinics is used for National Indicators as well as data for funding bodies and specific programs.
  21. 21. Assessing the implementation of a Clinic System Researcher Robert K. Yin defines the case study research method as an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used (Yin, 1984, p. 23).
  22. 22. Case Study Critics of case study say that that have no grounds for establishing reliability or generality of findings And are only good for exploring a subject This study is an illuminative study to explore the implementation feasibility of an information system so it can be considered as a “proof of concept” for the rural area in which it is situated
  23. 23. Research Question Can you implement a cloud computer system accessing a web2 database for patient records successfully in a rural area at Gqaqhala Clinic
  24. 24. Case Study Method  Determine and define the research questions  Select the cases and determine data gathering and analysis techniques  Prepare to collect the data  Collect data in the field  Evaluate and analyze the data  Prepare the report (Soy 1997)
  25. 25. The Equipment The Clinic was supplied with state of the art Satellite 3G connection with support from the top supplier in SA together with a Desktop Computer and Printer The software was supplied by a UK software house and included two UK staff visiting to install the systems and train.
  26. 26. The methods  Data collection  Record of time taken to input data  Observations  Record of issues seen by research team  Interviews  Record of issues discussed  Examination of historical records  Identification of issues
  27. 27. Issues with environment • Cloud Computing is becoming Mainstream. • Broadband exists on 3G but is extremely costly R15000 a Month to do what I used to do in UK for R300 • Cloud relies “on always on systems” and thin client – Gmail is cloud computing • Outages are a common occurrence – i.e. no electricity sometimes for a week • This clinic has no water – for washing or drinking
  28. 28. Computer literacy Not enough initial training. Non of the staff had seen or used a computer before • This was at a very basic level – no idea how to switch on the computer and nobody knew their password or user-name. • The training was given by the system programmers who only focused on the input of data • Note: all staff used mobile phones – the area has 3G connection
  29. 29. The are also major conceptual issues that need to be addressed. In primary care nurses take on a role which is more aligned to that of a doctor. Their cognitive processes are based in the same problem oriented approach having been taught at Universities which use Problem Orientated Learning. They are not familiar with the Care Plan approach which is used by Hospital Nurses
  30. 30. Staff have a positive attitude! • All of the nurses are positive about having a system and have gained some confidence in using the equipment following the employment of a computer graduate for one month on site to teach and support them. • It would be expected that a positive response is exhibited by staff when all of their senior line mangers are positive about the system as they see the opportunity to get computers for the clinical; • and having all these important people from the DoH visiting with the local politicians will have an influence.
  31. 31. Nurses data entry • Analysis of a small sample shows an average of – 19.58 minutes for inputting just the demographic data – 14.15 minutes additionally for inputting the clinical data. – total of 34. 13 minutes which compares to 5 minutes to complete the paper record. • Work undertaken by A Odama for a Masters thesis indicates that clinic nurses tend to leave the completion of register sometimes to the end of the week and then they rely on memory.
  32. 32. 4 Projects and team from 3 Faculties data collection at rural clinics Prof. Graham Wright Dr. Don O’Mahony Chrispin Kabuya Tony Odama Prof. Parimalarani Yogeswaran Frederick Govere Malcolm Ellis
  33. 33. Health Data Ownership and Data Quality: Clinics in the Nyandeni district, Eastern Cape, South African Wright and Odama • clinical registers were designed to meet the needs of the information officers at government institutions and not necessarily the clinicians. This would probably explain the exclusion of clinicians from the design process. • This implies that the development of clinical registers is linked to government initiatives for monitored health programmes • The study identified 17 patient collection tools. Thirteen (13) of these source tools originate from the Department of Health, while others were ordinary notebooks used by all health facilities surveyed to supplement the ones from the Department.
  34. 34. Health Data Ownership and Data Quality: Clinics in the Nyandeni district, Eastern Cape, South African • In summary collated data lacked validity, reliability, precision and there was no evidence clinics were using their data for strategic decision-making. In essence, data quality was very poor. • Nurses who had a register in their room would not leave the room to hunt for another register – they would leave the data entry until the end of day or at clinic the nurses meet on a Friday afternoon to fill in the registers • National figures produced from such show each nurse seeing an average 29 patients – I have never seen that few waiting to see the nurses. Under-reporting possibly by 50%
  35. 35. Knowledge helps decisions
  36. 36. Nurses at Community health centres (CHCs) and their satellite clinics provide primary health care services to most of SA population ( Reagon, Irlam & Levin 2004) .
