Thusitha De Silva Mabotuwana (PhD, BE Hons)


 

 Uni12May08_20

I completed my PhD in Computer Science, specialising in health informatics at the University of Auckland under the supervision of Prof. Jim Warren. I successfully defended my work on the 1st of October 2010 and scheduled to graduate in May 2011. Having submitted my thesis, I may not have access to update this page for much longer, so please have a look at my LinkedIn profile or my blog for more recent updates.


An overview of my PhD research:

Title:
ChronoMedIt – A Computational Quality Audit Framework for Better Management of Patients with Chronic Disease

Background:
NZ general practitioners (GPs) are diligent users of clinical computing by world standards, using electronic records that include prescribing data, laboratory test results, patient problem classifications as well as observation data such as blood pressure measurements. These data provide relatively obvious capabilities for practice introspection or clinical audit. Simple reporting queries can answer questions such as how many angiotensin converting enzyme inhibitors (ACEi) were prescribed last quarter (actually, there may be a few tricks around accurately identifying all prescriptions in this class since drugs are usually prescribed using generic/brand names with no association to a ‘drug class’). It is only slightly more complex to identify the percentage of patients with hypertension and diabetes that were prescribed with ACEi within the last 90 days. What is harder is to identify what percentage of patients with hypertension and diabetes have a persistent coverage with ACEi throughout the last quarter with no therapeutically significant lapses.

This latter type of query has a strong “temporal” nature. Such queries can become even more demanding if we wish to examine the progression of blood pressure measurements, or evaluate therapy with respect to the timing of relevant laboratory observations. As part of this research, we worked with HealthWest Fono to formulate and validate clinical audit reporting capability around antihypertensive prescribing.

Proposed solution and findings:
This work identified the temporal query requirements for a reporting tool that can more readily support relevant questions apropos to chronic disease management. Taking the identified requirements as guidance on the nature of queries that need to be formulated, a model of chronic disease audit was developed with four broad classes of indicators: (1) persistence to indicated medication; (2) timely measurement recording; (3) time to achieve target; and (4) measurement contraindicating therapy.

The criteria model has been implemented with the ChronoMedIt framework (indicating Chronological Medical AudIt) as an extensible and configurable architecture. The main components of the ChronoMedIt architecture are: an XML based specification for indicator formulation (with an associated XML-Schema), a drug and classification knowledge base maintained using Semantic Web technologies, a C# based criteria processing engine, a SQL-Server based patient database with related stored procedures and a graphical user interface to formulate queries and generate reports. ChronoMedIt can produce patient-specific audit reports as well as reports to benchmark an entire practice for a given evaluation period. A visualisation tool has been developed to provide an alternate representation of patient prescribing and measurement histories. By modifying the indicator specification and knowledge base an analyst can address a wide array of chronic disease management queries as specific instances of the four broad indicator classes.  The framework’s core computation has been verified using redundant query implementations on a battery of simulated case data and is illustrated against the EMRs of several practices. A paper that discusses some of the computational challenges can be found here while the details of the proposed solution can be found in this paper.

We have applied the ChronoMedIt in several real-world settings already and shown below are some of the important findings based on patient EMR data from two general practices:

  1. a significant portion (59% and 63% respectively for the two practices concerned) of patients with hypertension have >30 day lapses in their antihypertensive medication; and over a third of people with hypertension have not had a BP measurement for >180 days (see Pubmed);
  2. at least 56% of patients with hypertension and diabetes showed poor adherence to ACEi/ARB therapy (MPR <80%), although as a result, these patients were more likely to have uncontrolled BP than adherent patients (odds ratio = 4.0, p = 0.002 and odds ratio = 2.5, p = 0.034 for the two practices) (see Pubmed);
  3. adherence to antihypertensive therapy is correlated to having controlled BP with non-adherent patients being more likely to have uncontrolled BP than adherent patients (odds ratio = 2.4, p = 0.001 and odds ratio = 1.7, p = 0.03 for the two practices); mean reductions in systolic BPs were observed to be 19.31 mmHg and 16.39 mmHg respectively for the two practices for being adherent from 0% to 100% (see HINZ paper);
  4. interval based measures, such as MPR, are more stable measures than single, point-in time measures in identifying patients with poor BP control;
  5. satisfying a single, point-in time measure may not necessarily be an indication of optimal management of BP and other measures need to be considered, especially if quality indicators are associated with financial incentives (see Pubmed);
  6. analysing prescribing data has much merit and can provide 81% PPV and 76% NPV for dispensing based non-adherence (Pubmed); and
  7. 39% of the patients starting antidepressants were found to be non-adherent and it was shown that using the prescription-visualisation tool may provide an opportunity for clinicians to have more informed conversations with patients.

