Rethinking workforce planning for integrated care: using scenario analysis to facilitate policy development.

BACKGROUND: A goal of health workforce planning is to have the most appropriate workforce available to meet prevailing needs. However, this is a difficult task when considering integrated care, as future workforces may require different numbers, roles and skill mixes than those at present. With this uncertainty and large variations in what constitutes integrated care, current health workforce policy and planning processes are poorly placed to respond. In order to address this issue, we present a scenario-based workforce planning approach. METHODS: We propose a novel mixed methods design, incorporating content analysis, scenario methods and scenario analysis through the use of a policy Delphi. The design prescribes that data be gathered from workforce documents and studies that are used to develop scenarios, which are then assessed by a panel of suitably qualified people. Assessment consists of evaluating scenario desirability, feasibility and validity and includes a process for indicating policy development opportunities. RESULTS: We confirmed our method using data from New Zealand's Older Persons Health sector and its workforce. Three scenarios resulted, one that reflects a normative direction and two alternatives that reflect key sector workforce drivers and trends. One of these, based on alternative assumptions, was found to be more desirable by the policy Delphi panel. The panel also found a number of favourable policy proposals. CONCLUSIONS: The method shows that through applying techniques that have been developed to accommodate uncertainty, health workforce planning can benefit when confronting issues associated with integrated care. The method contributes to overcoming significant weaknesses of present health workforce planning approaches by identifying a wider range of plausible futures and thematic kernels for policy development. The use of scenarios provides a means to contemplate future situations and provides opportunities for policy rehearsal and reflection.

New Zealand's health workforce planning should embrace complexity and uncertainty.

Concerns over New Zealand's health workforce sufficiency, distribution and sustainability continue. Proposed solutions tend to focus on supplying medical professionals to meet predicted numbers or to resolve distributional problems. This is despite quantitative forecasts being known to have poor reliability. A recent study on New Zealand's health workforce planning, which focused less on medical workforce numbers and more on the system's organisation and constituent interrelations, highlights the use of complementary methods to define the problems and design a range of policy responses. Core to deciding on suitable interventions is the use of analysis tools, such as judgement-based approaches, which are commensurate with the actual levels of uncertainty being experienced, and which complement quantitative predictive forecasting.

The promise of complementarity: Using the methods of foresight for health workforce planning.

Health workforce planning aims to meet a health system's needs with a sustainable and fit-for-purpose workforce, although its efficacy is reduced in conditions of uncertainty. This PhD breakthrough article offers foresight as a means of addressing this uncertainty and models its complementarity in the context of the health workforce planning problem. The article summarises the findings of a two-case multi-phase mixed method study that incorporates actor analysis, scenario development and policy Delphi. This reveals a few dominant actors of considerable influence who are in conflict over a few critical workforce issues. Using these to augment normative scenarios, developed from existing clinically developed model of care visions, a number of exploratory alternative descriptions of future workforce situations are produced for each case. Their analysis reveals that these scenarios are a reasonable facsimile of plausible futures, though some are favoured over others. Policy directions to support these favoured aspects can also be identified. This novel approach offers workforce planners and policy makers some guidance on the use of complimentary data, methods to overcome the limitations of conventional workforce forecasting and a framework for exploring the complexities and ambiguities of a health workforce's evolution.

Availability of antidotes, antivenoms, and antitoxins in New Zealand hospital pharmacies.

AIM: To assess the adequacy of the types and quantities of antidotes, antivenoms and antitoxins held by New Zealand hospital pharmacies. METHODS: A list of 61 antidotes, antivenoms, antitoxins and their various forms was developed following literature review and consideration of national pharmaceutical listings. An Internet-accessible survey was then developed, validated and, during the period 28 February to 7 April 2014, sent to 24 hospital pharmacies nationally for completion. Results were assessed and compared with published guidelines for adequate stocking of antidotes in hospitals that provide emergency care. RESULTS: The response rate for the survey was 100%. Wide variation in stock levels were reported with only N- acetylcysteine and octreotide held in adequate quantities by all hospitals to manage a single patient for 24 hours. While archaic compounds were still stocked, newer and more effective pharmaceuticals were not. The national replacement cost for expiring drugs was estimated at $171,024, with smaller, more isolated facilities facing the greatest expense and difficulty in achieving timely resupply. CONCLUSION: Shortcomings in the types and quantities of antidotes, antivenoms and antitoxins held by New Zealand hospital pharmacies were recognised. This situation may be improved through national rationalisation of pharmaceutical storage and supply, and implementation of a national antidote database.

Evolving connectionist system versus algebraic formulas for prediction of renal function from serum creatinine.

BACKGROUND: In clinical trials, equation 7 from the Modification of Diet in Renal Disease (MDRD) Study is the most accurate formula for the prediction of glomerular filtration rate (GFR) from serum creatinine. An alternative approach has been developed using evolving connectionist systems (ECOS), which are novel computing structures that can be trained to generate accurate output from a given set of input variables. This study aims to compare the prediction errors associated with each method, using data that reproduce routine clinical practice as opposed to the artificial setting of clinical trials. METHODS: The methods were compared using 441 radioisotope measurements of GFR in 178 chronic kidney disease patients from 12 centers in Australia and New Zealand. All clinical and laboratory measurements were obtained from the patients' center rather than central laboratories, as would be the case in routine clinical practice. Both the MDRD formula and ECOS used the same predictive variables, and both were optimized to the study cohort by stepwise regression and training, respectively. RESULTS: Mean measured GFR in the cohort was 22.6 mL/min/1.73 m(2). The bias and precision of the MDRD formula were -3.5 mL/min/1.73 m(2) and 34.5%, respectively, improving to -1.2 mL/min/1.73 m(2) and 31.1% after maximal optimization of the formula to study data. The bias and precision of the ECOS were 0.7 mL/min/1.73 m(2) and 32.6%, respectively, improving to -0.1 mL/min/1.73 m(2) and 16.6% after maximal optimization of the system to study data. The prediction of GFR using ECOS was improved by accounting for the center from where clinical and laboratory measurements originated within the connectionist model. CONCLUSION: Algebraic formulas will be associated with greater prediction error in routine clinical practice than in the original trials, and machine intelligence is more likely to predict GFR accurately in this setting.

Discovery of the archaeal chemical link between glycogen (starch) synthase families using a new mass spectrometry assay.

Starch and its analogue glycogen are biosynthesized by enzymes that have been classified by sequence similarities into two families that have no significant sequence overlap: the animal/fungal glycogen synthases and the plant/bacterial glycogen (starch) synthases. Recent gene sequence analysis of putative archaea enzymes implicates them as a third family that links the structural and functional features of the other two classes. Herein, we present the first rapid electrospray ionization mass spectrometry-based assay to quantify any carbohydrate-polymerizing activity, the first cloning and recombinant expression as well as verification of the putative function of a glycogen synthase from the hyperthermophilic archaea Pyrococcus furiosus, and the characterization of a variety of glycogen synthases with the new assay. The new assay allowed the determination of Km and Vmax values for the rabbit, yeast, and P. furiosus glycogen synthases. Most surprisingly, unlike the synthases from rabbit or yeast and in contradiction to what would be expected from structural studies of other nucleotide-sugar binding proteins, the synthase from the archaea source accepts both uridine- and adenine-diphosphate activated glucose competitively and with comparable affinities to form a glucose polymer. This loose substrate specificity implicates this protein as the chemical link between the two branches of glycogen synthases that have evolved to accept primarily one or the other nucleotide as well as a good source enzyme for polymer bioengineering efforts.