  37. 37. Why a Tablet as recording device? • Electronic devices better than pen & paper? • Handheld more portable & robust than laptops and desktops? • PDA’s? • Android phones? • Tablets: clinician-client interaction, ‘mobility like paper’, ?
  38. 38. Paper Records: Nurses’ Experience • ‘You will have to finish tomorrow and that is not nice because it is today’s work, like today I started with yesterday’s work.’ • ‘It’s like we‘re nursing the books than the patients.’ • ‘The bad side it takes time and sometimes you are exhausted and you omit some information.’ O’Mahony D, Wright, G, Yogeswaran P, Govere F. 2013 Knowledge and attitudes of nurses in community health centres in the King Sabata Dalindyebo Local Municipality, Eastern Cape Province, about electronic medical records. Curationis (in press)
  39. 39. Qualitative assessment • Tablets were easy to use and saved time. • Happy to use Tablets in preference to pen and paper. • Expressed a desire to extend the use of Tablets to other areas of their work
  40. 40. DHIS: Data collection • Retrospective • Inaccurate • No evidence that data analysis informs any policy or programme management in individual clinics • Efforts under away to improve – using data capturers e.g. tier.net, eKapa Garrib, Stoops et al. 2008; Odama 2010; Heunis, Wouters et al. 2011
  41. 41. Principles of data capture: Error Reduction • Any piece of data is recorded only once, and it is available for all users both in primary and in secondary care • ‘Enter once: use many times’ • Data quality improves the closer it is to the point of capture and if the staff who enter data benefit from the coding Coiera 1997; Stonham, Heyes et al 2012; Douglas, Gabadu et al 2010
  42. 42. Tablet computers for recording TB data at a community health centre, King Sabata Dalindyebo Sub-District, Eastern Cape: a proof of concept report The aims of this study were: • Phase 1 - to describe the process of identifying and developing a Tablet computer programme to capture data • Phase 2 - a qualitative evaluation of the use of Tablet computers to record data at a rural CHC
  43. 43. Mthakulo Community Health Centre
  44. 44. The use of Tablet computers to record patient health data at a CHC, Mhlontlo District, Eastern Cape Aim: To compare the work burden of data collection using Tablet computers compared with handwritten entries in registers. Objectives: • To measure before and after Tablet implementation • The time taken for recording patient data required for the DHIS • The time taken for other tasks in the consultation
  45. 45. Chrispin setting up the new equipment
  46. 46. Training the research assistants on the T&M system
  47. 47. Tablet Data Collection at CHC Hypothesis Tablets will reduce nurses recording workload at CHC Method • Quantitative: Time & motion study • Qualitative: nurses experience of using Tablets patients experience of Tablets in CHC Recording data over 2 months
  48. 48. TB Room Registers (Manual) 1. Tick register - every patient visit recorded 2. Tuberculosis Register (GW 20/11)- every patient visit recorded 3. Transfer out Form (GW20/14) 4. HCT register 5. Suspect Register 6. Case Identification & Follow-up Register 7. Notification of Medical Conditions Form 8. IPT Register 9. Blood Collection Book (a local Facility record)
  49. 49. TB room – note the number of papers to write on
  50. 50. HIV COUNSELLING AND TESTING REGISTER HIV Test Results SEX Service Attended Accept Test Screening Test Confirmatory Test ELISA TB Screen Results IPT PCR 1 2 3 4 5 6 7 8 9 10 TOTAL Age M F Med Self ANC TB STI Pos Neg Pos Neg Neg CD4 Cell Count Staging Prophy Mento laxis ux Other method Pos Neg Yes No Name( Last,First) Pos Code Family Planning No Date Referral Year: Yes Month: Comments Sinature
  51. 51. They have introduced new forms to make it easier for the Data Capturers
  52. 52. Time & Motion Study • Compare time for writing in registers before & after implementation • Java application running on apple server into MySQL database • Non of available suitable either environment or too nursing – not primary care focused
  53. 53. The lady with the Tablet is undertaking a T&M study – what nurses do….