Also, ChronoMedIt has been used to identify patients with poor antihypertensive medication adherence and currently there is an ongoing nurse-led medication adherence promotion feasibility study (funded by NZ Health Research Council).


Educational background:

  • April 2007 – October 2010: University of Auckland, PhD in Computer Science, specialising in health informatics
  • 2006: University of Auckland, PhD candidate at the Bioengineering Institute working on Modelling Blood Flow in the Gastrointestinal System (realised after about 10 months that mathematical modelling wasn't what I wanted to be doing for the rest of my life..so I changed topics!)
  • 2001 - 2004: University of Auckland, Department of Electrical and Computer Engineering, Bachelor of Computer Systems Engineering (First Class Hons)


Research interests:

Quality audit reporting, Semantic Web applications, clinical audit reporting, user interfaces, interoperability


Scholarships/awards received:

  • PhD thesis nominated for ‘Best PhD thesis’ award in Computer Science
  • What Can Primary Care Prescribing Data Tell Us about Individual Adherence to Long-Term Medication? – Comparison to Pharmacy Dispensing Data. Pharmacoepidemiology and Drug Safety, 18(10), pp 956-64, 2009 paper selected for inclusion in the International Medical Informatics Association’s “2010 IMIA Yearbook of Medical Informatics” which “includes the best papers in medical informatics from around the world”
  • Computer Science Best Student Published Paper Award for journal paper: Mabotuwana, T. and Warren, J., ChronoMedIt – A Computational Quality Audit Framework for Better Management of Patients with Chronic Conditions. Journal of Biomedical Informatics, 2009 (Pubmed). Awarded by the Department of Computer Science, University of Auckland
  • BuildIT Travel Award, 2009
  • Royal Society of New Zealand Travel Award, 2009
  • National Heart Foundation Travel Grant, 2009
  • Best Student Scientific Paper Award for conference paper: Mabotuwana, T., Warren, J., Gaikwad, R., Kennelly J. and Kenealy, T., Analysis of Medication Possession Ratio for Improved Blood Pressure Control – Towards a Semantic Web Technology Enabled Workbench. Awarded at the Health Informatics New Zealand (HINZ) Conference, 2008
  • Computer Science Best Student Published Paper Award (2nd Place) for journal paper: Mabotuwana, T., Warren, J., Gaikwad, R., Kennelly J. and Kenealy, T., Analysis of Medication Possession Ratio for Improved Blood Pressure Control – Towards a Semantic Web Technology Enabled Workbench. Health Care and Informatics Review Online, October 2008. Awarded by the Department of Computer Science, University of Auckland
  • University of Auckland Doctoral Scholarship (for my current work – PhD in Computer Science)
  • Tertiary Education Commission (TEC) Bright Future Scheme Top Achiever Doctoral Scholarship (for the work at the Bioengineering Institute), 2005
  • Prize for best Part IV project in Electronic Systems, awarded by Industrial Research Limited (IRL), New Zealand
  • Senior Prize in Computer Systems Engineering, 2003
  • Senior Prize in Computer Systems Engineering, 2002
  • Nominated to Engineering School’s Dean’s Honours List, 2002


Employment history:

  • Jan 2011 onwards: Currently looking for opportunities.
  • Oct 2010 – Jan 2011: Research intern (2nd term), Microsoft Health Solutions Group, Washington DC
  • May 2010 – Aug 2010: Research intern, Microsoft Health Solutions Group, Washington DC
  • April 2008 – May 2010 (part-time): Assistant Research Fellow, Faculty of Medical and Health Sciences, Auckland University
  • May 2005 - Feb 2006 (full time, and then been doing some contract work on and off till mid 2007): Software engineer, ECONZ
  • Dec 2004 - May 2005: Embedded systems development engineer, Oscmar International
  • Dec 2003 - Feb 2004: Summer studentship, Industrial Research Limited, Wellington (work report)
  • Dec 2002 - Feb 2003: Summer studentship, Rakon NZ (work report)


Publications:

Refereed journal articles

  1. Mabotuwana, T. and Warren, J., ChronoMedIt – A Computational Quality Audit Framework for Better Management of Patients with Chronic Conditions. Journal of Biomedical Informatics, 43(1), pp 144-58, 2010 (Pubmed).
  2. Mabotuwana, T., Warren, J., Elley, R. et al, Use of interval based quality indicators in blood pressure management to enhance quality of pay for performance incentives: comparison to two indicators from the Quality and Outcomes Framework. Quality in Primary Care, 18(2), pp 93-101, 2010 (Pubmed).
  3. Mabotuwana, T., Warren, J., Elley, R. et al, Quality Indicators to Measure Blood Pressure Management over a Time Interval. Informatics in Primary Care, (in press), 2010.
  4. Chang Wai, K., Elley, CR., Nosa, V., Kennelly, J., Mabotuwana, T. and Warren, J., Perspectives on adherence to blood pressure–lowering medications among Samoan patients: qualitative interviews. Journal of Primary Health Care, 2(3), pp 217-24, 2010.
  5. Mabotuwana, T., Warren, J. and Kennelly J., A Computational Framework to Identify Patients with Poor Adherence to Blood Pressure Lowering Medication. International Journal of Medical Informatics, 78(11), pp 745-56, 2009 (Pubmed).
  6. Mabotuwana, T. and Warren, J., An Ontology Based Approach to Enhance Querying Capabilities of General Practice Medicine for Better Management of Hypertension. Artificial Intelligence in Medicine, 47(2), pp 87-103, 2009 (Pubmed). (Ontology can be download from here)
  7. Mabotuwana, T., Warren, J., Harrison, J. and Kenealy, T., What Can Primary Care Prescribing Data Tell Us about Individual Adherence to Long-Term Medication? – Comparison to Pharmacy Dispensing Data. Pharmacoepidemiology and Drug Safety, 18(10), pp 956-64, 2009 (Pubmed).
  8. Mabotuwana, T., Warren, J., Gaikwad, R., Kennelly J. and Kenealy, T., Analysis of Medication Possession Ratio for Improved Blood Pressure Control – Towards a Semantic Web Technology Enabled Workbench. Health Care and Informatics Review Online, October 2008.
  9. Warren, J., Gaikwad, R., Mabotuwana, T., Kennelly, J. and Kenealy, T, Utilising Practice Management System Data for Quality Improvement in Use of Blood Pressure Lowering Medications in General Practice. The New Zealand Medical Journal, 121(1285), pp 53-62, 2008 (Pubmed).
  10. Warren, J., Gaikwad, R., Mabotuwana, T., Adnan, M., Kenealy, T., Plimmer, B., Wells, S., Roseman, P. and Cole, K., The Challenge of Evaluating Electronic Decision Support in the Community. Health Care and Informatics Review Online, October 2008.
  11. Warren, J., Gaikwad, R., Mabotuwana, T., Kennelly, J. and Kenealy, T., Developing a Quality Audit Report for General Practice Prescribing for Hypertension: Methodology. Health Care and Informatics Review Online, October 2007.
  12. Mabotuwana, T.D., Cheng, L.K. and Pullan, A.J., A model of blood flow in the mesenteric arterial system. Biomedical Engineering Online, 6(17), 2007 (Pubmed).