  54. 54. Layout & Deployment of Technologies
  55. 55. iXhosa Women may have three + legal Surnames at any one time. National ID numbers based on age – sex so many with the same number
  56. 56. OR Tambo - What’s next? As we are an NHI pilot site, we have been given the licence to try out new things. One of those things is the development of a software system that has the following modules: 1. Client record management system 2. Electronic data collection system for Community Health Workers 3. District Computerised Client record management module 4. Electronic patient Registry module I have been asked to rapidly resolve this one, by the end of this financial year
  57. 57. The objectives of the planned National Health Insurance (NHI) 1. Provide improved access to quality health services for all South Africans irrespective of whether they are employed or not; 2. Pool risks and funds so that equity and social solidarity will be achieved through the creation of a single fund; 3. Procure services on behalf of the entire population and efficiently mobilise and control key financial resources; and 4. Strengthen the under-resourced and strained public sector so as to improve health systems performance.
  58. 58. To successfully implement these reforms, the NDOH is focussing on four key interventions: 1. A complete transformation of healthcare service provision and delivery; 2. The total overhaul of the entire healthcare system; 3. The radical change of administration and management of healthcare; and 4. The provision of a comprehensive package of care under-pinned by a re-engineered Primary Health Care service.
  59. 59. The Alliance for Affordable Internet founded by BernersLee's World Wide Web has as its goal the bringing affordable internet to 90 percent of the global population that don't have access yet.
  60. 60. The group's mission is to bring entry-level broadband service to Asia and Africa, and to ensure it is priced at less than 5 percent of the country's average monthly income. At present, a basic fixed line broadband connection costs around a third of monthly income to those in developing countries, compared to an average of two percent in the UK and US. Berners-Lee said lowering the cost is crucial to getting users in developing countries online, citing the fact that in Mozambique, 1GB of data can cost "well over" two months wages for the average citizen.
  61. 61. Today, the internet isn’t accessible for two thirds of the world. Imagine a world where it connects us all. Mark Zuckerberg
  62. 62. Biomedical Informatics: We Are What We Publish Summary This article is part of a For-Discussion-Section of Methods of Information in Medicine on “Biomedical Informatics: We Are What We Publish” written by Peter L. Elkin, Steven H. Brown, and Graham Wright. It is introduced by this editorial and followed by a commentary paper with invited comments. 29 pages in all. In their paper, P. Elkin et al. attempt to define the fields of Medical Informatics and Bioinformatics through a bottom-up approach by searching the medical literature. This innovative approach provides interesting results that are discussed in the commentary paper. In subsequent issues the discussion may continue through letters to the editor.
  63. 63. Discussion of “Biomedical Informatics: We Are What We Publish” A. Geissbuhler1; W. E. Hammond2; A. Hasman3; R. Hussein4; R. Koppel5; C. A. Kulikowski6; V. Maojo7; F. Martin-Sanchez8; P. W. Moorman9; L. A. Moura10; F. G. B. de Quirós11; M. J. Schuemie12; B. Smith13; J. Talmon14 1 Department of Radiology and Medical Informatics, Geneva University, Geneva, Switzerland; 2 Duke Center for Health Informatics, Durham, North Carolina, USA; 3 Department of Medical Informatics, AMC-University of Amsterdam , Amsterdam, The Netherlands; 4 The Biomedical Informatics Center of Excellence, Information Technology Institute, Ministry of Communications and Information Technology, Egypt; 5 Sociology Department and the School of Medicine, University of Pennsylvania , Philadelphia, USA; 6 Department of Computer Science, Rutgers – The State University of New Jersey, New Jersey, USA: 7 Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain; 8 Health and Biomedical Informatics Centre, The University of Melbourne, Melbourne, Victoria, Australia; 9 Medical Informatics Department, Erasmus University Medical Center, Rotterdam, The Netherlands; 10 Assis Moura eHealth, Porto Alegre, Rio Grande do Sul, Brazil; 11 Department of Health Informatics, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina; 12 Janssen Research & Development, Titusville, New Jersey, USA; 13 Department of Philosophy, University at Buffalo, Buffalo, New York, USA; 14 Centre for Research Innovation, Support and Policy, Maastricht University, Maastricht, The Netherlands
  64. 64. Mark Shuttleworth was born in Welkom, Free State, South Africa - a son of a surgeon. Shuttleworth on board the International Space Station – the first African in space.

×