Refereed conference papers

  1. Mabotuwana, T., Warren, J., Elley, R. et al, Interval-based measures as quality indicators in blood pressure management. Conf Proc Health Informatics Congress, Birmingham, 2010.
  2. Mabotuwana, T. and Warren, J., A Framework for Assessing Adherence and persistence to Long-Term Medication. Conf Proc Medical Informatics Europe (MIE), Sarajevo, September 2009 (Pubmed, IOSPress).
  3. Ho, H., Mithraratne, K., Mabotuwana, T. and Hunter, P., A Software Tool for Hemodynamics Modeling in Large Vasculatures. Conf Proc 11th World Congress on Medical Physics and Biomedical Engineering, Munich, September, 2009.
  4. Mabotuwana, T., Warren, J., Gaikwad, R., Kennelly J. and Kenealy, T., Analysis of Medication Possession Ratio for Improved Blood Pressure Control – Towards a Semantic Web Technology Enabled Workbench. Conf Proc Health Informatics New Zealand (HINZ), Rotorua, October 2008 – This paper won the Best Student Scientific Paper award at the conference. Slides
  5. Warren, J., Gaikwad, R., Mabotuwana, T., Adnan, M., Kenealy, T., Plimmer, B., Wells, S., Roseman, P. and Cole, K., The Challenge of Evaluating Electronic Decision Support in the Community. Conf Proc Health Informatics New Zealand (HINZ), Rotorua, October 2008. Slides
  6. Mabotuwana, T., Warren, J., A Semantic Web Technology Based Approach to Identify Hypertensive Patients for Follow-Up/Recall. Conf Proc 21st IEEE International Symposium on Computer-Based Medical Systems (CBMS), June 2008 (IEEE, ACM).
  7. Mabotuwana, T., Warren, J., Gaikwad, R., Kennelly J. and Kenealy, T., Towards an Architecture for Quality Audit Reporting to Improve Hypertension Management. Conf Proc The Australian Workshop on Health Data and Knowledge Management (HDKM), January 2008 (ACM).
  8. Warren, J., Gaikwad, R., Mabotuwana, T., Kennelly, J. and Kenealy, T., Developing a Quality Audit Report for General Practice Prescribing for Hypertension: Methodology. Conf Proc Health Informatics New Zealand (HINZ), Rotorua, October 2007.
  9. Mabotuwana, T.D., Cheng, L.K., Smith, N.P. and Pullan, A.J., Modeling Blood Flow in the Gastrointestinal System. Conf Proc IEEE Eng Med Biol Soc, New York, 2006. 1: p. 1810-1813 (Pubmed, IEEE).

Conference abstracts

  1. Mabotuwana, T. and Warren, J., Towards a Framework for Better Management of Patients with Hypertension. Conf Proc Medical Informatics Europe (MIE), Sarajevo, September 2009 (Pubmed, IOSPress).
  2. Warren, J., Gaikwad, R., Mabotuwana, T., Kennelly J. and Kenealy, T., What You Can Learn about Your Practice from Your Data – and How We Might Improve this Capability for Better Chronic Disease Management. Conf Proc First North American Primary Care Research Group (NAPCRG) New Zealand Regional Meeting, Auckland, October 2007.

Technical Reports

1.    Warren, J., Day, K., Gandar, K., Pollock, M., Mabotuwana, T. and Orr, M., Organising Health Information in an eHealth Environment. Wellington: Ministry of Health, 269pp, September 2008.


A list of other reports I've written (mainly during my undergrad years) can be found here.

Ad-hoc reviewing activities:

Reviewer for Computer Methods and Programs in Biomedicine (CMPB) 2010
Reviewer for Health Informatics New Zealand (HINZ) Conference, 2009

Reviewer for Medical Informatics Europe (MIE) Conference, 2009

Software Utilities:

MedTech32FileParser to extract selected labs out of the big blob (full of control characters) MT32 puts out

MPR_Comparer to compare different types of adherence measures.


Other interests:

Please visit my personal homepage to see what else I do and a whole bunch of photos I've uploaded! I'm a pretty keen badminton player as well and here's a list of awards/certificates I’ve received over the last so many years and also some other school activities I was involved in.


Contact details:

Postal:
Thusitha Mabotuwana
PhD student
Department of Computer Science
University of Auckland - Tamaki Campus
Private Bag 92019
Auckland 1142
New Zealand.

Location:
730 356 C1 1
School of Population and Health
Tamaki Campus

Phone:
+64 9 373 7599 ext. 88489

Fax:
+64 9 303 5932

Email:
thusitha@cs.auckland.ac.nz


Last modified 19-Aug-2009